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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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Computational methods based on density functional theory for reactions and processes involving electronic spin (Final Technical Report)
This award supports one post-doctoral researcher for 1.5 years. Publications that acknowledge this grant: Refs. 1–14. Refs. 3,10,12 assess current methodology for the evaluation of magnetic exchange couplings in transition metal complexes. In particular, Ref. 10 validates the use of an approximate (non-iterative) Green’s function approach for the calculation of magnetic exchange couplings and will be the foundation for Thrust 2 in this proposal. Refs. 3 and 12 focus on widely used density functional approaches based on the standard energy differences methodology for the particular case of oxo-bridged Fe(III) complexes. Refs. 2,4–7,11 apply current methodologies to problems of practical interest in molecular magnetism. Ref. 13 presents a methodology to explicitly simulate the dynamics of open quantum systems within density functional theory (DFT) calculations based on the Liouville-von Neumann equation of motion for quantum systems driven out-of-equilibrium. Ref. 8 uses non-collinear spin DFT to explain the mechanical behavior of magnetic mono-atomic Pt wires produced in break-junction experiments in the presence of a magnetic field.
Methods for operating solar-thermochemical processes
Methods for controlling or operating solar thermochemical reactions process that maximize the two-step thermochemical energy cycle efficiency by a combination of pressure and temperature swing are disclosed.
Elucidating the Link Between Alkali Metal Ions and Reaction-Transport Mechanisms in Cathode Electrodes for Alkali-ion Batteries
Our long-term goal is to improve the reliability of electrode materials and their ability to transport and store various metal ions for electrochemical energy storage applications. The main objective of this work was to investigate the intrinsic relationship between the role of alkali metal ions and electrochemically driven mechanical stability and kinetic properties of battery materials. The overall question was “What is the role of alkali metal ions on the electrochemical and mechanical behavior of cathode electrodes? Our guiding hypothesis was that intercalation of larger alkali metal ions (Na and K) inevitably alters the coupled transport-reaction processes during battery operation in organic electrolytes, leading to more intensive chemo-mechanical instabilities in cathode electrodes, resulting in rapid capacity fade. To validate the hypothesis, we experimentally characterized the reaction-transport processes and governing forces driving the instability of electrode materials in different alkali metal-ion environments. The project had three main tasks. The first one was to investigate intercalation-induced strains and associated stress generation, and their impact on structural deformations in composite cathode electrodes. The second task focused on identifying potential-dependent dynamic changes in the electrode-electrolyte interface in alkali metal ion batteries. The last task was focused on determining how larger alkali metal ions with slower diffusivity affect the transport-mechanics coupling at faster scan rates, compared to smaller ions with faster diffusivity in electrodes. We shortly provided the outcome of each task in the accomplishment section. This project produced 10 peer-reviewed publications (9 research papers and one review manuscript) and supported two Ph.D. students, who graduated from Oklahoma State University.
Insights into the Enhanced Cycle and Rate Performances of the F-Substituted P2-Type Oxide Cathodes f
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PUMA:POWDER UTILIZATION MODELING APPLICATION
SF-25-084 PUMA a high performance modeling framework to simulate powder processing. It provides a scalable tool for manufacturers to simulate powder pre- and post-processing. The tool can predict the distortion, residual stress, and (for reactive processes) reaction completion fraction of complex parts after curing/debinding, sintering, and infiltration processes. These predictions are key metrics industry uses to optimize these processes to produce dense, defect-free, stable components.
Development of a microwave-assisted downdraft moving-bed gasifier for continuous processing of lignite and biomass chars
This research illustrates a microwave-assisted downdraft moving-bed gasifier for the first time. Such design enables continuous solid gasification process. An adjustable auger was applied to control the solid removal rate and the gas-solid interaction time. Both lignite and biomass chars were investigated to determine the capability of the current system for low-tar feedstocks with different densities. Here, the presented reactor design was able to operate continuously for 3 hours and 20 minutes under 700 ℃ and atmospheric pressure, with air as the gasifying agent. For yellow pine char, the processing rate could reach 34.1 grams per hour with decent syngas production. The downdraft moving-bed design shows better cold gas and syngas production efficiencies compared to the common fixed-bed design, due to controllable residence time and more homogeneous microwave heating. The limitations of the current design and the direction of novel microwave-assisted chemical reactor design were discussed. This novel reactor design provides a way to improve the efficiency of microwave-assisted gasification process and shows its potential to be incorporated into other established chemical reaction processes as a modular add-on.
Thermal and Catalytic Decomposition of 2-Hydroxyethylhydrazine and 2-Hydroxyethylhydrazinium Nitrate Ionic Liquid
To develop chemical kinetics models for the combustion of ionic liquid-based monopropellants, identification of the elementary steps in the thermal and catalytic decomposition of components such as 2-hydroxyethylhydrazinium nitrate (HEHN) is needed but is currently not well understood. The first decomposition step in protic ionic liquids such as HEHN is typically the proton transfer from the cation to the anion, resulting in the formation of 2-hydroxyethylhydrazine (HEH) and HNO 3 . In the first part of this investigation, the high-temperature thermal decomposition of HEH is probed with flash pyrolysis (<1400 K) and vacuum ultraviolet (10.45 eV) photoionization time-of-flight mass spectrometry (VUV-PI-TOFMS). Next, the investigation into the thermal and catalytic decomposition of HEHN includes two mass spectrometric techniques: (1) tunable VUV-PI-TOFMS (7.4-15 eV) and (2) ambient ionization mass spectrometry utilizing both plasma and laser ionization techniques whereby HEHN is introduced onto a heated inert or iridium catalytic surface and the products are probed. The products can be identified by their masses, their ionization energies, and their collision-induced fragmentation patterns. Further, formation of product species indicates that catalytic surface recombination is an important reaction process in the decomposition mechanism of HEHN. The products and their possible elementary reaction mechanisms are discussed.
(Photo)Electrocatalytic CO 2 Reduction at the Defective Anatase TiO 2 (101) Surface
Excessive carbon dioxide (CO 2 ) emissions by combustion of fossil fuels are linked to global warming and rapid climate change. One promising route to lowering the concentration of CO 2 in the atmosphere is to reduce it to useful small molecules via photoelectrocatalytic hydrogenation, which would enable solar energy storage with a zero-carbon emission cycle and perform a more efficient separation of the photogenerated electron and hole pair than pure photocatalysis. Indeed, photoelectrocatalytic CO 2 reduction has been an intense focus of research. Using the density functional theory (DFT), we studied the CO 2 reduction reaction on the defective anatase TiO 2 (101) surface, at both the solvent/catalyst and the electrolyte/catalyst interfaces. The analysis of the electronic structure of the surface shows a contrast between the solvent/catalyst and the electrolyte/catalyst interfaces, which results in the two corresponding catalytic cycles being distinct. Furthermore, our study explains at the electronic and mechanistic levels why methanol is the main product in the presence of the electrolyte and why the overpotential is not only controlled by the reaction process but also by the diffusion process.
Explicit physics-informed neural networks for nonlinear closure: The case of transport in tissues
In upscaling methods, closures for nonlinear problems present a well-known challenge. While a number of theoretical methods have been proposed for handling such closures, nonlinearities still remain a significant obstacle for many problems. In this work, we use a combination of formal upscaling and data-driven machine learning for explicitly closing a nonlinear transport and reaction process in multiscale tissues. The classical effectiveness factor model is used to formulate the macroscale reaction kinetics. We train a multilayer perceptron network using training data generated by direct numerical simulations over microscale examples. Once trained, the network is used in an algorithm for numerically solving the upscaled (coarse-grained) differential equation describing mass transport and reaction in two example tissues. The network is described as being explicit in the sense that the network is trained using macroscale concentrations and gradients of concentration as components of the feature space rather than incorporating them as part of a constraint in the optimization process. Network training and solutions to the macroscale transport equations were computed for two different tissues. The two tissue types (brain and liver) exhibit markedly different geometrical complexity and spatial scale (cell size and sample size). The upscaled solutions for the average concentration are compared with numerical solutions derived from the microscale concentration fields by a posteriori averaging. There are three outcomes of this work of particular note. 1) Our overall approach results in an upscaled nonlinear PDE. The PDE is closed using a neural network, and our approach results in the definition of the classical effectiveness factor for effecting closure. 2) We identify particular source terms for the closure problem that are important for representing the structure of the closure. These source terms involve macroscale concentrations and their gradients. We adopt these source terms to use as explicit features in the learning algorithm. We find the trained networks that include the macroscale source terms generate models that are able to predict the correction factor with increased fidelity over those that do not. 3) We find that the trained network exhibits good generalizability, and it is able to predict the effectiveness factor with high fidelity for realistically-structured tissues despite the significantly different scale and geometrical complexity of the two example tissue types. This latter result emphasizes our purposeful connection between conventional averaging methods with the use of machine learning for closure; this contrasts with some machine learning methods for upscaling where the exact form of the macroscale equation remains unknown.
Water film-driven Mn (oxy)(hydr)oxide nanocoating growth on rhodochrosite
Minerals exposed to moist air stabilize thin water films that drive a score of chemical reactions of great importance to water-unsaturated terrestrial environments. In this study, we identified Mn (oxy)(hydr)oxide nanocoatings formed by the dissolution, oxidation and precipitation of Mn in oxygenated water films grown on rhodochrosite (MnCO 3 ) microparticles. Nanocoatings that could be identified by vibrational spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and (scanning and transmission) electron microscopy formed in water films containing the equivalent of at least 7 monolayers (~84 H 2 O/nm 2 ). These films were formed by exposing microparticles to moist air with at least 50% relative humidity (RH). Films of neutral pH reacted up to 14% of the Mn II located in the topmost ~5 nm region of the microparticles in atmospheres of up to 90% RH for 7 d. These reactions produced MnOOH, birnessite (MnO 2 ) and hausmannite (Mn 3 O 4 ) nanoparticles of low crystallinity, while exposure to atmospheric air for 1 yr. converted only 2% of Mn II in this region to MnOOH. In contrast, reactions in alkaline water films converted up to ~75% of the Mn II but only after 16 d of reaction. These films produced MnOOH and MnO 2 of low crystallinity, as well as crystalline hausmannite. Kinetic modeling of the time-resolved growth of the Mnsingle bondO stretching vibrational bands of these nanocoatings revealed two concurrent reaction processes. A 1 rst -order process was assigned to nucleation events terminating only after a few hours, and a 0-order process was assigned to the sustained growth of nanocoatings from these nuclei over longer reaction time. By identifying nanocoatings formed by water film-driven reactions on rhodochrosite, our study adds new insight into mineralogical transformations relevant to anoxic–oxic boundaries in water-unsaturated environments.
Experimental and numerical study of the effects of solution concentration and temperature on concrete under external sulfate attack
The work reports on an experimental programme, conducted to validate comprehensively our previously proposed coupled chemo-transport model for external sulfate attack on concrete. Specifically, the effects of the concentration of sulfate solution and temperature on the distribution of sulfate ions in concrete are experimentally investigated and used to demonstrate the accuracy of the modeling framework. Further, the profile of aluminate depletion and the leaching depth numerically are investigated. For all cases the model predictions are in good agreement with the experimental results, showing increases of the concentration of sulfate ions in concrete with higher concentrations of sulfate solution and higher temperatures. It is concluded that higher sulfate solution concentration and temperature enhance the processes involved in the external sulfate attack on concrete, namely diffusion of sulfate ions and their chemical reactions with concrete. It is found that these parameters affect the external sulfate attack predominantly via the chemical reaction process.
Enhancement of Two Heterogeneous Reactions in the Production of the Medical Isotope 188 W
We report the efficiency of heterogeneous reactions is influenced by kinetic conditions with an emphasis on reactants in different phases to have effective interactions. Optimal interactions of reactants rely on the rational design of the equipment and engineering parameters for the reaction process, especially for the process on a large scale. 188 W production at the Oak Ridge National Laboratory is such an example. In processing the irradiated 186 W metal target for the 188 W product, two of the heterogeneous reactions are essential ones: (1) the gas–solid reaction of O 2 + W to form WO 3 and (2) the gas–liquid reaction of OsO 4 being absorbed by the NaOH sorbent. Better understanding of the two reactions has led to revisions to the design of the quartz reaction vessel (gas–solid reaction) and the scrubbing system (gas–liquid reaction). The optimized quartz vessel resulted in less heating hours, whereas a more efficient OsO 4 scrubbing system ensured that all volatile OsO 4 was qualitatively captured.
Application of a temporal multiscale method for efficient simulation of degradation in PEM Water Electrolysis under dynamic operating conditions
Hydrogen is emerging as a vital energy carrier, driven by the need to reduce carbon emissions. Proton Electrolyte Membrane Water Electrolysis (PEMWE) enables hydrogen production under fluctuating renewable power conditions but requires improved understanding and stability of the anode catalyst layer under dynamic operating conditions, especially with low noble metal loadings. Long-term degradation experiments are both time-consuming and costly; therefore, a systematic, model-aided approach is essential. In the present work, a temporal multiscale method is applied to reduce the computational effort of simulating long-term degradation processes in PEMWE, with an exemplary focus on catalyst dissolution. A mechanistic model incorporating the oxygen evolution reaction, catalyst dissolution, and hydrogen permeation from the cathode to the anode was hypothesized and implemented. In this way, the local periodicity of transport and reaction processes in dynamic PEMWE operation, which influence the gradual degradation of the catalyst layer, is captured. The temporal multiscale method significantly reduces the computational effort of simulation, decreasing processing time from hours to mere minutes. This efficiency gain is attributed to the limited evolution of Slow-Scale variables during each period of time P of the Fast-Scale variables. Consequently, simulation is required only until local periodicity is achieved within each Slow-Scale time step. Hence, the fully resolved dynamic problem is decoupled into these two scales, employing a heterogeneous multiscale technique. The developed approach effectively accelerates parameter estimation and predictive simulations, supporting systematic modeling of PEMWE degradation under dynamic conditions.
Half-life determination of heavy ions in a storage ring considering feeding and depleting background processes
Heavy-ion storage rings have relatively large momentum acceptance which allows for multiple ion species to circulate at the same time. This needs to be considered in radioactive decay measurements of highly charged ions, where atomic charge exchange reactions can significantly alter the intensities of parent and daughter ions. In this study, we investigate this effect using the decay curves of ion numbers in the recent 205 Tl 81+ bound-state beta decay experiment conducted using the Experimental Storage Ring at GSI Darmstadt. To understand the intricate dynamics of ion numbers, we present a set of differential equations that account for various atomic and nuclear reaction processes—bound state beta decay, atomic electron recombination and capture, and electron ionization. By incorporating appropriate boundary conditions, we develop a set of differential equations that accurately simulate the decay curves of various simultaneously stored ions in the storage ring: 205 Tl 81+ , 205 Pb 81+ , 205 Pb 82+ , 200 Hg 79+ , and 200 Hg 80+ . Through a quantitative comparison between simulations and experimental data, we provide insights into the detailed reaction mechanisms governing stored heavy ions within the storage ring. Our approach effectively models charge-changing processes, reduces the complexity of the experimental setup, and provides a simpler method for measuring the decay half-lives of highly charged ions in storage rings.
Laboratory Study of Nonlinear QED in Intense Laser-Matter Interactions
The goal of the project was to investigate the interaction of powerful laser light with matter, which is of fundamental interest to electrodynamics, thermonuclear fusion plasmas, and high-energy-density physics for DOE. Experiments on highly nonlinear relativistic interactions were performed using the state-of-the-art DIOCLES laser at the Extreme Light Laboratory of the University of Nebraska–Lincoln (UNL). We have demonstrated a novel testbed for laser-plasma interactions in which laser pulses collided in plasma with femtosecond and micron-scale accuracy under extreme experiment conditions. This capability is crucial for future radiation reaction experiments and nonlinear QED studies. Moreover, this is also a milestone towards the efficient generation of GeV electron beams via travelling wave laser wakefield accelerator. We proposed a novel idea for measuring the radiation reaction process using travelling wave Thomson scattering, which was studied in numerical simulations. This method allows unambiguous measurement of radiation reaction in a single shot, therefore, surpassing the conventional methods, which suffer severely from the shot-to-shot fluctuations, due to the instability of laser wavefield acceleration.
Systematic study of the validity of the eikonal model including uncertainties
Nuclear reactions at intermediate beam energies are often interpreted using the eikonal model. In the analysis of complex reaction probes, where few-body reaction methods are needed, the eikonal method may be used as an efficient way for describing the fragment-target reaction process. In this work, we perform a systematic study to test the validity of the eikonal approximation for nucleon-nucleus reactions. We also quantify uncertainties due to the nucleon optical potential on reaction observables. We inspect the validity of the eikonal model and its semiclassical correction by comparing it to exact solutions (obtained from solving the optical-model equation with a finite-differences method) for a wide range of reactions. We also study the effect of relativistic corrections, both kinematic and dynamic, by effectively incorporating the relativistic effects at intermediate energies. The uncertainties from a Bayesian global optical potential (KDUQ) are propagated to the observables of interest. Our study includes neutron and proton reactions on 27 Al , 40 Ca , 90 Zr , and 208 Pb , for a wide range of energies 𝐸 lab = 0–400 MeV. We calculate neutron-total cross sections (elastic and reactions) as well as proton-absorption cross sections as a function of beam energy, using the eikonal model, the eikonal model with a semiclassical correction, and the exact solution. Here, we also compute angular distributions for the methods above. Our results show that for the proton-absorption cross section, the eikonal model can be used down to around 60 MeV and the semiclassical correction extends its use to 30 MeV. However, the validity of the eikonal model for the neutron-total cross section only goes down to ≈120 MeV, a range extended to ≈ 50 MeV when using the semiclassical correction. We find the semiclassical correction to the eikonal model to be less effective in describing the angular distributions. The 1𝜎 uncertainty intervals on the observables we studied is less than 5% for most of the energies considered, but increases rapidly for higher energies, namely energies outside the range of KDUQ (𝐸 lab > 200MeV).
Coherent Neutrino-Nucleus Scattering: A Tool to Search for New Physics
The Neutrino is a well-understood particle in the models of particle physics. Even so, it is electrically neutral, and has a very small mass. As such, it’s interaction probability is extremely small. Detecting neutrinos has always been a challenge for particle physics. Over 40 years ago, Daniel Freedman predicted a new type of interaction that neutrinos could undergo that would be much more frequent. This has since been called Coherent Elastic Neutrino Nucleus Scattering (CEvNS). While this process occurred more frequently than the traditionally used interaction process (called inverse beta decay) it was more challenging to detect. Interestingly, though, if you could detect the CEvNS process, you would be sensitive to many new studies of fundamental particle physics. A researcher may also be able to use this process to study neutrinos in more applied settings, for instance by more easily monitoring the neutrinos given off during the nuclear reaction processes in nuclear reactors. The aim of this project was to observe coherent neutrino scattering for the first time, and begin to use it as a tool both to study new types of physics models, and to study the feasibility of this concept for applied situations.