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. 2026 Aug 18;26(17):4602–4623. doi: 10.1039/d6lc00386a

From flow to form: structuring and patterning hydrogels using microfluidic approaches

Ella E Bouker a,†, Lauren G Brown a,†, Emilie Newsham Novak a,†, Ariel Lin a,b, Jamison M Whitten a, Asha R Viswanathan a, Laura A Milton a,c,d, M Yunos Alizai a, Siwan Park e,f, Jungseub Lee e, Liam A Knudsen a, Sophie R Cook a, Yi-Chin Toh c,d, Jean Berthier a, Amanda J Haack a,g, Noo Li Jeon e,h,i,✉, Erwin Berthier a,✉, Ashleigh B Theberge a,j,✉
PMCID: PMC13482385  PMID: 42609155

Abstract

Three-dimensional (3D) cell culture can leverage the precise arrangement of materials, known as patterning, to generate physiologically relevant tissue-like structures. Hydrogels are widely used in 3D cell culture due to their ability to mimic the properties of biological extracellular matrix networks. In this tutorial review, we discuss the use of microfluidic systems to control fluid movement and placement within fabricated microchannels to pattern hydrogel precursors in 3D through the use of capillary flow. Such systems offer unique advantages in their ability to create complex biomimetic structures, organs-on-a-chip, and microphysiological systems with high spatial resolution and relatively small volumes of hydrogel material. We first discuss the fundamental principles behind capillary pinning and aspiration-mediated patterning. We then review literature describing the development and applications of three different types of microfluidic systems – closed, semi-open, and open – and describe how different patterning techniques are applied to each system. We also discuss modular microfluidic systems, in which multiple classes of microfluidic systems are combined together for complex and biomimetic modeling of biological systems. In each section, we provide synthesis and critical analysis of established and novel techniques to draw connections across diverse papers in literature. Finally, we offer our perspectives on the advantages of microfluidic systems for hydrogel patterning and the future of the field. Taken together, microfluidic flow-based patterning is an exciting tool for microphysiological systems and other 3D cell culture models that are poised to transform our understanding of basic biological mechanisms and provide new opportunities for studying diverse phenomena in physiologically relevant tissue models.


Three-dimensional (3D) cell culture can leverage the precise arrangement of materials, known as patterning, to generate physiologically relevant tissue-like structures.graphic file with name d6lc00386a-ga.webp

1. Introduction

Patterning refers to a category of techniques that facilitate the precise arrangement of materials in a user-specified geometry. Three-dimensional (3D) cell culture can leverage patterning techniques for the precise arrangement of cells, hydrogels, or molecular gradients to generate physiologically-relevant tissue-like structures. Hydrogels, both natural and synthetic, are widely used in 3D cell culture techniques due to their ability to mimic the structural, mechanical, and biochemical properties present in native extracellular matrix (ECM) networks.1 Conventional methods for 3D cell culture involve embedding cells within a hydrogel scaffold to increase cell–cell and cell-ECM interactions in vitro; these cultures are usually limited to a single hydrogel type with the cells, which can be a single cell type or a mixture of cell types, spread homogenously throughout the hydrogel.2–10 Incorporating patterning within conventional 3D cell-laden hydrogel systems allows for multiple cell types, ECM types, and/or ECM compositions to be spatially arranged within a single 3D tissue construct. Hydrogel patterning in 3D systems thereby enables user-defined designs of tissue-level structures or interfacial regions between different tissue types in a controlled microenvironment. By enabling spatial control over cell and ECM placement, patterned hydrogels can be used as scaffolding or barriers to compartmentalize cells, allowing different cell types to be cultured adjacently in their optimal hydrogel or ECM environments. This compartmentalization also facilitates biologically-relevant transport of small molecules throughout a culture, either through cellular interactions that establish chemical gradients or by incorporating various concentrations of molecules within the hydrogel itself.11,12 Furthermore, patterned hydrogels enable multiple regions of cell–cell and cell-ECM communication to aid in developing complex networks of cellular signaling. The tissue complexity mediated by 3D patterning allows for more physiologically relevant investigations into cell signaling behavior, tissue regeneration, and drug or other small molecule interactions.13–21

There are multiple common techniques for cell-embedded hydrogel patterning that enable spatially and geometrically controlled tissue structures. These include photolithography, soft lithography (e.g., micromolding), 3D bioprinting, and microfluidics.22–25 Briefly, in photolithography, light is used to activate photo-crosslinkable moieties in a cell-laden hydrogel.26,27 By defining the area that is exposed to light through the use of photomasks or laser irradiation, the geometry and composition of the resulting tissue structure can be controlled. Soft lithography uses a mold or stamp to dictate the shape and pattern of cells/proteins in a cell-laden hydrogel.28,29 In extrusion-based 3D bioprinting, bioink is printed in a controlled layer-by-layer approach to create 3D structures with different regions of cells and ECMs.30,31

Microfluidic systems utilize manipulation of fluid flow to enable precise spatial control of hydrogel placement within fabricated microchannels. Controlled fluid movement and placement within the channels is often achieved by changing the channel dimensions and/or surface properties to cause or prevent fluid advancement.32,33 These modifications assist in the precise control of hydrogels to create patterned tissue constructs. This review will focus on using microfluidic systems to achieve hydrogel patterning in 3D tissue constructs.

Comparatively to other hydrogel patterning modalities, microfluidic-based hydrogel patterning systems are relatively easy to implement and enable high spatial resolution and the ability to create complex biomimetic structures (Fig. 1). To implement microfluidic patterning systems, usually only a patterning device and a pump or pipette are required, making them accessible to labs of diverse resource levels. Microfluidic platforms also provide higher throughput capabilities than other patterning techniques and increased user control through precise fluid manipulation. Additionally, the use of small volumes (microliter to sub-microliter scale) in microfluidics reduces material consumption, which is an important consideration for precious hydrogel materials such as custom-engineered synthetic hydrogels or ex vivo decellularized ECMs. Furthermore, microfluidic systems can be readily integrated with external sensing and actuation components, enabling real-time monitoring and dynamic manipulation of patterned constructs. The ability to flow and pattern hydrogels with precision opens new possibilities for engineering biomimetic constructs that closely resemble physiological conditions, thereby advancing research in personalized medicine, drug screening, and organ-on-a-chip applications. These advantages can be leveraged through microfluidic channel configurations with the choice of system depending on the desired experimental setup, such as recapitulating specific tissue interfaces or modeling tissue architectures with defined cellular or ECM organizations.

Fig. 1. Microfluidic-based hydrogel patterning can be used to recapitulate hierarchical tissue structures, from the molecular level to the tissue level. Microfluidic systems offer high-throughput fabrication and precise fluid manipulation within microchannels to aid in developing physiologically relevant tissue constructs at scale. For illustration, a microfluidic device is shown with three distinct hydrogel regions and flow occurring in channels bordering the outer regions of the hydrogel regions. Each hydrogel region could contain different cell types, thereby allowing the co-culture of different cell types present in a target tissue, as well as different ECM types, whether native or synthetic, for increasing cell-ECM and cell–cell contact. This multi-region microfluidic design can be used to mimic the organization of multiple tissue types with distinct interfaces (enabling tissue-level recapitulation), multiple cell types within a target tissue (enabling cellular-level recapitulation), or biomolecular gradients within a target tissue (enabling molecular-level recapitulation).

Fig. 1

When patterning within microchannels, there are two main fluidic phenomena employed to control the placement of a fluid front or confinement of a fluid: capillary pinning and aspiration-mediated patterning. Both of these patterning mechanisms are discussed in Section 2 of this review, which will demonstrate that, depending on device design, hydrogels can be compartmentalized using capillary pinning to disrupt surface tension, generating distinct regions within a single channel.34–36 Additionally, aspiration-mediated patterning can be employed, where intentionally overloaded hydrogel precursor solution is removed to reveal patterned structures in desired compartments, allowing rapid patterning of multiple regions simultaneously.37

Sections 3 through 6 of this review detail how various types of systems in microfluidic patterning have been developed. Each offer distinct patterning control methods and applications. These microfluidic systems can be classified into three categories based on their overall channel architecture and degree of enclosure. Considered in this review are closed, semi-open, and open systems (Fig. 2). It is important to note that the classification used in this review, defined below by the authors with respect to prior literature, refers to the physical structure of the microfluidic device itself, rather than the local fluid and air interfaces that may occur during patterning processes.34

Fig. 2. Categories of microfluidic systems for hydrogel patterning applications. (i) Cross-sectional view of closed microfluidic systems, which are characterized by a channel with four walls and sealed inlets and outlets. Adapted from ref. 38 with permission from Nature Portfolio, Gumuscu et al., Scientific Reports, 2017, 7, 3381, Copyright ©2017 (ii) Cross-sectional views of semi-open microfluidic systems, which are characterized by a channel with four walls and an open inlet and/or outlet. Adapted from ref. 39 with permission from Royal Society of Chemistry, Huang et al., Lab on a Chip, 2009, 9, 1740–1748, Copyright ©2009 (iii) Cross-sectional views of open microfluidic systems, which are characterized by having at least one channel boundary open to the air and open inlets and outlets. Adapted from ref. 40 with permissions from Nature Portfolio, Park et al., Nature Methods, 2022, 19, 1449–1460, Copyright ©2022.

Fig. 2

In this review, closed microfluidic systems are fully enclosed assemblies where channel structures are surrounded on all sides with walls and inlets/outlets are sealed and often connected to pumps or other flow control mechanisms (Fig. 2i). Traditionally, closed systems utilize active pumping, where pumps at the channel inlet and outlet control flow and pattern fluids.41 Recent advancements have introduced control methods such as gravity-driven, vacuum-driven, and acoustic-driven flow, as well as capillary pinning to pattern fluids within closed systems without external pumps.42–44

Semi-open microfluidic systems emerged as a method to reduce the cost and complexity associated with closed systems, and to create regions that can interface with the environment. Semi-open systems have structurally enclosed channels (i.e., channels with four solid borders) but feature open inlets and/or outlets that are exposed to air (Fig. 2ii). By making inlets and outlets accessible, semi-open systems reduce the need for external pumps, allowing for simpler, lower-cost devices that can be operated with basic pipetting techniques. Passive mechanisms are often used to drive fluid flow in these systems, such as gravity, surface tension, or pressure gradients controlling fluid patterning after application.45–47

Open microfluidic systems represent a further progression toward accessibility and simplicity, where the channel lacks one or more solid borders along the axial direction. This introduces an air–liquid interface along a channel length (e.g., rail-based systems which contain ceiling and floor solid borders but lack side walls) (Fig. 2iii). This open architecture provides continuous direct access to the channel interior, enabling user manipulation and precise placement of materials. Open channel systems also allow for integration with external components and post-gelation manipulation such as transporting hydrogels to a new culture environment or stacking multiple hydrogels. Manual pipetting is the typical method for loading open channels, and fluid flow is often driven by surface tension and interactions between the fluid and solid walls without the use of external pumps. This is also referred to as capillary-driven flow.34,48,49

Closed, semi-open, and open microfluidic systems each offer distinct patterning mechanisms for flow of hydrogel precursor solutions and cell suspensions, as well as other biomolecular components such as liquid media, proteins, and chemicals, thereby expanding the possibilities for hydrogel patterning. Notably, these methods can be combined into modular systems that employ the advantages of multiple types of microfluidic systems for more complex and physiologically representative modeling of biological systems. Modular microfluidics can range from simple channel wall removal during experimentation to dynamic integration of 3D printing extrusion methods, all of which increase the complexity of 3D culture models available and allow the user to expertly tailor experiments for specific biological questions.50–52

In this review, we first introduce two categories of microfluidic approaches used to shape and pattern hydrogels, specifically discussing different methods for multi-region patterning. We then focus on the three main types of microfluidic channels (closed, semi-open, and open channels) and their respective patterning control mechanisms, emphasizing recent advances and emerging trends for recapitulating physiological tissue structure and function, such as the development of modular microfluidic systems. As the conditions and mechanisms of flow in closed, open, and semi-open systems have been previously reviewed in detail, this review focuses mainly on patterning and flow control methods used with hydrogel precursor solutions in microfluidic systems.34,53–58 The authors acknowledge that microfluidic systems have also been used to pattern substrates and solutions other than hydrogels via liquid flow manipulation or changes in surface wettability or topography; these applications will not be discussed in this review paper.59–68

By categorizing the methods of hydrogel patterning based on patterning techniques and microfluidic system configurations, this review aims to provide a comprehensive exploration on how microfluidic systems and associated patterning control methods can be used to generate different targeted outputs and offer insight into the future of microfluidic hydrogel patterning for biomedical applications. The three goals of this review are to help both new and experienced users in microfluidics and hydrogel patterning: (1) gain a broad understanding of the various techniques described in literature, (2) assist in the intelligent selection of the best strategy to achieve their biomedical research objectives, and (3) share our perspectives on the future of the field.

2. Multi-region patterning in microfluidics

In section 1, we introduced three different classes of microfluidic systems used for hydrogel patterning. Before reviewing the different systems in greater detail, in this section, we will introduce two classifications of hydrogel patterning approaches – capillary pinning and aspiration (Fig. 3) – and briefly describe the fluid mechanic principles driving their function. These mechanisms of patterning can be leveraged in each of the three classes of systems.

Fig. 3. Comparison of the two core hydrogel patterning mechanisms introduced in this review: capillary pinning (left) and aspiration-mediated patterning (right). Capillary pinning relies on a fluid front being held in place at a geometric feature (as shown in left panel) or due to a change in surface treatment/wettability (pinning = fluid stopping). Aspiration-mediated patterning instead relies on active fluid removal via applied negative pressure (aspiration = fluid receding). Capillary pinning images adapted from ref. 69 with permissions from Creative Commons Attribution 4.0 International License with permission from Wiley-VCH, Haack et al., 2025, 12, 2501148, Copyright ©2025. Aspiration-mediated patterning images adapted from ref. 37 with permissions from Creative Commons Attribution 4.0 International License with permission from Springer Nature, Park et al., 2021, 11, 19;986, Copyright ©2021.

Fig. 3

2.1. Capillary pinning: patterning via capillary force interactions

Capillary pinning is a phenomenon in microfluidics where the advancement of an air–liquid interface (meniscus) is spontaneously halted at a specific geometric or chemical boundary within a microchannel.70 Pinning is sometimes unwanted, as in the case of defects in a channel wall that cause surface roughness, but in biological and chemical applications, capillary pinning can be used as a “passive valve” to precisely control fluid volumes (e.g., trigger valves), confine or stop capillary fluid flows (e.g., building liquid walls to confine flow), or to create stable interfaces between different phases without the need for active external pumps or mechanical valves.71–73 Capillary pinning occurs when the energy required for a meniscus to move past a certain point exceeds the available capillary pressure. Pinning is generally achieved by using a sharp edge, formed by additional channel architecture either extruding into the channel to create a ridge (case 1) or by removal of architecture from the channel itself to create a cavity (case 2); see Fig. 4 for channel geometric considerations for these two cases. These channel discontinuities will be referred to generally as pinning features.

Fig. 4. Geometric construction for the determination of the burst pressure, which corresponds to the Laplace pressure of the stability limit, within a microfluidic channel. Case 1 demonstrates the geometric considerations for a ridge pinning feature with angle α while case 2 demonstrates the geometric considerations for a cavity pinning feature with angle Created by potrace 1.16, written by Peter Selinger 2001-2019 . In both cases, w/2 denotes the half-channel width measured from the channel middle axis to the pinning feature; θa is the apparent contact angle of the meniscus at the pinning feature; Created by potrace 1.16, written by Peter Selinger 2001-2019 is the angle between the solid wall direction (channel axis) and the downstream slope of the pinning structure, which determines the burst pressure as described in the main text; R is the radius of curvature of the fluid front along the pinning feature at the burst limit; and β is is the auxiliary angle. Note that Created by potrace 1.16, written by Peter Selinger 2001-2019 = α only in the cavity case (case 2); in the ridge case (case 1), α is the geometric angle of the pinning relief and differs from Created by potrace 1.16, written by Peter Selinger 2001-2019 .

Fig. 4

As the liquid reaches a sharp outward corner, the meniscus must “bend” or increase its curvature to maintain its contact angle with the new solid surface. This change in curvature creates a pressure barrier that the fluid cannot overcome unless additional external pressure is applied. This pressure difference is governed by the Young–Laplace equation which describes the pressure difference (P) across an interface due to surface tension (γ) and curvature (κ) defined by Inline graphic, where R1 and R2 are two curvature radii in two perpendicular planes intersecting the interface:

2.1. 1

Constraints are exerted on the fluid front's air–liquid interface where it contacts the solid channel walls. These constraints are described by Young's equation (eqn (2)) specifying a contact angle θ related to the different surface tensions between each of the three boundary components: liquid (L), solid (S) and gas (G).

γLG cos θ = γSG − γSL 2

In the case where a capillary flow reaches a sharp corner (i.e., a change in local channel geometry), the free surface bends accordingly to the Young–Laplace equation (eqn (1)). The angle of the interface pinned on the ridge changes to an apparent value θa. The interface stays pinned, or anchored, as long as the apparent contact angle satisfies the relation first described by Gibbs (eqn (3)):74

θ ≤ θa ≤ θ + (π − α) 3

As more liquid is introduced, the applied pressure eventually pushes the apparent contact angle past the upper bound of the limit given by eqn (3), and the meniscus advances past the pinning feature, resulting in a pinning failure mode known as depinning. The pressure necessary to depin the interface is called the burst pressure (Pburst) and is given by

2.1. 4

where γ is the surface tension of the liquid, R is the curvature radius of the air–liquid interface, w is the width of the channel, θ is the contact angle of the liquid at the pinning feature, and Created by potrace 1.16, written by Peter Selinger 2001-2019 is the angle between the channel axis and the slope of the pinning feature (illustrated in Fig. 4), downstream from the ridge. Note that, in any case, if the curvature radius of the interface decreases to w/2, corresponding to a semi-circular (cavity) interface, the meniscus depins. Notably, eqn (4) shows that the burst pressure increases as Created by potrace 1.16, written by Peter Selinger 2001-2019 decreases unto the value θ, meaning pinning is most robust when the slope of the pinning feature (annotated as Created by potrace 1.16, written by Peter Selinger 2001-2019 in Fig. 4) forms an angle of less than 90° relative to the channel axis.

To achieve the complex architectural requirements of organ-on-a-chip systems, various engineering strategies for liquid pinning have been developed to pattern hydrogels with high spatial fidelity. Micropillar arrays are the most common, utilizing a series of vertical pillars to act as capillary barriers that confine the gel through capillary pinning between posts.17,75–77 This allows for compartmentalization while still providing access for cell migration, molecule transport, chemical gradients, and cellular barriers. For more seamless interfaces, phase-guided systems employ structural features, such as a guiding extrusion, on the channel ceiling and/or floor to continuously guide the liquid meniscus along a predefined path, allowing for the liquid patterning without the microposts.78–80 In the literature, micropillars are referred to also as microposts, phase guides, or capillary barriers. For the purpose of this review, from this point on, we will refer to rows of posts as micropillars, and conversely, continuous barriers as phase guides.

2.2. Aspiration: patterning via removal of excess material

During aspiration, defined as the application of negative pressure to manipulate fluids, the fluid front is initially pinned and resists the pulling force; recession starts only when the local contact angle decreases below a critical receding contact angle (θR,c). This behavior is illustrated in Fig. 5A, where a microchannel is first overfilled with fluid and then drained by aspiration, causing the fluid front to recede unevenly: menisci advance first through the larger gaps between microposts, leaving the empty microchannel exposed in those regions, while fluid remains pinned and retained within the more tightly spaced regions, producing a patterned array of discrete fluid-filled squares. Therefore, patterning depends on features which create interfaces at which the critical receding condition is higher than the negative pressure applied to the entire channel. Consistently, micropipette-suction models describe that the meniscus recedes when the aspiration-induced pressure drop exceeds the critical Laplace pressure, which corresponds to the critical receding condition.

Fig. 5. Aspiration-mediated patterning and capillary-threshold ordering. (Ai) A channel containing micropost arrays is initially overfilled with fluid, which is then drained via aspiration to advance the fluid front. (Aii) As draining proceeds, the fluid recedes preferentially through the larger gaps between microposts, where the critical receding condition is reached first, producing advancing menisci and progressively exposing the empty microchannel. (Aiii) Following drainage, fluid remains selectively retained within the tightly spaced micropost regions, yielding a patterned array of discrete fluid-filled squares. The mechanism underlying the preferential recession of the fluid front is known capillary-threshold ordering. (B) Geometric construction of the meniscus at a micropost gap during aspiration. As the applied pressure increases, the local apparent contact angle (α) increases; once α exceeds 90° (phase 2), the meniscus becomes unstable and rapidly advances through the gap. Because gap width determines the meniscus radius of curvature (R, referred to as Rm in the text), wider gaps (L1) reach this transition before narrower gaps (L2, angle β), which remain pinned. (Ci) Simulated and (Cii) experimental cross-sections with systematically varied micropost spacing (100–400 μm) show that as aspiration pressure increases (left to right), the advancing meniscus is largest at the widest (400 μm) gap; the largest 400 μm gap in the channel has the lowest critical Laplace pressure, which corresponds to a larger radius of curvature. Images adapted from ref. 81 with permissions from John Wiley and Sons, Kang et al., Small, 2015, 11, 2789–2797, Copyright ©2015.

Fig. 5

Since ΔP, as defined in eqn (1), is inversely proportional to the radius of curvature, interfaces with larger radii of curvature (i.e., geometrically “flatter” interfaces) exhibit lower Laplace pressure and thus reach the recession condition at a lower imposed suction pressure than more strongly curved interfaces. Specifically, the in-plane radius of curvature of the meniscus (Rm) is minimized at Rm = (L − 2r)/2 for a gap of width L between two posts and a post radius r (see Fig. 5B for geometric considerations of meniscus with radius R), so that the corresponding critical Laplace pressure can be simplified to eqn (5):

2.2. 5

Because the out-of-plane curvature 1/R2 is common to all gaps, the in-plane radius Rm alone dictates the ordering of thresholds, with the widest gap (largest Rm) reaching recession at the lowest ΔPcrit. This relationship is demonstrated in Fig. 5C, where posts with systematically varied interpost spacing (100–400 μm) show that the widest gap consistently recedes first, in both simulation and experimental conditions, as the larger radius of curvature at that gap corresponds to the lowest critical Laplace pressure. In practice, aspiration-mediated patterning leverages this relationship to engineer a hierarchy of critical capillary pressure thresholds across competing interfaces (ΔPcrit,1 < ΔPcrit,2 < ⋯), so that recession and liquid removal proceed in a predictable order as suction is increased. This “capillary-threshold ordering” is the core methodology for selectively removing hydrogel from targeted regions while keeping other regions pinned.

Aspiration-mediated patterning differs in various microfluidic systems based on where the negative pressure gradient contacts the hydrogel precursor. In closed and semi-open systems, this is confined to the inlet or outlet, while in an open system, any open face can be accessed.

Sections 3–6 will discuss in more detail each of the types of microfluidic patterning systems, their unique advantages and limitations, and their applications in literature and bioengineering practice.

3. Closed systems

Historically, the field of microfluidics has centered around closed systems, where the channel is fully enclosed and fluid access occurs via tubing that is sealed to the channel inlet and outlet. Hydrogel patterning in closed systems relies on externally applied pressure gradients to drive hydrogel precursor solutions through the channel.57 Spatial control arises from regulated flow within confined geometries, enabling precise patterning of hydrogels. By tuning the channel design, flow rate, injection pressure, relative concentrations of gel precursors, and timing, these systems achieve reproducible spatial organization of multiple hydrogel regions. Consequently, pressure-driven platforms have been widely used to generate defined chemical and mechanical gradients and to construct organ-on-chip models that recreate physiologically relevant tissue architectures.82

3.1. Inlet-driven (pump-based) hydrogel patterning

Many inlet-driven strategies rely on the laminar co-flow of multiple precursor streams that gel at their interface or through an external curing mechanism. Early work demonstrated ionic crosslinking between parallel alginate and calcium chloride streams, forming layered hydrogels with spatial control defined by flow timing.83 These concepts were later extended to photopolymerizable systems, where distinct precursor streams were flowed side by side and UV cured to fix the laminar-defined interfaces.84 Similar approaches utilizing controlled inlet flow ratios and microfluidic mixing have been used to produce graded collagen hydrogels, as demonstrated by Pedron et al. (Fig. 6Ai). These graded hydrogels have been used in tumor modeling and coaxial core–shell hydrogel microfibers for nerve-on-chip scaffolds.85,86 Collectively, these studies highlight a central advantage of inlet-driven laminar patterning: flow defines spatial organization which can be immobilized into three-dimensional structures upon gelation.

Fig. 6. Closed microfluidic patterning. (Ai) A multiplexed hepatocyte chip integrated with a linear gradient generator permits parallel drug dosing across independently addressed 3D culture channels. Adapted from ref. 93 with permissions from John Wiley and Sons, Mahadik et al., Advanced Healthcare Materials, 2014, 3, 449–458, Copyright ©2013. (Aii) Laminar flow surface patterning enables confinement of collagen hydrogels within microchannels without micropillars or phase guides, allowing tunable gel geometries. Adapted from ref. 92 with permissions from MDPI, Loessberg-Zahl et al., Micromachines, 2020, 11(12), 1112, Copyright ©2014. (Bi) Patterning process for a device containing micropillars, which pin gel precursor into place during the aspiration and allow formation of tissue compartments. Adapted from ref. 81 with permissions from John Wiley and Sons, Kang et al., Small, 2015, 11, 2789–2797, Copyright ©2015. (Bii) Bird's-eye and cross-sectional view of a device with phase guides that pin gel precursors beneath to create arrays of gel. Adapted from ref. 96 with permissions from Springer Nature, Gumuscu et al., Cell-Based Microarrays, 2018, 225–238, Copyright ©2018. (Biii) Schematic of a typical vacuum-driven assembly, creating a closed channel sealed off to a vacuum pump. Adapted from ref. 97 with permissions from John Wiley and Sons, Jeon et al., Advanced Materials, 1999, 11, 946–950, Copyright ©1999.

Fig. 6

Despite their versatility, laminar co-flow approaches are highly sensitive to the relative volumetric flow rates of co-flowing streams (e.g., ratio of precursor to crosslinker flowrates), as small variations can shift the laminar interface, distort gradients, or result in incomplete gelation.87 These limitations have driven the development of alternative confinement strategies that mediate spatial localization with rigid microstructures such as micropillars and phase guides that halt capillary flow.47,84 The magnitude of this pinning pressure depends on fluid surface tension and the radius of curvature at the interface, with higher surface tension and sharper feature geometry increasing resistance to flow.44,69 By pinning the flow of the first hydrogel precursor, a second precursor solution can be introduced to enable multi-region patterning. Due to the ability to precisely regulate pressure with controlled inlet flow or vacuum aspiration, closed systems are able to achieve consistent and reproducible patterning.88

In lieu of capillary phase guides, dynamic or chemically defined boundaries have also been used to direct hydrogel placement. Tibbe et al. employed a temporary chitosan membrane formed via interfacial gelation to compartmentalize chambers without permanent barriers whereas Pei et al. introduced a recoverable elastic barrier that deforms during injection and reseals to prevent leakages.89,90 Other researchers achieved hydrogel precursor confinement through patterned surface hydrophilicity, which was applied by Loessberg et al. to generate interfacing regions of gel without physical barriers surrounding or separating them (Fig. 6Aii).91,92 Altogether, these strategies preserve the precision of pressure-driven flow while minimizing rigid structural constraints.

Inlet-driven systems regulate gel composition and microenvironment either during gel formation or after gelation. During formation, relative flow rates of two or more hydrogel precursor solutions determine the local mixing ratio that are fixed upon gelation or photopolymerization. This approach has been used to generate gradients of cells, matrix components, and matrix stiffnesses.93 After gelation, soluble factor gradients can be established by diffusion into the gel from adjacent perfused channels, allowing spatially resolved dosing without altering matrix composition.94 Despite their precision, inlet-driven systems require continuous pumping hardware, introducing challenges such as dead volume, setup complexity, and flow instability that can limit reproducibility and throughput.41,95 These limitations have motivated alternative pressure-driven approaches based on controlled suction rather than positive injection.

3.2. Outlet-driven (vacuum/aspiration based) hydrogel patterning

Aspiration-mediated patterning (also known as vacuum-driven patterning) in closed channels operates by applying negative pressure at an outlet to create a controlled pressure differential that deforms the air–liquid meniscus. Given that these terms are often used interchangeably in literature, we have decided to use both terms, and for the most part have preserved the use of the terminology in the original citations. As described in section 2, the pressure difference across each meniscus is governed by the Young–Laplace relationship and draws hydrogel precursor solutions through the microfluidic channel. This enables selective hydrogel retention while keeping adjacent channels open for perfusion. Maintaining gel confinement between capillary barriers is essential to preserve unobstructed perfusion after patterning. Confinement is improved by minimizing meniscus stretching and maximizing surface wetting. These parameters can be achieved through parenthesis- and slash-shaped phase guides that form acute angles to micropillar walls, as demonstrated by Gumuscu and Eijkel (Fig. 6Bii).96 Confinement can also be achieved with micropillars alone, as discussed in section 2.1 (Fig. 6Bi).44,81 An example of how a device utilizing aspiration-based patterning is assembled was described by Jeon et al. (Fig. 6Biii).97

Vacuum-driven patterning in closed systems has been leveraged to create discontinuous, compartmentalized hydrogel constructs separated by microfluidic channels, referred to as tissue arrays or microarrays, as shown previously in Fig. 2ii, and which is shown in greater detail in Fig. 7i. Microarrays are frequently employed as high throughput co-culture platforms because of their ability to continuously deliver media, drugs, or biomolecules of interest via perfusion, and to confine cell types to small isolated compartments and control their relative position to create gel-liquid interfaces of defined size and geometry.38,44 Wong et al. used vacuum-based patterning to achieve spatial control of multiple immune cells types, which is typically difficult in conventional cell culture systems. The separation of regions by a microfluidic channel allowed for both intracellular communication between regions and the application of gradients of soluble factors to both regions.123 Gumuscu et al. generated compartmentalized intestinal co-cultures with varying hydrogel–media interfaces to highlight how geometric and pressure-driven parameters together affect biological outcomes.38

Fig. 7. Semi-open microfluidic patterning. (A) Micropillars divide adjacent channels with breast cancer cells patterned in collagen adjacent to cell-free collagen as a proof of concept. Adapted from ref. 39 with permissions from the Royal Society of Chemistry, Huang et al., Lab Chip, 2009, 9, 1740–1748, Copyright ©2009. (B) Viscous fingering patterning enables endothelial cell-lined lumen creation. Adapted from ref. 121 with permissions from Elsevier, Bischel et al., Biomaterials, 2013, 34, 1471–1477, Copyright ©2013. (C) Stepped patterning enables adjacent cultures of blank and cell-laden hydrogel for cell migration assays. Adapted from ref. 113 with permissions from MDPI in https://Biorender.com, Su et al., Biosensors, 2021, 11, 509, Copyright ©2021. (D) Partially pump-driven vacuum patterning of hydrogel precursor provides substrate for cell adhesion in microchannels, visualized with green food dye in DI water. Adapted from ref. 42 with permissions from The Institute of Physics (Great Britain), Shriraro et al., Biofabrication, 2014, 6, 035016, Copyright ©2014. (E) Guitar- and wave-shaped channels are created via plasma treatment using masking to define channel shape, confining cell-laden hydrogel within the desired patterning region. Scale bar 1000 μM. Adapted from ref. 127 with permissions from the Royal Society of Chemistry, Olaizola-Rodrigo et al., Lab Chip, 2024, 24, 2094, Copyright ©2024.

Fig. 7

Aspiration-based methods of hydrogel patterning excel at forming compartmentalized arrays conducive to continuous perfusion, while inlet-driven systems are better suited for continuous gradients and co-flow designs. Despite the versatility of aspiration-mediated patterning in organ-on-chip platforms, reliance on external pumps and closed-channel architectures continues to drive interest in simpler, fully passive alternatives that maintain spatial precision while simplifying device operation. Importantly, while vacuum-based patterning in closed channels involves negative pressure, their operating context differs in open systems, which is discussed in a later section. Specifically, negative pressure in closed systems is applied through sealed ports within fully enclosed channels to advance or complete filling, whereas aspiration-mediated patterning in open systems applies suction directly to a hydrogel precursor phase across an extended, exposed meniscus.

4. Semi-open systems

The term “semi-open” is not universally defined within microfluidics. For the purposes of this review, we will define a semi-open system as a closed channel with menisci existing at the inlet and/or outlet.34,98 The open inlets and outlets allow semi-open systems to be accessible via standard pipetting and remove the need for tubing and pump systems that are typically required in closed microfluidic systems. While semi-open systems may have tubing and pump systems connected to assist in promoting flow, it is more common for fluid movement to be directed actively through pipetting or passively through surface tension or viscous fingering. In this section, we will discuss patterning strategies driven by surface tension, viscous fingering, and partial pumping.

4.1. Surface tension-driven patterning

In devices with surface tension-driven flow, hydrogel precursor is pipetted into an inlet and wicks to fill the channel via spontaneous capillary flow. One basic example of this principle is demonstrated by the tissue geometries achievable via Suspended Tissue Engineering with Assemblable Microfluidics (STEAM), in which hydrogel precursor flows along the length of the channel and gels in a customizable configuration as defined by the channel parameters.99 Similarly to closed systems, semi-open systems also frequently employ micropillars to separate adjacent channels while simultaneously facilitating physicochemical interactions at gel interfaces through the gaps between adjacent posts. Huang et al. demonstrated that rows of micropillars in a semi-open microfluidic device can be used to establish multiple adjacent channels of hydrogel with no leakage while still permitting cell migration from one channel to the next (Fig. 7A).39 Such multi-channel devices featuring micropillars have been implemented in a variety of biological investigations. These devices have been used in immunology to study migratory dendritic and T cell behavior, and model the lymph node T cell-B cell border; and in cancer to model cancer cell invasion or tumor cell extravasation and conduct drug screening for hepatocellular carcinoma therapies.100–106 Multi-channel hydrogel systems have also been applied to create functional microvascular networks and investigate the effect of shear stress on the alignment of components within the extracellular matrix.17,107,108 Another particularly unique use of the micropillar is its application as a micro anchor instead of as a capillary barrier. In one example by Park et al., micropillars are used to anchor tissues in place when exposed to parallel air flow for airway modeling.109

While many researchers custom design and fabricate their own semi-open microfluidic devices in which micropillars guide surface tension-driven flow, a simplified configuration has been made commercially available by MIMETAS, an organ-on-chip biotechnology company. In their OrganoPlate® device, MIMETAS implements phase guide style continuous barriers instead of micropillars to confine the flow of hydrogel precursor within a single channel while still enabling contact between channels. The OrganoPlate® also fits within the OrganoFlow® rocker (MIMETAS), which can be programmed to the user's target specifications to enable gravity-driven media perfusion, tube structure formation, and sheer stress induction in microphysiological systems.110–112

An additional way that channels can be delineated in semi-open devices is by engineered step height discrepancies in the space below each microfluidic channel. Su et al. demonstrated a use of this stepped patterning technique to create a three-laned device with two step heights, enabling cell migration studies where cell-embedded hydrogel can be patterned next to cell-free hydrogel (Fig. 7C).113 Other stepped devices have been used to study mesenchymal cell migration, examine endothelial cell and smooth muscle cell interactions in atherosclerosis, and investigate dynamics of neutrophil transendothelial migration in samples from patients with chronic obstructive pulmonary disease compared to samples from healthy individuals.114–117 In another example by Ko et al., these stepped devices were used to pattern independent channels to permit diffusion, enabling the study of trophoblast cell migration in differential environments to provide insight into the effects of hypoxia in placental development.118

4.2. Viscous fingering patterning

Another method of passively driving flow in semi-open systems is viscous fingering. Viscous fingering patterning is defined when a less viscous fluid (in this case, culture media) displaces a more viscous fluid (hydrogel) due to the viscosity differential.119,120 This is typically achieved by first patterning a channel with a higher-viscosity hydrogel and then introducing another, less-viscous fluid at the inlet as a droplet. The second fluid displaces the first to form a hollow channel positioned at the center of the higher-viscosity channel that spans the channel length.119,120 This enables the generation of hollow channels within patterned hydrogels without the need to incorporate complex geometries in the patterning device. Microphysiological lumen development is the most common application of viscous fingering patterning; Bischel et al. demonstrated the use of such lumens to recapitulate angiogenesis (Fig. 7B) while Herland et al. modeled the blood–brain barrier.121,122

4.3. Partially pump-driven patterning

Researchers have also integrated pumps within semi-open systems to actively guide hydrogel through the channels through vacuum forces. In these systems, cell-laden hydrogel precursor is pipetted into the device via the inlet, and the device is then placed under vacuum to drive fluid flow through the remainder of the device (Fig. 7D).42,123 Platforms with pipette-loading followed by pump-driven flow have been developed to create competitive immunoassays or enable high-throughput patterning of iPSC-derived cardiac myocytes.124,125 Trietsch et al. and Olaizola-Rodrigo et al. have combined the use of pumps with other patterning mechanisms and techniques, such as capillary barrier patterning for cell aggregation and invasion modeling or channel surface treatment for the creation of custom-shaped channels for the development of a blood–brain barrier (Fig. 7E).126,127 These applications highlight the advantages of using pumps for part of the patterning process; systems that require additional distance and flow rate beyond what capillary action permits can benefit from the use of pumps to drive a portion of flow.

5. Open systems

Beyond semi-open systems, scientists have increasingly adopted open microfluidic systems to improve ease of fabrication and accessibility in device production as well as implementation. In open microfluidic systems, at least one of the channel walls is open to the environment. Flow in open channels is typically passive and driven by surface tension without external pumping. The most commonly used open channel configuration with a single air–liquid interface is a wedge channel, where two walls and a floor form a U-shaped cross section with no ceiling. Channel configurations with two air–liquid interfaces include rail-based and suspended channels, where the fluid is confined by the two opposing channel walls.34,37,56,128–130

5.1. Single region and discrete multi-region patterning

Rail-based patterning has been used to create cell-free, single hydrogel type structures for the study of small molecule diffusion and vessel modeling.131–133 In rail-based systems with passive flow, capillary pinning forces the fluid to follow the outline of the channel ceiling. Thus, control of the resulting hydrogel shape is mediated through intentional device design. Berry et al. created a rail-based co-culture platform to study paracrine signaling where cells are placed in compartments separated by patterned hydrogel walls (Fig. 8A).131 Marder et al. leveraged rail-based channels to pattern collagen around a removable nylon filament and fabricate a vessel lumen model.133

Fig. 8. Open microfluidic patterning. (A) Cell-free agarose precursor is patterned to form 3 chambers for seeding cells (two separate cell types are seeded in the inner and outer culture compartments in the cross-section schematic). Adapted from ref. 131 with permissions from the Royal Society of Chemistry, Berry et al., Lab Chip, 2017,17, 4253–4264, Copyright ©2017. (B) The patterning rail guides fluid flow under spontaneous capillary flow conditions. The inset is a fluorescence image showing patterned fibrin laden with GFP-expressing endothelial cells with RFP-expressing endothelial cells seeded along the edge of the fibrin structure. Adapted from ref. 135 with permissions from the Royal Society of Chemistry, Ko et al., Lab Chip, 2019,19, 2822–2833, Copyright ©2019. (C) STOMP creates a multi-region suspended tissue. (i) Fibrin structure laden with 3T3 mouse fibroblast cells dyed by CellTracker Green (green) and CellTracker Red (magenta). Scale bar is 500 μm. (ii) Workflow of multi-region patterning of cell-free dyed agarose precursor leveraging capillary pinning features. Scale bars are 2 mm. Adapted from ref. 69 with permissions from Creative Commons Attribution 4.0 International License with permission from Wiley-VCH, Haack et al., 2025, 12, 2501148, Copyright ©2025. (D) Various biological applications have been studied using the U-IMPACT platform including angiogenesis, perfusable vessel networks, and tumor-induced angio/vasculogenesis. Adapted from ref. 143 with permissions from Creative Commons Attribution 4.0 International License with permission from Springer Nature, Lee et al., 2022, 8, 126, Copyright ©2022.

Fig. 8

Beyond cell-free hydrogel patterning, researchers have also employed open microchannels to pattern cell-laden structures and create 3D tissue models. Single region patterning, in which a tissue is patterned with one homogenous hydrogel precursor, is useful for modeling tissues with uniform composition. Park et al. used wedge channels to pattern Matrigel precursors containing human adult intestinal stem cells as a radially arranged, homogeneous organoid to improve diffusion of nutrients and avoid necrotic core formation.40 Similarly, discrete multi-region patterning can be employed in models where tissue structures need to be separated from each other within a system. Milton et al. developed a rail-based channel that patterns three discrete hydrogel niches in a single well, allowing for the customization of the hydrogel microenvironment and cell type in each niche and enabling investigation of paracrine signaling between cell types.134

5.2. Patterning of contiguous multi-region cultures: 3D cultures adjacent to 2D cultures

To study the biological mechanisms that occur at the interface between distinct regions, researchers have developed platforms that enable spatial heterogeneity within a larger hydrogel structure. Spatial heterogeneity is defined as two or more regions with different cell types, different ECM types, or a combination of both. Researchers have successfully created multi-region constructs with multiple cell types by using open microchannels to pattern hydrogel precursor laden with the first cell type and directly seeding the second cell type adjacent to the patterned hydrogel. Ko et al. used rail-based patterning to create a fibroblast-laden fibrin structure with a neighboring 2D endothelial cell region to study angiogenesis (Fig. 8B).135 Other researchers have employed similar methods to study angiogenesis and vascularization with other cell types.136–138 Oh et al. used an open channel with a micropore array ceiling and spaced micropillar walls to pattern endothelial cell-laden fibrin precursor and placed a tumor spheroid on the micropores. The micropores, small holes approximately 200 microns in diameter and 100 microns deep, connected the two regions and allowed for the study of vascularization.139

5.3. Increasing complexity of contiguous multi-region cultures: 3D cultures adjacent to 3D cultures

To create more complex multi-region constructs, scientists have leveraged open microfluidic principles to pattern multiple, distinct cell-laden hydrogel regions in a contiguous 3D structure. Lee et al. developed a rail-based patterning method that creates vertically layered 3D structures with multiple hydrogel types including agarose, type I collagen, and polymer-peptide gels. The method relies on a series of removable 3D printed patterning devices to form temporary channels.140 Rail-based patterning can also be combined with mesh-assisted structures to create a horizontally layered multi-region structure. Lee et al. used a 3D-printed device to sequentially pattern endothelial cells and stromal cells in an outer channel followed by tumor organoid clusters mixed with cells in a central chamber, to create a fully vascularized tumor microenvironment.141 Multi-region suspended hydrogel structures can be achieved by introducing pinning features to a suspended channel. Haack et al. developed the Suspended Tissue Open Microfluidic Patterning (STOMP) platform, which uses a removable 3D-printed device with capillary pinning features to pattern multiple cell types and extracellular matrix compositions within a free-standing suspended tissue anchored between posts that exhibit distinct contractile dynamics and mechanical properties (Fig. 8C).69 The suspended nature of this system permitted investigation of dynamic processes, such as contraction during cardiac tissue beating.

In recent years, there has been a greater push toward ensuring devices can eventually be manufactured at scale. For this reason, injection-molded devices have also been used to pattern cell-laden hydrogels with conjoining compartments. One family of devices, known as injection molded plastic array 3D culture (IMPACT) platforms, employs rail-based patterning to enable high-throughput 3D cell co-culture for a variety of organ-on-a-chip applications (Fig. 8D). In the first demonstration of the IMPACT platform, Lee et al. created a rail-based device that employs surface tension-driven patterning and varying step heights to facilitate the side-by-side patterning of cell laden hydrogels for modeling angiogenesis.142 Other IMPACT platforms have been designed to study the effects of tumor spheroids, interstitial flow, and anti-angiogenic drugs on angiogenesis and vascularization.143–146 While the majority of open channel multi-region patterning platforms have been fabricated through either 3D printing or injection molding, researchers have shown that other fabrication methods, such as PDMS casting and laser cutting of poly(methyl methacrylate), can be utilized as well.130,147,148

5.4. Aspiration-mediated patterning in open systems

Aspiration-mediated patterning has been adopted as a practical route to translate geometrically defined capillary thresholds into reproducible, multi-region hydrogel architectures in open microfluidic formats.37 In open microfluidic systems, aspiration-mediated patterning can be achieved by overloading and then partially removing hydrogel precursor, leaving hydrogel selectively pinned in designated compartments. Examples in literature demonstrate that this simple load-and-aspirate operation can generate multiplexed hydrogel microstructures, form thin, pinned hydrogel membranes supported by micropillar arrays for layered co-culture/barrier-style constructs, and enable high-throughput 3D cell–cell interaction assays in well plate-compatible layouts by rapid hydrogel patterning via pipette aspiration.37,149,150

Aspiration-mediated patterning can also be deployed in micropillar-guided open systems to create thin, pinned hydrogel membranes that are challenging to reproduce with conventional enclosed microchannels. In open microfluidics, micropillars, as previously discussed in section 2, create strong capillary confinement of a hydrogel phase, such that after loading, liquid removal by suction can leave behind a stable, thin hydrogel membrane pinned between pillars. This strategy can be integrated with open, pipette-accessible operation to produce membranes near physiologically relevant thickness scales (e.g., ∼100 μm) and can be used to construct air–liquid interface relevant microenvironments for pulmonary modeling. Such membrane-based patterning can be applied to additional applications including powder inhalation testing and drug screening, while maintaining an open workflow that is compatible with rapid handling.149 A related membrane-forming implementation is suspended microfluidics, where collagen membrane “μDots” are generated in an open architecture via a workflow that includes hydrogel aspiration/withdrawal prior to polymerization, yielding membrane arrays that separate two compartments in a transwell-like configuration.128

In other applications of aspiration-mediated patterning, Park et al. used 3D-printed rail-based devices exploiting differential capillary pressures at interfaces under shallow and deep steps to selectively remove hydrogel during aspiration, demonstrating formation of multiple hollow channels with a single aspiration step for screening vasculogenic capacities of five cell types in co-culture.37 Similarly, Nguyen et al. used 3D-printed micropillar-based devices leveraging surface tension to retain a thin fibrin hydrogel membrane between closely spaced pillars after suction, creating a lung-on-chip platform that co-cultured endothelial cells, epithelial cells, and fibroblasts embedded in the membrane to mimic the alveolar air–liquid interface for pharmaceutical screening applications.149

Altogether, open microfluidic systems offer an alternate strategy for complex patterning to traditional closed or semi-open systems, facilitating device fabrication and providing greater access to the hydrogel precursor during patterning for easier manipulation and integration with other systems. Such integration of microfluidic systems, defined here as modular systems discussed later in Section 6, can be used to take advantage of multiple patterning control methods and capabilities offered by each type of microfluidic system.

6. Modular systems

The benefits of closed, semi-open, and open channel microfluidics are abundant in current literature as their applicability across research fields expands. Consequently, there has been a trend towards combining varying elements of such systems to create “modular” microfluidics. For the purpose of this review, modular microfluidic systems are defined as either platforms with convertible elements or platforms where the channel type changes over the course of the experimental workflow; both types of modularity allow for dynamic experimental settings. Modular microfluidics allows the user to reap the benefits of different systems within a single device, such as the desired fluid flow obtained from a closed channel system in combination with the reduction of air bubbles or improved accessibility of an open channel system. In this section we will touch briefly on the emerging field of modular microfluidics, where elements such as channel wall removal, stacking of separate microfluidic channels, and dynamic integrations of extrusion methods and microfluidic patterning are utilized to increase the complexity of 3D culture models.

Common types of modular channels include transitioning from a closed or semi-open channel to an open channel configuration by removing one or more of the initial channel walls. Wall removal creates an increase in user accessibility to the patterned hydrogels, adding a dynamic element of complexity to the experiment. For example, Li et al. created a device where a PDMS lid is peeled off the microfluidic channel after the hydrogel sets, allowing for direct access to the trapped cells for genotypic end point studies (Fig. 9A).151 Kheiri et al. employed another approach to modular channels through a multi-layer microfluidic platform referred to as ReSCUE (Recoverable-Spheroid-on-a-Chip with Unrestricted External Shape). ReSCUE enables the generation of tumoroids or organoids by assembling channel layers on top of each other via a sliding mechanism to form channels of different shapes, selectively releasing the patterned tissue through removal of the top channel.152 Similar methods of channel disassembly to access hydrogels or cells for subsequent analytical analysis are becoming more common, increasing the possible complexity of 3D cultures.153,154 Ugolini et al. utilized the removability of a microfluidic channel component to not only access cultures for downstream analysis, but also to pattern multiple cell-laden hydrogels adjacent and/or on top of each other (Fig. 9B).155

Fig. 9. Modular microfluidic patterning. (A) Cells and hydrogel are loaded on the device by applying vacuum, after gelation of the hydrogel the PDMS lid is peeled off to allow open access to the channel. This demonstrates a benefit of a closed or semi-open channel transition to an open channel configuration. Adapted from ref. 151 with permissions from the American Chemical Society, Li et al., Anal Chem, 2020, 92, 3, 2794–2801, Copyright ©2020. (Bi) A PDMS channel mold is inserted into a top PDMS culture channel, hydrogel is flowed into the negative space created, and the channel mold is removed to reveal a patterned structure. This structure acts as a wall for the second hydrogel to be flowed in. (ii) A final configuration of two side-by-side hydrogels where one hydrogel was laden with red fluorescent cells and the other hydrogel was laden with green fluorescent cells to demonstrate successful spatial distribution. Scale bar is 300 μM. Adapted from ref. 155 with permissions from John Wiley and Sons, Ugolini et al., Adv. Healthcare Mater., 2017, 6, 1601170, Copyright ©2017. (C) Schematic of continuous microfiber generation via a pulled borosilicate glass pipet equipped to a microfluidic device. Microfluidic devices with 3D printer-like extrusion heads open up the possibilities for sample integration and modification during experimentation. Adapted from ref. 156 with permissions from the American Chemical Society, Shin et al., Langmuir, 2007, 23, 17, 9104–9108, Copyright ©2007. (D) Individual microfluidic channels of various configurations can be premade and stacked together to create a single congruent microdevice shown here with an exploded view (i) and assembled view (ii). The unique ability to stack channels together, or take them apart, expands the applications and experimental parameters allotted to answer complex biological questions. Adapted from ref. 50 with permissions from the Royal Society of Chemistry, Humayun et al., Lab Chip, 2018, 18, 1298–1309, Copyright ©2018. (E) Cells are cultured in separate suspended channels (i) before stacking cultures on top of each other (ii) for spatiotemporal control of an experiment. Adapted from ref. 52 with permission from Springer Nature, Yu et al., Nat Biomed Eng, 2019, 3, 830–841, Copyright ©2019.

Fig. 9

Recent advancements have also enabled high performance extrusion setups for integration with microfluidic systems to dynamically adjust biomaterial properties in real-time. Shin et al. was one of the first to introduce the method of a continuous generation of calcium alginate fibers with a microfluidic chip approach where a sodium alginate solution is extruded from a borosilicate glass pipet into a sheath flow of calcium chloride solution. This set-up allowed for the continuous extrusion of cylindrical fibers through diffusion-controlled ionic cross-linking without clogging in the microfluidic system or extrusion setup (Fig. 9C).156 These hydrogels, also called microfibers, can be generated with the base technique above in conjunction with various spinning or twisting motions with various hydrogels, giving the ending microfibers a helical structure with spatial resolution between hydrogels.157,158 Microfiber generation can also increase in complexity by manipulating the extruding mechanism or microfluidic channel configuration to create hollow microfibers in both helical and string-like structures.51,159–162 Applications of a hollow microfiber range from microvessel studies, open cultivation systems for microorganisms, and functional material or cell encapsulation.51,156,158,159,161,162 These methods are also leveraged with stimuli-responsive hydrogels, combining the benefits of gel shrinking or swelling with spatial regulation and hollow patterning.163

Another usage of modular channels includes the unique ability to stack channels, or cell cultures, together to create dynamic elements for continued experimentation and downstream analysis. Humayun et al. found that current technology used to recapitulate chronic lung diseases was not sufficient due to the complexities in the microenvironment of human lung tissue. To overcome this limitation, they integrated this modular ability of stacking by fabricating a microdevice with three microfluidic compartments stacked on top of each other to effectively mimic interactions between airway smooth muscle cells, airway epithelial cells, and the supporting extracellular matrix (Fig. 9D).50 While stacking of separate microfluidic channels into a master microdevice is useful, the ability to stack separate cell cultures into a reconfigurable microfluidic assembly can also be integrated into the overall system design. Discrete systems can be stacked, unstacked, and restacked in different configurations, rendering highly versatile systems. Yu et al. created a reconfigurable open microfluidic assembly where tissue models cultured in their ideal microenvironments can be stacked together to model multicellular interactions with spatiotemporal specificity (Fig. 9E).52 This unique ability to stack cultures together was utilized to model sequential paracrine signaling events as well as examine soluble factor signaling between mycobacterial infection and its surrounding environment with spatiotemporal control.52,164

From channel wall removal to extrusion patterning to stackable hydrogels, there are a multitude of ways to modulate between microfluidic systems to attain the advantages desired from each configuration. The versatility of modular systems will enable many different embodiments of different microfluidic systems configured together, leading to many novel systems, models, and biomedical applications in the future.

7. Executive summary of microfluidic systems and their considerations

Throughout sections 3–6, this review has cited work employing a wide range of hydrogel materials, which is summarized in Table 1. Notably, many of these hydrogels have been used across multiple microfluidic systems and patterning methods, highlighting that hydrogel choice is rarely restricted to a single device architecture; rather, researchers must instead consider how to appropriately adapt their approach to the hydrogel and system at hand. For example, channel surfaces may need to be coated to promote hydrogel adhesion in some microfluidic systems, while in others, particularly those relying on wall removal or compaction away from channel walls, coatings are instead selected to minimize adhesion. Similarly, researchers must understand how a given hydrogel's gelation mechanism can be leveraged within a specific microfluidic system. These processes typically require an incubation period, during which flow is often paused (e.g., in closed systems, to avoid disrupting the forming gel) or performed in discrete steps, in which a volume of precursor is introduced and allowed to gel before subsequent volumes are added. Semi-synthetic hydrogels, which combine natural and synthetic polymers to form a network structure (e.g., gelatin methacrylate), and fully synthetic hydrogels (e.g., polyethylene glycol, polyacrylamide), by contrast, can often be tuned to gel at a specific, user-defined time upon introduction to a second cross-linking solution or exposure to light. Table 2 provides a full summary of the microfluidic systems and patterning methods discussed throughout this review, alongside high-level hydrogel material considerations relevant to each.

Table 1. Hydrogel materials used across microfluidic systems and patterning methods.

Hydrogel material Gelation mechanism Microfluidic system Patterning method Reference(s)
Agarose Thermo-gelation Closed Outlet-driven (vacuum) 44
Open Surface tension/capillary pinning 69, 140
Alginate Cross-linking (ionic) Closed Inlet-driven (pump) 83, 86, 156–163
Outlet-driven (vacuum) 81
Chitosan pH-responsive Closed Inlet-driven (pump) 89
Collagen, type I pH-induced neutralization/thermo-gelation Closed Inlet-driven (pump) 91–94
Outlet-driven (vacuum) 38, 44, 96
Semi-open Surface tension-driven 39, 76, 99–103, 109, 111, 113–117, 126, 127, 153, 154
Viscous fingering 119–122
Partially pump-driven 42
Open Surface tension/capillary pinning 50, 52, 69, 133, 134, 140, 164
Aspiration-mediated 150
Fibrinogen Enzymatic polymerization Closed Inlet-driven (pump) 90
Outlet-driven (vacuum) 81
Semi-open Surface tension-driven 17, 39, 99–101, 104–107, 112, 114, 155
Partially pump-driven 125
Open Surface tension/capillary pinning 135–139, 141–147
Aspiration-mediated 37, 149
Fibronectin N/A (substrate deposition) Semi-open Partially pump-driven 42
Gelatin methacrylate (GelMA) Cross-linking (UV-based photopolymerization) Closed Outlet-driven (vacuum) 85, 86
Semi-open Surface tension-driven 110, 118
Open Surface tension/capillary pinning 134
Matrigel Thermo-gelation Closed Outlet-driven (vacuum) 81, 89
Semi-open Surface tension-driven 39, 102, 103, 108, 109, 114, 126
Viscous fingering 119, 121
Partially pump-driven 42, 123
Open Surface tension/capillary pinning 40, 12, 131
Polyacrylamide Cross-linking (UV-based photopolymerization) Closed Outlet-driven (vacuum) 44, 96
Polyethylene glycol (PEG)/ Cross-linking (UV-based photopolymerization and/or covalent) Closed Inlet-driven (pump) 84
Outlet-driven (vacuum) 44, 81, 96, 151
Polyethylene glycol diacrylate (PEG-DA)
Semi-open Partially pump-driven 124
Open Surface tension/capillary pinning 69, 132, 140

Table 2. Use comparisons and considerations for each microfluidic patterning system.

Microfluidic system Relevant patterning methods Advantages Limitations Hydrogel material considerations
Closed - Inlet-driven (pump-based)

- Outlet-driven (vacuum/aspiration)

- Precise, reproducible spatial control via regulated flow rate and/or pressure

- Well suited to continuous gradients and co-flow designs (inlet-driven) or compartmentalized, high-throughput array formats with selective hydrogel retention (outlet-driven)

- Requires continuous pumping/vacuum hardware, introducing dead volume, setup complexity, and flow instability

- Inlet-driven approaches are highly sensitive to relative flow rates between co-flowing streams, which can distort gradients or cause incomplete gelation

- Velocity is not constant across the cross-section of a channel which may cause shear-stress on hydrogels/cells flowing through

- Flow rate or vacuum pressure must be faster than gelation rate of precursor hydrogel solution

- Ionic crosslinking materials (e.g., sodium alginate + calcium chloride) or other two-step cross-linking materials are particularly well suited to inlet-driven co-flow streams, since a second stream can continuously deliver a crosslinker at a defined interface

- Channel surfaces often require pre-treatment (e.g., plasma treatment, silanization) to increase wettability of channel as well as promote hydrogel adhesion during active flow

Semi-open - Surface-tension driven

- Viscous fingering

- Partially pump-driven

- Accessible via standard pipetting

- Removes the need for tubing and pump systems in fully passive configurations, lowering cost and device complexity

- Viscous fingering enables hollow lumen structures without complex device geometry

- Partial pumping extends flow distance beyond what capillary action alone permits

- Passive, capillary/surface-tension-driven flow offers less precise control than pump-driven systems

- Viscous fingering requires a specific viscosity differential between hydrogel and displacing fluid, constraining material choice

- Partially pump-driven approaches still require external vacuum equipment, offsetting some simplicity

- Viscous fingering specifically requires the hydrogel precursor to be more viscous than the displacing fluid, which constrains compatible material choice/concentration

- Thermogelling hydrogel materials (e.g., collagen, Matrigel) and enzymatically gelled hydrogel materials (e.g., fibrin) have gelation periods that suit manual pipette loading

- Channel surfaces may require pre-treatment (e.g., plasma treatment) to achieve the wettability needed for reliable surface tension-driven flow, while still promoting sufficient hydrogel adhesion to prevent detachment during culture

Open - Single region patterning

- Discrete and contiguous multi-region patterning

-Aspiration-mediated

- Continuous direct access to the channel interior enables user manipulation, precise placement, and post-gelation manipulation (e.g., transport, stacking)

- Simple manual pipetting with no external pumps required

- Aspiration-based approaches allow rapid, load-and-aspirate formation of thin, pinned hydrogel membranes

- Restricted in certain channel geometries; must maintain specific channel dimensions to achieve spontaneous capillary flow

- More prone to evaporation/drying during culture time

- Precursor must remain stable during open-air exposure prior to gelation, making evaporation and premature drying a concern

- Thermogelling hydrogel materials (e.g., collagen, Matrigel, agarose) and enzymatically gelled hydrogel materials (e.g., fibrin) have gelation periods that suit manual pipette loading

- Surface treatments are often used to fine-tune wettability at pinning features, ensuring reliable capillary pinning

Modular - Wall removal (e.g., closed-to-open)

- Channel/device stacking

- Extrusion-based integration

- Combines advantages of multiple system types within a single device or workflow (e.g., closed-system flow control with open-system accessibility)

- Increases achievable model complexity

- May add fabrication and operational complexity - Hydrogel must remain compatible across multiple patterning mechanisms within a single workflow (e.g., a material patterned in a closed channel via pump-driven flow that later has a channel surface removed in an open, accessible configuration)

- In architectures relying on wall removal, channel surfaces are often treated to minimize hydrogel adhesion, allowing the hydrogel structure to be cleanly released or manipulated without damage; this is in contrast to closed and semi-open systems, where adhesion promotion is typically the goal

8. Conclusion

Precise hydrogel patterning in microfluidic devices can be achieved through many different strategies, both in isolation and in combination, permitting novel in vitro studies of physiological systems. In this review, we discussed how multi-region hydrogel patterning can be achieved through internal structures in microfluidic devices using capillary pinning as well as by physical removal (aspiration) of hydrogel precursor material – both of which are governed by microfluidic mechanical principles. Closed, semi-open, and open microfluidic systems can be designed to achieve multi-region patterning, each with unique, intrinsic properties and patterning strategies. Of note, the three categories of microfluidic systems were defined here for the purposes of differentiating unique strategies; however, in practice, there is significant overlap between how various microfluidic systems function. Additionally, we discussed the benefits of combining multiple techniques rather than picking one optimal system. By exploiting the advantages of modular systems, the possibilities of novel microfluidic devices and biological systems modeled is greatly increased, thus highlighting the importance and versatility of microfluidics as a tool for scientists across disciplines.

There remain many opportunities for advances and novel technologies in the field of microfluidic devices for hydrogel patterning. New embodiments and applications of closed, semi-open, and open systems are published every year, emphasizing the relevance of these devices to an increasingly diverse body of biomedical research. One of the grand challenges of in vitro physiological systems modeling is the limited ability to recapitulate infinitely complex in vivo systems. We hope that microfluidic systems can help to overcome this limitation through increased modularity – by combining elements of multiple tissue patterning techniques, microphysiological systems can be more comprehensively modeled. We anticipate that this will be achieved through novel combinations of the microfluidic features described in this review: while each was initially designed to address a specific challenge or study a specific phenomenon, together, they have evolved into a toolbox for researchers to pick and choose components for different applications. We anticipate that this will enable new discoveries and scientific advancements in fields spanning biology, organ-on-a-chip, and microphysiological systems.

Author contributions

Conceptualization: E. E. B, L. G. B. Investigation: E. E. B., L. G. B., E. N. N., A. L., J. M. W., A. R. V., L. A. M., M. Y. A., S. P., J. L., L. A. K., J. B. Project administration: E. E. B., L. G. B., E. N. N. Writing – original draft: E. E. B., L. G. B., E. N. N., A. L., J. M. W., A. R. V., L. A. M., M. Y. A., S. P., J. L., J. B. Writing – review and editing: E. E. B., L. G. B., E. N. N., A. L., J. M. W., A. R. V., L. A. M., M. Y. A., S. P., J. L., L. A. K., S. R. C., Y. C. T., J. B., A. J. H., E. B., N. L. J., A. B. T. Visualization: E. E. B., L. G. B., A. L., J. M. W., A. R. V., L. A. M., M. Y. A., S. R. C., J. B. Supervision: Y. C. T., E. B., N. L. J., A. B. T. Funding acquisition: L. G. B., L. A. M., A. J. H., N. L. J., E. B., A. B. T.

Conflicts of interest

A. B. T. received a gift to support research outside the submitted work from Ionis Pharmaceuticals. L. G. B. is employed by Seabright, LLC. E. B. has ownership in Tasso, Inc., Salus Discovery, LLC, and Seabright, LLC and is employed by Tasso Inc. and Seabright, LLC; and A. B. T. has ownership in Seabright, LLC; however, this review is not related to these companies. The terms of this arrangement have been reviewed and approved by the University of Washington in accordance with its policies governing outside work and financial conflicts of interest in research. The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

Research reported in this publication was supported by the National Institutes of Health (NIH) National Institute of General Medical Sciences Grant R35GM128648 (A. B. T.) and National Heart, Lung, and Blood Institute Grant F30HL158030 (A. J. H.), and the National Center for Advancing Translational Sciences Grant TL1TR002318 (L. G. B.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or other funding bodies. This study was also supported by the Fulbright Program (L. A. M.), and a grant from the National Research Foundation of Korea (NRF), funded by the Korean Government (MSIT) (RS-2021-NR059924, RS-2024-00424551) (N. L. J.). This study is also supported by the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the International Cooperative R&D program (No. P0030236) (N. L. J.). Artificial Intelligence tools including Inciteful and Connected Papers were used to help identify some of the sources for this review article; all sources cited were read by the authors. Some sections of the article were proofread by Gemini for grammatical errors and better legibility; the original writing and final editing was done by the authors.

Data availability

No primary research results, software or code have been included and no new data were generated or analyzed as part of this review.

References

  1. Tibbitt M. W. Anseth K. S. Biotechnol. Bioeng. 2009;103:655–663. doi: 10.1002/bit.22361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Lee S.-Y. Koo I.-S. Hwang H. J. Lee D. W. SLAS Discovery. 2023;28:119–137. doi: 10.1016/j.slasd.2023.03.006. [DOI] [PubMed] [Google Scholar]
  3. Abuwatfa W. H. Pitt W. G. Husseini G. A. J. Biomed. Sci. 2024;31:7. doi: 10.1186/s12929-024-00994-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Sugimoto S. and Sato T., in 3D Cell Culture, ed. Z. Koledova, Springer New York, New York, NY, 2017, vol. 1612, pp. 97–105 [Google Scholar]
  5. Herreros-Pomares A. Zhou X. Calabuig-Fariñas S. Lee S.-J. Torres S. Esworthy T. Hann S. Y. Jantus-Lewintre E. Camps C. Zhang L. G. Mater. Sci. Eng., C. 2021;122:111914. doi: 10.1016/j.msec.2021.111914. [DOI] [PubMed] [Google Scholar]
  6. Smith A. S. Luttrell S. M. Dupont J.-B. Gray K. Lih D. Fleming J. W. Cunningham N. J. Jepson S. Hesson J. Mathieu J. Maves L. Berry B. J. Fisher E. C. Sniadecki N. J. Geisse N. A. Mack D. L. J. Tissue Eng. 2022;13:20417314221122127. doi: 10.1177/20417314221122127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Norberg K. J. Liu X. Fernández Moro C. Strell C. Nania S. Blümel M. Balboni A. Bozóky B. Heuchel R. L. Löhr J. M. BMC Cancer. 2020;20:475. doi: 10.1186/s12885-020-06867-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Lazzari G. Nicolas V. Matsusaki M. Akashi M. Couvreur P. Mura S. Acta Biomater. 2018;78:296–307. doi: 10.1016/j.actbio.2018.08.008. [DOI] [PubMed] [Google Scholar]
  9. Yakavets I. Francois A. Benoit A. Merlin J.-L. Bezdetnaya L. Vogin G. Sci. Rep. 2020;10:21273. doi: 10.1038/s41598-020-78087-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Moghimi N. Hosseini S. A. Dalan A. B. Mohammadrezaei D. Goldman A. Kohandel M. Sci. Rep. 2023;13:13648. doi: 10.1038/s41598-023-40680-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Keenan T. M. Folch A. Lab Chip. 2008;8:34–57. doi: 10.1039/B711887B. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Cosson S. and Lutolf M. P., in Methods in Cell Biology, Elsevier, 2014, vol. 121, pp. 91–102 [DOI] [PubMed] [Google Scholar]
  13. Zhong H. Xuan L. Wang D. Zhou J. Li Y. Jiang Q. RSC Adv. 2017;7:21837–21847. doi: 10.1039/C7RA01868A. [DOI] [Google Scholar]
  14. Piard C. Jeyaram A. Liu Y. Caccamese J. Jay S. M. Chen Y. Fisher J. Biomaterials. 2019;222:119423. doi: 10.1016/j.biomaterials.2019.119423. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Sugiura S. Cha J. M. Yanagawa F. Zorlutuna P. Bae H. Khademhosseini A. J. Tissue Eng. Regener. Med. 2016;10:690–699. doi: 10.1002/term.1843. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Kazemzadeh-Narbat M. Rouwkema J. Annabi N. Cheng H. Ghaderi M. Cha B. Aparnathi M. Khalilpour A. Byambaa B. Jabbari E. Tamayol A. Khademhosseini A. Adv. Healthcare Mater. 2017;6:1601122. doi: 10.1002/adhm.201601122. [DOI] [PubMed] [Google Scholar]
  17. Kim S. Lee H. Chung M. Jeon N. L. Lab Chip. 2013;13:1489. doi: 10.1039/C3LC41320A. [DOI] [PubMed] [Google Scholar]
  18. Gegg C. Yang F. Acta Biomater. 2020;101:196–205. doi: 10.1016/j.actbio.2019.10.025. [DOI] [PubMed] [Google Scholar]
  19. Biju T. S. Priya V. V. Francis A. P. Drug Delivery Transl. Res. 2023;13:2239–2253. doi: 10.1007/s13346-023-01327-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Liu Y. Xia T. Wei J. Liu Q. Li X. Nanoscale. 2017;9:4950–4962. doi: 10.1039/C7NR00001D. [DOI] [PubMed] [Google Scholar]
  21. Liu Y. Wei J. Lu J. Lei D. Yan S. Li X. Mater. Sci. Eng., C. 2016;63:475–484. doi: 10.1016/j.msec.2016.03.025. [DOI] [PubMed] [Google Scholar]
  22. Tenje M. Cantoni F. Porras Hernández A. M. Searle S. S. Johansson S. Barbe L. Antfolk M. Pohlit H. Organs-on-a-Chip. 2020;2:100003. doi: 10.1016/j.ooc.2020.100003. [DOI] [Google Scholar]
  23. Primo G. A. Mata A. Adv. Funct. Mater. 2021;31:2009574. doi: 10.1002/adfm.202009574. [DOI] [Google Scholar]
  24. Weigel N. Li Y. Thiele J. Fery A. Curr. Opin. Colloid Interface Sci. 2023;64:101673. doi: 10.1016/j.cocis.2022.101673. [DOI] [Google Scholar]
  25. Khetan S. Burdick J. A. Soft Matter. 2011;7:830–838. doi: 10.1039/C0SM00852D. [DOI] [Google Scholar]
  26. Lee M. Rizzo R. Surman F. Zenobi-Wong M. Chem. Rev. 2020;120:10950–11027. doi: 10.1021/acs.chemrev.0c00077. [DOI] [PubMed] [Google Scholar]
  27. Francis R. M. DeForest C. A. Acc. Mater. Res. 2023;4:704–715. doi: 10.1021/accountsmr.3c00062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Lima M. J. Correlo V. M. Reis R. L. Mater. Sci. Eng., C. 2014;42:615–621. doi: 10.1016/j.msec.2014.05.064. [DOI] [PubMed] [Google Scholar]
  29. Moeinzadeh S. and Jabbari E., in 3D Cell Culture, ed. Z. Koledova, Springer New York, New York, NY, 2017, vol. 1612, pp. 239–252 [Google Scholar]
  30. Chae S. Ha D.-H. Lee H. Int. J. Bioprint. 2023;9:748. doi: 10.18063/ijb.748. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Hull S. M. Brunel L. G. Heilshorn S. C. Adv. Mater. 2022;34:2103691. doi: 10.1002/adma.202103691. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Chiu D. T. Jeon N. L. Huang S. Kane R. S. Wargo C. J. Choi I. S. Ingber D. E. Whitesides G. M. Proc. Natl. Acad. Sci. U. S. A. 2000;97:2408–2413. doi: 10.1073/pnas.040562297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Choi N. W. Cabodi M. Held B. Gleghorn J. P. Bonassar L. J. Stroock A. D. Nat. Mater. 2007;6:908–915. doi: 10.1038/nmat2022. [DOI] [PubMed] [Google Scholar]
  34. Berthier E. Dostie A. M. Lee U. N. Berthier J. Theberge A. B. Anal. Chem. 2019;91:8739–8750. doi: 10.1021/acs.analchem.9b01429. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Juncker D. Schmid H. Drechsler U. Wolf H. Wolf M. Michel B. De Rooij N. Delamarche E. Anal. Chem. 2002;74:6139–6144. doi: 10.1021/ac0261449. [DOI] [PubMed] [Google Scholar]
  36. Wang S. Zhang X. Ma C. Yan S. Inglis D. Feng S. Biosensors. 2021;11:405. doi: 10.3390/bios11100405. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Park D. Lee J. Lee Y. Son K. Choi J. W. Jeang W. J. Choi H. Hwang Y. Kim H.-Y. Jeon N. L. Sci. Rep. 2021;11:19986. doi: 10.1038/s41598-021-99387-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Gumuscu B. Albers H. J. Van Den Berg A. Eijkel J. C. T. Van Der Meer A. D. Sci. Rep. 2017;7:3381. doi: 10.1038/s41598-017-01944-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Huang C. P. Lu J. Seon H. Lee A. P. Flanagan L. A. Kim H.-Y. Putnam A. J. Jeon N. L. Lab Chip. 2009;9:1740. doi: 10.1039/B818401A. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Park S. E. Kang S. Paek J. Georgescu A. Chang J. Yi A. Y. Wilkins B. J. Karakasheva T. A. Hamilton K. E. Huh D. D. Nat. Methods. 2022;19:1449–1460. doi: 10.1038/s41592-022-01643-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Iakovlev A. P. Erofeev A. S. Gorelkin P. V. Biosensors. 2022;12:956. doi: 10.3390/bios12110956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Shrirao A. B. Kung F. H. Yip D. Cho C. H. Townes-Anderson E. Biofabrication. 2014;6:035016. doi: 10.1088/1758-5082/6/3/035016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Narayanamurthy V. Jeroish Z. E. Bhuvaneshwari K. S. Bayat P. Premkumar R. Samsuri F. Yusoff M. M. RSC Adv. 2020;10:11652–11680. doi: 10.1039/D0RA00263A. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Gumuscu B. Bomer J. G. Van Den Berg A. Eijkel J. C. T. Lab Chip. 2015;15:664–667. doi: 10.1039/C4LC01350F. [DOI] [PubMed] [Google Scholar]
  45. Melin J. Van Der Wijngaart W. Stemme G. Lab Chip. 2005;5:682. doi: 10.1039/B501781E. [DOI] [PubMed] [Google Scholar]
  46. Berthier E. Beebe D. J. Lab Chip. 2007;7:1475. doi: 10.1039/B707637A. [DOI] [PubMed] [Google Scholar]
  47. Walker G. M. Beebe D. J. Lab Chip. 2002;2:131. doi: 10.1039/B204381E. [DOI] [PubMed] [Google Scholar]
  48. Kolliopoulos P. Kumar S. npj Microgravity. 2021;7:51. doi: 10.1038/s41526-021-00180-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Olanrewaju A. Beaugrand M. Yafia M. Juncker D. Lab Chip. 2018;18:2323–2347. doi: 10.1039/C8LC00458G. [DOI] [PubMed] [Google Scholar]
  50. Humayun M. Chow C.-W. Young E. W. K. Lab Chip. 2018;18:1298–1309. doi: 10.1039/C7LC01357D. [DOI] [PubMed] [Google Scholar]
  51. Wang J. Wang H. Wang Y. Liu Z. Li Z. Li J. Chen Q. Meng Q. Shu W. W. Wu J. Xiao C. Han F. Li B. Acta Biomater. 2022;142:85–98. doi: 10.1016/j.actbio.2022.01.055. [DOI] [PubMed] [Google Scholar]
  52. Yu J. Berthier E. Craig A. De Groot T. E. Sparks S. Ingram P. N. Jarrard D. F. Huang W. Beebe D. J. Theberge A. B. Nat. Biomed. Eng. 2019;3:830–841. doi: 10.1038/s41551-019-0421-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Bayraktar T. Pidugu S. B. Int. J. Heat Mass Transfer. 2006;49:815–824. doi: 10.1016/j.ijheatmasstransfer.2005.11.007. [DOI] [Google Scholar]
  54. Malloggi F., in Soft Matter at Aqueous Interfaces, ed. P. Lang and Y. Liu, Springer International Publishing, 2016, vol. 917, pp. 515–546 [Google Scholar]
  55. Novotný J. Foret F. J. Sep. Sci. 2017;40:383–394. doi: 10.1002/jssc.201600905. [DOI] [PubMed] [Google Scholar]
  56. Oliveira N. M. Vilabril S. Oliveira M. B. Reis R. L. Mano J. F. Mater. Sci. Eng., C. 2019;97:851–863. doi: 10.1016/j.msec.2018.12.040. [DOI] [PubMed] [Google Scholar]
  57. Ge T. Hu W. Zhang Z. He X. Wang L. Han X. Dai Z. Mater. Today Bio. 2024;26:101048. doi: 10.1016/j.mtbio.2024.101048. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Kaigala G. V. Lovchik R. D. Delamarche E. Angew. Chem., Int. Ed. 2012;51:11224–11240. doi: 10.1002/anie.201201798. [DOI] [PubMed] [Google Scholar]
  59. Zeng Y. Khor J. W. Van Neel T. L. Tu W. Berthier J. Thongpang S. Berthier E. Theberge A. B. Nat. Rev. Chem. 2023;7:439–455. doi: 10.1038/s41570-023-00483-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Lin J. Hou Y. Zhang Q. Lin J.-M. Lab Chip. 2025;25:787–805. doi: 10.1039/D4LC00646A. [DOI] [PubMed] [Google Scholar]
  61. Fergola A. Ballesio A. Frascella F. Napione L. Cocuzza M. Marasso S. L. Biosensors. 2025;15:345. doi: 10.3390/bios15060345. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Wei Z. Wang S. Hirvonen J. Santos H. A. Li W. Adv. Healthcare Mater. 2022;11:2200846. doi: 10.1002/adhm.202200846. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Liu Y. Chen Z. Xu J. Green Chem. Eng. 2024;5:16–30. doi: 10.1016/j.gce.2023.02.002. [DOI] [Google Scholar]
  64. Zhang Q. Feng S. Lin L. Mao S. Lin J.-M. Chem. Soc. Rev. 2021;50:5333–5348. doi: 10.1039/D0CS01516D. [DOI] [PubMed] [Google Scholar]
  65. Kim S. M. Lee S. H. Suh K. Y. Lab Chip. 2008;8:1015. doi: 10.1039/B800835C. [DOI] [PubMed] [Google Scholar]
  66. Rothbauer M. Zirath H. Ertl P. Lab Chip. 2018;18:249–270. doi: 10.1039/C7LC00815E. [DOI] [PubMed] [Google Scholar]
  67. Pereiro I. Cors J. F. Pané S. Nelson B. J. Kaigala G. V. Chem. Soc. Rev. 2019;48:1236–1254. doi: 10.1039/C8CS00852C. [DOI] [PubMed] [Google Scholar]
  68. Turunen S. Haaparanta A.-M. Äänismaa R. Kellomäki M. J. Tissue Eng. Regener. Med. 2013;7:253–270. doi: 10.1002/term.520. [DOI] [PubMed] [Google Scholar]
  69. Haack A. J. Brown L. G. Goldstein A. J. Mulimani P. Berthier J. Viswanathan A. R. Kopyeva I. Whitten J. M. Lin A. Nguyen S. H. Leahy T. P. Bouker E. E. Padgett R. M. Mazzawi N. A. Tokihiro J. C. Bretherton R. C. Wu A. Tapscott S. J. DeForest C. A. Popowics T. E. Berthier E. Sniadecki N. J. Theberge A. B. Adv. Sci. 2025;12:2501148. doi: 10.1002/advs.202501148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Qiao C. Sun Y. Han Y. Ma H. Zhao Z. Hu Y. Zeng H. ACS Nano. 2025;19:29898–29933. doi: 10.1021/acsnano.5c05689. [DOI] [PubMed] [Google Scholar]
  71. Wang S. Zhang X. Ma C. Yan S. Inglis D. Feng S. Biosensors. 2021;11:405. doi: 10.3390/bios11100405. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Walsh E. J. Feuerborn A. Wheeler J. H. R. Tan A. N. Durham W. M. Foster K. R. Cook P. R. Nat. Commun. 2017;8:816. doi: 10.1038/s41467-017-00846-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Lade R. K. Hippchen E. J. Macosko C. W. Francis L. F. Langmuir. 2017;33:2949–2964. doi: 10.1021/acs.langmuir.6b04506. [DOI] [PubMed] [Google Scholar]
  74. Gibbs J. W. Trans. Conn. Acad., II. 1873:382–404. [Google Scholar]
  75. Park S. Jang H. Kim B. S. Hwang C. Jeong G. S. Park Y. PLoS One. 2017;12(9):e0184595. doi: 10.1371/journal.pone.0184595. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Shin Y. Han S. Jeon J. S. Yamamoto K. Zervantonakis I. K. Sudo R. Kamm R. D. Chung S. Nat. Protoc. 2012;7:1247–1259. doi: 10.1038/nprot.2012.051. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Chen S. W. Blazeski A. Zhang S. Shelton S. E. Offeddu G. S. Kamm R. D. Lab Chip. 2023;23:4552–4564. doi: 10.1039/D3LC00512G. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Wong J. F. Mohan M. D. Young E. W. K. Simmons C. A. Biosens. Bioelectron. 2020;147:111757. doi: 10.1016/j.bios.2019.111757. [DOI] [PubMed] [Google Scholar]
  79. Mohan M. D. Young E. W. K. Lab Chip. 2021;21:4081–4094. doi: 10.1039/D1LC00279A. [DOI] [PubMed] [Google Scholar]
  80. Vulto P. Podszun S. Meyer P. Hermann C. Manz A. Urban G. A. Lab Chip. 2011;11:1596. doi: 10.1039/C0LC00643B. [DOI] [PubMed] [Google Scholar]
  81. Kang M. Park W. Na S. Paik S. Lee H. Park J. W. Kim H. Jeon N. L. Small. 2015;11:2789–2797. doi: 10.1002/smll.201403596. [DOI] [PubMed] [Google Scholar]
  82. Bhatia S. N. Ingber D. E. Nat. Biotechnol. 2014;32:760–772. doi: 10.1038/nbt.2989. [DOI] [PubMed] [Google Scholar]
  83. Johann R. M. Renaud P. Biointerphases. 2007;2:73–79. doi: 10.1116/1.2746873. [DOI] [PubMed] [Google Scholar]
  84. Zguris J. C. Itle L. J. Koh W.-G. Pishko M. V. Langmuir. 2005;21:4168–4174. doi: 10.1021/la0470176. [DOI] [PubMed] [Google Scholar]
  85. Pedron S. Becka E. Harley B. A. Adv. Mater. 2015;27:1567–1572. doi: 10.1002/adma.201404896. [DOI] [PubMed] [Google Scholar]
  86. Yu Y. Jin B. Chen J. Lou C. Guo J. Yang C. Zhao Y. Adv. Sci. 2023;10:2207536. doi: 10.1002/advs.202207536. [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Whitesides G. M. Nature. 2006;442:368–373. doi: 10.1038/nature05058. [DOI] [PubMed] [Google Scholar]
  88. Wang X. Phan D. T. T. Zhao D. George S. C. Hughes C. C. W. Lee A. P. Lab Chip. 2016;16:868–876. doi: 10.1039/C5LC01563D. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Tibbe M. P. Leferink A. M. Van Den Berg A. Eijkel J. C. T. Segerink L. I. Adv. Mater. Technol. 2018;3:1700200. doi: 10.1002/admt.201700200. [DOI] [Google Scholar]
  90. Pei J. Sun Q. Yi Z. Li Q. Wang X. J. Micromech. Microeng. 2020;30:035005. doi: 10.1088/1361-6439/ab68b2. [DOI] [Google Scholar]
  91. Bai H. Olson K. N. P. Pan M. Marshall T. Singh H. Ma J. Gilbride P. Yuan Y. McCormack J. Si L. Maharjan S. Huang D. Qian X. Livermore C. Zhang Y. S. Xie X. Adv. Sci. 2024;11:2304332. doi: 10.1002/advs.202304332. [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Loessberg-Zahl J. Beumer J. Van Den Berg A. Eijkel J. Van Der Meer A. Micromachines. 2020;11:1112. doi: 10.3390/mi11121112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  93. Mahadik B. P. Wheeler T. D. Skertich L. J. Kenis P. J. A. Harley B. A. C. Adv. Healthcare Mater. 2014;3:449–458. doi: 10.1002/adhm.201300263. [DOI] [PubMed] [Google Scholar]
  94. Toh Y.-C. Lim T. C. Tai D. Xiao G. Van Noort D. Yu H. Lab Chip. 2009;9:2026. doi: 10.1039/B900912D. [DOI] [PubMed] [Google Scholar]
  95. Moscovici M. Chien W.-Y. Abdelgawad M. Sun Y. Biomicrofluidics. 2010;4:046501. doi: 10.1063/1.3499939. [DOI] [PMC free article] [PubMed] [Google Scholar]
  96. Gumuscu B. and Eijkel J. C. T., in Cell-Based Microarrays, Humana Press, 2018, vol. 1771 [Google Scholar]
  97. Jeon N. L. Choi I. S. Xu B. Whitesides G. M. Adv. Mater. 1999;11:946–950. doi: 10.1002/(SICI)1521-4095(199908)11:11<946::AID-ADMA946>3.0.CO;2-9. [DOI] [Google Scholar]
  98. Khanjani E. Fergola A. López Martínez J. A. Nazarnezhad S. Casals Terre J. Marasso S. L. Aghajanloo B. Tissue Eng., Part C. 2025;4:1502127. [Google Scholar]
  99. Haack A. J., Whitten J. M., Knudsen L. A., Bouker E. E., Viswanathan A. R., Brown L. G., Kim D. A., Milton L. A., Lin A., Georgiou A., Schumacher E. A., Alizai M. Y., Toh Y.-C., Berthier J., DeForest C. A., Sniadecki N. J., Theberge A. B. and Berthier E., bioRxiv, 2025, 10.1101/2025.10.28.684690 [DOI]
  100. Kwee B. J. Mansouri M. Akue A. Sung K. E. Biofabrication. 2025;17:015009. doi: 10.1088/1758-5090/ad80ce. [DOI] [PubMed] [Google Scholar]
  101. Raskovic D., Zatorski J. M., Arneja A., Kiridena S., Ozulumba T., Hammel J. H., Anbaei P., Ortiz-Cárdenas J. E., Braciale T. J., Munson J. M., Luckey C. J. and Pompano R. R., bioRxiv, 2026, 10.1101/2025.01.12.632545 [DOI]
  102. Anguiano M. Morales X. Castilla C. Pena A. R. Ederra C. Martínez M. Ariz M. Esparza M. Amaveda H. Mora M. Movilla N. Aznar J. M. G. Cortés-Domínguez I. Ortiz-de-Solorzano C. PLoS One. 2020;15:e0220019. doi: 10.1371/journal.pone.0220019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  103. Jeon J. S. Zervantonakis I. K. Chung S. Kamm R. D. Charest J. L. PLoS One. 2013;8:e56910. doi: 10.1371/journal.pone.0056910. [DOI] [PMC free article] [PubMed] [Google Scholar]
  104. Chen M. B. Whisler J. A. Jeon J. S. Kamm R. D. Integr. Biol. 2013;5:1262. doi: 10.1039/c3ib40149a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  105. Chen M. B. Whisler J. A. Fröse J. Yu C. Shin Y. Kamm R. D. Nat. Protoc. 2017;12:865–880. doi: 10.1038/nprot.2017.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  106. Liu T. Zhou C. Ji J. Xu X. Xing Z. Shinohara M. Sakai Y. Sun T. Feng X. Yu Z. Pang Y. Sun W. Biofabrication. 2023;15:044102. doi: 10.1088/1758-5090/ace3f9. [DOI] [PubMed] [Google Scholar]
  107. Whisler J. A. Chen M. B. Kamm R. D. Tissue Eng., Part C. 2014;20:543–552. doi: 10.1089/ten.tec.2013.0370. [DOI] [PMC free article] [PubMed] [Google Scholar]
  108. Jang J. M. Tran S.-H.-T. Na S. C. Jeon N. L. ACS Appl. Mater. Interfaces. 2015;7:2183–2188. doi: 10.1021/am508292t. [DOI] [PubMed] [Google Scholar]
  109. Park S. Young E. W. K. Adv. Mater. Technol. 2021;6:2100828. doi: 10.1002/admt.202100828. [DOI] [Google Scholar]
  110. Hopkins T. Midha S. Grossemy S. Screen H. R. C. Wann A. K. T. Knight M. M. J. Tissue Eng. 2025;16 doi: 10.1177/20417314251326256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  111. Trietsch S. J. Naumovska E. Kurek D. Setyawati M. C. Vormann M. K. Wilschut K. J. Lanz H. L. Nicolas A. Ng C. P. Joore J. Kustermann S. Roth A. Hankemeier T. Moisan A. Vulto P. Nat. Commun. 2017;8:262. doi: 10.1038/s41467-017-00259-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  112. Jung O. Tung Y.-T. Sim E. Chen Y.-C. Lee E. Ferrer M. Song M. J. Biofabrication. 2022;14:025012. doi: 10.1088/1758-5090/ac32a5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  113. Su C. Chuah Y. J. Ong H. B. Tay H. M. Dalan R. Hou H. W. Biosensors. 2021;11:509. doi: 10.3390/bios11120509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  114. Menon N. V. Tay H. M. Wee S. N. Li K. H. H. Hou H. W. Lab Chip. 2017;17:2960–2968. doi: 10.1039/C7LC00607A. [DOI] [PubMed] [Google Scholar]
  115. Coskun U. C. Kus F. Rehman A. U. Morova B. Gulle M. Baser H. Kul D. Kiraz A. Baysal K. Erten A. ACS Omega. 2022;7:8281–8293. doi: 10.1021/acsomega.1c05118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  116. Su C. Menon N. V. Xu X. Teo Y. R. Cao H. Dalan R. Tay C. Y. Hou H. W. Lab Chip. 2021;21:2359–2371. doi: 10.1039/D1LC00131K. [DOI] [PubMed] [Google Scholar]
  117. Kim S. Lee S. K. Son A. Lee J. Kim H. G. Adv. Healthcare Mater. 2023;12:2301673. doi: 10.1002/adhm.202301673. [DOI] [PMC free article] [PubMed] [Google Scholar]
  118. Ko G. Jeon T.-J. Kim S. M. Micromachines. 2022;13:2216. doi: 10.3390/mi13122216. [DOI] [PMC free article] [PubMed] [Google Scholar]
  119. Bischel L. L. Lee S.-H. Beebe D. J. SLAS Technol. 2012;17:96–103. doi: 10.1177/2211068211426694. [DOI] [PMC free article] [PubMed] [Google Scholar]
  120. De Graaf M. N. S. Cochrane A. Van Den Hil F. E. Buijsman W. Van Der Meer A. D. Van Den Berg A. Mummery C. L. Orlova V. V. APL Bioeng. 2019;3:026105. doi: 10.1063/1.5090986. [DOI] [PMC free article] [PubMed] [Google Scholar]
  121. Bischel L. L. Young E. W. K. Mader B. R. Beebe D. J. Biomaterials. 2013;34:1471–1477. doi: 10.1016/j.biomaterials.2012.11.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  122. Herland A. Van Der Meer A. D. FitzGerald E. A. Park T.-E. Sleeboom J. J. F. Ingber D. E. PLoS One. 2016;11:e0150360. doi: 10.1371/journal.pone.0150360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  123. Wong A. P. Perez-Castillejos R. Christopher Love J. Whitesides G. M. Biomaterials. 2008;29:1853–1861. doi: 10.1016/j.biomaterials.2007.12.044. [DOI] [PMC free article] [PubMed] [Google Scholar]
  124. Rocca M. Dufresne M. Salva M. Niemeyer C. M. Delamarche E. Angew. Chem. 2021;60:24064–24069. doi: 10.1002/anie.202110974. [DOI] [PMC free article] [PubMed] [Google Scholar]
  125. Visone R. Ugolini G. S. Vinarsky V. Penati M. Redaelli A. Forte G. Rasponi M. Adv. Mater. Technol. 2019;4:1800319. doi: 10.1002/admt.201800319. [DOI] [Google Scholar]
  126. Trietsch S. J. Israëls G. D. Joore J. Hankemeier T. Vulto P. Lab Chip. 2013;13:3548. doi: 10.1039/C3LC50210D. [DOI] [PubMed] [Google Scholar]
  127. Olaizola-Rodrigo C. Palma-Florez S. Ranđelović T. Bayona C. Ashrafi M. Samitier J. Lagunas A. Mir M. Doblaré M. Ochoa I. Monge R. Oliván S. Lab Chip. 2024;24:2094–2106. doi: 10.1039/D3LC01082A. [DOI] [PubMed] [Google Scholar]
  128. Casavant B. P. Berthier E. Theberge A. B. Berthier J. Montanez-Sauri S. I. Bischel L. L. Brakke K. Hedman C. J. Bushman W. Keller N. P. Beebe D. J. Proc. Natl. Acad. Sci. U. S. A. 2013;110:10111–10116. doi: 10.1073/pnas.1302566110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  129. Berthier J., Brakke K. A. and Berthier E., Open Microfluidics, Scrivener Publishing LLC, 2016 [Google Scholar]
  130. Berthier J., Theberge A. B. and Berthier E., Open-Channel Microfluidics, IOP Publishing, 2nd edn, 2024 [Google Scholar]
  131. Berry S. B. Zhang T. Day J. H. Su X. Wilson I. Z. Berthier E. Theberge A. B. Lab Chip. 2017;17:4253–4264. doi: 10.1039/C7LC00878C. [DOI] [PubMed] [Google Scholar]
  132. Lee S. H. Heinz A. J. Shin S. Jung Y.-G. Choi S.-E. Park W. Roe J.-H. Kwon S. Anal. Chem. 2010;82:2900–2906. doi: 10.1021/ac902903q. [DOI] [PubMed] [Google Scholar]
  133. Marder M. Remmert C. Perschel J. A. Otgonbayar M. Von Toerne C. Hauck S. Bushe J. Feuchtinger A. Sheikh B. Moussus M. Meier M. Cell Rep. 2024;43:114008. doi: 10.1016/j.celrep.2024.114008. [DOI] [PubMed] [Google Scholar]
  134. Milton L. A. Kasetsirikul S. Catano J. A. Hilmi F. S. Zhou Z. Molley T. G. Kilian K. A. Ong L. J. Y. Chirnside J. Byrom N. Balshaw G. Liang S. Bray L. J. Hutmacher D. W. Meinert C. Toh Y.-C. Lab Chip. 2025;25:5875–5893. doi: 10.1039/D5LC00753D. [DOI] [PubMed] [Google Scholar]
  135. Ko J. Ahn J. Kim S. Lee Y. Lee J. Park D. Jeon N. L. Lab Chip. 2019;19:2822–2833. doi: 10.1039/C9LC00140A. [DOI] [PubMed] [Google Scholar]
  136. Lee S. Kim S. Jeon J. S. Lab Chip. 2022;22:4359–4368. doi: 10.1039/D2LC00672C. [DOI] [PubMed] [Google Scholar]
  137. Kim S. Ko J. Lee S. Park D. Park S. Jeon N. L. Biotechnol. Bioeng. 2021;118:2524–2535. doi: 10.1002/bit.27765. [DOI] [PubMed] [Google Scholar]
  138. Kim J. Song Y. Jolly A. L. Hwang T. Kim S. Lee B. Jang J. Jo D. H. Baek K. Liu T. Yoo S. Jeon N. L. Adv. Mater. Technol. 2024;9:2400634. doi: 10.1002/admt.202400634. [DOI] [Google Scholar]
  139. Oh S. Ryu H. Tahk D. Ko J. Chung Y. Lee H. K. Lee T. R. Jeon N. L. Lab Chip. 2017;17:3405–3414. doi: 10.1039/C7LC00646B. [DOI] [PubMed] [Google Scholar]
  140. Lee U. N. Day J. H. Haack A. J. Bretherton R. C. Lu W. DeForest C. A. Theberge A. B. Berthier E. Lab Chip. 2020;20:525–536. doi: 10.1039/C9LC00621D. [DOI] [PMC free article] [PubMed] [Google Scholar]
  141. Lee J. Jung S. Hong H. K. Jo H. Rhee S. Jeong Y.-L. Ko J. Cho Y. B. Jeon N. L. Lab Chip. 2024;24:2208–2223. doi: 10.1039/D3LC01055D. [DOI] [PubMed] [Google Scholar]
  142. Lee Y. Choi J. W. Yu J. Park D. Ha J. Son K. Lee S. Chung M. Kim H.-Y. Jeon N. L. Lab Chip. 2018;18:2433–2440. doi: 10.1039/C8LC00336J. [DOI] [PubMed] [Google Scholar]
  143. Lee S.-R. Kim Y. Kim S. Kim J. Park S. Rhee S. Park D. Lee B. Baek K. Kim H.-Y. Jeon N. L. Microsyst. Nanoeng. 2022;8:126. doi: 10.1038/s41378-022-00431-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  144. Park S. Kim Y. Lee J. Jung S. Hong J. Kim S. Lee S. Song J. Park S. Oh Y. S. Ko J. Jeon N. L. Adv. Mater. Technol. 2025;10:2401526. doi: 10.1002/admt.202401526. [DOI] [Google Scholar]
  145. Yu J. Lee S. Song J. Lee S.-R. Kim S. Choi H. Kang H. Hwang Y. Hong Y.-K. Jeon N. L. Nano Convergence. 2022;9:16. doi: 10.1186/s40580-022-00306-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  146. Ko J. Lee Y. Lee S. Lee S. Jeon N. L. Adv. Healthcare Mater. 2019;8:1900328. doi: 10.1002/adhm.201900328. [DOI] [PubMed] [Google Scholar]
  147. Li Q. Niu K. Wang D. Xuan L. Wang X. Lab Chip. 2022;22:2682–2694. doi: 10.1039/D1LC00767J. [DOI] [PubMed] [Google Scholar]
  148. Akcay G. Van Venrooij J. Luttge R. J. Vac. Sci. Technol., B. 2024;42:063001. doi: 10.1116/6.0003967. [DOI] [Google Scholar]
  149. Nguyen T. T. Y. Lee J. Choi S. Jeon N. L. BioChip J. 2024;18:589–600. doi: 10.1007/s13206-024-00171-1. [DOI] [Google Scholar]
  150. Park D. Son K. Hwang Y. Ko J. Lee Y. Doh J. Jeon N. L. Front. Immunol. 2019;10:1133. doi: 10.3389/fimmu.2019.01133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  151. Li Y. Motschman J. D. Kelly S. T. Yellen B. B. Anal. Chem. 2020;92:2794–2801. doi: 10.1021/acs.analchem.9b05099. [DOI] [PMC free article] [PubMed] [Google Scholar]
  152. Kheiri S. Yakavets I. Cruickshank J. Ahmadi F. Berman H. K. Cescon D. W. Young E. W. K. Kumacheva E. Adv. Mater. 2024;36:2410547. doi: 10.1002/adma.202410547. [DOI] [PubMed] [Google Scholar]
  153. Moya M. L. Triplett M. Simon M. Alvarado J. Booth R. Osburn J. Soscia D. Qian F. Fischer N. O. Kulp K. Wheeler E. K. Ann. Biomed. Eng. 2020;48:780–793. doi: 10.1007/s10439-019-02405-y. [DOI] [PubMed] [Google Scholar]
  154. Shanti A. Samara B. Abdullah A. Hallfors N. Accoto D. Sapudom J. Alatoom A. Teo J. Danti S. Stefanini C. Pharmaceutics. 2020;12:464. doi: 10.3390/pharmaceutics12050464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  155. Ugolini G. S. Visone R. Redaelli A. Moretti M. Rasponi M. Adv. Healthcare Mater. 2017;6:1601170. doi: 10.1002/adhm.201601170. [DOI] [PubMed] [Google Scholar]
  156. Shin S.-J. Park J.-Y. Lee J.-Y. Park H. Park Y.-D. Lee K.-B. Whang C.-M. Lee S.-H. Langmuir. 2007;23:9104–9108. doi: 10.1021/la700818q. [DOI] [PubMed] [Google Scholar]
  157. Yasuda S. Hayakawa M. Onoe H. Takinoue M. Soft Matter. 2017;13:2141–2147. doi: 10.1039/C6SM02695H. [DOI] [PubMed] [Google Scholar]
  158. Kang E. Jeong G. S. Choi Y. Y. Lee K. H. Khademhosseini A. Lee S.-H. Nat. Mater. 2011;10:877–883. doi: 10.1038/nmat3108. [DOI] [PubMed] [Google Scholar]
  159. Yoshida K. Onoe H. Sci. Rep. 2017;7:45987. doi: 10.1038/srep45987. [DOI] [PMC free article] [PubMed] [Google Scholar]
  160. Jia L. Han F. Yang H. Turnbull G. Wang J. Clarke J. Shu W. Guo M. Li B. Adv. Healthcare Mater. 2019;8:1900435. doi: 10.1002/adhm.201900435. [DOI] [PubMed] [Google Scholar]
  161. Higashi K. Ogawa M. Fujimoto K. Onoe H. Miki N. Micromachines. 2017;8:176. doi: 10.3390/mi8060176. [DOI] [Google Scholar]
  162. Lee K. H. Shin S. J. Park Y. Lee S. Small. 2009;5:1264–1268. doi: 10.1002/smll.200801667. [DOI] [PubMed] [Google Scholar]
  163. Nakajima S. Kawano R. Onoe H. Soft Matter. 2017;13:3710–3719. doi: 10.1039/C7SM00279C. [DOI] [PubMed] [Google Scholar]
  164. Berry S. B. Gower M. S. Su X. Seshadri C. Theberge A. B. Front. Bioeng. Biotechnol. 2020;8:931. doi: 10.3389/fbioe.2020.00931. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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Data Availability Statement

No primary research results, software or code have been included and no new data were generated or analyzed as part of this review.


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