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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Simulation of thermal hydraulic performance of multiple parallel micropin arrays for concentrating solar thermal applications with supercritical carbon dioxide

Concentrated solar power (CSP) plants have the potential to provide 24 h, renewable electricity. Current CSP systems have high capital and operational costs which makes the levelized cost of electricity uncompetitive with conventional techniques. Recent experimental research has shown the potential of small unit cells (up to 2 × 2 cm) containing micropin arrays (D H < 1 mm) to operate efficiently at high incident flux (>140 W cm -2 ) using supercritical carbon dioxide as the working fluid. Applying this technology to CSP systems would result in a smaller central receiver, which would reduce thermal losses, increase receiver efficiency and reduce the capital cost of the receiver component. This study investigates and addresses the practical thermal and hydraulic issues in numbering up these small unit cells into numerous parallel cells within an integrated module design. A thermal hydraulic network model is developed to quantify the distribution and the overall receiver efficiency of an integrated module. This model is used to specify maximum allowable unit cell size and header dimensions to maintain acceptable thermal performance and pressure loss. Once a module design was finalized, parametric studies were performed to study the effects of varying incident flux on flow distribution and thermal performance of the module. Finally, the results show that an integrated module design can be achieved with less than 5% flow maldistribution and a pressure drop acceptable to the remainder of the system.

14 SOLAR ENERGY↗
DOE OSTI2018

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis

Rationale: The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment. Objective: We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy. Methods: Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoafinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points. Results: A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were sig- ni?cantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status. Conclusion: A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Kedia, Komal↗
DOE OSTI2016

Application of a Pyroprobe-Deuterium NMR System: Deuterium Tracing and Mechanistic Study of Upgrading Process for Lignin Model Compounds

In this study, a pyroprobe-deuterium (2H) NMR system has been used to identify isotopomer products formed during the deuteration and ring opening of lignin model compounds. Several common model compounds for lignin and its upgraded products, including guaiacol, syringol, toluene, p-xylene, phenol, catechol, cyclohexane, methylcyclohexane, and methylcyclopentane, have been examined for selective ring opening. Similar pathways for upgrading of toluene and p-xylene has been found, which will undergo hydrogenation, methyl group elimination, and ring opening process, and benzene, cyclohexane, and methylcyclohexane have been found as major intermediates before ring opening. Very interestingly, the 2H NMR analysis for the deuterium-traced ring opening of catechol on Ir/..gamma..-Al2O3 is almost identical to the ring opening process for phenol. The ring opening processes for guaiacol and syringol appeared to be very complicated, as expected. Benzene, phenol, toluene, cyclohexane, and methylcyclohexane have been determined to be the major products.

09 BIOMASS FUELS↗
DOE OSTI2018

Initiation of Flash Boiling of Multicomponent Miscible Mixtures with Application to Transportation Fuels and Their Surrogates

This paper presents methodologies to predict thermodynamic conditions that initiate flash boiling by spontaneous nucleation of liquids consisting of hundreds of miscible liquids and their lower order surrogate mixtures. The methods are illustrated with a kerosene-based fuel and a seven-component surrogate for it. The predictions are compared to measurements of nucleation temperatures obtained from a pulse-heating technique that rapidly heats a microscale platinum film immersed in a pool of the test fluid. Nucleation temperatures are predicted using a generalized corresponding states principle (GCSP), and a modification of classical nucleation theory that considers the mixture as a pseudo single component fluid (PSCF). The intent is to offer a simple means to predict the initiation of flash boiling that can have important consequences for fuel efficiency in combustion engines. We show that contact angle has a strong effect such that predicted and measured spontaneous nucleation temperatures agree for a given heating rate only if contact angle is accounted for in the theory. For low heating rates (less than 2 × 10 7 K/s), predicted nucleation temperatures, assuming a spherical bubble, are 13% higher than measurements. The gap is closed to about 6% as the heating rate reaches 3 × 10 8 K/s (the highest that could be reached in the experiments) and to less than 1% when the measured nucleation temperature is extrapolated to an asymptotic (zero contact angle) limit. Here, the PSCF method (using mixture properties as mole fraction averages of mixture component properties evaluated at the same reduced temperatures as the mixtures) and the GSCP predict virtually identical nucleation temperatures, while the GCSP method does not require any mixture property values.

42 ENGINEERING↗
DOE OSTI2021

Biofuel Options for Marine Applications: Technoeconomic and Life-Cycle Analyses

This study performed technoeconomic and life-cycle analyses to assess the economic feasibility and emission benefits and tradeoffs of various biofuel production pathways as an alternative to conventional marine fuels. We analyzed production pathways for (1) Fischer-Tropsch diesel from biomass and cofeeding biomass with natural gas or coal, (2) renewable diesel via hydroprocessed esters and fatty acids from yellow grease and cofeeding yellow grease with heavy oil, and (3) bio-oil via fast pyrolysis of low-ash woody feedstock. We also developed a new version of the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) marine fuel module for the estimation of life-cycle greenhouse gas (GHG) and criteria air pollutant (CAP) emissions of conventional and biobased marine fuels. The alternative fuels considered have a minimum fuel selling price between 2.36 and 4.58 $/heavy fuel oil gallon equivalent (HFOGE), and all exhibit improved life-cycle GHG emissions compared to heavy fuel oil (HFO), with reductions ranging from 40 to 93%. The alternative fuels also exhibit reductions in sulfur oxides and particulate matter emissions. Additionally, when compared with marine gas oil and liquified natural gas, they perform favorably across most emission categories except for cases where carbon and sulfur emissions are increased by the cofed fossil feedstocks. The pyrolysis bio-oil offers the most promising marginal CO2 abatement cost at less than $100/tonne CO2e for HFO prices >$1.09/HFOGE followed by Fischer-Tropsch diesel from biomass and natural gas pathways, which fall below $100/tonne CO2e for HFO prices >$2.25/HFOGE. Pathways that cofeed fossil feedstocks with biomass do not perform as well for marginal CO2 abatement cost, particularly at low HFO prices. This study indicates that biofuels could be a cost-effective means of reducing GHG, sulfur oxide, and particulate matter emissions from the maritime shipping industry and that cofeeding biomass with natural gas could be a practical approach to smooth a transition to biofuels by reducing alternative fuel costs while still lowering GHG emissions, although marginal CO2 abatement costs are less favorable for the fossil cofeed pathways.

Greenhouse gas, life cycle assessment, techno-econ↗
DOE OSTI2020

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

In this work, we present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Natural Charge-Transfer Analysis: Eliminating Spurious Charge-Transfer States in Time-Dependent Density Functional Theory via Diabatization, with Application to Projection-Based Embedding

For many types of vertical excitation energies, linear-response time-dependent density functional theory (LR-TDDFT) offers a useful degree of accuracy combined with unrivaled computational efficiency, although charge-transfer excitation energies are often systematically and dramatically underestimated, especially for large systems and those that contain explicit solvent. As a result, low energy electronic spectra of solution-phase chromophores often contain tens to hundreds of spurious charge-transfer states, making LR-TDDFT needlessly expensive in bulk solution. More nefariously, intensity borrowing by the low-energy charge-transfer states can affect intensities of the valence excitations even if those excitation energies are accurate. At higher excitation energies, it is difficult to distinguish spurious CT states from genuine charge-transfer-to-solvent (CTTS) excitations. In this work, we introduce an automated diabatization scheme that enables fast and effective screening of the CTTS acceptor space in bulk solution. Our procedure introduces the concept of “natural charge-transfer orbitals”, which provide a means to isolate characteristic pairs of orbitals that are most likely to participate in a CTTS excitation. The projection of these orbitals onto solvent-centered virtual orbitals provides a criterion for defining the most important solvent molecules in a given excitation. We apply this method to analyze an ab initio molecular dynamics (MD) trajectory of I-(aq) and report the lowest-energy CTTS band in the absorption spectrum. Our results are in excellent agreement with experimental measurements for bulk I-(aq), and only one-third of the water molecules in the I-(H2O)96 simulation cell need to be described with LR-TDDFT in order to obtain excitation energies that are converged to < 0.1 eV. The tools introduced herein will improve the accuracy, efficiency, and usability of LR-TDDFT in solution-phase environments

Carter-Fenk, Kevin D.↗
DOE OSTI2023

Multicomponent Cholesky Decomposition: Application to Nuclear–Electronic Orbital Theory

The Cholesky decomposition technique is commonly used to reduce the memory requirement for storing two-particle repulsion integrals in quantum chemistry calculations that use atomic orbital bases. However, when quantum methods use multicomponent bases, such as nuclear–electronic orbitals, additional challenges are introduced due to asymmetric two-particle integrals. This work proposes several multicomponent Cholesky decomposition methods for calculations using nuclear–electronic orbital density functional theory. To analyze the errors in different Cholesky decomposition components, benchmark calculations using water clusters are carried out. The largest benchmark calculation is a water cluster (H 2 O) 27 where all 54 protons are treated quantum mechanically. Furthermore, this study provides energetic and complexity analyses to demonstrate the accuracy and performance of the proposed multicomponent Cholesky decomposition method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A Perspective on Quantum Computing Applications in Quantum Chemistry Using 25-100 Logical Qubits

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗