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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predictable third harmonic generation in GaAs metasurfaces through group theory inverse design of meta-atoms

Here we report the group theory-based inverse design of meta-atoms for a dielectric metasurface in GaAs with predictable optical linear response and third harmonic generation (THG). Six sharp Fano resonances have been observed with a corresponding polarization dependence as predicted by group theory and the meta-atom’s symmetry in the D2h point group. THG has been observed for two modes under x-polarization excitation and one mode for y-polarization, in agreement with theoretical symmetry predictions. The polarization-dependent THG aspect ratio was observed to reach as high as 108. Through strategic structural or symmetry-preserving perturbations, it was shown that the THG can be enhanced or reduced by a factor of 7. The highest THG conversion efficiency was estimated to be 3.1×10-7 at the pump intensity of 1.51 MW/cm2. This high THG conversion efficiency indicates that our group theory approach to modal engineering opens a new path towards optical nonlinearity tuning in dielectric metasurfaces.

Aoueille, Andrew↗
DOE OSTI2026

Paradigm for universal quantum information processing with integrated acousto-optic frequency beamsplitters

Frequency-bin encoding offers tremendous potential in quantum photonic information processing, in which a single waveguide can support hundreds of lightpaths in a naturally phase-stable fashion. This stability, however, comes at a cost: arbitrary unitary operations can be realized by cascaded electro-optic phase modulators and pulse shapers, but require nontrivial numerical optimization for design and have thus far been limited to discrete tabletop components. In this article, we propose, formalize, and computationally evaluate a new paradigm for universal frequency-bin quantum information processing using acousto-optic scattering processes between distinct transverse modes. We show that controllable phase matching in intermodal processes enables 2 × 2 frequency beamsplitters and transverse-mode-dependent phase shifters, which together comprise cascadable FRequency-transverse-mODe Operations (FRODOs) that can synthesize any unitary via analytical decomposition procedures. Modeling the performance of both random gates and discrete Fourier transforms, we demonstrate the feasibility of high-fidelity quantum operations with existing integrated photonics technology, highlighting prospects of parallelizable operations achieving 100% bandwidth utilization. Our approach is realizable with CMOS technology, opening the door to scalable on-chip quantum information processing in the frequency domain.

Lukens, Joseph M. [Purdue Univ., West Lafayette, I↗
DOE OSTI2022

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n rs495828 = 53 and n rs505922 = 59); strongest association with venous embolism, odds ratio (OR rs495828 1.33 (p = 1.32 x 10 –199 ), and thrombosis OR rs505922 1.33, p = 2.2 x10 -265 . Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10 –191 ; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10 –12 . The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10 -23 , lupus OR 0.84, p = 3.97 x 10 –06 . PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10 –13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Using case-level context to classify cancer pathology reports

Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence—for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We test our approach on a corpus of 431,433 cancer pathology reports, and we show that incorporating case-level context significantly boosts classification accuracy across six classification tasks—site, subsite, laterality, histology, behavior, and grade. We expect that with minimal modifications, our add-on can be applied towards a wide range of other clinical text-based tasks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Mapping the immunogenic landscape of near-native HIV-1 envelope trimers in non-human primates

The induction of broad and potent immunity by vaccines is the key focus of research efforts aimed at protecting against HIV-1 infection. Soluble native-like HIV-1 envelope glycoproteins have shown promise as vaccine candidates as they can induce potent autologous neutralizing responses in rabbits and non-human primates. In this study, monoclonal antibodies were isolated and characterized from rhesus macaques immunized with the BG505 SOSIP.664 trimer to better understand vaccine-induced antibody responses. Our studies reveal a diverse landscape of antibodies recognizing immunodominant strain-specific epitopes and non-neutralizing neo-epitopes. Additionally, we isolated a subset of mAbs against an epitope cluster at the gp120-gp41 interface that recognize the highly conserved fusion peptide and the glycan at position 88 and have characteristics akin to several human-derived broadly neutralizing antibodies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

SSGF Mineral Major Elements and Lithium Concentration

Presented are major element and lithium concentrations of minerals from the Salton Sea Geothermal Field (SSGF), located in the Imperial Valley, California. With a recent increase in demand for lithium, the area is now being studied as a source of geothermal brine for lithium extraction. This study was performed to help quantify lithium storage in the SSGF brine and surrounding minerals. Rocks and brines sampled in this study are from surface rhyolitic domes on the South Eastern shore of the Salton Sea, the sedimentary and evaporitic rocks in the Durmid Hills, rhyolitic drill clippings previously studied by Schmitt & Hulen, commercial drill wells, and CA State 2-14 well.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Utah FORGE: LBNL Reports on VEMP Electromagnetic Data Collection and Processing - 2024

This archive contains reports related to Vertical Electromagnetic Profiling (VEMP) tool data collection and processing at Utah FORGE in 2024. The first report describes LBNL's effort to collect electromagnetic geophysical data with the tool in well 78-32B and a downhole electrode in well 16A. The second report describes the final data acquisition and processing of the VEMP electromagnetic data collected at the Utah FORGE site in May of 2024. Also included are a noise analysis as well as a comparison of the data to numerical models. This was originally presented as a paper at the 2025 Stanford Geothermal Workshop.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Chymotrypsin-like Elastase-1 Mediates Progressive Emphysema in Alpha-1 Antitrypsin Deficiency

Alpha-1 antitrypsin (AAT) deficiency is a rare disease affecting approximately 1 in 2000 White individuals with approximately 10% of these individuals developing AATD lung disease. This lung disease is marked by progressive alveolar loss despite the withdrawal of triggering agents such as cigarette smoke. Although the PiZZ genotype is the most common mutation, there are over 100 described variants making true population estimates difficult and AAT deficiency is typically diagnosed by reduced levels of AAT in the blood. Typically developing in the fourth and fifth decades of life, AAT-deficient lung disease is marked by progressive emphysema and is the fourth leading indication for lung transplantation. AAT augmentation therapy does not prevent disease progression making the development of new therapeutic approaches critical. Chymotrypsin-like elastase 1 (CELA1) is a serine protease synthesized and secreted by alveolar type 2 cells with a physiologic role in reducing postnatal lung elastance. At a molecular level, CELA1 binds and cleaves non-crosslinked, hydrophobic domains of tropoelastin, and its binding to lung elastin fibers is increased with strain—similar to other pancreatic elastases. CELA1 is neutralized by covalent binding with AAT, and Cela1 -/- mice were completely protected from emphysema in an antisense oligonucleotide model of AAT-deficient emphysema. This model, however, did not include any injury apart from administration of the antisense oligonucleotide with levels of emphysema exceeding that seen in mice with genetic ablation of 5 Serpina1 paralogues and subjected to tracheal lipopolysacharide or cigarette smoke. Here, we use this murine genetic model of AAT deficiency to test the role of the CELA1 gene in AAT-deficient emphysema using multiple models to show that CELA1 has a role in progressive airspace enlargement in AAT-deficiency independent of inflammation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Dataset for Blueprinting Electrified Transit System Implementation

This dataset contains the figures and tabulated results generated from a system-level optimization study of transit fleet electrification planning. The dataset does not include executable modeling code required to reproduce the optimization. The dataset includes results for optimized charging infrastructure deployment by location and power level and service block assignments by fuel type, battery capacity selections, and distributed energy resource sizing. It also contains aggregated financial results, capital expenditures, operating cost summaries, net present cost comparisons across scenarios, and quantified air quality impacts. Results are structured to reflect multiple planning scenarios, including heuristic electrification plans, system-optimized configurations, and sensitivity cases with alternative objective weightings. The modeling was developed using publicly available General Transit Feed Specification data from Omnitrans and standardized modeling assumptions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Dataset for Blueprinting Electrified Transit System Implementation

This dataset contains the figures and tabulated results generated from a system-level optimization study of transit fleet electrification planning. The dataset does not include executable modeling code required to reproduce the optimization. The dataset includes results for optimized charging infrastructure deployment by location and power level and service block assignments by fuel type, battery capacity selections, and distributed energy resource sizing. It also contains aggregated financial results, capital expenditures, operating cost summaries, net present cost comparisons across scenarios, and quantified air quality impacts. Results are structured to reflect multiple planning scenarios, including heuristic electrification plans, system-optimized configurations, and sensitivity cases with alternative objective weightings. The modeling was developed using publicly available General Transit Feed Specification data from Omnitrans and standardized modeling assumptions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Surface water geochemistry along St. Louis River Estuary (Duluth/Superior, MN/WI)

This dataset is aimed at understanding changes in surface water chemistry associated with urbanization in the Great Lakes region. Surface water chemistry including cations, anions, organic and inorganic carbon, and nitrogen were collected from six locations along St. Louis River – a freshwater estuary entering Lake Superior (Duluth/Superior, MN/WI). The Duluth/Superior, MN/WI metropolitan area is the largest port on the United States side of Lake Superior. Samples were collected near different land uses every two weeks from late July 2023 to the onset of ice cover in November 2023. Water samples were analyzed using In-Situ AquaTroll 500 Multiparameter Sonde with Ammonium Ion Selective Electrode and Chlorophyll-a sensor (unfiltered), METTLER TOLEDO FiveEasy Plus FP20 and METTLER TOLEDO LE407 probe (unfiltered); HACH DR300 Pocket Colorimeter Iron FerroVer (filtered 0.22 μm in field); Shimadzu TOC-L Total Organic Carbon Analyzer with TNM-L Total Nitrogen Unit (filtered 0.22 μm in field); Agilent 8900 triple quadrupole ICP-MS (ICP-QQQ) (filtered 0.22 μm in field); and Dionex ICS-6000 HPIC System (filtered 0.22 μm in field).The data package is comprised of 5 files. dd.csv contains the description of columns in Geochemistry_LSNERR_water.csv and Sampling_sites.csv. flmd.csv contains descriptions of each file in the dataset. README.txt contains description of the dataset structure and file content. Geochemistry_LSNERR_water.csv contains geochemistry data for six sampling locations along the St. Louis River. Sampling_sites.csv contains latitude and longitude coordinates for each of the six sampling site locations along the St. Louis River.This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

End-of-Life Plastics Management: A Review: Mechanical recycling, pyrolysis and hydrocracking methods

End-of-life plastics present a significant challenge to achieving a sustainable economy. It is crucial to develop environmentally friendly technologies to process the waste streams beyond landfilling. This review provides a detailed overview of end-of-life plastics management, covering mechanical recycling, pyrolysis and hydrocracking methods. Mechanical recycling is the predominant technique employed on a large scale in recycling end-of-life plastics, and this review discusses the technoeconomic assessment and life cycle assessment (LCA) of mechanical recycling. This review also summarises key studies concentrating on chemical recycling techniques for handling end-of-life plastics. Among these, pyrolysis and hydrocracking are discussed in depth. Recent advancements and fundamentals of these two techniques are covered, highlighting their significance in tackling the plastic waste challenge. The prospects of scaling up pyrolysis and hydrocracking technologies are interpreted in terms of technical and economic feasibility. The discussion concludes with recommendations for future research to commercialise chemical recycling of end-of-life plastics.

Chemistry↗
DOE OSTI2021

Argonaut - A Robotic System for Cryogenic Environments

Fermilab and the HEP community invest significant resources into liquid argon detectors. The largest and most expensive of these detectors will be located in the Deep Underground Neutrino Experiment (DUNE). However, recent experiences have shown that there are limited avenues of monitoring, intervention, and interaction in the internal liquid environment. This proposal shows a technological path that could provide a valuable tool to ensure or at least improve the management of these HEP detectors. The development of a robotic system named Argonaut will demonstrate several technologies including 1) demonstration of suitable mobility of a small robotic device at liquid argon temperatures, 2) demonstration of wireless communication, 3) demonstration of improved diagnostics capabilities - such as tunable optics with motion control, 4) demonstration of interconnectivity of a robotic system with hardware residing within the detector. This initial research will be a seed for extended development in cold robotics and associated technologies. This work will allow FNAL to contribute a significant technology capability to recent efforts to cryogenic detector operations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Improving Magnetic Materials for RCS Cavity Tuners

Within the Lab Directed R&D Program at Fermilab, and in partnership with National Magnetics, we have recently begun to study and attempt to improve the loss parameter in garnet material. This could be used for fast tuner applications such as in rapid cycling synchrotrons.

Madrak, Robyn Leigh↗
DOE OSTI2021

Recent Progress Toward a Conduction-Cooled Superconducting Radiofrequency Electron Gun

High-repetition-rate electron sources have widespread applications. This contribution discusses the progress toward a proof-of-principle demonstration for a conduction-cooled electron source. The source consists of a simple modification of an elliptical cavity that enhances the field electric field at the photocathode surface. The source was cooled to cryogenic temperatures and preliminary measurements for the quality factor and accelerating field were performed. Additionally, we present future plans to improve the source along with simulated beam-dynamics performances.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

FrESCO: Framework for Exploring Scalable Computational Oncology

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information from electronic health records. This data is then used to create summary statistics about cancer incidence and mortality to facilitate population health monitoring. Extracting phenotypic information from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating the information extraction process from cancer pathology reports has the potential to improve data quality by extracting information in a consistent manner across registries. It can also improve patient outcomes by reducing the time from diagnosis, enabling rapid case ascertainment for clinical trials. Here we present FrESCO, a modular deep-learning natural language processing (NLP) library initially designed for extracting pathology information from clinical text documents. This repository is not solely limited to clinical medical text, but may also be used by researchers just getting started with NLP methods and those looking for a robust solution for their classification problems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

SSAPy - Space Situational Awareness for Python

SSAPy is a fast and flexible orbit modeling and analysis tool for orbits spanning from low-Earth into the cislunar regime. Orbits can be flexibly specified from common input formats such as Keplerian elements or two-line element (TLE) data files. SSAPy allows users to model satellites and specify parameters such as satellite area, mass, and drag coefficients. SSAPy includes a customizable force-propagation with a range of Earth, Lunar, radiation, atmospheric, and maneuvering models. SSAPy makes use of various community integration methods and can calculate time-evolved orbital quantities, including satellite magnitudes and state vectors. Users can specify various space- and ground-based observation models with support for multiple coordinate and reference frames. SSAPy also supports orbit analysis and propagation methods such as multiple hypothesis tracking and has built-in uncertainty quantification. The majority of SSAPy’s methods are vectorized and parallelizable, allowing for effective use of high-performance computer (HPC) systems. Finally, SSAPy has plotting functionality, allowing users to visualize orbits and trajectories. Examples are shown in Figure 1 and Figure 2.

97 MATHEMATICS AND COMPUTING↗