7 papers
From Materials Database to Materials Bank: Assetizing Data for AI Driven Materials Innovation
Chenyao Ma, Di Zhang, Weibo Gong +9
Driven by high-throughput experimentation, computational modeling, and artificial intelligence (AI), materials data has expanded at an unprecedented rate. Conventional materials da…
Empowering Polymeric Materials Discovery by Artificial Intelligence
Chenyao Ma, Linda Zhang, Yuheng Chen +29
Polymeric materials underpin modern technologies spanning energy storage, microelectronics, healthcare and sustainable manufacturing. Yet their rational design remains exceptionall…
Building a physics-aware AI ecosystem for solid-state hydrogen storage materials
Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu +66
Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evo…
The Python Simulations of Chemistry Framework: 10 years of an open-source quantum chemistry project
Qiming Sun, Matthew R Hermes, Xiaojie Wu +100
Over the past decade, the Python-based Simulations of Chemistry Framework (PySCF) has developed into a widely used open-source platform for electronic structure theory and quantum…
Digital Hydrogen Platform (DigHyd): A Rigorously Curated Database for Hydrogen Storage Materials Empowered by AI-Assisted Literature Mining
Seong-Hoon Jang, Di Zhang, Xue Jia +8
Solid-state hydrogen storage materials are promising candidates for safe and compact hydrogen storage; however, data-driven discovery in this field remains limited by the availabil…
Physically Interpretable Descriptors Drive the Materials Design of Metal Hydrides for Hydrogen Storage
Seong-Hoon Jang, Di Zhang, Hung Ba Tran +5
Designing metal hydrides for hydrogen storage remains a longstanding challenge due to the vast compositional space and complex structure-property relationships. Herein, for the fir…