Federal agency name: defense advanced research projects agency (DARPA), defense sciences office (DSO) funding opportunity title: young faculty award (YFA) funding opportunity number:…

The Defense Advanced Research Projects Agency (DARPA), Defense Sciences Office awarded a Cooperative Agreement to Purdue University totaling $250,000 under the Research and Technology Development program (CFDA 12.910). The award, dated September 30, 2025, with completion scheduled for September 29, 2027, supports the Young Faculty Award (YFA) program. The research deliverables focus on combining atomistic simulations, machine learning approaches, and existing experimental data on crystalline materials to advance the understanding and prediction of novel material synthesis likelihood, defect consequences, and resulting electronic properties. The project is designed to provide theoretical and computational guidance to experimental researchers addressing critical material design questions, including optimal target chemistries, synthesis feasibility using existing laboratory strategies, and the effects of environmental factors such as temperature and pressure on material synthesizability and performance.

This research initiative aims to deliver revolutionary advances in materials science by bridging computational theory and experimental practice, enabling more efficient discovery and development of electronic materials for defense and dual-use applications. The cooperative agreement structure reflects DARPA's commitment to supporting transformative research at leading academic institutions, with Purdue University's established capabilities in advanced materials and computational research positioning it to execute the proposed work at its facilities in Indiana.

Federal agency name: defense advanced research projects agency (DARPA), defense sciences office (DSO) funding opportunity title: young faculty award (YFA) funding opportunity number: DARPARA2501CATALOG of federal domestic assistance (cfda) number(s): 12.910 research and technology developmentprogram description: DARPA is soliciting innovative research proposals in the areas of interest to the following DARPA technical offices: defense sciences office (DSO), information innovation office (I2O), microsystems technology office (MTO), and the tactical technology office (TTO). Further detail regarding the specific technical areas of interest can be found below under open office topics. Proposed research should investigate innovative approaches that enable revolutionary advances in science, devices, or systems. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice. The goal of this proposed research is to combine atomistic simulations, machine learning (ML) approaches, and existing experimental data on crystalline materials to accelerate the understanding and prediction of the synthesis likelihood, consequence of defects, and resulting electronic properties of novel materials.when trying to design new materials for any application, an experimental researcher is faced with the following questions: (a) which chemistries should i target, that would be easy to make and show the structural, electronic, and defect properties i am looking for, (b) can these promising materials be made and synthesized in the lab using existing strategies, and (c) what might be the effect of factors such as temperature, pressure, chemical growth conditions, etc., on the synthesizability and properties of these materials? The goal of this proposal is to answer these questions from an atomistic theoretical point of view and thus guide new experimental synthesis and characterization efforts for creating better electronic materials. The primary objectives are to utilize information from past publications and databases, systematic first principles simulations on bulk and defect-containing structures, and machine learning models for predicting structure, properties, synthesizability, and possible synthesis routes, to propose novel materials that will improve upon the state-of-the-art in various electronic devices. The success of this project will overcome past bottlenecks (i.e., heavy computational expense of high-level theory and connecting theory with experiments) of effectively making accurate quantum mechanical predictions on large supercell crystal structures (necessary for simulating alloys, defects, heterostructures, substrate growth, etc.), forecasting synthesis likelihood and reaction schemes for new materials, especially in the presence of defects, and generally bridging the gaps between computational predictions and experimental realization. This project will lead to the discovery of dozens of novel materials and the establishment of a pipeline for continuous discovery in different chemical spaces, via generation of new data and retraining of ML models as necessary. IT will also result in the development of interactive and user-friendly tools on nanohub (an online science gateway hosted at purdue) and similar online repositories, which will enable researchers to seamlessly interface with the data, make synthesizability and property predictions for any new compositions structures of interest, and build on the ML models to make extensions to other chemistries and applications. The proposed materials design framework will help the PI fulfill his career goals of using materials informatics-based approaches to drive atoms-to-device materials discovery and to develop a fundamental atomistic understanding of the factors governing the creation of new materials in the lab that fulfill multiple desired objectives.