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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Left-right spin asymmetry in ℓ⁢ 𝑁 ↑ → ℎ⁡𝑋

We consider the inclusive production of hadrons in lepton-nucleon scattering. For a transversely polarized nucleon this reaction shows a left-right azimuthal asymmetry, which we compute in twist-3 collinear factorization at leading order in perturbation theory. All nonperturbative parton correlators of the calculation are fixed through information from other hard processes. Our results for the left-right asymmetry agree in sign with recent data for charged pion production from the HERMES Collaboration and from Jefferson Lab. However, the magnitude of the computed asymmetries tends to be larger than the data. Potential reasons for this outcome are identified. Furthermore, we also give predictions for future experiments and highlight in particular the unique opportunities at an electron ion collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Postdoctoral insights on mentoring excellence: a framework for best practices at Sandia National labs

The Sandia National Laboratories Strategic Plan FY24-FY27, updated for FY25, outlines Sandia’s two Big Labs-wide Goals, Accelerate Innovation and Lead in Modern Engineering. The goal of Accelerate Innovation is that “by FY27, Sandia will be a leader in scientific, engineering and operational innovation and an employer of choice for highly innovative and creative talent.” Sandia’s postdocs are leaders in innovation, well-versed in emerging techniques and cutting-edge methods, and capable of acting as a highly agile technical force across domains at the lab. As a federally funded research and development center (FFRDC), Sandia National Laboratories attracts top doctoral talent by offering a unique opportunity for postdoctoral researchers to develop at the crossroads of government, academia, and industry, working in multi-disciplinary teams and performing cutting-edge, mission-specific research that responds to immediate needs of national interest. However, this creates unique opportunities and demands of both postdoctoral appointees and the Sandia staff who act as their mentors, making mentorship key to attract talent. Since 2007 the Sandia Postdoctoral Development (SPD) Board, originally Postdoc To Professional (PD2P), a networking group at Sandia composed of a voluntary board of current postdocs and two staff liaisons, has advocated for postdoctoral development within Sandia National Labs. In this white paper, SPD board members and the Sandia Postdoctoral Development Office, organized in 2019, have come together to develop a comprehensive overview of the postdoctoral mentoring landscape at Sandia National Labs as we currently know it. By scouring various forms of data from efforts since 2018, we’ve compiled a community-derived perspective on what makes postdoctoral mentorship at Sandia unique. First, we analyze working sessions held between mentors and mentees to develop a comprehensive map of who is involved in postdoctoral mentorship at the lab and how the responsibilities are divided amongst mentors and mentees. We then combine multiple forms of data, including exit surveys, annual surveys, and community workshops, to identify the specific challenges that mentors and mentees encounter at the national lab. Finally, we use text mining and sentiment analysis to analyze mentoring award data to develop an idea of what postdocs are self-identifying as excellent mentorship within the lab. It is our goal that this white paper act as an ongoing resource to the postdoc and postdoc mentoring communities and provide a firm foundation for further conversations on the future of postdoctoral mentorship at Sandia National Labs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗
DOE OSTI2017

Meson Form Factors and Deep Exclusive Meson Production Experiments

Pion and kaon electroproduction data play a unique role in Nature and our understanding of them is essential for explaining hadron structure. Precision longitudinaltransverse separated pion and kaon cross sections are of particular interest. They allow for the extraction of meson form factors and validation of understanding of hard exclusive and semi-inclusive reactions (π+, K+, π0, γ) towards 3D hadron imaging and potential future flavor decomposition. We review recent data and present prospects for deep exclusive pion and kaon electroproduction at the 12 GeV Jefferson Lab including the prospects to use projected charged- and neutral pion data to further determine the spin, charge-parity and flavor of GPDs, including the helicity-flip GPDs.

Horn, Tanja↗
DOE OSTI2012

National Geothermal Data System: Interactive Assessment of Geothermal Energy Potential in the U.S.

Geothermal-relevant geosciences data from all 50 states (www.stategeothermaldata.org), federal agencies, national labs, and academic centers are being digitized and linked in a distributed online network via the U.S. Department of Energy-funded National Geothermal Data System (NGDS) to foster geothermal energy exploration and development through use of interactive online ‘mashups,’data integration, and applications. Emphasis is first to make as much information as possible accessible online, with a long range goal to make data interoperable through standardized services and interchange formats. An initial set of thirty geoscience data content models is in use or under development to define a standardized interchange format: aqueous chemistry, borehole temperature data, direct use feature, drill stem test, earthquake hypocenter, fault feature, geologic contact feature, geologic unit feature, thermal/hot spring description, metadata, quaternary fault, volcanic vent description, well header feature, borehole lithology log, crustal stress, gravity, heat flow/temperature gradient, permeability, and feature descriptions data like developed geothermal systems, geologic unit geothermal properties, permeability, production data, rock alteration description, rock chemistry, and thermal conductivity. Map services are also being developed for isopach maps, aquifer temperature maps, and several states are working on geothermal resource overview maps. Content models are developed preferentially from existing community use in order to encourage widespread adoption and promulgate minimum metadata quality standards. Geoscience data and maps from other NGDS participating institutions, or “nodes” (USGS, Southern Methodist University, Boise State University Geothermal Data Coalition) are being supplemented with extensive land management and land use resources from the Western Regional Partnership (15 federal agencies and 5 Western states) to provide access to a comprehensive, holistic set of data critical to geothermal energy development. As of September 2011, we have over 34,000 records registered in the system catalog, and 234,942 data resources online, along with scores of Web services to deliver integrated data to the desktop for free downloading or online use. The data exchange mechanism is built on the U.S. Geoscience Information Network (USGIN, http://usgin.org and http://lab.usgin.org) protocols and standards developed as a partnership of the Association of American State Geologists (AASG) and U.S. Geological Survey.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗
DOE OSTI2015

Compositional analysis of biomass reference materials: Results from an interlaboratory study

Biomass compositional methods are used to compare different lignocellulosic feedstocks, to measure component balances around unit operations and to determine process yields and therefore the economic viability of biomass-to-biofuel processes. Four biomass reference materials (RMs NIST 8491–8494) were prepared and characterized, via an interlaboratory comparison exercise in the early 1990s to evaluate biomass summative compositional methods, analysts, and laboratories. Having common, uniform, and stable biomass reference materials gives the opportunity to assess compositional data compared to other analysts, to other labs, and to a known compositional value. The expiration date for the original characterization of these RMs was reached and an effort to assess their stability and recharacterize the reference values for the remaining material using more current methods of analysis was initiated. We sent samples of the four biomass RMs to 11 academic, industrial, and government laboratories, familiar with sulfuric acid compositional methods, for recharacterization of the component reference values. In this work, we have used an expanded suite of analytical methods that are more appropriate for herbaceous feedstocks, to recharacterize the RMs’ compositions. We report the median values and the expanded uncertainty values for the four RMs on a dry-mass, whole-biomass basis. The original characterization data has been recalculated using median statistics to facilitate comparisons with this data. We found improved total component closures for three out of the four RMs compared to the original characterization, and the total component closures were near 100 %, which suggests that most components were accurately measured and little double counting occurred. Here, the major components were not statistically different in the recharacterization which suggests that the biomass materials are stable during storage and that additional components, not seen in the original characterization, were quantified here.

09 BIOMASS FUELS↗
DOE OSTI2021

Carbonate clumped isotope analysis (Δ 47 ) of 21 carbonate standards determined via gas‐source isotope‐ratio mass spectrometry on four instrumental configurations using carbonate‐based standardization and multiyear data sets

Rationale Clumped isotope geochemistry examines the pairing or clumping of heavy isotopes in molecules and provides information about the thermodynamic and kinetic controls on their formation. The first clumped isotope measurements of carbonate minerals were first published 15 years ago, and since then, interlaboratory offsets have been observed, and laboratory and community practices for measurement, data analysis, and instrumentation have evolved. Here we briefly review historical and recent developments for measurements, share Tripati Lab practices for four different instrument configurations, test a recently published proposal for carbonate‐based standardization on multiple instruments using multi‐year data sets, and report values for 21 different carbonate standards that allow for recalculations of previously published data sets. Methods We examine data from 4628 standard measurements on Thermo MAT 253 and Nu Perspective IS mass spectrometers, using a common acid bath (90°C) and small‐sample (70°C) individual reaction vessels. Each configuration was investigated by treating some standards as anchors (working standards) and the remainder as unknowns (consistency standards). Results We show that different acid digestion systems and mass spectrometer models yield indistinguishable results when instrument drift is well characterized. For linearity correction, mixed gas‐and‐carbonate standardization or carbonate‐only standardization yields similar results. No difference is observed in the use of three or eight working standards for the construction of transfer functions. Conclusions We show that all configurations yield similar results if instrument drift is robustly characterized and validate a recent proposal for carbonate‐based standardization using large multiyear data sets. Δ 47 values are reported for 21 carbonate standards on both the absolute reference frame (ARF; also refered to as the Carbon Dioxide Equilibrated Scale or CDES) and the new InterCarb‐Carbon Dioxide Equilibrium Scale (I‐CDES) reference frame, facilitating intercomparison of data from a diversity of labs and instrument configurations and restandardization of a broad range of sample sets between 2006, when the first carbonate measurements were published, and the present.

58 GEOSCIENCES↗
DOE OSTI2011

Spin Asymmetries on Nucleon Experiment at Jefferson Lab

The Spin Asymmetries of the Nucleon Experiment (SANE) of Jefferson Lab is a comprehensive measurement of double spin asymmetries of the proton for both parallel and almost perpendicular spin configurations of the proton spin and the electron beam polarization directions. The experiment will provide both spin structure functions, g{sub 2} and g{sub 1} and spin observable A{sub 2} and A{sub 1} of the proton over Q{sup 2} region from 2.5 to 6.5 GeV{sup 2}/c{sup 2} and Bjorken x region of 0.3 to 0.8. Using the polarized electron beam of Thomas Jefferson National Accelerator Facility and the polarized frozen NH{sub 3} target, the data were taken early 2009 in Hall C of Jefferson Lab. Scattered electrons from the inclusive reaction were detected by the Big Electron Telescope Array (BETA), a new non-magnetic detector with a large acceptance of 194 msr. The current analysis effort is focused on the proton spin structure functions g{sub 2} and g{sub 1}. Physics motivations with the experimental methods will be presented with an overview of the current status of the data analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Spectral Hardness of X- and Gamma-Ray Emissions From Lightning Stepped and Dart Leaders

During the 2022 New Mexico monsoon season, we deployed two X-ray scintillation detectors, coupled with a 180 MHz data acquisition system to detect X-rays from natural lightning at the Langmuir Lab mountain-top facility, located at 3.3 km above mean sea level. Data acquisition was triggered by an electric field antenna calibrated to pick up lightning within a few km of the X-ray detectors. We report the energies of over 240 individual photons, ranging between 13 keV and 3.8 MeV, as registered by the LaBr3(Ce) scintillation detector. These detections were associated with four lightning flashes. Particularly, four-stepped leaders and seven dart leaders produced energetic radiation. Importantly, the reported photon energies allowed us to confirm that the X-ray energy distribution of natural stepped and dart leaders follows a power-law distribution with an exponent ranging between 1.09 and 1.96, with stepped leaders having a harder spectrum. Characterization of the associated leaders and return strokes was done with four different electric field sensing antennas, which can measure a wide range of time scales, from the static storm field to the fast change associated with dart leaders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

A Really Good Hammer: Quantification of Mass Transfer Using Perfluorocarbon Tracers (475th Brookhaven Lecture)

Brookhaven Lab’s perfluorocarbon tracer (PFT) technology can be viewed as a hammer looking for nails. But, according to Tom Watson, leader of the Lab’s Tracer Technology Group in the Environmental Research and Technology Division (ERTD), “It’s a really good hammer!” The colorless, odorless and safe gases have a number of research uses, from modeling how airborne contaminants might move through urban canyons to help first responders plan their response to potential terrorist attacks and accidents to locating leaks in underground gas pipes. Their extremely low background level — detectable at one part per quadrillion — allows their transport to be easily tracked. Lab researchers used PFTs during the 2005 Urban Dispersion Program field studies in New York City, gathering data to help improve models of how a gas or chemical release might move around Manhattan’s tall buildings and canyons. Closer to home, scientists also used PFTs to make ventilation measurements in Bldg. 400 on the Lab site to provide data to test air flow models used in determining the effects of passive and active air exchange on the levels of indoor and outdoor air pollution, and to determine the effects of an accidental or intentional release of hazardous substances in or around buildings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Perspectives for self-driving labs in synthetic biology

Self-driving labs (SDLs) combine fully automated experiments and data collection with artificial intelligence (AI) and control algorithms that decide not only the set of parameters for the next experiment, but also potentially which scientific hypotheses to test. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. Whereas there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single, easily accessible, target for affecting the incredibly wide repertoire of biological cell behavior. Since they can provide large amounts of high-quality data, SDLs can be a platform for AI to develop approaches to systematically convert data into scientific knowledge systems. These knowledge systems can be used both to understand the biological world and to design bioengineered systems to fit a desired specification (inverse design). However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Hydrological Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Hydrologic sciences depend on data monitoring, analyses, and simulations of hydrologic processes to ensure safe, sufficient, and equal water distribution. These hydrologic data come from but are not limited to primary (lab, plot, and field experiments) and secondary sources (remote sensing, UAVs, hydrologic models) that typically follow FAIR Principles (Findable, Accessible, Interoperable, and Reusable: (go-fair.org)). Easy availability of FAIR data has become possible because the hydrology-oriented organizations have pushed the community to increase coordination of the protocols for generating data and sharing model platforms. In addition, networking at all levels has emerged with an invigorated effort to activate community science efforts that complement conventional data collection methods. However, it has become difficult to decipher various complex hydrologic processes with increasing data. Machine learning, a branch of artificial intelligence, provide more accurate and faster alternatives to better understand different hydrological processes. The Integrated, Coordinated, Open, Networked (ICON) framework provides a pathway for water users to include and respect diversity, equity, and inclusivity. In addition, ICONs support the integration of peoples with historically marginalized identities into this professional discipline of water sciences. This article comprises three independent commentaries about the state of ICON principles in hydrology and discusses the opportunities and challenges of adopting them.

(ICON) principles to address↗
DOE OSTI2012

Study of Three-Nucleon Short Range Correlations in Inclusive Electron Scattering

Inclusive electron scattering is a powerful tool to study short range correlations (SRCs) in nuclei. Two nucleon SRCs (2N-SRCs) were first observed in data from SLAC and further studied at Jefferson Lab, appearing, between $1.4 < x< 2$, as plateaus in the per nucleon cross section ratio of heavy to light nuclei. The Jefferson Lab experiments also provided the first evidence of three nucleon SRCs (3N-SRCs) at $x>2$. However, because of limited statistics of the earlier experiments, the scaling behavior of 3N-SRCs is not well established. Jefferson Lab experiment E08014 ran in April and May of 2011 in Hall~A and aimed to study the onset of 3N-SRCs with better accuracy and, for the first time, to examine the isospin dependence of SRCs. The experiment will be briefly described followed by a discussion of the data analysis and the presentation of the preliminary results.

Ye, Zhihong↗
DOE OSTI2025

GeoGridFusion (Open-Source Geospatial Toolkit for Solar Data Integration​) [SWR-25-19]

GeoGridFusion facilitates the usage and storage of gridded geospatial satellite data by users outside of the National Renewable Lab (NREL), particularly those without access to high-performance computing (HPC) resources. This tool builds on work done by the PVDegradationTools project for DuraMAT, with the goal of making our advancements from this project widely accessible. This repo contains utilities to allow for the storage of user downloaded geospatial weather data by providing a local datastore for storage and spatial queries, supporting large-scale analyses without the need for HPC resources.

Ford, Tobin [National Renewable Energy Laboratory ↗
DOE OSTI2013

Hadronization Studies via π 0 Electroproduction off D, C, Fe, and Pb

Propagation of partons and formation of hadrons is a topic of interest to multiple communities. New data available from Drell-Yan measurements at FermiLab, heavy ion collisions in RHIC and LHC, SIDIS measurements from HERMES at DESY and Jefferson Lab, all bring different types of information on short distance processes. DIS data obtained in the well understood nuclear medium provide direct information on hadron formation, essential to lay the groundwork for testing theoretical tools. A series of semi-inclusive DIS measurements were performed on D, C, Fe, Pb nuclei. The data were collected during the EG2 run period using the CLAS at Jefferson Lab. A double-target system consisting of liquid deuterium and one of the solid targets was exposed to a 5.014 GeV electron beam. The goal of the experiment is to extract hadronic multiplicity ratios (R$h\atop{A}$) off nuclei of varying size. These are believed to have sensitivity to the parton fragmentation as well as in-medium hadronization.

Mineeva, Taisiya↗
DOE OSTI2021

Electromagnetic calorimeters based on scintillating lead tungstate crystals for experiments at Jefferson Lab

A new electromagnetic calorimeter consisting of 140 lead tungstate (PbWO 4 ) scintillating crystals was constructed for the PrimEx- &#x3B7; experiment at Jefferson lab. The calorimeter was integrated into the data acquisition and trigger systems of the GlueX detector and used in the experiment to reconstruct Compton scattering events. The experiment started collecting data in the spring of 2019 and acquired about 30% of the required statistics. The calorimeter is a prototype for two PbWO 4 -based detectors: the Neutral Particle Spectrometer (NPS) and the lead tungstate insert of the Forward CALorimeter (FCAL) of the GlueX detector. The article presents the design and performance of the Compton calorimeter and gives a brief overview of the FCAL and NPS projects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Near threshold J / ψ and ϒ photoproduction at JLab and RHIC

We update our previous calculation of J/ψ photo-production near threshold by incorporating the recent developments in theory and the new experimental data from the GlueX collaboration at Jefferson Lab. We then propose to study the near threshold production of Υ and J/ψ in ultraperipheral pA collisions at RHIC. These processes are sensitive to the gluon condensate in the proton which is related to the QCD trace anomaly. Our result emphasizes the role of gluons as the origin of the proton mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗