Quantum ESPRESSO Executor

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Quantum ESPRESSO calculation skill for DFT simulations with pseudopotential management

Use Quantum ESPRESSO Executor in Claude, ChatGPT or Ahel Desktop

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Then ask your AI: use the Quantum ESPRESSO Executor skill

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.

Quantum ESPRESSO ExecutorStart free

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/quantum-espresso-executor/SKILL.md and read by Ahel’s review.

Purpose

The Quantum ESPRESSO Executor skill provides DFT calculation capabilities using Quantum ESPRESSO for nanomaterial simulations, with specialized support for phonon calculations, reaction pathways, and time-dependent phenomena.

Capabilities

PWscf calculations
Phonon calculations (DFPT)
NEB reaction pathway modeling
Time-dependent DFT
Pseudopotential library management
Wannier function analysis

Usage Guidelines

QE Calculation Workflow

Input Preparation
- Generate input files
- Select pseudopotentials
- Set k-point grids
Calculation Types
- SCF for ground state
- Phonon for vibrational
- NEB for barriers
Post-Processing
- Extract band structure
- Calculate Wannier functions
- Analyze phonon dispersions

Process Integration

DFT Calculation Pipeline for Nanomaterials
Multiscale Modeling Integration

Input Schema

{
  "structure_file": "string",
  "calculation": "scf|relax|nscf|bands|phonon|neb",
  "ecutwfc": "number (Ry)",
  "ecutrho": "number (Ry)",
  "kpoints": {"grid": [3, 3, 3], "shift": [0, 0, 0]}
}

Output Schema

{
  "total_energy": "number (Ry)",
  "fermi_energy": "number (eV)",
  "forces": [{"atom": "number", "force": []}],
  "phonon_frequencies": ["number (cm-1)"],
  "neb_barrier": "number (eV)",
  "wannier_centers": [{"orbital": "string", "center": []}]
}

Signals

GitHub stars: 2k
Forks: 113
Last commit: Sep 2026

Advanced

Item type: skill
Key: quantum-espresso-executor
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter