Semiconductors electronics is integral to Americas economic and national security as manifested by the CHIPS act. Ever-increasing materials requirements for semiconductor R&D, combined with the advent of machine learning, and availability of materials databases, pose a need to understand and exploit these methods for acceleration of the materials and manufacturing lifecycle. The proposal aims to provide a digital framework establishing modular and flexible data standards allowing to accelerate semiconductor materials research. The proposed work will help researchers involved in the NIST-lead CHIPS and Materials Genome initiatives and many other materials researchers worldwide organize and accelerate their work for a critical set of applications of interest to both the public and private sector. The proposal improves the speed and efficiency of the research and development R&D of new materials and chemicals and enables data-driven capabilities that facilitate the development of new kinds of products for semiconductor electronics. The proposed solution benefits the customers by enabling digital practices that (i) are accessible, flexible, and materials-design-specific, (ii) allow to participate in collaborative research without revealing sensitive information, and (iii) able to reduce the complexity of materials development and the sparseness/heterogeneity of the available data.
