Bayesian optimization identifies cement-salt hydrate composites achieving up to five times higher specific energy than prior cement-based TCES materials, with LiCl-based formulations reaching 458 kJ/kg.
Coley, Hidenobu Mochigase, Haley K
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Topology-aware large graph representations of polymer chains combined with masked pretraining on unlabeled data reduce prediction error for glass transition temperature by 5.1% compared to repeat-unit baselines.
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High-Throughput Bayesian Optimization of Cement-Salt Hydrates Composites for Seasonal Thermochemical Energy Storage
Bayesian optimization identifies cement-salt hydrate composites achieving up to five times higher specific energy than prior cement-based TCES materials, with LiCl-based formulations reaching 458 kJ/kg.
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It's All Connected: Topology-Aware Structural Graph Encoding Improves Performance on Polymer Prediction
Topology-aware large graph representations of polymer chains combined with masked pretraining on unlabeled data reduce prediction error for glass transition temperature by 5.1% compared to repeat-unit baselines.