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Phase diagrams offer substantial predictive power for materials synthesis by identifying the stability regions of target phases. However, thermodynamic phase diagrams do not offer explicit information regarding the kinetic competitiveness of undesired by-product phases. Here we propose a quantitative and computable thermodynamic metric to identify synthesis conditions under which the propensity to form kinetically competing by-products is minimized. We hypothesize that thermodynamic competition is minimized when the difference in free energy between a target phase and the minimal energy of all other competing phases is maximized. We validate this hypothesis for aqueous materials synthesis through two empirical approaches: first, by analysing 331 aqueous synthesis recipes text-mined from the literature; and second, by systematic experimental synthesis of LiIn(IO₃)₄and LiFePO₄across a wide range of aqueous electrochemical conditions. Our results show that even for synthesis conditions that are within the stability region of a thermodynamic Pourbaix diagram, phase-pure synthesis occurs only when thermodynamic competition with undesired phases is minimized.

The development of a materials synthesis route is usually based on heuristics and experience. A possible new approach would be to apply data-driven approaches to learn the patterns of synthesis from past experience and use them to predict the syntheses of novel materials. However, this route is impeded by the lack of a large-scale database of synthesis formulations. In this work, we applied advanced machine learning and natural language processing techniques to construct a dataset of 35,675 solution-based synthesis procedures extracted from the scientific literature. Each procedure contains essential synthesis information including the precursors and target materials, their quantities, and the synthesis actions and corresponding attributes. Every procedure is also augmented with the reaction formula. Through this work, we are making freely available the first large dataset of solution-based inorganic materials synthesis procedures.

Li‐excess disordered rocksalts (DRXs) are emerging as promising cathode materials for Li‐ion batteries due to their ability to use earth‐abundant transition metals. In this work, a new strategy based on partial Li deficiency engineering is introduced to optimize the overall electrochemical performance of DRX cathodes. Specifically, by using Mn‐based DRX as a proof‐of‐concept, it is demonstrated that the introduction of cation vacancies during synthesis (e.g., Li_1.3‐xMn²⁺_0.4‐xMn³⁺_xNb_0.3O_1.6F_0.4,x = 0, 0.2, and 0.4) improves both the discharge capacity and rate performance due to the more favored short‐range order in the presence of Mn³⁺. Density functional theory calculations and Monte Carlo simulations, in combination with spectroscopic tools, reveal that introducing 10% vacancies (Li_1.1Mn²⁺_0.2Mn³⁺_0.2Nb_0.3O_1.6F_0.4) enables both Mn²⁺/Mn³⁺redox and excellent Li percolation. However, a more aggressive vacancy doping (e.g., 20% vacancies in Li_0.9Mn³⁺_0.4Nb_0.3O_1.6F_0.4) impairs performance because it induces phase separation between an Mn‐rich and a Li‐rich phase.

Relating the synthesis conditions of materials to their functional performance has long been an experience‐based trial‐and‐error process. However, this methodology is not always efficient in identifying an appropriate protocol and can lead to overlooked opportunities for the performance optimization of materials through simple modifications of the synthesis process. In this work, the authors systematically track the structural evolution in the synthesis of a representative disordered rock salt (a promising next‐generation Li‐ion cathode material) at the scale of both the long‐range crystal structure and the short‐range atomic structure using various in situ and ex situ techniques, including transmission electron microscopy, X‐ray diffraction, and pair distribution function analysis. An optimization strategy is proposed for the synthesis protocol, leading to a remarkably enhanced capacity (specific energy) of 313 mAh g⁻¹(987 Wh kg⁻¹) at a low rate (20 mA g⁻¹), with a capacity of more than 140 mAh g⁻¹retained even at a very high cycling rate of 2000 mA g⁻¹. This strategy is further rationalized using ab initio calculations, and important opportunities for synthetic optimization demonstrated in this study are highlighted.