born effective charge 1graph neural networks 1high-throughput simulation 1molecular dynamics 1multitask learning 1
From the 1 of 3 linked papers with an AI index.
3 papers
cond-mat.mtrl-sci2026
SevenNet-Polar for MultiTask Prediction of Energy, Forces, Stress, and Born Effective Charges: Development and Application to ZrO, LiPO, and Perovskites
Anh Khoa Augustin Lu, Shungo Arai, Yutack Park +3
The paper introduces SevenNet-Polar, an equivariant graph neural network that simultaneously predicts energy, forces, stress, and Born effective charge tensors with high accuracy,…
cond-mat.mtrl-sci2026
Adaptable Method for Crystal Design across Diverse Constraints and Objectives with Pretrained Property Predictors
Akihiro Fujii, Yoshitaka Ushiku, Koji Shimizu +2
Advanced crystal design can accelerate materials discovery across applications from photovoltaics to spintronics. Practical design must satisfy multiple properties and physical con…
cond-mat.supr-con2025
A Straightforward Gradient-Based Approach for High-Tc Superconductor Design: Leveraging Domain Knowledge via Adaptive Constraints
Akihiro Fujii, Anh Khoa Augustin Lu, Koji Shimizu +1
Materials design aims to discover novel compounds with desired properties. However, prevailing strategies face critical trade-offs. Conventional element-substitution approaches rea…