　　Han Liu, 　　Associate Professor - Professors/Staff - Processing and Equipmen for Advanced Plastics Group

Personal profile Educational experience Work experience Research areas Contact Representative papers

Han LIU is a materials physicist who is combining computational simulations and machine learning techniques to accelerate materials’ inverse designs for wide-range engineering applications. He obtained his Ph.D. from the Department of Civil and Environmental Engineering at University of California, Los Angeles (UCLA) in 2021, and concurrently obtained a master’s degree from the Department of Electrical and Computer Engineering at UCLA in 2020. Prior to UCLA, he obtained his bachelor’s and master’s degrees from the College of Polymer Science and Engineering at Sichuan University (SCU, CHINA) in 2013 and 2016, respectively. Since 2022, he works as an Associate Professor in the Department of Polymer Processing Engineering at Sichuan University (SCU, CHINA). Prior to the faculty of SCU, he worked as a Postdoctoral Associate in Physics of AmoRphous and Inorganic Solids Laboratory (PARIS Lab) at UCLA.

His researches combine computational simulations and machine learning to accelerate the design of disordered materials, including glassy materials, porous materials, and mechanical metamaterials. So far, he has published 25 scientific papers, including 15 first-author publications. His present research interest lies in the intersection between machine learning and computational materials. By developing the cutting-edge techniques and theories of artificial intelligence (AI), he systematically investigates the AI-computing methodologies for materials modeling and inverse design and, ultimately, aims to build an advanced AI-computing platform for polymer processing (and materials design in general).

2017–2021 Ph.D.: Civil Engineering, University of California, Los Angeles (UCLA)

Department of Civil & Environmental Engineering

2018 – 2020 M.S.: Electrical Engineering, UCLA

Department of Electrical & Computer Engineering

2016 – 2017 Enrolled Ph.D. Student: Materials Science and Engineering, UCLA

Department of Materials Science & Engineering

2013 – 2016 M.S.: Materials Science, Sichuan University

College of Polymer Science and Engineering

2012 – 2014 B.S.: Business Administration, Sichuan University

Business school

2011 – 2013 B.S.: Polymer Materials and Engineering, Sichuan University

College of Polymer Science and Engineering & Polymer Research Institute

2010 – 2011 Enrolled Undergraduate: Chemical Engineering and Technology, Sichuan University

College of Chemical Engineering

● GPA Ranking 1/220, National Scholarship Winner (top 1%)

2022-Present College of Polymer Science and Engineering, Sichuan University

Associate Professor

2021-2022 University of California, Los Angeles (UCLA)

Postdoctoral Associate

Machine learning and computational materials

Address: College of Polymer Science and Engineering, Sichuan University (Wangjiang campus)

No.24 South Section 1, Yihuan Road,

Chengdu, China, 610065

Email: happylife@ucla.edu

Website: http://www.ppescu.com/xxxx.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.