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Introducing multiplicity and variation into the components of MOFs are fascinating demonstrations of reticular chemistry. In this Review, variances in the framework backbone, functionality and metal, and how this variance creates unique sequences of chemical information, are highlighted. Anisotropy in the MOFs is imposed by the variance and realized along a specific direction. See Xu et al.
Batteries, as complex materials systems, pose unique challenges for the application of machine learning. Although a shift to data-driven, machine learning-based battery research has started, new initiatives in academia and industry are needed to fully exploit its potential.
Collagen subtypes contribute to the function of many tissues, but most studies on collagen focus on one or two subtypes only. This Review surveys the roles of collagen subtypes and crosslinks, their structure–function relationships and the possibility of using the resulting insight to engineer better neotissues.
When single layers of 2D materials are stacked on top of one another with a small twist, the resulting moiré pattern introduces new electronic properties. This Review surveys and compares the modelling techniques used in this emerging field of twistronics.
Introducing multiplicity and variation into the components of metal–organic frameworks has emerged as new fascinating directions in reticular chemistry. In this Review, the variances in the framework backbone, functionality and metal, and their leading to sequences of chemical information, are highlighted. Anisotropy in these structures is imposed by the variance and realized along a specific direction.