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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Role of ripples in altering the electronic and chemical properties of graphene

Ripples of graphene are known to manipulate electronic and hydrogenation properties of graphitic materials. More detailed work is needed to elucidate the structure–property relationship of these systems. In this work, the density functional theory is used to compute the energy and electronic structure of the graphene models with respect to variable curvatures and hydrogen adsorption sites. The magnitude of finite bandgap opening depends on the orientation of ripples, and the hydrogen adsorption energy depends on the local curvature of graphene. An adsorbed hydrogen alters the local curvature, resulting in relatively weakened adsorption on the neighboring three sites, which gives a rationale to experimentally observed dynamic equilibrium stoichiometry (H:C = 1:4) of hydrogenated graphene. The surface diffusion transition state energy of adsorbed hydrogen is computed, which indicates that the Eley–Rideal surface recombination mechanism may be important to establish the dynamic equilibrium, instead of the commonly assumed Langmuir–Hinshelwood mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structural water in amorphous carbonate minerals: ab initio molecular dynamics simulations of X-ray pair distribution experiments

Water is known to play a controlling role in directing mineralization pathways and stabilizing metastable amorphous intermediates in hydrous carbonate mineral MCO 3 ·nH 2 O systems, where M 2+ is a divalent metal cation. Despite this recognition, the nature of the controls on crystallization is poorly understood, largely owing to the difficulty in characterizing the dynamically disordered structures of amorphous intermediates at the atomic scale. Here, we present a series of atomistic models, derived from ab initio molecular dynamics simulation, across a range of experimentally relevant cations (M = Ca, Mg, Sr) and hydration levels (0 ≤ n ≤ 2). Theoretical simulations of the dependence of the X-ray pair distribution function on the hydration level n show good agreement with available experimental data and thus provide further evidence for a lack of significant nanoscale structure in amorphous carbonates. Upon dehydration, the metal coordination number does not change significantly, but the relative extent of water dissociation increases, indicating that a thermodynamic driving force exists for water dissociation to accompany dehydration. Mg strongly favors monodentate conformation of carbonate ligands and shows a marked preference to exchange monodentate carbonate O for water O upon hydration, whereas Ca and Sr exchange mono- and bidentate carbonate ligands with comparable frequency. Finally, water forms an extensive hydrogen bond network among both water and carbonate groups that exhibits frequent proton transfers for all three cations considered suggesting that proton mobility is likely predominantly due to water dissociation and proton transfer reactions rather than molecular water diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Li 2 GeS 3 : Lithium Ionic Conductor with an Unprecedented Structural Type

Lithium-ion batteries (LIBs) are widely used in electric vehicles, mobile electronic devices, and large-scale stationary energy storage systems. However, their liquid electrolytes present significant safety concerns due to their inherent flammability. To address this, the focus has shifted toward all-solid-state batteries (ASSBs) utilizing inorganic solid electrolytes that promise enhanced safety. In this work, we report the discovery of a new crystal structural type of Li-ion conductor, Li 2 GeS 3 , with a unique structure, synthesized by a solid-state reaction from Li 2 S and GeS 2 . It was first reported in 2000 with an orthorhombic unit cell, but its detailed crystal structure remains veiled. Here, we have unveiled its structure for the first time, employing an ab initio structure determination technique from powder X-ray and time-of-flight neutron diffraction data. The compound has an unprecedented crystal structural type with a hexagonal $P6_1$ symmetry and a unit cell of α = 6.79364(4) Å and c = 17.90724(14) Å. Its structure is comprised of a distorted hexagonal close-packed arrangement of sulfur anions with three asymmetric metal atoms: Li1, Li2, and Ge are in tetrahedral cavities surrounded by sulfur atoms. The ionic conductivity of Li 2 GeS 3 was measured to be 1.63 × 10 –8 S cm –1 at 303 K and 2.45 × 10 –7 S cm –1 at 383 K. Bond valence energy landscape calculations revealed three-dimensional lithium diffusion pathways within the structure. This novel crystal structure in Li 2 GeS 3 holds the potential for developing high-performance ionic conductors through suitable chemical substitution and offers valuable insights into designing new ionic conductors for ASSBs.

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

Hexamethyldisiloxane pyrolysis: probing H-atom initiation by femtosecond two-photon LIF

Previous experiments have led to the hypothesis that pyrolysis of silica nanoparticle precursors carried in an inert central gas jet surrounded by a laminar flame is initiated not by thermal decomposition (the measured jet temperatures are too low for pyrolysis), but by reactions with H-atoms diffusing from the surrounding flame into the jet. The current work tests this hypothesis using femtosecond two-photon laser-induced fluorescence (fs-TPLIF) to image H-atom concentrations in the same flame configuration as the previous experiments. Methane flames (ϕ = 0.83, 1.01 and 1.13) were generated using a multi-element diffusion (Hencken) burner equipped with a central tube through which the N2 jet was introduced. The fs-TPLIF line imaging showed significant concentrations of H-atoms in the nitrogen jets at heights above the burner (HAB) close to the methane flame front. The measurements indicate radial diffusion of the H atoms from the flame to the jet is significant. The H-atom concentrations in the jet increased with increasing stoichiometry of the methane flame. Additional experiments were performed with hexamethyldisiloxane entrained in the central jet flow. In each case, a diffusion flame producing silica nanoparticles was established at the boundaries between the central jet and the methane flames. The 2D H-atom images showed a transition from over-ventilated diffusion flames to under-ventilated diffusion flames with increasing equivalence ratio. Furthermore, the fs-TPLIF profiles show a significant production of H-atoms within the jet when the surrounding flame is lean. This knowledge contributes to a deeper understanding of the underlying mechanisms governing these synthesis flame systems and opens avenues for advancing silica nanoparticle synthesis techniques.

Kim, Keunsoo↗
DOE OSTI2021

A Pore‐Scale Investigation of Mineral Precipitation Driven Diffusivity Change at the Column‐Scale

Abstract Mineral precipitation affects the pore structure and thus transport properties of porous media. In this study, we investigated the pore‐scale dynamics of precipitation in diffusion controlled systems and the resulting impacts on the effective diffusivity, using a micro‐continuum reactive transport model. Forty two‐dimensional pore structures representing both idealized and realistic geometries were simulated with consideration of different precipitation scenarios and rates. A homogeneous nucleation scenario reproduced patterns observed in previous experimental study showing mixing‐induced precipitation, and a surface growth scenario captured the pattern for mineral precipitation on a substrate with the same or similar mineral structures. In all cases, local precipitation resulted in the reduction in the average porosity of the domain ( Φ ) until the cessation of diffusive transport and the termination of precipitation. The minimum porosity reached was referred to as the critical porosity ( Φ c ). The effective diffusivity ( D eff ) decreased with Φ and dropped sharply to effectively zero, that is, the critical effective diffusivity ( D eff c ), as Φ c was reached. These pore‐scale dynamics can be captured by a revised relationship that explicitly considers the critical porosity and the corresponding effective diffusivity, and the pre‐exponential coefficient and the exponent of the relationship varied with initial pore structure and the precipitation kinetics. Overall, the homogeneous nucleation scenario results in systematically larger Φ c and coefficients that give rise to a sharper decrease in diffusivity as Φ c is approached, compared to the surface growth scenario. The revised relationship was also implemented at continuum scale and used to examine column scale diffusivity change and reactions.

58 GEOSCIENCES↗
DOE OSTI2025

Recombination of Autodissociated Water Ions in a Nanoscale Pure Water Droplet

The recombination of water ions has diverse scientific and practical implications, ranging from acid-base chemistry and biological systems to planetary environments and applications in fuel cell and carbon conversion technologies. While spatial confinement affects the physicochemical properties of water dynamics, its impact on the recombination process has rarely been studied. In this work, we investigate the dynamics of water, the water ion distribution, and the ion recombination process in water droplets as a function of droplet size through molecular dynamics simulations and adaptive quantum mechanical/molecular mechanical calculations. We compare the dynamics of recombination in water droplet sizes ranging from 100 to 18 000 waters, both in their interiors and on their surfaces. We found that the self-diffusion of water dramatically decreases in droplets with a diameter below 2.2 nm. Using a classical RexPoN force-field, we found that the ions in 1000 H2O's spend almost 50% of the time on the surface and 0.5 nm beneath it with a slight preference for OH- ion to reside longer on the surface. We estimate that, on average, recombination in these drops occurs at 400 ps in 1000 H2O's and 1 ns in 3000 H2O's. We also found that recombination is not limited by the local structure of the surface or the size of the droplet but can be influenced by the geometry of the water wire connecting the ions as they approach each other, which can often prevent recombination. Our results provide insights to the reaction microenvironments presented by nanoscopic water droplets.

Kwon, Soonho↗
DOE OSTI2025

SULI Intern Final Report: Computationally Investigating Hydrogen Thermo-Diffusion in Yttrium Hydride Using Multiscale Methods

The renaissance of nuclear energy has arrived, heralding an age of abundant inexpensive clean energy, and renewed space exploration. In nuclear-powered spacecraft and microreactors, safety and size are of utmost importance. Yttrium Hydride (YHx) is being researched for its utility as a neutron moderator in nuclear reactors; the hydrogen in YHx slows down neutrons, enabling a continuous nuclear reaction in the reactor. This has the benefit of allowing reactors to be more safe, compact, and efficient. The goal of this effort is to computationally predict the coefficient of temperature-dependent hydrogen diffusion within YHx, the Soret coefficient. This parameter is essential for determining the safe operating modes of YHx moderators. Zirconium Hydride (ZrHx) is used in the Training, Research, Isotopes, General Atomics (TRIGA) reactor, is the reference material for these calculations. In this work, nanoscale atomic modeling in the Vienna Ab initio Simulation Package (VASP) is combined with the mesoscale finite element phase-field module in the Multiphysics Object-Oriented Simulation Environment (MOOSE); this culminates in a new multiscale computational method to simulate Soret diffusion of hydrogen in YHx. This data is useful for predicting experimental outcomes. This workflow involves convergence testing followed by static, Nudged Elastic Band (NEB), Quasi-Harmonic Approximation (QHA), and Molecular Dynamics (MD) calculations - linked with phase field simulation. NEB simulates hydrogen migration, while QHA and MD predict temperature-dependent properties. The static calculations align with literature, and preliminary NEB and QHA calculations yield accurate results. Once the atomic calculations are complete, we will incorporate Electron Backscatter Diffraction (EBSD) images and VASP-generated parameters into the phase field module to simulate intra- and intergranular transport of hydrogen in ZrHx and YHx. Future research will extend our approach to fuel-moderator materials systems such as Uranium-Yttrium Hydride (U-YHx). This work contributes to the development of advanced nuclear energy solutions for space travel.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Mechanistic understanding of catalytic conversion of ethanol to 1-butene over 2D-pillared MFI zeolite

Ethanol is an important C2 platform molecule for producing value-added chemicals and distillate hydrocarbon fuels (e.g., jet and diesel). Among these, catalytic upgrading of ethanol to butenes can generate valuable commodity chemicals (e.g., 1-butene) and provide C4 olefin intermediates that can be further upgraded to jet/diesel fuels. 2D zeolites offer hierarchical mesoporous structures, leading to improved mass transport and reduced diffusion length, which can help to address the coking challenges faced by ethanol conversion to hydrocarbons over 3D zeolites. In this study, we investigate the acid-catalyzed conversion of ethanol to 1-butene over the Brønsted acid sites (BAS) in 2D-pillared MFI zeolite (2D-PMFI) using ab initio molecular dynamics (AIMD) simulations, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and calorimetric measurements. A detailed thermodynamic analysis, using quasi-harmonic approximation (QHA), on the Gibbs free energy pathway of ethanol conversion shows that the consideration of entropy is critical to accurately capture the detailed thermodynamic profiles. The formation of bulky ethoxy-ethene complex is found to be a potential rate-determining step (RDS), proceeding via stepwise mechanism. The reactivity of 2D-PMFI can be further tuned by manipulating RDS through a careful control of number of BAS and operating temperatures. The accuracy of computational model is confirmed through the comparison of calculated vibrational density of states (VDOS) against the experimental DRIFTS measurements. Overall, our study provides mechanistic insights into ethanol upgrading over the 2D-PMFI and shows the importance of evaluating entropic effects in such confined system.

Ethanol conversion, 2D-pillared zeolite, MFI, Anha↗
DOE OSTI2022

Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach

Summary Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO 2 . We developed a 3D reaction‐diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO 2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf‐level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO 2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A numerical study of ignition and flame development characteristics in GCI combustion using large eddy simulations and chemical explosive mode analysis

Here, this work investigates the ignition and flame development processes of low reactivity fuel combustion under compression ignition conditions based on the large eddy simulation approach. The chemical explosive mode analysis (CEMA) is employed to characterize the local combustion features, including gas-liquid fuel zone, auto-ignition, diffusion-assisted, extinction, cool flame and post-ignition zone, among which auto-ignition and post-ignition are found to play a key role in the overall heat release process. The local flame propagation modes in gasoline compression ignition (GCI) are determined by quantifying the relative magnitude of diffusion/chemistry at a representative progress variable in the pre-ignition zone. The results show that autoignition fronts and deflagration waves exist simultaneously in the ignition and intense high temperature heat release (HTHR) stages, but autoignition fronts dominate. In addition, the chemical kinetic processes of four heat release periods are analyzed. The heat release during the ignition period is found to be dominated by the reactions CH 3 + H (+M) <=> CH 4 (+M) and CH 3 CHO + H <=> CH 2 CHO + H 2 . The reaction CH 2 OH + OH <=> CH 2 O + H 2 O always plays an important role in the heat releases during the other three combustion stages including intense HTHR, moderate HTHR and post-combustion.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Bridging the time scale in exascale computing of chemical systems (Final Technical Report)

This report summarizes the work carried out with support of the United States Department of Energy under Award DE-SC0019441. The theme of this project was to develop and apply methods that allowed for the acceleration of atomistic calculations, particularly in challenging areas such as multiphase systems, electrified interfaces, uncertainty estimation, and applications requiring chemical accuracy, which tend to be applications where simulation time is severely bottlenecked by the computational time requirements. Much of the focus was on the application of emerging machine-learning methodologies, although a wide range of methodologies were employed. This report has two major sections. The first focuses on the methodological advances themselves. Within this part, we report a number of major advances, a few examples of which are described here. We report the first machine-learning scheme for the acceleration of electronically grand-canonical calculations (that is, those applicable to electrochemistry). We report new methods of performing transfer learning, in which physics-based priors can be used to provide predictions, often with uncertainty estimates, of images well outside of training sets; we also offer ways to fine-tune these transfer-learning models. We provide a new systematic means to generate and apply minimal training data sets to very large (10,000’s of atoms) systems, with only small training sets appropriate for electronic structure. We developed new methodologies to integrate surface vibrations into surface adsorption calculations. We made advances to the applicability of diffusion Monte Carlo methods to allow (learned) force prediction, finite-size error correction, and force-free means of searching for transition states. We integrated machine-learned atomistic predictions into mechanism generation codes. Additionally, we released new software including AmpTorch, a modernized version of our original atomistic machine-learning code Amp. The second part of this report focuses on the scientific applications that accompanied, and were often enabled by, the methodological advances described earlier. A few examples follow, but full details are in the individual chapters of the report. For example, we developed a general theory of phonon-induced friction on molecular adsorbates. We showed fundamentally how solvent influences the adsorption and desorption process and how it differs from the processes typically involved at the solid–gas interface, making aqueous-phase and electrocatalysis different from traditional thermocatalysis. We examined how metal–insulator and magnetic transitions can be probed, and accelerated exciton dynamics via Frenkel Hamiltonian parameters. We showed that the nearsighted force-training approach, developed within this project, can predict both the stability and reactivity of large nanoparticles, and can also lead to insights on catalyst coverage on binding energies and entropies. These applied studies, which generally integrated with our method development, allowed us to push forward the theoretical understanding of several reaction classes.

08 HYDROGEN↗
DOE OSTI2020

Reactive particle-tracking solutions to a benchmark problem on heavy metal cycling in lake sediments

Geochemical systems are known to exhibit highly variable spatiotemporal behavior. This may be observed both in non-smooth concentration curves in space for a single sampling time and also in variability between samples taken from the same location at different times. However, most models that are designed to simulate these systems provide only single-solution smooth curves and fail to capture the noise and variability seen in the data. We apply a recently developed reactive particle-tracking method to a system that displays highly complex geochemical behavior. When the method is made to most closely resemble a corresponding Eulerian method, in its unperturbed form, we see near-exact match between solutions of the two models. More importantly, we consider two approaches for perturbing the model and find that the spatially-perturbed condition is able to capture a greater degree of the variability present in the data. This method of perturbation is a task to which particle methods are uniquely suited and Eulerian models are not well-suited. Additionally, because of the nature of the algorithm, noisy spatial gradients can be highly resolved by a large number of mobile particles, and this incurs negligible computational cost, as compared to expensive chemistry calculations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

One of the open problems in scientific computing is the long-time integration of nonlinear stochastic partial differential equations (SPDEs), especially with arbitrary initial data. We address this problem by taking advantage of recent advances in scientific machine learning and the spectral dynamically orthogonal (DO) and borthogonal (BO) methods for representing stochastic processes. The recently introduced DO/BO methods reduce the SPDE to solving a system of deterministic PDEs and a system of stochastic ordinary differential equations. Specifically, we propose two new physics-informed neural networks (PINNs) for solving time-dependent SPDEs, namely the neural network (NN)-DO/BO methods. The proposed methods incorporate the DO/BO constraints into the loss function (along with the modal decomposition of the SPDE) with an implicit form instead of generating explicit expressions for the temporal derivatives of the DO/BO modes. Hence, the NN-DO/BO methods can overcome some of the drawbacks of the original DO/BO methods. For example, we do not need the assumption that the covariance matrix of the random coefficients is invertible as in the original DO method, and we can remove the assumption of no eigenvalue crossing as in the original BO method. Moreover, the NN-DO/BO methods can be used to solve time-dependent stochastic inverse problems with the same formulation and same computational complexity as for forward problems. Furthermore, we demonstrate the capability of the proposed methods via several numerical examples, namely: (1) A linear stochastic advection equation with deterministic initial condition: we obtain good results with the proposed methods, while the original DO/BO methods cannot be applied directly in this case. (2) Long-time integration of the stochastic Burgers' equation: we show the good performance of NN-DO/BO methods, especially the effectiveness of the NN-BO approach for such problems with many eigenvalue crossings during the whole time evolution, while the original BO method fails. (3) Nonlinear reaction diffusion equation: we consider both the forward problem and the inverse problems, including very noisy initial point values, to investigate the flexibility of the NN-DO/BO methods in handling inverse and mixed type problems. Taken together, these simulation results demonstrate that the NN-DO/BO methods can be employed to effectively quantify uncertainty propagation in a wide range of physical problems, but future work should address the efficiency issue of PINNs for forward problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A mass-transfer particle-tracking method for simulating transport with discontinuous diffusion coefficients

The problem of a spatially discontinuous diffusion coefficient (D(x)) is one that may be encountered in hydrogeologic systems due to natural geological features or as a consequence of numerical discretization of flow properties. To date, mass-transfer particle-tracking (MTPT) methods, a family of Lagrangian methods in which diffusion is jointly simulated by random walk and diffusive mass transfers, have been unable to solve this problem. This manuscript presents a new mass-transfer (MT) algorithm that enables MTPT methods to accurately solve the problem of discontinuous D(x). To achieve this, we derive a semi-analytical solution to the discontinuous D(x) problem by employing a predictor-corrector approach, and we use this semi-analytical solution as the weighting function in a reformulated MT algorithm. Furthermore, this semi-analytical solution is generalized for cases with multiple 1D interfaces as well as for 2D cases, including a 2 × 2 tiling of 4 subdomains that corresponds to a numerically-generated diffusion field. The solutions generated by this new mass-transfer algorithm closely agree with an analytical 1D solution or, in more complicated cases, trusted numerical results, demonstrating the success of our proposed approach.

42 ENGINEERING↗
DOE OSTI2021

Mixing Cell Model: A One-Dimensional Numerical Model for Assessment of Water Flow and Contaminant Transport in the Unsaturated Zone

This report describes the Mixing Cell Model code, a one dimensional model for water flow and solute transport in the unsaturated zone under steady state or transient flow conditions. The model is based on the principles and assumptions underlying mixing-cell model formulations. The unsaturated zone is discretized into a series of independent mixing cells. Each cell may have unique hydrologic, lithologic, and sorptive properties. Ordinary differential equations describe the material (water and solute) balance within each cell. Water-flow equations are derived from the continuity equation, assuming that unit gradient conditions exist at all times in each cell. Pressure gradients are considered implicitly through model discretization. Unsaturated hydraulic conductivity and moisture contents are determined by the material specific moisture-characteristic curves. Solute-transport processes include explicit treatment of advective processes, first order chain decay, and linear sorption reactions. Dispersion is addressed through implicit and explicit dispersion. Implicit dispersion is an inherent feature of all mixing-cell models and originates from the formulation of the problem in terms of mass balance around fully mixed volume elements. Expressions are provided that relate implicit dispersion to the physical dispersion of the system. Two FORTRAN codes were developed to solve the water flow and solute-transport equations: (1) the Mixing Cell Model for Flow (MCMF) solves transient water-flow problems and (2) the Mixing Cell Model for Transport (MCMT) solves the solute-transport problem. The transient water-flow problem is typically solved first by estimating the water flux through each cell in the model domain as a function of time using the MCMF code. These data are stored in either ASCII or binary files that are later read by the solute transport code (MCMT). Code output includes solute pore water concentrations, water and solute inventories in each cell and at each specified output time, and water and solute fluxes through each cell and specified output time. Computer run times for coupled transient water flow and solute transport were typically several seconds on a 2 GHz Intel Pentium IV desktop computer. The model was benchmarked against analytical solutions and finite element approximations to the partial differential equations (PDE) describing unsaturated flow and transport. Differences between the maximum solute flux estimated by the mixing cell model and the PDE models were typically less than two percent. This revision includes an option for a fixed concentration lower boundary condition for diffusive fluxes for versions 020321 and later.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reaction Diffusion Modelling of 3D Pillar Electrodes in Single-Catalyst CO 2 Reduction Cascades

Effective electrochemical CO 2 reduction to liquid fuels requires that the local catalytic environment facilitates the desired reactivity, yet a microscopic understanding of this environment is difficult to achieve from experiment alone. In this work, a 3D reaction-diffusion model was developed to explore the effects of electrode surface area and local geometry on the performance of a heterogeneous catalyst that performs a two-step CO 2 reduction cascade reaction to CO and then CH 3 OH under aqueous conditions. Kinetic parameters for the model were inspired by experimental results using a cobalt phthalocyanine (CoPc) catalyst. Three-dimensional architectures composed of arrays of square pillars with varying dimensions and either smooth or periodically modulated surfaces were tested, revealing the extent to which geometry modulates the performance of the cascade reactions. Although structural variations modulate local concentration gradients, we find that electrochemically active surface area predominantly governs the overall cascade reaction. Moreover, the results suggest that supersaturation of CO, with concentrations up to ten-fold higher than the equilibrium solubility limit, might be critical for more efficient conversion to CH 3 OH. For any given geometry, the spatially averaged ratio of [CO] to [CO 2 ] is dictated by the electrochemically active surface area and determines the yield of CH 3 OH. For a fixed surface area, geometries that spatially confine the electrolyte yield moderate local [CO] to [CO 2 ] ratios within small volumes. In contrast, less confining geometries result in a broader distribution of local ratios spread over larger volumes, with both configurations yielding the same spatially averaged [CO] to [CO 2 ] ratio. These insights provide valuable design principles—highlighting the critical importance of surface area and possibly CO supersaturation—for engineering advanced electrode architectures that leverage intermediate trapping and CO supersaturation to enhance overall performance in tandem CO 2 reduction systems.

COMSOL↗
DOE OSTI2021

Elucidating Mass Transport Regimes in Gas Diffusion Electrodes for CO 2 Electroreduction

Gas diffusion electrodes (GDEs) have shown promising performance for the electrochemical reduction of CO 2 (CO 2 R). In this study, a resolved, pore scale model of electrochemical reduction of CO 2 within a liquid-filled catalyst layer is developed. Three CO 2 mass transport regimes are identified in which the CO 2 penetration depth is controlled by CO 2 consumption in the electrolyte, CO 2 conversion along the solid-electrolyte double-phase boundaries (DPBs), and CO 2 conversion concentrated around the gas–solid–electrolyte triple-phase boundaries (TPBs). While it is possible for CO 2 R to be localized around the TPBs, in systems with submicron pore radii operating at <1 A cm –2 CO 2 R will be distributed across the DPBs within the catalyst layer. This validates the assumption of pore-scale uniformity implicit in popular, volume-averaged GDE models. Overall, the CO 2 conversion efficiency depends strongly on the governing mass transport regime, and operational-phase diagrams are constructed to guide the catalyst layer design.

10 SYNTHETIC FUELS↗
DOE OSTI2023

AN ACID BAKING APPROACH TO ENHANCE RARE EARTH ELEMENT RECOVERY FROM BITUMINOUS COAL SOURCES

Rare earth elements (REE) are a group of 17 elements typically classified as light and heavy rare earth elements, which play a crucial role in developing the latest technologies for energy, defense, and medical sectors. Even though REEs have been found in more than 200 minerals, only bastnaesite, monazite and xenotime are commercially exploited for REE extraction. However, the recent exponential increase in REE demand has spurred countries such as the United States into research for the extraction of REEs from secondary sources such as coal, acid mine drainage, and coal ash. Several coal sources (e.g., Fire Clay seam coal) across the United States have been identified to contain elevated concentrations of rare earth elements (>600 ppm), and various researchers have investigated the feasibility of both physical and hydrometallurgical extraction techniques for rare earth concentration and subsequent extraction. However, both physical and direct leaching were concluded to be inefficient for RE beneficiation and extraction due to low recoveries. Alternatively, thermal treatment provides promising means for RE recovery from bituminous coal sources. The positive impact of thermal treatment/calcination was established to be due to the decarbonization and dehydroxylation of the clays, which released entrapped rare earth elements within the dominant minerals and converted them into an acid-soluble form. Nonetheless, the improvement in recovery was limited to the light REEs (LREEs) with an insignificant increase in the heavy REEs (HREE). It was demonstrated that the light and heavy REEs in the material were associated with difficult-to-leach minerals such as monazite, xenotime, and zircon, which were not decomposed by simple calcination due to their high thermal stability. Hence, roasting in the presence of chemicals was necessary to ensure the decomposition of those REE-containing minerals. As such, this study was focused on the acid baking treatment of bituminous coals with an aim to enhance REE recovery, especially HREEs. Based on the presence of REE minerals like monazite and xenotime, three pre-leach treatment methods, i.e., 1) roasting, 2) direct acid baking, and 3) acid baking after roasting were investigated. Roasting tests at 600 ⁰C revealed that the recovery of light REEs (LREEs) was enhanced while the recovery of HREEs remained relatively unaffected. LREE and HREE recovery values of 38.3% and 21.3%, respectively, were achieved using a 50 g/L sulfuric acid solution at 5% solid concentration and a solution temperature of 75 ⁰C for 2 hours. Comparatively, direct acid baking at 250 °C provided substantial increased LREE and HREE recovery values to approximately 49.4% and 53.0%, respectively, using an equivalent acid dosage. Recoveries were maximized to 77.0% and 79.6% for LREE and HREE, respectively, by roasting followed by acid baking. Similar results were obtained from the treatment of a second bituminous coal source. Due to strong correlations between REE and Al recovery values, tests were performed on kaolinite and illite, which were prominent clay minerals within the source coals. These experiments revealed that the REE recovery improvements were likely a result of dehydroxylation of clays and subsequent release and decomposition of REE-bearing minerals such as monazite, xenotime and zircon. Subsequently, a parametric study was conducted to identify the impact of acid baking parameters on rare earth element recovery. The factors investigated using a three-level statistical experimental program were acid baking time, acid solution concentration, baking temperature, and acid solution-to-solids ratio which were found to significantly impact REE and contaminant element (Al, Fe, and Ca) recovery. An increase in baking temperature up to around 250 ⁰C improved the light and heavy REE recovery values by more than 50 absolute percentage points relative to performances achieved when direct leaching. As aforementioned, acid baking was needed to both decompose the clay minerals and liberate the REE minerals, which allowed access for the acid to solubilize the REEs. Acid concentration of the solution used for acid baking was studied as a means of minimizing the amount of acid needed to achieve a target REE recovery. However, thermo-gravimetric and differential scanning calorimetry analysis (TGA-DSC) of sulfuric acid under oxidizing atmosphere revealed that the addition of water decreased the evaporation temperature, which explains the lower REE recovery values obtained when using acid concentrations less than 100%. Using pure sulfuric acid at an acid-to-solid ratio of 0.8:1 resulted in recovery values of around 70% for both LREEs and HREEs. The decomposition reaction time was relatively quick with 65% of the TREEs recovered within the first 10 minutes. Following the identification of optimum operating conditions through the parametric study, a systematic leaching study was carried out to examine the impact of leaching parameters, such as solid-to-liquid (S/L) ratio, temperature, and time, on REE recovery using acid baking conditions of 1:1 acid to solids ratio at 250 °C for 30 minutes. The solid-to-liquid ratio was varied from 1-20% by weight at 25 °C, 50 °C, and 75 °C solution temperatures. The results indicated that reaction time and solution temperature considerably impacted the recovery of heavy and light REEs. Interestingly, LREE recovery reduced from 68% at 5% S/L to 58% at 20%S/L, whereas HREE recovery of 78% remained unaffected. The decrease in the LREE recovery was determined to be due to La and Ce precipitation, likely through isomorphic substitution with calcium in gypsum. The kinetic data indicated that 67% LREE and 77% HREE recovery could be obtained within the first 15 minutes of the reaction, suggesting fast reaction kinetics. Furthermore, raising the solution temperature from 25 °C to 75 °C increased the LREE and HREE recovery from 60% and 32% to 67% and 79%, respectively. The kinetic modeling results demonstrated that the rate-limiting step in the LREE dissolution was diffusion and chemical reaction, whereas the HREE extraction was controlled by only chemical reaction. The leaching study concluded that using 20% S/L at 75 °C for 15 minutes maximized LREE and HREE recovery. The lab-scale precipitation study showed that Fe and Al in solution could be removed at pH 4.5 followed by REE precipitation at pH 6.0 using 6 mol/L NaOH. Finally, the bench-scale data was used to develop a process flowsheet for REE recovery from low-grade bituminous coal sources using acid baking. Finally, based on the proposed flowsheet, a concentrated RE-cake obtained through selective precipitation at pH 6.5 was re-leached using HCl at pH 1.5. The resultant leachate was used to identify the impact of various operating parameters on REE recovery and purity with an aim to maximize REE precipitation efficiency while minimizing the oxalic acid dosage. The operating parameters for this investigation were oxalic acid dosage, iron (III) contamination, solution pH and temperature. The resultant model suggested that oxalic acid dosage and reaction pH are the most significant factors for the REE precipitation efficiency, followed by the interaction of oxalic dosage and Fe concentration. Test results indicated that increasing the oxalic acid concentration from 0g/L to 80g/L improved the REE precipitation efficiency from approximately 4.2% to 95.0%. Furthermore, raising the solution pH from 0.5 to 2.5 considerably enhanced the precipitation efficiency from 0.0% to 98.9%. A solution temperature elevation decreased REE recovery, which indicated an exothermic reaction between REEs and oxalate anions. Finally, a high level of Fe contamination adversely impacted REE precipitation efficiency. The speciation analysis revealed that the dominant iron species in the solution system were Fe-(C₂O₄)₃³⁻, Fe-(C₂O₄)²⁻, and Fe-(C₂O₄)⁺, which consumed the majority of the oxalate anions

rare earth elements, acid baking, high-temperature↗