VASP DFT Executor
SkillDev toolsVASP DFT calculation skill for electronic structure, geometry optimization, and property prediction of nanomaterials
Use VASP DFT Executor in Claude, ChatGPT or Ahel Desktop
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/vasp-dft-executor/SKILL.md and read by Ahel’s review.
Purpose
The VASP DFT Executor skill provides density functional theory calculation capabilities using VASP for nanomaterial property prediction, enabling electronic structure analysis, geometry optimization, and materials property computation.
Capabilities
- Input file generation (INCAR, POSCAR, KPOINTS, POTCAR)
- Geometry optimization
- Electronic band structure calculation
- Density of states analysis
- Formation energy calculation
- Optical property prediction
Usage Guidelines
DFT Calculation Workflow
-
Input Preparation
- Generate structure files
- Select appropriate pseudopotentials
- Set convergence parameters
-
Calculation Execution
- Monitor convergence
- Check for errors
- Manage computational resources
-
Result Analysis
- Extract electronic properties
- Analyze band structure
- Calculate derived properties
Process Integration
- DFT Calculation Pipeline for Nanomaterials
- Multiscale Modeling Integration
- Machine Learning Materials Discovery Pipeline
Input Schema
{
"structure_file": "string (POSCAR/CIF)",
"calculation_type": "relax|static|band|dos|optical",
"functional": "PBE|HSE06|SCAN",
"kpoint_density": "number",
"encut": "number (eV)"
}
Output Schema
{
"total_energy": "number (eV)",
"bandgap": "number (eV)",
"formation_energy": "number (eV/atom)",
"optimized_structure": "string (CONTCAR)",
"electronic_properties": {
"dos_file": "string",
"band_file": "string"
},
"convergence": {
"energy_converged": "boolean",
"force_converged": "boolean"
}
}
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
vasp-dft-executor- Source
- github.com/a5c-ai/babysitter