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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Compositionally Tuning Electron Transfer from Photoexcited Core/Shell Quantum Dots via Cation Exchange

It is critical to find methods to control the thermodynamic driving force for photoexcited charge transfer from quantum dots (QDs) and explore how this affects charge transfer rates, since the efficiency of QD-based photovoltaic and photocatalysis technologies depends on both this rate and the associated energetic losses. In this work, we introduce a single-pot shell growth and Cu-catalyzed cation exchange method to synthesize Cd x Zn 1-x Se/Cd y Zn 1-y S QDs with tunable driving forces for electron transfer. Functionalizing them with two molecular electron acceptors—naphthalenediimide (NDI) and anthraquinone (AQ)—allowed us to probe nearly 1 eV of driving forces. For AQ, at lower driving forces, we find that higher Zn content results in a 130-fold increase of electron transfer rate constants. However, at higher driving forces electron transfer dynamics are unaltered. Here, the data are understood using an Auger-assisted electron transfer model and analyzed with computational work to determine approximate binding geometries of these electron acceptors. Our work provides a method to tune QD reducing power and produces useful metrics for optimizing QD charge transfer systems that maximize rates of electron transfer while minimizing energetic losses.

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

Particle phase-state variability in the North Atlantic free troposphere during summertime is determined by atmospheric transport patterns and sources

Abstract. Free tropospheric aerosol particles have important but poorly constrained climate effects due to transformations of their physicochemical properties during long-range transport. In this study, we investigate the chemical composition and provide an overview of the phase states of individual particles that have undergone long-range transport over the North Atlantic Ocean in June and July 2014, 2015, and 2017 to the Observatory of Mount Pico (OMP) in the Azores. The OMP is an ideal site for studying long-range-transported free tropospheric particles because local emissions have a negligible influence and contributions from the boundary layer are rare. We used the FLEXible PARTicle Lagrangian particle dispersion model (FLEXPART) to determine the origins and transport trajectories of sampled air masses and found that most of them originated from North America and recirculated over the North Atlantic Ocean. The FLEXPART analysis showed that the sampled air masses were highly aged (average plume age >10 d). Size-resolved chemical compositions of individual particles were probed using computer-controlled scanning electron microscopy with an energy-dispersive X-ray spectrometer (CCSEM-EDX) and scanning transmission X-ray microscopy with near-edge X-ray absorption fine structure spectroscopy (STXM-NEXAFS). CCSEM-EDX results showed that the most abundant particle types were carbonaceous (∼ 29.9 % to 82.0 %), sea salt (∼ 0.3 % to 31.6 %), and sea salt with sulfate (∼ 2.4 % to 31.5 %). We used a tilted stage interfaced within an environmental scanning electron microscope (ESEM) to determine the phase states of individual submicron particles. We found that most particles (∼ 47 % to 99 %) were in the liquid state at the time of collection due to inorganic inclusions. Moreover, we also observed substantial fractions of solid and semisolid particles (∼ 0 % to 30 % and ∼ 1 % to 42 %, respectively) during different transport patterns and events, reflecting the particles' phase-state variability for different atmospheric transport events and sources. Combining phase state measurements with FLEXPART CO tracer analysis, we found that wildfire-influenced plumes can result in particles with a wide range of viscosities after long-range transport in the free troposphere. We also used temperature and RH values extracted from the Global Forecast System (GFS) along the FLEXPART-simulated path to predict the phase state of the particles during transport and found that neglecting internal mixing with inorganics would lead to an overestimation of the viscosity of free tropospheric particles. Our findings warrant future investigation aiming at the quantitative assessment of the influence of internal mixing on the phase states of the individual particles. This study also provides insights into the chemical composition and phase state of free tropospheric particles, which can help models to reduce uncertainties about the effects of ambient aerosol particles on climate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multiphysics Time-Integration for Turbulent Combustion at the Exascale

Turbulent reacting flow systems are often modeled with coupled time-dependent partial differential equations (PDEs). Solving such equations can easily tax the world's largest supercomputers. One pragmatic strategy for attacking such problems is to split the PDEs into components that can more easily be solved in isolation. This generic operator-splitting strategy leads to a set of ordinary differential equations (ODEs) that need to be solved as part of an "outer-loop" time-stepping approach. In many combustion applications, the ODEs to be solved can be very stiff, exhibiting timescales that span many orders of magnitude. The SUNDIALS library provides a plethora of robust time integration algorithms for solving these ODEs on exascale-capable computing hardware, yet for many complex applications (such multicomponent fuels or emissions predictions), the chemical models remain too complex to solve using reasonable resources. The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of the simulations. In this talk, I will discuss the use of the SUDIALS library of ODE solvers together with automatic code generation tools to solve complex turbulent reacting flow problems using QSSA models.

chemistry↗
DOE OSTI2025

Water structure and electric fields at the interface of oil droplets

Interfacial water exhibits rich and complex behaviour, playing an important part in chemistry, biology, geology and engineering. However, there is still much debate on the fundamental properties of water at hydrophobic interfaces, such as orientational ordering, the concentration of hydronium and hydroxide, improper hydrogen bonds and the presence of large electric fields. This controversy arises from the challenges in measuring interfacial systems, even with the most advanced experimental techniques and theoretical approaches available. Here we report on an in-solution, interface-selective Raman spectroscopy method using multivariate curve resolution to probe hexadecane-in-water emulsions, aided by a monomer-field theoretical model for Raman spectroscopy. Our results indicate that oil-water emulsion interfaces can exhibit reduced tetrahedral order and weaker hydrogen bonding, along with a substantial population of free hydroxyl groups that experience about 95 cm -1 redshift in their stretching mode compared with planar oil-water interfaces. Given the known electrostatic zeta potential characteristic of oil droplets, we propose the existence of a strong electric field (about 50-90 MV cm -1 ) emanating from the oil phase. This field is inferred indirectly but supported by control experiments and theoretical estimates. These observations are either absent or opposite in the molecular hydrophobic interface formed by small solutes or at planar oil-water interfaces. Instead, water structural disorder and enhanced electric fields emerge as unique features of the mesoscale interface in oil-water emulsions, potentially contributing to the accelerated chemical reactivity observed at hydrophobic-water interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

A two-dimensional model with coupled dynamics, radiative transfer, and photochemistry. 2: Assessment of the response of stratospheric ozone to increased levels of CO2, N2O, CH4, and CFC

The impact of increased levels of carbon dioxide (CO2), chlorofluorocarbons (CFCs), and other trace gases on stratospheric ozone is investigated with an interactive, two-dimensional model of gas phase chemistry, dynamics, and radiation. The scenarios considered are (1) a doubling of the CO2 concentration, (2) increases of CFCs, (3) CFC increases combined with increases of nitrous oxide (N2O) and methane CH4, and (4) the simultaneous increase of CO2, CFCs, N2O, and CH4. The radiative feedback and the effect of temperature and circulation changes are studied for each scenario. For the double CO2 calculations the tropospheric warming was specified. The CO2 doubling leads to a 3.1% increase in the global ozone content. Doubling of the CO2 concentrations would lead to a maximum cooling of about 12 C at 45 km if the ozone concentration were held fixed. The cooling of the stratosphere leads to an ozone increase with an associated increase in solar heating, reducing the maximum temperature drop by about 3 C. The CFC increase from continuous emissions at 1985 rate causes a 4.5% loss of ozone. For the combined perturbations a net loss of 1.3% is calculated. The structure of the perturbations shows a north-south asymmetry. Ozone losses (when expressed in terms of percent changes) are generally larger in the high latitudes of the southern hemisphere as a result of the eddy mixing being smaller than in the northern hemisphere. Increase of chlorine leads to ozone losses above 30 km altitude where the radiative feedback results in a cooler temperature and an ozone recovery of about one quarter of the losses predicted with a noninteractive model. In all the cases, changes in circulation are small. In the chlorine case, circulation changes reduce the calculated column depletion by about one tenth compared to offline calculations.

Schneider, Hans R.↗
DOE OSTI2026

Model Sensitivities of Biomass-Burning Aerosol Chemical Aging, Sulfate Formation, and Cloud Droplet Activation in the Southeastern Atlantic Using CESM and E3SM

Biomass-burning smoke drives large uncertainty in climate projections of the Earth's radiative balance. This is due to the chemical and physical evolution of smoke and its impact on clouds and radiation. Here we focus on the southeastern Atlantic region and its inflow of African biomass-burning smoke during August 2017. We evaluate smoke properties and processes in two coupled earth-system models, the Energy Exascale Earth System Model (E3SM) and Community Earth System Model (CESM). These are compared against in situ aircraft observations from two field campaigns, ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) and CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017). Observations reveal an increase and subsequent decrease in smoke mean diameter, and a steady decrease in the mass ratio of organic aerosol (OA) to black carbon aerosol (BC) (OA:BC) over 4–12 days of aging, neither captured by the base models. Implementation of a photolytic loss scheme for secondary organic aerosol (SOA)—as a proxy for other heterogeneous volatilization chemistry—and a ∼1-day conversion for primary OA to SOA significantly improves the representation of this loss. In the boundary layer, both models show dimethyl sulfide driving a large increase in the sulfate aerosol mass fraction from the free troposphere, which is consistent with observations. Finally, models tend to underpredict cloud droplet number concentration partially due to weak modeled turbulent updraft strength, and model performance improves when the parameterized turbulent updraft strength is increased substantially. These results are expected to provide insights into future model development to reduce climate model uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Kicking the can down the road: understanding the effects of delaying the deployment of stratospheric aerosol injection

Abstract Climate change is a prevalent threat, and it is unlikely that current mitigation efforts will be enough to avoid unwanted impacts. One potential option to reduce climate change impacts is the use of stratospheric aerosol injection (SAI). Even if SAI is ultimately deployed, it might be initiated only after some temperature target is exceeded. The consequences of such a delay are assessed herein. This study compares two cases, with the same target global mean temperature of ∼1.5° C above preindustrial, but start dates of 2035 or a ‘delayed’ start in 2045. We make use of simulations in the Community Earth System Model version 2 with the Whole Atmosphere Coupled Chemistry Model version 6 (CESM2-WACCM6), using SAI under the SSP2-4.5 emissions pathway. We find that delaying the start of deployment (relative to the target temperature) necessitates lower net radiative forcing (−30%) and thus larger sulfur dioxide injection rates (+20%), even after surface temperatures converge, to compensate for the extra energy absorbed by the Earth system. Southern hemisphere ozone is higher from 2035 to 2050 in the delayed start scenario, but converges to the same value later in the century. However, many of the surface climate differences between the 2035 and 2045 start simulations appear to be small during the 10–25 years following the delayed SAI start, although longer simulations would be needed to assess any longer-term impacts in this model. In addition, irreversibilities and tipping points that might be triggered during the period of increased warming may not be adequately represented in the model but could change this conclusion in the real world.

Brody, Ezra (ORCID:000900030008681X)↗
DOE OSTI2021

Reduction of Vanadium(V) by Iron(II)-Bearing Minerals

Fe(II)-bearing minerals (magnetite, siderite, green rust, etc.) are common products of microbial Fe(III) reduction, and they provide a reservoir of reducing capacity in many subsurface environments that may contribute to the reduction of redox active elements such as vanadium; which can exist as V(V), V(IV), and V(III) under conditions typical of near-surface aquatic and terrestrial environments. To better understand the redox behavior of V under ferrugenic/sulfidogenic conditions, we examined the interactions of V(V) (1 mM) in aqueous suspensions containing 50 mM Fe(II) as magnetite, siderite, vivianite, green rust, or mackinawite, using X-ray absorption spectroscopy at the V K-edge to determine the valence state of V. Two additional systems of increased complexity were also examined, containing either 60 mM Fe(II) as biogenic green rust (BioGR) or 40 mM Fe(II) as a mixture of biogenic siderite, mackinawite, and magnetite (BioSMM). Within 48 h, total solution-phase V concentrations decreased to <20 µM in all but the vivianite and the biogenic BiSMM systems; however, >99.5% of V was removed from solution in the BioSMM and vivianite systems within 7 and 20 months, respectively. The most rapid reduction was observed in the mackinawite system, where V(V) was reduced to V(III) within 48 h. Complete reduction of V(V) to V(III) occurred within 4 months in the green rust system, 7 months in the siderite system, and 20 months in the BioGR system. Vanadium(V) was only partially reduced in the magnetite, vivianite, and BioSMM systems, where within 7 months the average V valence state stabilized at 3.7, 3.7, and 3.4, respectively. The reduction of V(V) in soils and sediments has been largely attributed to microbial activity, presumably involving direct enzymatic reduction of V(V); however the reduction of V(V) by Fe(II)-bearing minerals suggests that abiotic or coupled biotic–abiotic processes may also play a critical role in V redox chemistry, and thus need to be considered in modeling the global biogeochemical cycling of V.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Prediction of Calcium Oxalate Stone Risk with Interventions

Introduction Mitigations intended to reduce bone mineral loss in-flight also influence the level of renal stone risk to astronauts. Extending a recent study completed by our group [1], we investigate the likely influence of combined fluid intake and Ca excretion mitigation strategies. Methods A computational biochemistry model representing CaOx crystal precipitation, growth, and agglomeration [2] is combined with a probabilistic analysis to predict the in-flight CaOx renal stone incidence risk ratio (IRR) relative to pre-flight values using 1517 astronaut 24-hour urine chemistries. The output of this simulation is used to assess the combined impact of controlling fluid intake and Ca excretion on maintaining IRR < 1.2 for > 95% of the population, a threshold determined from initial analysis of the model output compared to referent populations [1]. Results and Conclusions Figure 1 illustrates the simulated in-flight astronaut population (n=40000) with CaOx IRR > 1.2. The red lines indicate the known clinical risk boundary of each factor, and the white box is considered the area of high combined clinical risk. The simulation and identified risk threshold conform well to the expected clinical risk boundaries. The results, assuming insensible water losses equal or exceed 0.7 L/day, imply mitigations achieve risks similar to pre-flight levels when either Ca < 150 mg/day or fluid volume intake > 3.2 L/day individually, or combined Ca < 200 and fluid volume intake > 2.5 L/day. We continue to investigate similar compounded effects and look to apprise engineering trades by informing relative risk changes during mission design. References [1] D. A. Goodenow-Messman, S. A. Gokoglu, M. Kassemi, and J. Myers, Jerry G., “Characterization of Astronaut CaOx Renal Stone Incidence Rates to Quantify In-flight and Post-flight Relative Risk,” npj Microgravity, in review, 2021. [2] M. Kassemi and D. Thompson, “Prediction of renal crystalline size distributions in space using a PBE analytic model. 1. Effect of microgravity-induced biochemical alterations,” Am. J. Physiol. Physiol., vol. 311, no. 3, pp. F520–F530, Sep. 2016, doi: 10.1152/ajprenal.00401.2015.

Debra A Goodenow↗
DOE OSTI2023

Tuning the surface reactivity of oxides by peroxide species

The Mars–van Krevelen mechanism is the foundation for oxide-catalyzed oxidation reactions and relies on spatiotemporally separated redox steps. Herein, we demonstrate the tunability of this separation with peroxide species formed by excessively adsorbed oxygen, thereby modifying the catalytic activity and selectivity of the oxide. Using CuO as an example, we show that a surface layer of peroxide species acts as a promotor to significantly enhance CuO reducibility in favor of H 2 oxidation but conversely as an inhibitor to suppress CuO reduction against CO oxidation. Together with atomistic modeling, we identify that this opposite effect of the peroxide on the two oxidation reactions stems from its modification on coordinately unsaturated sites of the oxide surface. By differentiating the chemical functionality between lattice oxygen and peroxide, these results are closely relevant to a wide range of catalytic oxidation reactions using excessively adsorbed oxygen to activate lattice oxygen and tune the activity and selectivity of redox sites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine learning accelerated discrete element modeling of granular flows

Granular flows are widely encountered in many industrial processes and natural phenomena. Discrete Element Modeling (DEM) is a useful tool for understanding and troubleshooting devices, which handle granular materials. However, its applicability is significantly limited by the huge computational cost associated with detecting and computing collisions. In this research, the computation speed of DEM was accelerated by orders of magnitude using a convolutional neural network to replace the direct calculation of particle-particle and particle-boundary collisions. The MFiX software was used to generate the training and testing dataset. Additionally, a GPU accelerated TensorFlow model was used to train the neural network and test the results. The model fluctuations caused by different training steps were reduced with a multi-scale loss function. The accuracy was improved with more frames within one training step. The modeling of a rotating drum and a hopper demonstrated the accuracy and efficiency of this machine learning accelerated DEM in the simulation of granular flows.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Alkylation of monomeric, dimeric, and polymeric lignin models through carbon-hydrogen activation using Ru-catalyzed Murai reaction

In this study, we have assessed directed carbon-hydrogen activation (CHA) for alkylation of monomeric, dimeric, and polymeric lignin models using Murai's catalyst [RuH 2 (CO)(PPh 3 ) 3 ]. Based on related work from our laboratory showing that isolated organosolv lignin bears benzylic directing groups ideal for CHA reactions, this approach could offer new methodology for the valorization of biorefinery lignin. Monomeric and dimeric models bearing a keto group at the benzylic position undergo Ru-catalyzed alkylation in good to excellent yield. Similarly, models bearing a benzylic OH group also undergo alkylation via a tandem oxidation/alkylation process enabled by the Ru catalyst. Polymeric models show low levels of functionalization as a result of the poor solubility of the starting polymer. With unsymmetrical models, functionalization occurs first at the least sterically hindered ortho-site, but a subsequent alkylation, leading to disubstituted products can occur at the more sterically hindered site, leading to hexasubstituted arenes. The reaction shows sensitivity to free phenolic OH groups, which appears to reduce the yield in some reactions, and is also a contributing factor to the low yields observed with polymeric lignin models. Finally, combining CHA methodology with lignin isolation technology able to introduce appropriate directing groups for catalytic functionalization will form the basis for improved conversion of lignin to high value chemical products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Kinetic Modeling Analysis of Ar Addition to Atmospheric Pressure N 2 –H 2 Plasma for Plasma-Assisted Catalytic Synthesis of NH 3

Zero-dimensional kinetic modeling of atmospheric pressure Ar–N 2 –H 2 nonthermal plasma was carried out to gain mechanistic insights into plasma-assisted catalytic synthesis of ammonia. Ar dilution is a common technique for tailoring plasma discharge properties and has been shown to enhance NH 3 formation when added to N 2 –H 2 plasma. The kinetic model was developed for a coaxial dielectric barrier discharge quartz wool-packed bed reactor operating at near room temperature using a kHz-frequency plasma source. With 30% Ar mixed in a 1:1 N 2 –H 2 plasma at 760 Torr, we find that NH 3 production is dominated by Eley–Rideal (E-R) surface reactions, which heavily involve surface NH x species derived from N and H radicals in the gas phase, while the influence of excited N 2 molecules is negligible. This is contrary to the commonly proposed mechanism that excited N 2 molecules created by Penning excitation of N 2 by Ar(4s) and Ar(4p) play a significant role in assisting NH 3 formation. Our model shows that the enhanced NH 3 formation upon Ar dilution is unlikely due to the interactions between Ar and H species, as excited Ar atoms have a weak effect on H radical formation through H 2 dissociation compared to electrons. We find that excited Ar atoms contribute to 28% of the N radical production in the gas phase via N 2 dissociation, while the rest are dominated by electron-impact dissociation. Furthermore, Ar species play a negligible role in the product NH 3 dissociation. N 2 conversion sensitivity analyses were carried out for electron number density (ne) and reduced electric field (E/N), and contributions from Ar to gas-phase N radical production were quantified. Finally, the model can provide guidance on potential reasons for observing enhanced NH 3 formation upon Ar dilution in N 2 –H 2 plasma beyond changes in the discharge characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2015

Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new-generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach.While the new algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarsemodes,while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single-scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10-30% in the refractive index, and 10-40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part study.

aerosol retrieval algorithm↗
DOE OSTI2022

Chemical kinetic interactions and sensitivity analyses for 2-ethylhexyl nitrate-doped PRF91 using a reduced mechanism

A numerical and experimental investigation about the chemical kinetic interactions between 2-ethylhexylnitrate (EHN) and PRF91 was performed in this study. Rapid compression machine experiments were conducted to investigate the effect of EHN on the autoignition reactivity of the fuel, and a reduced chemical kinetic mechanism was developed including an EHN sub-model. Experiments showed that the ignition delay decreases as the fuel is doped with EHN, but the effect of the doping level of EHN on the ignition is highly non-linear. Moreover, experiments showed that the EHN effectiveness is lowest during the transition between the low-temperature regime and the negative temperature coefficient (NTC) regime, and it rapidly increases as the temperature increases. Both detailed and (developed) reduced mechanisms were validated against the experimental results, allowing a more in-depth EHN-fuel chemistry study. Additionally, ignition delay sensitivity and EHN effectiveness sensitivity analyses were performed with the reduced mechanism to identify the reactions that control the interaction between EHN and the fuel. As the result, EHN thermal decomposition is only relevant for very low temperatures. The chemistry of EHN-doped fuel is more sensitive to intermediate temperature reactions than that of straight fuel, especially at lower temperatures, due to the effect of EHN on the NTC behavior of the fuel. Finally, the chemistry of EHN-doped fuel is very sensitive to NO 2 -to-NO reactions, especially at high temperatures, because these reactions transform the NO 2 generated by EHN into NO, which is a very effective fuel reactivity enhancer.

2-ethylhexyl nitrate↗
DOE OSTI2026

Comparison of the Arrhenius parameters between conventional hydrothermal and microwave-assisted synthesis methods for tin oxide nanoparticles

Microwave (MW) irradiation has emerged as a powerful tool for accelerating materials synthesis, yet the origins of its specific influence on reaction kinetics remain elusive. While multiple studies have attributed the observed enhancements in reaction rates under MW heating to reduced activation energies, other accounts have suggested modifications to the Arrhenius pre-exponential factor as the predominant cause. Distinguishing between these parameters in modern applications of MW processing in nanomaterials requires experimental approaches capable of resolving the dynamic and nuanced structural kinetics that govern MW-assisted chemistry. Here, we combine in-situ synchrotron X-ray total scattering with pair distribution function (PDF) analysis to track the structural evolution of SnO 2 nanoparticles synthesized via MW-assisted and conventional hydrothermal conditions. Avrami modeling and Arrhenius analysis suggest that although MW irradiation yields a higher apparent activation energy, the enhanced crystallization is better explained by a pre-exponential factor several orders of magnitude larger than that of conventional heating. These findings suggest that the MW field induces a higher frequency of successful molecular rearrangements rather than lowering the intrinsic activation barrier. The results contribute further insights clarifying the role of the applied MW field for materials design where MW-specific effects can be deliberately harnessed. Furthermore, this work presents a framework promoting the utility of in-situ PDF characterization coupled with kinetic analysis for developing more sophisticated descriptions of nanoscale transformations for MW-driven reaction kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimizing Direct Air Capture Solvents to Minimize Energy Consumption of CO 2 Release in a Carbonate Electrolyzer

Addressing climate change by carbon management is critical to achieving the goal of net zero carbon emissions by 2050. In this work, we examined the electrochemically-driven recovery of CO 2 during alkaline solvent regeneration for solvent-based direct air capture. A mathematical model was developed by incorporating carbonate chemistry with water electrolysis to predict the energy consumption per unit of CO 2 released. The predicted results were consistent with the experimental data, in which the experimental work was achieved by characterizing alkalinity and carbon loading values of solvent collected from a flow carbonate electrolyzer. Through this study, we learned that minimizing the energy expended on CO 2 release can be achieved by using an anolyte with a lower alkalinity, increasing the electric charge input to the electrolyzer, and reducing the ohmic resistance of the electrolyzer. Furthermore, using a supporting electrolyte, e.g., Na 2 SO 4 in the present work, effectively compensates for the higher ohmic resistance from using an anolyte with a lower alkalinity.

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

Toward Higher-order Accuracy in Self-gravitating Hydrodynamics

High-order algorithms have emerged in numerical astrophysics as a promising avenue to reduce truncation error (proportional to a power of the linear resolution Δ x ) with only a moderate increase to computational expense. Significant effort has been placed in the development of finite-volume algorithms for (magneto)hydrodynamics; however, state-of-the-art astrophysical simulations tightly couple a plenitude of physics, additionally including gravity, photon transport, cosmic-ray transport, chemistry, and/or diffusion, to name a few. Algorithms frequently operator-split this additional physics (often a first-order error in time) and/or adopt a model wherein their evaluation is limited to second-order accuracy in space. In this work, we present a fourth-order-accurate finite-volume scheme for self-gravitating hydrodynamics on a uniform Cartesian grid. The method supplies source terms for the gravitational acceleration ( ρ g ) and gravitational energy release ( ρ v · g ) associated with fourth-order-accurate solutions to the Poisson equation. Our scheme (1) guarantees the conservation of total linear momentum while (2) decreasing (in proportion to Δ x 4 ) the effects of spurious heating and/or cooling associated with truncation error in the gravity. We demonstrate expected convergence rates for the algorithm by measuring errors in test problems evolving self-gravity modified linear waves and 3D polytropic equilibria. We test robustness of the algorithm by integrating an induced “inside-out” adiabatic collapse. We also discuss a method to smoothly downgrade the solution to second-order spatial accuracy to avoid spurious overshoots near steep density and/or pressure gradients.

79 ASTRONOMY AND ASTROPHYSICS↗