# hea-bench

> hea-bench — dfieser-hea-bench. Use this tool when you need to calculate and predict the properties of high-entropy alloys (HEAs) and high-entropy oxides, solving problems in materials science and phase prediction. It takes input parameters such as composition and outputs values like mixing entropy, atomic-size mismatch, and VEC. Use hea-bench in research and development contexts where predicting phase formation and stability of complex alloys is crucial.

Canonical page: https://skillsregistry.net/skills/dfieser-hea-bench  
JSON: https://api.skillsregistry.net/v1/skills/dfieser-hea-bench

## Description

Free high-entropy alloy (HEA) and high-entropy oxide calculator: mixing entropy, atomic-size mismatch, VEC, Miedema enthalpy, and the canonical empirical phase-prediction rules. Python library, browser app, desktop app, and MCP server.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/dfieser/hea-bench)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "dfieser-hea-bench"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dfieser-hea-bench` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dfieser-hea-bench/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt
