Solid State and Materials Chemistry

The multidisciplinary Solid State and Materials Chemistry program supports foundational research on inorganic, organic, and hybrid solids with an emphasis on materials synthesis and studies correlating crystal structure and materials properties. This typically involves a focus on experimentally elucidating atomic and molecular underpinnings for materials development and properties of extended solid-state materials, which are defined as the entire range from nanoscale assemblies to bulk materials.

Studies that combine experimental and computational aspects, including machine learning and artificial intelligence aspects, are welcome, but proposing supporting computational efforts is not required.

The program particularly encourages submissions of proposals at the frontiers of solid-state and materials chemistry research, which include but are not limited to:

• Elucidation of the design principles for materials synthesis yielding innovative design strategies.

• Crystal growth studies of inorganic and organic solids that demonstrate materials properties.

• Synthesis of hybrid materials or multicomponent materials systems as well as fundamental investigations of their emergent properties.

• Studies correlating materials properties to their structure and/or components, including for nanomaterial assemblies, 2D materials, or framework materials.

• All materials aspects of sustainability, including those investigating the replacement of supply chain-limited elements, or with a specific focus on synthesis and characterization of next generation “beyond Li-ion” energy storage materials.

An exception to the above definition of extended solid-state materials is the area of liquid crystal research. Such proposals, when submitted to the program, will be discussed with the Condensed Matter Physics program and possibly either co-reviewed or transferred depending on the extent of alignment with the goals of both programs. PIs should consult the sections below and are strongly encouraged to contact the program to discuss the submission of proposals that potentially fall in this category.

Grant Opportunities for Academic Liaison with Industry (GOALI) proposals, where advances involve collaborative research with an industrial partner, are welcome and supported by the program.

The following are research topics that are not of interest to or priorities of the program:

• Proposals with significant emphasis on catalysis-related research that are submitted to the program will be discussed with program directors for the catalysis programs in the NSF Mathematical and Physical Sciences (MPS) and Engineering (ENG) directorates. Proposals may either be transferred or reviewed jointly depending on the extent of alignment with the goals of both programs, but they will not be reviewed solely by the program. PIs are strongly encouraged to contact the program to discuss the submission of proposals that potentially fall in this category.

• Projects for which the novelty of the research resides in molecular chemistry, including studying reaction kinetics of molecular reactions, the synthesis of molecular cages or other atomically defined building units, or developing new synthesis concepts for macromolecular, supramolecular and nanoscopic structures.

• Research projects in the area of energy storage materials investigations that focus on novel liquid or polymer electrolytes, explicitly target improved system or component-level performance, or aim to optimize commercially deployed electrode materials in other ways.

• Foundational materials research on epitaxial thin films, grain boundary effects, ceramic materials, metals and alloys, or polymers. Researchers considering proposal submission in these areas are directed to other programs in MPS Materials Research.

• Studies centered around adsorption, desorption and separation phenomena or thermal transport processes should be submitted to programs with portfolios in these areas.

• While the program acknowledges the importance of computational materials chemistry, including the use of machine learning and artificial intelligence, and sees merit in studies that combine experimental and computational aspects, exclusively computational proposals are not aligned with the portfolio of the program and should be submitted elsewhere.

The program works closely with other programs within MPS and ENG to accommodate the multidisciplinary nature of proposal submissions.