Nature Reviews Materials paper - Nanyang Asst/P Kedar Hippalgaonkar
As materials researchers increasingly embrace machine-learning (ML) methods, it is natural to wonder what lessons can be learned from other fields undergoing similar developments. In this Review, we comparatively assess the evolution of applied ML in materials research, gameplaying and robotics. We observe ML being integrated into each field in three phases: first into discrete hardware and software tools (toolset integration); second across different steps in a workflow (workflow integration); and third through the incorporation, generation and representation of generalizable knowledge beyond any one study (knowledge integration). We identify transferrable lessons from gameplaying and robotics to materials research, including adaptive and accessible automation, the gamification of grand challenges to focus community efforts on specific workflow integrations and motivate benchmarks and canonical datasets, and the adoption of hybrid (data-based and model-based) algorithms that combine domain expertise and current learning to economically address high-complexity tasks. We identify opportunities for researchers from different fields to collaborate, including novel ways to represent and integrate a rich but heterogeneous corpus of knowledge (such as heuristics, physical laws, literature or data) with ML algorithms to create new knowledge, and safe and equitable deployment of technologies with societally beneficial outcomes.
The Review Article can be found via the link here: https://www.nature.com/articles/s41578-022-00513-1
About Nature Reviews Materials
Nature Reviews Materials is an online-only journal for the weekly publication of Reviews, Perspectives and Comments in all scientific disciplines within materials science. It aims to cover the making, measuring, modelling and manufacturing of materials – thus, looking at materials science throughout the pipeline of laboratory discovery to functional device. Reviews aim to be balanced and objective analyses of the selected topic – with descriptions of relevant scientific literature and discussions that are easy to grasp for recent graduates in any materials-science related discipline, as well as informing principal investigators and industry-based research scientists of the latest advances. Reviews should provide the authors' insight into future directions and their opinion of the major challenges faced by researchers in the field. The journal has a 2021 impact factor of 76.679.