游 濟華

研究成果

每年研究成果 2012 2019 2021 2022 2023

• 28 Article
• 2 Chapter
• 1 Conference article
• 1 Review article

每年研究成果

每年研究成果

搜尋結果

• 2023

  A micromechanical study on the effects of precipitation on the mechanical properties of CoCrFeMnNi high entropy alloys with various annealing temperatures

  Huang, C. W., Su, P. Y., Yu, C-H., Wang, C. L., Lo, Y. C., Jang, J. S. C. & Hu, H. T., 2023 12月, 於: Scientific reports. 13, 1, 3379.

  研究成果: Article › 同行評審

  開啟存取

  • Temperature 59%
  • Chromium 33%
  • Normal Distribution 33%
  • Tensile Strength 32%
  • Particle Size 28%
  1 引文 斯高帕斯（Scopus）

• Reinforcement learning design framework for nacre-like structures optimized for pre-existing crack resistance

  Tseng, B. Y., Cai, Y. C., Conan Guo, C. W., Zhao, E. & Yu, C. H., 2023 5月 1, 於: Journal of Materials Research and Technology. 24, p. 3502-3512 11 p.

  研究成果: Article › 同行評審

  開啟存取

  • Dissipation 100%
  • Calcium Carbonate 97%
  • Reinforcement learning 91%
  • Biomaterial 78%
  • Soft materials 73%
  1 引文 斯高帕斯（Scopus）

• Ultrathin arch-like labyrinthine acoustic metasurface for low-frequency sound absorption

  Chen, J. S., Chung, Y. T., Wang, C. Y., Lo, W. Y., Liu, C. H., Yu, C. H., Chang, I. L. & Lin, T. R., 2023 1月, 於: Applied Acoustics. 202, 109142.

  研究成果: Article › 同行評審

  • arches 100%
  • sound transmission 85%
  • low frequencies 54%
  • acoustics 44%
  • printing 19%
  4 引文 斯高帕斯（Scopus）
• 2022

  3D Printing of Metal-Organic Framework-Based Ionogels: Wearable Sensors with Colorimetric and Mechanical Responses

  Pal, S., Su, Y. Z., Chen, Y. W., Yu, C. H., Kung, C. W. & Yu, S. S., 2022 6月 22, 於: ACS applied materials & interfaces. 14, 24, p. 28247-28257 11 p.

  研究成果: Article › 同行評審

  • Metal-Organic Frameworks 100%
  • Wearable sensors 76%
  • 3D printers 60%
  • Metalorganic frameworks 55%
  • Deformation (Mechanical) 42%
  14 引文 斯高帕斯（Scopus）

• ColGen: An end-to-end deep learning model to predict thermal stability of de novo collagen sequences

  Yu, C. H., Khare, E., Narayan, O. P., Parker, R., Kaplan, D. L. & Buehler, M. J., 2022 1月, 於: Journal of the Mechanical Behavior of Biomedical Materials. 125, 104921.

  研究成果: Article › 同行評審

  • Collagen 100%
  • Thermodynamic stability 77%
  • Deep learning 67%
  • Thermal Stability 49%
  • Mutation 27%
  13 引文 斯高帕斯（Scopus）

• Deep learning based design of porous graphene for enhanced mechanical resilience

  Yu, C. H., Wu, C. Y. & Buehler, M. J., 2022 4月 15, 於: Computational Materials Science. 206, 111270.

  研究成果: Article › 同行評審

  開啟存取

  • Graphene 100%
  • Resilience 92%
  • resilience 87%
  • learning 70%
  • Learning 58%
  6 引文 斯高帕斯（Scopus）

• De novo multiscale method for nonequilibrium molecular dynamics

  Yu, C. H., Chen, J. S., Hsu, Y. C. & Chen, C. S., 2022 10月, 於: Computational Materials Science. 213, 111636.

  研究成果: Article › 同行評審

  • Non-equilibrium Molecular Dynamics 100%
  • Multiscale Methods 64%
  • Molecular dynamics 56%
  • Nonequilibrium 53%
  • Atoms 51%

• Discovering design principles of collagen molecular stability using a genetic algorithm, deep learning, and experimental validation

  Khare, E., Yu, C. H., Gonzalez Obeso, C., Milazzo, M., Kaplan, D. L. & Buehler, M. J., 2022 10月 4, 於: Proceedings of the National Academy of Sciences of the United States of America. 119, 40, e2209524119.

  研究成果: Article › 同行評審

  開啟存取

  • Deep Learning 100%
  • Collagen 55%
  • Temperature 34%
  • Hydrogen Bonding 7%
  • Molecular Dynamics Simulation 6%
  7 引文 斯高帕斯（Scopus）

• End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins

  Yu, C. H., Chen, W., Chiang, Y. H., Guo, K., Martin Moldes, Z., Kaplan, D. L. & Buehler, M. J., 2022 3月 14, 於: ACS Biomaterials Science and Engineering. 8, 3, p. 1156-1165 10 p.

  研究成果: Article › 同行評審

  • Proteins 100%
  • Deep learning 97%
  • Secondary Structure 96%
  • Protein 45%
  • Biomaterials 24%
  15 引文 斯高帕斯（Scopus）

• Hierarchical Multiresolution Design of Bioinspired Structural Composites Using Progressive Reinforcement Learning

  Yu, C. H., Tseng, B. Y., Yang, Z., Tung, C. C., Zhao, E., Ren, Z. F., Yu, S. S., Chen, P. Y., Chen, C. S. & Buehler, M. J., 2022 11月, 於: Advanced Theory and Simulations. 5, 11, 2200459.

  研究成果: Article › 同行評審

  開啟存取

  • Reinforcement Learning 100%
  • Reinforcement learning 66%
  • Composite 58%
  • Design 41%
  • Composite materials 38%
  7 引文 斯高帕斯（Scopus）

• Main-chain engineering of polymer photocatalysts with hydrophilic non-conjugated segments for visible-light-driven hydrogen evolution

  Chang, C. L., Lin, W. C., Ting, L. Y., Shih, C. H., Chen, S. Y., Huang, T. F., Tateno, H., Jayakumar, J., Jao, W. Y., Tai, C. W., Chu, C. Y., Chen, C. W., Yu, C. H., Lu, Y. J., Hu, C. C., Elewa, A. M., Mochizuki, T. & Chou, H. H., 2022 12月, 於: Nature communications. 13, 1, 5460.

  研究成果: Article › 同行評審

  開啟存取

  • Hydrogen 100%
  • Conjugated Polymer 86%
  • Polymers 76%
  • engineering 63%
  • Light 61%
  10 引文 斯高帕斯（Scopus）

• Substituent engineering of the diboron molecular architecture for a nondoped and ultrathin emitting layer

  Wu, T. L., Lei, J., Hsieh, C. M., Chen, Y. K., Huang, P. Y., Lai, P. T., Chou, T. Y., Lin, W. C., Chen, W., Yu, C. H., Hsu, L. Y., Lin, H. W. & Cheng, C. H., 2022, 於: Chemical Science. 492

  研究成果: Article › 同行評審

  開啟存取

  • Delayed Fluorescence 88%
  • Molecular Shape 43%
  • Exciton 35%
  • Steric Hindrance 33%
  • Liquid Film 33%
  4 引文 斯高帕斯（Scopus）
• 2021

  A perspective on musical representations of folded protein nanostructures

  Franjou, S. L., Milazzo, M., Yu, C. H. & Buehler, M. J., 2021, 於: Nano Futures. 5, 1, 012501.

  研究成果: Article › 同行評審

  • Nanostructures 100%
  • Proteins 75%
  • proteins 65%
  • Nanomaterial 51%
  • Protein Structure 40%
  6 引文 斯高帕斯（Scopus）

• Deep learning model to predict complex stress and strain fields in hierarchical composites

  Yang, Z., Yu, C. H. & Buehler, M. J., 2021 4月 9, 於: Science Advances. 7, 15, eabd7416.

  研究成果: Article › 同行評審

  開啟存取

  • Game Theory 100%
  • Deep Learning 81%
  • Physical Functional Performance 64%
  91 引文 斯高帕斯（Scopus）

• Deep learning model to predict fracture mechanisms of graphene

  Lew, A. J., Yu, C. H., Hsu, Y. C. & Buehler, M. J., 2021 12月, 於: npj 2D Materials and Applications. 5, 1, 48.

  研究成果: Article › 同行評審

  開啟存取

  • Crystal Orientation 100%
  • learning 85%
  • Deep learning 70%
  • graphene 64%
  • Graphene 55%
  21 引文 斯高帕斯（Scopus）

• End-to-end deep learning method to predict complete strain and stress tensors for complex hierarchical composite microstructures

  Yang, Z., Yu, C. H., Guo, K. & Buehler, M. J., 2021 9月, 於: Journal of the Mechanics and Physics of Solids. 154, 104506.

  研究成果: Article › 同行評審

  開啟存取

  • stress tensors 100%
  • learning 97%
  • Tensors 89%
  • Deep learning 80%
  • Microstructure 60%
  43 引文 斯高帕斯（Scopus）

• Micromechanical study of strengthening mechanisms for Ti₆₅(AlCrNb)₃₅ medium-entropy alloy

  Yu, C. H., Huang, G. H., Huang, W. T., Huang, C. W., Lo, Y. C., Hung, Z. J., Liao, Y. C., Jang, J. S. C. & Hu, H. T., 2021 10月, 於: Intermetallics. 137, 107275.

  研究成果: Article › 同行評審

  • Crystals 100%
  • Grain Size 94%
  • Yield stress 91%
  • Yield Point 87%
  • Entropy 84%
  3 引文 斯高帕斯（Scopus）

• Tuning Mechanical Properties in Polycrystalline Solids Using a Deep Generative Framework

  Hsu, Y. C., Yu, C. H. & Buehler, M. J., 2021 4月, 於: Advanced Engineering Materials. 23, 4, 2001339.

  研究成果: Article › 同行評審

  • Polycrystalline Solid 100%
  • toughness 95%
  • tuning 84%
  • Toughness 84%
  • mechanical properties 74%
  10 引文 斯高帕斯（Scopus）
• 2020

  Sonification based de novo protein design using artificial intelligence, structure prediction, and analysis using molecular modeling

  Yu, C. H. & Buehler, M. J., 2020 3月 1, 於: APL Bioengineering. 4, 1, 016108.

  研究成果: Article › 同行評審

  開啟存取

  • Molecular modeling 100%
  • Artificial Intelligence 87%
  • Proteins 60%
  • Molecular Modeling 59%
  • Artificial intelligence 57%
  31 引文 斯高帕斯（Scopus）

• Using Deep Learning to Predict Fracture Patterns in Crystalline Solids

  Hsu, Y. C., Yu, C. H. & Buehler, M. J., 2020 7月 1, 於: Matter. 3, 1, p. 197-211 15 p.

  研究成果: Article › 同行評審

  開啟存取

  • Crystalline materials 100%
  • Shear 87%
  • Deep learning 85%
  • Simulation 60%
  • Resistance 60%
  67 引文 斯高帕斯（Scopus）
• 2019

  Artificial intelligence design algorithm for nanocomposites optimized for shear crack resistance

  Yu, C. H., Qin, Z. & Buehler, M. J., 2019 9月, 於: Nano Futures. 3, 3, 035001.

  研究成果: Article › 同行評審

  • artificial intelligence 100%
  • Nanocomposites 73%
  • Shear 63%
  • Artificial intelligence 60%
  • nanocomposites 59%
  55 引文 斯高帕斯（Scopus）

• A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence

  Yu, C. H., Qin, Z., Martin-Martinez, F. J. & Buehler, M. J., 2019, (Accepted/In press) 於: ACS nano.

  研究成果: Article › 同行評審

  • artificial intelligence 100%
  • Amino acids 82%
  • amino acids 79%
  • Amino Acid Sequence 64%
  • Proteins 63%
  73 引文 斯高帕斯（Scopus）

• Self-Folding Hybrid Graphene Skin for 3D Biosensing

  Xu, W., Paidi, S. K., Qin, Z., Huang, Q., Yu, C. H., Pagaduan, J. V., Buehler, M. J., Barman, I. & Gracias, D. H., 2019 3月 13, 於: Nano letters. 19, 3, p. 1409-1417 9 p.

  研究成果: Article › 同行評審

  • pollen 88%
  • folding 86%
  • Skin 73%
  • platforms 71%
  • graphene 69%
  45 引文 斯高帕斯（Scopus）

• Sounds interesting: can sonification help us design new proteins?

  Franjou, S. L., Milazzo, M., Yu, C. H. & Buehler, M. J., 2019 12月 2, 於: Expert Review of Proteomics. 16, 11-12, p. 875-879 5 p.

  研究成果: Article › 同行評審

  • Music 100%
  • Protein 47%
  • Proteins 42%
  • Amino Acid Sequence 26%
  • Secondary Structure 25%
  16 引文 斯高帕斯（Scopus）
• 2017

  Semi-analytical solution for the generalized absorbing boundary condition in molecular dynamics simulations

  Lee, C. S., Chen, Y. Y., Yu, C. H., Hsu, Y. C. & Chen, C. S., 2017 7月 1, 於: Computational Mechanics. 60, 1, p. 23-37 15 p.

  研究成果: Article › 同行評審

  • Molecular Dynamics Simulation 100%
  • Absorbing Boundary Conditions 86%
  • Molecular dynamics 72%
  • Crystal lattices 49%
  • Boundary conditions 49%
  2 引文 斯高帕斯（Scopus）
• 2014

  Micromechanics modeling of creep fracture of zirconium diboride-silicon carbide composites at 1400-1700°C

  Yu, C. H., Bird, M. W., Huang, C. W., Chen, C. S., Gao, Y. F., White, K. W. & Hsueh, C. H., 2014, 於: Journal of the European Ceramic Society. 34, 16, p. 4145-4155 11 p.

  研究成果: Article › 同行評審

  • Zirconium 100%
  • Micromechanics 98%
  • Creep 97%
  • Silicon carbide 85%
  • Grain Boundary 82%
  18 引文 斯高帕斯（Scopus）
• 2013

  A micromechanics study of competing mechanisms for creep fracture of zirconium diboride polycrystals

  Yu, C. H., Huang, C. W., Chen, C. S., Gao, Y. & Hsueh, C. H., 2013 9月, 於: Journal of the European Ceramic Society. 33, 10, p. 1625-1637 13 p.

  研究成果: Article › 同行評審

  • Polycrystals 100%
  • Zirconium 90%
  • Micromechanics 89%
  • Creep 88%
  • Grain Boundary 74%
  10 引文 斯高帕斯（Scopus）
• 2012

  Effects of grain boundary heterogeneities on creep fracture studied by rate-dependent cohesive model

  Yu, C. H., Huang, C. W., Chen, C. S., Gao, Y. & Hsueh, C. H., 2012 10月, 於: Engineering Fracture Mechanics. 93, p. 48-64 17 p.

  研究成果: Article › 同行評審

  • Creep 100%
  • Grain Boundary 84%
  • Grain boundaries 82%
  • Heterogeneity 75%
  • Subroutines 45%
  15 引文 斯高帕斯（Scopus）