Discovery and design of soft polymeric bio-inspired materials with multiscale simulations and artificial intelligence
CX Zhai and TJ Li and HY Shi and JJ Yeo, JOURNAL OF MATERIALS CHEMISTRY B, 8, 6562-6587 (2020).
Materials chemistry is at the forefront of the global "Fourth Industrial Revolution", in part by establishing a "Materials 4.0" paradigm. A key aspect of this paradigm is developing methods to effectively integrate hardware, software, and biological systems. Towards this end, we must have intimate knowledge of the virtual space in materials design: materials omics (materiomics), materials informatics, computational modelling and simulations, artificial intelligence (AI), and big data. We focus on the discovery and design of next-generation bio-inspired materials because the design space is so huge as to be almost intractable. With nature providing researchers with specific guiding principles, this material design space may be probed most efficiently through digital, high-throughput methods. Therefore, to enhance awareness and adoption of digital approaches in soft polymeric bio- inspired materials discovery and design, we detail multiscale simulation techniques in soft matter from the molecular level to the macroscale. We also highlight the unique role that artificial intelligence and materials databases will play in molecular simulations as well as soft materials discovery. Finally, we showcase several case studies that concretely apply computational modelling and simulations for integrative soft bio-inspired materials design with experiments.
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