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Results for “differential kinetics”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Learning heterogeneous reaction kinetics from X-ray movies pixel-by-pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries 1 and electrocatalysts 2. Experimental characterizations of such materials by operando microscopy produce rich image datasets 3–6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation 7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Chueh, William↗
DOE OSTI2021

Data from: Niche differentiation of bacterial versus archaeal soil nitrifiers induced by ammonium inhibition along a management gradient

Soil nitrification, mediated mainly by ammonia oxidizing archaea (AOA) and bacteria (AOB), converts ammonium (NH4+) to nitrite (NO2−) and thence nitrate (NO3−). To better understand ecological differences between AOA and AOB, we investigated the nitrification kinetics of AOA and AOB under eight replicated cropped and unmanaged ecosystems (including two fertilized natural systems) along a long-term management intensity gradient in the upper U.S. Midwest. For five of eight ecosystems, AOB but not AOA exhibited Haldane kinetics (inhibited by high NH4+ additions), especially in perennial and successional systems. In contrast, AOA predominantly exhibited Michaelis-Menten kinetics, suggesting greater resistance to high nitrogen inputs than AOB. These responses suggest the potential for NH4+-induced niche differentiation between AOA and AOB. Additionally, long-term fertilization significantly enhanced maximum nitrification rates (Vmax) in the early successional systems for both AOA and AOB, but not in the deciduous forest systems. This was likely due to pH suppression of nitrification in the acidic forest soils, corroborated by a positive correlation of Vmax with soil pH but not with amoA gene abundance. Results also demonstrated that soil nitrification potentials were relatively stable, as there were no seasonal differences. Overall, results suggest that (1) NH4+ inhibition of AOB but not AOA could be another factor contributing to niche differentiation between AOA and AOB in soil, and (2) nitrification by both AOA and AOB can be significantly promoted by long-term nitrogen inputs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Gravothermal evolution of dark matter halos with differential elastic scattering

Here, we study gravothermal evolution of dark matter halos in the presence of differential self-scattering that has strong velocity and angular dependencies. We design controlled N-body simulations to model Rutherford and Møller scatterings in the halo, and follow its evolution in both core-expansion and -collapse phases. The simulations show the commonly-used transfer cross section underestimates the effects of dark matter self-interactions, but the viscosity cross section provides an accurate approximation for modeling angular-dependent dark matter scattering. We investigate thermodynamic properties of the halo, and find that the three moments of the Boltzmann equation under the fluid approximation are satisfied. We further propose a constant effective cross section, which integrates over the halo's characteristic velocity dispersion with weighting kernels motivated by kinetic theory of heat conduction. The effective cross section provides a good approximation to differential self-scattering for most of the halo evolution. It indicates that we can map astrophysical constraints on a constant self-interacting cross section to an SIDM model with velocity- and angular-dependent scatterings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Niche Differentiation of Bacterial Versus Archaeal Soil Nitrifiers Induced by Ammonium Inhibition Along a Management Gradient

Soil nitrification, mediated mainly by ammonia oxidizing archaea (AOA) and bacteria (AOB), converts ammonium (NH 4 + ) to nitrite (NO 2 – ) and thence nitrate (NO 3 – ). To better understand ecological differences between AOA and AOB, we investigated the nitrification kinetics of AOA and AOB under eight replicated cropped and unmanaged ecosystems (including two fertilized natural systems) along a long-term management intensity gradient in the upper U.S. Midwest. For five of eight ecosystems, AOB but not AOA exhibited Haldane kinetics (inhibited by high NH 4 + additions), especially in perennial and successional systems. In contrast, AOA predominantly exhibited Michaelis-Menten kinetics, suggesting greater resistance to high nitrogen inputs than AOB. These responses suggest the potential for NH 4 + -induced niche differentiation between AOA and AOB. Additionally, long-term fertilization significantly enhanced maximum nitrification rates (V max ) in the early successional systems for both AOA and AOB, but not in the deciduous forest systems. This was likely due to pH suppression of nitrification in the acidic forest soils, corroborated by a positive correlation of V max with soil pH but not with amoA gene abundance. Results also demonstrated that soil nitrification potentials were relatively stable, as there were no seasonal differences. Overall, results suggest that (1) NH 4 + inhibition of AOB but not AOA could be another factor contributing to niche differentiation between AOA and AOB in soil, and (2) nitrification by both AOA and AOB can be significantly promoted by long-term nitrogen inputs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A small heterocyclic molecule as a multistate transistor: a quantum many-body approach

Weakly coupled molecular junctions are an active and important field of research due to their non-linear charge carrier transport. In this study, we investigate transport properties in a weakly coupled molecule, B 2 C 2 N 2 H 6 , using a combined quantum many-body approach and kinetic (master) equations. Various non-linear current–voltage characteristics such as negative differential conductance (NDC), rectifications, and Coulomb staircase, which are the hallmarks of multistate transport devices, have been obtained. We further explore the effect of different perturbations such as gate voltage and perpendicular magnetic field on molecular transport. Depending on the strength of the applied perturbing field, several phenomena such as current switching, and suppression of NDC, have been realized in the device. This study demonstrates small molecules as promising components in next-generation nano-devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Seabed bathymetry and friction modeling in MoorDyn

This paper presents the implementation and verification of a seabed bathymetry feature and seabed friction feature to the open-source, lumped-mass mooring system dynamics modeler, MoorDyn, which is part of the National Renewable Energy Laboratory’s aero-hydro-servo-elastic simulation tool, OpenFAST. Variations in seabed slope, as well as the frictional effects of mooring lines moving along the seabed, will affect the mooring line tensions of a floating platform and the consequent platform response. These new features are especially relevant for modeling mooring systems in deep-water coastal areas where seabed depth can change significantly over an entire mooring footprint. The bathymetry feature models the seabed as a rectangular grid of variable water depths in place of the existing, uniform water depth in MoorDyn. The friction force is primarily represented as a Coulombic friction force, or the product of a kinetic friction coefficient and the seabed contact normal force, with the ability to differentiate between transverse and axial motion of a line node on the seabed in any bathymetry grid. These capabilities were tested by running MoorDyn and OpenFAST simulations over a variety of seabed and environmental conditions; the resulting fairlead tensions, node tensions, and mooring line kinematics were verified against equivalent OrcaFlex simulations. The results match closely, meaning the features are verified, which will increase the overall fidelity of OpenFAST and FAST.Farm simulations.

17 WIND ENERGY↗
DOE OSTI2025

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗
DOE OSTI2024

Measurement of the double-differential cross section of muon-neutrino charged-current interactions with low hadronic energy in the NOvA Near Detector

The NOvA collaboration reports cross-section measurements for $\nu_{\mu}$ charged-current interactions with low hadronic energy (maximum kinetic energy of 250 MeV for protons and 175 MeV for pions) in the NOvA Near Detector. The results are presented as a double-differential cross section as a function of the direct observables of the final-state muon kinematics. Results are also presented as a single-differential cross section as a function of the derived square of the four-momentum transfer, $Q^{2}$, and as a function of the derived neutrino energy. The data correspond to an accumulated 8.09$\times10^{20}$ protons-on-target (POT) in the neutrino mode of the NuMI beam, with a narrow band of neutrino energies peaked at 1.8 GeV. The analysis provides a sample of neutrino-nucleus interactions with an enhanced fraction of quasi-elastic and two-particle-two-hole (2p2h) interactions. This enhancement allows quantitative comparisons with various nuclear models. We find strong disagreement between data and theory-based models in various regions of the muon kinematic phase space, especially in the forward muon direction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Towards a heat- and mass-balanced kinetic model of TATB decomposition

We report TATB (1,3,5-triamino-2,4,6-trinitrobenzene) was thermally degraded by two small-scale analytical methods – simultaneous differential scanning calorimetry and thermogravimetric analysis (SDT) and a hot-stage microscope with Fourier Transform Infrared (FTIR) analysis capabilities. SDT used ramped heating, isothermal soaking, and thermal pretreatment at various conditions. The heat flow and mass loss were monitored during various treatment conditions to derive chemical decomposition kinetics and Arrhenius parameters. FTIR experiments used isothermal heating, and changes were monitored spectroscopically. Solid samples generated at specific conditions were collected from both methods and were analyzed by DMSO extraction followed by chemical speciation by optical and mass spectrometric methods. Characterization provided the following reaction insights: TATB decreases in a sigmoidal pattern in isothermally heated samples. Other soluble products gradually increase in concentration and then abruptly decline in concentration during the second exotherm, such as diamino-dinitro-benzofurazan and amino-nitro-benzodifurazan. FTIR showed gradual changes in the amino and nitro functionality, shifting positions and decreasing intensity for the first 40 min. Then the solid gradually appeared more like an amorphous C with N incorporated, similar to previous studies on thermally degraded TATB-type materials. Extracted residues (DMSO-soluble components removed) examined by FTIR showed an abrupt change in chemical composition between 40- and 45-min isothermal treatment, indicating early forming solids are different than later forming residues. A reliable mass- and energy-balanced global reaction network must include at least two autocatalytic reactions, either in parallel or series, and at least one must have an explicit initiation reaction having a low activation energy.

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

Measurement of 3 Λ H production in Pb–Pb collisions at √ s NN = 5.02 TeV

The first measurement of 3 Λ H and $^{3}_{\overline{Λ}}$$\overline{H}$ differential production with respect to transverse momentum and centrality in Pb–Pb collisions at √ s NN = 5.02 TeV is presented. The 3 Λ H has been reconstructed via its two-charged-body decay channel, i.e., 3 Λ H → 3 He → π - . A Blast-Wave model fit of the p T -differential spectra of all nuclear species measured by the ALICE collaboration suggests that the kinetic freeze-out surface is consistent with that of other nuclei. The ratio between the integrated yields of 3 Λ H and 3 He is compared to predictions from the statistical hadronisation model and the coalescence model, with the latter being favoured by the presented measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Analytical ab initio hessian from a deep learning potential for transition state optimization

Identifying transition states—saddle points on the potential energy surface connecting reactant and product minima—is central to predicting kinetic barriers and understanding chemical reaction mechanisms. In this work, we train a fully differentiable equivariant neural network potential, NewtonNet, on thousands of organic reactions and derive the analytical Hessians. By reducing the computational cost by several orders of magnitude relative to the density functional theory (DFT) ab initio source, we can afford to use the learned Hessians at every step for the saddle point optimizations. We show that the full machine learned (ML) Hessian robustly finds the transition states of 240 unseen organic reactions, even when the quality of the initial guess structures are degraded, while reducing the number of optimization steps to convergence by 2–3× compared to the quasi-Newton DFT and ML methods. All data generation, NewtonNet model, and ML transition state finding methods are available in an automated workflow.

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

A neural master equation framework for multiscale modeling of molecular processes: application to atomic-scale plasma processes

Plasma-surface interactions (PSI) play a crucial role in microelectronics fabrication; however, their multiscale nature and array of complex, often unknown interactions make computational modeling of PSIs extremely difficult. To this end, we propose a general neural master equation (NME) framework that uses master equations to describe the dynamics of a molecular process, wherein neural networks learned from atomistic simulations represent unknown transitions between different system states. By leveraging the physics-based structure of master equations and data-driven state transitions, the NME framework promotes generalizability and physics interpretability, and can bridge disparate length and time scales. The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. The NME-based surface kinetic models obey physical constraints, which are violated in models based on neural ordinary differential equations. The proposed NME framework for multiscale modeling of molecular processes can pave the way for the discovery of new chemistries and materials in atomic-scale plasma processes.

Chemical engineering↗
DOE OSTI2021

Linear embedding of nonlinear dynamical systems and prospects for efficient quantum algorithms

The simulation of large nonlinear dynamical systems, including systems generated by discretization of hyperbolic partial differential equations, can be computationally demanding. Such systems are important in both fluid and kinetic computational plasma physics. This motivates exploring whether a future error-corrected quantum computer could perform these simulations more efficiently than any classical computer. In this work, we describe a method for mapping any finite nonlinear dynamical system to an infinite linear dynamical system (embedding) and detail three specific cases of this method that correspond to previously studied mappings. Then we explore an approach for approximating the resulting infinite linear system with finite linear systems (truncation). Using a number of qubits only logarithmic in the number of variables of the nonlinear system, a quantum computer could simulate truncated systems to approximate output quantities if the nonlinearity is sufficiently weak. Other aspects of the computational efficiency of the three detailed embedding strategies are also discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Modeling Nanoscale Ohmics in Carbon Supports of Fuel Cell Cathodes

Here, reducing platinum (Pt) loading in polymer electrolyte fuel cells (PEFCs) while meeting performace requirements is critical to their widespread deployment. However, significant polarization losses manifest at higher current densities in cathodes with lower Pt content. The morphology of the carbon supports in PEFC cathodes affects the location of Pt deposition into the micropits or onto the surface of the carbon support, translating into different kinetic and transport resistances. In this work, we derive an agglomerate scale model that differentiates the sink terms for Pt on the surface and in the pits of carbon supports. We develop an approach to assess the impact of nanoscale ohmic resistance to Pt in the micropits arising from weakly ionic solution in the carbon support on PEFC performance. Effectiveness factors relating the actual reaction rate to the maximum reaction rate (had all the Pt been exposed) are derived and embedded into a one-dimensional catalyst layer model. Parameters in the catalyst layer model are tuned based on experimental local oxygen transport resistances. Subsequently, we estimate bounds for the micropore resistances based on geometric and physical arguments. Lastly, polarization curves are simulated to assess the effect of the micropore resistance in fully-humidified and oxygen-rich environments.

25 ENERGY STORAGE↗
DOE OSTI2020

Kinetics of TATB and LX-17 Decomposition by Thermal Analysis

The kinetics of TATB decomposition have been investigated by thermal analysis (thermogravimetric analysis, TGA, and differential scanning calorimetry, DSC) at both LLNL and the University of Alabama Birmingham. This report summarizes progress in understanding from those results within the context of identifying the global reaction mechanism, i.e., sequential, autocatalytic, competitive, or some mixture thereof. A particularly important issue is how pressure affects both the reaction rate and enthalpy. The effect of pressure helps identify dominant mechanisms and construct and constrain a global mechanism that will work over a wide range of conditions. This memorandum is simply a snapshot of current progress and not a definitive interpretation. I have written it to organize work of others and my interpretations in a systematic manner with the intention of stimulating further advances in understanding. SDT data comes from Jen Montgomery at LLNL, and high-pressure DSC comes from Victoria Stanford and Sergey Vyazovkin at University of Alabama at Birmingham. Major observations and conclusions, some new and some not, are (1) outgassing below 150 °C prior to decomposition releases adsorbed water vapor, (2) outgassing between 150 and 250 °C may come primarily from intercalated water (3) initial thermal decomposition above 250 °C or so involves dehydration of TATB to create furazans, (4) quickly heating to higher temperatures in open pans with flowing gas leads primarily to TATB evaporation between 270 and 390 °C, (5) using a pinhole crucible at atmospheric pressure largely eliminates TATB sublimation, (6) at typical thermal analysis heat rates, the main stage of decomposition is described by a single mass loss process, and decomposition of residual material is spread over a wide range of thermal severity, (7) at typical thermal analysis heat rates and constant temperatures above 300 °C, heat release occurs in two overlapping peaks, with the first one a little faster than mass loss and the second on a little slower than mass loss, (8) total heat release increases significantly with heating rate and substantially with increased pressure, and (9) isothermal experiments at 340 °C indicate that the first exotherm increases by more with LX-17 than TATB, which suggests a possible chemical role of Kel-F decomposition.

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

Analytical solutions of the Arrhenius-Semenov problem for constant volume burn

Analytical solutions to the Semenov thermal ignition problem for constant volume burn governed by Arrhenius reaction kinetics are derived. Specifically, an approximate analytical solution technique for the Arrhenius-Semenov differential equation is derived for reaction orders n ϵ R> 0 and exact solutions are also constructed for reaction orders n ϵ N : n ≤ 3. The approximation technique relies on expansion of the respective nondominant terms in the differential equation at the lower and upper bounds of the reaction progress variable in order to create a pair of integrable series. The two integrated series are then connected to create a single continuous analytical solution. Excellent agreement is observed between the analytical approximation and solutions obtained numerically. The presented approximation constitutes a simple and robust strategy for solving the Arrhenius-Semenov problem analytically.

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

Matlab implementation of a novel semi-structured kinetic model for methanotroph-photoautotroph cocultures

This paper presents the MatLab implementation details of a novel semi-structured kinetic model for methanotroph-photoautotroph cocultures. This includes the parameterization of the modeling equations, and the initialization of the simulation based on experimental conditions. More importantly, it provides details on how the differential equations governing mass balances in both gas and liquid phases are integrated together to simulate the system dynamics over time. The semi-structured kinetic model for methanotroph-photoautotroph coculture is validated using a wide range of experimental conditions. The model: Accurate predicts both the coculture growth in liquid phase and the gas composition changes in head space over time; Explicitly models the exchange of in situ produced O 2 and CO 2 within the coculture; Considers the self-shading effect on the growth of photoautotroph.

42 ENGINEERING↗
DOE OSTI2026

Simulations of grain growth in tungsten armor materials under ARC plasma edge operation conditions using an integrated plasma-edge/materials model

An integrated model of grain growth deuterium-exposed tungsten polycrystals, consisting of a two-dimensional vertex dynamics model fitted to atomistic data, has been developed to assess the grain growth kinetics of deuterium-exposed polycrystalline tungsten (W). The model tracks the motion of grain boundaries under the effect of driving forces stemming from grain boundary curvature and differential deuterium concentration accumulation. Here, we apply the model to experimentally synthesized tungsten polycrystals under deuterium-saturated conditions relevant to the ARC concept design. The results indicate rapid grain growth kinetics in the near-surface region adjacent to the plasma, where the temperature reaches 1400 K, whereas the microstructure remains stable deeper in the material with the lower temperature of 1000 K. The combined modeling and analysis further reveal that monolithic tungsten produced via conventional fabrication routes is highly susceptible to grain coarsening at temperatures exceeding 1000 K, largely independent of the magnitude of the applied driving force. Moreover, the accumulation of deuterium near grain boundaries has a pronounced inhibitory effect on grain boundary migration. High-angle grain boundaries ( > 50°) contribute more significantly to the overall grain growth process.

36 MATERIALS SCIENCE↗