Stable and Efficient Single-Atom Zn Catalyst for CO2 Reduction to CH4
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This study investigates multiphysics block preconditioners that are critical in devising scalable Newton–Krylov iterative solvers for longer time-scale fully implicit fluid plasma models. The specific model of interest is the visco-resistive, low Mach number, compressible magnetohydrodynamics (MHD) model. This model describes the dynamics of conducting fluids in the presence of electromagnetic fields and can be used to study aspects of astrophysical phenomena, important science and technology applications, and basic plasma physics. The specific application of interest that motivates this study is the macroscopic simulation of longer time-scale stability and disruptions of magnetic confinement fusion devices, specifically the ITER Tokamak. The computational solution of the governing balance equations for mass, momentum, heat transfer, and magnetic induction for resistive MHD systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena as well as the significant range of time and length scales that the interactions of these physical mechanisms produce. To handle the range of time and spatial scales of interest, a fully implicit unstructured variational multiscale finite element formulation is employed. For the scalable solution of the Newton linearized systems, fully coupled block preconditioners are designed to leverage algebraic multigrid subsolves. In conclusion, results are presented for the strong and weak scaling of the method as well as the robustness of these techniques for a large range of Lundquist numbers.
The H-Canyon facility will be dissolving unirradiated stainless-steel clad Fast Critical Assembly (FCA) fuel in HNO3 and neutralizing the resulting solution with 50 wt% NaOH with no recovery operations prior to transfer to the Concentration, Storage, and Transfer Facility (CSTF). There are two types of FCA fuel, including a Pu-Al metal alloy and a mixed U and Pu oxide. H-Canyon anticipates dissolving 16 batches of the metal fuel and two batches of the oxide fuel. Potassium fluoride will be added to the dissolver solution at 0.05 M to promote dissolution. Gadolinium will be added after the dissolution as a thermal neutron poison for criticality control. H-Canyon requested that SRNL evaluate Gd:239Pu equivalent (239PuEq) ratios of 1:1 and 10:1. The neutralization process precipitates metals including actinides, Gd, and cladding components resulting in a slurry. Caustic neutralization is a routine H-Canyon operation, but the FCA dissolver solution will be unique relative to solutions that are typically processed due to the stainless-steel components, high HNO3 concentration of ~8.5 M, and an initial Pu concentration of up to 4 g/L. Previous neutralization studies have been performed for Pu containing solutions but at less than half the initial Pu concentration and much lower initial HNO3 concentrations. Experimental neutralizations targeted a final free hydroxide (OH-) concentration of 0.6 M as this was anticipated to be the final endpoint, but H-Canyon now expects the endpoint to be 1.2 M OH-. The purpose of this study was to characterize the distribution of the actinide, Gd, and cladding components between the precipitate and supernate, determine if the slurry will back up in the header during the transfer to the CSTF, and determine if solids will settle in the pipeline during the transfer.
In this study, an energy and highly time efficient, cost effective, and scalable forward osmosis (FO) composite polyvinylidene fluoride (PVDF) membrane is developed to concentrate lithium chloride recovered from naturally occurring geothermal brine resources. Dense thin robust defect-free Kynar-PVDF membranes are fabricated on porous PVDF hollow fiber supports. Various membrane fabrication parameters such as membrane thickness, coating solution concentration, cross-linker concentration, and curing temperature are studied to develop a defect-free dense membrane. Advanced characterization tools such as FIB-SEM, Raman, FTIR spectroscopy, and XRD are used to study the surface and cross-sectional morphology, chemistry of crosslinking, crystallinity and chemical structure of the dense PVDF membrane. FO is utilized to concentrate LiCl in the solution from 36 to 175 g L -1 with an average water transfer rate of 0.450 L m -2 h -1 (LMH) at 85 °C. Furthermore, the membrane showed stable performance for more than 550 h while maintaining the purity of the concentrated lithium chloride solution of >99.99 wt%. Overall, the results suggest that the FO-based technology is an innovative, time and energy efficient approach compared to the conventional technologies for concentration of battery grade LiCl for application in lithium ion batteries and other clean energy technologies.
The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.
While electric fields primarily result in migration of charged species in electrolytic solutions, the solutions are dynamically heterogeneous. Solvent molecules within the solvation shells of the cation will be dragged by the field while free solvent molecules will not. Here we combine electrophoretic NMR measurements of ion and solvent velocities under applied electric fields with molecular dynamics simulations to interrogate different solvation motifs in a model liquid electrolyte. Measured values of the cation transference number $(t^0_+)$ agree quantitatively with simulation-based predictions over a range of electrolyte concentrations. Solvent-cation interactions strongly influence the concentration-dependent behavior of $t^0_+$. We identify a critical concentration at which most of the solvent molecules lie within solvation shells of the cations. The dynamic heterogeneity of solvent molecules is minimized at this concentration where $t^0_+$ is approximately equal to zero.
The degradation of archetype organic photovoltaics comprising both vacuum and solution-deposited bulk heterojunction active regions is investigated and quantified using a theory based on detailed balance, which relates the open-circuit voltage to the efficiency of charge transfer state emission. To describe this relationship, we account for the difference between electroluminescent external quantum efficiency and the charge transfer emission efficiency. Here, an empirical factor, m, is introduced to distinguish between nonradiative defect sites both within, m = 1, and outside, m >1, of the photoactive heterojunction. The m-factor is used to determine the primary sources of degradation for archetype solution- and vacuum-processed material systems. We conclude that degradation occurs primarily within the donor–acceptor heterojunction for the vacuum-processed devices (where m = 1.020 ± 0.002) and outside of the photoactive heterojunction for the solution-processed devices studied, both with and without an anode buffer layer (where m = 2.93 ± 0.09 and m = 1.90 ± 0.01, respectively).
Membranes for post-combustion CO 2 capture are required to have a high CO 2 permeance due to the limited driving force. For facilitated transport membranes synthesized with polyvinylamine (PVAm), a defect-free selective layer of <200 nm is usually required to render sufficient permeance with high CO 2 /N 2 selectivity. In order to meet such a demand through the knife-coating process, the coating solution needs to have a high viscosity at a relatively low concentration to minimize its penetration into the substrate. The demand was met by synthesizing PVAm with an ultrahigh molecular weight (MW) via inverse emulsion polymerization (IEP) in this study. Compared to solution polymerization, IEP isolates the reaction in inverse micelles suspended in a continuous organic phase, which allows excellent dissipation of the heat generated by the reaction and reduces gel formation drastically. The polymerization parameters, including monomer concentration, initiator concentration, and reaction temperature, were investigated to obtain the optimal MW of PVAm for membrane performance. As compared to solution polymerization, IEP enhanced the MW of PVAm from 1.2 to 12.7 MDa, which minimized the penetration of the coating solution into the substrate and hence the extra mass transfer resistance. The effect of MW and degree of hydrolysis of PVAm on the membrane transport properties were studied. Furthermore, by employing PVAm with a MW of 12.7 MDa to strengthen the polymer matrix, the loading of piperazine glycinate in the membrane was increased up to 85 wt.%. In conclusion, the resultant membrane achieved a CO 2 permeance of 839 GPU and a CO 2 /N 2 selectivity of 161 at the typical flue gas temperature of 57°C.
Linear cyanide-bridged polymetallic complexes, which undergo photoinduced metal-to-metal charge transfer, represent prototypical systems for studying long-range electron-transfer reactions and understanding the role played by specific solute–solvent interactions in modulating the excited-state dynamics. Here, to tackle this problem, while achieving a statistically meaningful description of the solvent and of its relaxation, one needs a computational approach capable of handling large polynuclear transition-metal complexes, both in their ground and excited states, as well as the ability to follow their dynamics in several environments up to nanosecond time scales. Here, we present a mixed quantum classical approach, which combines large-scale molecular dynamics (MD) simulations based on an accurate quantum mechanically derived force field (QMD-FF) and self-consistent QMD polarized point charges, with IR and UV–vis spectral calculations to model the solvation dynamics and optical properties of a cyano-bridged trinuclear mixed-valence compound (trans-[(NC) 5 Fe III (μ-CN)Ru II (pyridine) 4 (μ-NC)Fe III (CN) 5 ] 4– ). We demonstrate the reliability of the QMD-FF/MD approach in sampling the solute conformational space and capturing the local solute–solvent interactions by comparing the results with higher-level quantum mechanics/molecular mechanics (QM/MM) MD reference data. The IR spectra calculated along the classical MD trajectories in different solvents correctly predict the red shift of the CN stretching band in the aprotic medium (acetonitrile) and the subtle differences measured in water and methanol, respectively. By explicitly including the solvent molecules around the cyanide ligands and calculating the thermal averaged absorption spectra using time-dependent density functional theory calculations within the Tamm–Dancoff approximation, the experimental solvatochromic shift is quantitatively reproduced going from water to methanol, while it is overestimated for acetonitrile. This discrepancy can likely be traced back to the lack of important dispersion interactions between the solvent cyano groups and the pyridine substituents in our micro solvation model. The proposed protocol is applied to the ground state in water, methanol, and acetonitrile and can be flexibly generalized to study excited-state nonequilibrium solvation dynamics.
Solar harvesting devices using dyes convert the sun's energy to usable forms. The photophysics involved are generally investigated using time-resolved spectroscopic experiments with femtosecond to nanosecond resolution. We show that a kinetic framework constructed from transient and linear absorption measurements of metal-ligand charge transfer states for a set of ruthenium complexes in solution can be used to simulate the steady-state dynamics of dyes adsorbed on a substrate under diffuse solar radiation. Even though the intensity of sunlight is relatively low, double excitations to higher excited states can occur. The steady-state populations show that the dyes' triplet state is the main species present besides the ground state. While small, these persistent excited populations can influence reactivity over the extended periods of time that the systems operate. The results show that non-radiative and optical events (dye -1 s -1 ) within the singlet manifold and from the triplet state exhibit a dependence on ligand substituents.
The formation and growth of plasma kernels generated via nano-second mode-beating laser pulses is investigated here via a non-equilibrium self-consistent computational model. Chemically reactive Navier–Stokes equations are used to describe the hydrodynamics, and non-equilibrium effects are taken into account with a two-temperature model. Inverse Bremsstrahlung and multiphoton ionization are included self-consistently in the model via a coupled solution of the plasma governing equations and the radiative transfer equation (that describes the laser beam propagation and attenuation). A self-consistent approach (despite carrying additional challenges) minimizes the empiricism and it allows for a more accurate description since it prevents both the utilization of artificial plasma seeds to trigger the breakdown and the implementation of tuning parameters to simulate the laser-energy deposition. The advantages of this approach are confirmed by the good agreement between the numerically predicted and the experimentally measured plasma boundary evolution and absorbed energy. This also holds true for the periodic plasma kernel structures that, as suggested by the experiments and confirmed by the simulations presented here, are connected to the modulating frequency.
Complex system requirements can often lead to a situation wherein no single product or platform can provide a solution. In these cases, a solution integrating the features of multiple products and platforms is needed. Recently, a program sponsor required discontinued use of a third-party Security Assertion Markup Language Identity Provider that was being used to implement a two-factor authentication (2FA) solution that fully integrated with Pulse Connect Secure (PCS). PCS alone could not provide the features necessary to meet all the requirements of a new 2FA solution. The challenge was to leverage the features of additional platforms to design an integrated solution to meet all requirements. This paper presents a solution that integrates the features of PCS, Apache HyperText Transfer Protocol Server, and a custom application that meets all requirements, including a requirement to defend against Uniform Resource Locator manipulation as means to gain unauthorized access to backend applications.
Mixed-valent iron oxide minerals, such as magnetite (Fe(II)(Fe(III)) 2 O 4 ), are an important source of solid-state ferrous iron (Fe(II)) that can impact the speciation and transport of electron accepting contaminants in the Earth’s subsurface, such as radioactive pertechnetate ( 99 Tc(VII)O 4 − ). However, when oxidizing conditions are encountered, structural Fe(II) at the mineral surface is consumed yielding a maghemite (γ-Fe(III) 2 O 3 )-like layer that limits further electron transfer. This oxidized surface layer can be recharged back to the original Fe(II)/(III) ratio by re-exposure to reducing conditions, i.e., aqueous solutions containing Fe 2+ . However, for substituted magnetite (Fe 3−x M x O 4 , M = transition metal cation), the extent of this redox recyclability is unclear. Here, we examine oxidation and recharge for titanomagnetite (Fe 3−x Ti x O 4 ) nanoparticles, where the Fe(II)/Fe(III) ratio varies by the amount of Fe(II) required to charge balance the titanium (Ti(IV)) substituted into the structure. The nanoparticles were synthesized by aqueous precipitation from a solution containing ferrous, ferric and titanium chloride at room temperature. Transmission electron microscopy combined with electron energy loss spectroscopy revealed that rapid precipitation formed core–shell-like nanoparticles consisting of a hyperstoichiometric magnetite core, with Ti(IV) and charge balancing Fe(II) enriched at the surface. This surface enrichment made Fe(II) more available for electron transfer reactions with redox active solution species. Examination of oxidation by H 2 O 2 followed by recharge with aqueous Fe 2+ indicates recyclability of reducing equivalents in the nanoparticles, yielding a core recrystallized to stoichiometric magnetite and a shell bearing excess Fe(II) to charge balance the substituted Ti(IV). The recharged particles are shown to have restored redox reactivity with 99 Tc(VII)O 4 − resulting in reduction to 99 Tc(IV)O 2 and oxidation of the structural Fe(II) to Fe(III).
The present work concerns the transferability of coarse-grained (CG) modeling in reproducing the dynamic properties of the reference atomistic systems across a range of parameters. In particular, we focus on implicit-solvent CG modeling of polymer solutions. The CG model is based on the generalized Langevin equation, where the memory kernel plays the critical role in determining the dynamics in all time scales. Thus, we propose methods for transfer learning of memory kernels. The key ingredient of our methods is Gaussian process regression. By integration with the model order reduction via proper orthogonal decomposition and the active learning technique, the transfer learning can be practically efficient and requires minimum training data. Through two example polymer solution systems, we demonstrate the accuracy and efficiency of the proposed transfer learning methods in the construction of transferable memory kernels. The transferability allows for out-of-sample predictions, even in the extrapolated domain of parameters. Built on the transferable memory kernels, the CG models can reproduce the dynamic properties of polymers in all time scales at different thermodynamic conditions (such as temperature and solvent viscosity) and for different systems with varying concentrations and lengths of polymers.
Many semiconductor devices (e.g., light emitting diodes and photovoltaics) utilize heterojunctions of doped and undoped layers or depend on gradients of electronic doping to control charge transport. Understanding of the formation and stability of gradients in doping requires an understanding of diffusion of dopants and the complex changes in polymer properties that arise during doping. Conjugated polymers can be electrically doped by strong acids, but the details of the reaction mechanism and subsequent stability are not understood. Here, we show a clear kinetic isotope effect in the doping of thin films of poly(3-hexylthiophene) (P3HT) by bis(trifluoromethane)sulfonimide (HTFSI) from solution indicating that this doping process is limited by proton transfer to the polymer. Complementary X-ray photoelectron spectroscopy and dynamic secondary ion mass spectrometry (DSIMS) depth profiling of dopant concentrations show definitive evidence of dopant enrichment at the P3HT surface. These surface-limited concentration profiles suggest that diffusivity of dopants vary inversely with dopant concentration due to doping-induced changes to the structure of the conjugated polymer.
The removal of radiocesium from Hanford tank waste supernate is a critical step in preparing feed for low-activity waste immobilization. This study evaluated cesium ion exchange performance using crystalline silicotitanate (CST) media in a series of tests designed to evaluate the influence of waste matrix variability on capacity and kinetics. Tank waste supernate subsampled from five Hanford double-shell tanks encompassed a range of sodium, hydroxide, nitrate, and nitrite concentrations in order to assess the impact of feed variability on the performance of the ion exchange system. Both equilibrium and dynamic ion exchange tests were conducted to quantify cesium distribution coefficients and breakthrough behavior under prototypic operating conditions. Results indicated that effective cesium capacity varied by up to a factor of five across the matrices tested, with higher sodium concentrations significantly reducing uptake. Kinetic behavior was similarly matrix-dependent, with solution viscosity contributing to a twofold variation in mass-transfer rates. These results demonstrate the strong dependence of CST ion exchange performance on waste composition and must be incorporated into predictive models for future treatment system design and optimization.
Electroactive coatings based on non-conjugated redox-active polymers have increased in popularity with the development of thin film organic batteries. Here, control over coating deposition, redox-activity, and ion transport are key to improving their energy storage performance. In this work, the synthesis, solution state electrochemical characterization, and layer-by-layer (LbL) assembly of a nitroxide-based polycation and polyanion are presented. Solution state electrochemical characterization indicates that the rate of electron transfer for the nitroxide polyanion is much higher as compared to the nitroxide polycation. LbL thin films of the nitroxide polyanion and nitroxide polycation are assembled, demonstrating linear growth and tunable thickness (28 nm/layer pair). This work confirms that the ion transport mechanism of the LbL films during the redox reaction is influenced depending on the charge of the terminating layer, where the nitroxide polyanion can participate in self-doping, which leads to a contribution from cation transport. The nitroxide polyanion-terminated film also exhibits a higher capacity and a slightly reduced charge transfer resistance. However, it was also observed that a more pronounced capacity fade occurred for the polyanion-terminated film than the polycation-terminated film. Taken together, this highlights how oppositely charged radical-containing polyelectrolytes can form electroactive coatings for possible applications in energy storage or sensing.
This research is focused on applying the NLem method to the full thermal radiative transfer (TRT) equations in the context of a Monte Carlo solution strategy. A framework has been developed for obtaining a solution to the TRT equations using the nonlinear elimination method (NLem) method. Current efforts are focused of the development and verification of the required Monte Carlo algorithm, diffusion algorithm, and material energy solver. Once all three pieces have been verified, the algorithms will then be coupled into a fully functioning method for applying NLem to the TRT equations.