computational-chemistry-guide
DFT, molecular simulation, and reaction prediction tools for chemists
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill computational-chemistry-guide --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Computational Chemistry Guide ## Overview Computational chemistry bridges quantum mechanics and practical chemistry, enabling researchers to predict molecular properties, reaction mechanisms, and material behaviors without stepping into a wet lab. From drug design to catalyst optimization, computational methods accelerate discovery by screening thousands of candidates before committing to synthesis. This guide covers the major computational chemistry paradigms: Density Functional Theory (DFT) for electronic structure calculations, molecular dynamics (MD) for simulating atomic motion, machine learning potentials for scaling up simulations, and reaction prediction tools for retrosynthesis and mechanism elucidation. Each section includes tool recommendations, typical workflows, and code examples. Whether you are a chemistry PhD student running your first Gaussian calculations, a materials scientist exploring new alloys with VASP, or a medicinal chemist using ML-based property prediction, this skill provides the conceptual framework and practical recipes to get productive quickly. ## Density Functional Theory (DFT) ### When to Use DFT DFT is the workhorse of quantum chemistry. It pro
- Overview
- Density Functional Theory (DFT)
- When to Use DFT
- Software Comparison
- ORCA DFT Workflow Example
- Analyzing DFT Results with Python
- Molecular Dynamics Simulations
- MD Pipeline
- OpenMM Quick Start
- Machine Learning in Computational Chemistry
- ML Potential Energy Surfaces
- Property Prediction with RDKit
- Reaction Prediction
- Retrosynthesis Tools
orca geometry_optimization.inp > geometry_optimization.out
What does the computational-chemistry-guide skill do?
DFT, molecular simulation, and reaction prediction tools for chemists
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill computational-chemistry-guide --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.