# Methods for efficient eutectic screening in CALPHAD databases

https://mdr.nims.go.jp/datasets/8c5c387d-703e-4fe6-b335-cb0a261c8bcd

## File

- [Methods for efficient eutectic screening (Final).pdf](https://mdr.nims.go.jp/filesets/69955a09-da00-4d74-b6be-d5487f015e43/download) ([Detail](https://mdr.nims.go.jp/filesets/69955a09-da00-4d74-b6be-d5487f015e43.md))

## Id

8c5c387d-703e-4fe6-b335-cb0a261c8bcd

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2026-11-08T21:08:28.929114Z

## Updated at

2026-11-09T00:34:28.569574Z

## Published at

2026-11-09T03:35:19.799237Z

## Doi

https://doi.org/10.48505/nims.8711

## First published url

https://doi.org/10.1016/j.calphad.2026.103019

## Date published

2026-11-02

## Recorded date published

2026-12

## Resource type

journal_article

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: Methods for efficient eutectic screening in CALPHAD databases
  title_type: original
  lang: en

## Description

- description: "Eutectic points play a critical role in material science due to their
    low melting points, absence of a solidification range, and formation of unique
    microstructures that enhance properties. However, identifying eutectics in calculated
    ternary and higher-order systems remains computationally challenging due to the
    lack of a well-established screening approach.\r\nThis work addresses this gap
    by developing a general, efficient methodology for efficient eutectic screening
    in multicomponent systems. We first propose and benchmark four CALPHAD-based methods
    for eutectic identification, evaluating their computational speed and reliability.
    We then investigate the potential of combining CALPHAD with machine learning to
    further accelerate the process, leveraging two eutectic properties: (1) eutectics
    are local minima on the liquidus, and (2) they lie at the intersections of primary
    crystallization regions. Active learning surrogate models are employed to interpolate
    CALPHAD data for predicting liquidus and primary crystallization phases, and the
    performance of each approach is evaluated. By benchmarking multiple strategies
    and releasing code for three approaches that enable rapid and reliable eutectic
    screening in high-order systems, this work advances the design of materials such
    as cast alloys, phase change materials, eutectic high entropy alloys, or metallic
    glasses."
  description_type: abstract
  lang: und

## Creator

- name: K. Firdová
  role: author
- name: K.E. Borowski
  role: author
- name: R. Tamura
  role: author
  orcid: https://orcid.org/0000-0002-0349-358X
- name: J.-M. Joubert
  role: author
  orcid: https://orcid.org/0000-0001-7266-1850
- name: G. Deffrennes
  role: author
  orcid: https://orcid.org/0000-0002-3752-2537

## Contact agent



## Publisher

organization: Elsevier BV

## Managing organization



## Keyword

- subject: Eutectic point
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

## Other identifier(s)



## Data origin



## Embargo



## Journal

- title: Calphad
  issn: '03645916'
  volume: '95'
  article_number: '103019'

## Conference



## Related item



## Funding

- funder_name: ANR

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



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## Fileset

- id: 69955a09-da00-4d74-b6be-d5487f015e43
  filename: Methods for efficient eutectic screening (Final).pdf
  content_type: application/pdf
  size: 933396
  md5: 4c62b95eed171d717f2cc911ba006421

## Thumbnail

fileset_id: 69955a09-da00-4d74-b6be-d5487f015e43
filename: Methods for efficient eutectic screening (Final).pdf