Stinville Research Group
Materials Science and Engineering
Equipment & Automated Research Infrastructure
Our research infrastructure combines advanced electron microscopy, mechanical testing across extreme environments, high-throughput experimentation, and robotic sample preparation and characterization. These capabilities are increasingly integrated into automated workflows for producing large, high-fidelity materials datasets and accelerating materials testing and qualification.
Microscopy & Characterization
Imaging and measurement infrastructure for resolving microstructure, surface state, deformation and temperature from the millimeter scale to the nanoscale.
ThermoFisher NOVA NanoSEM 650
High-performance field-emission SEM for high-resolution imaging and large-area materials characterization. The system provides high- and low-vacuum operation, a motorized five-axis stage, and nanometer-scale imaging capability.
Bichromatic Reflectometric Pyrometer
PhonOptics reflectometric pyrometry for precise temperature measurements during testing, including real-time emissivity measurement and correction for changes in surface state.
Mechanical & Extreme-Environment Testing
Specialized testing systems for quantifying deformation, fatigue and material-state evolution from cryogenic temperatures to elevated-temperature conditions.
NewTec MT1300 In-Situ Mechanical Stage
In-situ tensile and compressive loading inside the scanning electron microscope, enabling direct observation of material deformation across cryogenic, room, and elevated-temperature conditions.
Cryostat & Immersion Testing Systems
Dedicated cryogenic infrastructure for mechanical testing and deformation characterization at temperatures ranging from liquid-helium and liquid-nitrogen regimes toward room temperature.
Very High Cycle Fatigue Frame
Ultrasonic fatigue platform operating at 20 kHz for testing into the gigacycle regime. The system supports fully reversed and non-zero mean-stress conditions across cryogenic, room, and elevated temperatures.
Automation & Computing
Robotic and computational infrastructure designed to remove manual bottlenecks, standardize experimental workflows, and support high-throughput generation of AI-ready materials datasets.
Robotic Sample Preparation & Handling
Robotic infrastructure for repeatable specimen handling and preparation, designed to standardize operations such as sample loading, preparation, transfer, and routing between experimental steps while reducing manual intervention.
Automated Microscopy & Data Acquisition
Infrastructure for connecting sample handling with repeatable microscopy and characterization workflows. The objective is to enable large-area, multimodal measurements with consistent acquisition conditions and minimal operator intervention.
GPU Computing Infrastructure
Dedicated GPU computing resources for data-intensive scientific workflows, including image processing, computer vision, machine learning, representation learning, and large multimodal materials datasets.
Toward a Materials Data Factory
These instruments are increasingly connected as a single experimental pipeline. Robotic preparation and sample handling improve repeatability; advanced microscopy captures microstructure and local response; mechanical and environmental systems perturb the material state; and automated data pipelines convert the resulting measurements into large, standardized datasets for Materials Spatial Intelligence and AI-enabled materials qualification.
