相关信息

MLatom是一个AI增强计算化学的开源程序包。该程序包支持多种人工智能及量子化学方法，用户还可以训练自己的AI模型来执行多种模拟任务。此外，我们还在XACS云平台上提供了高级版的A-MLatom及其变体MLatom@XACS。

自2022年起，MLatom成为厦门原子计算套件（ XACS ）的一部分，您可以使用MLatom@XACS云计算服务。

该程序包由 Pavlo O. Dral 于2013年9月10日创建。Pavlo继续开发并监督程序包的发展。

开发者

开发人员及其主要贡献（按时间顺序排列）：

Pavlo O. Dral，厦门大学，始于2013，总体设计，核脊回归等
Bao-Xin Xue, 2020–2022, ML-NEA, many top-level implementations such as argument parsing.
Fuchun Ge, from 2020, interfaces to third-party software, direct learning of MD, code improvements and maintenance.
Yi-Fan Hou, from 2020, gradients in KREG, molecular dynamics, IR and Raman spectra simulations, active learning, code improvements.
Max Pinheiro Jr, 2021, interfaces to third-party software.
Peikun Zheng, 2021–2023, AIQM1, geometry optimization, thermochemical calculations.
Yuming Su, Yiheng Dai, Yangtao Chen, 2022, ML-TPA.
Shuang Zhang, 2022-2023, implementations for data module, unpublished implementations of a new MLIP.
Arif Ullah, 2023, interface to MLQD.
Yanchi Ou, 2023, implementations in data and plotting routines (many unpublished).
Yuxinxin Chen, from 2023, UAIQM, DENS24, interfaces to PySCF and xtb, improvements to AIQM1.
Lina Zhang, 2023–2024, surface-hopping dynamics, active learning for surface-hopping dynamics.
Sebastian V. Pios, August 2023, interface to Turbomole.
Quanhao Zhang, from 2023, documentation.
Mikolaj Martyka, from 2024, MS-ANI, active learning for surface-hopping dynamics.
Matheus O. Bispo, from 2024, update of MACE interface.
Vignesh B. Kumar, from 2024, TDA and TDDFT implementation via the PySCF interface
Xin-Yu Tong, from 2024, interface to DFTB+

MLatom的形成和发展也离不开我们的合作伙伴：