CAREER: Introducing synthetic feasibility predictions in large scale computational screening of open-framework materials (OFMs)

Colorado School Of Mines, Golden CO

Investigators

Abstract

Metal-organic frameworks (MOFs) are materials with tunable nanoscale structures that have the potential to revolutionize a wide spectrum of technologies, including catalysis, energy storage, and chemical separations. The proposed research project aims to accelerate the discovery of synthesizable MOFs with tailored properties using advanced computational methods including high-throughput computational screening and machine learning tools. The proposed educational and outreach plan aims to develop research internships for students from underrepresented groups in STEM and to engage a broader audience via interactive web-based activities. The research project would provide fundamental knowledge and new understanding of MOF formation mechanisms which would allow experimentalists to explore a much broader range of the vast parameter space of potential MOFs. This could have a transformational impact on the important field of MOF synthesis and its numerous applications. MOF synthesizability will be determined by estimating (i) lattice energy, (ii) MOF free energy, (iii) solvent-loaded MOF free energy, and/or (iv) free energy barriers for key self-assembly steps. The gained knowledge will be used to provide a MOF synthesizability factor, which will be calculate efficiently for large databases using machine learning tools. The proposed approach will create MOF databases that provide synthetic feasibility for each hypothesize MOF. Validation of the predictions will be performed through collaborative work with experimentalists. The proposed integration of research and education will target underrepresented groups in STEM through a research experience program for high school and undergraduate students. The knowledge obtained from MOF databases will be incorporated into educational movies. An interactive pedagogical website that allows performing virtual chemistry experiments will be developed and made accessible to general audiences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.