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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2026

TCAD-Machine Learning Enabled TID Compact Model Development for Commercial SiC MOSFET

We propose a TCAD (Technology Computer Aided Design)-machine learning coupled approach that combines a TCAD tool (Charon), optimization/uncertainty quantification tool (Dakota), surrogate models, and Bayesian learning capabilities. The coupling approach is used for accurate modeling and calibration of total ionizing dose (TID) induced threshold voltage (V th ) shifts in Commercial-Off-The-Shelf (COTS) semiconductor devices and to develop physics-informed TID compact models. This versatile approach is applied to model the TID effect in an exemplar COTS 3.3 kV SiC power MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor). With the Charon-Dakota coupling, we can determine key device geometry and doping values based on device physics, which are difficult to obtain or not available for COTS devices but important for TCAD simulation; additionally, we can efficiently generate thousands of simulation results in a large parameter space, which makes it possible to develop data-driven surrogate models and perform Bayesian calibration. Utilizing the full tool-coupling approach, we achieve calibrated TCAD simulation models that accurately capture the average TID-induced V th shifts behavior with total doses and V th shifts saturation at high doses as observed in experimental data. More importantly, the calibrated TCAD simulations are obtained with determined TID model parameters (e.g., hole trap density and capture cross section) values that contain well quantified uncertainties. Furthermore, we can isolate and quantify the noises that are not captured by the TCAD models but exist in the measured data due to measurements and devices variabilities. Lastly, the calibrated surrogate models are used to develop physics-informed TID compact models. The method is generalizable to other devices and/or radiation conditions with few modifications and can provide well-determined uncertainties.

COTS↗
DOE OSTI2024

Advancing the Understanding of Manufacturing Tools for Hardware Security

This project’s goal was to explore new methods and tools to evaluate the focused ion beam (FIB) effect on active electrical devices, which is becoming increasingly challenged by the continual decrease in transistor geometry. Novel hole transfer methods leveraging FIB patterning were demonstrated utilizing selective area atomic layer deposition (ALD) and metal assisted chemical etching. A FIB damage electrical tester device was fabricated, and the effects of FIB beams were characterized by examining change in performance of damaged transistors. Detailed characterization of end-of-range damage for common FIB ions were correlated to modeling methods. Finally, undamaged and damaged devices were simulated by Charon to begin understanding the FIB effects on active devices. This test platform along with modeling methods give a powerful way to assess FIB damage in materials and devices, and with more development can help establish methods to predict FIB damage effects on electrical devices.

42 ENGINEERING↗