The goal of the project is to develop novel advanced materials integrated with real-time process feedback, assisted by a machine learning algorithm, to enable scalable, autonomous in-situ manufacturing of electronics. The technology will provide capabilities for on-demand fabrication, adaptive repair, and dynamic reconfiguration of circuits, functions that are particularly critical for long-duration space missions where resupply is difficult. These enhanced materials and manufacturing processes will support future space exploration initiatives. Beyond space applications, the methods developed here may also transform multiple technology sectors including flexible hybrid electronics for wearable devices, neuromorphic computing systems that mimic brain functions, and distributed manufacturing solutions for remote or resource-limited environments. The research incorporates workforce development initiatives to train students in cutting-edge techniques spanning materials science, artificial intelligence, and advanced manufacturing. Participants will gain hands-on experience in functional materials synthesis, intelligent process control systems, and semiconductor device fabrication, skills directly aligned with emerging needs in the advanced manufacturing sector. The project specifically addresses national workforce development priorities in critical technology areas including additive manufacturing, semiconductor processing, and autonomous production systems. This project devel