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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing

This paper presents a physics-informed machine learning (ML) framework to construct reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on high-fidelity numerical simu-lations. QoIs include species decay, product yield, and degree of mixing. The ROMs for QoIs are applied to quantify and understand how the chemical species evolve over time. First, high-resolution datasets for constructing ROMs are generated by solving anisotropic reaction-di?usion equations using a non-negative finite element formulation for di?erent input parameters. The reactive-mixing model input parameters are: time-scale associated with flipping of velocity, spatial-scale controlling small/large vortex structures of velocity, perturbation parameter of the vortex-based velocity, anisotropic dispersion strength/contrast, and molecular diffusion. Second, random forests, F-test, and mutual information criterion are used to evaluate the importance of model inputs/features with respect to QoIs. We observed that anisotropic dispersion strength/contrast is the most important feature and time-scale associated with flipping of velocity is the least important feature. Third, Support Vector Machines (SVM) and Support Vector Regression (SVR) are used to construct ROMs based on the model inputs. The constructed SVR-ROMs are then used to predict scaling of QoIs. We also present estimates and inequalities on the QoIs, which inform that the species decay, mix, and produce in an exponential fashion. These inequalities also inform that a radial basis function is the most suitable kernel for the SVM/SVR models for QoIs. It is observed that R2-score for SVR-ROMs on unseen data is greater than 0.9, implying that the SVR-ROMs are able to predict the reaction-diffusion system state reasonably well. Finally, in terms of the computational cost, the proposed SVM-ROMs are O(107) times faster than running a high-fidelity finite element simulation for evaluating QoIs. This makes the proposed ML-based ROMs attractive for reactive-transport sensing and real-time monitoring applications as they are significantly faster yet reasonably accurate.

Mudunuru, Maruti K.↗
DOE OSTI2020

Low Temperature Activation of Methane on Metal-Oxides and Complex Interfaces: Insights from Surface Science

The abundance of inexpensive, natural gas has transformed the energy landscape, whereby revealing new possibilities for sustainable chemical technologies or impacting those that have relied on traditional fossil fuels. The primary component, methane, is underutilized and wastefully exhausted, leading to anthropogenic global warming. Historically, the manipulation of methane remained “ clavis aurea ,” an insurmountable yet rewarding challenge and thus the focus of intense research. This is primarily due to an inability to dissociate C–H bonds in methane selectively, which requires a high energy penalty and is an essential prerequisite for the direct conversion of methane into a large set of value-added products. The discovery of such processes would promise an energy gainful use of natural gas benefiting several essential chemical processes associated with C1 chemistry. This first C–H bond dissociation step of the methane molecule appears in numerous catalytic mechanisms as the rate-determining step or most essential barrier sequence for all subsequent steps that follow in the production of C–C, C–O, or C x –H y –O z bonds found in value added products. A main goal is to catalytically reduce the energy barrier for the first C–H bond dissociation to be able to achieve the activation of methane at low or moderate temperatures. As such there is great value in understanding the fundamental nature of the active sites responsible for bond breaking or formation and thus be able to facilitate better control of this chemistry, leading to the development of new technologies for fuel production and chemical conversion. Surface science studies offer enhanced perspectives for a careful manipulation of bonds over the last layer atoms of catalyst surfaces, an essential factor for the design of atomically precise catalysts and unravelling of the reaction mechanism. With the advent of new surface imaging, spectroscopy, and in situ tools, it has been possible to decipher the surface chemistry of complex materials systems and further our understanding of atomic active sites on the surfaces of metals, oxides, and carbides or metal–oxide and metal–carbide interfaces. The once considered near impossible step of C–H bond activation is now observed at low temperatures with high propensity over a collection of oxide, metal–oxide, and metal–carbide systems in a conventional or inverse configuration (oxide or carbide on metal). The enabling of C–H activation at low temperature has opened interesting possibilities for the specific production of chemicals such as methanol directly from methane, a step toward facile synthesis of liquid fuels. We highlight the most recent of these results and present the key aspects of active site configurations engineered from surface science studies which enable such a simple reactive event through careful manipulation of the last surface layer of atoms found in the catalyst structure. New concepts which help in the activation and conversion of methane are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Dynamic linear response quantum algorithm

The dynamic linear response of a quantum system is critical for understanding both the structure and dynamics of strongly interacting quantum systems, including neutron scattering from materials, photon and electron scattering from atomic systems, and electron and neutrino scattering by nuclei. Here, we present a general algorithm for universal quantum computers to calculate the dynamic linear response function with controlled errors and to obtain information about specific final states that can be directly compared to experimental observations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Estimates of Acetonitrile Generation from Scale Melter Testing of LAW Simulants (VSL-19S4573-1, Rev A)

With high nitrate feeds, such as Hanford low activity waste (LAW) feeds, the addition of reductants is necessary in order to control foaming of the molten glass pool in the melter because such foaming can lead to extensive downtime. Sugar, which was used for this purpose at the West Valley Demonstration Project vitrification facility, has been selected as the baseline reductant for the Hanford Waste Treatment and Immobilization Plant (WTP). The amount of sugar required increases with the amount of nitrates present in the feed and decreases with the amount of waste organics present in the feed, which themselves act as reductants. Excessive additions of reductants can be deleterious, leading to over-reduction of the melt and formation of sulfides and molten metals. Consequently, the oxidants and reductants in the feed must be suitably balanced. The basis for achieving this balance was developed by VSL and Atkins for the vitrification of high-sodium-nitrate feeds at Savannah River's M-Area and has been successfully applied to the processing of a wide variety of simulated WTP feeds over many years and was ultimately incorporated into the WTP process control models. The reaction of sugar with nitrates and nitrites in the cold cap controls the redox state of the underlying melt, which prevents foaming, and also significantly decreases the amount of NOx produced. In addition, however, small amount of organics reaction products are formed. Extensive testing at VSL over the past more than 20 years has shown that acetonitrile is the most prevalent such organic species. That testing has also shown that a significant amount of acetonitrile is captured in the liquid scrubbers in the WTP off-gas treatment system and will therefore be present in the secondary liquid effluents. In particular, acetonitrile is prevalent in the submerged bed scrubber (SBS) and wet electrostatic precipitator (WESP) liquid effluents from WTP LAW off-gas treatment. When these liquids are concentrated in the WTP Effluent Management Facility (EMF) evaporator in the direct feed LAW (DFLAW) flow-sheet, VSL testing has shown that the majority of the acetonitrile partitions to the evaporator condensate. Since the evaporator condensate is directed to the Hanford Effluent Treatment Facility (ETF), this creates a potential issue with the ETF waste acceptance criteria. Consequently, there is a need to assess the available test data in order to develop projections of the likely concentrations of acetonitrile in the streams to ETF. The objective of the present report is to provide such an assessment in order to provide input to flow-sheet model projections.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Large-Scale Thermoset Pick and Place Testing and Implementation

Oak Ridge National Laboratory is developing the first commercially available medium to large-scale thermoset additive manufacturing (AM) system with Magnum Venus Products (MVP). This 3D printer is capable of fabricating large-scale thermoset components at room temperature with a build volume of 16’ x 8’ x 42’’. The thermoset extrusion process uses irreversible exothermic chemical reactions to form a cross-linked polymer. Printing thermosets at such large scales with highly customizable materials at room temperature provides huge opportunities for complex and smart tooling applications. Integrating a pick and place actuator into this system will allow for the placement of heating/cooling channels as well as sensors to monitor tooling health and heat distribution. The pneumatically-driven pick and place actuator is integrated into the existing electrical and mechanical design and is controlled using custom M-code commands. The system is comprised mostly of commercially available components, providing easy adoptability by future thermoset systems.

Boulger, Alex↗
DOE OSTI2019

Identification of Rate, Extent, and Mechanisms of Hot Metal Resulfurization with CaO-SiO{sub 2}-Na{sub 2}O Slag Systems

The resulfurization of hot metal has not been comprehensively studied in literature. This study presents an experimental and mathematical modeling study of resulfurization in thermodynamic and kinetic point of view. The rate, extent, and mechanisms of resulfurization were evaluated by analyzing concurrently the physical properties and sulfur-extracting ability of the slag. Experiments were conducted in a chamber furnace in an argon atmosphere, and the hot metal was sampled with pre-defined basis. The experiments were continued until the metal–slag system reached an apparent thermodynamic equilibrium. To obtain a quantitative measure on the effect of system properties on the rate and extent of resulfurization, the results of this study were combined with previous studies handling the sulfide capacities of Na{sub 2}O-SiO{sub 2} and CaO-SiO{sub 2}-Na{sub 2}O slag systems. The sulfide capacities of the slag and corresponding metal–slag sulfur partition ratios were mathematically modeled with data-driven techniques such as multiple linear and non-linear regression and artificial neural networks. Finally, with the help of these, to study the kinetics of resulfurization, a simple mechanistic reaction model was derived. The results suggest that resulfurization of hot metal follows 1st-order kinetics and that the rate and extent can be regulated through the control of the associated thermodynamic driving force and by modifying the physical properties of the slag. The rate-limiting factor was found to be determined by the morphology of the slag phase.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Synthesis of Composition Tunable and Highly Luminescent Cesium Lead Halide Nanowires through Anion-Exchange Reactions

In this paper, we demonstrate the successful synthesis of brightly emitting colloidal cesium lead halide (CsPbX 3 , X = Cl, Br, I) nanowires (NWs) with uniform diameters and tunable compositions. By using highly monodisperse CsPbBr 3 NWs as templates, the NW composition can be independently controlled through anion-exchange reactions. CsPbX 3 alloy NWs with a wide range of alloy compositions can be achieved with well-preserved morphology and crystal structure. The NWs are highly luminescent with photoluminescence quantum yields (PLQY) ranging from 20% to 80%. The bright photoluminescence can be tuned over nearly the entire visible spectrum. The high PLQYs together with charge transport measurements exemplify the efficient alloying of the anionic sublattice in a one-dimensional CsPbX 3 system. Finally, the wires increased functionality in the form of fast photoresponse rates and the low defect density suggest CsPbX 3 NWs as prospective materials for optoelectronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simulated Hydrological Dynamics and Coupled Iron Redox Cycling Impact Methane Production in an Arctic Soil

The fate of organic carbon (C) in permafrost soils is important to the climate system due to the large global stocks of permafrost C. Thawing permafrost can be subject to dynamic hydrology, making redox processes an important factor controlling soil organic matter (SOM) decomposition rates and greenhouse gas production. In iron (Fe)-rich permafrost soils, Fe(III) can serve as a terminal electron acceptor, promoting anaerobic respiration of SOM and increasing pH. Current large-scale models of Arctic C cycling do not include Fe cycling or pH interactions. Here, a geochemical reaction model was developed by coupling Fe redox reactions and C cycling to simulate SOM decomposition, Fe(III) reduction, pH dynamics, and greenhouse gas production in permafrost soils subject to dynamic hydrology. In this study we parameterized the model using measured CO 2 and CH 4 fluxes as well as changes in pH, Fe(II), and dissolved organic C concentrations from oxic and anoxic incubations of permafrost soils from polygonal permafrost sites in northern Alaska, United States. In simulations of repeated oxic-anoxic cycles, Fe(III) reduction during anoxic periods enhanced CO 2 production, while the net effect of Fe(III) reduction on cumulative CH 4 fluxes depended on substrate C availability. With lower substrate availability, Fe(III) reduction decreased total CH 4 production by further limiting available substrate. With higher substrate availability, Fe(III) reduction enhanced CH 4 production by increasing pH. Our results suggest that interactions among Fe-redox reactions, pH and methanogenesis are important factors in predicting CH 4 and CO 2 production as well as SOM decomposition rates in Fe-rich, frequently waterlogged Arctic soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Photon–photon chemical thermodynamics of frequency conversion processes in highly multimode systems

Abstract Frequency generation in highly multimode nonlinear optical systems is inherently a complex process, giving rise to an exceedingly convoluted landscape of evolution dynamics. While predicting and controlling the global conversion efficiencies in such nonlinear environments has long been considered impossible, here, we formally address this challenge even in scenarios involving a very large number of spatial modes. By utilizing fundamental notions from optical statistical mechanics, we develop a universal theoretical framework that effectively treats all frequency components as chemical reactants/products, capable of undergoing optical thermodynamic reactions facilitated by a variety of multi-wave mixing effects. These photon–photon reactions are governed by conservation laws that directly determine the optical temperatures and chemical potentials of the ensued chemical equilibria for each frequency species. In this context, we develop a comprehensive stoichiometric model and formally derive an expression that relates the chemical potentials to the optical stoichiometric coefficients, in a manner akin to atomic/molecular chemical reactions. This advancement unlocks new predictive capabilities that can facilitate the optimization of frequency generation in highly multimode photonic arrangements, surpassing the limitations of conventional schemes that rely exclusively on nonlinear optical dynamics. Notably, we identify a universal regime of Rayleigh–Jeans thermalization where an optical reaction at near-zero optical temperatures can promote the complete and entropically irreversible conversion of light to the fundamental mode at a target frequency. Our theoretical results are corroborated by numerical simulations in settings where second-harmonic generation, sum-frequency generation and four-wave mixing processes can manifest.

Optics↗
DOE OSTI2023

Development and modeling for a small-scale, rapidly heated high explosives initiation time (HEIT) experiment

Most small-scale assessments of explosive sensitivity, including the popular drop-weight impact test, convolute thermal and mechanical phenomena to the extent that it has been extremely challenging to decipher how an explosive ignites and propagates reactions. For instance, an impact generates heat through a range of dissipation mechanisms, which can in turn, depending on the reaction rates of the explosive, lead to chemical decomposition. To deconvolute the various contributions to the sub-shock initiation and propagation of explosive reactions, we describe the development and modeling of the High Explosives Initiation Time (HEIT) test - a new, small-scale, high-throughput experiment designed to rapidly heat milligram quantities of energetic materials confined within small diameter steel needles. Specifically, we have modeled and designed a 250 joule pulsed power system capable of rapidly delivering electrical current to the needles, resulting in rapid heat delivery to the sample. In conclusion, the energy deposition rate into the sample is controlled by different transmission line topologies. Modeling in COMSOL is performed to understand the energy required to heat up the explosive sample.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Metabolic Redox Coupling Controls Methane Production in Permafrost‐Affected Peatlands Through Organic Matter Quality‐Dependent Energy Allocation

ABSTRACT Permafrost thaw represents one of Earth's largest climate feedback risks, potentially releasing vast carbon (C) stores as greenhouse gases (GHG). However, our ability to predict emissions remains limited by poor understanding of how changing organic matter (OM) composition affects microbial carbon processing. We test a metabolism‐centered redox framework, which views microbial processes as coupled oxidative‐reductive reactions, to mechanistically explain how organic matter metabolite quality controls greenhouse gas production in permafrost‐affected peatland ecosystems. Rather than relying solely on geochemical redox measurements, our approach examines how microbes balance electron flow through metabolic pathways. Using active layer peat (9–19 cm) from contrasting environments (bog and fen), we employed multi‐omics approaches, including metabolomics, metagenomics, and metatranscriptomics, to link OM chemistry to microbial function. Our results reveal distinct dissolved organic matter metabolite composition, with fen systems enriched in compounds with higher substrate quality (low molecular weight (MW) sugars with high H:C ratios and low aromaticity) and bog systems dominated by compounds with lower substrate quality (high MW phenols with lower H:C ratios and higher aromaticity). In fen samples, these sugar‐like compounds correlated with higher oxidative metabolism and methanogenesis, supported by increased glycolysis gene expression. Initially, electrons from increased oxidative metabolism were balanced through nitrate and sulfate reduction, but as these electron acceptors were depleted, methanogenesis increased to maintain redox balance. Fen samples showed rapid degradation of both high‐ and low‐substrate‐quality compounds, suggesting sufficient energy for efficient C cycling. Conversely, bog samples exhibited more polyphenolic compounds, lower glycolysis activity, and higher stress‐related gene expression, suggesting energy was diverted towards cell maintenance under acidic conditions rather than C processing. This approach suggests that predicting greenhouse gas emissions requires an understanding of how organic matter quality shapes microbial energy allocation strategies, providing a mechanistic framework for improving emission predictions from permafrost‐affected peatlands and similar ecosystems.

Biodiversity & Conservation↗
DOE OSTI2019

PathParser [SWR-19-54]

PathParser is a python-based computational tool for the thermodynamics and robustness analysis of native and designed metabolic pathways. The following functionalities are provided: 1 Max-min driving force (MDF) optimization. The Gibbs free energy change of the least favorable reaction will be maximized to evaluate thermodynamic feasibility of the entire pathway. 2 Protein cost estimation. The smallest enzyme investment will be assessed by calculating the minimal total enzyme cost supporting a given pathway flux. 3 Robustness analysis. Specifically, an ensemble of models is generated to simulate the system response to enzyme perturbation based on bifurcation theory and a continuation method. Probability of system failure and flux fold change against enzyme perturbation are estimated as well as a flux control index.

Xiong, Wei↗
DOE OSTI2018

Numerical study of a micro flow reactor at engine pressures: Flames with repetitive extinction and ignition and simulations with a reduced chemical model

Combustion in a narrow channel with an imposed temperature gradient is studied numerically at elevated pressure with engine-relevant fuels. Here, the focus is placed on unsteady flames with repetitive extinction and ignition (FREI) to determine the potential of this regime for fuel testing and calibration of reduced chemical mechanisms. First, it is shown that the FREI regime does occur at elevated pressures for sufficiently small tube diameters. The sensitivity of the extinction and ignition temperatures to low-temperature chemistry is found to be significantly enhanced at 25 bar compared to atmospheric conditions. The ignition and extinction temperatures differ by up to 100 K between PRF mixtures with varying octane numbers. Ternary mixtures of iso-octane/n-heptane/toluene and iso-octane/n-heptane/ethanol at similar research and motor octane numbers are also studied. Second, the potential of using data from the micro flow reactor to infer reaction rates is assessed. A reduced chemical mechanism combining a small fuel-dependent submechanism with a detailed fuel-independent submechanism for the core species chemistry is used for that purpose. Only the most sensitive fuel-dependent reactions are inferred. the calibrated reduced model is compared to a detailed model and good agreement in ignition delay times and laminar flame speeds is observed. Finally, this illustrates the potential of a micro flow reactor with a controlled temperature profile to test fuels and infer kinetic data.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

A study of Ni/La-Al 2 O 3 catalysts: A competitive system for CO 2 methanation

Ni/La-γ-Al 2 O 3 samples containing 13.6 wt.% Ni and a variable amount of lanthana (0, 4, 14 and 37 wt.%) were prepared by incipient wetness impregnation, using silica-free γ-Al 2 O 3 support. The materials were characterized, as such or after reaction, with XRD, H 2 -TPR, IR, UV–vis-NIR, XPS and FE-SEM techniques. They were tested as catalysts for CO 2 methanation at atmospheric pressure at GHSV 55000 h –1 . The reaction is under kinetic control at T < 650–673 K, while the product mixture is under thermodynamic control above this temperature range. Lanthanum addition strongly increases the activity of Ni/γ-Al 2 O 3 for CO 2 methanation. Methane selectivity is increased to nearly 100% at low temperatures (T < 650 K). The CO 2 methanation reaction on La-doped Ni/γ-Al 2 O 3 occurs with similar activation energies (80 kJ/mol), and with slightly higher reaction order for hydrogen and lower reaction order for CO 2 than those observed for undoped Ni/γ-Al 2 O 3 . Lanthanum acts as a promoter because of the stronger basicity of the lanthana-alumina support allowing stronger adsorption of CO 2 as surface carbonates that can be act as “reactant reservoirs”. Finally, the Ni/La-alumina catalysts studied here are similarly effective as Ru/alumina catalysts for the selective CO 2 methanation at low temperature and atmospheric pressure.

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

Additives and solvents-induced phase and morphology modification of NaYF{sub 4} for improving up-conversion emission

Both cubic and hexagonal NaYF{sub 4} were synthesized in different reaction systems via hydro/solvo-thermal route. The effects of reaction temperature, solvents, and additives on the synthesis of NaYF{sub 4} have been studied in detail. It has been shown that phase transformation from cubic NaYF{sub 4} to hexagonal NaYF{sub 4} always occurred. The sequence of the ability for inducing the phase transformation was ethanol>H{sub 2}O>acetic acid. It is found that ethanol can not only facilitate the formation of hexagonal NaYF{sub 4} but also control the growth of the crystal. This is quite unusual for the growth of H-NaYF{sub 4}. The up-conversion emission properties of Yb/Er co-doped NaYF{sub 4} have also been investigated and the results demonstrated some general principles for improving up-conversion emission. - Graphical abstract: Additives and solvents can induce the phase transformation of NaYF{sub 4}, typically the use of organic sodium salt and ethanol. - Highlights: • The effect of additives and solvents on the synthesis of NaYF{sub 4} was studied in detail. • Ethanol can facilitate the formation of H-NaYF{sub 4} while acetic acid restrain it. • Three general principles for improving up-conversion emission were summarized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Mitochondrial targeting of bilirubin regulatory enzymes: An adaptive response to oxidative stress

The intracellular level of bilirubin (BR), an endogenous antioxidant that is cytotoxic at high concentrations, is tightly controlled within the optimal therapeutic range. We have recently described a concerted intracellular BR regulation by two microsomal enzymes: heme oxygenase 1 (HMOX1), essential for BR production and cytochrome P450 2A5 (CYP2A5), a BR oxidase. Herein, we describe targeting of these enzymes to hepatic mitochondria during oxidative stress. The kinetics of microsomal and mitochondrial BR oxidation were compared. Treatment of DBA/2J mice with 200 mg pyrazole/kg/day for 3 days increased hepatic intracellular protein carbonyl content and induced nucleo-translocation of Nrf2. HMOX1 and CYP2A5 proteins and activities were elevated in microsomes and mitoplasts but not the UGT1A1, a catalyst of BR glucuronidation. A CYP2A5 antibody inhibited 75% of microsomal BR oxidation. The inhibition was absent in control mitoplasts but elevated to 50% after treatment. An adrenodoxin reductase antibody did not inhibit microsomal BR oxidation but inhibited 50% of mitochondrial BR oxidation. Ascorbic acid inhibited 5% and 22% of the reaction in control and treated microsomes, respectively. In control mitoplasts the inhibition was 100%, which was reduced to 50% after treatment. Bilirubin affinity to mitochondrial and microsomal CYP2A5 enzyme is equally high. Lastly, the treatment neither released cytochrome c into cytoplasm nor dissipated membrane potential, indicating the absence of mitochondrial membrane damage. Collectively, the observations suggest that BR regulatory enzymes are recruited to mitochondria during oxidative stress and BR oxidation by mitochondrial CYP2A5 is supported by mitochondrial mono-oxygenase system. The induced recruitment potentially confers membrane protection. - Highlights: • Pyrazole induces oxidative stress in the mouse liver. • Pyrazole-induced oxidative stress induces mitochondrial targeting of key bilirubin regulatory enzymes, HMOX1, BVR and CYP2A5. • Mitochondrial cytochrome P450 2A5 (CYP2A5) can function as bilirubin oxidase. • Mitochondrial targeting of the key microsomal enzymes is not associated with mitochondrial membrane disruption.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Understanding the depletion of electrons in dusty plasmas at atmospheric pressure

The nucleation and growth of NPs in the gas phase using atmospheric-pressure plasma systems is an important approach to synthesizing novel dimensionally-controlled materials. In this paper, we investigated the effect of the NPs on a typical type of continuous-flow, substrate-free plasma at atmospheric pressure to understand their potential contribution to electron density changes. A tandem plasma system was set up consisting of one plasma reactor that produced carbonaceous NPs from mixtures of argon and hexane, and another identical plasma reactor where the as-grown particles were injected and non-intrusive electrical and optical measurements were performed. The electron densities obtained from conductivity measurements and a plasma fluid model were found to decrease in the presence of NPs. However, control experiments revealed that the main source of the electron depletion was residual vapor or reaction byproducts in the form of molecular species or nanoclusters and not the particles themselves. These results were validated by constant number Monte Carlo simulations which showed that at the experimentally-measured conditions, the NPs were not of sufficiently high enough concentration to reduce the electron density; however, if molecules or clusters are ionizable, they remain in sufficient concentration to deplete electron densities. Our study shows that at atmospheric pressure, because of their typically larger electron density values, particle-producing plasmas are distinct from those at low pressure, and nanoparticle formation does not have the same impact while molecular-scale species may be a more important consideration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗