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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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DOE OSTI2013

VALIDATION OF THE EQUILIBRIUM MODEL FOR GALAXY EVOLUTION TO z ∼ 3 THROUGH MOLECULAR GAS AND DUST OBSERVATIONS OF LENSED STAR-FORMING GALAXIES

We combine IRAM Plateau de Bure Interferometer and Herschel PACS and SPIRE measurements to study the dust and gas contents of high-redshift star-forming galaxies. We present new observations for a sample of 17 lensed galaxies at z = 1.4-3.1, which allow us to directly probe the cold interstellar medium of normal star-forming galaxies with stellar masses of ∼10{sup 10} M{sub ☉}, a regime otherwise not (yet) accessible by individual detections in Herschel and molecular gas studies. The lensed galaxies are combined with reference samples of submillimeter and normal z ∼ 1-2 star-forming galaxies with similar far-infrared photometry to study the gas and dust properties of galaxies in the SFR-M{sub *}-redshift parameter space. The mean gas depletion timescale of main-sequence (MS) galaxies at z > 2 is measured to be only ∼450 Myr, a factor of ∼1.5 (∼5) shorter than at z = 1 (z = 0), in agreement with a (1 + z){sup –1} scaling. The mean gas mass fraction at z = 2.8 is 40% ± 15% (44% after incompleteness correction), suggesting a flattening or even a reversal of the trend of increasing gas fractions with redshift recently observed up to z ∼ 2. The depletion timescale and gas fractions of the z > 2 normal star-forming galaxies can be explained under the 'equilibrium model' for galaxy evolution, in which the gas reservoir of galaxies is the primary driver of the redshift evolution of specific star formation rates. Due to their high star formation efficiencies and low metallicities, the z > 2 lensed galaxies have warm dust despite being located on the star formation MS. At fixed metallicity, they also have a gas-to-dust ratio 1.7 times larger than observed locally when using the same standard techniques, suggesting that applying the local calibration of the δ{sub GDR}-metallicity relation to infer the molecular gas mass of high-redshift galaxies may lead to systematic differences with CO-based estimates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The utility of {sup 82}Rb PET for myocardial viability assessment: Comparison with perfusion-metabolism {sup 82}Rb-{sup 18}F-FDG PET

Background: {sup 82}Rb kinetics may distinguish scar from viable but dysfunctional (hibernating) myocardium. We sought to define the relationship between {sup 82}Rb kinetics and myocardial viability compared with conventional {sup 82}Rb and {sup 18}F-fluorodeoxyglucose (FDG) perfusion-metabolism PET imaging. Methods: Consecutive patients (N = 120) referred for evaluation of myocardial viability prior to revascularization and normal volunteers (N = 37) were reviewed. Dynamic {sup 82}Rb 3D PET data were acquired at rest. {sup 18}F-FDG 3D PET data were acquired after metabolic preparation using a standardized hyperinsulinemic-euglycemic clamp. {sup 82}Rb kinetic parameters K{sub 1}, k{sub 2}, and partition coefficient (KP) were estimated by compartmental modeling Results: Segmental {sup 82}Rb k{sub 2} and KP differed significantly between scarred and hibernating segments identified by Rb-FDG perfusion-metabolism (k{sub 2}, 0.42 ± 0.25 vs. 0.22 ± 0.09 min{sup −1}; P < .0001; KP, 1.33 ± 0.62 vs. 2.25 ± 0.98 ml/g; P < .0001). As compared to Rb-FDG analysis, segmental Rb KP had a c-index, sensitivity and specificity of 0.809, 76% and 84%, respectively, for distinguishing hibernating and scarred segments. Segmental k{sub 2} performed similarly, but with lower specificity (75%, P < .001) Conclusions: In this pilot study, {sup 82}Rb kinetic parameters k{sub 2} and KP, which are readily estimated using a compartmental model commonly used for myocardial blood flow, reliably differentiated hibernating myocardium and scar. Further study is necessary to evaluate their clinical utility for predicting benefit after revascularization. [French] French Abstract: Contexte: La cinétique du {sup 82}Rb pourrait être utilisée pour distinguer la fibrose myocardique des zones viables mais dysfonctionnelles (en hibernation). Dans cette étude, nous avons cherché à définir la relation entre la cinétique du {sup 82}Rb et la viabilité myocardique en comparant les images de perfusion et métabolisme myocardique utilisant le {sup 82}Rb et le {sup 18}F-fluorodésoxyglucose (FDG) Méthodes: les données obtenues chez 120 patients consécutifs (N = 120) référés pour évaluation de la viabilité du myocarde avant revascularisation et 37 volontaires considérés normaux (N = 37) ont été étudieés. Les données TEP 3D dynamiques {sup 82}Rb ont été acquises au repos. Les données TEP 3D au {sup 18}F-FDG ont été acquises après préparation métabolique utilisant une pince hyperinsulémique-euglycémique normalisée. Les paramètres k1, k2 et le coefficient de partage (KP) de la cinétique du {sup 82}R bont été évalues par modélisation compartimentale. Résultats: les paramètres k2 et KP de distribution du {sup 82}Rb se sont révélés significativement différent entre les zones tissulaires cicatricielles fibreuses et celles en hibernation identifiées par étude métabolique au FDG (k2, 0,42 ± 0,25 vs. 0,22 ± 0,09 min{sup −1}; P < 0,0001; KP, 1,33 ± 0,62 vs. 2,25 ± 0,98 ml/g; P < 0,0001). Par rapport aux données FDG, le paramètre KP du rubidium a révélé un indice de concordance de 0,809 et une sensibilité et spécificité de 76% et 84%, pour la distinction des segments en hibernation et cicatrisés. Les résultats du paramètre k2 se sont révélés similaires, mais avec une spécificité plus faible calculée à 75% (P < 0,001). Conclusions: Dans cette étude pilote, les paramètres cinétiques k2 et KP de perfusion myocardique au {sup 82}Rb, qui sont facilement estimés à l’aide d’un modèle compartimental couramment utilisé pour flux sanguin myocardique, ont permis de différencier de manière fiable le myocarde cicatricielle des zones myocardiques hibernantes. Une étude plus approfondie est souhaitable pour valider leur utilité clinique en revacularisation. [Spanish] Spanish Abstract: Antecedentes: La cinética con {sup 82}Rb puede distinguir las cicatrices miocárdicas del tejido viable pero disfuncional (hibernante). Buscamos definir la relación entre la cinética del {sup 82}Rb y la viabilidad miocárdica comparada con las imágenes convencionales de PET con {sup 82}Rb y {sup 18}F-flurodeoxyglucosa (FDG). Métodos: se evaluaron a Pacientes Consecutivos (N = 120) referidos para evaluación de viabilidad miocárdica previos a revascularización y voluntarios normales (N = 37). Los datos de PET 3D dinámico con {sup 82}Rb fueron adquiridos en reposo. Los datos de {sup 18}F-FDG 3D PET fueron adquiridos posterior a la preparación metabólica usando un clamp hiperinsulínico-euglucémico. Los patrones cinéticos K1, k2 y el coeficiente de partición (KP) fueron estimados por el modelo compartimental. Resultados: el k2 y KP del {sup 82}Rb permitueron distinguier el tejido cicatricial de los segmentos hibernados identificados por la vía perfusión metabolismo de Rb-FDG (k{sub 2}, 0.42 ± 0.25 vs. 0.22 ± 0.09 min-1; P < .0001; KP, 1.33 ± 0.62 vs. 2.25 ± 0.98 ml/g; P < .0001). En comparación con el análisis de Rb-FDG, el KP segmentario del Rb tuvo un índice-c, sensbilidad y especificidad de 0.809 76 y 84%, respectivamente, para distinguir segmentos hibernantes y cicatriciales. k2 Segmentario tuvo un desempeño similar pero con una menor especificidad (75%, P < .001). Conclusiones: En este estudio piloto, los parámetros cinéticos k2 y KP del {sup 82}Rb, los cuales son estimados usando un modelo compartimental usado comúnmente para flujo sanguíneo miocárdico, diferenciaron el miocardio hibernante del cicatricial. Se necesita estudiar más a fondo para evaluar la utilidad clínica para la predicción del beneficio posterior a la revascularización [Chinese] Chinese Abstract: 背景: 铷-82({sup 82}Rb)药代动力学可能区分梗死与功能受损但存活的心肌(冬眠心肌)。我们将探讨{sup 82}Rb药代动力学与存活心肌的关系,并与常规的{sup 82}Rb和{sup 18}F-氟脱氧葡萄糖(FDG)灌注-代谢PET显像进行比较。 方法: 连续纳入120名血运重建前评估存活心肌的患者和37名正常志愿者。获得静息{sup 82}Rb 3D-PET动态采集数据;采用标准化的高胰岛素 - 正葡萄糖钳夹试验得到{sup 18}F-FDG 3D PET代谢显像数据; 通过房室模型计算{sup 82}Rb动力学参数k{sub 1},k{sub 2}和分配系数(KP)。 结果: 以Rb-FDG灌注代谢显像鉴定疤痕心肌组和冬眠心肌组,两组的{sup 82}Rb节段性 k{sub 2}值和KP值有明显差异(k{sub 2}, 0.42 ± 0.25 vs 0.22 ± 0.09 min{sup −1}; P < .0001; KP, 1.33 ± 0.62 vs 2.25 ± 0.98 ml/g; P < .0001)。以Rb-FDG灌注代谢显像为诊断标准,{sup 82}Rb节段性 KP对疤痕和冬眠心肌鉴别效能的c指数,敏感性和特异性分别是0.809, 76%和84%。节段性k{sub 2}的鉴别效能与KP相似,但特异性较低(75%,P < .001)。 结论: 在本试验性研究中,通过常规用于{sup 82}Rb心肌血流量测定的房室模型计算出的{sup 82}Rb动力学参数k{sub 2}和KP,可以有效的区分冬眠心肌和瘢痕心肌。 但需要进一步的研究来评估其对预测血运重建是否获益的临床价值。.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

A redefinition of the halo boundary leads to a simple yet accurate halo model of large-scale structure

ABSTRACT We present a model for the halo–mass correlation function that explicitly incorporates halo exclusion and allows for a redefinition of the halo boundary in a flexible way. We assume that haloes trace mass in a way that can be described using a single scale-independent bias parameter. However, our model exhibits scale-dependent biasing due to the impact of halo-exclusion, the use of a ‘soft’ (i.e. not infinitely sharp) halo boundary, and differences in the one halo term contributions to ξhm and ξmm. These features naturally lead us to a redefinition of the halo boundary that lies at the ‘by eye’ transition radius from the one-halo to the two-halo term in the halo–mass correlation function. When adopting our proposed definition, our model succeeds in describing the halo–mass correlation function with $\approx 2{{\ \rm per\ cent}}$ residuals over the radial range 0.1 h−1 Mpc < r < 80 h−1 Mpc, and for halo masses in the range 1013 h−1 M⊙ < M < 1015 h−1 M⊙. Our proposed halo boundary is related to the splashback radius by a roughly constant multiplicative factor. Taking the 87 percentile as reference we find rt/Rsp ≈ 1.3. Surprisingly, our proposed definition results in halo abundances that are well described by the Press–Schechter mass function with δsc = 1.449 ± 0.004. The clustering bias parameter is offset from the standard background-split prediction by $\approx 10{{\ \rm per\ cent}}\!-\!15{{\ \rm per\ cent}}$. This level of agreement is comparable to that achieved with more standard halo definitions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models

Purpose: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Methods: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. Results: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: −11.6%–23.8%) and 14.6% (range: −7.3%–27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: −6.8%–40.3%) and 13.1% (range: −1.5%–52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: −11.1%–20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. Conclusions: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Prospects of direct search for dark photon and dark Higgs in SeaQuest/E1067 experiment at the Fermilab main injector

In this study, we present the current status and prospects of the dark sector physics search program of the SeaQuest/E1067 fixed target dimuon experiment at Fermilab Main Injector. There has been tremendous excitement and progress in searching for new physics in the dark sector in recent years. Dark sector refers to a collection of currently unknown particles that do not directly couple with the Standard Model (SM) strong and electroweak (EW) interactions but assumed to carry gravitational force, thus could be candidates of the missing Dark Matter (DM). Such particles may interact with the SM particles through “portal” interactions. Two of the simple possibilities are being investigated in our initial search: (1) dark photon and (2) dark Higgs. They could be within immediate reach of current or near future experimental search. We show there is a unique opportunity today at Fermilab to directly search for these particles in a highly motivated but uncharted parameter space in high-energy proton–nucleus collisions in the beam-dump mode using the 120 GeV proton beam from the Main Injector. Our current search window covers the mass range 0.2–10 GeV/c 2 , and in the near future, by adding an electromagnetic calorimeter (EMCal) to the spectrometer, we can further explore the lower mass region down to about ~1 MeV/c 2 through the di-electron channel. If dark photons (and/or dark Higgs) were observed, they would revolutionize our understanding of the fundamental structures and interactions of our universe.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Stabilization of Cu 2 O through Site-Selective Formation of a Co 1 Cu Hybrid Single-Atom Catalyst

Single-atom catalysts (SACs) consist of a low coverage of isolated metal atoms dispersed on a metal substrate, called single-atom alloys (SAAs), or alternatively single metal atoms coordinated to oxygen atoms on an oxide support. We present the synthesis of a new type of Co 1 Cu SAC centers on a Cu 2 O(111) support by means of a site-selective atomic layer deposition technique. Isolated metallic Co atoms selectively coordinate to the native oxygen vacancy sites (Cu sites) of the reconstructed Cu 2 O(111) surface, forming a Co 1 Cu SAA with no direct Co–O x bonds. The centers, here referred to as Co 1 Cu hybrid SACs, are found to stabilize the active Cu + sites of the low-cost Cu 2 O catalyst that otherwise is prone to deactivation under reaction conditions. The stability of the Cu 2 O(111) surface was investigated by synchrotron radiation-based ambient-pressure X-ray photoelectron spectroscopy under reducing CO environment. The structure and reduction reaction are modeled by density functional theory calculations, in good agreement with experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Connected three-body terms in single-reference unitary many-body theories: Iterative and perturbative approximations

This work introduces various approaches to include connected three-body terms in unitary many-body theories, focusing on the driven similarity renormalization group (DSRG). Starting from the least approximate method—the linearized DSRG truncated to one-, two-, and three-body operators [LDSRG(3)]—we develop several approximate LDSRG(3) models with reduced computational cost. Through a perturbative analysis, we motivate a family of iterative LDSRG(3)-n and -n' (n = 1, 2, 3, 4) methods that contain a subset of the LDSRG(3) diagrams. Among these variants, the LDSRG(3)-2 scheme has the same computational complexity of coupled cluster theory with singles, doubles, and triples (CCSDT), but it outperforms CCSDT in the accuracy of the predicted correlation energies. We also propose and implement two perturbative triples corrections based on the linearized DSRG truncated to one- and two-body operators augmented with recursive semi-quadratic commutators [qDSRG(2)]. Overall, the resulting qDSRG(2)+(T) approach matches the accuracy of the “gold-standard” coupled cluster theory with singles, doubles, and perturbative triples model on the energetics of twenty-eight closed-shell atoms and small molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Retrospective Analysis of NIST Standard Reference Material 1450, Fibrous Glass Board, for Thermal Insulation Measurements

Thermal conductivity data acquired previously for the establishment of Standard Reference Material (SRM) 1450, Fibrous Glass Board, as well as subsequent renewals 1450a, 1450b, 1450c, and 1450d, are re-analyzed collectively and as individual data sets. Additional data sets for proto-1450 material lots are also included in the analysis. The data cover 36 years of activity by the National Institute of Standards and Technology (NIST) in developing and providing thermal insulation SRMs, specifically high-density molded fibrous-glass board, to the public. Collectively, the data sets cover two nominal thicknesses of 13 mm and 25 mm, bulk densities from 60 kg∙m -3 to 180 kg∙m -3 , and mean temperatures from 100 K to 340 K. The analysis repetitively fits six models to the individual data sets. The most general form of the nested set of multilinear models used is given in the following equation: λ(ρ, T) = α 0 + α 1 ρ +α 2 T + α 3 T 3 +α 4 e - ($\frac{T-a_{5}}{a_{6}}$) 2 = where λ(ρ,T) is the predicted thermal conductivity (W∙m -1 ∙K -1 ), ρ is the bulk density (kg∙m -3 ), T is the mean temperature (K) and $a_i$ (for i = 1, 2, … 6) are the regression coefficients. The least squares fit results for each model across all data sets are analyzed using both graphical and analytic techniques. The prevailing generic model for the majority of data sets is the bilinear model in ρ and T. λ(ρ, T) = α 0 + α 1 ρ +α 2 T One data set supports the inclusion of a cubic temperature term and two data sets with low-temperature data support the inclusion of an exponential term in T to improve the model predictions. Physical interpretations of the model function terms are described. Recommendations for future renewals of SRM 1450 are provided. An Addendum provides historical background on the origin of this SRM and the influence of the SRM on external measurement programs.

regression analysis↗
DOE OSTI2022

Solar Radiation Research Laboratory (SRRL) Final Report: Fiscal Years 2019-2021

The Solar Radiation Research Laboratory (SRRL) at the National Renewable Energy Laboratory (NREL) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m 2 ) for the United States, which is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two International Organization for Standardization (ISO)/International Electrotechincal Commission (IEC) 17025 calibration facilities that provide unique, high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop: improved methods for the calibration of solar radiometers; new standards through the ISO, the IEC, and ASTM International; models; advanced instrumentation and methods for operating solar measurement stations. The SRRL data sets are also critical for the validation of new models and data sets, such as the National Solar Radiation Database (NSRDB).

14 SOLAR ENERGY↗
DOE OSTI2016

SU-F-T-119: Development of Heart Prediction Model to Increase Accuracy of Dose Reconstruction for Radiotherapy Patients

Purpose: To assess individual variation in heart volume and location in order to develop a prediction model of the heart. This heart prediction model will be used to calculate individualized heart doses for radiotherapy patients in epidemiological studies. Methods: Chest CT images for 30 adult male and 30 adult female patients were obtained from NIH Clinical Center. Image-analysis computer programs were used to segment the whole heart and 8 sub-regions and to measure the volume of each sub- region and the dimension of the whole heart. An analytical dosimetry method was used for the 30 adult female patients to estimate mean heart dose during conventional left breast radiotherapy. Results: The average volumes of the whole heart were 803.37 cm{sup 3} (COV 18.8%) and 570.19 cm{sup 3} (COV 18.8%) for adult male and female patients, respectively, which are comparable with the international reference volumes of 807.69 cm{sup 3} for males and 596.15 cm{sup 3} for females. Some patient characteristics were strongly correlated (R{sup 2}>0.5) with heart volume and heart dimensions (e.g., Body Mass Index vs. heart depth in males: R{sup 2}=0.54; weight vs. heart width in the adult females: R{sup 2}=0.63). We found that the mean heart dose 3.805 Gy (assuming prescribed dose of 50 Gy) in the breast radiotherapy simulations of the 30 adult females could be an underestimate (up to 1.6-fold) or overestimate (up to 1.8-fold) of the patient-specific heart dose. Conclusion: The study showed the significant variation in patient heart volumes and dimensions, resulting in substantial dose errors when a single average heart model is used for retrospective dose reconstruction. We are completing a multivariate analysis to develop a prediction model of the heart. This model will increase accuracy in dose reconstruction for radiotherapy patients and allow us to individualize heart dose calculations for patients whose CT images are not available.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

235 U– 231 Pa age dating of uranium materials for nuclear forensic investigations

Here, age dating of nuclear material can provide insight into source and suspected use in nuclear forensic investigations. We report here a method for the determination of the date of most recent chemical purification for uranium materials using the 235 U- 231 Pa chronometer. Protactinium is separated from uranium and neptunium matrices using anion exchange resin, followed by sorption of Pa to an SiO 2 medium. The concentration of 231 Pa is measured by isotope dilution mass spectrometry using 233 Pa spikes prepared from an aliquot of 237 Np and calibrated in-house using the rock standard Table Mountain Latite and the uranium isotopic standard U100. Combined uncertainties of age dates using this method are 1.5 to 3.5 %, an improvement over alpha spectrometry measurement methods. Model ages of five uranium standard reference materials are presented; all standards have concordant 235 U- 231 Pa and 234 U- 230 Th model ages.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

A hybrid framework of first principles molecular orbital calculations and a three-dimensional integral equation theory for molecular liquids: Multi-center molecular Ornstein–Zernike self-consistent field approach

In this study, we reported the development of a new quantum mechanics/molecular mechanics (QM/MM)-type framework to describe chemical processes in solution by combining standard molecular-orbital calculations with a three-dimensional formalism of integral equation theory for molecular liquids (multi-center molecular Ornstein–Zernike (MC-MOZ) method). The theoretical procedure is very similar to the 3D-reference interaction site model self-consistent field (RISM-SCF) approach. Since the MC-MOZ method is highly parallelized for computation, the present approach has the potential to be one of the most efficient procedures to treat chemical processes in solution. Benchmark tests to check the validity of this approach were performed for two solute (solute water and formaldehyde) systems and a simple S{sub N}2 reaction (Cl{sup −} + CH{sub 3}Cl → ClCH{sub 3} + Cl{sup −}) in aqueous solution. The results for solute molecular properties and solvation structures obtained by the present approach were in reasonable agreement with those obtained by other hybrid frameworks and experiments. In particular, the results of the proposed approach are in excellent agreements with those of 3D-RISM-SCF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

High-pressure dynamics of hydrated protein in bioprotective trehalose environment

Here we present a pressure-dependence study of the dynamics of lysozyme protein powder immersed in deuterated , α-trehalose environment via quasielastic neutron scattering (QENS). The goal is to assess the baroprotective benefits of trehalose on biomolecules by comparing the findings with those of a trehalose-free reference study. While the mean-square displacement of the trehalose-free protein (hydrated to d D₂O ≃40 w%) as a whole, is reduced by increasing pressure, the actual observable relaxation dynamics in the picoseconds to nanoseconds time range remains largely unaffected by pressure up to the maximum investigated pressure of 2.78(2) Kbar. Our observation is independent of whether or not the protein is mixed with the deuterated sugar. This suggests that the hydrated protein s conformational states at atmospheric pressure remain unaltered by hydrostatic pressures, below 2.78 Kbar. We also found the QENS response to be totally recoverable after ambient pressure conditions are restored. Small-angle neutron diffraction measurements confirm that the protein-protein correlation remains undisturbed.We observe, however, a clear narrowing of the QENS response as the temperature is decreased from 290 to 230 K in both cases, which we parametrize using the Kohlrausch-Williams-Watts stretched exponential model. Finally, only the fraction of protons that are immobile on the accessible time window of the instrument, referred to as the elastic incoherent structure factor, is observably sensitive to pressure, increasing only marginally but systematically with increasing pressure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A novel means to flexibly operate a hybrid concentrated solar power plant and improve operation during non-ideal direct normal irradiation conditions

Hybridization of concentrated solar power (CSP) with other energy sources can drastically increase how much solar energy is harnessed and potentially expand the current geographical deployment of CSP installlations. In this study, a novel operation strategy referred to as flexible heat integration (FHI), is proposed and applied to a hybrid CSP-natural gas power plant. The proposed plant, modeled in Simulink, employs a solar central receiver (SCR) and dual-source gas boiler to drive a steam Rankine power cycle. FHI involves collecting and dispatching solar energy at modified temperatures during off-design direct normal irradiance (DNI). During low-grade (<100 W/m 2 ) and medium-grade (100–500 W/m 2 ) levels of DNI, molten salt is used for steam boiling and feedwater preheating, respectively, rather than superheating usually seen in SCR steam plants. Hybrid gas-firing supplies energy to bypassed systems. FHI is applied to a hybrid plant over the course of a day from each season for a plant located in Salt Lake City, Utah, an unconventional location due to off-design DNI variability. A spring day exhibiting variable DNI is used as the main case study to demonstrate the dynamics and robust operation under the FHI framework. The operation of the plant over the winter day shows the largest improvement in solar-to-electric (STE) efficiency whereas the summer day exhibits the smallest improvement. Monthly results follow a similar trend with FHI improving STE from 15.3% and 16.3% to 17.0% and 16.7% in January and July, respectively. Yearly results show FHI improving STE efficiency from 16.1% to 17.1% relative to standard hybrid operation. Altogether, the proposed concept expands the current understanding of energy management in hybrid SCR-natural power plants under non-ideal DNI conditions and locations that have lower DNI by applying FHI.

14 SOLAR ENERGY↗
DOE OSTI2026

Li1−xNiO2 Many-body DMC Benchmark Dataset

The dataset contains all numerical data generated in support of the manuscript “Many‑body Benchmark of Electronic Charge and Spin Densities for Li1–xNiO2​” (Journal of Chemical Theory and Computation, DOI: 10.1021/acs.jctc.5c02097, URL: https://pubs.acs.org/doi/10.1021/acs.jctc.5c02097). The materials included in this repository are: 1. Data files used to produce all figures and tables in the main manuscript and supporting information. 2. Benchmark density‑functional theory (DFT) datasets used for the charge‑ and spin‑density analyses. 3. Reference many‑body diffusion Monte Carlo (DMC) calculations and associated input/output files.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Artificial Intelligence Application to D and D - 20492

As aging facilities across the DOE complex await decommissioning, there is an ongoing need to understand any changes in the structural conditions. Many of these facilities were built over 50 years ago and, in some cases, these facilities have gone beyond the expected operational lifetime. Many facilities have been placed in a state of 'cold and dark,' sitting unused and awaiting decommissioning. Especially challenging are the aging facilities that provide unique operational/production capabilities to support critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may become compromised as time passes. It is critical that adequate inspections be performed on a continual basis and that the data collected undergoes sufficient analysis to support timely identification of any new or worsening structural issues as well as prompt needed maintenance and repairs to maintain the facilities in a safe condition. In recent days, Artificial Intelligence (AI) [1] and its application to various domains are growing at fast speed. FIU is performing research in this area and exploring the associated technologies to solve nuclear decommissioning problems. Artificial intelligence refers to the capability of a program to autonomously act, react and adapt to the working environment. AI enables the machine to behave like humans and perform the cognitive functions such as 'learning' and 'problem solving'. AI systems gradually moving from traditional approaches (algorithms and expert systems) towards more efficient and advanced technologies (machine learning [1] and deep learning [2] [3]). AI is the study of algorithms and statistical models that is being used by computers to perform specific tasks without using explicit instructions. FIU is working to develop a pilot-scale infrastructure to implement structural health monitoring using AI technologies with focus on machine learning, deep learning. This research is focused on Computer Vision/Image Classification area of AI applications. This can also be expanded to other areas of AI related to Object Recognition and Character Recognition in images. In addition to utilizing existing data sets, FIU will collect and investigate image and video data using FIU test-bed mockups to monitor structural health of the facility. Resulting data will be processed and analyzed using machine learning/deep learning technologies. The proposed pilot system is intended to serve as a starting point to engage the DOE field sites on related data sets and their decision making needs. It is anticipated that proposed machine learning/deep learning technologies can be effectively employed using anomaly detection to solve EM challenges in surveillance and maintenance of the D and D facilities. FIU will work with research stakeholders to identify applications at various sites and other DOE facilities. (authors)

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DOE OSTI2019

Solar Resource Calibration, Measurement, and Dissemination: Final Report FY 2016-FY 2018

The Solar Resource Calibration, Measurement, and Dissemination project supports the U.S. Department of Energy's Solar Energy Technologies Office (SETO) initiative to make solar energy cost-competitive with other forms of electricity by improving the tools and methods to measure and model solar radiation and therefore reduce uncertainty in predicting solar output and improve the bankability of solar projects. This project has three tasks that conduct research on advancing solar resource measurements and modeling: Task 1: Applied solar Radiation Measurements. Task 2: National Solar Radiation Data Base (NSRDB). Task 3: Knowledge Sharing. The National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) activities ensure traceable solar measurements throughout the United States that are essential for project feasibility, due diligence, financing, and plant operations. The SRRL houses NREL's Baseline Measurement System (BMS), which provides a platform for improving the accuracy of solar measurements through research to improve the calibration and characterization of instruments and enable the development of new measurement technology and standards. The platform contains a variety of instruments measuring solar radiation and other meteorological parameters. Following best practices, BMS instruments are calibrated to ensure traceability to the World Radiometric Reference in compliance with ISO/IEC 17025 accreditation requirements. The BMS data sets are quality-controlled and made publicly available through the Measurement and Instrumentation Data Center website. The NSRDB is the most accessed public database of solar irradiance and associated weather parameters for use in energy modeling. It supports SETO's goals of reducing barriers to high penetrations of solar technologies by providing easy access to high-quality, foundational data essential for innovative product development and downstream modeling through the NSRDB website. Data are currently available for the contiguous United States and beyond for 20 years covering 1998-2017. The Physical Solar Model (PSM) that underpins the current NSRDB data sets is a unique physics-based model that has been developed at NREL and has opened the door to the use of next-generation satellite data sets for solar resource assessment and forecasting. Through the American Society for Testing Materials (ASTM) International and other international standards organizations, NREL continues to provide leadership in the development of standards that are relevant to the measurement and modeling of solar radiation for solar energy applications. Standards developed cover the calibration method of pyrheliometers (direct normal irradiance measurements), pyranometers (global horizontal irradiance measurements), spectroradiometers, ultraviolet radiometers, correct field deployment of these instruments, spectral distribution reference tables for photovoltaic modeling, and transfer of indoor calibrations. Further, NREL leads the International Energy Agency (IEA) Photovoltaic Power Systems Programme Task 16: Subtask 1, which focuses on the evaluation of current and emerging resource assessment methodologies. NREL and the IEA updated the Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications, which is widely used by the solar industry.

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