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  1. DFT
    1. 0. Outline
    2. 1. Theory
      1. 1.1 code-DFT
      2. 1.2 Energy band theory
      3. 1.3 DFT
      4. 1.4 Solid state physics
      5. 1.5 ARPES
      6. 1.6 杂化
      7. 1.7 Space group
      8. 1.8 Surface science
      9. 1.9 Tight Binding
      10. 1.10 分子轨道理论
      11. 1.11 他人资源
      12. 1.12 Phase diagram
    3. 2. Special features
      1. 2.1 underestimating the band gap
      2. 2.2 Convergence
      3. 2.3 Elastic constant
      4. 2.4 相变
      5. 2.5 lattice constant relaxing
      6. 2.6 Fix specified basic vector and relax others’
      7. 2.7 Compile / Recompile VASP
      8. 2.8 Parameters
      9. 2.9 K-points test
      10. 2.10 Deformation potential (stretch)
      11. 2.11 Encut test
      12. 2.12 Exfoliation energy and binding energy
      13. 2.13 半导体载流子有效质量
      14. 2.14 unfold energy band
      15. 2.15 Slab / Surface
      16. 2.16 NEB 过渡态/固体相变
    4. 3. OUTPUT
      1. 3.1 Energy change
      2. 3.2 Force change
      3. 3.3 Convergence
      4. 3.4 OVITO
        1. 3.4.1 多线程
    5. 4. Universal
      1. 4.1 units transform
      2. 4.2 Generate Kpoints
      3. 4.3 Other people’s experience
      4. 4.4 python
      5. 4.5 Parallel computing
    6. 5. Introduction
    7. 6. Deep-learning neural network
  2. MD
    1. 1. Model

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知足者常乐

Updated time: 10/05 2024.

DFT

0. Outline

To summary some useful text on Wechat, Zhihu, Github, or any other source about DFT

  • DFT
    • Theory
      • code-DFT
    • Special features
      • structure relax
      • heterostructure
      • …
    • Tips
    • universal

1. Theory

1.1 code-DFT

1.2 Energy band theory

1.3 DFT

1.4 Solid state physics

1.5 ARPES

1.6 杂化

1.7 Space group

1.8 Surface science

1.9 Tight Binding

1.10 分子轨道理论

1.11 他人资源

1.12 Phase diagram

2. Special features

2.1 underestimating the band gap

  • VASP实战-DFT低估带隙的解决方案对比 (qq.com)
    • 基于密度泛函的能带计算往往会因为电子的分数占据（这里太复杂，简单讲就是电子不可能即在这里又在那里，但密度泛函关心的是电荷密度，再加上交换关联项都是近似的，所以电子会出现分数占据的问题），而导致低估能带的问题，严重的甚至有可能将半导体误判成导体.

2.2 Convergence

2.3 Elastic constant

2.4 相变

2.5 lattice constant relaxing

2.6 Fix specified basic vector and relax others’

2.7 Compile / Recompile VASP

2.8 Parameters

2.9 K-points test

2.10 Deformation potential (stretch)

2.11 Encut test

2.12 Exfoliation energy and binding energy

2.13 半导体载流子有效质量

2.14 unfold energy band

2.15 Slab / Surface

2.16 NEB 过渡态/固体相变

3. OUTPUT

3.1 Energy change

3.2 Force change

3.3 Convergence

3.4 OVITO

3.4.1 多线程

4. Universal

4.1 units transform

4.2 Generate Kpoints

4.3 Other people’s experience

4.4 python

4.5 Parallel computing

5. Introduction

6. Deep-learning neural network

MD

1. Model

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