SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
CO 2 BOLs are promising CCS solvents, whose mass transfer rates improve upon cooling. We show this unintuitive behavior is due to slow transport of reaction products from the gas–liquid interface, caused by shifts in reaction equilibria.
It has been recently suggested that hydroxide ions can be formed in the electrolyte of molten carbonate fuel cells when water vapor is present. The hydroxide can replace carbonate in transporting electrons across the electrolyte, thereby reducing the CO 2 separation efficiency of the fuel cell although still producing electricity. In this work, we obtain the equilibrium concentration of hydroxide in five molten alkali carbonate salts from molecular simulations. The results reveal that there can be a substantial amount of hydroxide in the electrolyte at low partial pressures of CO 2 . In addition, we find that the equilibrium concentration of molecular water dissolved in the electrolyte is over two orders of magnitude higher than that of CO 2 . Increasing the size and polarizability (or in other words reducing the “hardness”) of the cations present in the electrolyte can reduce the hydroxide fraction, but at the cost of lowering ionic conductivity.
Not Available
Partial molar volumes, energies, and enthalpies can be computed from NpT-Gibbs ensemble simulations through a post-processing procedure that leverages fluctuations in composition, total volume, and total energy of a simulation box. By recording the instantaneous box volumes V and instantaneous number of molecules N i of each of n species for M frames, a large M ×n matrix N is constructed, as well as the M × 1 vector V. The 1 × n vector of partial molar volumes V¯ may then be solved using N • V¯=V. A similar construction permits calculation of partial molar energies using M instantaneous measurements of the total energy of the simulation box, and N • U¯=U. Partial molar enthalpies may be derived from U¯, V¯, and pressure p. These properties may be used to calculate enthalpy and entropy of transfer (absorption, extraction, and adsorption) for species in complex mixtures. The method is demonstrated on three systems in the NpT-Gibbs ensemble: a highly compressible natural gas condensate of methane, n-butane, and n-decane, the liquid-phase adsorption of 1,5-pentanediol and ethanol onto the MFI zeolite, and a relatively incompressible mixture of ethanol, n-dodecane, and water at liquid-liquid equilibrium. Property predictions are compared to those from numerical differentiation of simulation data sequentially changing the composition and from equations of state. Here, the method can also be extended to reaction equilibria in a closed system and is applied to a reactive first-principles Monte Carlo simulation of compressed nitrogen/oxygen.
In modern steelmaking, the decarburization of hot metal is converted into steel primarily in converter processes, such as the basic oxygen furnace. The objective of this work was to develop a new mathematical model for top blown steel converter, which accounts for the complex reaction equilibria in the impact zone, also known as the hot spot, as well as the associated mass and heat transport. An in-house computer code of the model has been developed in Matlab. The main assumption of the model is that all reactions take place in a specified reaction zone. The mass transfer between the reaction volume, bulk slag, and metal determine the reaction rates for the species. The thermodynamic equilibrium is calculated using the partitioning of Gibbs energy (PGE) method. The activity model for the liquid metal is the unified interaction parameter model and for the liquid slag the modified quasichemical model (MQM). The MQM was validated by calculating iso-activity lines for the liquid slag components. The PGE method together with the MQM was validated by calculating liquidus lines for solid components. The results were compared with measurements from literature. The full chemical reaction model was validated by comparing the metal and slag compositions to measurements from industrial scale converter. The predictions were found to be in good agreement with the measured values. Furthermore, the accuracy of the model was found to compare favorably with the models proposed in the literature. The real-time capability of the proposed model was confirmed in test calculations.
An important scientific debate focuses on the possibility of abiotic synthesis of hydrocarbons during oceanic crust-seawater interactions. While on-site measurements near hydrothermal vents support this possibility, laboratory studies have provided data that are in some cases contradictory. At conditions relevant for sub-surface environments it has been shown that classic thermodynamics favour the production of CO 2 from CH 4 , while abiotic methane synthesis would require the opposite. However, confinement effects are known to alter reaction equilibria. This report shows that indeed thermodynamic equilibrium can be shifted towards methane production, suggesting that thermal hydrocarbon synthesis near hydrothermal vents and deeper in the magma-hydrothermal system is possible. We report reactive ensemble Monte Carlo simulations for the CO 2 methanation reaction. We compare the predicted equilibrium composition in the bulk gaseous phase to that expected in the presence of confinement. In the bulk phase we obtain excellent agreement with classic thermodynamic expectations. When the reactants can exchange between bulk and a confined phase our results show strong dependency of the reaction equilibrium conversions, X CO 2 , on nanopore size, nanopore chemistry, and nanopore morphology. Some physical conditions that could shift significantly the equilibrium composition of the reactive system with respect to bulk observations are discussed.
Hydrogen production from serpentinization of ultramafic rocks represents a promising natural pathway for generating carbon-free energy, yet its kinetics and controlling factors remain incompletely understood. A key challenge in advancing serpentinization research lies in the heterogeneity of porosity and permeability in rocks, which leads to nonuniform fluid velocity fields, as well as uncertainties in estimating reactive surface area and identifying appropriate mineral reaction equilibria. Additional complexities arise from the role of dissolved SiO 2 , Fe 2+ /Fe 3+ partitioning, and the limited effect of pH variations within the strongly alkaline regime on hydrogen yields. These challenges hinder straightforward extrapolation from laboratory tests to practical applications of hydrogen production from natural rocks. Here, in this work, we address these questions using a simulation-based reactive transport modeling framework calibrated against controlled laboratory experiments reported elsewhere. The model couples geochemical kinetics, multiphase flow, and mineralogical feedbacks, enabling systematic evaluation of how surface area, dissolved silica concentration, Fe redox state, temperature, and pressure govern serpentinization and H2 generation. We find that surface area exerts the strongest control on reaction rates and hydrogen yields, while Fe 2+ /Fe 3+ ratios act as secondary modulators. Elevated dissolved silica concentrations suppress hydrogen production but accelerate serpentine precipitation, whereas increasing pH beyond 12 within the strongly alkaline regime produces only marginal gains. Finally, we demonstrate that integrating targeted experiments with calibrated simulations offers a powerful and efficient approach for predicting hydrogen yields and assessing parameter trade-offs in industrial-scale applications. This integration can substantially reduce the experimental burden while improving predictive capability, thereby enhancing both the mechanistic understanding and the practical feasibility of hydrogen production from serpentinization.
Purifying sour natural gas streams containing hydrogen sulfide and carbon dioxide has been a long-standing environmental and economic challenge. In the presence of cation-exchanged zeolites, these two acid gases can react to form carbonyl sulfide and water (H 2 S+CO 2 H 2 O+COS), but this reaction is rarely accounted for. In this work, we carry out reactive first-principles Monte Carlo (RxFPMC) simulations for mixtures of H 2 S and CO 2 in all-silica and Na-exchanged forms of zeolite beta to understand the governing principles driving the enhanced conversion. The RxFPMC simulations show that the presence of Na + cations can change the equilibrium constant by several orders of magnitude compared to the gas phase or in all-silica beta. The shift in the reaction equilibrium is caused by very strong interactions of H 2 O with Na + that reduce the reaction enthalpy by about 20 kJmol -1 . The simulations also demonstrate that the siting of Al atoms in the framework plays an important role. Lastly, the RxFPMC method presented here is applicable to any chemical conversion in any confined environment, where strong interactions of guest molecules with the host framework and high activation energies limit the use of other computational approaches to study reaction equilibria.
Macromolecular crowding is known to modulate chemical equilibria, reaction rates, and molecular binding events, both in aqueous solutions and at lipid bilayer membranes, natural barriers that enclose the crowded environments of cells and their subcellular compartments. Previous studies on the effects of macromolecular crowding in aqueous compartments on conduction through membranes have focused on single-channel ionic conduction through previously formed pores at thermodynamic equilibrium. Furthermore, the effects of macromolecular crowding on the mechanism of pore formation itself were studied using the droplet interface bilayer (DIB) technique with the voltage-dependent pore-forming peptide alamethicin (alm). Macromolecular crowding was varied using 8 kDa molecular weight polyethylene glycol (PEG8k) or 500 kDa dextran (DEX500k) in two aqueous droplets on both sides of the bilayer membrane. In general, voltage thresholds for pore formation in the presence of crowders in the droplets decreased compared to their values in the absence of crowders, due to excluded volume effects, water binding by PEG, and changes in the ordering of water molecules and hydrogen-bonding interactions involving the polar lipid headgroups. In addition, asymmetric crowder loading (e.g., PEG8k–DEX500k on either side of the membrane) resulted in transmembrane osmotic pressure gradients that either enhanced or degraded the ionic conduction through the pores.
In the dynamic environment of multi-component reactive molten salts, speciation unfolds as a complex process, involving multiple competing reaction pathways that are likely to face free energy barriers before reaching the reaction equilibria.
Phase reactions occurring during a low temperature selenization of thin In/Cu-multilayer stacks were investigated by ex-situ x-ray diffraction (XRD) and energy dispersive x-ray spectroscopy (EDS). Therefore, dc-sputtered In/Cu-multilayers onto molybdenum coated soda lime glass were selenized in a high vacuum system at temperatures between 260 and 340 °C with different dwell times and selenium supply. The combination of the results of the phase analysis by XRD and the measurements of the in-depth elemental distribution by EDS allowed a conclusion on the occurring reactions within the layer depth. We found two CuInSe{sub 2} formation processes depending on the applied temperature. Already, at a heater temperature of 260 °C, the CuInSe{sub 2} formation can occur by the reaction of Cu{sub 2−x}Se with In{sub 4}Se{sub 3} and Se. At 340 °C, CuInSe{sub 2} is formed by the reaction of Cu{sub 2−x}Se with InSe and Se. Because both reactions need additional selenium, the selenium supply during the selenization can shift the reaction equilibria either to the metal binaries side or to the CuInSe{sub 2} side. Interestingly, a lower selenium supply shifts the equilibrium to the CuInSe{sub 2} side, because the amount of selenium incorporated into the metallic layer is higher for a lower selenium supply. Most likely, a larger number of grain boundaries are the reason for the stronger selenium incorporation. The results of the phase formation studies were used to design a two stage selenization process to get a defined structure of an indium selenide- and a copper selenide-layer at low temperatures as the origin for a controlled interdiffusion to form the CuInSe{sub 2}-absorber-layer at higher temperatures. The approach delivers a CuInSe{sub 2} absorber which reach total area efficiencies of 11.8% (13.0% active area) in a CuInSe{sub 2}-thin-film solar cell. A finished formation of CuInSe{sub 2} at low temperature was not observed in our experiments but is probably possible for longer dwell times.
Seeds provide the basis for many food, feed, and fuel products. Continued increases in seed yield, composition, and quality require an improved understanding of how the developing seed converts carbon and nitrogen supplies into storage. Current knowledge of this process is often based on the premise that transcriptional regulation directly translates via enzyme concentration into flux. In an attempt to highlight metabolic control, we explore genotypic differences in carbon partitioning for in vitro cultured developing embryos of oilseed rape (Brassica napus). We determined biomass composition as well as 79 net fluxes, the levels of 77 metabolites, and 26 enzyme activities with specific focus on central metabolism in nine selected germplasm accessions. We observed a tradeoff between the biomass component fractions of lipid and starch. With increasing lipid content over the spectrum of genotypes, plastidic fatty acid synthesis and glycolytic flux increased concomitantly, while glycolytic intermediates decreased. The lipid/starch tradeoff was not reflected at the proteome level, pointing to the significance of (posttranslational) metabolic control. Enzyme activity/flux and metabolite/flux correlations suggest that plastidic pyruvate kinase exerts flux control and that the lipid/starch tradeoff is most likely mediated by allosteric feedback regulation of phosphofructokinase and ADP-glucose pyrophosphorylase. Also, quantitative data were used to calculate in vivo mass action ratios, reaction equilibria, and metabolite turnover times. Compounds like cyclic 3',5'-AMP and sucrose-6-phosphate were identified to potentially be involved in so far unknown mechanisms of metabolic control. This study provides a rich source of quantitative data for those studying central metabolism..
Many powerful and variable gamma-ray sources, including pulsar wind nebulae, active galactic nuclei and gamma-ray bursts, seem capable of accelerating particles to gamma-ray emitting energies efficiently over very short timescales. These are likely due to the rapid dissipation of electromagnetic energy in a highly magnetized, relativistic plasma. In order to understand the generic features of such processes, we have investigated simple models based on the relaxation of unstable force-free magnetostatic equilibria. In this work, we make the connection between the corresponding plasma dynamics and the expected radiation signal, using 2D particle-in-cell simulations that self-consistently include synchrotron radiation reactions. We focus on the lowest order unstable force-free equilibrium in a 2D periodic box. We find that rapid variability, with modest apparent radiation efficiency as perceived by a fixed observer, can be produced during the evolution of the instability. The “flares” are accompanied by an increased polarization degree in the high energy band, with rapid variation in the polarization angle. Furthermore, the separation between the acceleration sites and the synchrotron radiation sites for the highest energy particles facilitates acceleration beyond the synchrotron radiation reaction limit. We also discuss the dynamical consequences of the radiation reaction, and some astrophysical applications of this model. Our current simulations with numerically tractable parameters are not yet able to reproduce the most dramatic gamma-ray flares, e.g., from the Crab Nebula. Higher magnetization studies are promising and will be carried out in the future.
This article addresses the modeling of non-equilibrium phenomena in inductively coupled plasma discharges. In the proposed computational model, the electromagnetic induction equation is solved together with the set of Navier-Stokes equations in order to compute the electromagnetic and flow fields, accounting for their mutual interaction. Semi-classical statistical thermodynamics is used to determine the plasma thermodynamic properties, while transport properties are obtained from kinetic principles, with the method of Chapman and Enskog. Particle ambipolar diffusive fluxes are found by solving the Stefan-Maxwell equations with a simple iterative method. Two physico-mathematical formulations are used to model the chemical reaction processes: (1) A Local Thermodynamics Equilibrium (LTE) formulation and (2) a thermo-chemical non-equilibrium (TCNEQ) formulation. In the TCNEQ model, thermal non-equilibrium between the translational energy mode of the gas and the vibrational energy mode of individual molecules is accounted for. The electronic states of the chemical species are assumed in equilibrium with the vibrational temperature, whereas the rotational energy mode is assumed to be equilibrated with translation. Three different physical models are used to account for the coupling of chemistry and energy transfer processes. Numerical simulations obtained with the LTE and TCNEQ formulations are used to characterize the extent of non-equilibrium of the flow inside the Plasmatron facility at the von Karman Institute. Each model was tested using different kinetic mechanisms to assess the sensitivity of the results to variations in the reaction parameters. A comparison of temperatures and composition profiles at the outlet of the torch demonstrates that the flow is in non-equilibrium for operating conditions characterized by pressures below 30 000 Pa, frequency 0.37 MHz, input power 80 kW, and mass flow 8 g/s.
Water chemistry plays a critical role in the design and operation of water treatment processes. Detailed chemistry modeling tools use a combination of advanced thermodynamic models and extensive databases to predict phase equilibria and reaction phenomena. The complexity and formulation of these models preclude their direct integration in equation-oriented modeling platforms, making it difficult to use their capabilities for rigorous water treatment process optimization. Neural networks (NN) can provide a pathway for integrating the predictive capability of chemistry software into equation-oriented models and enable optimization of complex water treatment processes across a broad range of conditions and process designs. Herein, we assess how NN architecture and training data impact their accuracy and use in equation-oriented water treatment models. We generate training data using PhreeqC software and determine how data generation and sample size impact the accuracy of trained NNs. The effect of NN architecture on optimization is evaluated by optimizing hypothetical black-box desalination processes using a range of feed compositions from USGS brackish water data set, tracking the number of successful optimizations, and testing the impact of initial guess on the final solution. Our results clearly demonstrate that data generation and architecture impact NN accuracy and viability for use in equation-oriented optimization problems.
This Review brings a new perspective to the study of chemical reactions in compressed fluid media. We begin by reviewing the substantial insight gained from more than 50 years of experimental studies on organic reactions in solution under pressure. These led to a proper estimation of the critical roles of volume of activation (Δ ≠ V) and reaction volume (ΔV) in understanding pressure effect on rates and equilibria of organic reactions. A recently developed computational method, the XP-PCM (extreme pressure polarizable continuum model) method, capable of carrying out quantum mechanical calculations of reaction pathways of molecules under pressure, is introduced. A case study of the Diels–Alder cycloaddition of cyclopentadiene with ethylene serves, in pedagogical detail, to describe the methodology. We then apply the XP-PCM method to a selection of other pericyclic reactions, including the parent Diels–Alder cycloaddition of butadiene with ethylene, electrocyclic ring-opening of cyclobutene, electrocyclic ring-closing of Z-hexatriene, the [1,5]-H shift in Z-pentadiene, and the Cope rearrangement. These serve as examples of some of the most common combinations of Δ ≠ V and ΔV. Interesting phenomena such as a shift in a transition state along a reaction coordinate, a switch of rate-determining step, and the possible turning of a transition state into a stable minimum are revealed by the calculations. A reaction volume profile, the change in the volume of the reacting molecules as the reaction proceeds, emerges as being useful.
Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.
The low weighted carrier mobility has long been considered to be the key challenge for improvement of thermoelectric (TE) performance in BiTeI. The Rashba-effect-induced two-dimensional density of states in this bulk semiconductor is beneficial for thermopower enhancement, which makes it a prospective compound for TE applications. In this report, we show that intercalation of minor Cu-dopants can substantially alter the equilibria of defect reactions, selectively mediate the donor-acceptor compensation, and tune the defect concentration in the carrier conductive network. Consequently, the potential fluctuations responsible for electron scattering are reduced and the carrier mobility in BiTeI can be enhanced by a factor of two to three between 10 K and 300 K. The carrier concentration can also be optimized by tuning the Te/I composition ratio, leading to higher thermopower in this Rashba system. Cu-intercalation in BiTeI gives rise to higher power factor, slightly lower lattice thermal conductivity, and consequently improved figure of merit. Compared with pristine BiTe 0.98 I 1.02 , the TE performance in Cu 0.05 BiTeI reveals a 150% and 20% enhancement at 300 and 520 K, respectively. Ultimately, these results demonstrate that defect equilibria mediated by selective doping in complex TE and energy materials could be an effective approach to carrier mobility and performance optimization.