Skip to main content
NCBI home page
ACS Omega logoLink to ACS Omega
. 2021 Jan 11;6(3):2121–2126. doi: 10.1021/acsomega.0c05207

Gradient-Wrinkled Microparticle with Grayscale Lithography Controlling the Cross-Linking Densities for High Security Level Anti-Counterfeiting Strategies

Cheolheon Park †, Hyung Jong Bae ‡, Jinsik Yoon †, Seo Woo Song □, Yunjin Jeong □, Kibeom Kim †, Sunghoon Kwon ‡,□,*, Wook Park †,¶,*
PMCID: PMC7841948  PMID: 33521451

Abstract

graphic file with name ao0c05207_0006.jpg

Physical unclonable functions (PUFs) enable different characteristics according to the purpose, such as easy to access identification, high security level, and high code capacity, against counterfeiting a product. However, most multiplex approaches have been implemented by embedding several security features rather than one feature. In this paper, we present a high security level anti-counterfeiting strategy using only labyrinth wrinkle patterns with different complexities, which can be used as unique and unclonable codes. To generate codes with different levels in a microtaggant, we fabricated wrinkle patterns with characteristic wavelength gradients using grayscale lithography. The elastic modulus of the polymer substrate and corresponding wavelength after the wrinkling process were controlled by designing the gray level of each subcode region in a gray-level mask image for photopolymerization of the microparticle substrate. We then verified the uniqueness of the extracted minutia codes through a cross-correlation analysis. Finally, we demonstrated the authentication strategies by decoding different minutia codes according to the scanning resolution during the decoding. Overall, the presented patterning method can be widely used in security code generation.

1. Introduction

Encoded microparticles have been fabricated for various applications, including cell carriers,1,2 multiplex bioassay platforms,3−8 and anti-counterfeiting strategies.9−13 Among the various nondeterministic encoding methods, including physical unclonable functions (PUFs),14,15 wrinkling is valuable where a large code capacity is required or for security purposes because a myriad of irreproducible topographical codes can be generated in a high-throughput manner. In our previous study, we utilized a labyrinth wrinkle pattern with a homogeneous ridge periodicity (characteristic wavelength) throughout the microparticle for an unclonable code.12

For anti-counterfeiting methods, several security features are generally introduced on a single product because one authentication layer is vulnerable to an attack as counterfeiting techniques become more sophisticated.16 In addition, a one-layer system cannot simultaneously perform simple identification and powerful authentication because of the trade-off between the security level and code readability. Consequently, multiplex approaches are universal to satisfy various authentication requirements for given purposes in the markets. For example, a banknote has more than 10 features, including a holographic image and watermark for overt authentication and fluorescence fibers for covert authentication. However, these approaches require different encoding mechanisms or mixing of different materials, which increases the production cost or complexity of the decoding system. Therefore, a gradient-wrinkled microparticle with one security feature is more effective for application to the actual market.

To achieve high security level anti-counterfeiting on a single microtaggant using only wrinkles, wrinkle patterns with different complexities need to be created so that users can read different codes according to the resolution of the decoding optic system. For example, a higher security level code with a wavelength of a few microns requires a higher resolution of the reading system, such as a confocal laser scanning microscope with a low scanning speed. As the code complexity or security level is determined by the wavelength, it is necessary to generate several wrinkle patterns with different characteristic wavelengths in a single taggant.

To fabricate heterogeneous random wrinkle patterns in a single structure, the elastic modulus of the substrate or film thickness in the structure must be designed differently because the wavelength of the wrinkle pattern in a bilayer structure is determined by

1. 1

where Es and Ef are the elastic moduli of the substrate and film, respectively, vs and vf are Poisson’s ratios of the substrate and film, respectively, and t is the thickness of the film.17,18 Various fabrication techniques for simultaneous patterning of wrinkles with different periodicities have been developed by utilizing geometric gradients,19−22 film thickness gradients,23 elastic modulus gradients,24−26 or both thickness and modulus gradients.27 However, these methods are inappropriate for the fabrication of numerous microparticles encoded with different wrinkle gradients because (i) the realization of a certain wavelength in a certain location is challenging owing to the geometric gradient or film thickness gradient and (ii) repetitive modification processes are required to fabricate heterogeneous patterns using the modulus gradient.

2. Materials and Methods

2.1. Silica-Coating Process for Formation of Gradient-Wrinkled Microparticles

In this paper, we present a designable and scalable patterning method with gradient wrinkles for a novel high security level anti-counterfeiting strategy using random wrinkles by controlling the elastic modulus of a substrate using grayscale lithography. The microparticles with inhomogeneous wrinkle patterns were fabricated using a grayscale optofluidic maskless lithography system27 and subsequent wrinkling process.12 We generated wrinkle patterns with wavelength gradients in a single microparticle using a gray-level mask image that divided the particle into an array of subcode regions with gray levels in the range of 95–255 (distance between gray levels: 8) (Figure 1a). The height of each subcode region in the gradient-wrinkled microparticle was synthesized differently according to the gray level chosen for the region, and 15 gray levels, for example, 239–255, can be captured at a time at a specific focal height. The gray-level mask was designed to allow for decoding at a single focal height, allowing for at most 15 gray levels to be used within the same microparticle. The particles were produced using wavelengths for each of the gray levels, as shown in Figure 1d, to create the range of 21 possible gray levels, ranging from 95 to 255, each being eight gray-level units apart. The grayscale colors were converted from a decimal code (Figure 1b). For the microparticle synthesis, we prepared a photocurable prepolymer mixture consisting of ethoxylated trimethylolpropane triacrylate and 3-(trimethoxysilyl)propyl acrylate. Using grayscale lithography, the intensity of ultraviolet (UV) light reflected from a digital micromirror device was controlled according to the gray level of the loaded gray-level mask image (Figure 1c,d). The number of particles that can be silica-coated at a time, with a TEOS reaction time of 160 min, was about 5000, and photolithography took about 1 h to manufacture 5000 particles. Consequently, we can simultaneously expose a single microstructure to several UV intensities during photopolymerization, which enables the control of the cross-linking density of the synthesized polymeric microparticles in specific regions. After the synthesis of the polymeric microparticles, patterned with different elastic moduli, they were incubated in an aqueous solution for a silica-coating process with tetraethyl orthosilicate (Figure 1b). A thin silica layer was formed on the surface of the polymeric microparticles, yielding a core–shell-type microstructure. By drying these silica-coated microparticles immersed in the solution, wrinkle patterns were generated on the microparticle surface due to the mismatched strain between the core and shell layers during shrinking (Figure 1c). The silica-coated microparticles consist of a shell formed from silica and a core synthesized from monomers. Since silica is relatively more rigid than the synthesized monomers, there is a mismatched strain between the core and the shell during shrinkage. The shell cannot shrink much due to its lower elasticity relative to the core. By applying this to eq 1, the UV power changes as the gray level changes, and the values of Es and the wavelength are changed. In this wrinkling process, the characteristic wavelength of the wrinkle pattern was determined by the elastic moduli of the core (Es) and shell (Ef) and the shell thickness (t), as shown in eq 1. Es can be controlled by changing the cross-linking density with the UV intensity during photopolymerization, while t can be controlled by changing the silica-coating conditions. Consequently, under the same silica-coating conditions, various wavelengths could be easily generated within each subcode region based on the gray level and corresponding Es, all in a single fabrication process, which was quite desirable in previously developed control techniques using geometric, thickness, or modulus gradients.

Figure 1.

Figure 1

Open in a new tab

Gradient wrinkle patterned microparticle by grayscale lithography. (a) Schematic of grayscale lithography. Polymeric microparticles were synthesized by reflecting UV light through a gray-level mask image with a gradient gray level. (b) Grayscale color creator from a decimal code. (c) Schematic of the UV power of the different grayscale colors from the gray-level mask image, and the heights of the bars are digitalized by the UV power. (d) UV powers by the gray level from the mask image. (e) Schematic of the wrinkling process. After the synthesized polymeric microparticles were coated with silica, they were dried to generate surface wrinkles by shrinking, (i) silica coating process, (ii) drying, (iii) wrinkling after drying, and (iv) changes of the polymeric layer during wrinkle formation. (f) Confocal laser scanning microscopy image of a fabricated gradient-wrinkled microparticle with 20 different levels (scale bar: 200 μm).

2.2. Array of Gradient-Wrinkled Microparticles with Grayscale Lithography

We then quantitatively analyzed the fabricated gradient wrinkles in terms of both the wavelength and minutia (ridge ending or ridge bifurcation point) density to verify code control mechanisms based on the gray level. By fabricating four subcode regions with different gray levels in each microparticle, we covered 20 levels between 103 and 255, with five types of microparticles (Figure 2a–e). We used the same particle synthesis (UV power: 80 mW/cm2; 0.2 s illumination with a 20× objective lens (numerical aperture: 0.45, Olympus)) and silica-coating conditions for this experiment.12 After imaging of these wrinkled microparticles using CLSM, we extracted the wavelength values in each code region using a fast Fourier transform analysis. Overall, the wavelength exhibited an inversely proportional relationship with the gray level (Figure 2f) because Es decreased with the decrease in the gray level, while the corresponding wavelength increased, as shown in eq 1. The wavelength maintained similar values in the upper two levels (Figure 2a) because the polymer monomers were fully cross-linked with the corresponding gray levels. In contrast, the patterns were incomplete in the lower two levels (Figure 2e) because the UV doses were not sufficient to polymerize the monomers. We also utilized the distribution of minutiae as a code in this chaotic wrinkle pattern and verified that the minutia density was proportional to the gray level (Figure 2f). Consequently, we could control the code complexity in each subcode region by changing the gray level because the minutia density determines the complexity.

Figure 2.

Figure 2

Open in a new tab

Control of the wavelength codes. (a–e) Representative CLSM images of the wrinkled microparticles containing four subcode regions with different gray levels (scale bar: 100 μm). The subcode regions covered gray levels in the range of 103–255 in eight intervals. (f) Distribution of the wavelength and minutia density according to the gray level. Each bar and error bar represent the average and standard deviation, obtained from 5, 7, 10, 5, and 5 samples for panels (a–e), respectively.

3. Results and Discussion

3.1. Decoding and Correlation with 30 Subcodes

Finally, we demonstrate the decoding of the minutia code using three types of encoded microparticles with different gray-level distributions (Figure 3a). As shown in Figure 3b, we extracted minutia information in each subcode region after processing of the CLSM images. The subcodes were then merged into a single code with the same position as the gray-level array shown in the mask image in Figure 3c. Using this processed code information, we performed a cross-correlation analysis to verify the uniqueness of the code. For this purpose, we transformed the merged minutia position information into a binary matrix in each encoded microparticle and calculated the cross-correlation values between matrices.12 The particle analysis using CLMS-based imaging takes about 7 s per image when processed in the environment of an Intel Core i3-1005G1 processor (1.20 up to 3.40 GHz 4 MB L3 Cache). The correlation values were obtained from a total of 30 microparticle samples, 10 samples in each group. The heat map in Figure 3c shows that intercorrelation values (correlations among different microparticles; mean value: 0.12) were distinguished from intracorrelation values (correlations between the same microparticle). This verifies that the four subcodes had different codes, although they were represented as one encoded microparticle. Thus, we can use a merged minutia code as a unique identification.

Figure 3.

Figure 3

Open in a new tab

Decoding of minutia codes. (a) Designed gray-level mask images. (b) Extraction of minutia distributions from subcode regions. The left and right images are representative images of groups 2 and 3, respectively. The green and red points represent ridge ending and bifurcation points, respectively. Only the region corresponding to 60% of the entire subcode area was used as a code to minimize the undesired edge effect on the code region (scale bar: 100 μm). (c) Heat map of the cross-correlation values of the merged minutia codes. The correlation values were averaged after separately calculating those for the ridge ending and bifurcation points.

3.2. Single Gradient-Wrinkled Microparticle that has Two Security Codes for High Security Level Anti-Counterfeiting

The random wrinkle pattern with homogeneous periodicity cannot achieve both high security level and simple decoding because of the trade-off between the security level and readability. For example, a high security level code with a wavelength of a few microns requires a higher resolution reading system, such as CLSM, with a low scanning speed. This enables the simultaneous generation of different codes in a single encoding process and reading of these codes using a microscope with different resolutions, which provides an efficient encoding and decoding of multiple codes without additional processes.

We fabricated a gradient wrinkling pattern onto a single microparticle, which can be precisely decoded at a specific focal height (Figure 4). Despite the use of the same particle, the decoding results can be changed by refocusing CLSM. As the height of the particles produced through grayscale lithography varies, the optimal focal height for decoding each area varies according to the gray level of the illuminated UV, even after the generation of wrinkles. Thus, unintended minutia codes can appear at any focal length among the detectable focal heights of gradient wrinkling patterns in a particle. The minutia code extracted without knowing the initial information is different from the intended minutia code, which is decoded by extracting all areas of information at a specific focal height (Figure 4b,d). It is challenging to evaluate the type of initial information to attempt replication. Thus, the gradient wrinkling microparticles can be used as a PUF for the high security level anti-counterfeiting strategy.

Figure 4.

Figure 4

Open in a new tab

(a) Multiple-wrinkled particle observed by CLSM with a low resolution (256 × 256) (scale bar: 50 μm). (b) Minutiae at two low gray-level regions. (c) Multiple-wrinkled particle observed by CLSM with a high resolution (1024 × 1024). (d) Minutiae at all gray-level regions.

4. Conclusions

In summary, we developed a microtaggant with a high security level anti-counterfeiting strategy using gradient wrinkling based on grayscale lithography. We controlled the wavelength of the wrinkle patterns by changing the gray level in the gray-level mask image. For demonstration, we created microparticles having subcodes with different wavelength combinations. We then verified that the minutia code generated by merging minutia distributions extracted from each subcode region could be used as a unique code. Finally, by designing a mixture of wrinkle patterns with a large wavelength difference, we generated different codes in a single microstructure, according to the resolution of the reading microscope. Ultimately, we can provide a high security level anti-counterfeiting strategy enabling a simple, powerful authentication in a single anti-counterfeiting taggant, without additional fabrication processes, by sharing the encoding system. Moreover, using the developed encoding method, other encryption approaches can also be utilized to further increase the security level, which will be investigated in a future study.

Acknowledgments

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2018R1A6A1A03025708). This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health and Welfare, Republic of Korea (grant number: HI20C0068). This research was supported by the Global Research Development Center Program through the NRF funded by the Ministry of Science and ICT (MSIT) (2015K1A4A3047345). This work was supported by the Brain Korea 21 Plus Project in 2020. This work was supported by the Ministry of Science and ICT(MSIT) of the Republic of Korea and the National Research Foundation of Korea (NRF-2020R1A3B3079653).

Author Contributions

§ C.P. and H.J.B. contributed equally to this study. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

The authors declare no competing financial interest.

References

  1. Liu W.; Shang L.; Zheng F.; Lu J.; Qian J.; Zhao Y.; Gu Z. Photonic Crystal Encoded Microcarriers for Biomaterial Evaluation. Small 2014, 10, 88–93. 10.1002/smll.201301253. [DOI] [PubMed] [Google Scholar]
  2. Fayazpour F.; Lucas B.; Vandenbroucke R. E.; Derveaux S.; Tavernier J.; Lievens S.; Demeester J.; De Smedt S. C. Evaluation of Digitally Encoded Layer-by-Layer Coated Microparticles as Cell Carriers. Adv. Funct. Mater. 2008, 18, 2716–2723. 10.1002/adfm.200800255. [DOI] [Google Scholar]
  3. Lee H.; Kim J.; Kim H.; Kim J.; Kwon S. Colour-Barcoded Magnetic Microparticles for Multiplexed Bioassays. Nat. Mater. 2010, 745–749. 10.1038/nmat2815. [DOI] [PubMed] [Google Scholar]
  4. Appleyard D. C.; Chapin S. C.; Doyle P. S. Multiplexed Protein Quantification with Barcoded Hydrogel Microparticles. Anal. Chem. 2011, 83, 193–199. 10.1021/ac1022343. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Clarke L. I.; Horinek D.; Michl J.; Gavina P.; Sauvage J. P.; Osgood A. J.; Zhao Y. M.; Kelly K. F.; Tour J. M.; Credi A.; Raymo F. M.; Stoddart J. F.; de Silva H.; Silva R. A.; Costantini G.; Kern K.; Kamna M. M.; Weiss P. S.; Oxtoby N. S.; Phillips M. A.; Champness N. R.; Beton P. H.; Giovannini M.; Bromann K.; Kern K.; Weiss P. S.; Schlatterbeck D.; Christmann K.; Hafner J.; Wang Y.; Teter M.; Allan D.; Arias T.; Joannopoulos J.; Rose M. K.; Fomin E.; Ogletree D. F.; Salmeron M.; Witte G.; Woll C.; Wong K. L.; Kwon K. Y.; Bartels L.; Lutz C. P.; Gupta J. A.; Eigler D. M.. Multifunctional Encoded Particles for High-Throughput. 2007, 2 (), 1393–1397, 10.1126/science.1134929. [DOI] [Google Scholar]
  6. Chung S. E.; Kim J.; Oh D. Y.; Song Y.; Lee S. H.; Min S.; Kwon S. One-Step Pipetting and Assembly of Encoded Chemical-Laden Microparticles for High-Throughput Multiplexed Bioassays. Nat. Commun. 2014, 5, 1–12. 10.1038/ncomms4468. [DOI] [PubMed] [Google Scholar]
  7. Kim L. N.; Kim M.; Jung K.; Bae H. J.; Jang J.; Jung Y.; Kim J.; Kwon S. Shape-Encoded Silica Microparticles for Multiplexed Bioassays. Chem. Commun. 2015, 51, 12130–12133. 10.1039/c5cc02048d. [DOI] [PubMed] [Google Scholar]
  8. Destgeer G.; Ouyang M.; Wu C. Y.; Di Carlo D. Fabrication of 3D Concentric Amphiphilic Microparticles to Form Uniform Nanoliter Reaction Volumes for Amplified Affinity Assays. Lab Chip 2020, 20, 3503–3514. 10.1039/d0lc00698j. [DOI] [PubMed] [Google Scholar]
  9. Braeckmans K.; De Smedt S. C.; Roelant C.; Leblans M.; Pauwels R.; Demeester J. Encoding Microcarriers by Spatial Selective Photobleaching. Nat. Mater. 2003, 169–173. 10.1038/nmat828. [DOI] [PubMed] [Google Scholar]
  10. Han S.; Bae H. J.; Kim J.; Shin S.; Choi S. E.; Lee S. H.; Kwon S.; Park W. Lithographically Encoded Polymer Microtaggant Using High-Capacity and Error-Correctable QR Code for Anti-Counterfeiting of Drugs. Adv. Mater. 2012, 24, 5924–5929. 10.1002/adma.201201486. [DOI] [PubMed] [Google Scholar]
  11. Lee J.; Bisso P. W.; Srinivas R. L.; Kim J. J.; Swiston A. J.; Doyle P. S. Universal Process-Inert Encoding Architecture for Polymer Microparticles. Nat. Mater. 2014, 13, 524–529. 10.1038/nmat3938. [DOI] [PubMed] [Google Scholar]
  12. Bae H. J.; Bae S.; Park C.; Han S.; Kim J.; Kim L. N.; Kim K.; Song S. H.; Park W.; Kwon S. Biomimetic Microfingerprints for Anti-Counterfeiting Strategies. Adv. Mater. 2015, 27, 2083–2089. 10.1002/adma.201405483. [DOI] [PubMed] [Google Scholar]
  13. Bae H. J.; Bae S.; Yoon J.; Park C.; Kim K.; Kwon S.; Park W. Self-Organization of Maze-like Structures via Guided Wrinkling. Sci. Adv. 2017, 3, e1700071. 10.1126/sciadv.1700071. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Caruthers J. M.; Mckay D. B.; Opin C.; Biol S.; Pappu R.; Recht B.; Taylor J.; Gershenfeld N. Physical One-Way Functions 2002, 297, 2026–2031. [DOI] [PubMed] [Google Scholar]
  15. Kim J.; Yun J. M.; Jung J.; Song H.; Kim J. B.; Ihee H. Anti-Counterfeit Nanoscale Fingerprints Based on Randomly Distributed Nanowires. Nanotechnology 2014, 25, 155303. 10.1088/0957-4484/25/15/155303. [DOI] [PubMed] [Google Scholar]
  16. Li L. Technology Designed to Combat Fakes in the Global Supply Chain. Bus. Horiz. 2013, 56, 167–177. 10.1016/j.bushor.2012.11.010. [DOI] [Google Scholar]
  17. Mosca M. Spontaneous Formation of Ordered Structures in Thin. 1998, 393, 0–3. [Google Scholar]
  18. Genzer J.; Groenewold J. Soft Matter with Hard Skin: From Skin Wrinkles to Templating and Material Characterization. Soft Matter 2006, 2, 310. 10.1039/b516741h. [DOI] [PubMed] [Google Scholar]
  19. Langley K. R.; Sharp J. S. Microtextured Surfaces with Gradient Wetting Properties. Langmuir 2010, 26, 18349–18356. 10.1021/la1036212. [DOI] [PubMed] [Google Scholar]
  20. Raayai-Ardakani S.; Yague J. L.; Gleason K. K.; Boyce M. C. Mechanics of Graded Wrinkling. J. Appl. Mech. Trans. ASME 2016, 83, 1–10. 10.1115/1.4034829. [DOI] [Google Scholar]
  21. Yu S.; Sun Y.; Ni Y.; Zhang X.; Zhou H. Controlled Formation of Surface Patterns in Metal Films Deposited on Elasticity-Gradient PDMS Substrates. ACS Appl. Mater. Interfaces 2016, 8, 5706–5714. 10.1021/acsami.5b12369. [DOI] [PubMed] [Google Scholar]
  22. Parihar V.; Bandyopadhyay S.; Das S.; Mukherjee R.; Chakraborty S.; Dasgupta S. Tailored Topography: A Novel Fabrication Technique Using an Elasticity Gradient. Soft Matter 2018, 14, 7034–7044. 10.1039/c8sm01054d. [DOI] [PubMed] [Google Scholar]
  23. Stafford C. M.; Harrison C.; Beers K. L.; Karim A.; Amis E. J.; Vanlandingham M. R.; Kim H. C.; Volksen W.; Miller R. D.; Simonyi E. E. A Buckling-Based Metrology for Measuring the Elastic Moduli of Polymeric Thin Films. Nat. Mater. 2004, 545–550. 10.1038/nmat1175. [DOI] [PubMed] [Google Scholar]
  24. Wilder E. A.; Guo S.; Lin-Gibson S.; Fasolka M. J.; Stafford C. M. Measuring the Modulus of Soft Polymer Networks via a Buckling-Based Metrology. Macromolecules 2006, 39, 4138–4143. 10.1021/ma060266b. [DOI] [Google Scholar]
  25. Claussen K. U.; Tebbe M.; Giesa R.; Schweikart A.; Fery A.; Schmidt H. W. Towards Tailored Topography: Facile Preparation of Surface-Wrinkled Gradient Poly(Dimethyl Siloxane) with Continuously Changing Wavelength. RSC Adv. 2012, 2, 10185. 10.1039/c2ra21859c. [DOI] [Google Scholar]
  26. Hiltl S.; Oltmanns J.; Böker A. A One-Step Screening Process for Optimal Alignment of (Soft) Colloidal Particles. Nanoscale 2012, 4, 7338–7345. 10.1039/c2nr32710d. [DOI] [PubMed] [Google Scholar]
  27. Ma S. J.; Mannino S. J.; Wagner N. J.; Kloxin C. J. Photodirected Formation and Control of Wrinkles on a Thiol-Ene Elastomer. ACS Macro Lett. 2013, 2, 474–477. 10.1021/mz400166e. [DOI] [PubMed] [Google Scholar]

Articles from ACS Omega are provided here courtesy of American Chemical Society

RESOURCES