HEA: High Entropy Alloys

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About this app

HEA computes the design parameters that describe a high-entropy alloy, and shows you where every one of them came from. Enter a formula and get configurational entropy, enthalpy of mixing, atomic-size difference, valence-electron concentration and the rest, each with the equation that produced it, the paper it was published in, and a plain statement of where it stops being reliable.

Built for HEA and MPEA researchers, materials students, and alloy designers.

Every number shows its work

The equation, typeset properly
The full citation: author, journal, year, pages
A plain note on what the correlation assumes and where it breaks down
A refusal when the bundled data cannot honestly support the number
That last one is the point. Enter an element the bundled table has no metallic radius for, and the atomic-size difference is withheld with the missing element named, not estimated. A missing binary mixing-enthalpy pair withholds the enthalpy but leaves the size difference alone. Configurational entropy needs no element data, so it stays available. A withheld number is honest. A silently wrong one is not.

Eight design parameters

dSmix, configurational entropy of mixing (Yeh 2004)
dHmix, enthalpy of mixing from Miedema binary terms (Takeuchi and Inoue 2005)
delta, atomic-size difference (Zhang 2008)
VEC, valence-electron concentration (Guo 2011)
Omega, the solid-solution parameter (Yang and Zhang 2012)
dChi, electronegativity difference
Tm, melting point by rule of mixtures
rho, density by rule of mixtures
Three published rules, side by side Yang-Zhang Omega-delta, the Zhang enthalpy-size window, and Guo's VEC structure rule are applied independently and shown with their individual verdicts. When one rule cannot be evaluated it says so rather than guessing a pass or a fail. These are screening rules, not a phase diagram.

A reality check against the literature Every result is compared with what has actually been reported for that element set: 9,762 records drawn from published papers, with the reported phases and a source DOI on every one. Note that this set was extracted from the literature by a language model rather than curated by hand, at roughly 80% accuracy on phase identification, so the app presents it as evidence to verify rather than as fact. Data from Chizhevskiy et al., High Entropy Alloys Database generated with Large Language Model, Scientific Data 13:612 (2026), Mendeley 10.17632/j75v9bbbjz, used under CC BY 4.0.

Learn, if the field is new to you A six-section primer covering what a high-entropy alloy is, the four core effects, how to read each design parameter, how the parameters become a phase prediction, a glossary, and further reading. Read it once and the results screen makes more sense.

Reference, always to hand

Every equation the app computes, typeset with its citation
The empirical rules that read them, with their thresholds stated
22 elements with per-field sources for every property
Atomic percent or molar ratio, kelvin or Celsius throughout
Private by design

No account, no sign-up
No ads, no tracking, no analytics, no data collection
No internet permission at all. The app cannot make a network call, even by accident.
Works in a lab, a lecture hall, or on a plane
Please note: HEA gives estimates from published empirical parameters, for orientation and education. They are screening rules, not a phase diagram and not a specification. Confirm any candidate alloy experimentally before relying on it.

What’s new

What's New (Release Notes), v1.0.0
Welcome to HEA, a high-entropy-alloy design tool that shows its work.

Eight design parameters from any formula: dSmix, dHmix, delta, VEC, Omega, dChi, Tm and rho
Every parameter with its typeset equation, its full citation, and a plain note on its limits
Atomic percent or molar ratio, kelvin or Celsius throughout
A reality check against 9,762 reported alloys from the literature, each with its source DOI