Videos of the conference are now available on KouShare! You can also find links to the videos of specific talks in the program below.
- The morning sessions were domestic sessions and are in English & 中文.
- The afternoon & night sessions were international and in English.
- The Book_of_Abstracts is available to download.
Skip to: Overview | Tuesday July 12 | Wednesday July 13 | Thursday July 14 | Friday July 15
The conference program may be subject to revisions. Last update: 11. July 2022.
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Tuesday July 12 |
Wednesday July 13 |
Thursday July 14 |
Friday July 15 | |||
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Session 4 (Data & ML) 9:00 – 10:15 Beijing 03:00 - 04:14 Berlin |
Session 11 (Data & ML) 9:00 – 10:15 Beijing 03:00 - 04:15 Berlin |
Session 17 (Data & ML) 9:00 – 10:15 Beijing 03:00 - 04:15 Berlin |
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| Tea & Coffee Break | ||||||
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Session 5 (Data & ML) 10:35 – 11:35 Beijing 04:35 – 05:35 Berlin |
Session 12 (Data & ML) 10:35 – 11:35 Beijing 04:35 - 05:35 Berlin |
Session 18 (Data & ML) 10:35 – 11:35 Beijing 04:35 - 05:35 Berlin |
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| Lunch Break | ||||||
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Opening 14:20 – 14:40 Beijing 08:20 - 08:40 Berlin |
Session 6 (Data) 14:30 – 16:00 Beijing 08:30 - 10:00 Berlin |
Session 7 (ML) 14:30 –16:00 Beijing 08:30 - 10:00 Berlin |
Session 13 (Plenary Talks) 14:30 – 15:50 Beijing 08:30 - 09:50 Berlin |
Session 19 (Data & ML) 14:30 – 16:10 Beijing 08:30 - 10:10 Berlin |
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Session 1 (Plenary Talks) 14:40 – 16:00 Beijing 08:40 - 10:00 Berlin |
Closing 16:10 – 16:30 Beijing 10:10 - 10:30 Berlin |
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| Tea & Coffee Break | ||||||
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Session 2 (Data) 16:20 – 18:00 Beijing 10:20 - 12:00 Berlin |
Session 3 (ML) 16:20 – 18:00 Beijing 10:20 - 12:00 Berlin |
Session 8 (Data) 16:20 – 17:30 Beijing 10:20 - 11:30 Berlin |
Session 9 (ML) 16:20 – 17:30 Beijing 10:20 - 11:30 Berlin |
Session 14 (Data) 16:10 – 17:20 Beijing 10:10 - 11:20 Berlin |
Session 15 (ML) 16:10 – 17:20 Beijing 10:10 - 11:20 Berlin |
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| Dinner Break | ||||||
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Session 10 (Data) 21:00 – 22:00 Beijing 15:00 - 16:00 Berlin |
Session 16 (ML) 21:00 – 22:00 Beijing 15:00 - 16:00 Berlin |
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Tuesday July 12 Back to top
| Events | |
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Session 1, Chairs: Tong-Yi Zhang & Yibin Xu. Opening and Plenary Talks |
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Opening Remarks Jincang Zhang (张金仓), Tong-Yi Zhang (张统一), Matthias Scheffler |
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Data-Driven Alloy Design via the Integration of Multiple Research Paradigms Yi Liu (刘轶), Shanghai University, China |
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FAIR Materials Data with the OPTIMADE API and Ontologies for Materials Design Rickard Armiento, Linköping University, Sweden |
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| Tea & Coffee Break | |
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Session 2, Chairs Haiqing Yin & Zhimei Sun. Data Management & Database |
Session 3, Chairs: Wencong Lu & Jing Ma. Machine Learning |
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The Material Data for The AI Era Hong Wang (汪洪), SJTU, China |
Machine Learned Spectroscopy for Chemistry and Material |
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An Open-Access Database and Analysis Tool for Perovskite Solar Cells Based on the FAIR Data Principles Jesper Jacobsson, Nankai University, China |
Machine-Enabled Chemical Structure-Property-Synthesizability Predictions Yousung Jung, KAIST, South Korea |
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The SHU Materials Data Platform and Data Copyright Quan Qian (钱权), Shanghai University, China |
Rapid Discovery of Two-Dimensional Ferromagnetic Materials via Machine Learning Jinlan Wang (王金兰), Southeast University, China |
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The Importance of Data Management Plans in Large Battery Initiatives Ivano E. Castelli, DTU, Denmark |
Challenges and Opportunities in Polymer Informatics from a Statistical Perspective Stephen Wu, The Institute of Statistical Mathematics, Japan |
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Development and Recent Progress of 2D Materials Encyclopedia Database (2DMatPedia) Lei Shen (沈雷), NUS, Singapore |
AI-Assisted Physical Modelling: From Scientific Discoveries Linfeng Zhang (张林峰), DP Technology, China |
Wednesday July 13 Back to top
| Events | |
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Session 4, Chairs: Runhai Ouyang & Ziqiang Dong. Data & Machine Learning |
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The Development of LASP Software and its Application in Material Structure Identification Cheng Shang (商城), Fudan University, China |
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High-Throughput Screening of Single-Atom Alloy Catalysts using First-Principles Calculations and Data Analytics Zhong-Kang Han (韩仲康), Zhejiang University, China |
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Design of Mixed Metal Oxides for Oxygen Electrocatalysis Xiang-Kui Gu (顾向奎), Wuhan University, China |
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Active Learning of Formation Energies of the Sigma Phase in Magnetic Systems Yang Zha (查炀), Shanghai University, China |
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InterMat: A Digital Infrastructure Based on Blockchain and Privacy Computing for Material Data Discovery and Sharing Hang Su (苏航), CISRI, China |
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| Tea & Coffee Break | |
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Session 5, Chairs: Hang Su & Jing Feng. Data & Machine Learning |
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Predicting Single-Phase Solid Solutions in High Entropy Alloys: High-Throughput Screening with an Optimized Machine-Learning Model Ji-Chang Ren (任吉昌), Nanjing University of Science and Technology, China |
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Data-Driven Glass-Forming Ability Criteria of Amorphous Alloys Jie Xiong (熊杰), Harbin Institute of Technology Shenzhen, China |
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Fatigue S-N Curve Prediction Based on Transfer Learning for Extremely Small Steel Sample Databases Wei Xu (徐伟), Northeastern University, China |
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Predicting Experimental Formability of Hybrid Organic-Inorganic Perovskites via Imbalanced Learning Tian Lu (卢天), Shanghai University, China |
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| Lunch Break | |
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Session 6, Chairs: Lei Zhang & Markus Scheidgen. Data Management, Database, Exascale Computation |
Session 7, Chairs: Zhipan Liu & Jun Jiang. Machine Learning |
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Exploring A Data Ecosystem for Materials Genome Engineering and FAIR Data Haiqing Yin (尹海清), USTB, China |
Does AI Really Help in Materials Design? Two Case Studies. Wan-jian Yin (尹万健), Soochow University, China |
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Construction of a Literature Database for Battery Materials Yibin Xu (徐一斌), NIMS, Japan |
Machine Learning Prediction of Electronic Structure and Material Properties Jing Ma (马晶), Nanjing University, China |
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Be FAIR with your Experimental Data Sandor Brockhauser, HU Berlin, Germany |
Combining Machine Learning and High-Throughput Experimentation to Discover Organic Photocatalysts Xiaobo Li (李小波), Zhejiang Normal University, China |
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NOMAD OASIS Cloud Computing Tools for the Atom Probe Microscopy Community Markus Kühbach, HU Berlin, Germany |
Search for New Catalytic Materials Based on Consistent Experimental Data, DFT and AI: OCM Reaction Aliaksei Mazheika, TU Berlin, Germany |
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Exascale Systems & Data Infrastructures in Europe and Germany – Status and Developments Erwin Laure, MPCDF, Germany |
Uncertainty Quantification for Accelerated Optimization of Material Properties via Active Learning Dezhen Xue (薛德祯), Xi’an Jiaotong University, China |
| Tea & Coffee Break | |
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Session 8, Chairs: Hong Wang & Xiaoyu Yang. Data Management & Database |
Session 9, Chairs: Wan-Jian Yin & Xiaonan Wang. Machine Learning |
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Data Management for High-Throughput Analysis of Hampus Näsström, Helmholtz-Zentrum Berlin, Germany |
Chemical Hardness-Driven Interpretable Machine Abhishek K. Singh, Indian Institute of Science, India |
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Accelerating Materials Discovery and Design by ALKEMIE Zhimei Sun (孙志梅), Beihang University, China |
Optimization of Nanoporous Metallic Actuators by Combining Multiscale Calculations and Machine Learning Sheng Sun (孙升), Shanghai University, China |
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Multi-Dimensional Photoemission Spectroscopy: A Concept for FAIR Photoemission Data Tommaso Pincelli, FHI Berlin, Germany |
Accelerating the High-Throughput Search for new Thermal Insulators with Symbolic Regression Thomas Purcell, The NOMAD Lab, Germany |
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Flexible Schema for FAIR Synthesis Data Andrea Albino, HU Berlin, Germany |
Exploring High Thermal Conductivity Polymers via Interpretable Machine Learning Shenghong Ju (鞠生宏), SJTU, China |
| Dinner Break | |
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Session 10, Chair: Carsten Baldauf. Database & High-Throughput |
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High-Throughput Discovery of Inorganic Compounds Chris Wolverton, Northwestern University, USA |
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Applications of FAIR Data Principles within the AFLOW Database Cormac Toher, UT Dallas/Duke Uni., USA |
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Evaluating Chemical Composition and Crystal Structure Representations using the Matbench Test Set Anubhav Jain, LBNL, USA |
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Thursday July 14 Back to top
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Session 11, Chairs: Cheng Shang & Sheng Sun. Data & Machine Learning |
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Learning Chemical Element Representations with Structural Information for Alloys Hongxiang Zong (宗洪祥), Xi'an Jiaotong University, China |
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Valorization of Biomass to Aromatic Monomers enabled by Predictive Modeling Changru Ma (马畅儒), Eco-Efficient Products and Processes Laboratory, UMI 3464 CNRS/Solvay, China |
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Analysis and Modeling of Corrosion Behavior of Ferritic-Martensitic Steels in Supercritical Water using Domain Knowledge-Guided Interpretive Machine Learning Ziqiang Dong (董自强), Shanghai University, China |
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Design of Oxidation-Resistant Superalloy at High Temperature by Machine Learning Jing Feng (冯晶), Kunming University of Science and Technology, China |
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Unraveling the Relationships between Chemical Bonding and Thermoelectric Properties: N-Type ABO3 Perovskites Lili Xi (席丽丽), Shanghai University, China |
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| Tea & Coffee Break | |
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Session 12, Chairs: Xiang-Kui Gu & Zhong-Kang Han. Data & Machine Learning |
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Physics-Inspired Scaling Nanomaterial Dynamics and Kinetic Sulei Hu (胡素磊), University of Science and Technology of China, China |
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Standardization of Metadata Schema for Materials Experiment Following FAIR Principles Yongchao Lu (路勇超), Shanghai Jiao Tong University, China |
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Computational Screening of Bimetallic Ordered Catalysts for Nitrogen Reduction Reaction Jing Zhou (周靖), Hunan University, China |
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Machine Learning-Assisted the Discovery of Thermoelectric materials via Image Analysis & Graph Representation Ye Sheng (盛晔), Shanghai University, China |
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| Lunch Break | |
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Session 13, Chair: Claudia Draxl. Plenary Talks |
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NOMAD – FAIR Data Management Infrastructure for Materials Science Markus Scheidgen, HU Berlin, Germany |
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Combining DFT and Machine Learning to Accurately Predict Material Properties Silvana Botti, Friedrich Schiller University Jena, Germany |
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| Tea & Coffee Break | |
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Session 14, Chairs: Miao Liu & Jiong Yang. Database, High-Throughput |
Session 15, Chairs: Dezhen Xue & Xiaobo Li. Machine Learning |
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Multiscale High-Throughput Materials Simulation in Cloud: An Integrated Infrastructure for Modelling, Workflow Design, Database, and AI Xiaoyu Yang (杨小渝), CNIC CAS, China |
Resolving the Structure of Complex Systems via Machine-Learning based Atomic Simulation Zhipan Liu (刘智攀), Fudan University, China |
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Digital Transformation and FAIR Data in the Light of the Resulting Opportunities and Challenges related to Catalysis Stephan Schunk, The HTE Company, Germany |
Smart Systems Engineering Contributing to Intelligent Laboratory and Carbon-Neutral Future Xiaonan Wang (王笑楠), Tsinghua University, China |
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High-Throughput First-Principles Predictions of Polar Materials Yue-Wen Fang, University of the Basque Country, Spain |
The NOMAD Artificial-Intelligence Toolkit: Turning Materials-Science Data into Knowledge and Understanding Luigi Sbailò, HU Berlin, Germany |
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Atomly.net: A Data-Centric Approach to Advance Materials Science Miao Liu (刘淼), Institute of Physics CAS, China |
Development of High-Entropy Alloys Facilitated by Multiscale Simulation, High-Throughput Computation and Machine Learning Shuai Chen (陈帅), IHPC, Singapore |
| Dinner Break | |
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Session16, Chairs: Silvana Botti & Luca Ghiringhelli. Machine Learning |
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Designing Universal Machine Learning Models for Materials Science Shyue Ping Ong, LBNL, USA |
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Materials Discovery Facilitated by Classical Description of Interatomic Interactions Howard Sheng, George Mason University, USA |
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NWChemEx, Moving Computational Chemistry to the Exascale Wibe de Jong, LBNL, USA |
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Friday July 15 Back to top
| Events |
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Session 17, Chairs: Shenghong Ju & Ji-Chang Ren. Data & Machine Learning |
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Deep Learning Strategy for Limited and Imbalanced Data, A Case Study on Screening Coformer for Diverse Co-Crystal Materials Xuemei Pu (蒲雪梅), Sichuan University, China |
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Revealing the Materials Genome for Advanced High-Entropy Materials Yi Wang (王毅), Northwestern Polytechnical University, China |
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Predicting Properties of Inorganic Crystalline Solid Materials using a Modified TPOT Framework Hongwei Du (杜红伟), Shanghai Jiao Tong University, China |
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Thermal Transport of Mg3(Sb/Bi)2 from Machine Learning Interatomic Potential Yifan Zhu (朱一凡), Shanghai Institute of Ceramics, CAS, China |
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Development of a Machine Learning Potential for the Study of Uranium Hongjian Chen (陈洪剑), Hunan University, China |
| Tea & Coffee break |
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Session 18, Chairs: Xuemei Pu & Yi Wang. Data & Machine Learning |
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Accelerated Design of Linear-Superelastic Ti-Nb Nanocomposite Alloys with Ultralow Modulus via High-Throughput Phase-Field Simulations and Machine Learning Tao Xu (徐涛), Shanghai University/NIMTE CAS, China |
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Semi-Supervised Learning Guided for Exploration of High-Performance Thermoelectric Materials Xue Jia (贾雪), Harbin Institute of Technology Shenzhen, China |
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Machine Learning for Accelerated Prediction of the Seebeck Coefficient at Arbitrary Carrier Concentration Hongmei Yuan (袁红梅), Wuhan University, China |
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Accelerated Search of Shape Memory Alloy with Large Latent Heat via Active Learning Considering Experimental Data Uncertainties Yuan Tian (田原), Shanghai University, China |
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Session 19, Chairs: Yi Liu & Gian-Marco Rignanese. Database, Data Management, High-Throughput, Machine Learning |
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Microstructure Database Construction Using Integrated CALPHAD Approach and Phase-Field Modeling Rongpei Shi (施荣沛), Harbin Institute of Technology Shenzhen, China |
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First-Principles MatHub-3d Database and the Applications in Thermoelectrics Jiong Yang (杨炯), Shanghai University, China |
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Materials Science in the Information Age Christof Wöll, KIT, Institute of Functional Interfaces, Germany |
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FAIRifying Computational Materials-Science Data: Workflows, Ontologies, and Data Quality Luca Ghiringhelli, HU Berlin, Germany Cancelled |
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Materials Data Infrastructure Development based on the Materials Genome Engineering Database Architecture Lei Zhang (张雷), USTB, China |
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Closing Remarks Matthias Scheffler, Jincang Zhang (张金仓), Tong-Yi Zhang (张统一) |