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This Perspective explores correlative characterization for bringing together multiple imaging modalities with maps of local chemistry, structure and functional performance to improve our understanding and manufacturing of existing materials and facilitate data-centric materials innovation.
Disorder in two-dimensional materials largely affects their properties and performance. This Perspective discusses disorder sources in graphene and transition metal dichalcogenides, the progress in disorder control, and possible uses of disorder.
This Perspective describes the application of machine learning models in the design, synthesis and characterisation of molecules at different stages in the drug discovery and development process.
