Chong, Lina; Gao, Guoping; Wen, Jianguo; Li, Haixia; Xu, Haiping; Green, Zach; Sugar, Joshua D.; Kropf, A.J.; Xu, Wenqian; Lin, Xiao M.; Xu, Hui; Wang, Lin W.; Di Liu, Jia
Discovery of earth-abundant electrocatalysts to replace iridium for the oxygen evolution reaction (OER) in a proton exchange membrane water electrolyzer (PEMWE) represents a critical step in reducing the cost for green hydrogen production. We report a nanofibrous cobalt spinel catalyst codoped with lanthanum (La) and manganese (Mn) prepared from a zeolitic imidazolate framework embedded in electrospun polymer fiber. The catalyst demonstrated a low overpotential of 353 millivolts at 10 milliamperes per square centimeter and a low degradation for OER over 360 hours in acidic electrolyte. A PEMWE containing this catalyst at the anode demonstrated a current density of 2000 milliamperes per square centimeter at 2.47 volts (Nafion 115 membrane) or 4000 milliamperes per square centimeter at 3.00 volts (Nafion 212 membrane) and low degradation in an accelerated stress test.
Glusa, Christian; D'Elia, Marta; Alla, Alessandro; Oliveira, Hugo
In this study, we explore the approximation of feedback control of integro-differential equations containing a fractional Laplacian term. To obtain feedback control for the state variable of this nonlocal equation, we use the Hamilton–Jacobi–Bellman equation. It is well known that this approach suffers from the curse of dimensionality, and to mitigate this problem we couple semi-Lagrangian schemes for the discretization of the dynamic programming principle with the use of Shepard approximation. This coupling enables approximation of high-dimensional problems. Numerical convergence toward the solution of the continuous problem is provided together with linear and nonlinear examples. The robustness of the method with respect to disturbances of the system is illustrated by comparisons with an open-loop control approach.
The efficient utilization of lignin, the direct source of renewable aromatics, into value-added renewable chemicals is an important step towards sustainable biorefinery practices. Nevertheless, owing to the random heterogeneous structure and limited solubility, lignin utilization has been primarily limited to burning for energy. The catalytic depolymerization of lignin has been proposed and demonstrated as a viable route to sustainable biorefinery, however, low yields and poor selectivity of products, high char formation, and limited to no recycling of transition-metal-based catalyst involved in lignin depolymerization demands attention to enable practical-scale lignocellulosic biorefineries. In this study, we demonstrate the catalytic depolymerization of ionic liquid-based biorefinery poplar lignin into guaiacols over a reusable zirconium phosphate supported palladium catalyst. The essence of the study lies in the high conversion (>80 %), minimum char formation (7–16 %), high yields of guaiacols (up to 200 mg / g of lignin), and catalyst reusability. Both solid residue, liquid stream, and gaseous products were thoroughly characterized using ICP-OES, PXRD, CHN analysis, GC-MS, GPC, and 2D NMR to understand the hydrogenolysis pathway.
Oriented attachment (OA) of nanoparticles is an important crystal growth pathway in the synthesis of hierarchical structures. Although a significant understanding of OA has been made, the effect of atomistic misalignment and the roles of solvent/particle and particle/particle interactions on the structure-energy relationship during an OA remain elusive. In this study, we perform molecular dynamics simulations to calculate the potential of mean force (PMF) profile for gibbsite particle translation on a gibbsite slab with 1 or 2 intervening water layers (1W or 2W). The structures of the gibbsite surfaces and the confined water are analyzed to determine how the number and type of hydrogen bonds (H-bonds) influence the free energy profile during the translation. The PMF profile exhibits a periodicity of length 5.078 Å, consistent with the gibbsite unit cell size along the translation direction. The changes in the surface-water and water-water hydrogen bond network and water and surface OH groups’ orientations during the translation are strongly coupled with the changes in the PMF profile in the 1W case. However, when increasing the number of intervening water layers from 1W to 2W, the particle/slab misalignment becomes a dominant factor controlling the behavior of the PMF profile. We also establish a method to quantify misalignment between the particle and the slab, which exhibits a strong correlation with the free energy for the 2W case. These results shed more light into the roles of particle/slab misalignment and hydrogen bond network in the OA of mineral particles in aqueous solution.
Using first-principles density functional theory (DFT) methods and size-converged supercell models, we analyze the electronic and atomic structure of magnetic $3d$ transition metal dopants in cubic gallium nitride (c-GaN). All stable defect charge states for Fermi levels across the full experimental gap are computed using a method that correctly resolves the boundary condition problem (without a jellium approximation) and eliminates finite-size errors. The resulting computed defect levels are not impacted by the DFT band-gap problem, they span a width consistent with the experimental gap rather than being limited to the single-particle DFT gap. All defects with electronically degenerate (half-metal) $T$d ground states are found to have significant distortions, relaxing to $D$2d structures driven by the Jahn-Teller instability. This leads to insulating ground states for all substitutional $3d$ dopants, refuting claims in the literature that +$U$ or hybrid functional methods are required to avoid artificial half-metal results. Interpreting the $d$n atomic occupations within a crystal-field model and exchange splittings, we identify a systematic trend across the $3d$ transition metal series. Approaches to estimate excited-state energies as observed in photoluminescence from defect centers are assessed, ranging from a Koopmans-type single-particle energy interpretation to relaxed total energy differences in fully self-consistent DFT. The single-particle interpretations are found to be qualitatively predictive and the calculations are consistent with the limited available experimental data across the $3$d dopant series. These results provide a baseline understanding to guide future studies and a conceptual framework within which to interpret new results.
Balogun, Shuaib A.; Lively, Ryan P.; Losego, Mark D.; Ren, Yi; Steiner, Adam M.
Vapor phase infiltration (VPI) is a post-polymerization modification technique that infuses inorganics into polymers to create organic–inorganic hybrid materials with new properties. Much is yet to be understood about the chemical kinetics underlying the VPI process. The aim of this study is to create a greater understanding of the process kinetics that govern the infiltration of trimethyl aluminum (TMA) and TiCl4 into PMMA to form inorganic-PMMA hybrid materials. To gain insight, this paper initially examines the predicted results for the spatiotemporal concentrations of inorganics computed from a recently posited reaction–diffusion model for VPI. This model provides insight on how the Damköhler number (reaction versus diffusion rates) and non-Fickian diffusional processes (hindering) that result from the material transforming from a polymer to a hybrid can affect the evolution of inorganic concentration depth profiles with time. Subsequently, experimental XPS depth profiles are collected for TMA and TiCl4 infiltrated PMMA films at 90 °C and 135 °C. The functional behavior of these depth profiles at varying infiltration times are qualitatively compared to various computed predictions and conclusions are drawn about the mechanisms of each of these processes. TMA infiltration into PMMA appears to transition from a diffusion-limited process at low temperatures (90 °C) to a reaction-limited process at high temperatures (135 °C) for the film thicknesses investigated here (200 nm). While TMA appears to fully infiltrate these 200 nm PMMA films within a few hours, TiCl4 infiltration into PMMA is considerably slower, with full saturation not occurring even after 2 days of precursor exposure. Infiltration at 90 °C is so slow that no clear conclusions about mechanism can be drawn; however, at 135 °C, the TiCl4 infiltration into PMMA is clearly a reaction-limited process, with TiCl4 permeating the entire thickness (at low concentrations) within only a few minutes, but inorganic loading continuously increasing in a uniform manner over a course of 2 days. Near-surface deviations from the uniform-loading expected for a reaction-limited process also suggest that diffusional hindering is high for TiCl4 infiltration into PMMA. In conclusion, these results demonstrate a new, ex situ analysis approach for investigating the rate-limiting process mechanisms for vapor phase infiltration.
Polymorphism and phase transitions in sodium diuranate, Na2U2O7, are investigated with density functional perturbation theory (DFPT). Thermal properties of crystalline α-, β- and γ-Na2U2O7 polymorphs are predicted from DFPT phonon calculations, i.e., the first time for the high-temperature γ-Na2U2O7 phase (R3̄m symmetry). The standard molar isochoric heat capacities predicted within the quasi-harmonic approximation are for P21/a α-Na2U2O7 and C2/m β-Na2U2O7, respectively. Gibbs free energy calculations reveal that α-Na2U2O7 (P21/a) and β-Na2U2O7 (C2/m) are almost energetically degenerate at low temperature, with β-Na2U2O7 becoming slightly more stable than α-Na2U2O7 as temperature increases. These findings are consistent with XRD data showing a mixture of α and β phases after cooling of γ-Na2U2O7 to room temperature and the observation of a sluggish α → β phase transition above ca. 600 K. A recently observed α-Na2U2O7 structure with P21 symmetry is also shown to be metastable at low temperature. Based on Gibbs free energy, no direct β → γ solid-solid phase transition is predicted at high temperature, although some experiments reported the existence of such phase transition around 1348 K. This, along with recent experiments, suggests the occurrence of a multi-step process consisting of initial β-phase decomposition, followed by recrystallization into γ-phase as temperature increases.
Machine learning is on a bit of a tear right now, with advances that are infiltrating nearly every aspect of our lives. In the domain of materials science, this wave seems to be growing into a tsunami. Yet, there are still real hurdles that we face to maximize its benefit. This Matter of Opinion, crafted as a result of a workshop hosted by researchers at Sandia National Laboratories and attended by a cadre of luminaries, briefly summarizes our perspective on these barriers. By recognizing these problems in a community forum, we can share the burden of their resolution together with a common purpose and coordinated effort.
Wexler, Robert B.; Sai Gautam, Gopalakrishnan; Bell, Robert T.; Shulda, Sarah; Strange, Nicholas A.; Trindell, Jamie T.; Sugar, Joshua D.; Nygren, Eli; Sainio, Sami; Mcdaniel, Anthony H.; Ginley, David; Carter, Emily A.; Stechel, Ellen B.
Modeling-driven design of redox-active off-stoichiometric oxides for solar thermochemical H2 production (STCH) seldom has resulted in empirical demonstration of competitive materials. We report the theoretical prediction and experimental evidence that the perovskite Ca2/3Ce1/3Ti1/3Mn2/3O3 is synthesizable with high phase purity, stable, and has desirable redox thermodynamics for STCH, with a predicted average neutral oxygen vacancy (VO) formation energy, Ev = 3.30 eV. Flow reactor experiments suggest potentially comparable or greater H2 production capacity than recent promising Sr-La-Mn-Al and Ba-Ce-Mn metal oxide perovskites. Utilizing quantum-based modeling of a solid solution on both A and B sub-lattices, we predict the impact of nearest-neighbor composition on Ev and determine that A-site Ce4+ reduction dominates the redox-activity of Ca2/3Ce1/3Ti1/3Mn2/3O3. X-ray absorption spectroscopy measurements provide evidence that supports these predictions and reversible Ce4+-to-Ce3+ reduction. Our models predict that Ce4+ reduces even when it is not nearest-neighbor to the VO, suggesting that refinement of Ce stoichiometry has the possibility of further enhancing performance.
The propagation of self-sustained formation reactions in sputter-deposited Co/Al multilayers is known to exhibit a design-dependent instability. Multilayers having thin bilayers (<55 nm period) exhibit stable propagating waves, whereas those with a larger period react unstably. The specific two-dimensional (2D) instability observed involves the transverse propagation of a band in front of a stalled front commonly referred to as a “spin band.” Previous finite-element studies have shown that these instabilities are thermodynamically driven by the forward conduction of heat away from the flame front. However, the magnitude of that loss is inherently tied to the bilayer design in traditional bimetallic multilayers, which couples any proposed stability criteria to a varying critical diffusion distance. This work utilizes a recently developed class of materials known as “inert-mediated reactive multilayers” to decouple the thermodynamic and kinetic contributions to propagating wave stability by reducing the stored chemical energy density in normally stable bilayer designs. By depositing an inert product phase (B2-CoAl) within the mid-plane of Co and Al reactant layers, spin instabilities arise as a function of both diluted volume and critical diffusion distance. From there, a stability criterion is determined for Co/Al multilayers based on enthalpy loss from the reaction zone, and its physical significance is explored.
Measured salt compositions in dust collected over roughly the last decade from surfaces of in-service stainless-steel alloys at four locations around the United States are presented, along with the predicted brine compositions that would result from deliquescence of these salts. The salt compositions vary greatly from ASTM seawater and from laboratory salts (i.e., NaCl or MgCl2) commonly used on corrosion testing. The salts contained relatively high amounts of sulfates and nitrates, evolved to basic pH values, and exhibited deliquescence relative humidity values (RH) higher than seawater. Additionally, inert dust in components were quantified and considerations for laboratory testing are presented. The observed dust compositions are discussed in terms of the potential corrosion behavior and are compared to commonly used accelerated testing protocols. Finally, ambient weather conditions and their influence on diurnal fluctuations in temperature (T) and RH on heated metal surfaces are evaluated and a relevant diurnal cycle for laboratory testing a heated surface has been developed. Suggestions for future accelerated tests are proposed that include exploration of the effects of inert dust particles on atmospheric corrosion, chemistry considerations, and realistic diurnal fluctuations in T and RH. Understanding mechanisms in both realistic and accelerated environments will allow development of a corrosion factor (i.e., scaling factor) for the extrapolation of laboratory-scale test results to real world applications.
The burgeoning field of materials informatics necessitates a focus on educating the next generation of materials scientists in the concepts of data science, artificial intelligence (AI), and machine learning (ML). In addition to incorporating these topics in undergraduate and graduate curricula, regular hands-on workshops present the most effective medium to initiate researchers to informatics and have them start applying the best AI/ML tools to their own research. With the help of the Materials Research Society (MRS), members of the MRS AI Staging Committee, and a dedicated team of instructors, we successfully conducted workshops covering the essential concepts of AI/ML as applied to materials data, at both the Spring and Fall Meetings in 2022, with plans to make this a regular feature in future meetings. Here, in this article, we discuss the importance of materials informatics education via the lens of these workshops, including details such as learning and implementing specific algorithms, the crucial nuts and bolts of ML, and using competitions to increase interest and participation.
X-ray diffraction (XRD) is a necessary technique for understanding states of materials under static and dynamic loading conditions. The higher-pressure Equation of State (EOS) of many materials can only be explored via shock or ramp compression at temperatures and pressures of interest. While static XRD work has yielded EOS measurements in the 100 - 200 GPa regime, dynamic X-ray diffraction (DXRD) can explore EOS phases in the TPa regime, which closely resembles inner-core planetary conditions. DXRD hinges on the ability to measure the exact phase or phase change of a material while under dynamic loading conditions. Macroscopic diagnostic systems (e.g. velocimetry and pyrometry) can infer a phase change but not identify the specific phase entered by a material. While microscopic (atomic-level) diagnostic systems (e.g. DXRD) have been designed and implemented in Department of Energy’s (DOE) National Laboratories complex, the unique nature of Sandia National Laboratories’ Pulsed Power Facility (Z Machine) prohibits the use of such devices. The destructive nature of Z experiments presents a challenge to data capture and retrieval. Furthermore there are electromagnetic interference, X-ray background, and mechanical constraints to consider. Thus, a multi-part X-ray diagnostic for use on the Z Machine and Z-Beamlet Laser system has been designed and analyzed. Portions of this new DYnamic SCintillator Optic (DYSCO) have been built, tested and fielded. A data analysis software has been written. Finally, the radiance profile of the DYSCO’s scintillator has been characterized through experiments performed at the University of Arizona.
Deploying Tidal Energy Converters for electricity generation requires prior-knowledge of the potential Annual Energy Production (AEP) at the site, Ideally using a year-long tidal current record at the proposed site to minimize uncertainty. However, such records are often unavailable. Fortunately, using the periodic nature of tidal variability, the International Electrotechnical Commission Technical Specification for tidal energy resource assessment requires AEP calculation using at least 90 days of tidal current records at each turbine location. The sensitivity of AEP to different record durations has not been fully assessed. This is the goal of our study. The study utilized the U.S. tidal energy geodatabase to simulate tidal currents with various lengths, during 100 years of the 21st century. We then consider two frameworks for evaluating AEP: (a) The long-term (months) fixed instrument (FI) measurement at each proposed tidal turbine location, and (b) one FI measurement and short-term (hours) boat-based moving vessel measurements. Under the two scenarios, we examine the AEP assessed from short tidal current records, including how the AEP uncertainties vary spatially and temporally, and how they are associated with various astronomical factors. This helps provide guidance on choosing the appropriate assessment methodologies to reduce the AEP uncertainties and project cost.
Solving large number of small linear systems is increasingly becoming a bottleneck in computational science applications. While dense linear solvers for such systems have been studied before, batched sparse linear solvers are just starting to emerge. In this paper, we discuss algorithms for solving batched sparse linear systems and their implementation in the Kokkos Kernels library. The new algorithms are performance portable and map well to the hierarchical parallelism available in modern accelerator architectures. The sparse matrix vector product (SPMV) kernel is the main performance bottleneck of the Krylov solvers we implement in this work. The implementation of the batched SPMV and its performance are therefore discussed thoroughly in this paper. The implemented kernels are tested on different Central Processing Unit (CPU) and Graphic Processing Unit (GPU) architectures. We also develop batched Conjugate Gradient (CG) and batched Generalized Minimum Residual (GMRES) solvers using the batched SPMV. Our proposed solver was able to solve 20,000 sparse linear systems on V100 GPUs with a mean speedup of 76x and 924x compared to using a parallel sparse solver with a block diagonal system with all the small linear systems, and compared to solving the small systems one at a time, respectively. We see mean speedup of 0.51 compared to dense batched solver of cuSOLVER on V100, while using lot less memory. Thorough performance evaluation on three different architectures and analysis of the performance are presented.
Diesel piston-bowl shape is a key design parameter that affects spray-wall interactions and turbulent flow development, and in turn affects the engine’s thermal efficiency and emissions. It is hypothesized that thermal efficiency can be improved by enhancing squish-region vortices as they are hypothesized to promote fuel-air mixing, leading to faster heat-release rates. However, the strength and longevity of these vortices decrease with advanced injection timings for typical stepped-lip (SL) piston geometries. Dimple stepped-lip (DSL) pistons enhance vortex formation at early injection timings. Previous engine experiments with such a bowl show 1.4% thermal efficiency gains over an SL piston. However, soot was increased dramatically [SAE 2022-01-0400]. In a previous study, a new DSL bowl was designed using non-combusting computational fluid dynamic simulations. This improved DSL bowl is predicted to promote stronger, more rotationally energetic vortices than the baseline DSL piston: it employs shallower, narrower, and steeper-curved dimples that are placed further out into the squish region. In the current experimental study, this improved bowl is tested in a medium-duty diesel engine and compared against the SL piston over an injection timing sweep at low-load and part-load operating conditions. No substantial thermal efficiency gains are achieved at the early injection timing with the improved DSL design, but soot emissions are lowered by 45% relative to the production SL piston, likely due to improved air utilization and soot oxidation. However, these benefits are lost at late injection timings, where the DSL piston renders a lower thermal efficiency than that of the SL piston. Energy balance analyses show higher wall heat transfer with the DSL piston than with the SL piston despite a 1.3% reduction in the piston surface area. Vortex enhancement may not necessarily lead to improved efficiency as more energetic squish-region vortices can lead to higher convective heat transfer losses.
Sandia National Laboratories (SNL) has developed a novel reduced order modeling approach. Prioritization of inputs is accomplished using Sobo' indices obtained through a more efficient variance-based global sensitivity analysis. To determine the Sobo' functions, simulated input values are aligned to collocation points to permit the use of Gauss-Lobatto integration, thereby reducing the number of simulation trials needed by more than an order of magnitude compared to standard Monte Carlo approaches. Furthermore, by leveraging the orthogonality of Legendre polynomials in conjunction with those same simulations at the collocation nodes, an efficient fitting method is developed to represent the Sobo' functions from which a reduced order model (ROM) is constructed. The developed method is both more efficient computationally, and the resulting ROM is more accurate. The efficacy of this technique is demonstrated on a nonlinear polynomial test function as well as the nonlinear Ishigami and Sobo' g functions.
Protecting against multi-step attacks of uncertain start times and duration forces the defenders into indefinite, always ongoing, resource-intensive response. To allocate resources effectively, the defender must analyze and respond to an uncertain stream of potentially undetected multiple multi-step attacks and take measures of attack and response intensity over time into account. Such response requires estimation of overall attack success metrics and evaluating effect of defender strategies and actions associated with specific attack steps on overall attack metrics. We present a novel game-theoretic approach GPLADD to attack metrics estimation and demonstrate it on attack data derived from MITRE's ATT&CK Framework and other sources. In GPLADD, the time to complete attack steps is explicit; the attack dynamics emerges from attack graph and attacker-defender capabilities and strategies and therefore reflects 'physics' of attacks. The time the attacker takes to complete an attack step is drawn from a probability distribution determined by attacker and defender strategies and capabilities. This makes time a physical constraint on attack success parameters and enables comparing different defender resource allocation strategies across different attacks. We solve for attack success metrics by approximating attacker-defender games as discrete-time Markov chains and show evaluation of return on detection investments associated with different attack steps. We apply GPLADD to MITRE's APT3 data from ATT&CK Framework and show that there are substantial and un-intuitive differences in estimated real-world vendor performance against a simplified APT3 attack. We focus on metrics that reflect attack difficulty versus attacker ability to remain hidden in the system after gaining control. This enables practical defender optimization and resource allocation against multi-step attacks.
The purpose of this protocol is to define procedures and practices to be used by the PACT center for field testing of metal halide perovskite (MHP) photovoltaic (PV) modules. The protocol defines the physical, electrical, and analytical configuration of the tests and applies equally to mounting systems at a fixed orientation or sun tracking systems. While standards exist for outdoor testing of conventional PV modules, these do not anticipate the unique electrical behavior of perovskite cells. Further, the existing standards are oriented toward mature, relatively stable products with lifetimes that can be measured on the scale of years to decades. The state of the art for MHP modules is still immature with considerable sample to sample variation among nominally identical modules. Version 0.0 of this protocol does not define a minimum test duration, although the intent is for modules to be fielded for periods ranging for weeks to months. This protocol draws from relevant parts of existing standards, and where necessary includes modifications specific to the behavior of perovskites.
