Data-driven study of the enthalpy of mixing in the liquid phase Article Swipe
Guillaume Deffrennes
,
Bengt Hallstedt
,
Taichi Abe
,
Quentin Bizot
,
Evelyne Fischer
,
Jean‐Marc Joubert
,
Kei Terayama
,
Ryo Tamura
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.11004
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.11004
The enthalpy of mixing in the liquid phase is a thermodynamic property reflecting interactions between elements that is key to predict phase transformations. Widely used models exist to predict it, but they have never been systematically evaluated. To address this, we collect a large amount of enthalpy of mixing data in binary liquids from a review of about 1000 thermodynamic evaluations. This allows us to clarify the prediction accuracy of Miedema's model which is state-of-the-art. We show that more accurate predictions can be obtained from a machine learning model based on LightGBM, and we provide them in 2415 binary systems. The data we collect also allows us to evaluate another empirical model to predict the excess heat capacity that we apply to 2211 binary liquids. We then extend the data collection to ternary metallic liquids and find that, when mixing is exothermic, extrapolations from the binary systems by Muggianu's model systematically lead to slight overestimations of roughly 10% close to the equimolar composition. Therefore, our LightGBM model can provide reasonable estimates for ternary alloys and, by extension, for multicomponent alloys. Our findings extracted from rich datasets can be used to feed thermodynamic, empirical and machine learning models for material development.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2406.11004
- https://arxiv.org/pdf/2406.11004
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4399794773Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2406.11004Digital Object Identifier
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Data-driven study of the enthalpy of mixing in the liquid phaseWork title
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preprintOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-06-16Full publication date if available
- Authors
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Guillaume Deffrennes, Bengt Hallstedt, Taichi Abe, Quentin Bizot, Evelyne Fischer, Jean‐Marc Joubert, Kei Terayama, Ryo TamuraList of authors in order
- Landing page
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https://arxiv.org/abs/2406.11004Publisher landing page
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https://arxiv.org/pdf/2406.11004Direct link to full text PDF
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2406.11004Direct OA link when available
- Concepts
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Enthalpy of mixing, Mixing (physics), Enthalpy, Phase (matter), Thermodynamics, Materials science, Liquid phase, Physics, Chemistry, Organic chemistry, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| abstract_inverted_index.extension, | 176 |
| abstract_inverted_index.prediction | 67 |
| abstract_inverted_index.reasonable | 169 |
| abstract_inverted_index.reflecting | 12 |
| abstract_inverted_index.exothermic, | 141 |
| abstract_inverted_index.predictions | 80 |
| abstract_inverted_index.composition. | 162 |
| abstract_inverted_index.development. | 199 |
| abstract_inverted_index.evaluations. | 60 |
| abstract_inverted_index.interactions | 13 |
| abstract_inverted_index.thermodynamic | 10, 59 |
| abstract_inverted_index.extrapolations | 142 |
| abstract_inverted_index.multicomponent | 178 |
| abstract_inverted_index.systematically | 35, 150 |
| abstract_inverted_index.thermodynamic, | 191 |
| abstract_inverted_index.overestimations | 154 |
| abstract_inverted_index.transformations. | 22 |
| abstract_inverted_index.state-of-the-art. | 74 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.10487038 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |