Skip to main content
ACS AuthorChoice logoLink to ACS AuthorChoice
. 2024 Jan 26;24(9):2735–2742. doi: 10.1021/acs.nanolett.3c04421

Three-Dimensional Optical Imaging of Internal Deformations in Polymeric Microscale Mechanical Metamaterials

Brian W Blankenship , Timon Meier , Naichen Zhao , Stefanos Mavrikos , Sophia Arvin , Natalia De La Torre , Brian Hsu , Nathan Seymour , Costas P Grigoropoulos †,*
PMCID: PMC10921468  PMID: 38277644

Abstract

graphic file with name nl3c04421_0006.jpg

Recent advances in two-photon polymerization fabrication processes are paving the way to creating macroscopic metamaterials with microscale architectures, which exhibit mechanical properties superior to their bulk material counterparts. These metamaterials typically feature lightweight, complex patterns such as lattice or minimal surface structures. Conventional tools for investigating these microscale structures, such as scanning electron microscopy, cannot easily probe the internal features of these structures, which are critical for a comprehensive assessment of their mechanical behavior. In turn, we demonstrate an optical confocal microscopy-based approach that allows for high-resolution optical imaging of internal deformations and fracture processes in microscale metamaterials under mechanical load. We validate this technique by investigating an exemplary metamaterial lattice structure of 80 × 80 × 80 μm3 in size. This technique can be extended to other metamaterial systems and holds significant promise to enhance our understanding of their real-world performance under loading conditions.

Keywords: mechanical metamaterials, two-photon polymerization, confocal microscopy, polymers


The application of machine learning and automated routines for geometry generation and mechanical analysis are leading to the rapid exploration of the possible design spaces of mechanical metamaterials with tailored properties.15 Typically, these materials contain repetitive patterns of low-density unit cells composed of lattices or minimal surface geometries.6,7 Through precise manipulation of features at the micro- and nanoscale, these metamaterials can be engineered to exhibit enhanced or even novel properties, surpassing those of traditional bulk materials. So far, these innovative design approaches have yielded materials with extraordinary characteristics, including ultrastiffness,8,9 auxetic behavior,1012 negative thermal expansion coefficients,1315 exceptional energy absorption,3,16 and atypical material behavior such as “Cauchy symmetry” and roton-like acoustic dispersion among many others.4,17 The extent of possible properties has yet to be fully explored, and there are new frontiers in designing materials that possess multiple desired properties.18

Coinciding with design advancements has been the development of mesoscale additive manufacturing techniques, enabling the production of arbitrarily shaped metamaterials with intricate nanoscale features and dimensions extending to several centimeters.1921 Among these, two-photon polymerization (TPP) stands out for its fine and versatile printing capabilities, achieving subdiffraction limit feature sizes at volumetric printing rates exceeding 1,000,000 μm3/s.19 Further enhancements in spatial light modulation and materials science are anticipated to elevate these rates even more, promising a leap in scalability and functionality.22

However, as these developments proceed, new diagnostic tools and imaging techniques become necessary to provide advanced in situ diagnostics and to better quantify the detailed behavior and performance of these materials. In this context, for instance, microscale metamaterial structures have been functionalized with nanodiamonds containing NV centers to provide fine temperature and magnetic field measurement capabilities inside of these structures.23 Likewise, the functionalization of structures has been explored with other particles such as quantum dots and gold nanoparticles which can impart sensing capabilities.24 In terms of imaging, existing methods like scanning electron microscopy (SEM) or helium ion microscopy (HIM) provide detailed surface images that can adequately resolve the nanoscale features of these materials.25 However, these imaging modalities fail to capture the internal deformation mechanics of these materials as they rely on the scattering of electrons or ions from the surface of complex structures, which shield the interior members. Thus, subsurface unit cells and interior-facing sections of unit cells on the surface of a larger array are difficult, if not impossible, to image using these techniques.

Alternative techniques utilizing X-ray tomography have been developed that capture the interior deformation of these materials during mechanical compression, yet these techniques require specialized equipment paired to synchrotron radiation sources to achieve resolutions below 500 nm.26 Confocal imaging techniques have been recorded across literature to statically image three-dimensional microscale structures made with TPP. However, they do not appear to have been applied in studies involving in situ mechanical compression.27,28

Addressing this diagnostic gap, we develop and demonstrate a technique to image the deformation mechanics of microscale polymeric metamaterials during mechanical loading by using confocal microscopy. By capturing fluorescence from the polymerized material, we can produce high-fidelity three-dimensional renderings of these structures.

Furthermore, we capture a series of 3D images across discrete deformation steps to validate this technique. In the process, we show the ability to resolve individual fracture and buckling events inside the lattice, thereby contributing significantly to the precise assessment of their mechanical behavior.

One of the most common approaches for designing mechanical metamaterials is by constructing large lattice arrays composed of microscale unit cells. These are made with either repetitive unit cells or by patterning distinct unit cell states. We present a prototypical 4 × 4 × 4 lattice structure composed of four distinct unit cell states in Figure 1 that embodies this latter design rationale and serves as a basis for our proceeding investigations.

Figure 1.

Figure 1

Lattice structure design. (A) Four constituent unit cells that are (B) patterned into a 4 × 4 × 4 arbitrary, symmetric lattice. Given the complex, inhomogeneous structure of this lattice it is difficult to view the internal members even from a (C) top view of the lattice. This engenders a need for more alternative imaging techniques to resolve these members and understand their deformation during mechanical loading.

We fabricate several copies of an 80 μm × 80 μm × 80 μm version of the same lattice design presented in Figure 1 by using a customized TPP setup. Details on this setup are discussed elsewhere in literature.23 SEM images of these structures are shown in Figure 2. Details about the resin materials and fabrication setup are provided in the Materials and Methods section.

Figure 2.

Figure 2

SEM Images. (A) Orthogonal view of the lattice structure design presented in Figure 1 that is fabricated with a two-photon polymerization setup. (B) Top view of the lattice shows internal beam members, but large sections of the view are masked by overlapping sections of the upper levels of the structure, making analysis of internal beam bending nearly impossible with these techniques.

Fabricated samples closely agree with the target geometry, with the elongated beam thicknesses originating from constraints associated with the voxel size from fabrication.29 We produce voxels with lateral dimensions ranging from 650 to 900 nm in size and axial dimensions spanning 3.2–4.0 μm. According to Zhou et al., the voxel resolution of TPP is approximately constrained as follows:29

graphic file with name nl3c04421_m001.jpg 1
graphic file with name nl3c04421_m002.jpg 2

where:

graphic file with name nl3c04421_m003.jpg

ω0 = beam waist

σ2 = effective two-photon cross section for the generation of radicals

I0 = the photon flux intensity at the beam center r = 0, z = 0

ρ0 = the primary initiator particle density

ρth = radical density threshold

τ = pulse width

n = number of pulses

t = total processing-irradiation time

Using an oil immersion lens, the beam waist can be described by the equation:

graphic file with name nl3c04421_m004.jpg 3

ηoil = refractive index of the oil medium

NA is the numerical aperture of the objective lens.

In practice, conventional TPP processes can achieve resolutions in the range 100–200 nm in the xy-plane and below 500 nm in the z axis. However, advanced techniques like stimulated emission depletion (STED) lithography have been successful in pushing these boundaries, achieving feature resolutions down to the tens of nanometers scale.30

In the effort to image the interior of the structures and especially to conduct this imaging simultaneous to compression testing, we first develop a method for reconstructing a three-dimensional representation of the lattice using confocal microscopy. According to the Rayleigh criterion, the resolution of a conventional confocal microscope is roughly constrained by31,32

graphic file with name nl3c04421_m005.jpg 4
graphic file with name nl3c04421_m006.jpg 5

where η is the refractive index of the medium. λex is the excitation wavelength, and λdet is the detected wavelength.

In practice, conventional confocal imaging yields lateral resolutions on the order of 200–600 nm and axial resolutions of 500–1000 nm with high numerical aperture oil objectives.33 These bounds are roughly in line with the capabilities of conventional TPP. In relation to the imaging of metamaterial structures, this would suggest that diffraction would limit the minimum spacing between disparate beam members rather than the minimum size of a structure that would be visible.

In our investigations, we utilize a 60× oil immersion objective with a numerical aperture of 1.25 to capture the features of our lattice structures. These images yield lateral dimensions of roughly 1–1.3 μm and axial dimensions of 3.8–4.5 μm which is larger than the dimensions measured by the SEM. Assuming that the beam sizes across the entire metamaterial structure are relatively uniform, the individual component images could be processed to create 3D arrays that closely reflect the true feature sizes of the structure, as measured to a datum such as SEM images.

We observed that the majority of the collected fluorescence appears to originate from the residual photoinitiator 4,4′-Bis(diethylamino)benzophenone, which is a component of the TPP resin. The fluorescence spectrum of this molecule is characterized by Ladika et al.34 and has a peak emission centered around 550 nm. Our testing suggests that at common excitation wavelengths of 405 and 488 nm the photopolymers can be sufficiently excited to produce images with high (>10:1) background contrast ratios at 50–120 μW of excitation. Other strategies for imaging are likely possible such as functionalizing the surface of a clear photo resin with fluorescent particles or dyes.

The refractive index of the polymerized resin material was measured to be approximately 1.48 at a wavelength of 488 nm. This agrees with similar measurements of the same polymer.35 Given that the refractive index mismatch of the polymer and surrounding air is large and that the lattice has a complex spatial variation in refractive index, scattering becomes dominant after imaging only a few layers into the structure, limiting the achievable imaging depth. To overcome this, we envelop the structures in a droplet of mineral oil whose refractive index was selected to match that of the photopolymerized resin to mitigate scattering from the structure, thus significantly reducing scattering and enhancing the imaging depth. In general, it is expected that this technique will be applicable to other photopolymerizable resin structures assuming that the resin is largely transparent and is either autofluorescent or functionalized with fluorescent particles or dyes. For best results, these structures should be immersed in fluids whose refractive index closely matches that of the resin.

Subsequently, cross-sectional images of the structure are taken in 100 nm increments to generate a stack of images for three-dimensional reconstruction. Select and distinct confocal microscope images of the fabricated structure are directly compared to 800 nm thick slices of their solid model counterparts in Figure S1 which demonstrate the ability of this technique to adequately capture the internal features of the structure at various depths. Furthermore, we develop an open-source code that binarizes the outputs of the individual confocal images to generate a point cloud to represent the structure and then subsequently generates a standard three-dimensional output file (.obj) of the structure. A simplified diagram of the imaging processing pipeline is shown in Figure S2.

Renderings of the lattice structure are shown in Figure 3. Orthogonal (Figure 3A) and top (Figure 3B) motifs closely resemble their solid model and SEM imaging counterparts. Notably, the axial beam thickness can be varied based on the method of imaging thresholding and binarization used during reconstruction and the lateral dimensions can be adjusted via dilation. Care should be taken to ensure that an appropriate processing methodology is used to produce reasonably accurate feature sizes.

Figure 3.

Figure 3

3D Renderings. (A) Orthogonal view of the lattice structure shown in Figure 2 that is imaged via confocal microscopy and digitally rendered. (B) Top view of the rendered structure. (C) (Left) Vertical sectional views depicting internal beam structure at two locations and (Right) Horizontal cross sections depicting the corresponding confocal image.

The cross-sectional views in Figure 3C clearly discern void spaces and the arrangement of beams inside the lattice. Beyond providing a three-dimensional visual representation, series of these reconstructions during mechanical compression can provide a basis to understand the deformation behavior of these structures—even deep inside the structure. This series of reconstructions, particularly during compression, grants insights into deformation behaviors that are imperceptible to SEM and HIM.

As a demonstration, we performed a mechanical compression test on the structure at various steps between 0 and 16 μm. We first construct a specialized in situ confocal micro compression apparatus shown in Figure 4 to incrementally compress structures and image between increments. Further details on this apparatus are included in the Materials and Methods section.

Figure 4.

Figure 4

Compression apparatus and load curves. (A) Rendering of the microcompression apparatus used to study the metamaterials under loading conditions while simultaneously being imaged.

Our methodology involves successively imaging entire z-stacks that encompass the volume of the metamaterial structure before incrementally moving the indenter in 2 μm steps. Load curves from this experiment shown in Figure S3 discern loading events and highlight polymer relaxation during imaging. We should note that the incremental nature of the compression protocol does not generate a standard rate-controlled compression loading profile and thus measures periods of relaxation during imaging, wherein the structure is held at static intervals of loading. For measuring the effective Young’s modulus of a metamaterial, it may be necessary to perform rate-controlled compression tests avoiding incremental confocal imaging.

Renderings of the structure during loading increments of 2 μm, 6 μm, and 16 μm, as well as after releasing the indenter tip, are shown in Figure 5. These renderings show a clear progression of structure deformation where the beams in the upper layers first begin buckling at 2 μm (2.5% strain) of compression, before fracturing around 6 μm (7.5% strain) compression. A close look internally inside of the structure shows a chiral twisting of beams in the innermost unit cell before crumpling in proceeding loading events. This deformation is mostly confined to the second layer of unit cells from the top, and the crumple zone is best observed at the point of maximum compression (16 μm corresponding to ∼20% strain).

Figure 5.

Figure 5

In-situ compression testing. (Top) 3D renderings at various indentation steps from 2 μm (left) to 16 μm (middle right) and after releasing the indentation tip (right). Various mechanical deformations across the different loading conditions are highlighted such as the onset of buckling, and the presence of fractures and plastic strain. (Bottom) (left) vertical cross-sectional view of the rendering depicting the beams twisting at 6 μm of compression. This same phenomenon is captured in a corresponding confocal slice (middle left, blue). At higher strains, sections of the metamaterial appear to crumple, which can be observed via imaging the internal structure (middle right) and investigating the exterior deformation of the structure (right).

Upon release of the indenter, the structure decompresses freely. Areas that experienced intense deformation recover to their original geometry, with only slight residual plastic deformation. This resilience is exemplified by a specific cross-section (highlighted in purple) that, while appearing significantly crumpled at the 16 μm deformation mark, retains minimal permanent deformation postunloading (indicated in dark blue). However, individual fractures across the volume of the structure are still visible after unloading, allowing a postexperimental failure analysis.

These experiments serve as a demonstration of the utility of using confocal microscopy techniques to analyze the deformation mechanics of microscale metamaterials with feature sizes less than one micrometer. The outcomes of these studies show that it is possible to capture individual buckling and fracture events across complex lattice structures that are commonly used in the design of mechanical metamaterials. Herein, we observe that the twisting of the internal unit cells seen at 6 μm of compression explains the onset of localized crumpling across the structure at subsequent stages of compression. These insights provide valuable information and a deeper understanding of how these structures internally deform, shedding light on the overarching deformation behaviors of such materials. In many cases, direct observation of internal deformation modes of complex architected materials as well as the onset of cracks across internal beam members and joints cannot be gained in situ with conventional techniques such as SEM or HIM.

Under extreme compression, the resolution of certain regions in our three-dimensional reconstructions becomes compromised as beam spacings fall beneath the microscope’s resolution capabilities and beams start to overlap in an unpredictable manner. Despite this limitation, sequential imaging during progressive compression stages allows us to put together an understanding of the deformation of beam elements under these conditions.

As we naturally seek to scale these techniques to larger materials with similar, submicrometer feature sizes, it becomes important to recognize the necessary trade-offs in imaging field of view and resolution required. Generally, higher numerical aperture lenses which can resolve smaller feature sizes have smaller working distances, which limit the maximum height that can be observed. Drawing inspiration from recent breakthroughs in mesoscale biological imaging could inform strategies to balance these trade-offs, enabling the study of larger systems.36,37

While our experiments focus on the deformation of lattices, the same tools can also be used to study biological and hybrid systems. Recent work has demonstrated cellular scaffolds of desired shapes and sizes that can be populated by cells.3841 Labeling the cells with spectrally distinct fluorophores from the TPP structures would enable the simultaneous imaging of both the scaffolding structure and the cells and how they interact during the tissue generation process.42,43 For example, substantial active forces and deformations have been observed in 3D human microtissue models on metamaterial scaffolds.44

Our study presents a robust technique for high-resolution optical imaging of microscale metamaterials using confocal microscopy. Through our investigation of a prototypical structure measuring 80 μm × 80 μm × 80 μm, we have demonstrated the capability of this method to capture and quantify internal deformations and fractures under a mechanical load with remarkable precision. Notably, the ability to 3D visualize the progressive deformation of lattices at such fine scales is a leap forward, overcoming the limitations of traditional imaging modalities. The success of this technique in characterizing the behavior of microscale metamaterials under stress opens new avenues for its application. Beyond enabling a more insightful analysis of mechanical metamaterials, there is potential for this technique to be utilized for imaging the deformation of cellular scaffolding to understand how different biological systems respond to imposed and self-induced stresses in their environments.

Materials and Methods

A hybrid organic–inorganic resin, SZ2080 is used with Zr-DMAEMA (30 wt %) as a binder. The resin is composed of 70 wt % zirconium propoxide and 10 wt % (2-dimethylaminoethyl) methacrylate (DMAEMA) (Sigma-Aldrich). See Ovsianikov et al. for more information.45

Structures were fabricated using submicrometer resolution direct femtosecond laser writing using two-photon polymerization on SZ2080 photoresist. The setup uses a FemtoFiber Pro NIR laser, which emits 780 nm, 100 fs fwhm, pulses at 80 MHz. Polymerization of the resin is achieved with a 1.3 NA microscope objective lens (Plan-Apochromat 40 × /1.3 Oil Olympus). The laser output energy was measured before the objective lens at 6 mW. The resin sample is positioned with three axis piezo and servo stages.

We utilized a Bruker Swept-Field Confocal microscope for imaging using an excitation wavelength of 488 nm and using a 488 nm long pass filter. Images were generated of the structure at pixel resolutions of 512 × 512- and 16-bit intensity resolution. Attached to the microscope stage is our custom compression setup seen in Figure 4 that enables movement of metamaterial structures relative to the indentation tip, and the entire compression apparatus relative to the microscope objective. The indentation tip has a relatively flat (1°) angled square tip that is approximately 200 μm across that is mounted to a 0.1N load cell (Novatech F329).

The imaging sequence begins by first imaging the entire structure in 100 nm intervals with layer spacing. After the entire structure was imaged, the compression apparatus would apply a user defined strain. In our studies, the apparatus moved 2 μm increments. During this time, images were not taken. Afterward the whole structure would be imaged while remaining at constant applied strain, before compressing the structure further. This cycle repeats until the compression apparatus is released, and the postcompressed structure is image. We demonstrate the ability to image at rates exceeding 4 2D slices per second, although faster rates are possible.

Acknowledgments

B.B. acknowledges support from the NSF Graduate Research Fellowship (DGE 2146752). Support to the Laser Thermal Laboratory by the National Science Foundation under grant CMMI-2124826 is gratefully acknowledged. SEM images were taken with the Scios 2 DualBeam available at the Biomolecular Nanotechnology Center of the California Institute for Quantitative Biosciences (QB3), UC Berkeley. Confocal images were taken at the Cell and Tissue Analysis Facility at UC Berkeley with the help of QB3 CTAF staff. C.P.G. acknowledges useful discussions on imaging of TPP fabricated structures with Dr. Zacharias Vangelatos at UCB’s LTL, as well as with Drs. Maria Farsari and Giannis Zacharakis of the Institute of Electronic Structure and Laser, FORTH in Heraklion, Crete, Greece.

Data Availability Statement

Our code for rendering the confocal images is made publicly available at: https://github.com/naichenzhao/Confocal-Rendering/tree/main?fbclid=IwAR0MIdlTX0NbsaCvXUi0f1v7Nk4WsUEDBFAkT7gWLbY_CdAXAwpV7Z0MnnA

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.nanolett.3c04421.

  • CAD cross-sectional slices compared to confocal images, diagram of the image processing procedure, load curves from compression tests, axial line width measurements. (PDF)

Author Contributions

B.W.B., T.M., and N.Z. contributed equally.

The authors declare no competing financial interest.

Supplementary Material

nl3c04421_si_001.pdf (824.2KB, pdf)

References

  1. Ha C. S.; Yao D.; Xu Z.; Liu C.; Liu H.; Elkins D.; Kile M.; Deshpande V.; Kong Z.; Bauchy M.; Zheng X. (Rayne). Rapid Inverse Design of Metamaterials Based on Prescribed Mechanical Behavior through Machine Learning. Nat. Commun. 2023, 14 (1), 5765. 10.1038/s41467-023-40854-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Zeng Q.; Duan S.; Zhao Z.; Wang P.; Lei H. Inverse Design of Energy-Absorbing Metamaterials by Topology Optimization. Adv. Sci. (Weinh) 2023, 10 (4), 2204977 10.1002/advs.202204977. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Vangelatos Z.; Sheikh H. M.; Marcus P. S.; Grigoropoulos C. P.; Lopez V. Z.; Flamourakis G.; Farsari M. Strength through Defects: A Novel Bayesian Approach for the Optimization of Architected Materials. Science Advances 2021, 7 (41), eabk2218 10.1126/sciadv.abk2218. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Sheikh H. M.; Meier T.; Blankenship B.; Vangelatos Z.; Zhao N.; Marcus P. S.; Grigoropoulos C. P. Systematic Design of Cauchy Symmetric Structures through Bayesian Optimization. International Journal of Mechanical Sciences 2022, 236, 107741 10.1016/j.ijmecsci.2022.107741. [DOI] [Google Scholar]
  5. Alderete N. A.; Pathak N.; Espinosa H. D. Machine Learning Assisted Design of Shape-Programmable 3D Kirigami Metamaterials. npj Comput. Mater. 2022, 8 (1), 1–12. 10.1038/s41524-022-00873-w. [DOI] [Google Scholar]
  6. Lu C.; Hsieh M.; Huang Z.; Zhang C.; Lin Y.; Shen Q.; Chen F.; Zhang L. Architectural Design and Additive Manufacturing of Mechanical Metamaterials: A Review. Engineering 2022, 17, 44–63. 10.1016/j.eng.2021.12.023. [DOI] [Google Scholar]
  7. Jiao P.; Mueller J.; Raney J. R.; Zheng X.; Alavi A. H. Mechanical Metamaterials and Beyond. Nat. Commun. 2023, 14 (1), 6004. 10.1038/s41467-023-41679-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. do Rosário J. J.; Lilleodden E. T.; Waleczek M.; Kubrin R.; Petrov A. Yu.; Dyachenko P. N.; Sabisch J. E. C.; Nielsch K.; Huber N.; Eich M.; Schneider G. A. Self-Assembled Ultra High Strength, Ultra Stiff Mechanical Metamaterials Based on Inverse Opals. Adv. Eng. Mater. 2015, 17 (10), 1420–1424. 10.1002/adem.201500118. [DOI] [Google Scholar]
  9. Zheng X.; Lee H.; Weisgraber T. H.; Shusteff M.; DeOtte J.; Duoss E. B.; Kuntz J. D.; Biener M. M.; Ge Q.; Jackson J. A.; Kucheyev S. O.; Fang N. X.; Spadaccini C. M. Ultralight, Ultrastiff Mechanical Metamaterials. Science 2014, 344 (6190), 1373–1377. 10.1126/science.1252291. [DOI] [PubMed] [Google Scholar]
  10. Kolken H. M. A.; Zadpoor A. A. Auxetic Mechanical Metamaterials. RSC Adv. 2017, 7 (9), 5111–5129. 10.1039/C6RA27333E. [DOI] [Google Scholar]
  11. Ren X.; Das R.; Tran P.; Ngo T. D.; Xie Y. M. Auxetic Metamaterials and Structures: A Review. Smart Mater. Struct. 2018, 27 (2), 023001 10.1088/1361-665X/aaa61c. [DOI] [Google Scholar]
  12. Kolken H. M. A.; Garcia A. F.; Du Plessis A.; Rans C.; Mirzaali M. J.; Zadpoor A. A. Fatigue Performance of Auxetic Meta-Biomaterials. Acta Biomaterialia 2021, 126, 511–523. 10.1016/j.actbio.2021.03.015. [DOI] [PubMed] [Google Scholar]
  13. Qu J.; Kadic M.; Naber A.; Wegener M. Micro-Structured Two-Component 3D Metamaterials with Negative Thermal-Expansion Coefficient from Positive Constituents. Sci. Rep 2017, 7 (1), 40643 10.1038/srep40643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Jin Z.-H. A Microlattice Material with Negative or Zero Thermal Expansion. Composites Communications 2017, 6, 48–51. 10.1016/j.coco.2017.08.005. [DOI] [Google Scholar]
  15. Wang Q.; Jackson J. A.; Ge Q.; Hopkins J. B.; Spadaccini C. M.; Fang N. X. Lightweight Mechanical Metamaterials with Tunable Negative Thermal Expansion. Phys. Rev. Lett. 2016, 117 (17), 175901 10.1103/PhysRevLett.117.175901. [DOI] [PubMed] [Google Scholar]
  16. Tancogne-Dejean T.; Spierings A. B.; Mohr D. Additively-Manufactured Metallic Micro-Lattice Materials for High Specific Energy Absorption under Static and Dynamic Loading. Acta Mater. 2016, 116, 14–28. 10.1016/j.actamat.2016.05.054. [DOI] [Google Scholar]
  17. Chen Y.; Kadic M.; Wegener M. Roton-like Acoustical Dispersion Relations in 3D Metamaterials. Nat. Commun. 2021, 12 (1), 3278. 10.1038/s41467-021-23574-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Meier T.; Li R.; Mavrikos S.; Blankenship B.; Vangelatos Z.; Yildizdag M. E.; Grigoropoulos C. P. Obtaining Auxetic and Isotropic Metamaterials in Counterintuitive Design Spaces: An Automated Optimization Approach and Experimental Characterization. npj Comput. Mater. 2024, 10 (1), 1–12. 10.1038/s41524-023-01186-2. [DOI] [Google Scholar]
  19. Jonušauskas L.; Gailevičius D.; Rekštytė S.; Baldacchini T.; Juodkazis S.; Malinauskas M. Mesoscale Laser 3D Printing. Opt. Express, OE 2019, 27 (11), 15205–15221. 10.1364/OE.27.015205. [DOI] [PubMed] [Google Scholar]
  20. Geng Q.; Wang D.; Chen P.; Chen S.-C. Ultrafast Multi-Focus 3-D Nano-Fabrication Based on Two-Photon Polymerization. Nat. Commun. 2019, 10 (1), 2179. 10.1038/s41467-019-10249-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Zheng X.; Smith W.; Jackson J.; Moran B.; Cui H.; Chen D.; Ye J.; Fang N.; Rodriguez N.; Weisgraber T.; Spadaccini C. M. Multiscale Metallic Metamaterials. Nat. Mater. 2016, 15 (10), 1100–1106. 10.1038/nmat4694. [DOI] [PubMed] [Google Scholar]
  22. Balena A.; Bianco M.; Pisanello F.; De Vittorio M. Recent Advances on High-Speed and Holographic Two-Photon Direct Laser Writing. Adv. Funct. Mater. 2023, 33 (39), 2211773 10.1002/adfm.202211773. [DOI] [Google Scholar]
  23. Blankenship B. W.; Jones Z.; Zhao N.; Singh H.; Sarkar A.; Li R.; Suh E.; Chen A.; Grigoropoulos C. P.; Ajoy A. Complex Three-Dimensional Microscale Structures for Quantum Sensing Applications. Nano Lett. 2023, 23, 9272. 10.1021/acs.nanolett.3c02251. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Issa A.; Izquierdo I.; Merheb M.; Ge D.; Broussier A.; Ghabri N.; Marguet S.; Couteau C.; Bachelot R.; Jradi S. One Strategy for Nanoparticle Assembly onto 1D, 2D, and 3D Polymer Micro and Nanostructures. ACS Appl. Mater. Interfaces 2021, 13 (35), 41846–41856. 10.1021/acsami.1c03905. [DOI] [PubMed] [Google Scholar]
  25. Surjadi J. U.; Gao L.; Du H.; Li X.; Xiong X.; Fang N. X.; Lu Y. Mechanical Metamaterials and Their Engineering Applications. Adv. Eng. Mater. 2019, 21 (3), 1800864 10.1002/adem.201800864. [DOI] [Google Scholar]
  26. Hu W.; Cao X.; Zhang X.; Huang Z.; Chen Z.; Wu W.; Xi L.; Li Y.; Fang D. Deformation Mechanisms and Mechanical Performances of Architected Mechanical Metamaterials with Gyroid Topologies: Synchrotron X-Ray Radiation in-Situ Compression Experiments and 3D Image Based Finite Element Analysis. Extreme Mechanics Letters 2021, 44, 101229 10.1016/j.eml.2021.101229. [DOI] [Google Scholar]
  27. Maibohm C.; Silvestre O. F.; Borme J.; Sinou M.; Heggarty K.; Nieder J. B. Multi-Beam Two-Photon Polymerization for Fast Large Area 3D Periodic Structure Fabrication for Bioapplications. Sci. Rep 2020, 10 (1), 8740. 10.1038/s41598-020-64955-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Groß M. F.; Schneider J. L. G.; Wei Y.; Chen Y.; Kalt S.; Kadic M.; Liu X.; Hu G.; Wegener M. Tetramode Metamaterials as Phonon Polarizers. Adv. Mater. 2023, 35 (18), 2211801 10.1002/adma.202211801. [DOI] [PubMed] [Google Scholar]
  29. Zhou X.; Hou Y.; Lin J. A Review on the Processing Accuracy of Two-Photon Polymerization. AIP Advances 2015, 5 (3), 030701 10.1063/1.4916886. [DOI] [Google Scholar]
  30. Wollhofen R.; Katzmann J.; Hrelescu C.; Jacak J.; Klar T. A. 120 Nm Resolution and 55 Nm Structure Size in STED-Lithography. Opt. Express, OE 2013, 21 (9), 10831–10840. 10.1364/OE.21.010831. [DOI] [PubMed] [Google Scholar]
  31. Kim Y.; Lee E. J.; Roy S.; Sharbirin A. S.; Ranz L.-G.; Dieing T.; Kim J. Measurement of Lateral and Axial Resolution of Confocal Raman Microscope Using Dispersed Carbon Nanotubes and Suspended Graphene. Curr. Appl. Phys. 2020, 20 (1), 71–77. 10.1016/j.cap.2019.10.012. [DOI] [Google Scholar]
  32. Müller M.Introduction to Confocal Fluorescence Microscopy, Second Edition SPIE: 1000 20th Street, Bellingham, WA 98227-0010 USA, 2005, 10.1117/3.639736. [DOI] [Google Scholar]
  33. Fouquet C.; Gilles J.-F.; Heck N.; Dos Santos M.; Schwartzmann R.; Cannaya V.; Morel M.-P.; Davidson R. S.; Trembleau A.; Bolte S. Improving Axial Resolution in Confocal Microscopy with New High Refractive Index Mounting Media. PLoS One 2015, 10 (3), e0121096 10.1371/journal.pone.0121096. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Ladika D.; Noirbent G.; Dumur F.; Gigmes D.; Mourka A.; Barmparis G. D.; Farsari M.; Gray D. Synthesis and Application of Triphenylamine-Based Aldehydes as Photo-Initiators for Multi-Photon Lithography. Appl. Phys. A: Mater. Sci. Process. 2022, 128 (9), 745. 10.1007/s00339-022-05887-1. [DOI] [Google Scholar]
  35. Zukauskas A.; Bataviciute G.; Sciuka M.; Balevicius Z.; Melninkaitis A.; Malinauskas M. Effect of the Photoinitiator Presence and Exposure Conditions on Laser-Induced Damage Threshold of ORMOSIL (SZ2080). Opt. Mater. 2015, 39, 224–231. 10.1016/j.optmat.2014.11.031. [DOI] [Google Scholar]
  36. Munck S.; Cawthorne C.; Escamilla-Ayala A.; Kerstens A.; Gabarre S.; Wesencraft K.; Battistella E.; Craig R.; Reynaud E. G.; Swoger J.; McConnell G. Challenges and Advances in Optical 3D Mesoscale Imaging. J. Microsc 2022, 286 (3), 201–219. 10.1111/jmi.13109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Clough M.; Chen I. A.; Park S.-W.; Ahrens A. M.; Stirman J. N.; Smith S. L.; Chen J. L. Flexible Simultaneous Mesoscale Two-Photon Imaging of Neural Activity at High Speeds. Nat. Commun. 2021, 12 (1), 6638. 10.1038/s41467-021-26737-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Accardo A.; Blatché M.-C.; Courson R.; Loubinoux I.; Vieu C.; Malaquin L. Two-Photon Lithography and Microscopy of 3D Hydrogel Scaffolds for Neuronal Cell Growth. Biomed. Phys. Eng. Express 2018, 4 (2), 027009 10.1088/2057-1976/aaab93. [DOI] [Google Scholar]
  39. Mačiulaitis J.; Deveikytė M.; Rekštytė S.; Bratchikov M.; Darinskas A.; Šimbelytė A.; Daunoras G.; Laurinavičienė A.; Laurinavičius A.; Gudas R.; Malinauskas M.; Mačiulaitis R. Preclinical Study of SZ2080 Material 3D Microstructured Scaffolds for Cartilage Tissue Engineering Made by Femtosecond Direct Laser Writing Lithography. Biofabrication 2015, 7 (1), 015015 10.1088/1758-5090/7/1/015015. [DOI] [PubMed] [Google Scholar]
  40. Song J.; Michas C.; Chen C. S.; White A. E.; Grinstaff M. W. From Simple to Architecturally Complex Hydrogel Scaffolds for Cell and Tissue Engineering Applications: Opportunities Presented by Two-Photon Polymerization. Adv. Healthcare Mater. 2020, 9 (1), 1901217 10.1002/adhm.201901217. [DOI] [PubMed] [Google Scholar]
  41. Trautmann A.; Rüth M.; Lemke H.-D.; Walther T.; Hellmann R. Two-Photon Polymerization Based Large Scaffolds for Adhesion and Proliferation Studies of Human Primary Fibroblasts. Optics & Laser Technology 2018, 106, 474–480. 10.1016/j.optlastec.2018.05.008. [DOI] [Google Scholar]
  42. Gandikota M. C.; Pogoda K.; van Oosten A.; Engstrom T. A.; Patteson A. E.; Janmey P. A.; Schwarz J. M. Loops versus Lines and the Compression Stiffening of Cells. Soft Matter 2020, 16 (18), 4389–4406. 10.1039/C9SM01627A. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Hart N. H.; Nimphius S.; Rantalainen T.; Ireland A.; Siafarikas A.; Newton R. U. Mechanical Basis of Bone Strength: Influence of Bone Material, Bone Structure and Muscle Action. J. Musculoskelet Neuronal Interact 2017, 17 (3), 114–139. [PMC free article] [PubMed] [Google Scholar]
  44. Wang C.; Vangelatos Z.; Winston T.; Sun S.; Grigoropoulos C. P.; Ma Z. Remodeling of Architected Mesenchymal Microtissues Generated on Mechanical Metamaterials. 3D Print Addit Manuf 2022, 9 (6), 483–489. 10.1089/3dp.2021.0091. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Ovsianikov A.; Viertl J.; Chichkov B.; Oubaha M.; MacCraith B.; Sakellari I.; Giakoumaki A.; Gray D.; Vamvakaki M.; Farsari M.; Fotakis C. Ultra-Low Shrinkage Hybrid Photosensitive Material for Two-Photon Polymerization Microfabrication. ACS Nano 2008, 2 (11), 2257–2262. 10.1021/nn800451w. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

nl3c04421_si_001.pdf (824.2KB, pdf)

Data Availability Statement

Our code for rendering the confocal images is made publicly available at: https://github.com/naichenzhao/Confocal-Rendering/tree/main?fbclid=IwAR0MIdlTX0NbsaCvXUi0f1v7Nk4WsUEDBFAkT7gWLbY_CdAXAwpV7Z0MnnA


Articles from Nano Letters are provided here courtesy of American Chemical Society

RESOURCES