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HEA Explorer

High-Entropy Alloy design tool. Two endpoints: (1) Compute — calculates thermodynamic parameters (ΔS_mix, atomic size mismatch δ, VEC, Ω parameter, ΔH_mix approximation) from element composition with equiatomic or custom fractions, predicts FCC/BCC phase and solid solution likelihood via Hume-Rothery rules. (2) Screen — searches JARVIS-DFT for multi-element compositions matching the target elements. Built-in database of 47 elements with atomic radii, melting points, VEC, electronegativity, density, and elastic modulus.

Open App

Overview

Data Source

Built-in element property database (47 elements) + JARVIS dft_3d (for composition screening).

Endpoints

POST /hea/compute — Compute HEA parameters

curl -X POST "https://atomgpt.org/hea/compute" \
  -H "Authorization: Bearer sk-XYZ" \
  -H "Content-Type: application/json" \
  -d '{"elements": ["Ti", "V", "Cr", "Mn", "Fe"]}'
Field Type Description
elements list[string] 2–10 element symbols
fractions list[float] Optional molar fractions (default: equiatomic)

Response: composition string, per-element properties, parameters (ΔS_mix, δ%, VEC, Ω, ΔH_mix, Tm_avg, ρ_avg, E_avg), predictions (FCC/BCC/mixed phase, solid solution likelihood, Hume-Rothery checks).

POST /hea/screen — Screen JARVIS-DFT

curl -X POST "https://atomgpt.org/hea/screen" \
  -H "Authorization: Bearer sk-XYZ" \
  -H "Content-Type: application/json" \
  -d '{"elements": ["Ti", "V", "Cr"], "require_all": true, "max_results": 50}'
Field Type Default Description
elements list[string] required Target elements
require_all bool true All elements must be present
min_elements int 2 Minimum number of elements
max_results int 50 Max results

Python Examples

import requests

response = requests.post(
    "https://atomgpt.org/hea/compute",
    headers={"Authorization": "Bearer sk-XYZ", "Content-Type": "application/json"},
    json={"elements": ["Ti", "V", "Cr", "Mn", "Fe"]},
)
data = response.json()
p = data["parameters"]
print(f"{data['composition']}: VEC={p['VEC']}, δ={p['delta_pct']}%, ΔS={p['delta_s_mix_R']}R")
print(f"Phase: {data['predictions']['phase']}, SS likely: {data['predictions']['solid_solution_likely']}")

AGAPI Agent

from agapi.agents import AGAPIAgent
import os
agent = AGAPIAgent(api_key=os.environ.get("AGAPI_KEY"))
response = agent.query_sync("Show hea explorer data")
print(response)

References