fig8

Machine learning descriptors for crystal materials: applications in Ni-rich layered cathode and lithium anode materials for high-energy-density lithium batteries

Figure 8. Crystal descriptors applied in MLFF for atomic simulation of lithium anode materials. (A) Schema of DeepMD and MTP potential, adapted with permission[115,116], Copyright 2022, Wiley-VCH and Copyright 2023, Elsevier; (B) Lithium dendrite self-healing simulation pairs with experimental observations, adapted with permission[117], Copyright 2022, Wiley-VCH; (C) Li-Cu surface simulated by MLFF, adapted with permission[118], Copyright 2022, Wiley-VCH; (D) Large-scale molecular dynamics simulations of Li dendrite growth under different external pressures were performed with a MTP ML force field. External pressure was found to promote the process of Li self-healing. This figure is quoted with permission[116], Copyright 2023, Elsevier. MTP: Moment tensor potential; MLFF: machine learning force fields; ML: machine learning.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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