An iterative optimization of interstitial chemical potential under partial equilibrium assumption produces thermodynamically consistent interstitial concentration maps from substitutional microscopy data and bulk measurements.
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Bayesian optimization with Gaussian process models finds near-optimal copper slag, limestone, and Portland cement blends meeting strength, cost, and emissions targets in 2-6 iterations from 10 initial points.
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Iterative Thermodynamic Augmentation of Spatially Resolved Analytic Microscopy for Fast-Diffusing Solutes
An iterative optimization of interstitial chemical potential under partial equilibrium assumption produces thermodynamically consistent interstitial concentration maps from substitutional microscopy data and bulk measurements.
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Active learning-based Bayesian optimization in the realm of copper slag-blended cement systems
Bayesian optimization with Gaussian process models finds near-optimal copper slag, limestone, and Portland cement blends meeting strength, cost, and emissions targets in 2-6 iterations from 10 initial points.