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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantification of SARS-CoV-2 spike protein expression from mRNA vaccines using isotope dilution mass spectrometry

The advent of mRNA vaccine technology has been vital in rapidly creating and manufacturing COVID-19 vaccines at an industrial scale. To continue to accelerate this leading vaccine technology, an accurate method is needed to quantify antigens produced by the transfection of cells with a mRNA vaccine product. This will allow monitoring of protein expression during mRNA vaccine development and provide information on how changes to vaccine components affects the expression of the desired antigen. Developing novel approaches that allow for high-throughput screening of vaccines to detect changes in antigen production in cell culture prior to in vivo studies could aid vaccine development. Here, we have developed and optimized an isotope dilution mass spectrometry method to detect and quantify the spike protein expressed after transfection of baby hamster kidney cells with expired COVID-19 mRNA vaccines. Five peptides of the spike protein are simultaneously quantified and provide assurance that protein digestion in the region of the target peptides is complete since results between the five peptides had a relative standard deviation of less than 15 %. In addition, two housekeeping proteins, actin and GAPDH, are quantified in the same analytical run to account for any variation in cell growth within the experiment. IDMS allows a precise and accurate means to quantify protein expression by mammalian cells transfected with an mRNA vaccine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗
DOE OSTI2018

Tracking Tumor Colonization in Xenograft Mouse Models Using Accelerator Mass Spectrometry [Tracking Tumor Colonization in vivo Using Accelerator Mass Spectrometry]

Here we propose an Accelerator Mass Spectrometry (AMS)-based high precision method for quantifying the number of cancer cells that initiate metastatic tumors, in xenograft mice. Quantification of 14 C per cell prior to injection into animals, and quantification of 14 C in whole organs allows us to extrapolate the number of cancer cells available to initiate metastatic tumors. The 14 C labeling was optimized such that 1 cancer cell was detected among 1 million normal cells. We show that ~1–5% of human cancer cells injected into immunodeficient mice form subcutaneous tumors, and even fewer cells initiate metastatic tumors. Comparisons of metastatic site colonization between a highly metastatic (PC3) and a non-metastatic (LnCap) cell line showed that PC3 cells colonize target tissues in greater quantities at 2 weeks post-delivery, and by 12 weeks post-delivery no 14 C was detected in LnCap xenografts, suggesting that all metastatic cells were cleared. The 14 C-signal correlated with the presence and the severity of metastatic tumors. AMS measurements of 14 C-labeled cells provides a highly-sensitive, quantitative assay to experimentally evaluate metastasis and colonization of target tissues in xenograft mouse models. This method can potentially be used to evaluate tumor aggressiveness and assist in making informed decisions regarding treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Strategies for designing biocatalysts with new functions

Enzymes can be optimized to accelerate chemical transformations via a range of methods. In this review, we showcase how protein engineering and computational design techniques can be interfaced to develop highly efficient and selective biocatalysts.

09 BIOMASS FUELS↗
DOE OSTI2023

On the convergence of an IEQ-based first-order semi-discrete scheme for the Beris-Edwards system

We present a convergence analysis of an unconditionally energy-stable first-order semi-discrete numerical scheme designed for a hydrodynamic Q-tensor model, the so-called Beris-Edwards system, based on the Invariant Energy Quadratization Method (IEQ). The model consists of the Navier–Stokes equations for the fluid flow, coupled to the Q-tensor gradient flow describing the liquid crystal molecule alignment. By using the Invariant Energy Quadratization Method, we obtain a linearly implicit scheme, accelerating the computational speed. However, this introduces an auxiliary variable to replace the bulk potential energy and it is a priori unclear whether the reformulated system is equivalent to the Beris-Edward system. In this work, we prove stability properties of the scheme and show its convergence to a weak solution of the coupled liquid crystal system. We also demonstrate the equivalence of the reformulated and original systems in the weak sense.

Weber, Franziska↗
DOE OSTI2018

Comparison of pseudo-static limit equilibrium and elastic wave equation analyses of dynamic earth pressures on retaining structures

The seismic earth pressure increment is typically computed using either pseudo-static limit equilibrium methods or elastic wave equation analyses of the interaction between a retaining structure and backfill material, yet current interpretations of the two methods provide conflicting recommendations. The focus of this study is to compare the seismic earth pressure increment computed using the two methods. This approach is demonstrated by subjecting an initially uniform prototype site selected from standard site classifications to harmonic excitation in one-dimensional equivalent linear analyses. Then, the seismic earth pressure resultant for a rigid wall is computed using the two methods. The limit equilibrium approach utilizes the acceleration records from the equivalent linear analysis to compute a seismic coefficient, whereas the elastic solution incorporates the reduced modulus and damping from the final iteration of the analysis, as well as the relative displacement records. The results presented herein corroborate the findings of recent centrifuge experiments and associated analyses.

58 GEOSCIENCES↗
DOE OSTI2015

Investigating {sup 13}C+{sup 12}C reaction by the activation method. Sensitivity tests

We have performed experiments to check the limits of sensitivity of the activation method using the new 3 MV Tandetron accelerator and the low and ultra-low background laboratories of the “Horia Hulubei” National Institute of Physics and Nuclear Engineering (IFIN-HH). We have used the {sup 12}C+{sup 13}C reaction at beam energies E{sub lab}= 6, 7 and 8 MeV. The knowledge of this fusion cross section at deep sub-barrier energies is of interest for astrophysical applications, as it provides an upper limit for the fusion cross section of {sup 12}C+{sup 12}C over a wide energy range. A {sup 13}C beam with intensities 0.5–2 particleμA was provided by the accelerator and used to bombard graphite targets, resulting in activation with {sup 24}Na from the {sup 12}C({sup 13}C,p) reaction. The 1369 and 2754 keV gamma-rays from {sup 24}Na de-activation were clearly observed in the spectra obtained in two different laboratories used for measurements at low and ultralow background: one at the surface and one located underground in the Unirea salt mine from Slanic Prahova, Romania. In the underground laboratory, for E{sub lab} = 6 MeV we have measured an activity of 0.085 ± 0.011 Bq, corresponding to cross sections of 1–3 nb. This demonstrates that it is possible to measure {sup 12}C targets irradiated at lower energies for at least 10 times lower cross sections than before β–γ coincidences will lead us another factor of 10 lower, proving that this installations can be successfully used for nuclear astrophysics measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Active sampling for neural network potentials: Accelerated simulations of shear-induced deformation in Cu–Ni multilayers

Neural network potentials (NNPs) can greatly accelerate atomistic simulations relative to ab initio methods, allowing one to sample a broader range of structural outcomes and transformation pathways. In this work, we demonstrate an active sampling algorithm that trains an NNP that is able to produce microstructural evolutions with accuracy comparable to those obtained by density functional theory, exemplified during structure optimizations for a model Cu–Ni multilayer system. We then use the NNP, in conjunction with a perturbation scheme, to stochastically sample structural and energetic changes caused by shear-induced deformation, demonstrating the range of possible intermixing and vacancy migration pathways that can be obtained as a result of the speedups provided by the NNP. The code to implement our active learning strategy and NNP-driven stochastic shear simulations is openly available at https://github.com/pnnl/Active-Sampling-for-Atomistic-Potentials .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Development of a bi-solvent liquid scintillator with slow light emission

One of the most promising approaches for the next generation of neutrino experiments is the realization of large hybrid Cherenkov/scintillation detectors made possible by recent innovations in photodetection technology and liquid scintillator chemistry. The development of a potentially suitable future detector liquid with particularly slow light emission is discussed in the present publication. This cocktail is compared with respect to its fundamental characteristics (scintillation efficiency, transparency, and time profile of light emission) with liquid scintillators currently used in large-scale neutrino detectors. In addition, the optimization of the admixture of wavelength shifters for a scintillator with particularly high light emission is presented. Furthermore, the pulse-shape discrimination capabilities of the novel medium was studied using a pulsed particle accelerator driven neutron source. Beyond that, purification methods based on column chromatography and fractional vacuum distillation for the co-solvent DIN (Diisopropylnaphthalene) are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Laser metal deposition of refractory high-entropy alloys for high-throughput synthesis and structure-property characterization

Progress in materials development is often paced by the time required to produce and evaluate a large number of alloys with different chemical compositions. This applies especially to refractory high-entropy alloys (RHEAs), which are difficult to synthesize and process by conventional methods. To evaluate a possible way to accelerate the process, high-throughput laser metal deposition was used in this work to prepare a quinary RHEA, TiZrNbHfTa, as well as its quaternary and ternary subsystems by in-situ alloying of elemental powders. Compositionally graded variants of the quinary RHEA were also analyzed. Our results show that the influence of various parameters such as powder shape and purity, alloy composition, and especially the solidification range, on the processability, microstructure, porosity, and mechanical properties can be investigated rapidly. The strength of these alloys was mainly affected by the oxygen and nitrogen contents of the starting powders, while substitutional solid solution strengthening played a minor role.

additive manufacturing↗
DOE OSTI2022

Energy dependence of $\textit{p}$ + 232 Th fission mass distributions: Mass-asymmetric standard I and standard II modes, and multichance fission

Background: The predominant mass-asymmetric fission of actinide nuclides occurs mainly through the so-called standard I and standard II modes. Though understood to be caused by shape-dependent shell structures encountered between the fission barrier deformation and scission, the most relevant shell gaps are still not firmly established. The standard I mode had been associated with the spherical doubly magic 132 Sn, and thus the $\textit{Z}$ = 50 proton shell, but recently it has been proposed that standard I and standard II are associated with quadrupole and octupole deformed gaps at $\textit{Z}$ = 52 and 56, respectively. Purpose: In this work, we investigate how the relative probabilities of the standard I and standard II modes vary with excitation energy near threshold, probing where the two modes bifurcate. Methods: The Australian National University Heavy Ion Accelerator Facility and CUBE fission spectrometer have been used to measure fission mass distributions for the $\textit{p}$ + 232 Th reaction (forming 233 Pa) at closely spaced bombarding energy intervals from 6.5 to 28 MeV. Results: A model-independent analysis of the energy dependence of the shape of the mass-asymmetric peak shows a strong dependence of the standard I and standard II relative probability on excitation energy near threshold. Conclusions: The results are consistent with the standard II mode having a lower fission barrier than standard I in 233 Pa, with the latter increasing continually in relative probability above its barrier energy. It is concluded that multichance fission, in particular last chance fission, plays a strong role in determining the observed energy dependence of all fission modes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Lifetime measurements in 102 Mo interpreted in the interacting boson model and the X(5) symmetry

Lifetimes of low-lying excited states in 102 Mo populated in the two-neutron transfer reaction 100 Mo ⁢( 18 O, 16 O)⁢ 102 Mo were measured using the recoil distance Doppler shift method at the IFIN-HH Tandem accelerator. Lifetimes of the $2^+_1$, $0^+_2$, $4^+_1$, $2^+_2$, $2^+_3$, $3^+_1$, $6^+_1$, ($0^+_3$), $4^+_2$, ($3^−_1$), and ($5^−_1$) states were obtained. The deduced electromagnetic transition strengths have been compared to calculations performed in the interacting boson model framework including models representing the U(5) and X(5) symmetries. It is found that 102 Mo lies between the U(5) limit and the X(5) critical point symmetry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Engineering Privacy at the Edge: A Practical Guide to Differential Privacy in System Architectures

The rapid expansion of distributed and edge computing platforms—spanning autonomous vehicles, IoT sensors, and healthcare monitors—has heightened concerns about data privacy. Differential Privacy (DP) offers a rigorous mathematical framework to protect sensitive information while retaining analytical utility. This tutorial introduces the foundations of DP for both numerical and categorical datasets and extends the discussion to correlation-aware techniques tailored for structured and high-dimensional data. Hands-on demonstrations will begin with the PETINA (Privacy prEservaTIoN Algorithms) package for numerical data and continue with MIC-DP (Maximum Information Correlated Differential Privacy) for tabular data. Designed for researchers and practitioners in secure systems, embedded architectures, and AI accelerators, the tutorial emphasizes practical and scalable methods for integrating DP into real-world system designs.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗
DOE OSTI2021

BACKFLIP: Identification of Materials and Changes Upon Aging of Emerging Fluoropolymer-Free and Industry-Benchmark PV Backsheets

Extending lifetimes of photovoltaic (PV) modules and decreasing manufacturing and decommissioning costs are motivating research of novel PV module backsheet materials. Backsheet integrity is critical to the safety and performance of a PV module, however, the polymeric materials are often vulnerable to environmental degradation. The long-term durability of emerging polyolefin (PO) materials is being examined to inform regarding the possible replacement of laminated backsheets containing polyethylene terephthalate (PET) cores and fluoropolymer protective inner/outer layers. This study compares traditional PET-based backsheets with novel, co-extruded, and recyclable PO-based backsheets after being subjected to hygrometric and UV photolytic accelerated weathering. A large set of characterization methods will compare physical, chemical, structural, mechanical, and insulating properties of these backsheets and the resulting mini-module (MiMo) PV performances. The study of chemical composition, glass- and phase-transition temperatures, degree of crystallinity, and crystalline structure are described here.

mini-module↗
DOE OSTI2023

A Flexible Field Mapping System for Accelerator Magnets

Magnetic field mapping is a fundamental magnetic measurement method that typically uses Hall and NMR sensors. In magnet measurement facilities, such systems are likely used in various configurations suitable for a specific task at hand. To address this diversity, the authors developed a flexible field mapping system capable of being configured and tailored to each particular measurement case. Further, the system needs to address the variability introduced by differences in sensors and their readout systems, probe positioning systems, power supply systems, and required mapping geometry (mapping space and grid, measurement steps and sequences). Although the discussed field mapping systems range from a self-propelled multi-sensor mapper of a large detector magnet to a single 3D Hall sensor system to scan a small permanent magnet, they were all built with the same core mapping system. The variability present in field mapping systems, the measurement system architecture addressing this variability, as well as examples of several field mapping systems built in this architecture are presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Chance-Constrained Energy Management System for Power Grids With High Proliferation of Renewables and Electric Vehicles

This paper proposes a two-stage energy management system (EMS) for power grids with massive integration of electric vehicles (EVs) and renewable energy resources. The first stage economic dispatch determines the optimal operating points of charging stations and battery swapping stations (BSS) for EVs under plug-in and battery swapping modes, respectively. The proposed stochastic model predictive control (SMPC) problem in this stage is characterized through a chance-constrained optimization formulation that can effectively capture the system and the forecast uncertainties. A distributed algorithm, the alternating direction method of multipliers (ADMM), is applied to accelerate the optimization computation through parallel computing. The second stage is aimed in coordinating the EV charging mechanisms to continuously follow the first-stage solutions, i.e., the target operating points, and meeting the EV customers' charging demands captured via the Advanced Metering Infrastructure (AMI). In this work, the proposed solution offers a holistic control strategy for large-scale centralized power grids in which the aggregated individual parameters are predictable and the system dynamics do not vary sharply within a short time-interval.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

SU-F-T-586: Pre-Treatment QA of InCise2 MLC Plans On a Cyberknife-M6 Using the Delta4 System in SBRT

Purpose: Performing pre-treatment quality assurance (QA) with the Delta4 system (ScandiDos Inc., Madison, WI) is well established for linac-based radiotherapy. This is not true when using a Cyberknife (Accuray Inc., Sunnyvale, CA) where, typically film-based QA is applied. The goal of this work was to test the feasibility to use the Delta4 system for pre-treatment QA for stereotactic body radiation therapy (SBRT) using a Cyberknife-M6 equipped with the InCise2 multileaf collimator (MLC). Methods: In order to perform measurements without accelerator pulse signal, the Tomotherapy option within the Delta4 software was used. Absolute calibration of the Delta4 phantom was performed using a 10×10 cm{sup 2} field shaped by the InCise2 MLC of the Cyberknife-M6. Five fiducials were attached to the Delta4 phantom in order to be able to track the phantom before and during measurements. For eight SBRT treatment plans (two liver, two prostate, one lung, three bone metastases) additional verification plans were recalculated on the Delta4 phantom using MultiPlan. Dicom data was exported from MultiPlan and was adapted in order to be compatible with the Delta4 software. The measured and calculated dose distributions were compared using the gamma analysis of the Delta4 system. Results: All eight SBRT plans were successfully measured with the aid of the Delta4 system. In the mean, 98.0±1.9%, 95.8±4.1% and 88.40±11.4% of measured dose points passed the gamma analysis using a global dose deviation criterion of 3% (100% corresponds to the dose maximum) and a distance-to-agreement criterion of 3 mm, 2 mm and 1 mm, respectively, and a threshold of 20%. Conclusion: Pre-treatment QA of SBRT plans using the Delta4 system on a Cyberknife-M6 is feasible. Measured dose distributions of SBRT plans showed clinically acceptable agreement with the corresponding calculated dose distributions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Design and analysis of CXL performance models for tightly-coupled heterogeneous computing

Truly heterogeneous systems enable partitioned workloads to be mapped to the hardware that nets the best performance. However, current practice requires that inter-device communication between different vendors' hardware use host memory as an intermediary step. To date, there are no widely adopted solutions that allow accelerators to directly transfer data. A new cache-coherent protocol, CXL, aims to facilitate easier, fine-grained sharing between accelerators. In this work we analyze existing methods for designing heterogeneous applications that target GPUs and FPGAs working collaboratively, followed by an exploration to show the benefits of a CXL-enabled system. Specifically, we develop a test application that utilizes both an NVIDIA P100 GPU and a Xilinx U250 FPGA to show current communication limitations. From this application, we capture overall execution time and throughput measurements on the FPGA and GPU. We use these measurements as inputs to novel CXL performance models to show that using CXL caching instead of host memory results in a 1.31X speedup, while a more tightly-coupled pipelined implementation using CXL-enabled hardware would result in a speedup of 1.45X.

Cabrera, Anthony↗