![]() ![]() Mismatch adopted in their study worked as the screening criterion. 35 The volume change during the charge–discharge cycle and planer That could prolong the cycle characteristics. (DFT) calculations has been applied to co-substituted LiFePO 4 cathode materials, and it successfully found element combinations On a high-throughput screening combined with density functional theory 34įocusing on the cycle performance of LIBs, Successfully to explore cathode coating materials, 33 and new cathodes with better capacity and thermal stability. In battery materials, AIMI approaches have been used (AIMI), although computationally proposed candidates should be verifiedĮxperimentally. This may be called “ab initio materials informatics” Learning-based prediction models, thereby tackling the exhaustive Simulations can satisfactorily generate data to construct machine In most cases regarding electronic properties, ab initio (e.g., bioinformatics), computational approaches are useful for generating Properties is generally unavailable unlike in other research areas 29− 35 Since a sufficiently large amount of experimental data on material There are a number of successful MI studies that have explored new Paradigm in materials science combined with information and data science. Problem is materials informatics (MI), 26− 28 a recently emerging One of the most promising solutions to the above This is because such an exhaustive search based on experiments requiresĮnormous amounts of time and high costs for the synthesis of candidate However, we cannot straightforwardly establish an experimental verificationĮven for binary substitutions having a huge number of possible combinations. It is really unclear if such a synergistic effect emerges. This is a commonly used strategy for improving the battery performances.Ī situation may occur, however, where a combination of “no-good”Įlements has the potential of improving the performance. Good” elements come together to tune the corresponding characteristics. Note that Co and Al are, respectively, known to improve the Used cathode material, has prolonged the cycle life compared to LNO Of Ni sites in LNO with Co and Al, Li(NiCoAl)O 2, a commercially Has fewer cycle characteristics than LCO. 3− 18 For example, consider LiNiO 2 (LNO), 19− 54 which is known to have a higherĬapacity and lower cost than LiCoO 2 (LCO). A practical solutionįor improving the performance is called “atomic substitution”. Thus, its development has recently attracted much attentionįrom the viewpoint of industrial applications. In LIBs is one of the most important factors that determine the battery Mechanism of the crystal structure change.īatteries (LIBs) have a high-voltage and high-capacityĪnd hence are widely used as secondary batteries for mobile devicesĪnd hybrid/electric cars. Propose a guideline for the binary substitutions by elucidating the We conclude that the synergy neverĮmerges from a common strategy restricted to combinations of “good”Įlements that individually improve the performance. Actually, by searching onlyĤ% of all of the combinations, our AIMI approach discovered two promisingĬombinations, Cr–Mg and Cr–Re, whereas each atom itself Search, we rely on Bayesian optimization. If we target the full substitution space, full simulations are infeasibleĮven for all binary combinations. Strongly correlates with less structural change during the charge–dischargeĬycles the latter can be used for evaluating the former. According to our previous study, a higher cycle performance Substitutions by an ab initio simulation-based materials informatics We explore LiNiO 2-based cathode materials with two-element ![]()
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