Volume 5, Issue 1 (2025) – 14 articles | Journal of Materials Informatics

Journal of Materials Informatics

ISSN 2770-372X (Online)

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Volume

Volume 5, Issue 1 (2025) – 14 articles

Review

AI in single-atom catalysts: a review of design and applications

Superior single-atom and single-cluster catalysts towards electrocatalytic nitrogen reduction reactions: a theoretical perspective

Research Article

Machine-learning prediction of facet-dependent CO coverage on Cu electrocatalysts

A property-oriented self-decision design strategy of low-alloyed rare earth-free magnesium alloys with a good strength-ductility synergy based on machine learning

PINK: physical-informed machine learning for lattice thermal conductivity

Design of Fe₂Mo@γ-GDY triatomic catalyst for electrocatalytic urea synthesis of N₂ and CO: a theoretical study

Towards mechanical performance paradox and behind thermo-kinetic origins of aluminum alloys with additional solutes (X = Mg, Cu and Si) from atomistic simulations

An optimized strategy for density prediction of intermetallics across varied crystal structures via graph neural network

Interpretable model of dielectric constant for rational design of microwave dielectric materials: a machine learning study

Improved hardness prediction for reduced-activation high-entropy alloys by incorporating symbolic regression and domain adaptation on small datasets

AI-driven design of fluorine-free polymers for sustainable and high-performance anion exchange membranes

A new simple and efficient molecular descriptor for the fast and accurate prediction of log P

Predicting stacking fault energy in austenitic stainless steels via physical metallurgy-based machine learning approaches

Discovering polyimides and their composites with targeted mechanical properties through explainable machine learning

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Committee on Publication Ethics

Portico

Committee on Publication Ethics

Portico

Volume

Volume 5, Issue 1 (2025) – 14 articles

Review

AI in single-atom catalysts: a review of design and applications

Superior single-atom and single-cluster catalysts towards electrocatalytic nitrogen reduction reactions: a theoretical perspective

Research Article

Machine-learning prediction of facet-dependent CO coverage on Cu electrocatalysts

A property-oriented self-decision design strategy of low-alloyed rare earth-free magnesium alloys with a good strength-ductility synergy based on machine learning

PINK: physical-informed machine learning for lattice thermal conductivity

Design of Fe2Mo@γ-GDY triatomic catalyst for electrocatalytic urea synthesis of N2 and CO: a theoretical study

Towards mechanical performance paradox and behind thermo-kinetic origins of aluminum alloys with additional solutes (X = Mg, Cu and Si) from atomistic simulations

An optimized strategy for density prediction of intermetallics across varied crystal structures via graph neural network

Interpretable model of dielectric constant for rational design of microwave dielectric materials: a machine learning study

Improved hardness prediction for reduced-activation high-entropy alloys by incorporating symbolic regression and domain adaptation on small datasets

AI-driven design of fluorine-free polymers for sustainable and high-performance anion exchange membranes

A new simple and efficient molecular descriptor for the fast and accurate prediction of log P

Predicting stacking fault energy in austenitic stainless steels via physical metallurgy-based machine learning approaches

Discovering polyimides and their composites with targeted mechanical properties through explainable machine learning

Actions for 0 selected articles

Committee on Publication Ethics

Portico

Committee on Publication Ethics

Portico

Design of Fe₂Mo@γ-GDY triatomic catalyst for electrocatalytic urea synthesis of N₂ and CO: a theoretical study