Domain oriented universal machine learning potential enables fast exploration of chemical space of battery electrolytes. [PDF]
Wang F, Tang YH, Ma ZB, Jin YC, Cheng J.
europepmc +1 more source
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán +5 more
wiley +1 more source
Construction of PANoptosis-Inhibiting Carbonized Polymer Dots via Machine Learning Potential for Mitigating Chemodrug-Induced Nephrotoxicity. [PDF]
Liu X +8 more
europepmc +1 more source
An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut +16 more
wiley +1 more source
The interlocking process in molecular machines explained by a combined approach: the nudged elastic band method and machine learning potential. [PDF]
Peña-Zarate L, Vela A, Tiburcio J.
europepmc +1 more source
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran +6 more
wiley +1 more source
Correction to "Machine Learning Potential Analysis of Structural Transition in Cu and Ag Nanoparticles: From Icosahedral to Face-Centered Cubic". [PDF]
Yang Y, Han J, Viñes F, Illas F.
europepmc +1 more source
Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari +3 more
wiley +1 more source
Decoding local framework dynamics in the ultra-small pore MOF MIL-120(Al) CO<sub>2</sub> adsorbent using machine-learning potential. [PDF]
Fan D +4 more
europepmc +1 more source
A Dislocation Perspective on Strength and Toughness in Ceramics
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley +1 more source

