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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Near-constant retreat rate of a terrestrial margin of the Laurentide Ice Sheet during the last deglaciation

The Laurentide Ice Sheet (LIS) was the largest ice sheet during the last glacial period. An accurate representation of its behavior during the last deglaciation is critical to understanding its influence on and response to a changing climate. Here we use 10 Be dating and Bayesian modeling to track the recession of the southwest sector of the Labrador Dome of the LIS along an ~500-km-long transect west of Lake Superior during the last deglaciation. This transect reflects terrestrial ice-margin retreat and crosses multiple moraine sets, with the southwestern part of the transect deglaciated by ca. 19 ka and the northeastern part deglaciated by ca. 10 ka. The predominant behavior of the ice margin during this interval is near-constant retreat with retreat rates varying between ~59 m/a and 38 m/a. The moraine sets mark standstills and/or readvances that in total constitute only ~17% of the retreat interval. The spatial and temporal pattern of ice-margin retreat tracked here differs from existing reconstructions that are based on using isochrons to define ice-margin positions. Acknowledging the uncertainties associated with the modeled ages of ice-margin retreat, we suggest that the overall retreat pattern is consistent with forcing by a gradual increase in Northern Hemisphere, high-latitude summer insolation. The pattern of ice-margin retreat is inconsistent with Greenland ice-core temperature records, and thus these records may not be suitable to drive models of the LIS.

58 GEOSCIENCES↗
DOE OSTI2022

Transmission estimation at the quantum Cramér-Rao bound with macroscopic quantum light

The field of quantum metrology seeks to apply quantum techniques and/or resources to classical sensing approaches with the goal of enhancing the precision in the estimation of a parameter beyond what can be achieved with classical resources. Theoretically, the fundamental minimum uncertainty in the estimation of a parameter for a given probing state is bounded by the quantum Cramér-Rao bound. From a practical perspective, it is necessary to find physical measurements that can saturate this fundamental limit and to show experimentally that it is possible to perform measurements with the required precision to do so. Here we perform experiments that saturate the quantum Cramér-Rao bound for transmission estimation over a wide range of transmissions when probing the system under study with a continuous wave bright two-mode squeezed state. To properly take into account the imperfections in the generation of the quantum state, we extend our previous theoretical results to incorporate the measured properties of the generated quantum state. For our largest transmission level of 84%, we show a 62% reduction over the optimal classical protocol in the variance in transmission estimation when probing with a bright two-mode squeezed state with -8 dB of intensity-difference squeezing. Given that transmission estimation is an integral part of many sensing protocols, such as plasmonic sensing, spectroscopy, calibration of the quantum efficiency of detectors, etc., the results presented promise to have a significant impact on a number of applications in various fields of research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Random Quantum Circuits

Quantum circuits—built from local unitary gates and local measurements—are a new playground for quantum many-body physics and a tractable setting to explore universal collective phenomena far from equilibrium. These models have shed light on longstanding questions about thermalization and chaos, and on the underlying universal dynamics of quantum information and entanglement. In addition, such models generate new sets of questions and give rise to phenomena with no traditional analog, such as dynamical phase transitions in quantum systems that are monitored by an external observer. Quantum circuit dynamics is also topical in view of experimental progress in building digital quantum simulators that allow control of precisely these ingredients. Randomness in the circuit elements allows a high level of theoretical control, with a key theme being mappings between real-time quantum dynamics and effective classical lattice models or dynamical processes. Many of the universal phenomena that can be identified in this tractable setting apply to much wider classes of more structured many-body dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Turbo FRMAC 2021 v.11.0.0

The Turbo FRMAC analysis tool performs complex calculations to quickly evaluate radiological hazards during an emergency response by assessing impacts to the public, workers, and the food supply. Turbo FRMAC can be used to evaluate the hazard from a wide variety of radiological incidents. Turbo FRMAC calculations are based on methods established by the Federal Radiological Monitoring and Assessment (FRMAC). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10713 O

Whitener, Dustin↗
DOE OSTI2024

Mnemosyne

SAND2024-08570O Mnemosyne is an interactive tool for finding, retrieving, and exploring information about U.S. nuclear tests documented in the National Nuclear Security Administration’s NV-209 report. It also acts as an information architecture and codebase for integrating additional information and computational tools related to these tests at the unclassified and classified levels. Users can search by any number of nuclear test attributes—name, yield range, altitude ranges, purpose of a test—and find all matching tests. Users can also retrieve specific test information published in NV-209. The tool displays geospatial and topological data about test location, and it provides an information architecture for storing additional contextual material, such as photographs. Mnemosyne provides a capability of interfacing with HYCHEM, Sandia's nuclear detonation optical waveform tool. The software is designed for use by government, academia, military, and research institutions. The software will likely be advanced to integrate seismic data and the nuclear detonation optical signal simulation code radCTH. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fisher, Dustin↗
DOE OSTI2024

MAPLE v.1.0

SAND2025-00659O MAPLE is a software tool that uses epigenomic data to predict gene expression. MAPLE uses a set of epigenomic modifications to determine the effect on gene expression in a specific subset of species. The algorithm can be trained on additional species and epigenomic modifications, enhancing its predictive capabilities. EAGLE employs a hybrid neural network architecture, featuring a convolutional front-end and a multi-head attention layer, to process pre-processed signal data as input. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Davis IV, Warren↗
DOE OSTI2025

MasQiTT

SAND2025-03471O MasQiTT software is a proof-of-concept code that implements the Secure MQTT protocol. It demonstrates a publish/subscribe model of message passing within a network where the publishers can encrypt messages according to a topic and the subscribers can decrypt those messages. The example code shows an example of deployment of an end-to-end system that includes certificate authority and key management in addition to basic implementation of the protocol. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fisher, Andrew [Sandia National Lab. (SNL-CA), Liv↗
DOE OSTI2025

FentaML Codebase

Analysis scripts to analyze Mass spectral datasets for fentaML project publication

Arasteh, Kourosh [Lawrence Livermore National Labo↗
DOE OSTI2025

Random forest models accurately classify synthetic opioids using high-dimensionality mass spectrometry datasets

Detection of novel threat agents presents several challenges, a principle one being the development of untargeted methods to screen an increasing number of threat chemicals whose exact structures are unknown. With the use of Machine Learning (ML) tools, we can guide the development of analytical methods for broad-spectrum detection of unbounded threat chemical families in complex mixtures. Toward this goal, we used nominal mass and high-resolution mass spectrometry data for hundreds of synthetic opioids and non-opioid compounds. We tested two ML techniques, logistic regression and random forest, to develop models towards a practical, implementable method for opioid detection. We found that of these tested ML methods, random forest models resulted in the highest validation accuracy (95+%) for both nominal mass and high-resolution classification of opioids versus non-opioids, with low false positive and false negative rates. The RF models were then used to successfully predict the classification of 10 compounds—five opioids and five non-opioids not part of the training and validation analysis. This application of ML is a critical step towards the development of field-deployable nominal mass spectrometers with ML-driven analyses for classification of emergent threats.

Arasteh, Kourosh [Lawrence Livermore National Labo↗
DOE OSTI2024

An emerging multi-omic understanding of the genetics of opioid addiction

Opioid misuse, addiction, and associated overdose deaths remain global public health crises. Despite the tremendous need for pharmacological treatments, current options are limited in number, use, and effectiveness. Fundamental leaps forward in our understanding of the biology driving opioid addiction are needed to guide development of more effective medication-assisted therapies. This Review focuses on the omics-identified biological features associated with opioid addiction. Recent GWAS have begun to identify robust genetic associations, including variants in OPRM1, FURIN, and the gene cluster SCAI/PPP6C/RABEPK. An increasing number of omics studies of postmortem human brain tissue examining biological features (e.g., histone modification and gene expression) across different brain regions have identified broad gene dysregulation associated with overdose death among opioid misusers. Drawn together by meta-analysis and multi-omic systems biology, and informed by model organism studies, key biological pathways enriched for opioid addiction–associated genes are emerging, which include specific receptors (e.g., GABAB receptors, GPCR, and Trk) linked to signaling pathways (e.g., Trk, ERK/MAPK, orexin) that are associated with synaptic plasticity and neuronal signaling. Studies leveraging the agnostic discovery power of omics and placing it within the context of functional neurobiology will propel us toward much-needed, field-changing breakthroughs, including identification of actionable targets for drug development to treat this devastating brain disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The core autophagy machinery is not required for chloroplast singlet oxygen-mediated cell death in the Arabidopsis thaliana plastid ferrochelatase two mutant

Chloroplasts respond to stress and changes in the environment by producing reactive oxygen species (ROS) that have specific signaling abilities. The ROS singlet oxygen ( 1 O 2 ) is unique in that it can signal to initiate cellular degradation including the selective degradation of damaged chloroplasts. This chloroplast quality control pathway can be monitored in the Arabidopsis thaliana mutant plastid ferrochelatase two ( fc2 ) that conditionally accumulates chloroplast 1 O 2 under diurnal light cycling conditions leading to rapid chloroplast degradation and eventual cell death. The cellular machinery involved in such degradation, however, remains unknown. Recently, it was demonstrated that whole damaged chloroplasts can be transported to the central vacuole via a process requiring autophagosomes and core components of the autophagy machinery. The relationship between this process, referred to as chlorophagy, and the degradation of 1 O 2 -stressed chloroplasts and cells has remained unexplored. Results To further understand 1 O 2 -induced cellular degradation and determine what role autophagy may play, the expression of autophagy-related genes was monitored in 1 O 2 -stressed fc2 seedlings and found to be induced. Although autophagosomes were present in fc2 cells, they did not associate with chloroplasts during 1 O 2 stress. Mutations affecting the core autophagy machinery ( atg5 , atg7 , and atg10 ) were unable to suppress 1 O 2 -induced cell death or chloroplast protrusion into the central vacuole, suggesting autophagosome formation is dispensable for such 1 O 2 –mediated cellular degradation. However, both atg5 and atg7 led to specific defects in chloroplast ultrastructure and photosynthetic efficiencies, suggesting core autophagy machinery is involved in protecting chloroplasts from photo-oxidative damage. Finally, genes predicted to be involved in microautophagy were shown to be induced in stressed fc2 seedlings, indicating a possible role for an alternate form of autophagy in the dismantling of 1 O 2 -damaged chloroplasts. Conclusions Our results support the hypothesis that 1 O 2 -dependent cell death is independent from autophagosome formation, canonical autophagy, and chlorophagy. Furthermore, autophagosome-independent microautophagy may be involved in degrading 1 O 2 -damaged chloroplasts. At the same time, canonical autophagy may still play a role in protecting chloroplasts from 1 O 2 -induced photo-oxidative stress. Together, this suggests chloroplast function and degradation is a complex process utilizing multiple autophagy and degradation machineries, possibly depending on the type of stress or damage incurred.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research

ABSTRACT The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a ‘big data’ resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote integration of multidisciplinary data while remaining dedicated to the FAIR principles of data management (findability, accessibility, interoperability and reusability) and providing a faceted search infrastructure for locating desired data efficiently. Summaries of the datasets generated by the FaceBase projects from 2014 to 2019 are provided here. FaceBase 3 now welcomes contributions of data on craniofacial and dental development in humans, model organisms and cell lines. Collectively, the FaceBase Consortium, along with other NIH-supported data resources, provide a continuously growing, dynamic and current resource for the scientific community while improving data reproducibility and fulfilling data sharing requirements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Electro-optic sampling based characterization of broad-band high efficiency THz-FEL

Extremely high beam-to-radiation energy conversion efficiencies can be obtained in a THz FEL using a strongly tapered helical undulator at the zero-slippage resonant condition, where a circular waveguide is used to match the radiation group velocity to the electron beam longitudinal velocity. In this paper we report on the first electro-optic sampling (EOS) based measurements of the broadband THz FEL radiation pulses emitted in this regime. The THz field waveforms are reconstructed in the spatial and temporal domains using multi-shot and single-shot EOS schemes respectively. The measurements are performed varying the input electron beam energy in the undulator providing insights on the complex dynamics in a waveguide FEL.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Ploidy evolution in a wild yeast is linked to an interaction between cell type and metabolism

Ploidy is an evolutionarily labile trait, and its variation across the tree of life has profound impacts on evolutionary trajectories and life histories. The immediate consequences and molecular causes of ploidy variation on organismal fitness are frequently less clear, although extreme mating type skews in some fungi hint at links between cell type and adaptive traits. Here, we report an unusual recurrent ploidy reduction in replicate populations of the budding yeast Saccharomyces eubayanus experimentally evolved for improvement of a key metabolic trait, the ability to use maltose as a carbon source. We find that haploids have a substantial, but conditional, fitness advantage in the absence of other genetic variation. Using engineered genotypes that decouple the effects of ploidy and cell type, we show that increased fitness is primarily due to the distinct transcriptional program deployed by haploid-like cell types, with a significant but smaller contribution from absolute ploidy. The link between cell-type specification and the carbon metabolism adaptation can be traced to the noncanonical regulation of a maltose transporter by a haploid-specific gene. This study provides novel mechanistic insight into the molecular basis of an environment–cell type fitness interaction and illustrates how selection on traits unexpectedly linked to ploidy states or cell types can drive karyotypic evolution in fungi.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system

Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this study, we created a novel agent-basedmodel applied to a specific context: Zimbabwean non-governmental organization the Muonde Trust has been collecting data on their agro-pastoral system for the last 35 years and had concerns about land-use planning and the effectiveness of management interventions in the face of climate change. We collaboratively created an agent-based model of their system using their data archive, qualitatively calibrating it to the observed behavior of the real system without tuning any parameters to match specific quantitative outputs. We then behaviorally validated the model using quantitative community-based data and conducted a sensitivity analysis to determine the relative impact of underlying parameter assumptions, Indigenous management interventions, and different rainfall variation scenarios. We found that our process resulted in a model which was successfully structurally validated and sufficiently realistic to be useful for Muonde researchers as a discussion tool. The model was inconsistently behaviorally validated, however, with some model variables matching field data better than others. We observed increased model system instability due to increasing variability in underlying drivers (rainfall), and also due to management interventions that broke feedbacks between the components of the system. Interventions that smoothed year-to-year variation rather than exaggerating it tended to improve sustainability. The Muonde trust has used the model to successfully advocate to local leaders for changes in land-use planning policy that will increase the sustainability of their system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Tracking ebolavirus genomic drift with a resequencing microarray

Filoviruses are emerging pathogens that cause acute fever with high fatality rate and present a global public health threat. During the 2013–2016 Ebola virus outbreak, genome sequencing allowed the study of virus evolution, mutations affecting pathogenicity and infectivity, and tracing the viral spread. In 2018, early sequence identification of the Ebolavirus as EBOV in the Democratic Republic of the Congo supported the use of an Ebola virus vaccine. However, field-deployable sequencing methods are needed to enable a rapid public health response. Resequencing microarrays (RMA) are a targeted method to obtain genomic sequence on clinical specimens rapidly, and sensitively, overcoming the need for extensive bioinformatic analysis. This study presents the design and initial evaluation of an ebolavirus resequencing microarray (Ebolavirus-RMA) system for sequencing the major genomic regions of four Ebolaviruses that cause disease in humans. The design of the Ebolavirus-RMA system is described and evaluated by sequencing repository samples of three Ebolaviruses and two EBOV variants. The ability of the system to identify genetic drift in a replicating virus was achieved by sequencing the ebolavirus glycoprotein gene in a recombinant virus cultured under pressure from a neutralizing antibody. Comparison of the Ebolavirus-RMA results to the Genbank database sequence file with the accession number given for the source RNA and Ebolavirus-RMA results compared to Next Generation Sequence results of the same RNA samples showed up to 99% agreement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Global gross primary production simulated by three terrestrial biosphere models to analyse smoothing of limiting rates

Processed global terrestrial gross primary production (GPP) from three terrestrial biosphere models (TBMs). Two simulations were run with each model, one that selects the rate limiting process of photosynthesis based on the minimum of the potential rates (following Farquhar et al. 1980) and the other that uses quadratic smoothing between the potential rates (following Collatz et al. 1991). The three TBMs are: 1) the Energy Exascale Earth System Model (E3SM) land model (ELM) (release: v1.1.0) (Burrows et al., 2020), a coupled carbon, nitrogen, and phosphorus model with sun/shade big-leaf canopy photosynthesis scaling. 2) The Functionally Assembled Terrestrial Ecosystem Simulator (FATES, tag: sci.1.30.0_api.8.0.0) (Koven et al., 2019), coupled with the Community Land Model (CLM, version 5; Lawrence et al., 2019), a carbon-only vegetation demography model with multi-leaf and multi-canopy layers for scaling photosynthesis, and with a leaf area index (LAI) optimisation scheme. 3) The Sheffield Dynamic Global Vegetation Model (SDGVM, tag: Walkeretal2020_GCB), a carbon-only model with multi-leaf-layer canopy photosynthesis scaling and also with an LAI optimisation scheme (Walker et al., 2017; Woodward & Lomas, 2004). These data were generated to evaluate the effect of Collatz smoothing of limiting rates on simulated GPP across a range of terrestrial biosphere models. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures and .RDS files, a binary format specific to R and read with the 'readRDS' function.

54 ENVIRONMENTAL SCIENCES↗