刘晗 副研究员 - 在职教师 - 塑料高性能化加工与装备课题组
刘晗 副研究员

刘晗,四川大学高分子科学与工程学院特聘副研究员。本科和硕士均毕业于四川大学高分子科学与工程学院,2013年获得高分子材料与工程专业学士学位,2016年获得材料学专业硕士学位,师从黄光速教授,主攻高分子材料结构与性能研究。随后前往美国加州大学洛杉矶分校(UCLA)攻读博士学位,专攻机器学习与计算材料学研究,师从 Mathieu Bauchy教授,2021年获得土木与环境工程专业博士学位,期间获得电子与计算机工程专业硕士双学位(2020)。博士毕业后随即在UCLA开展博士后工作,与谷歌大脑团队合作,从事图形网络与力学超材料研究工作。2022年加入四川大学高分子科学与工程学院,任高分子材料加工工程系特聘副研究员,从事智能计算在高分子加工中的应用研究。

当前其研究方向致力于构建基于人工智能的计算材料平台,实现对材料制备结构性能应用的全过程模拟与反向设计,从而精准预测并反向调控材料制备过程,快速降低目标材料的研发周期与成本,达到高性能新材料的加速开发,并在实际应用中促进该平台理论方法学的发展。目前已累计公开发表 SCI 论文25篇,参与编写英文专著1部,其中以第一作者发表15 SCI 论文,包括Acta Materialia, ACS Nano, Materials Horizon, Journal of the Mechanics and Physics of Solids, npj Materials Degradation, Applied Physics Letter, Journal of Physics Chemistry B, Journal of Chemical Physics等知名期刊。目前以第一作者在3个不同的材料计算方向撰文发表了3SCI 综述,内容受到广泛关注和美国媒体Ceramic Tech Today专题报道。担任npj Materials Degradation, Journal of Cleaner Production, Journal of Applied Physics, Journal of Physics: Condensed Matter等知名期刊特邀审稿人。


2016 2021   美国加州大学洛杉矶分校(UCLA),土木与环境工程系,博士

2018 2020   美国加州大学洛杉矶分校(UCLA),电子与计算机工程系,双学位硕士

2013 2016   四川大学高分子科学与工程学院,材料学,硕士

2012 2014   四川大学商学院,双学位学士

2010 2013   四川大学高分子科学与工程学院,高分子材料与工程,学士

2022 − 至今   四川大学高分子科学与工程学院,特聘副研究员

2021 − 2022   美国加州大学洛杉矶分校(UCLA),博士后研究员

机器学习与计算材料学研究

通讯地址:四川省成都市一环路南一段24号高分子科学与工程学院,邮编610065

Emailhappylife@ucla.edu

个人主页:http://www.ppescu.com/show-3-21-1.html

[1]    H. Liu, Z. Zhao, Q. Zhou, R. Chen, K. Yang, Z. Wang, L. Tang, M. Bauchy. Present Challenges and Future Developments in Atomistic Modeling of Glasses: A Review. Comptes Rendus Geoscience 2022, doi.org/10.5802/crgeos.116.

 

[2]    H. Liu, S. Xiao, L. Tang, E. Bao, E. Li, C. Yang, Z. Zhao, G. Sant, M. Smedskjaer, L. Guo, M. Bauchy. Predicting the Early-Stage Creep Dynamics of Gels from Their Static Structure by Machine Learning. Acta Materialia 2021, 210, 116817.

 

[3]    H. Liu, Y. Liu, Z. Zhao, S. Schoenholz, E. Cubuk, M. Bauchy. End-to-End Differentiability and Tensor Processing Unit Computing to Accelerate Materials’ Inverse Design. Workshop on machine learning for engineering modeling, simulation and design @ NeurIPS 2020.

 

[4]    H. Liu, Y. Li, Z. Fu, K. Li, M. Bauchy. Exploring the Landscape of Buckingham Potentials for Silica by Machine Learning: Soft vs Hard Interatomic Forcefields. Journal of Chemical Physics 2020, 152, 051101.

 

[5]    H. Liu, Z. Fu, K. Yang, X. Xu, M. Bauchy. Machine Learning for Glass Science and Engineering: A Review. Journal of Non-Crystalline Solids: X 2019, 4, 100036.

 

[6]    H. Liu, T. Zhang, N. Krishnan, M. Smedskjaer, J. Ryan, S. Gin, M. Bauchy. Predicting the Dissolution Kinetics of Silicate Glasses by Topology-informed Machine Learning, npj Materials Degradation 2019, 3, 32.

 

[7]    H. Liu, L. Tang, N. Krishnan, G. Sant, M. Bauchy. Structural Percolation Controls the Precipitation Kinetics of Colloidal Calcium–Silicate–Hydrate Gels. Journal of Physics D: Applied Physics 2019, 52, 315301.

 

[8]    H. Liu, Z. Fu, Y. Li, N. Sabri, M. Bauchy. Parameterization of Empirical Forcefields for Glassy Silica Using Machine Learning. MRS Communications 2019, 9, 593.

 

[9]    H. Liu, S. Dong, L. Tang, N. Krishnan, E. Masoero, G. Sant, M. Bauchy. Long-Term Creep Deformations in Colloidal Calcium–Silicate–Hydrate Gels by Accelerated Aging Simulations. Journal of Colloid and Interface Science 2019, 542, 339.

 

[10]  H. Liu, Z. Fu, Y. Li, N. Sabri, M. Bauchy. Balance between Accuracy and Simplicity in Empirical Forcefields for Glass Modeling: Insights from Machine Learning. Journal of Non-Crystalline Solids 2019, 515, 133.

 

[11]  H. Liu, S. Dong, L. Tang, N. Krishnan, G. Sant, M. Bauchy. Effects of Polydispersity and Disorder on the Mechanical Properties of Hydrated Silicate Gels. Journal of the Mechanics and Physics of Solids 2019, 122, 555.

 

[12]  H. Liu, T. Du, N. Krishnan, H. Li, M. Bauchy. Topological Optimization of Cementitious Binders: Advances and Challenges. Cement and Concrete Composites 2019, 101, 5.

 

[13]  H. Liu, G. Huang, J. Zeng, L. Xu, X. Fu, S. Wu, J. Zheng, J. Wu. Observing Nucleation Transition in Stretched Natural Rubber through Self-seeding. Journal of Physical Chemistry B 2015, 119, 11887.

 

[14]  H. Liu, G. Huang, L. Wei, J. Zeng, X. Fu, C. Huang, J. Wu. Inhomogeneous Natural Network Promoting Strain-induced Crystallization: A Mesoscale Model of Natural Rubber. Chinese Journal of Polymer Science 2019, 37, 1142.

 

[15]  H. Liu, M. Zhou, Y. Zhou, S. Wang, G. Li, L. Jiang, Y. Dan. Aging Life Prediction System of Polymer Outdoors Constructed by ANN. 1. Lifetime Prediction for Polycarbonate. Polymer Degradation and Stability 2014, 105, 218.

 

[16]  S. Xiao, H. Liu, E. Bao, E. Li, C. Yang, Y. Tang, J. Zhou, M. Bauchy. Finding Defects in Disorder: Strain-dependent Structural Fingerprint of Plasticity in Granular Materials. Applied Physics Letters 2021, 119, 241904.

 

[17]  Tao. Du, H. Liu, L. Tang, S. Sørensen, M. Bauchy, M. Smedskjaer. Predicting Fracture Propensity in Amorphous Alumina from its Static Structure using Machine Learning. ACS Nano 2021, 15, 11, 17705–17716.

 

[18]  L. Tang, H. Liu, G. Ma, T. Du, N. Mousseau, W. Zhou, M. Bauchy. The Energy Landscape Governs Ductility in Disordered Materials. Materials Horizons 2021, 8, 1242-1252.

 

[19]  Y. Zhang, H. Liu, Z. Chen, J. W. Ju, M. Bauchy. Deconstructing Water Sorption Isotherms in Cement Pastes by Lattice Density Functional Theory Simulations. Journal of the American Ceramic Society 2021, 104, 4226-4238.

 

[20]  R. Christensen, S. Sørensen, H. Liu, K. Li, M. Bauchy, M. Smedskjaer. Interatomic Potential Parameterization Using Particle Swarm Optimization: Case Study of Glassy Silica. Journal of Chemical Physics 2021, 154, 134505.

 

[21]  L. Tang, G. Ma, H. Liu, W. Zhou, M. Bauchy. Bulk Metallic Glasses’ Response to Oscillatory Stress Is Governed by the Topography of the Energy Landscape. Journal of Physical Chemistry B 2020, 124, 11294.

 

[22]  C. Zhao, W. Zhou, Q. Zhou, Y. Zhang, H. Liu, G. Sant, X. Liu, L. Guo, M. Bauchy. Precipitation of Calcium–Alumino–Silicate–Hydrate Gels: The Role of the Internal Stress. Journal of Chemical Physics 2020, 153, 014501.

 

[23]  L. Xu, C. Huang, M. Luo, W. Qu, H. Liu, Z. Gu, L. Jing, G. Huang, J. Zheng. A Rheological Study on Non-rubber Component Networks in Natural Rubber. RSC Advances 2015, 5, 91742.

 

[24]  C. Huang, G. Huang, S. Li, M. Luo, H. Liu, X. Fu, W. Qu, Z. Xie, J. Wu. Research on Architecture and Composition of Natural Network in Natural Rubber. Polymer 2018, 154, 90.

 

[25]  J. Wu, W. Qu, G. Huang, S. Wang, C. Huang, H. Liu. Super-Resolution Fluorescence Imaging of Spatial Organization of Proteins and Lipids in Natural Rubber. Biomacromolecules 2017, 18, 1705.


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