XACS Workshop 2023

第二届厦门原子计算套件研讨会在厦门成功举办

Tutorials in English for the second XACS workshop, held at Xiamen University, on May 12–16, 2023. Introduction to the workshop is in Chinese below.

为了满足广大理论与计算化学研究学者系统学习价键理论方法、能量分解分析方法和机器学习化学计算模拟的需求，由福建省化学会、福建省理论与计算化学重点实验室和嘉庚创新实验室联合主办的第二届厦门原子计算套件(XACS)研讨会在厦门大学思明校区成功举办。该研讨会的前身是厦门大学先期主办的厦门价键（XMVB）系列研讨会。自2012年至今，系列会已成功举办了四届国际研讨班和六届国内研讨班。本次研讨会以线下形式举行，来自厦门大学、中国科学院、香港中文大学、香港科技大学、四川大学、南京大学、中山大学、郑州大学、南京工业大学等国内21所高校/机构的70多名师生线下参加了本次研讨会。

在本次研讨会上，吴玮教授、苏培峰教授、Pavlo Dral教授，周晨副教授、应富鸣高级工程师，谷俊井高级工程师系统讲授了价键理论、分子相互作用理论和机器学习基础知识并详细介绍了原子计算套件(XACS)云计算功能、以及该套件所包括的XMVB, XEDA和MLATOM软件的应用实例。国内外资深专家受邀对相关理论方法以及XACS在化学材料等领域的应用进行深入研讨，其中，香港中文大学（深圳）的Hajime Hirao 教授、塞尔维亚克拉古耶瓦茨大学的Slavko Radenković副教授和奥地利自然资源与生命科学大学的Daniel Tunega教授分别做了专题学术报告，介绍他们应用XACS套件开展研究的最新进展。同时，研讨会为与会者提供了由厦门大学自主开发的XACS套件的上机培训，与会者基于XACS研究实例针对量子化学理论和人工智能展开了热烈的讨论。会议的成功举办提升了我校理论化学在国内外同行的影响力，为XACS套件及云计算平台的推广起到了重要促进作用。

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Contents:

• 1. Getting started
  • 1.1. Geometry optimization of C₂H₆
    • 1.1.1. Input files
    • 1.1.2. Computational results
    • 1.1.3. Questions
  • 1.2. Vibrational analysis and thermochemical calculations of C₂H₆
    • 1.2.1. Input file
    • 1.2.2. Computational result
    • 1.2.3. Questions
  • 1.3. Energy decomposition analysis of C–C bond in C₂H₆
    • 1.3.1. Input file
    • 1.3.2. Computational result
    • 1.3.3. Question
  • 1.4. Analysis of C–C bond in C₂H₆ with valence bond theory
    • 1.4.1. VB structures
    • 1.4.2. Input file
    • 1.4.3. Computational result
    • 1.4.4. Question
• 2. Practice in energy decomposition analysis with XEDA
  • 2.1. Examples
    • 2.1.1. H-bond in NH₃\(\cdots\)H₂O
    • 2.1.2. Covalent bond in CH₃-NH₂
    • 2.1.3. Ionic bond in NaCl
    • 2.1.4. \(\pi\)-\(\pi\) interaction
  • 2.2. Exercises
    • 2.2.1. Energy Decomposition Analysis for Menshutkin Reaction
    • 2.2.2. Cation-pi interaction
    • 2.2.3. Water tetramer
    • 2.2.4. Multiple bond
    • 2.2.5. Using initial guess
    • 2.2.6. Base Pair (Guanine\(\cdots\)Cytosine)
    • 2.2.7. Non-covalent interactions in S66
• 3. Practice in valence bond calculations with XMVB
  • 3.1. BDE and RE of F₂
    • 3.1.1. Introduction
    • 3.1.2. Computations with 3 Structures at Stationary Point
    • 3.1.3. Computations with 3 Structures at Dissociation Limit
    • 3.1.4. Computations with Covalent Structure at Stationary Point
  • 3.2. Resonance in C₆H₆
    • 3.2.1. Introduction
    • 3.2.2. Computations with 5 Covalent Structures
    • 3.2.3. Computations with 2 Kekulé Structures
    • 3.2.4. Computations with 1 Kekulé Structure
  • 3.3. Menshutkin Reaction NH₃ + CH₃Cl \(\rightarrow\) [NH₃CH₃]⁺ + Cl^-
    • 3.3.1. Chemical question to be addressed
    • 3.3.2. Active/inactive electrons and orbitals
    • 3.3.3. Fragmentation and important VB structures
    • 3.3.4. Basis set and its subsets based on orbital symmetry
    • 3.3.5. Structures
    • 3.3.6. Input File
    • 3.3.7. Computational Results
  • 3.4. Potential Energy Surface of LiF (Optional)
    • 3.4.1. Introduction
    • 3.4.2. Computations near equilibrium
    • 3.4.3. Computations for Other distances
• 4. Practice in machine learning with MLatom
  • 4.1. Machine learning model for H₂ potential energy curve
    • 4.1.1. Creating a kernel ridge regression model
    • 4.1.2. Using the model
    • 4.1.3. Questions
  • 4.2. Choosing the right machine learning potential
    • 4.2.1. Testing a KREG model
    • 4.2.2. Questions
    • 4.2.3. Testing ANI-type model
    • 4.2.4. Question
    • 4.2.5. Learning curves
    • 4.2.6. Questions
• 5. Molecular dynamics
• 6. Spectroscopy
  • 6.1. Infrared spectra
    • 6.1.1. Input file
    • 6.1.2. Computational results
  • 6.2. UV/vis absorption spectra with machine learning
    • 6.2.1. Input files
    • 6.2.2. Computational results
    • 6.2.3. Questions
  • 6.3. Two-photon absorption cross sections with machine learning
    • 6.3.1. Input files
    • 6.3.2. Computational results