neb

Generate ASE NEB workflow scripts for reaction-path optimization between specified states.

124|25|Updated Feb 20, 2026
One-click install
npx skills add https://github.com/jinzhezenggroup/computational-chemistry-agent-skills --skill neb
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: neb
Source: https://github.com/jinzhezenggroup/computational-chemistry-agent-skills/tree/main/atomistic-workflows/ase/ase-workflows/neb
Command: npx skills add https://github.com/jinzhezenggroup/computational-chemistry-agent-skills --skill neb

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prepare ASE NEB workflow tasks with backend-agnostic controls to perform reaction-path optimization between specified states, enabling consistent image construction, spring settings, and convergence criteria.

Core Features & Use Cases

  • Backend-agnostic NEB preparation: generates a complete NEB workflow script with image setup, optimizer, springs, and convergence settings.
  • Explicit control: supports explicit initial/final states, interpolation policy, climbing-image options, and spring-constant strategies.
  • Use Case: a chemist wants to map a reaction pathway between two states using a custom backend adapter and calibrated convergence thresholds, producing ready-to-run NEB scripts.

Quick Start

Provide initial and final structures, select a backend adapter, specify the number of images, and configure the optimizer and convergence policy to generate the NEB workflow.

Frequently Asked Questions about neb

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

FAQPage Schema
How do I prepare an ASE NEB workflow for reaction-path optimization?

To prepare an ASE NEB workflow, you provide initial and final structures, select a backend adapter, specify the number of images, and configure the optimizer and convergence policy to generate a ready-to-run NEB script.

What is backend-agnostic NEB image interpolation and when do I need it?

Backend-agnostic NEB image interpolation is the process of constructing intermediate states between initial and final structures independent of the computational backend, needed when mapping reaction pathways using custom adapters and calibrated convergence thresholds.

Can I use a custom backend adapter with ASE NEB for climbing-image optimization?

Yes, you can use a custom backend adapter with ASE NEB by selecting your adapter during workflow preparation and explicitly enabling the optional climbing-image setting along with your spring-constant and convergence policies.

How do I set spring constants and convergence criteria for a reaction-path optimization task?

You set spring constants and convergence criteria for reaction-path optimization by explicitly defining the spring-constant strategy and convergence policy as input parameters when generating the backend-agnostic ASE NEB workflow script.

What's the best way to generate NEB scripts across different computational backends?

The best way to generate NEB scripts across different computational backends is using a backend-agnostic adapter that standardizes image construction, interpolation policy, spring settings, and convergence criteria into one consistent workflow script.

What structures do I need to provide for ASE NEB workflow generation?

You need to provide explicit initial and final structures to generate an ASE NEB workflow, as these specified states are required to construct the interpolated images for the reaction-path optimization.