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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Feature review of photovoltaic modeling software utilizing blind performance assessment

While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.

14 SOLAR ENERGY↗
DOE OSTI2014

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure–Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R{sup 2} = 0.55 and CCR = 0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R{sup 2} = 0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern. - Highlights: • This is the largest curated dataset for ligand binding domain (LBD) of the THRβ. • We report the first QSAR model for antagonists of AF-2 domain of THRβ. • A combination of QSAR and docking enables prediction of both affinity and efficacy. • Models can be used to identify environmental chemicals interacting with THRβ. • Models can be used to eliminate the THRβ-mediated mechanism of action.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Inhibition of human anthracycline reductases by emodin — A possible remedy for anthracycline resistance

The clinical application of anthracyclines, like daunorubicin and doxorubicin, is limited by two factors: dose-related cardiotoxicity and drug resistance. Both have been linked to reductive metabolism of the parent drug to their metabolites daunorubicinol and doxorubicinol, respectively. These metabolites show significantly less anti-neoplastic properties as their parent drugs and accumulate in cardiac tissue leading to chronic cardiotoxicity. Therefore, we aimed to identify novel and potent natural inhibitors for anthracycline reductases, which enhance the anticancer effect of anthracyclines by preventing the development of anthracycline resistance. Human enzymes responsible for the reductive metabolism of daunorubicin were tested for their sensitivity towards anthrachinones, in particular emodin and anthraflavic acid. Intense inhibition kinetic data for the most effective daunorubicin reductases, including IC{sub 50}- and K{sub i}-values, the mode of inhibition, as well as molecular docking, were compiled. Subsequently, a cytotoxicity profile and the ability of emodin to reverse daunorubicin resistance were determined using multiresistant A549 lung cancer and HepG2 liver cancer cells. Emodin potently inhibited the four main human daunorubicin reductases in vitro. Further, we could demonstrate that emodin is able to synergistically sensitize human cancer cells towards daunorubicin at clinically relevant concentrations. Therefore, emodin may yield the potential to enhance the therapeutic effectiveness of anthracyclines by preventing anthracycline resistance via inhibition of the anthracycline reductases. In symphony with its known pharmacological properties, emodin might be a compound of particular interest in the management of anthracycline chemotherapy efficacy and their adverse effects. - Highlights: • Natural and synthetic compounds were identified as inhibitors for human daunorubicin reductases. • Emodin is a potent inhibitor for human daunorubicin reductases. • Emodin synergistically sensitizes multiresistant human cancer cells towards daunorubicin.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

The Papillomavirus E2 proteins

The papillomavirus E2 proteins are pivotal to the viral life cycle and have well characterized functions in transcriptional regulation, initiation of DNA replication and partitioning the viral genome. The E2 proteins also function in vegetative DNA replication, post-transcriptional processes and possibly packaging. This review describes structural and functional aspects of the E2 proteins and their binding sites on the viral genome. It is intended to be a reference guide to this viral protein. - Highlights: • Overview of E2 protein functions. • Structural domains of the papillomavirus E2 proteins. • Analysis of E2 binding sites in different genera of papillomaviruses. • Compilation of E2 associated proteins. • Comparison of key mutations in distinct E2 functions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Methane emissions from MBT landfills

Highlights: • Compilation of methane generation potential of mechanical biological treated (MBT) municipal solid waste. • Impacts and kinetics of landfill gas production of MBT landfills, approach with differentiated half-lives. • Methane oxidation in the waste itself and in soil covers. • Estimation of methane emissions from MBT landfills in Germany. - Abstract: Within the scope of an investigation for the German Federal Environment Agency (“Umweltbundesamt”), the basics for the estimation of the methane emissions from the landfilling of mechanically and biologically treated waste (MBT) were developed. For this purpose, topical research including monitoring results regarding the gas balance at MBT landfills was evaluated. For waste treated to the required German standards, a methane formation potential of approximately 18–24 m{sup 3} CH{sub 4}/t of total dry solids may be expected. Monitoring results from MBT landfills show that a three-phase model with differentiated half-lives describes the degradation kinetics in the best way. This is due to the fact that during the first years of disposal, the anaerobic degradation processes still proceed relatively intensively. In addition in the long term (decades), a residual gas production at a low level is still to be expected. Most of the soils used in recultivation layer systems at German landfills show a relatively high methane oxidation capacity up to 5 l CH{sub 4}/(m{sup 2} h). However, measurements at MBT disposal sites indicate that the majority of the landfill gas (in particular at non-covered areas), leaves the landfill body via preferred gas emission zones (hot spots) without significant methane oxidation. Therefore, rather low methane oxidation factors are recommended for open and temporarily covered MBT landfills. Higher methane oxidation rates can be achieved when the soil/recultivation layer is adequately designed and operated. Based on the elaborated default values, the First Order Decay (FOD) model of the IPCC Guidelines for National Greenhouse Gas Inventories, 2006, was used to estimate the methane emissions from MBT landfills. Due to the calculation made by the authors emissions in the range of 60,000–135,000 t CO{sub 2-eq.}/a for all German MBT landfills can be expected. This wide range shows the uncertainties when the here used procedure and the limited available data are applied. It is therefore necessary to generate more data in the future in order to calculate more precise methane emission rates from MBT landfills. This is important for the overall calculation of the climate gas production in Germany which is required once a year by the German Government.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Depollution benchmarks for capacitors, batteries and printed wiring boards from waste electrical and electronic equipment (WEEE)

Highlights: • We’ve analysed data on the dismantling of electronic and electrical appliances. • Ten years of mass balance data of more than recycling companies have been considered. • Percentages of dismantled batteries, capacitors and PWB have been studied. • Threshold values and benchmarks for batteries and capacitors have been identified. • No benchmark for the dismantling of printed wiring boards should be set. - Abstract: The article compiles and analyses sample data for toxic components removed from waste electronic and electrical equipment (WEEE) from more than 30 recycling companies in Switzerland over the past ten years. According to European and Swiss legislation, toxic components like batteries, capacitors and printed wiring boards have to be removed from WEEE. The control bodies of the Swiss take back schemes have been monitoring the activities of WEEE recyclers in Switzerland for about 15 years. All recyclers have to provide annual mass balance data for every year of operation. From this data, percentage shares of removed batteries and capacitors are calculated in relation to the amount of each respective WEEE category treated. A rationale is developed, why such an indicator should not be calculated for printed wiring boards. The distributions of these de-pollution indicators are analysed and their suitability for defining lower threshold values and benchmarks for the depollution of WEEE is discussed. Recommendations for benchmarks and threshold values for the removal of capacitors and batteries are given.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways' side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl. gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Improved scaling laws for the shock-induced dispersal of a dense particle curtain

Here, experiments were performed within Sandia National Labs’ Multiphase Shock Tube to measure and quantify the shock-induced dispersal of a shock/dense particle curtain interaction. Following interaction with a planar travelling shock wave, schlieren imaging at 75 kHz was used to track the upstream and downstream edges of the curtain. Data were obtained for two particle diameter ranges ( $d_{p}=106{-}125$ , $300{-}355~\unicode[STIX]{x03BC}\text{m}$ ) across Mach numbers ranging from 1.24 to 2.02. Using these data, along with data compiled from the literature, the dispersion of a dense curtain was studied for multiple Mach numbers (1.2–2.6), particle sizes ( $100{-}1000~\unicode[STIX]{x03BC}\text{m}$ ) and volume fractions (9–32 %). Data were non-dimensionalized according to two different scaling methods found within the literature, with time scales defined based on either particle propagation time or pressure ratio across a reflected shock. The data refelct that spreading of the particle curtain is a function of the volume fraction, with the effectiveness of each time scale based on the proximity of a given curtain’s volume fraction to the dilute mixture regime. It is observed that volume fraction corrections applied to a traditional particle propagation time scale result in the best collapse of the data between the two time scales tested here. In addition, a constant-thickness regime has been identified, which has not been noted within previous literature.

42 ENGINEERING↗
DOE OSTI2023

Measuring photometric redshifts for high-redshift radio source surveys

With the advent of deep, all-sky radio surveys, the need for ancillary data to make the most of the new, high-quality radio data from surveys like the Evolutionary Map of the Universe (EMU), GaLactic and Extragalactic All-sky Murchison Widefield Array survey eXtended, Very Large Array Sky Survey, and LOFAR Two-metre Sky Survey is growing rapidly. Radio surveys produce significant numbers of Active Galactic Nuclei (AGNs) and have a significantly higher average redshift when compared with optical and infrared all-sky surveys. Thus, traditional methods of estimating redshift are challenged, with spectroscopic surveys not reaching the redshift depth of radio surveys, and AGNs making it difficult for template fitting methods to accurately model the source. Machine Learning (ML) methods have been used, but efforts have typically been directed towards optically selected samples, or samples at significantly lower redshift than expected from upcoming radio surveys. This work compiles and homogenises a radio-selected dataset from both the northern hemisphere (making use of Sloan Digital Sky Survey optical photometry) and southern hemisphere (making use of Dark Energy Survey optical photometry). We then test commonly used ML algorithms such as k-Nearest Neighbours (kNN), Random Forest, ANNz, and GPz on this monolithic radio-selected sample. We show that kNN has the lowest percentage of catastrophic outliers, providing the best match for the majority of science cases in the EMU survey. We note that the wider redshift range of the combined dataset used allows for estimation of sources up to z = 3 before random scatter begins to dominate. When binning the data into redshift bins and treating the problem as a classification problem, we are able to correctly identify ≈ 76% of the highest redshift sources—sources at redshift z > 2.51 —as being in either the highest bin (z > 2.51) or second highest (z = 2.25).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The DESC stellarator code suite Part 3: Quasi-symmetry optimization

The DESC stellarator optimization code takes advantage of advanced numerical methods to search the full parameter space much faster than conventional tools. Only a single equilibrium solution is needed at each optimization step thanks to automatic differentiation, which efficiently provides exact derivative information. A Gauss–Newton trust-region optimization method uses second-order derivative information to take large steps in parameter space and converges rapidly. With just-in-time compilation and GPU portability, high-dimensional stellarator optimization runs take orders of magnitude less computation time with DESC compared to other approaches. This paper presents the theory of the DESC fixed-boundary local optimization algorithm along with demonstrations of how to easily implement it in the code. Example quasi-symmetry optimizations are shown and compared to results from conventional tools. Three different forms of quasi-symmetry objectives are available in DESC, and their relative advantages are discussed in detail. In the examples presented, the triple product formulation yields the best optimization results in terms of minimized computation time and particle transport. This paper concludes with an explanation of how the modular code suite can be extended to accommodate other types of optimization problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Simulating nonlinear optical processes on a superconducting quantum device

Simulating plasma physics on quantum computers is difficult because most problems of interest are nonlinear, but quantum computers are not naturally suitable for nonlinear operations. In weakly nonlinear regimes, plasma problems can be modelled as wave–wave interactions. In this paper, we develop a quantization approach to convert nonlinear wave–wave interaction problems to Hamiltonian simulation problems. We demonstrate our approach using two qubits on a superconducting device. Unlike a photonic device, a superconducting device does not naturally have the desired interactions in its native Hamiltonian. Nevertheless, Hamiltonian simulations can still be performed by decomposing required unitary operations into native gates. To improve experimental results, we employ a range of error-mitigation techniques. Apart from readout error mitigation, we use randomized compilation to transform undiagnosed coherent errors into well-behaved stochastic Pauli channels. Moreover, to compensate for stochastic noise, we rescale exponentially decaying probability amplitudes using rates measured from cycle benchmarking. We carefully consider how different choices of product-formula algorithms affect the overall error and show how a trade-off can be made to best utilize limited quantum resources. This study provides an example of how plasma problems may be solved on near-term quantum computing platforms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Performing fully parallel constraint logic programming on a quantum annealer

A quantum annealer exploits quantum effects to solve a particular type of optimization problem. The advantage of this specialized hardware is that it effectively considers all possible solutions in parallel, thereby potentially outperforming classical computing systems. However, despite quantum annealers having recently become commercially available, there are relatively few high-level programming models that target these devices. In this article, we show how to compile a subset of Prolog enhanced with support for constraint logic programming into a two-local Ising-model Hamiltonian suitable for execution on a quantum annealer. In particular, we describe the series of transformations one can apply to convert constraint logic programs expressed in Prolog into an executable form that bears virtually no resemblance to a classical machine model yet that evaluates the specified constraints in a fully parallel manner. We evaluate our efforts on a 1,095-qubit D-Wave 2X quantum annealer and describe the approach's associated capabilities and shortcomings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Single Quadrupole Multiple Fragment Ion Monitoring Quantitative Mass Spectrometry

Single quadrupole mass spectrometry (MS) with enhanced in-source multiple fragment ion monitoring was designed to perform high sensitivity quantitative mass analyses. Enhanced in-source fragmentation amplifies fragmentation from traditional soft electrospray ionization producing fragment ions that have been found to be identical to those generated in tandem MS. We have combined enhanced in-source fragmentation data with criteria established by the European Union Commission Directive 2002/657/EC for electron ionization single quadrupole quantitative analysis to perform quantitative analyses. These experiments were performed on multiple types of complex samples that included a mixture of 50 standards, as well as cell and plasma extracts. The dynamic range for these quantitative analyses was comparable to triple quadrupole multiple reaction monitoring (MRM) analyses at up to 5 orders of magnitude with the cell and plasma extracts showing similar matrix effects across both platforms. Amino acid and fatty acid measurements performed from certified NIST 1950 plasma with isotopically labeled standards demonstrated accuracy in the range of 91–110% for the amino acids, 76–129% for the fatty acids, and good precision (coefficient of variation <10%). To enhance specificity, a newly developed correlated ion monitoring algorithm was designed to facilitate these analyses. This algorithm autonomously processes, aligns, filters, and compiles multiple ions within one chromatogram enabling both precursor and in-source fragment ions to be correlated within a single chromatogram, also enabling the detection of coeluting species based on precursor and fragment ion ratios. Single quadrupole instrumentation can provide MRM level quantitative performance by monitoring/correlating precursor and fragment ions facilitating high sensitivity analysis on existing single quadrupole instrumentation that are generally inexpensive, easy to operate, and technically less complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Predicting Protein–Polymer Block Copolymer Self-Assembly from Protein Properties

Protein–polymer bioconjugate self-assembly has attracted a great deal of attention as a method to fabricate protein nanomaterials in solution and the solid state. To identify protein properties that affect phase behavior in protein–polymer block copolymers, a library of 15 unique protein- b -poly(N-isopropylacrylamide) (PNIPAM) copolymers comprising 11 different proteins was compiled and analyzed. Many attributes of phase behavior are found to be similar among all studied bioconjugates regardless of protein properties, such as formation of micellar phases at high temperature and low concentration, lamellar ordering with increasing temperature, and disordering at high concentration, but several key protein-dependent trends are also observed. In particular, hexagonal phases are only observed for proteins within the molar mass range 20–36 kDa, where ordering quality is also significantly enhanced. While ordering is generally found to improve with increasing molecular weight outside of this range, most large bioconjugates exhibited weaker than predicted assembly, which is attributed to chain entanglement with increasing polymer molecular weight. Additionally, order–disorder transition boundaries are found to be largely uncorrelated to protein size and quality of ordering. However, the primary finding is that bioconjugate ordering can be accurately predicted using only protein molecular weight and percentage of residues contained within β sheets. This model provides a basis for designing protein–PNIPAM bioconjugates that exhibit well-defined self-assembly and a modeling framework that can generalize to other bioconjugate chemistries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Anion Exchange in Cationic Frameworks: Structures of Channel-Forming Triarylpyrylium Tetrafluoroborate Salts

The crystal structure of a co-crystal of 2,4,6-tris(4-methylphenyl)pyridine and 2,4,6-tris(4-methylphenyl)pyrylium revealed a pseudohexagonal motif assembled from π-stacked helices that enclose 1-D channels containing disordered tetrafluoroborate counterions and solvent molecules. Though convoluted by disorder, aperiodicity, and complex twinning patterns, further investigation was motivated by the unique packing arrangement of this material, which enables solid-state anion diffusion, while resisting dissolution in water. Such properties are ideal for the development of anion exchange materials that can be employed for the remediation of agricultural and nuclear waste. Here, to develop a more complete understanding of the intermolecular interactions that give rise to this helical motif, we have compiled and analyzed the local interactions and extended structural motifs of 19 pore- and channel-forming 2,4,6-triarylpyrylium crystal structures. Here, three conserved local interactions were identified, including C–H···X– interactions, the rhombic binding pocket, and four-ring antiparallel dimerization. Development of this library of interaction motifs rationalizes the packing arrangement of the co-crystal and contributes to the informed design of anion exchange materials.

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

Solid Electrolytes in the Spotlight

This virtual issue is targeted to students and researchers, and highlights 32 research articles published over the past 5 years (from July 2016 to July 2021) in Chemistry of Materials (CM). Here, the compilation of papers summarizes the latest advances in the field of solid-state electrolytes for lithium (Li)-, sodium (Na)-, and multivalent-ion (not among the 32 articles discussed) all-solid-state batteries (ASSBs), with a focus on inorganic materials and excluding hybrid systems, e.g., polymer/ceramic composites or systems including liquid media. A total of 125 articles reporting exciting experimental and/or theoretical findings on solid electrolytes were considered for this issue. During 2017–2019, there were about 25–30 papers published per year on this topic, but 2020 and 2021 saw a significant increase, with 26 publications in the first half of 2021 alone. Submissions came from many countries around the world, as shown in Figure 1. While most papers were led by research groups located in the United States, Germany and Japan follow closely, and Austria, the United Kingdom, Canada, and China are also well represented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning

In the past several years, Materials Genome Initiative (MGI) efforts have produced myriad examples of computationally designed materials in the fields of energy storage, catalysis, thermoelectrics, and hydrogen storage as well as large data resources that are used to screen for potentially transformative compounds. The bottleneck in high-Throughput materials design has thus shifted to materials synthesis, which motivates our development of a methodology to automatically compile materials synthesis parameters across tens of thousands of scholarly publications using natural language processing techniques. To demonstrate our framework's capabilities, we examine the synthesis conditions for various metal oxides across more than 12 thousand manuscripts. We then apply machine learning methods to predict the critical parameters needed to synthesize titania nanotubes via hydrothermal methods and verify this result against known mechanisms. Lastly, we demonstrate the capacity for transfer learning by using machine learning models to predict synthesis outcomes on materials systems not included in the training set and thereby outperform heuristic strategies.

36 MATERIALS SCIENCE↗