Advanced and explainable machine learning model for prediction of surface roughness of tempered steel AISI 1060. [PDF]
Ziyad F +7 more
europepmc +1 more source
ABSTRACT The derived demand for the increased demand for meat and dairy products is clearly observed in the fast‐paced growth of the Indian feed industry and its increased demand for agricultural commodities (e.g., corn, soybean, rice, wheat, broken rice, millet, etc.) as feed ingredients.
Dwiti Baruah Thapa +2 more
wiley +1 more source
The Monomeric Conformational Ensembles of Aβ40 and Aβ42 Encode Their Differential Amyloid Aggregation Propensity. [PDF]
Cadenelli I +5 more
europepmc +1 more source
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source
An entropy-initiated coupled-trait ODE framework for modeling longitudinal cohort dynamics. [PDF]
Rodriguez AM.
europepmc +1 more source
Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei +9 more
wiley +1 more source
The Effect of Tempering Temperature on the Microstructure and Properties of a Novel High-Temperature Bearing Steel. [PDF]
Zheng K +7 more
europepmc +1 more source
Forming Feasibility of High-Strength and Toughness Drill Pipe Joint Based on Plastic Deformation Mechanism. [PDF]
Cao J +5 more
europepmc +1 more source
Unraveling insights for ion transport enhancement by metal-organic framework-5 in polyethylene oxide and polyvinylidene fluoride electrolytes: classical molecular dynamics and metadynamics simulations. [PDF]
Nazar F, Moin ST.
europepmc +1 more source

