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chem-dft-orca-optimization

Run DFT geometry optimization (minimization or TS search) on a molecular structure using ORCA via SCINE/ReaDuct wrapper.

Skill by learningmatter-mit

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About

Run DFT geometry optimization (minimization or TS search) on a molecular structure using ORCA via SCINE/ReaDuct wrapper.

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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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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/chem-dft-orca-optimization

What's inside

Skill name
chem-dft-orca-optimization
Description
Run DFT geometry optimization (minimization or TS search) on a molecular structure using ORCA via SCINE/ReaDuct wrapper.
License
MIT
Instructions
148 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (6)

  • SKILL.md
  • README.md · example/
  • h2o.xyz · example/
  • initial_structure.xyz · example/
  • ts_guess.xyz · example/
  • run_optimization.py · scripts/

SKILL.md (first lines)

# DFT Geometry Optimization with ORCA

## Goal

Optimize the geometry of a molecular structure at the DFT level using the ORCA quantum chemistry program. Supports two modes: **minimization** (finding the nearest local minimum) and **transition state (TS) optimization** (single-ended saddle point search). The calculation uses the SCINE/ReaDuct wrapper for robust optimizer management.

> [!IMPORTANT]
> This skill provides **single-ended TS optimization** only. For reaction pathway methods (NEB, IRC), consider using the MLIP-based [NEB skill](../chem-neb-barrier/SKILL.md) or [IRC skill](../chem-irc-verification/SKILL.md) with MLIP pre-screening, then refine with DFT. For advanced ORCA features, use the [advanced ORCA skill](../chem-dft-orca-advanced-calculation/SKILL.md).

## Background

Geometry optimization iteratively adjusts nuclear positions to minimize (or, for TS search, to find a first-order saddle point of) the potential energy surface $E(\mathbf{R})$. The SCINE/ReaDuct optimizer handles step control, coordinate transformations, and convergence criteria internally.

- **Minimization** seeks a stationary point where $\nabla E = 0$ and the Hessian has all positive eigenvalues.
- **TS optimization** seeks a first-order saddle point where $\nabla E = 0$ and the Hessian has exactly one negative eigenvalue.

## 1. Prerequisites

- **Environment:** `cpu` (commands run through `venv/run cpu ...`), which includes `scine_utilities`, `scine_readuct` (x86_64 only), and `ase`
- **ORCA binary:** The environment variable `ORCA_BINARY_PATH` must point to the ORCA executable
  ```bash
  export ORCA_BINARY_PATH=/path/to/orca
  ```
- **Input structure:** A molecular structure file readable by ASE (`.xyz`, `.cif`, `.mol`, etc.)
- For **TS optimization:** Provide a reasonable TS guess geometry. Poor initial guesses will likely fail to converge to the correct saddle point.

## 2. Parameters

| Parameter | Default | Description |
|-----------|---------|-------------|
| `--structure` | (required) | Path to input structure file |
| `--opt_type` | `min` | `min` for minimization, `ts` for transition state search |
| `--charge` | `0` | Molecular charge |
| `--spin_multiplicity` | `1` | Spin multiplicity (2S+1) |
| `--functional` | `PBE` | DFT functional (e.g. `PBE`, `B3LYP`, `wB97X-V`) |
| `--basis_set` | `def2-SVP` | Basis set (e.g. `def2-SVP`, `def2-TZVP`) |
| `--dispersion` | None | Dispersion correction (e.g. `D3BJ`, `D4`) |
| `--solvation` | None | Implicit solvation model: `CPCM` or `SMD` |
| `--solvent` | None | Solvent name; required if `--solvation` is set |
| `--special_option` | `NOSOSCF` | ORCA special option passed to SCINE calculator. Set to empty string to disable. |
| `--nprocs` | `1` | Number of CPU cores for ORCA |
| `--convergence_max_iterations` | `200` | Maximum optimization steps |
| `--calculate_final_hessian` | off | Compute Hessian at optimized geometry (for TS verification) |
| `--calculator_settings` | None | Extra SCINE calculator settings as a JSON string (see below) |
| `--optimizer_settings` | None | Extra ReaDuct optimizer kwargs as a JSON string (see below) |
| `--output_dir` | auto | Output directory |

## 3. Running an Optimization

### Geometry minimization

```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/run_optimization.py \
    --structure molecule.xyz \
    --functional B3LYP \
    --basis_set def2-TZVP \
    --dispersion D3BJ \
    --nprocs 4 \
    --output_dir research/my_project/optimization
```

### Transition state optimization

```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/run_optimization.py \
    --structure ts_guess.xyz \
    --opt_type ts \
    --functional B3LYP \
    --basis_set def2-TZVP \
    --dispersion D3BJ \
    --calculate_final_hessian \
    --nprocs 4 \
    --output_dir research/my_project/ts_optimization
```

### With extra settings (calculator + optimizer)

For settings not exposed as dedicated flags, pass JSON strings. `--calculator_settings` applies to the SCINE/ORCA calculator, `--optimizer_settings` applies to the ReaDuct optimization task. SCINE is strict about types, so JSON ensures values are passed with the correct type (int, float, string).

```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/run_optimization.py \
    --structure molecule.xyz \
    --functional B3LYP \
    --basis_set def2-TZVP \
    --calculator_settings '{"max_scf_iterations": 128}' \
    --optimizer_settings '{"convergence_delta_value": 1e-6}' \
    --output_dir research/my_project/opt_custom
```

### With implicit solvation

```bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/run_optimization.py \
    --structure molecule.xyz \
    --functional PBE0 \
    --basis_set def2-TZVP \
    --solvation SMD \
    --solvent water \
    --nprocs 4 \
    --output_dir research/my_project/opt_solvated
```

## 4. Output Files

- `optimization_results.json`: Structured results containing:
  - `converged`: Boolean indicating whether the optimization converged
  - `final_energy_hartree`, `final_energy_eV`: Final electronic energy
  - `final_max_force_eV_per_Ang`, `final_rms_force_eV_per_Ang`: Residual force information
  - `opt_type`: Whether this was a minimization or TS search
  - If `--calculate_final_hessian` was used: `hessian_eV_per_Ang2`, `hessian_wave_numbers_cm-1`, and `n_imaginary_modes`
  - All input parameters for reproducibility
- `initial_structure.xyz`: Copy of the input structure
- `optimized_structure.xyz`: The optimized geometry

## 5. Interpreting Results

### Minimization
- Check `converged: true` in the results JSON.
- Residual forces should be small (max force < 0.01 eV/A for typical convergence).

From learningmatter-mit/AtomisticSkills, MIT.

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Last commit (this folder)
Oct 5, 2026 (22 days ago)
Last release
Oct 6, 2026 (22 days ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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chem-dft-orca-optimization skill. Agent Mart. https://agentmart.dev/skills/learningmatter-mit-chem-dft-orca-optimization (last updated 2026-10-24)