ABSTRACT
Efforts to optimize known materials and enhance their performance are ongoing, driven by the advancements resulting from the discovery of novel functional materials. Traditionally, the search for and optimization of functional materials has relied on the experience and intuition of specialized researchers. However, materials informatics (MI), which integrates materials data and machine learning, has frequently been used to realize systematic and efficient materials exploration without depending on manual tasks. Nonetheless, the discovery of new materials using MI remains challenging. In this study, we propose a method for the discovery of materials outside the scope of existing databases by combining MI with the experience and intuition of researchers. Specifically, we designed a two-dimensional map that plots known materials data based on their composition and structure, facilitating researchers' intuitive search for new materials. The materials map was implemented using an autoencoder-based neural network. We focused on the conductivity of 708 lithium oxide materials and considered the correlation with migration energy (ME), an index of lithium-ion conductivity. The distribution of existing data reflected in the materials map can contribute to the development of new lithium-ion conductive materials by enhancing the experience and intuition of material researchers.
ABSTRACT
Development of metal-anode rechargeable batteries is a challenging issue. Especially, magnesium rechargeable batteries are promising in that Mg metal can be free from dendrite formation upon charging. However, in case of oxide cathode materials, inserted magnesium tends to form MgO-like rocksalt clusters in a parent phase even with another structure, which causes poor cyclability. Here, a design concept of high-performance cathode materials is shown, based on: i) selecting an element to destabilize the rocksalt-type structure and ii) utilizing the defect-spinel-type structure both to avoid the spinel-to-rocksalt reaction and to secure the migration path of Mg cations. This theoretical and experimental work substantiates that a defect-spinel-type ZnMnO3 meets the above criteria and shows excellent cycle performance exceeding 100 cycles upon Mg insertion/extraction with high potential (≈2.5 V vs Mg2+ /Mg) and capacity (≈100 mAh g-1 ). Thus, this work would provide a design guideline of cathode materials for various multivalent rechargeable batteries.
