Exploring the Synthesis and Properties of Hybrid Perovskites with a "Gas" Atom, or Molecule, as a Structural Component

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Part 1: Non-Technical SummaryA new family of solid materials that contain gas atoms or molecules as part of their structure is being synthesized and characterized in this project. This work takes fundamental understanding of functional solids in a new direction and also opens opportunities for new technologies. The materials under study can potentially trap large amounts of gas at room temperature and pressure, and then release the gas on warming. For a given volume, they can contain more gas than the high pressure storage tanks typically used to contain hydrogen, helium and other industrially important gases. Efficient and safe gas storage is one of the major barriers to using hydrogen as a fuel. The new gas-containing materials also have potential for gas separation and purification processes that are of importance to the nuclear industry and national defense. Computer simulations, which make use of a machine learning approach, support and guide the experimental work. The training of graduate and undergraduate students in a variety of techniques that are of wide utility in the development of new functional materials is integrated into the project, which is supported by the Solid State and Materials Chemistry program within the Division of Materials Research. Parts 2: Technical SummaryThis project explores the preparation and properties of perovskites where a small gas molecule or atom, for example molecular hydrogen, neon or helium, is a structural component of the material. While there is vast body of prior work on perovskites, due to their technological significance across a wide range of applications, there is almost nothing known about gas-containing perovskites. Materials of this type can contain the gas at much higher densities than found in conventional high pressure gas storage tanks, and the small pores within their structures may enable isotope separation by quantum sieving effects. Synthetic approaches include three distinct strategies for preparing new materials in different compositional families. High pressure diffraction and Raman spectroscopy, along with gas release measurements from recovered samples, provide information on the formation and properties of the materials. In this project, supported by the Solid State and Materials Chemistry program within the Division of Materials Research, experiment is complemented by advanced computational tools, so that computation both explains experimental results and guides the preparation of new materials. Monte Carlo and molecular dynamics simulations, based on force fields derived from density functional theory calculations using a deep-learning convolution neural network approach, provide an opportunity to realistically capture the behavior of the materials. The training of graduate and undergraduate students in a variety of synthetic, computational and materials characterization techniques is integrated into the work.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.