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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Mid-IR Selected Changing-look Quasar and Physical Scenarios for Abrupt AGN Fading

We report a new changing-look quasar, WISE J105203.55+151929.5 at $z$ = 0.303, found by identifying highly mid-IR-variable quasars in the Wide-field Infrared Survey Explorer (WISE) /Near-Earth Object WISE Reactivation (NEOWISE) data stream. Compared to multiepoch mid-IR photometry of a large sample of SDSS-confirmed quasars, WISE J1052+1519 is an extreme photometric outlier, fading by more than a factor of two at 3.4 and 4.6 $μ$m since 2009. Swift target-of-opportunity observations in 2017 show even stronger fading in the soft X-rays compared to the ROSAT detection of this source in 1995, with at least a factor of 15 decrease. We obtained second-epoch spectroscopy with the Palomar telescope in 2017 that, when compared with the 2006 archival SDSS spectrum, reveals that the broad H$β$ emission has vanished and that the quasar has become significantly redder. The two most likely interpretations for this dramatic change are source fading or obscuration, where the latter is strongly disfavored by the mid-IR data. We discuss various physical scenarios that could cause such changes in the quasar luminosity over this timescale, and favor changes in the innermost regions of the accretion disk that occur on the thermal and heating/cooling front timescales. We discuss possible physical triggers that could cause these changes, and predict the multiwavelength signatures that could distinguish these physical scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Brown Rot-Type Fungal Decomposition of Sorghum Bagasse: Variable Success and Mechanistic Implications

Sweet sorghum is a promising crop for a warming, drying African climate, and basic information is lacking on conversion pathways for its lignocellulosic residues (bagasse). Brown rot wood-decomposer fungi use carbohydrate-selective pathways that, when assessed on sorghum, a grass substrate, can yield information relevant to both plant biomass conversion and fungal biology. In testing sorghum decomposition by brown rot fungi ( Gloeophyllum trabeum , Serpula lacrymans ), we found that G. trabeum readily degraded sorghum, removing xylan prior to removing glucan. Serpula lacrymans , conversely, caused little decomposition. Ergosterol (fungal biomarker) and protein levels were similar for both fungi, but S. lacrymans produced nearly 4x lower polysaccharide-degrading enzyme specific activity on sorghum than G. trabeum , perhaps a symptom of starvation. Linking this information to genome comparisons including other brown rot fungi known to have a similar issue regarding decomposing grasses (Postia placenta, Fomitopsis pinicola) suggested that a lack of CE 1 feruloyl esterases as well as low xylanase activity in S. lacrymans (3x lower than in G. trabeum ) may hinder S. lacrymans , P. placenta, and F. pinicola when degrading grass substrates. These results indicate variability in brown rot mechanisms, which may stem from a differing ability to degrade certain lignin-carbohydrate complexes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Printed Potentiometric Ammonium Sensors for Agriculture Applications

Ammonium (NH 4 + ) concentration is critical to both nutrient availability and nitrogen (N) loss in soil ecosystems but can be highly variable across spatial and temporal scales. For this reason, effectively informing agricultural practices such as fertilizer management and understanding of mechanisms of soil N loss require sensor technologies to monitor ammonium concentrations in real time. Our work investigates the performance of fully printed ammonium ion-selective sensors used in diverse soil environments. Ammonium sensors consisting of a printed ammonium ion-selective electrode and a printed Ag/AgCl reference were fabricated and characterized in aqueous solutions and three different soil types (sand, peat, and clay) under the range of ion concentrations likely to be present in soil (0.01–100 mM). The response of ammonium sensors was further evaluated under variable gravimetric moisture content in the soil to reflect their reliability under field conditions. Ammonium sensors demonstrated a sensitivity of 53.6 ± 5.1 mV/decade when tested in aqueous solution, and a sensitivity of 55.7 ± 11 mV/dec, 57.5 ± 4.1 mV/dec, and 43.7 ± 4 mV/dec was measured in sand, clay, and peat soils, respectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Pre–T cell receptors topologically sample self-ligands during thymocyte β-selection

Self-discrimination, a critical but ill-defined molecular process programmed during thymocyte development, requires myriad pre–T cell receptors (preTCRs) and αβTCRs. Using x-ray crystallography, we show how a preTCR applies the concave β-sheet surface of its single variable domain (Vβ) to “horizontally” grab the protruding MHC α2-helix. By contrast, αβTCRs purpose all six complementarity-determining region (CDR) loops of their paired VαVβ module to recognize peptides bound to major histocompatibility complex molecules (pMHCs) in “vertical” head-to-head binding. Additionally, the preTCR topological fit ensures that CDR3β reaches the peptide’s featured C-terminal segment for pMHC sampling, establishing the subsequent αβTCR canonical docking mode. “Horizontal” docking precludes germline CDR1β- and CDR2β-MHC binding to broaden β-chain repertoire diversification before αβTCR-mediated selection refinement. Thus, one subunit successively attunes the recognition logic of related multicomponent receptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Search for dark matter produced in association with a Standard Model Higgs boson decaying into b -quarks using the full Run 2 dataset from the ATLAS detector

The production of dark matter in association with Higgs bosons is predicted in several extensions of the Standard Model. An exploration of such scenarios is presented, considering final states with missing transverse momentum and b-tagged jets consistent with a Higgs boson. The analysis uses proton-proton collision data at a centre-of-mass energy of 13 TeV recorded by the ATLAS experiment at the LHC during Run 2, amounting to an integrated luminosity of 139 fb -1 . The analysis, when compared with previous searches, benefits from a larger dataset, but also has further improvements providing sensitivity to a wider spectrum of signal scenarios. These improvements include both an optimised event selection and advances in the object identification, such as the use of the likelihood-based significance of the missing transverse momentum and variable-radius track-jets. No significant deviation from Standard Model expectations is observed. Limits are set, at 95% confidence level, in two benchmark models with two Higgs doublets extended by either a heavy vector boson Z' or a pseudoscalar singlet a and which both provide a dark matter candidate χ. In the case of the two-Higgs-doublet model with an additional vector boson Z', the observed limits extend up to a Z' mass of 3 TeV for a mass of 100 GeV for the dark matter candidate. The two-Higgs-doublet model with a dark matter particle mass of 10 GeV and an additional pseudoscalar a is excluded for masses of the a up to 520 GeV and 240 GeV for tan β = 1 and tan β = 10 respectively. Limits on the visible cross-sections are set and range from to 0.05 fb to 3.26 fb, depending on the missing transverse momentum and b-quark jet multiplicity requirements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach

We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Superstructure Optimization of Waste Plastic Pyrolysis, Integrating Thermal, Catalytic, and Plasma Technologies with Machine Learning

Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.

Life cycle assessment↗
DOE OSTI2019

Excited State Specific Multi-Slater Jastrow Wave Functions

We combine recent advances in excited state variational principles, fast multi-Slater Jastrow methods and selective configuration interaction, to create multi-Slater Jastrow wave function approximations that are optimized for individual excited states. In addition to the Jastrow variables and linear expansion coefficients, this optimization includes state-specific orbital relaxations in order to avoid the compromises necessary in state-averaged approaches. Here, we demonstrate that, when combined with variance matching to help balance the quality of the approximation across different states, this approach delivers accurate excitation energies even when very modest multi-Slater expansions are used. Intriguingly, this accuracy is maintained even when we study a difficult chlorine-anion-to-π* charge transfer in which traditional state-averaged multireference methods must contend with different states that require drastically different orbital relaxations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The structure of sc16 GaP obtained at 17.5 GPa and 1400 K

We report using a laser-heated diamond anvil cell, a powdered sample of gallium phosphide was compressed to 17.5 GPa and heated up to 1400 K. The material obtained was characterized at room temperature using synchrotron x-ray diffraction. Experimental results were compared with first-principles calculations. The polymorph observed assumes the simple cubic structure (sc16) initially reported for GaAs at high pressures. Microdiffraction mapping showed variable grain sizes of the synthesized phase, with the largest grains located in the middle of the heated spot. Structural refinements were performed on selected grains. The structure predicted based on first-principles calculations is in close agreement with the experiments. The two Ga–P bonds show similar lengths in sc16-GaP; however, the bond angles differ, resulting in a distorted tetrahedral coordination geometry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Conceptual design of a hybrid neutron-gamma detector for study of β-delayed neutrons at the RIB facility of RIKEN

Here, the conceptual design of the BRIKEN neutron detector at the radioactive ion beam factory (RIBF) of the RIKEN Nishina Center is reported. The BRIKEN setup is a complex system aimed at detecting heavy-ion implants, β particles, γ rays and β-delayed neutrons. The whole setup includes the Advanced Implantation Detection Array (AIDA), two HPGe Clover detectors and up to 166 3 He-filled counters embedded in a high-density polyethylene moderator. The design is quite complex due to the large number and different types of 3 He-tubes involved and the additional constraints introduced by the ancillary detectors for charged particles and γ rays. This article reports on a novel methodology developed for the conceptual design and optimisation of the 3 He-counter array, aiming for the best possible performance in terms of neutron detection. The algorithm is based on a geometric representation of two selected detector parameters of merit, namely, the average neutron detection efficiency and the efficiency flatness as a function of a reduced number of geometric variables. The response of the neutron detector is obtained from a systematic Monte Carlo simulation implemented in GEANT4. The robustness of the algorithm allowed us to design a versatile detection system, which operated in hybrid mode includes the full neutron counter and two clover detectors for high-precision gamma spectroscopy. In addition, the system can be reconfigured into a compact mode by removing the clover detectors and re-arranging the 3 He tubes in order to maximize the neutron detection performance. Both operation modes shows a rather flat and high average efficiency. In summary, we have designed a system which shows an average efficiency for hybrid mode ( 3 He tubes + clovers) of 68.6% and 64% for neutron energies up to 1 and 5 MeV, respectively. For compact mode (only 3 He tubes), the average efficiency is 75.7% and 71% for neutron energies up to 1 and 5 MeV, respectively. The performance of the BRIKEN detection system has been also quantified by means of Monte Carlo simulations with different neutron energy distributions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Application of Electronics Packaging Fundamentals to Photovoltaic Interconnects and Packaging

The energy capacity of photovoltaic (PV) installations worldwide has increased significantly in the last decade, increasing the demand for rigorous investigation of the physical phenomena causing degradation and failures in PV modules. As PV reliability science develops, established methods and approaches from longer-standing industries can inform and expedite PV reliability advances. This work demonstrates how thermomechanical solder bond fatigue models derived for electronics packaging applications can be applied to both standard and emerging PV interconnect designs. This expertise cannot be directly translated to PV however, as target PV module lifetimes are significantly longer than most electronics and the modules must withstand the natural climate wherever they are deployed. Verification of analytical reliability models is then an additional challenge, due to model size, test time, and climate variability. Furthermore, unconventional materials, such as low-temperature solders, are now being integrated into PV designs, for which appropriate material models must be selected and material parameters derived. In this paper, the current state of PV interconnect research is explored, with an emphasis on the experimental and simulation approaches and models being used for this work. Recent results for standard module architectures as well as emerging interconnect schemes are discussed.

14 SOLAR ENERGY↗
DOE OSTI2019

Comparing wall performance predicted from hygrothermal simulations to wall performance measured from environmental chamber experiments

To effectively mitigate prevailing perceptions of potential moisture risks in high-R wall assemblies, a comprehensive moisture durability assessment that incorporates BA team field evaluations, lab tests and simulations has been completed over the last couple years. In FY18, three stick-built walls were succumbed to typical Chicago weather in ORNL’s Heat, Air and Moisture chamber. The measured temperature, relative humidity and moisture content within these walls were compared to WUFI hygrothermal simulation results. In FY19, similar experiments and comparison to WUFI results were completed with two walls, a Structural Insulated Panel (SIP) based wall and a Concrete Masonry Unit (CMU) based wall. The following tasks were completed for these two walls: 1. Measure air permeance of each individual wall using ASTM E283 Standard Test Method. 2.Test walls in diffusion scenario as only moisture transport mechanism and compare measured transient temperature and relative humidity of select wall components to WUFI model results. Chicago summer and weather will be investigated. 3. Test walls in wetting event scenario and compare measured transient temperature and relative humidity of select wall components with Chicago summer weather to WUFI model results. 4. Test walls in diffusion/advection scenario. In addition to controlling outdoor chamber to match real outdoor weather, a pressure differential across the wall will be varied. Measured transient temperature and relative humidity of select wall components will be compared to WUFI model results. 5. Test walls in diffusion/advection with solar heating of cladding. In addition to the variables above, IR lamps will be used to heat the cladding on a diurnal cycle. Measured transient OSB MC and temperature will be compared to WUFI model results. This report documents the experimental method, results and comparison of the measured experimental hygrothermal performance of the two walls to simulations results.

42 ENGINEERING↗
DOE OSTI2021

Industrial Conveyor Motor Performance Evaluation

The purpose of this project is to estimate the energy savings potential from a switched-reluctance motor (SRM) compared to an induction motor equipped with variable frequency drive (VFD) in a straight belt conveyor application. To experimentally evaluate savings in a realistic scenario, a baseline motor and VFD were selected from one of ComEd’s manufacturing customers’ conveyor systems. It was desired to not only estimate savings in the selected conveyor system, but to evaluate potential savings from using the SRM in any straight belt conveyor. Therefore, NREL developed a conveyor system energy calculation tool to supplement the experimental results of this assessment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Rapid Evaluation Framework for the CMIP7 Assessment Fast Track

As Earth system models (ESMs) grow in complexity and in volume of output data, there is an increasing need for rapid, comprehensive evaluation of their scientific performance. The upcoming Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project (CMIP7) will require expeditious response for model analyses designed to inform and drive integrated Earth system assessments. To meet this challenge, the Rapid Evaluation Framework (REF), a community-driven platform for benchmarking and performance assessment of ESMs, was designed and developed. The initial implementation of the REF, constructed to meet the near-term needs of the CMIP7 Assessment Fast Track, builds upon four disparate community evaluation and benchmarking tools that are coupled together using the Coordinated Model Evaluation Capabilities (CMEC) framework. The REF runs within a containerized workflow for portability and reproducibility and is aimed at generating and organizing diagnostics covering a variety of model variables. The REF leverages well documented observational datasets to provide assessments of model fidelity across a collection of diagnostics. All diagnostics were identified and selected with community involvement and consultation. Operational integration with the Earth System Grid Federation (ESGF) will permit automated execution of the REF for selected diagnostics as soon as model output data are published on ESGF by the originating modeling centers. The REF is designed to be portable across a range of current computational platforms to facilitate use by modeling centers for assessing the evolution of model versions or gauging the relative performance of CMIP simulations before being published on ESGF. When integrated into production simulation workflows, results from the REF provide immediate quantitative feedback that allows model developers and scientists to quickly identify model biases and performance issues. After the REF is released to the community, its subsequent development and support will be prioritized by an international consortium of scientists and engineers, enabling a broader impact across Earth science disciplines. For instance, the REF will facilitate improvements to models and will enhance confidence in model projections through process-based selection of models based on their performance with respect to observations. Production of reproducible diagnostics and community-based assessments are key features of the REF. Furthermore, providing interoperability with existing evaluation packages assures that contributions from previous community efforts will be available for use in future model intercomparison projects.

Hoffman, Forrest [ORNL] (ORCID:0000000158024134)↗
DOE OSTI2022

Identification of Critical Material Attributes in Lignin Streams Based on Pseudomonas putida Performance

Variability in chemical composition of corn stover feedstocks has been suggested to play a role in biocatalyst performance during the conversion of lignocellulosic biomass to value-added compounds. In previous studies, we investigated the performance of Pseudomonas putida CJ781 - an engineered bacterium that converts aromatic compounds to muconate - on various lignin streams produced from the deacetylation of corn stover, and we found significant differences on muconate production. To better understand the origin of these differences, we down selected twenty-two compounds from literature - that had previously been detected as extractives in lignin streams - and we analyzed their concentrations in 12 lignin streams generated from different feedstocks. P. putida CJ781 was then cultivated in mock lignin streams supplemented with various concentrations of these compounds. Bacterial growth was tracked in microtiter plates and the performance was measured by comparing maximum growth rates among conditions. At maximum concentrations that may be found in lignin streams, sodium was the material attribute that limited growth rate in a greater extent, with a reduction in growth rate by 8 to 37%, depending on the counter ion, with sodium nitrate being the most inhibitory, followed by sodium acetate, sodium chloride, and sodium sulfate. Ammonium acetate was also found to be inhibitory at average concentrations of ammonium in lignin streams, reducing maximum growth rate by 18%. Overall, the data from this study has allowed to down select critical material attributes in lignin streams and process parameters that significantly affect the performance of P. putida and will be used as input to predictive models that aim to reduce risks attributed to feedstock variability in lignocellulosic biorefineries.

biocatalyst↗
DOE OSTI2023

Ionization detail parameters and cluster dose: a mathematical model for selection of nanodosimetric quantities for use in treatment planning in charged particle radiotherapy

Abstract Objective . To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP). Approach . Our model provides for selection of preferred ID parameters ( I p ) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopic I p and macroscopic RTP. Selection of I p is demonstrated using published cell survival measurements for protons through argon, comparing results for nineteen I p : N k , k = 2, 3, …, 10, the number of ionizations in clusters of k or more per particle, and F k , k = 1, 2, …, 10, the number of clusters of k or more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation. Main results . The preferred I p were N 4 and F 5 for aerobic cells, N 5 and F 7 for hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferred N k . Conversely, there was no significant difference for F 5 for aerobic cells and F 7 for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for these I p had the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert that I p exist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation. Significance . Our model provides a practical means to select preferred I p from radiobiological data, and to convert I p to the macroscopic cluster dose for particle RTP.

Engineering↗
DOE OSTI2025

Investigating performance and variability of NIF ICF experiments with deep learning

The parameter space involved in designing an inertial confinement fusion shot at the National Ignition Facility (NIF) is massively multi-dimensional and the cost of a single shot makes a comprehensive set of sensitivity studies in the laboratory impractical. The use of machine learning to overcome these challenges has gained popularity and has had several successful applications by the scientific community. We extend on these efforts by training a neural network (NN) on information about the experimental design, engineering elements, and drive asymmetry to predict with uncertainty the neutron yield of an experiment. We find the measured and model predicted values are in good agreement, with an R 2 value of 0.91 for a randomly selected test dataset. Almost all the predicted 95% credible intervals contain the corresponding measured value for both training and test datasets. We identify correlations picked up by the NN between the shot design, yield, and variability and use them to motivate shot sensitivity studies. The first shot to exceed the Lawson-like ignition criteria (N210808) was conducted at the NIF and subsequent shots studied the design’s robustness. In a follow-up shot to N210808, our model predicts capsule quality to be the main performance degradation mechanism that prevented the shot from repeating previous performance levels. Shot N221204 was the first shot to exceed a target energy gain of 1. Our model predicts increased yield with reduced coast time for a N221204 study and greater variability for designs with lower peak powers at constant yield. The model’s fast prediction speed and uncertainty prediction are useful for identifying interesting design paths that could warrant further investigation with conventional simulations to search for robust high yield designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Parametric Sensitivity and Uncertainty Quantification in the Version 1 of E3SM Atmosphere Model Based on Short Perturbed Parameter Ensemble Simulations

Abstract The atmospheric component of Energy Exascale Earth System Model version 1 has included many new features in the physics parameterizations compared to its predecessors. Potential complex nonlinear interactions among the new features create a significant challenge for understanding the model behaviors and parameter tuning. Using the one‐at‐a‐time method, the benefit of tuning one parameter may offset the benefit of tuning another parameter, or improvement in one target variable may lead to degradation in another target variable. To better understand the Energy Exascale Earth System Model version 1 model behaviors and physics, we conducted a large number of short simulations (three days) in which 18 parameters carefully selected from parameterizations of deep convection, shallow convection, and cloud macrophysics and microphysics were perturbed simultaneously using the Latin hypercube sampling method. From the perturbed parameter ensemble simulations and use of different skill score functions, we identified the most sensitive parameters, quantified how the model responds to changes of the parameters for both global mean and spatial distribution, and estimated the maximum likelihood of model parameter space for a number of important fidelity metrics. Comparison of the parametric sensitivity using simulations of two different lengths suggests that perturbed parameter ensemble using short simulations has some bearing on understanding parametric sensitivity of longer simulations. Results from this analysis provide a more comprehensive picture of the Energy Exascale Earth System Model version 1 behavior. The difficulty in reducing biases in multiple variables simultaneously highlights the need of characterizing model structural uncertainty (so‐called embedded errors) to inform future development efforts.

54 ENVIRONMENTAL SCIENCES↗