phonopy

Orchestrate phonopy workflows for band structure, DOS, and thermal properties.

124|25|Updated Feb 20, 2026

Search Tags:#workflow #band-structure #dos #phonopy #displacement #forces #phonon

Ready to run

npx skills add https://github.com/jinzhezenggroup/computational-chemistry-agent-skills --skill phonopy

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: phonopy
Source: https://github.com/jinzhezenggroup/computational-chemistry-agent-skills/tree/main/analysis/phonopy
Command: npx skills add https://github.com/jinzhezenggroup/computational-chemistry-agent-skills --skill phonopy

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

General orchestration of phonon workflows by coordinating displacement generation, force collection, and phonon analysis across multiple backends, enabling backend-agnostic phonopy tasks.

Core Features & Use Cases

Generate displaced supercells for phonon calculations.
Collect and assemble forces from backend engines and build FORCE_SETS or force constants.
Analyze phonon properties (band structure, density of states, thermal quantities) with support for different force providers (DFT or MLFF).
Provide clear handoffs to backend-specific submission or analysis steps when needed.

Quick Start

Provide an initial structure and a backend for force evaluation, then generate displacements and run phonon analysis with phonopy.

Frequently Asked Questions about phonopy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I calculate phonon band structure and DOS using different force calculation backends?▼

To calculate phonon band structure and DOS, this workflow orchestrates displacement generation and force collection across backend engines like VASP, QE, or ML force fields, assembling the required force constants for phonopy analysis.

Can I use machine learning force fields instead of DFT for phonon property calculations?▼

Yes, you can use machine learning force fields for phonon property calculations. The workflow supports different force providers, allowing you to collect forces from MLFF backends to build FORCE_SETS for analyzing thermal quantities and density of states.

What is needed to generate displaced supercells for phonopy calculations?▼

Generating displaced supercells requires a valid initial crystal structure, a chosen force-provider backend, and correctly configured supercell and displacement settings to ensure accurate force collection for the phonon workflow.

How do I build FORCE_SETS from VASP or Quantum Espresso outputs for phonon analysis?▼

You can build FORCE_SETS by generating displaced supercells, submitting them to backend engines like VASP or QE, and using the workflow to collect and assemble the resulting forces into the required phonopy input format.

Does phonon workflow orchestration validate data and report assumptions for thermal property calculations?▼

Phonon workflow orchestration validates data and reports assumptions during thermal property calculations. It ensures correctly configured supercell and displacement settings before applying phonopy analysis to your material's displacement data.

When should I use a backend-agnostic phonon workflow instead of direct phonopy scripts?▼

Use a backend-agnostic phonon workflow when coordinating displacement generation, force collection, and phonon analysis across multiple DFT or MLFF engines, providing clear handoffs to backend-specific submission steps when needed.