High-Throughput Bayesian Optimization of Cement-Salt Hydrates Composites for Seasonal Thermochemical Energy Storage
Alessio Mondello, Giulio Barletta, Luca Lavagna, Matteo Fasano, Matteo Pavese, Eliodoro Chiavazzo

TL;DR
This paper demonstrates a high-throughput Bayesian optimization framework to design cement-salt composites for seasonal thermochemical energy storage, achieving significant improvements in energy density and cost-effectiveness.
Contribution
It introduces a Bayesian optimization approach to efficiently explore and optimize cement-salt composite materials for thermochemical energy storage.
Findings
Identified Pareto-optimal cement-salt composites with enhanced energy storage capacity.
Achieved up to fivefold improvement in specific energy over previous materials.
Highlighted cost-effective formulations based on CaCl₂ and Zn(NO₃)₂.
Abstract
Thermochemical energy storage (TCES) based on salt hydrates is a promising route for seasonal heat storage; however, the design of practical sorbent materials remains challenging due to a non-trivial coupling between composition, synthesis feasibility, performance, and cost. Here, focusing on salt-into-matrix cement-based composites, we demonstrate that a high-throughput experimental framework based on Bayesian optimization (BO) can be used to orchestrate the optimization process of composite materials for low-temperature TCES. The explored design space is defined by salt type, salt concentration, water-to-cement ratio, and additive-to-cement ratio, while two competing objectives are pursued in parallel, namely the specific energy and the specific energy cost. The BO-guided campaign identified Pareto-optimal composites based on CaCl, Zn(NO), and LiCl, highlighting the…
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