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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamics and chemical mode analysis of plasma thermal-chemical instability

The stability of the weakly ionized plasma and the transition from a stable homogeneous discharge to unstable filaments play an important role in gas laser physics, plasma-assisted combustion, chemical reforming, and material synthesis. Here, theoretical stability analysis and thermal-chemical mode analysis were performed to understand the mechanism of plasma thermal-chemical instability by using a zero-dimensional plasma system with both simplified and detailed chemical kinetics of H 2 /O 2 /N 2 mixtures. The plasma dynamic and kinetic models accounted for multiple physical mechanisms in the chemically-reactive weakly ionized plasma, including ionization, attachment/detachment, recombination, vibrational and electronic energy relaxation, convective and diffusive species/heat removal, Joule heating, and detailed chemical kinetics. An analytical criterion and the explosive mode species/temperature pointers were formulated while the representative active species were identified for different thermal-chemical modes. The results showed that in addition to the classical thermal-ionization mechanism, various chemical modes from chemical heat imbalance and elementary kinetics significantly modified the time dynamics and the stability of the weakly ionized plasma. The present analysis provides insights and guidance to control plasma instability using chemical kinetics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

HCV kinetic and modeling analyses indicate similar time to cure among sofosbuvir combination regimens with daclatasvir, simeprevir or ledipasvir

Recent clinical trials of direct-acting-antiviral agents (DAAs) against hepatitis C virus (HCV) achieved >90% sustained virological response (SVR) rates, suggesting that cure often took place before the end of treatment (EOT). We sought to evaluate retrospectively whether early response kinetics can provide the basis to individualize therapy to achieve optimal results while reducing duration and cost. 58 chronic HCV patients were treated with 12-week sofosbuvir + simeprevir (n = 19), sofosbuvir + daclatasvir (n = 19), or sofosbuvir + ledipasvir in three French referral centers. HCV was measured at baseline, day 2, every other week, EOT and 12 weeks post EOT. Furthermore, mathematical modeling was used to predict the time to cure, i.e., <1 virus copy in the entire extracellular body fluid. All but one patient who relapsed achieved SVR. Mean age was 60 ± 11 years, 53% were male, 86% HCV genotype-1, 9% HIV coinfected, 43% advanced fibrosis (F3), and 57% had cirrhosis. At weeks 2, 4 and 6, 48%, 88% and 100% of patients had HCV <15 IU/ml, with 27%, 74% and 91% of observations having target not detected, respectively. Modeling results predicted that 23 (43%), 16 (30%), 7 (13%), 5 (9%) and 3 (5%) subjects were predicted to reach cure within 6, 8, 10, 12 and 13 weeks of therapy, respectively. The modeling suggested that the patient who relapsed would have benefitted from an additional week of sofosbuvir + ledipasvir. Adjusting duration of treatment according to the modeling predicts reduced medication costs of 43–45% and 17–30% in subjects who had HCV <15 IU/ml at weeks 2 and 4, respectively. Finally, the use of early viral kinetic analysis has the potential to individualize duration of DAA therapy with a projected average cost saving of 16–20% per 100-treated persons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Distinguishing Surface and Bulk Reactivity: Concentration-Dependent Kinetics of Iodide Oxidation by Ozone in Microdroplets

Iodine oxidation reactions play an important role in environmental, biological, and industrial contexts. The multiphase reaction between aqueous iodide and ozone is of particular interest due to its prevalence in the marine atmosphere and unique reactivity at the air–water interface. Here, we explore the concentration dependence of the I – + O 3 reaction in levitated microdroplets under both acidic and basic conditions. To interpret the experimental kinetics, molecular simulations are used to benchmark a kinetic model, which enables insight into the reactivity of the interface, the nanometer-scale subsurface region, and the bulk interior of the droplet. For all experiments, a kinetic description of gas- and liquid-phase diffusion is critical to interpreting the results. We find that the surface dominates the iodide oxidation kinetics under concentrated and acidic conditions, with the reactive uptake coefficient approaching an upper limit of 10 –2 at pH 3. In contrast, reactions in the subsurface dominate under more dilute and alkaline conditions, with inhibition of the surface reaction at pH 12 and an uptake coefficient that is 10× smaller. In conclusion, the origin of a changing surface mechanism with pH is explored and compared to previous ozone-dependent measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Extracting Knowledge from Data through Catalysis Informatics

Catalysis informatics is a distinct sub-field that lies at the intersection of cheminformatics and materials informatics, but with unique challenges arising from the dynamic, surface-sensitive, multi-scale nature of heterogeneous catalysis. The ideas behind catalysis informatics can be traced back decades, but the field is only recently emerging due to advances in data infrastructure, statistics, machine learning, and computational methods. In this work we review the field from early works on expert systems and knowledge engines to more recent approaches utilizing machine-learning and uncertainty quantification. The data-information-knowledge hierarchy is introduced and used to classify various developments. The chemical master equation and micro-kinetic models are proposed as a quantitative representation of catalysis knowledge, which can be used to generate explanative and predictive hypotheses for the understanding and discovery of catalytic materials. We discuss future prospects for the field, including improved quantitative coupling of experiment/theory, advanced micro-kinetic models, and the development of open-source software tools. As a result, integration of existing chemical and physical models with emerging statistical and computational tools presents a promising route toward the automated design, discovery, and optimization of heterogeneous catalytic processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Copper availability governs nitrous oxide accumulation in wetland soils and stream sediments

Denitrification is microbially-mediated through enzymes containing metal cofactors. Laboratory studies of pure cultures have highlighted that the availability of Cu, required for the multicopper enzyme nitrous oxide reductase, can limit N2O reduction. However, in natural aquatic systems, such as wetlands and hyporheic zones in stream beds, the role of Cu in controlling denitrification remains incompletely understood. In this study, we collected soils and sediments from three natural environments -- riparian wetlands, marsh wetlands, and a stream -- to investigate their nitrogen species transformation activity at background Cu levels and different supplemented Cu loadings. All of the systems contained solid-phase associated Cu below or around geological levels (40 - 280 nmol g-1) and exhibited low dissolved Cu (3-50 nM), which made them appropriate sites for evaluating the effect of limited Cu availability on denitrification. In laboratory incubation experiments, high concentrations of N2O accumulated in all microcosms lacking Cu amendment except for one stream sediment sample. With Cu added to provide dissolved concentrations at trace levels (10-300 nM), reduction rate of N2O to N 2 in the wetland soils and stream sediments was enhanced. A kinetic model could account for the trends in nitrogen species by combining the reactions for microbial reduction of NO 3 - to NO 2 -/N 2 O/N 2 and abiotic reduction of NO 2 - to N 2 . The model revealed that the rate of N 2 O to N 2 conversion increased significantly in the presence of Cu. For riparian wetland soils and stream sediments, the kinetic model also suggested that overall denitrification is driven by abiotic reduction of NO2- in the presence of inorganic electron donors. This study demonstrated that natural aquatic systems containing Cu at concentrations less than or equal to crustal abundances may display incomplete reduction of N 2 O to N 2 that would cause N 2 O accumulation and release to the atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Enhancing Drinking Water Quality Modeling: Leveraging Physics Informed Neural Networks for Learning with Imperfect Reaction Models and Partial Data

Chemical kinetics models, typically formulated as systems of ordinary or partial differential equations, are valuable tools for simulating drinking water quality. However, these models often face inaccuracies due to discrepancies between the laboratory and the real-world conditions, as well as limitations in experimental analytical methods, hindering the accurate representation of the true underlying chemical mechanisms. In this study, we propose a Physics Informed Neural Network (PINN), using the eXtreme Theory of Functional Connections, to improve the prediction of chemical concentrations over time. The PINN method accounts for imperfect chemical models and incorporates partial data to improve predictions. Focusing on reactions describing water disinfection residual and disinfectant byproduct formation, which are crucial for public health and regulatory compliance, we demonstrate that the PINN model is able to accurately predict the concentrations of chemical species across various pH values. Notably, the model extends its accuracy to predict concentrations of chemical species not originally included in its training data. The developed method can be extended to a variety of chemical systems, offering a wide array of potential applications.

13 HYDRO ENERGY↗
DOE OSTI2014

Experimental and modeling study of fuel interactions with an alkyl nitrate cetane enhancer, 2-ethyl-hexyl nitrate

Our study investigates the autoignition behavior of two gasoline surrogates doped with an alkyl nitrate cetane enhancer, 2-ethyl-hexyl nitrate (2EHN) to better understand dopant interactions with the fuels, including influences of accelerating kinetic pathways and enhanced exothermicity. A primary reference fuel (PRF) blend of n-heptane/iso-octane, and a toluene reference fuel (TRF) blend of n-heptane/iso-octane/toluene are used where the aromatic fraction of the latter is set to 20% (liquid volume), while the content of n-heptane is adjusted so that the overall reactivity of the undoped fuels is similar, e.g., Anti-Knock Index (AKI) of similar to 91, Cetane Number (CN) similar to 25. Doping levels of 0.1, 1.0 and 3.0% (liquid volume basis) are used where tests are conducted within a rapid compression machine (RCM) at a compressed pressure of 21 bar, covering temperatures from 675 to 1025 K with stoichiometric fuel-oxygen ratios at O-2 = 11.4%. At the experimental conditions, it is found that the doping effectiveness of 2EHN is fairly similar between the two fuels, though 2EHN is more effective in the aromatic blend at the lowest temperatures, while it is slightly more effective in the non-aromatic blend at intermediate temperatures. Furthermore, kinetic modeling of the experiments indicates that although some of the reactivity trends can be captured using a detailed model, the extents of predicted Cetane Number enhancement by 2EHN are too large, while differences in fuel interactions for the two fuels result in excessive stimulation of the non-aromatic blend. Sensitivity analysis using the kinetic model indicates that the CH 2 O and CH 3 O 2 chemistry are very sensitive to the dopant at all conditions. The rate of 2EHN decomposition is only important at low temperatures where its decomposition rate is slow due to the high activation energy of the reaction. At higher temperatures, dopant-derived 3-heptyl radicals are predicted to play an important role stimulating ignition. Finally, nitrogen chemistry is important through the 'NO - NO 2 loop' where this can generate substantial amounts of OH. But, at the highest doping levels the formation of methyl and ethyl nitrite, and nitric acid significantly competes with this so that less OH is generated and this constrains the reactivity enhancement of 2EHN.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2014

Study of nitrogen flowing afterglow with mercury vapor injection

The reaction kinetics in nitrogen flowing afterglow with mercury vapor addition was studied by optical emission spectroscopy. The DC flowing post-discharge in pure nitrogen was created in a quartz tube at the total gas pressure of 1000 Pa and discharge power of 130 W. The mercury vapors were added into the afterglow at the distance of 30 cm behind the active discharge. The optical emission spectra were measured along the flow tube. Three nitrogen spectral systems – the first positive, the second positive, and the first negative, and after the mercury vapor addition also the mercury resonance line at 254 nm in the spectrum of the second order were identified. The measurement of the spatial dependence of mercury line intensity showed very slow decay of its intensity and the decay rate did not depend on the mercury concentration. In order to explain this behavior, a kinetic model for the reaction in afterglow was developed. This model showed that the state Hg(6 {sup 3}P{sub 1}), which is the upper state of mercury UV resonance line at 254 nm, is produced by the excitation transfer from nitrogen N{sub 2}(A{sup 3}Σ{sup +}{sub u}) metastables to mercury atoms. However, the N{sub 2}(A{sup 3}Σ{sup +}{sub u}) metastables are also produced by the reactions following the N atom recombination, and this limits the decay of N{sub 2}(A{sup 3}Σ{sup +}{sub u}) metastable concentration and results in very slow decay of mercury resonance line intensity. It was found that N atoms are the most important particles in this late nitrogen afterglow, their volume recombination starts a chain of reactions which produce excited states of molecular nitrogen. In order to explain the decrease of N atom concentration, it was also necessary to include the surface recombination of N atoms to the model. The surface recombination was considered as a first order reaction and wall recombination probability γ = (1.35 ± 0.04) × 10{sup −6} was determined from the experimental data. Also sensitivity analysis was applied for the analysis of kinetic model in order to reveal the main control parameters in the model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Kinetic Deep Learning v0.1

Here, we present a method that uses protein levels to predict times series of metabolite concentrations. Understanding this type of pathway dynamics is important in order to predict the behavior of the pathway and, more pragmatically, to be able to design biological systems (such as strains bioengineered to produce chemical products) reliably. Typically, for this purpose, kinetic models consisting of differential equations based on the Michaelis-Menten dynamics have been used in the past. However, these methods can rarely produce good fits to measured data time series. Possibly, this happens because the kinetic constants are unknown or are different from the ones measured in vivo, or perhaps because Michaelis-Menten dynamics is not a satisfactory description. In order to improve the predictive nature of these kinetic models we have eliminated the Michaelis-Menten description of pathway dynamics and we have substituted it by algorithms that automatically learn these dynamics from previously obtained metabolomics and proteomics data using machine learning approaches. Specifically, kinetic deep learning uses deep learning to map proteomics time series to metabolite concentration time series, instead of learning the first metabolite derivative and integrating in (as in the first version of kinetic learning). This approach is shown to provide good to excellent results with a data set specifically collected for this purpose.

Garcia Martin, Hector [Joint BioEnergy Institute (↗
DOE OSTI2025

Portal matter models of kinetic mixing with two light dark gauge bosons

The kinetic mixing (KM) portal mandates the existence of at least one new gauge boson, the dark photon (DP) based on the group 𝑈⁢(1) 𝐷 , which mixes with the Standard Model (SM) photon via loops of other new heavy particles carrying both SM and dark charges called portal matter (PM). Arguments exist based on the renormalization group equations running of the 𝑈⁢(1) 𝐷 gauge coupling suggesting that at higher scales 𝑈⁢(1) 𝐷 becomes part of a more complex non-Abelian group, a simple example being just the SM-like 𝐺 𝐷 =𝑆⁢𝑈⁢(2)𝐼 ×𝑈⁢(1) 𝑌 𝐼 . In our past analyses, it was always assumed that 𝐺 𝐷 broke in a SM-like manner directly to the DP’s 𝑈⁢(1) 𝐷 which then subsequently broke at low energies ≲1 GeV. However, this need not be the case, and 𝐺 𝐷 can instead break to 𝑈⁢(1) 𝑇 3⁢𝐼 ×𝑈⁢(1) 𝑌 𝐼 , with 𝑇 3⁢𝐼 being the diagonal generator of 𝑆⁢𝑈⁢(2) 𝐼 , now producing two light gauge bosons which obtain masses at the ≲1 GeV scale. In this paper, we explore the phenomenology of a very simple realization of this kind of alternative setup employing non-Abelian KM and having a minimal, leptonlike PM sector, demonstrating its distinctive nature in comparison to the previously examined symmetry breaking path. The effects of interference between these gauge bosons on thermal dark matter annihilation, the production of new heavy gauge, and Higgs and PM states at colliders, as well as the corresponding signatures for the light dark gauge bosons are examined. Collider signatures of this setup are found to be particularly challenging.

extensions of Higgs sector↗
DOE OSTI2023

Catalytic Strategy for Conversion of Triacetic Acid Lactone to Potassium Sorbate

Here this study shows a new route to produce potassium sorbate (KS) from triacetic acid lactone (TAL), which is a chemical platform that can be biologically synthesized from natural sources. Sorbic acid and its potassium salt (KS) are widely used as preservatives in foods and pharmaceuticals. Three steps are used to produce KS from TAL: 1) hydrogenation of TAL into 4-hydroxy- 6-methyltetrahydro-2-pyrone (HMP), 2) dehydration of HMP to parasorbic acid (PSA), and 3) ring-opening and hydrolysis of PSA to KS. TAL can be fully hydrogenated over Ni/SiO2 to give near quantitative yields of HMP. A three-step reaction kinetics model was developed for dehydration of HMP into PSA. This model was used to show that the highest PSA yield occurs at low temperatures. An experimental PSA yield of 84.2% with respect to TAL was obtained which agreed with the prediction of the reaction kinetics model. KOH was used as a coreactant for the ring-opening hydrolysis of PSA to produce >99.9% yield of KS from PSA. Tetrahydrofuran (THF) was used to purify the TAL derived-KS (TAL-KS). The TAL-KS had a KS purity of 95.5%. The overall yield of TAL-KS with respect to TAL was calculated to be 77.3%. TAL-KS produced in this study had similar antimicrobial activities as commercial KS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Cooperative protein structural dynamics of homodimeric hemoglobin linked to water cluster at subunit interface revealed by time-resolved X-ray solution scattering

Homodimeric hemoglobin (HbI) consisting of two subunits is a good model system for investigating the allosteric structural transition as it exhibits cooperativity in ligand binding. In this work, as an effort to extend our previous study on wild-type and F97Y mutant HbI, we investigate structural dynamics of a mutant HbI in solution to examine the role of well-organized interfacial water cluster, which has been known to mediate intersubunit communication in HbI. In the T72V mutant of HbI, the interfacial water cluster in the T state is perturbed due to the lack of Thr72, resulting in two less interfacial water molecules than in wild-type HbI. By performing picosecond time-resolved X-ray solution scattering experiment and kinetic analysis on the T72V mutant, we identify three structurally distinct intermediates (I 1 , I 2 , and I 3 ) and show that the kinetics of the T72V mutant are well described by the same kinetic model used for wild-type and F97Y HbI, which involves biphasic kinetics, geminate recombination, and bimolecular CO recombination. The optimized kinetic model shows that the R-T transition and bimolecular CO recombination are faster in the T72V mutant than in the wild type. From structural analysis using species-associated difference scattering curves for the intermediates, we find that the T-like deoxy I 3 intermediate in solution has a different structure from deoxy HbI in crystal. In addition, we extract detailed structural parameters of the intermediates such as E-F distance, intersubunit rotation angle, and heme-heme distance. By comparing the structures of protein intermediates in wild-type HbI and the T72V mutant, we reveal how the perturbation in the interfacial water cluster affects the kinetics and structures of reaction intermediates of HbI.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Continuum-kinetic-microscopic model of lung clearance due to core-annular fluid entrainment

The human lung is protected against aspirated infectious and toxic agents by a thin liquid layer lining the interior of the airways. This airway surface liquid is a bilayer composed of a viscoelastic mucus layer supported by a fluid film known as the periciliary liquid. The viscoelastic behavior of the mucus layer is principally due to long-chain polymers known as mucins. The airway surface liquid is cleared from the lung by ciliary transport, surface tension gradients, and airflow shear forces. This work presents a multiscale model of the effect of airflow shear forces, as exerted by tidal breathing and cough, upon clearance. The composition of the mucus layer is complex and variable in time. To avoid the restrictions imposed by adopting a viscoelastic flow model of limited validity, a multiscale computational model is introduced in which the continuum-level properties of the airway surface liquid are determined by microscopic simulation of long-chain polymers. A bridge between microscopic and continuum levels is constructed through a kinetic-level probability density function describing polymer chain configurations. The overall multiscale framework is especially suited to biological problems due to the flexibility afforded in specifying microscopic constituents, and examining the effects of various constituents upon overall mucus transport at the continuum scale.

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

Elucidation of Fe-N-C electrocatalyst active site functionality via in-situ X-ray absorption and operando determination of oxygen reduction reaction kinetics in a PEFC

In the past decade the notable effort placed on improving intrinsic electrochemical kinetics of platinum group metal (PGM)-free electrocatalysts for the oxygen reduction reaction (ORR) has led to a significant improvement in both performance and understanding of this class of electrocatalysts. However, a limited amount of this development and understanding has been undertaken using operando electrochemical diagnostics at the membrane electrode assembly (MEA) level. In this work, the operando ORR kinetics on an atomically dispersed iron-nitrogen-carbon ((AD)Fe-N-C) PGM-free electrocatalyst have been examined to extract the reaction order and the activation energy of the ORR. The experiments were carefully designed to ensure the stability/predictability of the electrocatalyst during the data collection process and thus validate the relevance of the values obtained for the aforementioned parameters. A kinetic model that considers a potential-dependent availability of active sites (θ) is proposed. Active site availability is shown to be a function of both the change in the oxidation state (nR) and the redox potential at which the metal center transitions from a higher oxidation state to a lower one (). The resulting model fitting parameters for nR and (0.71 and 0.788 V, respectively) obtained from the analysis of operando data correlate well with those from in situ X-ray absorption near edge structure measurements (nR=0.57) and in situ cyclic voltammetry measurements (0.75 V < <0.8 V) in the MEA environment. The resulting model provides an excellent fit of MEA performance across the range of pressures, temperatures, and potentials under which the data were collected.

Activation energy↗
DOE OSTI2023

Data for Catalytic Strategy for Conversion of Triacetic Acid Lactone to Potassium Sorbate

This study shows a new route to produce potassium sorbate (KS) from triacetic acid lactone (TAL), which is a chemical platform that can be biologically synthesized from natural sources. Sorbic acid and its potassium salt (KS) are widely used as preservatives in foods and pharmaceuticals. Three steps are used to produce KS from TAL: 1) hydrogenation of TAL into 4-hydroxy-6-methyltetrahydro-2-pyrone (HMP), 2) dehydration of HMP to parasorbic acid (PSA), and 3) ring-opening and hydrolysis of PSA to KS. TAL can be fully hydrogenated over Ni/SiO2 to give near quantitative yields of HMP. A three-step reaction kinetics model was developed for dehydration of HMP into PSA. This model was used to show that the highest PSA yield occurs at low temperatures. An experimental PSA yield of 84.2% with respect to TAL was obtained which agreed with the prediction of the reaction kinetics model. KOH was used as a coreactant for the ring-opening hydrolysis of PSA to produce >99.9% yield of KS from PSA. Tetrahydrofuran (THF) was used to purify the TAL derived-KS (TAL-KS). The TAL-KS had a KS purity of 95.5%. The overall yield of TAL-KS with respect to TAL was calculated to be 77.3%. TAL-KS produced in this study had similar antimicrobial activities as commercial KS.

Catalysis↗
DOE OSTI2019

Ecosystem Controls on Methylmercury Production by Periphyton Biofilms in a Contaminated Stream: Implications for Predictive Modeling

Periphyton biofilms produce a substantial fraction of the overall monomethylmercury (MMHg) flux in East Fork Poplar Creek, an industrially contaminated, freshwater creek in Oak Ridge, Tennessee. We examined periphyton MMHg production across seasons, locations, and light conditions using mercury stable isotopes. Methylation and demethylation rate potentials (km, trans av and kd, trans av, respectively) were calculated using a transient availability kinetic model. Light exposure and season were significant predictors of km, trans av, with greater values in full light exposure and in the summer. Season, light exposure, and location were significant predictors of kd, trans av, which was highest in dark conditions, in the spring, and at the upstream location. Light exposure was the controlling factor for net MMHg production, with positive production for periphyton grown under full light exposure and net demethylation for periphyton grown in the dark. Ambient MMHg and km, trans av were significantly correlated. Transient availability rate potentials were 15 times higher for km and 9 times higher for kd compared to full availability rate potentials (km, full av and kd, full av) calculated at 1 d. No significant model for the prediction of km, full av or kd, full av could be constructed using light, season, and location. In addition, there were no significant differences among treatments for the full availability km, full av, kd, full av, or net MMHg calculated using the full availability rate potentials. km, full av was not correlated with ambient MMHg concentrations. The present results underscore the importance of applying transient availability kinetics to MMHg production data when estimating MMHg production potential and flux.

Schwartz, Grace E.↗