Project SCALE RH: Machine learning-based optimization of materials for microelectronics Program Engineering First Time Researcher (FTR) Fellowship Term Spring 2025 Status Closed Research Area Microelectronics, machine learning, active learning, generative AI, computational materials science Description New or optimized materials with desired properties are critical in microelectronics. For example, new alloys with stringent thermo-mechanical performance are needed to replace lead-based solders and understanding the response of materials to radiation is essential for space applications. Predictive computational methods have become an integral part of material discovery and optimization. These tools include physics-based simulations and machine learning models and can accelerate the introduction of new materials and enable the co-design of materials and devices. Predictive tools can accelerate the discovery of optimal materials reducing the number of costly and time-consuming experiments. Recent advancements in artificial intelligence (AI) have garnered significant attention from the scientific community as they provide solutions beyond traditional modeling approaches. In this project, we will combine atomistic materials simulations with generative AI and active learning to characterize and/or optimize materials for microelectronic applications. In addition, active learning methods will utilize these tools to discover the optimal composition of alloys for packaging and other applications. Students will be trained in atomistic simulations and machine learning tools. Supervisor Tanya A Faltens Mentor Alejandro H Strachan Type of work required Students will perform computational research using density functional theory, molecular dynamics, and machine learning tools. Websites See more details and read about all the SCALE FTR projects here: https://nanohub.org/groups/scale/research_opportunities/research_purdue/ftr2025 Qualifications Must be a SCALE student. Read more about SCALE and access the SCALE application link here: https://nanohub.org/groups/scale/learn_more. Once in SCALE, apply via the FTR portal: https://engineering.purdue.edu/Engr/Research/EURO/programs/ftr. Preferred majors: MSE, EE, ME, Chem, Phys. Academic Years Eligible: All years are invited to apply. Required Experience and Skills: Introductory college physics, math, and chemistry Desired experience and skills: programming, python, unix Credit Hours 0 Weekly Hours 10 (estimated)