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At least 163 records · Page 9

Physics-Based Model to Represent Membrane-Electrode Assemblies of Solid-Oxide Fuel Cells Based on Gadolinium-Doped Ceria

This paper reports a physics-based model that predicts membrane-electrode assembly (MEA) performance of solid-oxide fuel cells (SOFCs) with Ce 0.9 Gd 0.1 O 2− δ (GDC10) electrolyte membranes. The paper derives self-consistent thermodynamic and transport properties for GDC1o mobile charged defects (oxide vacancies and reduced-ceria small polarons) by fitting published measurements of oxygen non-stoichiometry and conductivity over ranges of temperature and O 2 partial pressures. The button-cell model is applied to evaluate how mixed ionic-electronic conductivity influences the performance of an SOFC MEA with a GDC10 electrolyte sandwiched between a porous, composite Ni-GDC10 anode and a porous, composite cathode of Sm 0.5 Sr 0.5 CoO 3− δ (i.e., SSC) and GDC10. SSC properties are also derived by fitting published conductivity and oxygen non-stoichiometry measurements. Mixed conductivity of GDC10 and competing charge transfer reactions at both electrodes reduce open circuit voltages due to leakage current and buildup of defect concentrations at electrode-electrolyte interfaces. To fit polarization data, the button-cell model includes heterogeneous reaction rates for defect incorporation on the GDC10 surface along with Butler–Volmer expressions derived for competing charge transfer reaction rates from rigorous analyses assuming rate-limiting, elementary charge transfer reactions for each electrode. The calibrated MEA model can support rigorous SOFC modeling with GDC10 electrolytes over the range of conditions within a fully operating cell.

Electrochemistry↗

Solution and Interface Structure and Dynamics in Geochemistry: Gateway to Link Elementary Processes to Mineral Nucleation and Growth

Our understanding of the process of mineral nucleation is starting to evolve from the solely thermodynamical aspects in classical nucleation theory toward a mechanistic study of reactions influenced by solvation structures of ions and their dynamics. A knowledge of how these atomic and molecular interactions respond to changing solution composition and/or the nature of an interface will form a fundamental foundation to understand rate-limiting reactions and processes for nucleation and growth. Here, we review recent advances from multidisciplinary experimental and computational approaches of the structure and dynamics of aqueous solutions and mineral–liquid interfaces that will influence rates of nucleation (and growth behavior) both homogeneously in aqueous solutions and heterogeneously at mineral–liquid interfaces. Furthermore, these processes include structure (and extent) of solute clustering, solvent degrees of freedom, and the presence of noninnocent charge-balancing ions, all of which can drive the selectivity and exert control over nucleation mechanisms. Similar controlling reactions can also occur at interfaces with the added complexities of how solute ions interact with and assemble on surface sites and use different mechanisms from bulk solutes, such as lateral solvent exchanges between distinct surface sites. To gain a predictive understanding of nucleation chemistry, we emphasize several key knowledge gaps that will need to be addressed in this field and highlight the importance of combining computations and experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TChem v2.0 - A Software Toolkit for the Analysis of Complex Kinetic Models

TChem is an open source software library for solving complex computational chemistry problems and analyzing detailed chemical kinetic models. The software provides support for: complex kinetic models for gas-phase and surface chemistry; thermodynamic properties based on NASA polynomials; species production/consumption rates; stable time integrator for solving stiff time ordinary differential equations; and, reactor models such as homogenous gas-phase ignition (with analytical Jacobian matrices), continuously stirred tank reactor, plug-flow reactor. This toolkit builds upon earlier versions that were written in C and featured tools for gas-phase chemistry only. The current version of the software was completely refactored in C++, uses an object-oriented programming model, and adopts Kokkos as its portability layer to make it ready for the next generation computing architectures i.e., multi/many core computing platforms with GPU accelerators. We have expanded the range of kinetic models to include surface chemistry and have added examples pertaining to Continuously Stirred Tank Reactors (CSTR) and Plug Flow Reactor (PFR) models to complement the homogenous ignition examples present in the earlier versions. To exploit the massive parallelism available from modern computing platforms, the current software interface is designed to evaluate samples in parallel, which enables large scale parametric studies, e.g. for sensitivity analysis and model calibration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing the Influence of Binding Motifs on Electron Transfer and Recombination Kinetics for CdSe Quantum Dots Functionalized with a Modified Viologen

Anchoring of molecules to the surfaces of semiconductor nanocrystals (NCs) presents an opportunity to leverage the precise synthetic tunability of molecular function and the remarkable light harvesting properties of NCs to drive photochemical reactions. However, charge transfer between the two species depends not only on the energy level alignments but also on the details of their binding interactions, which are difficult to probe. Here, in this work, we characterize the binding between CdSe quantum dots (QDs) and a new phosphonated derivative of the electron acceptor methyl viologen, designed to attach to the QD surface via the phosphonate group. We use isothermal titration calorimetry to probe the thermodynamics of the QD–molecule interaction and use the parameters determined therein to analyze transient absorption spectroscopy measurements of forward and back electron transfer from QDs to the viologen. We find that the ligand-like phosphonate binding leads to an electron-transfer rate constant that is 3 orders of magnitude smaller than that for the face-on binding of the bipyridine ring of methyl viologen. Back electron transfer is also significantly slower in the derivative. Interestingly, a minor fraction of the phosphonated derivative also binds in the face-on configuration, with similar forward and back electron transfer kinetics as methyl viologen. Numerical simulations show that the ligand-like binding will lead to significantly improved quantum yields of photocatalysis over a wide range of reaction rates. By independently characterizing binding thermodynamics and charge transfer kinetics, this work reveals how the complexities underlying electron transfer at the NC–molecule interface determine photocatalytic outcomes. This work also represents a step toward controlling forward and back electron transfer kinetics via rational molecular design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The mechanics of nucleation and growth and the surface tensions of active matter

Homogeneous nucleation, a textbook transition path for phase transitions, is typically understood on thermodynamic grounds through the prism of classical nucleation theory. However, recent studies have suggested the applicability of classical nucleation theory to systems far from equilibrium. Here, in this article, we formulate a purely mechanical perspective of homogeneous nucleation and growth, elucidating the criteria for the properties of a critical nucleus without appealing to equilibrium notions. Applying this theory to active fluids undergoing motility-induced phase separation, we find that nucleation proceeds in a qualitatively similar fashion to equilibrium systems, with concepts such as the Gibbs–Thomson effect and nucleation barriers remaining valid. We further demonstrate that the recovery of such concepts allows us to extend classical theories of nucleation rates and coarsening dynamics to active systems upon using the mechanically derived definitions of the nucleation barrier and surface tensions. Three distinct surface tensions—the mechanical, capillary, and Ostwald tensions—play a central role in our theory. While these three surface tensions are identical in equilibrium, our work highlights the distinctive role of each tension in the stability of active interfaces and the nucleation and growth of motility-induced phases.

Capillary waves↗

A thermodynamic model of integrated liquid-to-liquid thermoelectric heat pump systems

Thermoelectric (TE) heat pumps (TEHPs) are advantageous for heating and cooling in various applications because of their modularity and simple design. A TEHP system includes the TE modules with p- and n-type materials bonded to substrates, plus heat exchangers, thermal interfaces to the heat exchangers, and heat transfer fluids. Although modeling an individual TE module has been extensively studied, limited studies have reported performance at the larger system-level. Furthermore, no prior study has addressed the impact of temperature-dependent TE material properties (e.g., electric resistivity, thermal conductivity, and Seebeck coefficient) on overall heat-pump-system-level performance. Here, this work presents a mathematical model for TEHP system performance based on Goldsmid's approach for TE material performance, “effective” TE material properties, Gnielinski's correlation for convective heat transfer, and thermal balance theory for a heat exchange network. This combined approach provides an accurate model of the liquid-to-liquid TEHP system. Three different approaches—one empirical, one based on the manufacturer's specifications, and one drawn from the literature—were then used to determine values for TE material properties. The first two methods treated properties as constants, while the last approach treated properties as surface-temperature-based functions. Finally, experimental TEHP data was used to validate the models, all with relative absolute deviations of approximately 10% when predicting heating capacity and 10%–25% when forecasting cooling capacity up to a 30 K surface temperature lift. The results demonstrated that, at the TEHP system level, the TE material properties could be treated as constants, avoiding solver iterations and reducing the performance uncertainty by up to 95%.

42 ENGINEERING↗

Understanding the interface interaction between U3Si2 fuel and SiC cladding

Abstract Triuranium disilicide (U 3 Si 2 ) fuel with silicon carbide (SiC) composite cladding is being considered as an advanced concept/accident tolerant fuel for light water reactors thus, understanding their chemical compatibility under operational and accident conditions is paramount. Here we provide a comprehensive view of the interaction between U 3 Si 2 and SiC by utilizing density functional theory calculations supported by diffusion couple experiments. From the calculated reaction energies, we demonstrate that triuranium pentasilicide (U 3 Si 5 ), uranium carbide (UC), U 20 Si 16 C 3 , and uranium silicide (USi) phases can form at the interface. A detailed study of U 3 Si 2 and SiC defect formation energies of the equilibrated materials yielding the interfacial phases U 20 Si 16 C 3 , U 3 Si 5 and UC reveal a thermodynamic driving force for generating defects in both fuel and cladding. The absence of either the U 3 Si 2 or SiC phase, however, causes the defect formation energies in the other phase to be positive, removing the driving force for additional interfacial reactions. The diffusion couple experiments confirm the conclusion with demonstrated restricted formation of U 3 Si 5 , UC, and U 20 Si 16 C 3 /USi phases at the interface. The resulting lack of continuous interaction between the U 3 Si 2 and SiC, reflects the diminishing driving force for defect formation, demonstrating the substantial stability of this fuel-cladding system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Distinct Fracture Mineralogy That is Out of Equilibrium With Modern Groundwaters Provides Important Context for Subsurface Life

Rock fracture surfaces in the crust are essential habitat for microorganisms. Fracture‐groundwater interfaces provide physical substrates for biofilm growth and are sources of carbon, nutrients, and electron donors and acceptors. To better understand geochemical processes impacting fracture surfaces and the subsurface microbiome, we identified fractures in archived rock cores from the Soudan formation, which is known to host saline groundwaters and isolated microbial communities dependent on rock‐water interactions. Cores with open fractures were thin sectioned and studied via electron microprobe and synchrotron X‐ray fluorescence microprobe. Most fracture surfaces had mineralogy distinct from that of the bulk rock. Chlorite minerals were abundant on fracture surfaces and had elemental compositions suggesting deposition during late‐stage hydrothermal alteration. Fracture‐lining chlorites likely limit access to iron oxide and sulfide minerals that are active in subsurface biogeochemical cycles. Calcium‐rich rinds were also observed along fracture edges. These rinds were too thin and poorly ordered to be identified via light microscopy or X‐ray diffraction; however, Ca K‐edge micro‐X‐ray absorption near‐edge structure spectroscopy identified them as carbonates, minerals not observed in the bulk rock. Thermodynamic modeling shows that carbonate precipitation is largely unfavorable in Soudan groundwaters, indicating that fracture edge conditions differed from those in modern water samples. Because of the low carbon concentrations in Soudan groundwaters, carbonate rinds likely play an important role in subsurface carbon cycling and may mark fracture surfaces that once hosted biofilms. Overall, this study suggests that fracture alteration can both play an active role in and suppress rock‐water interactions essential to subsurface life.

36 MATERIALS SCIENCE↗

Lithium oxidation and electrolyte decomposition at Li-metal/liquid electrolyte interfaces

In this work, we examine the evolution of events occurring when a Li metal surface is in contact with a 2 M solution of a Li salt in a solvent or mixture of solvents, via classical molecular dynamics simulations with a reactive force field allowing bond breaking and bond forming. The main events include Li oxidation and electrolyte reduction along with expansion of the Li surface layers forming a porous phase that is the basis for the formation of the solid-electrolyte interphase (SEI) components. Nucleation of the main SEI components (LiF, Li oxides, and some organics) is characterized. The analysis clearly reveals the details of these physical–chemical events as a function of time, during 20 nanoseconds. The effects of the chemistry of the electrolyte on Li oxidation and dissolution in the liquid electrolyte, and SEI nucleation and structure are identified by testing two salts: LiPF 6 and LiCF 3 SO 3 , and various solvents including ethers and carbonates and mixtures of them. The kinetics and thermodynamics of Li 6 F, the core nuclei in the LiF crystal, are studied by analysis of the MD trajectories, and via density functional theory calculations respectively. The SEI formed in this computational experiment is the “native” film that would form upon contact of the Li foil with the liquid electrolyte. As such, this work is the first in a series of computational experiments that will help elucidate the intricate interphase layer formed during battery cycling using metal anodes.

25 ENERGY STORAGE↗

Understanding the Mechanism of Secondary Cation Release from the (001) Surface of Li(Ni 1/3 Mn 1/3 Co 1/3 )O 2 : Insights from First-Principles

The transformations of complex metal oxides in aqueous settings must be studied to form a chemical understanding of how technologically relevant nanomaterials impact the environment upon disposal. Owing to the inherent heterogeneity and structural complexity of the ternary intercalation material Li(Ni x Mn y Co 1-x-y )O 2 (NMC), the mechanisms of chemical processes at the solid–water interfac e are challenging to model. Here, density functional theory (DFT) + solvent ion methodology is used to study the energetics of stepwise release of two surface metals following unique pathways. Further, the study spans different combinations of metal removal and also considers unique patterns of defects formed by modeling the NMC surface in supercells. The approach here also considers the equilibration of the surface with the surroundings between successive metal removals. A key finding is that a second metal removal prefers to proceed at a metal lattice site adjacent to the initial defect, and this is attributed in part to how the resulting slab with two metal vacancies maintains the most antiferromagnetic couplings between the remaining Ni/Mn.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrically Powered High-Salinity Brine Separation Using Dimethyl Ether

Dewatering highly saline aqueous streams, from mining and geothermal leachates to industrial wastewater, is essential for effective resource recovery and safe disposal. Membraneless water extraction (MWE) uses a low-polarity solvent to separate water from concentrated aqueous solutions. In this study, we design a new MWE that uses dimethyl ether (DME) to selectively extract water from high-salinity brines, leveraging the volatility of DME to achieve rapid solvent recovery. By separating water and dissolved salts at a liquid–liquid interface, MWE minimizes the deleterious effects of scaling on vulnerable membrane and heat exchanger surfaces, reducing the need for extensive pretreatment and expensive materials. We begin by developing a computational framework for a multistage counterflow liquid–liquid contactor, which extracts water into DME, coupled with a multistage solvent regenerator that uses vapor compression to efficiently separate the desalinated water from the DME extractant. Excess Gibbs free energy and equation of state frameworks are used to model fluid phase equilibria in water–DME–sodium chloride (NaCl) mixtures, with interaction parameters estimated from experimental data. Incorporating equilibrium calculations into a system-scale computational model, we examine the performance of MWE using DME for the first time. Our analysis demonstrates that MWE can concentrate seawater desalination brine (>1.0 mol NaCl kg –1 ) to zero-liquid discharge salinities, with an energy consumption of under 50 kW h per m 3 of water extracted with a solvent recovery ratio greater than 99.9%. We highlight the importance of staging the vapor compression process to simultaneously minimize energy consumption while enabling brine concentration and product water solvent contamination. Finally, the thermodynamic framework developed here allows for the robust evaluation of new MWE solvents and systems for critical brine concentration and fractional precipitation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Size-Dependent Adsorption and Adhesion Energetics of Ag Nanoparticles on Graphene Films on Ni(111) by Calorimetry

Interest in the use of carbon supports for late transition metal nanoparticle catalysts has expanded rapidly due to the increasing importance of electrocatalysts for clean energy and environmental technologies and the use and storage of renewable electricity. Compared to oxide supports, almost nothing is known about the effect of metal nanoparticle size on the energies of the metal atoms within carbon-supported nanoparticles, yet these energies are crucial for understanding their surface reactivity and sintering kinetics. Here, the growth morphology and adsorption energetics of vapor-deposited Ag onto clean graphene/Ni(111) surfaces have been studied using a combination of single-crystal adsorption calorimetry (SCAC) and He + low-energy ion scattering (LEIS). The differential heat of Ag adsorption is 207 kJ/mol for making ~30 atom Ag particles on graphene terraces at 100 K and 16 kJ/mol higher for making ~9 atom Ag clusters at defect sites at the same temperature. The heat of adsorption increases rapidly with Ag coverage as 3D Ag nanoparticles nucleate and grow in size, asymptotically reaching within 5 kJ/mol of the bulk Ag sublimation enthalpy (285 kJ/mol) by 2 ML. The heats of adsorption and Ag nanoparticle densities from LEIS (~10 16 /m 2 ) were combined to provide the Ag/graphene adhesion energy (E adh = 1.8 J/m 2 in the large-particle limit) and the Ag chemical potential (μ) versus effective particle diameter (D). The Ag chemical potential was well-fitted by μ(D) = (3γ v /M – E adh )(1 + (1.5 nm)/D)(2V m /D), where γ v /M is the surface energy of bulk Ag and V m is its molar volume. The same equation is known to fit similar data for late transition metals on clean surfaces of metal oxide single crystals. The adhesion energy of Ag measured here on graphene falls within the wide range measured for Ag on those oxide surfaces and is almost as large as on the oxide that binds Ag particles most strongly, namely CeO 2 (111), which is well-known to be very effective at resisting catalyst deactivation by metal sintering. Furthermore, these results imply that carbon supports will be effective at resisting sintering and that Ag particles smaller than 6 nm on graphene will bind small adsorbed reaction intermediates more weakly than supports with weaker adhesion to Ag, like MgO(100).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics

For multilayer materials in thin substrate systems, interfacial failure is one of the most challenges. The traction-separation relations (TSR) quantitatively describe the mechanical behavior of a material interface undergoing openings, which is critical to understand and predict interfacial failures under complex loadings. However, existing theoretical models have limitations on enough complexity and flexibility to well learn the real-world TSR from experimental observations. A neural network can fit well along with the loading paths but often fails to obey the laws of physics, due to a lack of experimental data and understanding of the hidden physical mechanism. In this paper, we propose a thermodynamic consistent neural network (TCNN) approach to build a data-driven model of the TSR with sparse experimental data. The TCNN leverages recent advances in physics-informed neural networks (PINN) that encode prior physical information into the loss function and efficiently train the neural networks using automatic differentiation. We investigate three thermodynamic consistent principles, i.e., positive energy dissipation, steepest energy dissipation gradient, and energy conservative loading path. All of them are mathematically formulated and embedded into a neural network model with a novel defined loss function. A real-world experiment demonstrates the superior performance of TCNN, and we find that TCNN provides an accurate prediction of the whole TSR surface and significantly reduces the violated prediction against the laws of physics.

Zhang, Jiaxin↗

Understanding Solid Electrolyte Interphase Nucleation and Growth on Lithium Metal Surfaces

Experiments and theory are needed to decode the exact structure and distribution of components of a passivation layer formed at the anode surface of Li metal batteries, known as the Solid Electrolyte Interphase (SEI). Due to the inherent dynamic behavior as well as the lithium reactivity, the SEI structure and its growth mechanisms are still unclear. This study uses molecular simulation and computational chemistry tools to investigate the initial nucleation and growth dynamics of LiOH and Li2O that provide us with thermodynamics and structural information about the nucleating clusters of each species. Following the most favorable pathways for the addition of each of the components to a given nascent SEI cluster reveals their preferential nucleation mechanisms and illustrates different degrees of crystallinity and electron density distribution that are useful to understand ionic transport through SEI blocks.

25 ENERGY STORAGE↗

Physics-Informed Neural Networks for Heat Transfer Problems

Abstract Physics-informed neural networks (PINNs) have gained popularity across different engineering fields due to their effectiveness in solving realistic problems with noisy data and often partially missing physics. In PINNs, automatic differentiation is leveraged to evaluate differential operators without discretization errors, and a multitask learning problem is defined in order to simultaneously fit observed data while respecting the underlying governing laws of physics. Here, we present applications of PINNs to various prototype heat transfer problems, targeting in particular realistic conditions not readily tackled with traditional computational methods. To this end, we first consider forced and mixed convection with unknown thermal boundary conditions on the heated surfaces and aim to obtain the temperature and velocity fields everywhere in the domain, including the boundaries, given some sparse temperature measurements. We also consider the prototype Stefan problem for two-phase flow, aiming to infer the moving interface, the velocity and temperature fields everywhere as well as the different conductivities of a solid and a liquid phase, given a few temperature measurements inside the domain. Finally, we present some realistic industrial applications related to power electronics to highlight the practicality of PINNs as well as the effective use of neural networks in solving general heat transfer problems of industrial complexity. Taken together, the results presented herein demonstrate that PINNs not only can solve ill-posed problems, which are beyond the reach of traditional computational methods, but they can also bridge the gap between computational and experimental heat transfer.

Engineering↗

Validating first-principles molecular dynamics calculations of oxide/water interfaces with x-ray reflectivity data

Metal oxide/water interfaces play a crucial role in many electrochemical and photocatalytic processes, such as photoelectrochemical water splitting, the creation of fuel from sunlight, and electrochemical CO 2 reduction. First-principles electronic structure calculations can reveal unique insights into these processes, such as the role of the alignment of the oxide electronic energy levels with those of liquid water. An essential prerequisite for the success of such calculations is the ability to predict accurate structural models of these interfaces, which in turn requires careful experimental validation. Here we report a general, quantitative validation protocol for first-principles molecular dynamics simulations of oxide/aqueous interfaces. The approach makes direct comparisons of interfacial x-ray reflectivity (XR) signals from experimental measurements and those obtained from ab initio simulations with semilocal and van der Waals functionals. The protocol is demonstrated here for the case of the Al 2 O 3 (001)/water interface, one of the simplest oxide/water interfaces. We discuss the technical requirements needed for validation, including the choice of the density functional, the simulation cell size, and the optimal choice of the thermodynamic ensemble. Our results establish a general paradigm for the validation of structural models and interactions at solid/water interfaces derived from first-principles simulations. Furthermore, while there is qualitative agreement between the simulated structures and the experimental best-fit structure, direct comparisons of simulated and measured XR intensities show quantitative discrepancies that derive from both bulk regions (i.e., alumina and water) as well as the interfacial region, highlighting the need for accurate density functionals to properly describe interfacial interactions. Our results show that XR data are sensitive not only to the atomic structure (i.e., the atom locations) but also to the electron-density distributions in both the substrate and at the interface.

36 MATERIALS SCIENCE↗

Nickel hydroxide–nickel carbonate competitive growth on carbonate surfaces

The thermodynamic and kinetic factors controlling the competitive heterogeneous nucleation and growth of ubiquitous metal carbonate and hydroxide phases are poorly understood. In this work, calcite (CaCO 3 ) and magnesite (MgCO 3 ) powders were reacted with NiCl 2 (0–600 μM) for 7 days at 22 °C and 5 °C. The reacted powders were analyzed with X-ray photoelectron spectroscopy (XPS), scanning electron microscopy, and energy-dispersive X-ray spectroscopy to characterize the Ni surface precipitates formed. Evidence from these techniques pointed to the formation of mixed Ni carbonate-Ni hydroxide amorphous surface precipitates. On calcite, XPS detected primarily Ni(OH) 2 despite the initial solutions being more supersaturated with respect to gaspéite (NiCO 3 ) than to theophrastite (Ni(OH) 2 ) by a factor of 17–18. In contrast, NiCO 3 was the dominant component detected by XPS on magnesite in the same conditions. Decreasing the temperature had the effect of increasing the proportion of NiCO 3 to the detriment of Ni(OH) 2 . The experimental observations were consistent with low lattice/cation size mismatch favoring NiCO 3 nucleation and temperature most influencing Ni(OH) 2 nucleation. Comparison to previous work on Co-reacted powders indicated the differences in lattice/cation size mismatch and/or water exchange rate impacted the composition of the surface precipitates more than the relative thermodynamic stabilities of the competing minerals. This work explored the heterogeneous growth regime of Ni carbonate and hydroxide phases on carbonate surfaces and shed light on the factors that control the competition between surface precipitates when mineral surfaces are in contact with aqueous solutions supersaturated with respect to multiple mineral phases. In conclusion, these results contribute to geochemists’ efforts toward interpreting data from geochemical systems with elevated Ni concentrations, improving Ni environmental remediation and recovery strategies, and predicting the fate and transport of Ni in geochemical systems.

Heterogeneous nucleation↗

Sensitivity of magnetohydrodynamic simulations of Joule-heated conductors to the vaporization curve in equations of state

Magnetohydrodynamic (MHD) simulations of electrically exploded aluminum and copper rods demonstrate a technique to validate equations of state (EOS) for rapidly Joule-heated conductors. The balance of internal and magnetic forces at the conductor-insulator interface drives the metal there along the vaporization phase boundary. Variations between critical points and vaporization curves in existing models predict differing densities and temperatures in MHD simulations for these models. Here, the inclusion of Maxwell constructs in the liquid-vapor biphase region of the EOS caused the rod surface to vaporize earlier in time than unmodified tables with van der Waals loops. Velocimetry of recent experiments is used to validate the location of the vaporization curve in existing EOS models and differentiate between the vapor dome treatments. Dielectric coatings applied to the metal surface restricted the conductor’s expansion and diverted the metal into the warm dense matter regime.

36 MATERIALS SCIENCE↗