chem-ts-optimization
Optimize non-periodic molecular TS guesses and verify first-order saddle point from vibrational modes.
Skill by learningmatter-mit
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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
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- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/chem-ts-optimization
What's inside
- Skill name
chem-ts-optimization- Description
- Optimize non-periodic molecular TS guesses and verify first-order saddle point from vibrational modes.
- License
- MIT
- Instructions
- 101 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (10)
- SKILL.md
- README.md · examples/acetonitrile/
- ts_opt.traj · examples/acetonitrile/output/
- ts_optimization_results.json · examples/acetonitrile/output/
- ts_optimized.xyz · examples/acetonitrile/output/
- product_ch3nc.xyz · examples/acetonitrile/
- reactant_ch3cn.xyz · examples/acetonitrile/
- run_example.sh · examples/acetonitrile/
- ts_guess.xyz · examples/acetonitrile/
- optimize_ts_sella.py · scripts/
SKILL.md (first lines)
# TS Optimization with Sella
Optimize a transition-state guess and check whether it is a first-order saddle point.
## Scope
- Domain: molecular chemistry only (non-periodic systems).
- Trigger: user has a TS guess and needs TS optimization plus frequency validation.
- Exclusions: periodic diffusion/path workflows (use `chem-neb-barrier` instead).
## Tool
### `optimize_ts_sella.py`
Runs Sella TS optimization followed by finite-difference vibrations.
### Use with MACE
```bash
${CLAUDE_SKILL_DIR}/../../venv/run mlip python ${CLAUDE_SKILL_DIR}/scripts/optimize_ts_sella.py \
--ts_guess ts_guess.xyz \
--model_type mace \
--model_name MACE-OFF23-small \
--fmax 0.02 \
--steps 500 \
--imag_cutoff_cm1 -50.0 \
--output_dir results/ts_opt
```
### Use with FAIRChem (UMA)
```bash
${CLAUDE_SKILL_DIR}/../../venv/run fairchem python ${CLAUDE_SKILL_DIR}/scripts/optimize_ts_sella.py \
--ts_guess ts_guess.xyz \
--model_type fairchem \
--model_name uma-s-1p1 \
--task_name omol \
--fmax 0.02 \
--steps 500 \
--imag_cutoff_cm1 -50.0 \
--output_dir results/ts_opt
```
## Arguments
- `--ts_guess`: required TS guess geometry (XYZ supported by ASE I/O).
- `--model_type`: required backend (`mace` or `fairchem`).
- `--model_name`: optional model identifier/checkpoint.
- `--task_name`: optional model head/task (for UMA molecular runs use `omol`).
- `--device`: `auto|cpu|cuda` (default `auto`).
- `--fmax`: Sella convergence threshold in eV/A (default `0.02`).
- `--steps`: maximum TS optimization steps (default `500`).
- `--vib_delta`: finite-difference displacement in A (default `0.01`).
- `--vib_nfree`: finite-difference stencil size (`2` or `4`, default `2`).
- `--imag_cutoff_cm1`: imaginary mode cutoff in cm^-1 (default `-50.0`).
- `--keep_vib_cache`: optional flag to keep vibration cache files in `output_dir/vib`.
- `--output_dir`: required output directory.
## Outputs
- `ts_optimized.xyz`: optimized TS geometry.
- `ts_opt.traj`: TS optimization trajectory.
- `ts_opt.log`: optimizer log.
- `ts_optimization_results.json`: run summary and pass/fail decision.
- `vib/` cache files only when `--keep_vib_cache` is set.
`ts_optimization_results.json` fields include:
- run/model metadata
- convergence (`sella_converged`, `optimization_steps`, `max_force_eV_per_A`)
- vibrational data (`all_frequencies_cm1`, `imaginary_modes`)
- classification (`n_imag_below_cutoff`, `is_first_order_saddle`)
## TS Pass Criterion
A structure is accepted as first-order saddle only if:
- exactly one frequency satisfies `frequency < imag_cutoff_cm1`
Default criterion: exactly one mode below `-50 cm^-1`.
## Model Guidance
- Recommended for molecules:
- `MACE-OFF23-small` / `MACE-OFF23-medium`
- `uma-s-1p1` with `--task_name omol`
- Use the same backend/model/head across reactant/product/TS optimization and TS validation.
## Prerequisites And Constraints
- Run in `mlip` (MACE) or `fairchem` (FairChem) depending on backend (`venv/run <venv> ...`).
- Script enforces `pbc=False` (non-periodic only).
- TS guess quality matters; poor guesses can converge to minima or higher-order saddles.
## Examples
See `examples/` directory for sample inputs and outputs.
---
**Author:** Juno Nam
**Contact:** [GitHub @recisic](https://github.com/recisic)From learningmatter-mit/AtomisticSkills, MIT.
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Signals
- Stars
- 183
- Forks
- 31
- Open issues
- 0
- Last commit (this folder)
- Oct 5, 2026 (24 days ago)
- Last release
- Oct 6, 2026 (23 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Website
- arxiv.org/abs/2605.24002
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
chem-ts-optimization skill. Agent Mart. https://agentmart.dev/skills/learningmatter-mit-chem-ts-optimization (last updated 2026-10-24)