News

(September 2026) Our proposal titled "RFA-024 Energy-Efficient Cold Sintering of Lunar Regolith and Hybrid Composites for Sustainable Lunar Infrastructure" has been funded by the NASA EPSCoR Rapid Response Research (R3) program. We will receive 1-year funding ($124,912) to investigate low-temperature cold-sintering approaches for lunar regolith and regolith–polymer composites, with the goal of enabling energy-efficient fabrication of durable structural materials for future lunar infrastructure.

(July 2026) Our new Oxford Instruments NMT04 in-situ nanoindenter has been installed at OU! The system enables high-resolution nanomechanical and micromechanical testing directly inside the SEM, including indentation, micro-compression, micro-bending, fracture, and fatigue experiments. This capability will support our research on advanced composites, ceramics, nanostructured materials, and architected materials.

(December 2025) Our team has received a Strategic Equipment Investment Program (SEIP) award from the University of Oklahoma Office of the Vice President for Research and Partnerships to acquire an Oxford Instruments NMT04 in-situ SEM nanoindenter. The $75,000 SEIP award, together with team member cost share contributions, will help establish advanced in-situ nanomechanical testing capabilities at OU for studying deformation, fracture, and fatigue of materials at the micro- and nanoscale. The project is led by Dr. Jingyao Dai in collaboration with Dr. Yijie Jiang and Dr. Stefan Wilhelm.

(August 2025) Exactly one year after establishing the lab at OU, we successfully achieved our first growth of vertically aligned carbon nanotube (CNT) forests. This milestone was made possible through the dedicated efforts of the Spring 2025 Capstone Design team and the invaluable support from the Microfabrication Research & Education (MREC) Cleanroom. With this foundation, we are excited to begin refining the growth process and advancing toward the development of CNT-based nanocomposites.

(April 2025) Our collaborative proposal with Dr. Yijie Jiang, titled "Experimental Planning and Optimization of Nanotube Synthesis via Data-driven Machine Learning", has been selected for the DISC Faculty Seed Funding Program ($12,500). In this project, we aim to use the collected processing data (temperature, mass flow rate, and pressure) to aid experimental planning and process optimization for the synthesis of boron nitride nanotubes (BNNTs).