欢迎来到MLatom文档！
MLatom is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows. This open-source package provides plenty of choice to the users who can run simulations with the command-line options, input files, or with scripts using MLatom as a Python package, both on their computers and on the online XACS cloud computing service at XACScloud.com. Computational chemists can calculate energies and thermochemical properties, optimize geometries, run molecular and quantum dynamics, and simulate (ro)vibrational, one-photon UV/vis absorption, and two-photon absorption spectra with ML, quantum mechanical, and combined models. The users can choose from an extensive library of methods containing pretrained ML models and quantum mechanical approximations such as AIQM1 approaching coupled-cluster accuracy. The developers can build their own models using various ML algorithms. The great flexibility of MLatom is largely due to the extensive use of the interfaces to many state-of-the-art software packages and libraries.
下面的视频总结了MLatom的各项功能
查看这个展示了MLatom使用方法的 简单例子 以快速上手。
参见MLatom功能的 详细概览 以获得更多信息。
设置
教程
- 开始
- Density Functional Theory (DFT)
- 通用机器学习模型
- UAIQM
- AIQM1
- DFT ensembles
- 机器学习势
- User-defined models
- Transfer learning
- Delta-learning
- Learning molecular dynamics
- 单点能计算
- 几何优化
- 过渡态优化
- 频率和热化学
- Infrared spectra
- Raman spectra
- 分子动力学
- 准经典分子动力学
- 从分子动力学计算振动光谱
- 面跳跃动力学
- Active learning
- Data
- Periodic boundary conditions
- 更多教程
输入文件/命令行的使用手册
Python接口手册
索引及表单
索引
模块索引
搜索页面