The National Institute of Standards and Technology (NIST) has awarded over $1.8 million in grants to small businesses for research and development in advanced technologies, including additive manufacturing.
The National Institute of Standards and Technology (NIST) has announced the allocation of over $1.8 million in funding to support small businesses engaged in cutting-edge technological advancements. This initiative focuses on critical areas such as artificial intelligence, semiconductors, and additive manufacturing.
The grants are part of NIST's Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs, designed to foster innovation and commercialization of new technologies. The selected companies will use the funding to conduct research and development, aiming to bring novel solutions to market.
Several companies will receive funding to advance additive manufacturing capabilities. While specific project details were not immediately available, the focus is on developing new processes, materials, or applications that leverage 3D printing technology. This investment underscores NIST's commitment to strengthening U.S. technological leadership and competitiveness.
The awards aim to bridge the gap between laboratory research and commercial application, enabling small businesses to overcome financial hurdles in the early stages of technology development. The selected projects are expected to contribute to advancements across various sectors, driving economic growth and technological progress.
This NIST funding highlights the growing recognition of additive manufacturing as a key enabling technology. By supporting small businesses, NIST is fostering innovation in areas like novel materials, process optimization, and integrated systems for AM. This directly contributes to the broader push for more agile, resilient, and customizable manufacturing capabilities across industries, including aerospace and defense.
Edited by the news editor with AI from the original report — please refer to the original source.