M.A Vignon
Analyticaxpress,
United States
Keywords: 2D materials, machine learning, automated synthesis, material optimization, precision growth,scalable production, advanced materials, next-generation electronics, flexible electronics, transparent electronics, data-driven optimization, computational material science, resource optimization, real-time monitoring, industrial-scale production
Summary:
This proposal focuses on integrating machine learning (ML) into the synthesis of 2D materials to address challenges in scalability, precision, and cost-effectiveness. The goal is to enhance the production process for next-generation electronics by predicting optimal synthesis parameters, ensuring reproducibility, accelerating material discovery, optimizing resource usage, and enabling real-time adjustments during synthesis. The project aims to collect synthesis data, develop and validate ML models, and automate the process to achieve mass production of 2D materials. This approach could revolutionize the development of flexible, transparent, and energy-efficient technologies.