This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily understandable, review of general interest to the battery community. It addresses the concepts, approaches, tools, outcomes, and challenges of using AI/ML as an accelerator for the design and optimization of the next generation of batteriesa current hot topic. It intends to create both accessibility of these tools to the chemistry and electrochemical energy sciences communities and completeness in terms of the different battery R&D aspects covered.

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The FAULTS program is a powerful tool for the refinement of diffraction patterns of materials with planar defects. A new release of the FAULTS program is herein presented, together with a number of new capabilities, aimed at improving the refinement process and evolving towards a more user‐friendly approach. These include the possibility to refine multiple sets of single‐crystal profiles of diffuse streaks, the visualization of the model structures, the possibility to add the diffracted intensities from secondary phases as background and the new DIFFaX2FAULTS converter, among others. Three examples related to battery materials are shown to illustrate the capabilities of the program.

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In this work, a new bulk Li 3.6 PO 3.4 N 0.6 crystalline polymorph has been prepared from low-cost precursors, following a simple ball-milling procedure. The densified powder exhibits a conductivity of 5.0 × 10 −6 S cm −1 at 70 °C and an electrochemical stability allowing operation with high-voltage materials up to 5.0 V vs Li/Li + . Stripping and plating of lithium in a symmetric cell demonstrates the forthcoming bulk application of LiPON in electrochemical devices. Widening the use of lithium phosphorus oxynitride compositions to bulk solid-state batteries will have relevant implications because of its unique compatibility with both high-voltage electroactive materials and lithium metal and its low density.

To enhance the safety, cost, and energy density of Li-ion batteries, significant research efforts have been devoted to the search for new positive electrode materials that exhibit high redox potentials and are composed of low-cost, earth-abundant elements. Sulfate chemistry has yielded promising results for iron-based polyanionic electrode materials using the FeIII+/FeII+ redox couple, including the recent discovery of a monoclinic marinite Li2Fe­(SO4)2 phase (3.83 V vs Li+/Li0). Here, we report the ball-milling synthesis and electrochemical properties of a new orthorhombic polymorph of Li2Fe­(SO4)2, which reversibly reacts with lithium through a two-step redox process (3.73 and 3.85 V vs Li+/Li0) with an overall sustained capacity of about 90 mAh/g. Using similar synthesis conditions, the cobalt-, zinc-, magnesium-, and nickel-based orthorhombic analogues were also obtained, though no electrochemical activity was observed for these phases. Overall, our results demonstrate that polymorphism can play a crucial role in the search for new battery electrode materials and emphasize the need to understand and master synthetic control.

The microstructural complexity of Li-rich cathode materials has so far hampered understanding the critical link between size, morphology and structural defects with both capacity and voltage fadings that this family of materials exhibits. Li2MnO3 is used here as a model material to extract reliable structure-property relationships that can be further exploited for the development of high-performing and long-lasting Li-rich oxides. A series of samples with microstructural variability have been prepared and thoroughly characterized using the FAULTS software, which allows quantification of planar defects and extraction of average crystallite sizes. Together with transmission electron microscopy (TEM) and density functional theory (DFT) results, the successful application of FAULTS analysis to Li2MnO3 has allowed rationalizing the synthesis conditions and identifying the individual impact of concurrent microstructural features on both voltage and capacity fadings, a necessary step for the development of high-capacity Li-ion cathode materials with enhanced cycle life.

New materials initially designed for battery electrodes are often of interest for magnetic study, because their chemical compositions include 3d transition metals. We report here on the magnetic properties of marinite phases Li2M(SO4)2 (M = Fe, Co, Mn) and Li1Fe(SO4)2, which all order antiferromagnetically at low temperature. From neutron powder diffraction, we propose a model for their ground-state magnetic structures. The magnetism of marinite Li2M(SO4)2 compounds unambiguously results from super-super-exchange interactions; therefore, these materials can be considered as a model case for which the Goodenough-Kanamori-Anderson rules can be tested.