相关信息

MLatom is an open-source program package that leverages the power of AI to enhance computational chemistry. The package supports many AI and quantum chemical methods and the users can also train their AI models to perform a wide variety of simulations. We also offer advanced version A-MLatom and its variant MLatom@XACS on the XACS cloud.

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  • Shuang Zhang, 2022-2023, implementations for data module, unpublished implementations of a new MLIP.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  • Yanchi Ou, 2023, implementations in data and plotting routines (many unpublished).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.

MLatom的形成和发展也离不开我们的合作伙伴：

  • Mario Barbatti，法国艾克斯马赛大学教授，法国大学研究所高级研究员

  • Olexandr Isayev，卡内基梅隆大学化学系助理教授

  • Cheng Wang，厦门大学教授