Non-technical summary: This award supports research to accelerate the making of new inorganic materials, which are vital components of next-generation energy, optoelectronic, and biomedical devices. Often new materials are created through a trial-and-error approach that depends on the intuition of the researcher, but this is inefficient and wasteful of both materials and time. With support from the Solid State and Materials Chemistry program and the Ceramics program, both in the Division of Materials Research, the researchers predict how to make new inorganic materials using computational materials science and validate these predictions in the laboratory, setting up a feedback loop to further improve future predictions. Computational predictions rely on the understanding of material thermodynamic properties, and laboratory experiments use real time characterization to monitor how the material is made. The feedback loop is employed to make perovskite oxynitrides, which are inorganic materials with highly tunable properties. The impact of the starting materials, also known as precursors, from which perovskite oxynitride products form is being investigated, and formation pathway maps to perovskite oxynitrides from varied precursors and reaction conditions are being created. Through this project, the team of researchers bridges the gap between computer-aided materials design and practical synthesis in the laboratory, which benefits society by accelerating the creation of inorga