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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Novel Non‐Destructive Rapid Tool for Estimating Amino Acid Composition and Secondary Structures of Proteins in Solution

Abstract Amino‐acid protein composition plays an important role in biology, medicine, and nutrition. Here, a groundbreaking protein analysis technique that quickly estimates amino acid composition and secondary structure across various protein sizes, while maintaining their natural states is introduced and validated. This method combines multivariate statistics and the thermostable Raman interaction profiling (TRIP) technique, eliminating the need for complex preparations. In order to validate the approach, the Raman spectra are constructed of seven proteins of varying sizes by utilizing their amino acid frequencies and the Raman spectra of individual amino acids. These constructed spectra exhibit a close resemblance to the actual measured Raman spectra. Specific vibrational modes tied to free amino and carboxyl termini of the amino acids disappear as signals linked to secondary structures emerged under TRIP conditions. Furthermore, the technique is used inversely to successfully estimate amino acid compositions and secondary structures of unknown proteins across a range of sizes, achieving impressive accuracy ranging between 1.47% and 5.77% of root mean square errors (RMSE). These results extend the uses for TRIP beyond interaction profiling, to probe amino acid composition and structure.

Chemistry↗
DOE OSTI2024

Photocatalytic Nitrate Destruction Studies in Complex Environments

One method for denitration of nitric acid used in nuclear facilities is to use formic acid as a reductant. The major problem with formic acid denitration is an induction period of varying duration that may result in excessive accumulation of formic acid at the reaction onset. This accumulation poses an off-gas process control issue. In this talk, we will describe the use of titaniabased photocatalysts for the treatment of nitric acid and nitrate wastes. We find that the photocatalytic process is a simple and straightforward method to completely destroy nitrate ions at room temperature without any initiation period.

nanomaterials↗
DOE OSTI2025

Combining Deep Learning and scatterControl for High-Throughput X-ray CT Based Non-Destructive Characterization of Large-Scale Casted Metallic Components

X-ray computed tomography (XCT) is essential for nondestructive evaluation and quality control of large-scale metal components. XCT imaging, however, faces significant challenges from metal artifacts, particularly those caused by Compton scattering, which degrade image quality and obscure critical details. Hardware-based solutions (e.g. scatterControl) offer advancements by intercepting scattered photons and reducing artifacts, but they can be time-consuming and require additional processing. Here, we propose modifying and leveraging a novel deep learning (DL) framework, Simurgh, to enhance and accelerate scatter correction in XCT. By combining scatterControl with DL-based artifact removal, we demonstrate significant reduction in scan time while producing high-quality reconstructions. Through extensive evaluation on industrial XCT data, we show that our methods reduce scan time by up to more than 10 x while preserving flaw detectability. Quantitative analysis across multiple segmentation techniques confirms that Simurgh-based reconstructions consistently outperform traditional Feldkamp-Davis-Kress, model-based iterative reconstruction, and commercial DL models in both pixel-level and task-specific evaluations, enabling scalable, high-throughput XCT workflows for characterization of large scale components in applications such as casting and metal additive manufacturing.

Complex metal parts↗
DOE OSTI2022

Nondestructive and destructive assay for forensics characterization of weapons-grade plutonium produced in LEU irradiated in a thermal neutron spectrum

A post-irradiation examination (PIE) of an enriched uranium sample was performed to advance a nuclear forensics methodology, based on intra-elemental nuclide ratios. The PIE was carried out on a few milligrams of low enriched uranium dioxide (LEUO 2 ) sample, irradiated to a burnup of 1 GWd/MTU. The PIE of the LEUO 2 sample provided the concentration of selected plutonium and fission product nuclides ( 239 Pu, 240 Pu, 241 Pu, 91 Y, 95 Zr, 95 Nb, 103 Ru, 133 Cs, 134 Cs, 135 Cs, 137 Cs, 136 Ba, 138 Ba, 140 Ba, 140 La, 141 Ce, 144 Ce, 149 Sm, 150 Sm, 152 Sm, 153 Eu, and 154 Eu). The PIE supported validation of the MCNP (Monte Carlo N-Particle neutronics simulation code) predicted concentration of these nuclides in the irradiated LEUO 2 sample. This study showed that most of the MCNP predicted nuclide concentrations were within 15% and several within 10% compared to the PIE results. Furthermore, gamma and mass spectrometry of nuclides in irradiated LEUO 2 enabled the determination of uranium burnup and time since irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Revisiting a minimally destructive analytic approach for determining electrochemical kinetic parameters: Measuring aluminum corrosion across a wide pH range based on the Butler-Volmer equation

Here, this study revisits the three-point sampling of the simplified Butler-Volmer equation to address the limitations of strong potentiodynamic polarization, which can introduce irreversible damage and uncertainty in corrosion analysis. The method extracts electrochemical kinetic parameters while minimizing polarization effects, evaluates noise sensitivity relative to overpotential, and accounts for errors from signal noise, OCP drift, ohmic resistance, and mass-transfer constraints. Verified against the Tafel extrapolation method for aluminum corrosion across a wide pH range, this low-polarization approach enables accurate evaluations with specific error estimates, offering a robust alternative to linear polarization resistance methods that assume constant Tafel slopes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Non-destructive measurement and real-time monitoring of apple hardness during ultrasonic contact drying via portable NIR spectroscopy and machine learning

Portable near-infrared spectrometer in the spectral range of 900–1700 nm was evaluated for the first time to assess and monitor apple hardness in real-time during ultrasonic drying. Calibration models were developed using PLS and ANN, and their performances were evaluated by internal leave-one-out cross-validation and an external dataset. Several pre-treatments including standard normal variate (SNV), multiplicative scatter correction (MSC), Savitzky–Golay first and second derivatives were employed to examine the effects of spectral variations in hardness prediction. Seven important wavelengths were selected using weighted regression coefficients to develop a simple MLR model to facilitate the model interpretation and circumvent noise. The models using PLS, MLR, and ANN with selected wavelengths predicted the apple hardness with R 2 p of 0.91, 0.91, 0.95, and RMSEP of 14.78, 14.85, and 12.46 N, respectively. Finally, the results indicate that portable NIR spectrometers are quite promising for real-time monitoring of apple hardness during ultrasonic drying.

47 OTHER INSTRUMENTATION↗