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  1. C-T Chen and GX Gu, Physics‐Informed Deep‐Learning For Elasticity: Forward, Inverse, and Mixed Problems, Advanced Science, 2023, 2300439
    PDFDOI: 10.1002/advs.202300439

  2. Z Chen, T Zhang, C-T Chen, S Yang, Z Lv, L Cao, J Ren, Z Shao, L-B Jiang, S Ling, Mechanically and electrically biocompatible hydrogel ionotronic fibers for fabricating structurally stable implants and enabling noncontact physioelectrical modulation, Materials Horizons, 2022, 9, 1735-1749
    [PDF] DOI: 10.1039/D2MH00296E

  3. C-T Chen and GX Gu, Learning hidden elasticity with deep neural networks, 
    Proceedings of the National Academy of Sciences, 2021, 118, 21

    [PDF] DOI: 10.1073/pnas.2102721118

  4. T Shu, Z Lv, C‐T Chen, GX Gu, J Ren, L Cao, Y Pei, S Ling, DL Kaplan, Mechanical training-driven structural remodeling: a rational route for outstanding highly hydrated silk materials, Small, 2021, 2102660
    [PDF] DOI: 10.1002/smll.202102660

  5. C-T Chen, DC Chrzan, GX Gu, Nano-topology optimization for materials design with atom-by-atom control, Nature Communications, 2020, 11, 3745
    [PDF] DOI: 10.1038/s41467-020-17570-1
    Behind the paper article on Nature Research Device & Materials Engineering Community

  6. C-T Chen and GX Gu, Generative deep neural networks for inverse materials design using backpropagation and active learning, Advanced Science, 2020, 1902607
    [PDFDOI: 10.1002/advs.201902607

  7. C-T Chen and GX Gu, Effect of constituent materials on composite performance: exploring design strategies via machine learning, Advanced Theory and Simulations, 2019, 2: 1900056
    [PDFDOI: 10.1002/adts.201900056
    Featured article on the front cover of Adv. Theory Simul. 6/2019

  8. C-T Chen and GX Gu, Machine learning for composite materials, MRS Communications, 2019, 9(2), 556-566
    [PDFDOI: 10.1557/mrc.2019.32
    Received MRS Communications Lecture Award 2020

  9. TL Williams, SL Senft, J Yeo, FJ Martín-Martínez, AM Kuzirian, CA Martin, CW DiBona, C-T Chen, SR Dinneen, HT Nguyen, CM Gomes, JJC Rosenthal, MD MacManes, F Chu, MJ Buehler, RT Hanlon, LF Deravi, Dynamic pigmentary and structural coloration within cephalopod chromatophore organs, Nature Communications, 2019, 10, 1004
    [PDFDOI: 10.1038/s41467-019-08891-x

  10. R Devarapalli, SB Kadambi, C-T Chen, GR Krishna, B Kammari, MJ Buehler, U Ramamurty, CM Reddy, Remarkably distinct mechanical flexibility in three structurally similar semiconducting organic crystals studied by nanoindentation and molecular dynamics, Chemistry of Materials, 2019, 31 (4), 1391–1402
    [PDFDOI: 10.1021/acs.chemmater.8b04800

  11. C-T Chen and MJ Buehler, Polydopamine and eumelanin models in various oxidation states, Physical Chemistry Chemical Physics, 2018, 20 (44), 28135-28143
    [PDFDOI: 10.1039/C8CP05037F

  12. GX Gu, C-T Chen, DJ Richmond, MJ Buehler, Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment, Materials Horizons, 2018, 5, 939-945
    [PDFDOI: 10.1039/C8MH00653A
    Received Materials Horizons Outstanding Paper 2018

  13. GX Gu, C-T Chen, MJ Buehler, De novo composite design based on machine learning algorithm, Extreme Mechanics Letter, 2018, 18, 19-28
    [PDFDOI: 10.1016/j.eml.2017.10.001

  14. W Xu, Z Qin, C-T Chen, HR Kwag, Q Ma, A Sarkar, MJ Buehler, DH Gracias, Ultrathin thermoresponsive self-folding 3D graphene, Science Advances, 2017, 3 (10), e1701084
    [PDFDOI: 10.1126/sciadv.1701084

  15. C-T Chen, FJ Martin-Martinez, S Ling, Z Qin, MJ Buehler, Nacre-inspired design of graphene oxide–polydopamine nanocomposites for enhanced mechanical properties and multi-functionalities, Nano Futures, 2017, 1 (1), 011003
    [PDFDOI: 10.1088/2399-1984/aa6aed 

  16. C-T Chen, FJ Martin-Martinez, GS Jung, MJ Buehler, Polydopamine and eumelanin molecular structures investigated with ab initio calculations, Chemical Science, 2017, 8 (2), 1631-1641

    [PDFDOI: 10.1039/C6SC04692D
    Top 5% of highly cited papers in the RSC General chemistry portfolio of journals

  17. C-T Chen, Eumelanin and polydopamine: self-assembly, structure, and properties (Doctoral dissertation), Massachusetts Institute of Technology, 2016

  18. M d’Ischia, A Napolitano, V Ball, C-T Chen, MJ Buehler, Polydopamine and eumelanin: from structure-property relationships to a unified tailoring strategy, 
    Accounts of Chemical Research, 2014, 47 (12), 3541-3550

    [PDFDOI: 10.1021/ar500273y

  19. C-T Chen, C Chuang, J Cao, V Ball, D Ruch, MJ Buehler, Excitonic effects from geometric order and disorder explain broadband optical absorption in eumelanin, Nature Communications, 2014, 5, 3859

    Featured article on MIT News

  20. C-T Chen, S Ghosh, CM Reddy, MJ Buehler, Molecular mechanics of elastic and bendable caffeine co-crystals, Physical Chemistry Chemical Physics, 2014, 16 (26),

    [PDFDOI: 10.1039/C3CP55117B

  21. S Lin, C-T Chen, I Bdikin, V Ball, J Grácio, MJ Buehler, Tuning heterogeneous polydopamine structures and mechanics: in silico covalent cross-linking and thin film nanoindentation, Soft Matter, 2014, 10 (3), 457-464

    [PDFDOI: 10.1039/C3SM51810H

  22. C-T Chen, V Ball, JJ de Almeida Gracio, MK Singh, V Toniazzo, D Ruch, MJ Buehler, Self-assembly of tetramers of 5, 6-dihydroxyindole explains the primary physical properties of eumelanin: experiment, simulation, and design, ACS Nano, 2013, 7 (2), 1524-1532

    [PDFDOI: 10.1021/nn305305d

  23. Y-B Yang, C-T Chen, K-C Chang, On applicability of Hilbert–Huang transform for vibration analysis of a two-member truss, The IES Journal Part A: Civil & Structural Engineering, 2012, 5 (2), 67-78

    [PDFDOI: 10.1080/19373260.2012.663464

  24. Y-B Yang, C-T Chen, T-J Lin, C-R Hung, Consistent virtual work approach for the nonlinear and postbuckling analysis of steel frames under thermal and mechanical loadings, Engineering Structures, 2011, 33 (6), 1870-1882
    [PDFDOI: 10.1016/j.engstruct.2011.02.005

  25. C-T Chen, Application of HHT Techniques to Nonlinear Dynamic Analysis of Trusses
    (Master's thesis), 
    National Taiwan University, 2009


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