Quantitative high-throughput measurement of bulk mechanical properties using commonly available equipment
Source abstract
Abstract
Machine learning approaches have introduced an urgent need for large datasets of materials properties. However, for mechanical properties, current high-throughput measurement methods typically require complex robotic instrumentation, with enormous capital costs that are inaccessible to most experimentalists. A quantitative high-throughput method using only common lab equipment and consumables with simple fabrication steps is long desired. Here, we present such a technique that can measure bulk mechanical properties in soft materials with a common laboratory centrifuge, multiwell plates, and microparticles. By applying a homogeneous force on the particles embedded inside samples in the multiwell plate using centrifugation, we show that our technique measures the fracture stress of gels with similar accuracy to a rheometer. However, our method has a throughput on the order of 103 samples per run and is generalizable to virtually all soft material systems. We hope that our method can expedite materials discovery and potentially inspire the future development of additional high-throughput characterization methods.
Source: europepmc · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Machine Learning in Materials Science · Nanofabrication and Lithography Techniques · Innovative Microfluidic and Catalytic Techniques Innovation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, USA
Department of Materials Science & Engineering, Northwestern University, Evanston, Illinois 60208, USA
Funding
National Science Foundation
References (40)
Show source-provided references
1. Ong · Comput. Mater. Sci. · 2019 · 161 · 14310.1016/j.commatsci.2019.01.013 ↗
2. Kim · Phys. Rev. Mater. · 2018 · 2 · 12380110.1103/PhysRevMaterials.2.123801 ↗
3. Liu · J. Materiomics · 2017 · 3 · 15910.1016/j.jmat.2017.08.002 ↗
4. Suh · Annu. Rev. Mater. Res. · 2020 · 50 · 110.1146/annurev-matsci-082019-105100 ↗
5. Moliner · Acc. Chem. Res. · 2019 · 52 · 297110.1021/acs.accounts.9b00399 ↗
6. Schmidt · npj Comput. Mater. · 2019 · 5 · 8310.1038/s41524-019-0221-0 ↗
7. Wagner · Front. Mater. · 2016 · 3 · 2810.3389/fmats.2016.00028 ↗
8. Wahl · Sci. Adv. · 2021 · 7 · eabj550510.1126/sciadv.abj5505 ↗
9. Potyrailo · ACS Comb. Sci. · 2011 · 13 · 57910.1021/co200007w ↗
10. DeStefano · JACS Au · 2021 · 1 · 155610.1021/jacsau.1c00297 ↗
11. Koinuma · Nat. Mater. · 2004 · 3 · 42910.1038/nmat1157 ↗
12. Ludwig · npj Comput. Mater. · 2019 · 5 · 7010.1038/s41524-019-0205-0 ↗
13. Kafizas · Chem. Soc. Rev. · 2012 · 41 · 73810.1039/C1CS15178A ↗
14. Ding · J. Appl. Phys. · 2012 · 111 · 11490110.1063/1.4722996 ↗
15. Stewart · Oxid. Met. · 2018 · 90 · 48510.1007/s11085-018-9849-2 ↗
16. García-Cañadas · Rev. Sci. Instrum. · 2014 · 85 · 04390610.1063/1.4871553 ↗
17. Zhang · J. Materiomics · 2017 · 3 · 20910.1016/j.jmat.2017.07.002 ↗
18. Oellers · ACS Comb. Sci. · 2020 · 22 · 14210.1021/acscombsci.9b00182 ↗
19. Zhao · MRS Bull. · 2002 · 27 · 32410.1557/mrs2002.100 ↗
20. Kim · Rev. Sci. Instrum. · 2008 · 79 · 04511210.1063/1.2912826 ↗
21. Ludwig · Meas. Sci. Technol. · 2005 · 16 · 11110.1088/0957-0233/16/1/015 ↗
22. Salzbrenner · J. Mater. Process. Technol. · 2017 · 241 · 110.1016/j.jmatprotec.2016.10.023 ↗
23. Breedveld · J. Mater. Sci. · 2003 · 38 · 446110.1023/A:1027321232318 ↗
24. Spero · Rev. Sci. Instrum. · 2008 · 79 · 08370710.1063/1.2976156 ↗
25. Cribb · Rev. Sci. Instrum. · 2015 · 86 · 02371110.1063/1.4907705 ↗
26. Joyner · APL Bioeng. · 2020 · 4 · 04150810.1063/5.0013707 ↗
27. Ding · Adv. Funct. Mater. · 2021 · 31 · 210048910.1002/adfm.202100489 ↗
28. Wang · Nano Lett. · 2013 · 13 · 282610.1021/nl401088b ↗
29. Silvaroli · ACS Appl. Mater. Interfaces · 2020 · 12 · 4412510.1021/acsami.0c11643 ↗
30. Xu · Biomacromolecules · 2020 · 21 · 21410.1021/acs.biomac.9b01132 ↗
31. Halvorsen · Biophys. J. · 2010 · 98 · L5310.1016/j.bpj.2010.03.012 ↗
32. Yang · Nat. Commun. · 2016 · 7 · 1102610.1038/ncomms11026 ↗
33. Chen · ACS Cent. Sci. · 2021 · 7 · 113510.1021/acscentsci.1c00414 ↗
34. Seitz · Macromolecules · 2007 · 40 · 121810.1021/ma061993+ ↗
35. A. C.Pipkin , Lectures on Viscoelastic Theory , Springer-Verlag , New York , 198610.1007/978-1-4612-1078-8 ↗
36. E. M.Furst and T. M.Squires , Microrheology , Oxford University Press , 201710.1093/oso/9780199655205.001.0001 ↗
37. W. M.Deen , Analysis of Transport Phenomena , Oxford University Press , 2011
38. R. M.Jones , Deformation Theory of Plasticity , Bull Ridge Publishing , 2009
39. Fakhouri · Soft Matter · 2015 · 11 · 472310.1039/C5SM00230C ↗
40. Wang · Macromolecules · 2020 · 53 · 697510.1021/acs.macromol.0c01354 ↗