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PET-MAD, a lightweight universal interatomic potential for advanced materials...

B2FIND2026-04-11 收录

原子间势机器学习

材料设计

数据链接：

https://b2find.eudat.eu/dataset/f83fed20-9aa1-5413-9bb9-d58b3b17c8c9 数据链接链接失效反馈

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资源简介：

<p>Machine-learning interatomic potentials (MLIPs) have greatly extended the reach of atomic-scale simulations, offering the accuracy of first-principles calculations at a...

应用场景：

原子间势机器学习

量子化学计算

These datasets were used in the training and testing of Machine Learning Interatomic Potentials (MLIPs) as part of the work represented in the article titled Does Hessian Data Improve the Performance

DataCite Commons2025-05-29 更新160

Data from the paper "Improving Aqueous Metal Salt Interactions using Machine Learned Interatomic Potentials"

原子间势机器学习

水溶液金属盐模拟

This contains the datasets and models from MLIP training for aqueous arsenic and magnesium salts. From the paper "Improving Aqueous Metal Salt Interactions using Machine Learned Interatomic Potentials

Zenodo2025-08-13 更新60

Materials Data on Rb2TiAgF6 by Materials Project

材料电子结构计算

材料设计

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For

DataCite Commons2021-02-04 更新50

Materials Data on GePb2(SeO3)4 by Materials Project

晶体结构表征

材料设计

Pb2Ge(SeO3)4 crystallizes in the monoclinic P2_1/c space group. The structure is three-dimensional. Pb2+ is bonded in a 7-coordinate geometry to seven O2- atoms. There are a spread of Pb–O bond distan

DataCite Commons2021-02-04 更新80

Materials Data on Nd5Rh4 by Materials Project

晶体结构表征

材料设计

Nd5Rh4 crystallizes in the orthorhombic Pnma space group. The structure is three-dimensional. there are three inequivalent Nd sites. In the first Nd site, Nd is bonded in a 6-coordinate geometry to si

DataCite Commons2021-02-04 更新60

PET-MAD, a lightweight universal interatomic potential for advanced materials...

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