A Solution-Processable High-Modulus Crystalline Artificial Solid Electrolyte Interphase for Practical Lithium Metal Batteries
ADVANCED ENERGY MATERIALS
View details for DOI 10.1002/aenm.202201025
View details for Web of Science ID 000817818300001
Correlative image learning of chemo-mechanics in phase-transforming solids.
Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (for example, due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs the chemo-mechanical expansion in solids. Here we developed a generalizable, physically constrained image-learning framework to algorithmically learn the chemo-mechanical constitutive law at the nanoscale from correlative four-dimensional scanning transmission electron microscopy and X-ray spectro-ptychography images. We demonstrated this approach on LiXFePO4, a technologically relevant battery positive electrode material. We uncovered the functional form of the composition-eigenstrain relation in this two-phase binary solid across the entire composition range (0≤X≤1), including inside the thermodynamically unstable miscibility gap. The learned relation directly validates Vegard's law of linear response at the nanoscale. Our physics-constrained data-driven approach directly visualizes the residual strain field (by removing the compositional and coherency strain), which is otherwise impossible to quantify. Heterogeneities in the residual strain arise from misfit dislocations and were independently verified by X-ray diffraction line profile analysis. Our work provides the means to simultaneously quantify chemical expansion, coherency strain and dislocations in battery electrodes, which has implications on rate capabilities and lifetime. Broadly, this work also highlights the potential of integrating correlative microscopy and image learning for extracting material properties and physics.
View details for DOI 10.1038/s41563-021-01191-0
View details for PubMedID 35177785
Correlative analysis of structure and chemistry of LixFePO(4) platelets using 4D-STEM and X-ray ptychography
2022; 52: 102-111
View details for DOI 10.1016/j.mattod.2021.10.031
View details for Web of Science ID 000840325900010
Molecular design for electrolyte solvents enabling energy-dense and long-cycling lithium metal batteries
View details for DOI 10.1038/s41560-020-0634-5
View details for Web of Science ID 000542060100001