In silico design of microporous polymers for chemical separations and storage. (June 2022)

• Record Type: Journal Article
• Authors: Anstine, Dylan M; Sholl, David S; Siepmann, Joern Ilja; Snurr, Randall Q; Aspuru-Guzik, Alán; Colina, Coray M
• Is Part Of: Current opinion in chemical engineering. Volume 36(2022)
• Publication Date: 2022-06
• Subjects: Chemical engineering -- Periodicals; Chemical engineering; Periodicals; 660.05
• DOI: 10.1016/j.coche.2022.100795
• Languages: English
• ISSNs: 2211-3398

Abstract

Graphical abstract: Highlights: Atomistic modeling techniques for microporous feature analysis. In silico predictions of adsorption with flexible frameworks. Data-driven methods are positioned to accelerate PIM discovery and design. Abstract : Polymers of intrinsic microporosity (PIMs) are a family of materials with potential to be effective and scalable solutions for challenging adsorbent and membrane applications. The broad range of repeat unit chemistry, microporous structural features, and polymer processing makes exploration of the expansive PIM design space inefficient via chemical and materials intuition alone. Computational techniques such as molecular simulations and machine learning can provide a leap in capabilities to address this polymer design challenge and will be central to the future development of PIMs. We highlight recent microporous material studies that arrived at key results by employing computational techniques and provide our perspective on the prospects for in silico design and development of PIMs.