Software

Journal Club

1. Presented by Huiwen: Managing the computational chemistry big data problem: the ioChem-BD platform, Link to paper.
2. Presented by Jingyi: Ab initio characterization of protein molecular dynamics with AI2BMD, Link to paper.
3. Presented by Lewen: Large language model guided automated reaction pathway exploration, Link to paper.
4. Presented by Huiwen: E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potential, Link to paper.
5. Presented by Jingyi: Auto-Qchem: an automated workflow for the generation and storage of DFT calculations for organic molecules, Link to paper.
6. Presented by Yu: UMA: A Family of Universal Models for Atoms, Link to paper.
7. Presented by Sum Ming: Sampling 3D Molecular Conformers with Diffusion Transformers, Link to paper.
8. Presented by Zihan: Constructing and explaining machine learning models for chemistry: example of the exploration and design of boron-based Lewis acids, Link to paper.
9. Presented by Huiwen: Ab initio solution of the many-electron Schrödinger equation with deep neural networks, Link to paper.
10. Presented by Lewen: Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models, Link to paper.
11. Presented by Sum Ming: Comparing SMILES and SELFIES tokenization for enhanced chemical language modeling, Link to paper.
12. Presented by Isha: Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning, Link to paper.
13. Presented by Ansh: Leveraging large language models for predictive chemistry, Link to paper.
14. Presented by Zihan: Data extraction from polymer literature using large language models, Link to paper.
15. Presented by Jingyi: Large language models for scientific discovery in molecular property prediction, Link to paper.
16. Presented by Zihan: Toward a unified benchmark and framework for deep learning-based prediction of nuclear magnetic resonance chemical shifts, Link to paper.
17. Presented by Jingyi: Baseline Correction Using a Deep-learning Model Combining ResNet and UNet, Link to paper.
18. Presented by Huiwen: A review of large language models and autonomous agents in chemistry, Link to paper.
19. Presented by Zihan: An automatic end-to-end chemical synthesis development platform powered by large language models, Link to paper.

For Undergraduates

I must duly acknowledge that some of the materials are drawn freely from my undergraduate lecture notes. Where the explanations in the notes are unclear, or too brief, to the point where the actual derivations become difficult for some students, I attempt to make this clearer by explaining using my own reasoning. It should be noted, however, that any mistakes herein are mine and mine alone. Please send any suggestions and/or corrections to xinglong.zhang[AT]cuhk.edu.hk.

 

Chemistry

The following gives a brief introduction to electronic structure theory and quantum chemistry (taken from Chapter 1 of my Ph.D Thesis).

• Introduction to Quantum Chemistry

Oxford University Year 1 Physical Chemistry Notes:

• Use of Thermodynamic Square
• Thermodynamics Quick Summary
• A Rather Quick Introduction to Quantum Mechanics

Oxford University Year 2 Physical Chemistry Notes:

• Statistical Mechanics Part I

The following are some short notes that attempt to highlight some concepts or derivations that are not usually covered in a lecture setting or in some cases, not directly required for undergraduate examinations.

• Hermitian Operators
• Variational Principle
• Secular Equations
• Huckel Theory for Special Systems
• Molecular vibrations and its resemblance to Huckel problems

 

Mathematics

The following notes on applied mathematical topics are much longer. It is hoped that these notes on their own are accessible for anyone with an A level knowledge wishing to learn more about these topics.

• Vectors

For Postgraduates

• Contributed by Huiwen: Quasi-Rigid-Rotor-Harmonic-Oscillator Approximation