Mo-Re-W alloys for high temperature applications: Phase stability, elasticity, and thermal property insights via multi-cell Monte Carlo and machine learning

The increasing demand for materials capable of withstanding high temperatures and harsh environments necessitates the discovery of advanced alloys.This study introduces a computational routine to predict solid-state phase stability and calculates elastic constants to determine high temperature viability.With it, machine learning models were trained

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A computationally efficient algorithm to leverage average information REML for (co)variance component estimation in the genomic era

Abstract Background Methods for estimating creative grids quick trim and circle ruler variance components (VC) using restricted maximum likelihood (REML) typically require elements from the inverse of the coefficient matrix of the mixed model equations (MME).As genomic information becomes more prevalent, the coefficient matrix of the MME becomes de

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