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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Resolution of a discrepancy in the γ-ray emission probability from the β decay of 137 Ce g

We have deduced the emission probability of the 447-keV γ ray from the ε + β + decay of Ce g 137 (9.0 h) relative to that of the 254-keV γ ray from the Ce m 137 (34.4 h) decay in transient equilibrium. The time-dependent factor in transient equilibrium was applied following the Bateman equation for a radioactive decay chain. The isotope was produced via the La 139 ( p , 3 n ) Ce m , g 137 reaction by bombarding nat La with a proton beam from the 88-in. cyclotron at Lawrence Berkeley National Laboratory. γ -ray intensities were measured using an HPGe detector. The emission probability for the 447-keV γ ray deduced in this work is 1.21(3) (that is 1.21 ± 0.03) per hundred parent decays, which differs significantly from an earlier published value of 2.24(10). We identify the source of this discrepancy to be an incorrect use of the time-dependent factor. Additionally, we have deduced the emission probability of the 504-keV γ ray from the decay of Y g 85 (2.68 h) relative to that of the 232-keV γ ray from the Sr m 85 (1.127 h) decay in transient equilibrium. The isotope was produced via the Sr 86 ( p , 2 n ) Y g 85 reaction by bombarding SrCO 3 86 with a proton beam at the same facility. Overall, the study confirms the assumption of the time-dependent correction for recommending the emission probability of the 504-keV γ ray in the literature. Our work highlights the importance of explicit description by authors of any time-dependent correction they have made when reporting γ -ray intensities for nuclides in transient equilibrium. The need and significance of accurate and precise decay data of Ce g 137 and Y g 85 in basic science and medicine is briefly outlined.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Precision Loading and Delivery of Molecular Cargo by Size-Controlled Coacervation of Gold Nanoparticles Functionalized with Elastin-like Peptides

Thermoresponsive elastin-like peptides (ELPs) have been extensively investigated in biotechnology and medicine, but little attention has been paid to the process by which coacervation causes ELP-decorated particles to aggregate. Here, using gold nanoparticles (AuNPs) functionalized with a cysteine-terminated 96-repeat of the VPGVG sequence (V96-Cys), we show that the size of the clusters that reversibly form above the ELP transition temperature can be finely controlled in the 250 to 930 nm range by specifying the concentration of free V96-Cys in solution and using AuNPs of different sizes. We further find that the localized surface plasmon resonance peak of the embedded AuNPs progressively red-shifts with cluster size, likely due to an increase in particle–particle contacts. We exploit this fine control over size to homogeneously load precise amounts of the dye Nile Red and the antibiotic Tetracycline into clusters of different hydrodynamic diameters and deliver cargos near-quantitatively by deconstructing the aggregates below the ELP transition temperature. Beyond establishing a key role for free ELPs in the agglomeration of ELP-functionalized particles, our results provide a path for the thermally controlled delivery of precise quantities of molecular cargo. This capability might prove useful in combination photothermal therapies and theranostic applications, and to trigger spatially and temporally uniform responses from biological, electronic, or optical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Performance Comparison of Object Detection Networks for Shrapnel Identification in Ultrasound Images

Ultrasound imaging is a critical tool for triaging and diagnosing subjects but only if images can be properly interpreted. Unfortunately, in remote or military medicine situations, the expertise to interpret images can be lacking. Machine-learning image interpretation models that are explainable to the end user and deployable in real time with ultrasound equipment have the potential to solve this problem. We have previously shown how a YOLOv3 (You Only Look Once) object detection algorithm can be used for tracking shrapnel, artery, vein, and nerve fiber bundle features in a tissue phantom. However, real-time implementation of an object detection model requires optimizing model inference time. Here, we compare the performance of five different object detection deep-learning models with varying architectures and trainable parameters to determine which model is most suitable for this shrapnel-tracking ultrasound image application. We used a dataset of more than 16,000 ultrasound images from gelatin tissue phantoms containing artery, vein, nerve fiber, and shrapnel features for training and evaluating each model. Every object detection model surpassed 0.85 mean average precision except for the detection transformer model. Overall, the YOLOv7tiny model had the higher mean average precision and quickest inference time, making it the obvious model choice for this ultrasound imaging application. Other object detection models were overfitting the data as was determined by lower testing performance compared with higher training performance. In summary, the YOLOv7tiny object detection model had the best mean average precision and inference time and was selected as optimal for this application. Next steps will implement this object detection algorithm for real-time applications, an important next step in translating AI models for emergency and military medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

First-Principles Simulation of Beam-Induced Processes Underlying Atomic Manipulation in Electron Microscopes

The development of experimental methods and apparatuses capable of promoting atomically precise material manipulations holds great promise for realizing the ultimate limit of feature miniaturization in materials and devices. The ability to modify materials atom by atom is anticipated to usher in new technologies in areas as diverse as separation science, medicine, and quantum information science. Historically, scanning probe-based techniques have been the most prominent approaches in this space. However, these methods are best suited for the manipulation of surface-exposed regions of materials, as the strong perturbations required for bond scission are delivered most effectively to atoms in the near-proximity to the scanning probe. In contrast, convergent electron beams with energies tuned slightly below the threshold for inducing irreversible knock-on damage have recently been employed (within scanning transmission electron microscopy) to promote atomic-scale bond rearrangements in various beam-stable solids. Currently, however, the efficiency and selectivity of beam-induced atomic manipulation processes with focused electron beams are such that long irradiation times are required to induce a desired atomic rearrangement. With a better understanding of the underlying physics dictating the outcome of a given irradiation event, methods can be devised to improve the efficiency of these techniques so that their promise can be fully realized through widespread adoption.To this end, this Account details our recent efforts to develop and apply tractable first-principles simulation approaches for studying the response of materials to electric beam-like external electric potentials applied in real space. We briefly review the concepts and capabilities in the area of atomically precise materials manipulation and review the early demonstrations of accomplishments in this area, focusing on studies using scanned convergent electron beam probes in particular. We expound upon the depth of the challenge and identify critical shortcomings of theoretical methods that have previously been employed in the simulation of beam-induced processes. We then describe the computational methods that we have generalized from the concepts and tools most commonly applied to the study of molecular photochemistry and how our adaptations of these methods can be employed to capture the relevant dynamical phenomena for beam-induced processes ranging from the initial electron scattering to the ensuing multistate reactions. Here, we contextualize these methods within the current state of the art in this area, which has historically focused primarily on the simulation of inelastic image formation in the electron microscope for the purpose of interpreting the results of quantitative electron microscopy experiments. We demonstrate that the spatial distribution of state-specific excitation rates due to the presence of an external (probe) electric charge is inhomogeneous, such that irradiation at particular locations in materials can favor specific electronic transitions (and disallow others). In addition to the potential for excited-state reaction pathways to be accessed through the initial inelastic scattering of the tightly focused electron beam from the targeted atoms, we also identify favorable conditions for the electronically nonadiabatic evolution of the highly vibrationally excited system to open complex multistate reaction pathways. Implications of the early results for understanding the mechanisms and potential routes to improved efficiency and selectivity in beam-induced reactions are discussed. We conclude with a summary of the current state of theory and modeling capabilities in this area and provide our perspective on future directions for theoretical and experimental developments that we view as crucial to advancing the use of convergent electron beams in mode-specific, atomically precise platforms for direct-write materials modifications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗
DOE OSTI2022

Large Scale Study of Ligand–Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein–ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

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

Unveiling the nanoscale architectures and dynamics of protein assembly with in situ atomic force microscopy

Proteins play a vital role in different biological processes by forming complexes through precise folding with exclusive inter- and intra-molecular interactions. Understanding the structural and regulatory mechanisms underlying protein complex formation provides insights into biophysical processes. Furthermore, the principle of protein assembly gives guidelines for new biomimetic materials with potential applications in medicine, energy, and nanotechnology. Atomic force microscopy (AFM) is a powerful tool for investigating protein assembly and interactions across spatial scales (single molecules to cells) and temporal scales (milliseconds to days). It has significantly contributed to understanding nanoscale architectures, inter- and intra-molecular interactions, and regulatory elements that determine protein structures, assemblies, and functions. This review describes recent advancements in elucidating protein assemblies with in situ AFM. We discuss the structures, diffusions, interactions, and assembly dynamics of proteins captured by conventional and high-speed AFM in near-native environments and recent AFM developments in the multimodal high-resolution imaging, bimodal imaging, live cell imaging, and machine-learning-enhanced data analysis. These approaches show the significance of broadening the horizons of AFM and enable unprecedented explorations of protein assembly for biomaterial design and biomedical research.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Association of Radiation Exposure with Stable Chromosome Aberrations in Atomic Bomb Survivors Based on DS02R1 Dosimetry and FISH Methods

The frequency of stable chromosome aberrations (sCA) in lymphocytes is a recognized radiation biological dosimeter. Its analysis can provide insights into factors that affect individual susceptibility as well as into the adequacy of radiation dose estimates used in studies of atomic bomb survivors. We analyzed the relationship between atomic bomb radiation exposure using the most recent DS02R1 dose estimates and the frequency of sCA as determined by FISH in 1,868 atomic bomb survivors. We investigated factors that may affect the background sCA rate and the shape and magnitude of the dose response. As in previous analyses of sCA in atomic bomb survivors that were based on Giemsa staining methods and used older DS86 dose estimates, the relationship between radiation dose and sCA rate was significant (P < 0.0001) with a linear-quadratic relationship at lower doses that did not persist at higher doses. As before, age at the time of the bombing and type of radiation shielding were significant dose-effect modifiers (P < 0.0001), but in contrast the difference in dose response by city was not so pronounced (P = 0.026) with a city effect not evident at doses below 1.25Gy. Background sCA rate increased with age at the time of examination (P < 0.0001), but neither sex, city, nor smoking was significantly associated with background rate. Based on FISH methods and recent dosimetry, the relationship between radiation dose and sCA frequency is largely consistent with previous findings, although the lesser importance of city as an effect modifier may reflect better dosimetry as well as more reproducible scoring of sCA. The persisting difference in sCA dose response by shielding category points to remaining problems with the accuracy or precision of radiation dose estimates in some A-bomb survivors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Prospects of Nanoscience with Nanocrystals: 2025 Edition

Abstract Nanocrystals (NCs) of various compositions have made important contributions to science and technology, with their impact recognized by the 2023 Nobel Prize in Chemistry for the discovery and synthesis of semiconductor quantum dots (QDs). Over four decades of research into NCs has led to numerous advancements in diverse fields, such as optoelectronics, catalysis, energy, medicine, and recently, quantum information and computing. The last 10 years since the predecessor perspective “Prospect of Nanoscience with Nanocrystals” was published in ACS Nano have seen NC research continuously evolve, yielding critical advances in fundamental understanding and practical applications. Mechanistic insights into NC formation have translated into precision control over NC size, shape, and composition. Emerging synthesis techniques have broadened the landscape of compounds obtainable in colloidal NC form. Sophistication in surface chemistry, jointly bolstered by theoretical models and experimental findings, has facilitated refined control over NC properties and represents a trusted gateway to enhanced NC stability and processability. The assembly of NCs into superlattices, along with two-dimensional (2D) photolithography and three-dimensional (3D) printing, has expanded their utility in creating materials with tailored properties. Applications of NCs are also flourishing, consolidating progress in fields targeted early on, such as optoelectronics and catalysis, and extending into areas ranging from quantum technology to phase-change memories. In this perspective, we review the extensive progress in research on NCs over the past decade and highlight key areas where future research may bring further breakthroughs.

Chemistry↗
DOE OSTI2024

Using AI Segmentation Models to Improve Foreign Body Detection and Triage from Ultrasound Images

Medical imaging can be a critical tool for triaging casualties in trauma situations. In remote or military medicine scenarios, triage is essential for identifying how to use limited resources or prioritize evacuation for the most serious cases. Ultrasound imaging, while portable and often available near the point of injury, can only be used for triage if images are properly acquired, interpreted, and objectively triage scored. Here, we detail how AI segmentation models can be used for improving image interpretation and objective triage evaluation for a medical application focused on foreign bodies embedded in tissues at variable distances from critical neurovascular features. Ultrasound images previously collected in a tissue phantom with or without neurovascular features were labeled with ground truth masks. These image sets were used to train two different segmentation AI frameworks: YOLOv7 and U-Net segmentation models. Overall, both approaches were successful in identifying shrapnel in the image set, with U-Net outperforming YOLOv7 for single-class segmentation. Both segmentation models were also evaluated with a more complex image set containing shrapnel, artery, vein, and nerve features. YOLOv7 obtained higher precision scores across multiple classes whereas U-Net achieved higher recall scores. Using each AI model, a triage distance metric was adapted to measure the proximity of shrapnel to the nearest neurovascular feature, with U-Net more closely mirroring the triage distances measured from ground truth labels. Overall, the segmentation AI models were successful in detecting shrapnel in ultrasound images and could allow for improved injury triage in emergency medicine scenarios.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Latent bone modelling for estimation of plutonium concentration in skeleton of former nuclear workers

Abstract The skeleton is a major plutonium retention site in the human body. Estimation of the total plutonium activity in the skeleton is a challenging problem. For most tissue donors at the United States Transuranium and Uranium Registries, a limited number of bone samples is available. The skeleton activity is calculated using plutonium activity concentration (Cskel) and skeleton weight. In this study, latent bone modelling was used to estimate Cskel from the limited number of analysed bone samples. Data from 13 non-osteoporotic whole-body donors were used to develop latent bone model (LBM) to estimate Cskel for seven cases with four to eight analysed bone samples. LBM predictions were compared to Cskel estimated using an arithmetic mean in terms of accuracy and precision. For the studied cases, LBM offered a significant reduction of uncertainty of Cskel estimate.

Environmental Sciences & Ecology↗
DOE OSTI2021

Revisiting a Null Hypothesis: Exploring the Parameters of Oligometastasis Treatment

In the treatment of patients with metastatic cancer, the current paradigm states that metastasis-directed therapy does not prolong life. This paradigm forms the basis of clinical trial null hypotheses, where trials are built to test the null hypothesis that patients garner no overall survival benefit from targeting metastatic lesions. However, with advancing imaging technology and increasingly precise techniques for targeting lesions, a much larger proportion of metastatic disease can be treated. As a result, the life-extending benefit of targeting metastatic disease is becoming increasingly clear.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Accurate Dosimetry for Radiobiology

Accurate radiation dose is required to ensure reproducibility in establishing the radiobiological effect in biological systems among institutions. The dose should be the most precise and accurate parameter of the entire process. The goal is a system to provide uniform radiation dose verification among institutions that is traceable to the National Institute of Standards and Technology (NIST) through an Accredited Dosimetry Calibration Laboratory.

61 RADIATION PROTECTION AND DOSIMETRY↗
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 OSTI2020

A Novel Low-Cost Method of Manufacturing Nb3Sn Superconductors with Multiple-Tin-Tube Sources (CRADA FRA-2008-0001 Final Report)

In order to successfully sustain a fusion reaction, peak magnetic fields on the order of 12-13 Tesla will be required. Magnetic fields of this magnitude can only be accomplished by advanced superconductors such as Nb3Sn. However, the economic success of a fusion machine will depend on further improvements in the cost-performance of the Nb3Sn conductor. This project will develop a novel, low-cost, multiple-tin-tube process as a new manufacturing approach for large-scale Nb3Sn-conductor production. The process will be suitable for the efficient production of larger strands (0.83 mm), consistent with ITER (International Thermonuclear Experimental Reactor) specifications. In Phase I, Cu/Nb composites were manufactured and shaped into sub-elements. These sub-elements were tin-coated by electroplating, assembled into a precise-fit restack billet tube, and drawn to 0.83 mm diameter. In Phase II, the process will be scaled-up to full production levels. The improved Nb3Sn conductor should have an immediate benefit for high-field magnet applications. A prototype fusion machine, based on a cost effective Nb3Sn conductor, would have enormous economic and social benefits. In addition, the conductor should be applicable to nuclear magnetic resonance (NMR), which has requirements for use in chemical research, biochemistry, pharmaceutical chemistry, polymer science, petroleum research, agricultural chemistry, and medicine. Leszek Motowidlo, Principal Investigator, will be responsible for the overall coordination of the effort. He and others of SupraMagnetics staff will design and fabricate protoype PIT Nb3Sn conductors for evaluation at Fermilab. Emanuela Barzi will be responsible for the Fermilab subcontract and will coordinate and supervise critical current testing Nb3Sn strands and cable fabrication and evaluation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Cancer cell membrane-coated rare earth doped nanoparticles for tumor surgery navigation in NIR-II imaging window

With the attractive characteristics of low toxicity, narrow emission spectra, long fluorescence lifetime, and no photobleaching, rare-earth doped nanoparticles (RENPs) have become promising imaging nanoplatforms in the second near-infrared window (NIR-II, 1000–1700 nm). Many studies have been devoted to different surface modification strategies of RENPs to achieve good NIR-II tumor imaging property. However, the tumor imaging efficiency of these approaches remains disappointing. Herein, two methods were pursued to modify RENPs with either polyethylene glycol (PEG) or cancer-cell-membrane to generate PEGylated-RENPs and cancer-cell-membrane camouflaged RENPs (CC-RENPs), respectively. Furthermore, this study demonstrated that cancer-cell-membrane coating of RENPs greatly improved tumor imaging performance in NIR-II window than PEG coating. Besides, CC-RENPs uptakes in liver and spleen significantly decreased. Importantly, CC-RENPs was found to be capable to aid us to pursue precise resection of the tumor. In conclusion, CC-RENPs are capable of targeting tumors and show high tumor NIR-II imaging quality. They are highly promising nanomaterials for future medical applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Design and testing of ultrasound probe adapters for a robotic imaging platform

Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military settings. Ultrasound imaging can be used to rapidly identify free fluid in abdominal and thoracic cavities which could necessitate immediate surgical intervention. However, proper ultrasound image capture requires a skilled ultrasonography technician who is likely unavailable at the point of injury where resources are limited. Instead, robotics and computer vision technology can simplify image acquisition. As a first step towards this larger goal, here, we focus on the development of prototypes for ultrasound probe securement using a robotics platform. The ability of four probe adapter technologies to precisely capture images at anatomical locations, repeatedly, and with different ultrasound transducer types were evaluated across more than five scoring criteria. Testing demonstrated two of the adapters outperformed the traditional robot gripper and manual image capture, with a compact, rotating design compatible with wireless imaging technology being most suitable for use at the point of injury. Next steps will integrate the robotic platform with computer vision and deep learning image interpretation models to automate image capture and diagnosis. This will lower the skill threshold needed for medical imaging-based triage, enabling this procedure to be available at or near the point of injury.

47 OTHER INSTRUMENTATION↗