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Open access Sep 2026

Discovery of Multicomponent Invar Materials With Low Thermal Expansion, High Curie Temperature, and Superior Phase Stability Assisted by Active Learning.

Zero thermal expansion (ZTE) materials provide exceptional dimensional stability under temperature fluctuations, making them indispensable for high-precision instrumentation and extreme environments. However, their natural scarcity, combined with the vast compositional space in multicomponent systems, renders tradition...

Song Yang, Jing-Han Li, Wan-Da Yang et al. · 0 citations
Aug 2026

Interpretable Machine Learning Framework Deciphers the Role of Local Environment of High‐Entropy Intermetallic Compounds for Alkaline Hydrogen Evolution Reaction

The application of high‐entropy intermetallic (HEI) compounds in the field of catalysis has attracted widespread attention, but their huge material space seriously hinders experimental exploration. Herein, we for the first time reported the efficient design, screening, and prediction of a great deal of high‐perform...

Hao Deng, Li-Ming Yang · 0 citations
Open access Sep 2026

First-principles and machine-learning-guided study of 65 Sc-based quaternary Heusler alloys with high thermoelectric performance and promising optoelectronic properties

In this work, 65 Sc-based quaternary Heusler alloys with 18 valence electrons are systematically investigated by density functional theory in search of new semiconducting materials with multifunctional properties. Structural optimization identifies Y-type (I) and Y-type (II) as the dominant ground-state configurations,...

Miloudi Mohamed Esseddik, Salem Hebri, Imad Khaled Khaled Bensafa et al. · 0 citations
Aug 2026

Machine Learning‑Assisted Development of High-Performance Na0.5Bi2.5Nb2O9 Piezoceramics via Synergistic Multisite Codoping

Bismuth layer-structured ferroelectrics (BLSFs) are critical candidates for high-temperature piezoelectric applications, yet their inherently low piezoelectric activity (d33) restricts their practical implementation. In this study, a machine-learning-guided strategy was employed to rationally design multisite Li+/Ce3...

Chun Guo, Yan-Yan Zhang, Zhi-Yong Zhou · 0 citations
Preprint Aug 2026

Machine-Learning-Accelerated Metallene Stabilization from High-Throughput Sandwich Modeling

Metallenes have appealing properties, but stabilizing them in a monolayer phase poses challenges for their synthesis. A recent experiment showed that the van der Waals squeezing method can stabilize certain metallenes in a MoS2 sandwich. This pioneering work motivates systematic studies, but such studies are experiment...

Mohammad Bagheri, Pekkar Koskinen · 0 citations
Open access Aug 2026

Machine Learning Unveils Isolated‐Surrounded Pt Motifs in High‐Entropy Alloys for Superior Low‐Temperature Ammonia Oxidation

The sluggish kinetics of the ammonia oxidation reaction constitute a critical bottleneck in the development of low‐temperature direct ammonia fuel cells. High‐entropy alloys (HEAs), owing to their diverse active sites, have emerged as promising catalysts. However, their vast compositional space makes traditional quan...

Shangfeng Jiang, Ting Tao, Kexiang Guo et al. · 1 citation

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