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Transfer learning discovery of molecular modulators for perovskite solar cells
Haoming Yan, Xinyu Chen, Yanran Wang +10
The discovery of effective molecular modulators is essential for advancing perovskite solar cells (PSCs), but the research process is hindered by the vastness of chemical space and…
ABACUS: An Electronic Structure Analysis Package for the AI Era
Weiqing Zhou, Daye Zheng, Qianrui Liu +55
ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It…
An Extendable Cloud-Native Alloy Property Explorer
Zhuoyuan Li, Tongqi Wen, Yuzhi Zhang +8
The ability to rapidly evaluate materials properties through atomistic simulation approaches is the foundation of many new artificial intelligence-based approaches to materials ide…
Machine-Learning-Based Interatomic Potentials for Group IIB to VIA Semiconductors: Towards a Universal Model
Jianchuan Liu, Xingchen Zhang, Tao Chen +4
Rapid advancements in machine-learning methods have led to the emergence of machine-learning-based interatomic potentials as a new cutting-edge tool for simulating large systems wi…
Universal interatomic potential for perovskite oxides
Jing Wu, Jiyuan Yang, Yuan-Jinsheng Liu +5
With their celebrated structural and chemical flexibility, perovskite oxides have served as a highly adaptable material platform for exploring emergent phenomena arising from the i…
Deep Learning of Accurate Force Field of Ferroelectric HfO
Jing Wu, Yuzhi Zhang, Linfeng Zhang +1
The discovery of ferroelectricity in HfO-based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and hig…
Accurate Deep Potential model for the Al-Cu-Mg alloy in the full concentration space
Wanrun Jiang, Yuzhi Zhang, Linfeng Zhang +1
Combining first-principles accuracy and empirical-potential efficiency for the description of the potential energy surface (PES) is the philosopher's stone for unraveling the natur…