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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

New operation strategy for driving the selectivity of NO x reduction to N 2 , NH 3 or N 2 O during lean/rich cycling of a lean NO x trap catalyst

Periodical regeneration of NO x storage catalyst (also known as lean NO x trap) by short rich pulses of CO, H 2 and hydrocarbons is necessary for the reduction of nitrogen oxides adsorbed on the catalyst surface. Ideally, the stored NO x is converted into N 2 , but N 2 O and NH 3 by-products can be formed as well, particularly at low-intermediate temperatures. The N 2 and N 2 O products are formed concurrently in two peaks. The primary peaks appear immediately after the rich-phase inception, and tail off with the breakthrough of the reductant front accompanied by NH 3 product. In addition, the secondary N 2 and N 2 O peaks then appear at the rich-to-lean transition as a result of reactions between surface-deposited reductants/intermediates (CO, HC, NH 3 , — NCO) and residual stored NO x under increasingly lean conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

From electricity to fuels: Descriptors for C 1 selectivity in electrochemical CO 2 reduction

Electrochemical reduction of carbon dioxide (CO 2 RR) over transition metals follows a complex reaction network. Here, we combine observations from experimental literature with a theoretical analysis of energetics to rationalize that not all intermediates in the reduction of CO 2 are formed through direct protonation steps. We derive a selectivity map for two-electron products (carbon monoxide (CO) and formate) on pure metal surfaces using only the CO and OH binding energies as descriptors. For the pure metals that are selective towards CO formation, the variation of the CO binding energy is sufficient to further subdivide the map into domains that predominantly form H 2 , CO, and more reduced products. Our analysis rationalizes experimentally observed product distributions in CO 2 RR across pure metal systems. Overall, we highlight the need for additional material screening descriptors for CO 2 R and the importance of considering competition from the elementary steps of the hydrogen evolution reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Improving intrinsic oxygen reduction activity and stability: Atomic layer deposition preparation of platinum-titanium alloy catalysts

Improved activity and stability Pt-based catalysts for the oxygen reduction reaction (ORR) are needed to perpetuate the deployment of polymer electrolyte fuel cells (PEFCs) in the transportation sector. In this study, we use atomic layer deposition of TiO 2 and Pt coupled with thermal reductive annealing to prepare Pt 3 Ti electrocatalysts. The atomic level synthetic control resulted in Pt 3 Ti nanoparticles with high ORR performance, including a mass activity of 1.84 A/mg Pt and excellent electrochemical stability. The Pt 3 Ti nanoparticles show excellent specific activity — 5.3-fold higher than commercial Pt/C and 3-fold higher than polycrystalline Pt, exceeding the performance of any PtTi catalysts reported to date. Combined experimental and computational efforts indicate that Pt enrichment on the Pt 3 Ti enhances the activity, and the intrinsic stability of the Pt 3 Ti phase provides durability. Subsequently, this knowledge, along with the facile fabrication of alloys by atomic layer deposition, can be leveraged to designed improved performance catalysts.

25 ENERGY STORAGE↗
DOE OSTI2023

Co-existence of atomically dispersed Ru and Ce 3+ sites is responsible for excellent low temperature N 2 O reduction activity of Ru/CeO 2

Nitrous oxide N 2 O reduction is a big challenge due to high global warming potential of N 2 O. (~300 times higher compared with CO 2 ). The best known catalysts, such as Rh/ceria, require relatively high temperatures for N 2 O decomposition. Herein, we report that Ru/ceria catalysts with low Ru loading of ~0.25 wt% efficiently catalyze low temperature N 2 O reduction by CO starting at 100 °C (full N 2 O conversion below 200 °C) under industrially relevant flow rates and gas concentrations. Further, this remarkable performance stems from maintaining isolated Ru cations even on reduced ceria surface and, simultaneously, the propensity of Ru to affect ceria surface to form labile surface oxygen thereby creating large number of oxygen vacancies (Ce +3 cations) in the presence of CO. In contrast, for Rh/CeO 2 catalysts with equivalent metal loading, the activity is much lower because atomically dispersed Rh sinters into metallic clusters at the onset reaction temperature (~200 °C): these clusters are much less effective than isolated single Ru ions, with lower Ce +3 concentration maintained on reduced Rh/CeO 2 catalyst. Our study highlights the benefits of gaining molecular-level insight into the dynamic nature of catalytically active sites under reaction conditions for preparing catalysts containing low loading of precious metals with unsurpassed low temperature activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Thermochemical reduction modeling in a high-temperature moving-bed reactor for energy storage: 1D model

The design of robust and efficient high-temperature thermochemical reactors and determination of operating conditions are critical steps toward enabling high-efficiency long-duration solar energy storage. This work presents a computational model for the thermal reduction of a metal oxide material (Mg-Mn-O) up to 1450 °C and the coupled complex transport phenomena in a novel tubular thermal reactor design that features the capability for a high extent-of-reduction (high energy storage density) and inherent heat recuperation. A one-dimensional model coupling counter-current gas–solid flow, two-phase heat transfer, thermochemical redox reactions, and species transport in a moving-bed reactor is developed. Simplified versions of the model are validated with published results in the literature for packed beds with both inert and reactive particles; the fully coupled model is also validated with experimental measurements of a moving-bed reactor in terms of local temperatures and oxygen release at the exit. Detailed comparisons on the effects of different boundary conditions in the reaction zone (prescribed wall temperature vs. heat flux conditions) and formulations based on a simple uniform flow assumption vs. plug flow using Ergun equation for gas flow are investigated. The results are compared with experimental measurements, and for all cases, the energy flow components in the reactor system and the thermal to chemical conversion efficiency and overall system efficiency are computed. Finally, the predicted high thermal-to-chemical efficiency ~95% and system efficiency ~30% agree with experimental measurements.

25 ENERGY STORAGE↗
DOE OSTI2016

Adaptive model order reduction for the Jacobian calculation in inverse multi-frequency problem for Maxwell's equations

Here this work develops a model order reduction method for a numerical solution of an inverse multi-frequency eddy current problem using a rational interpolation of the transfer function in the complex plane. We use the Pade interpolation in the complex frequency plane; this allows us to speed up the calculation of the frequency-dependent Jacobian in the inversion procedure without loosing accuracy. Interpolating frequencies are chosen adaptively to reduce the maximal approximation error. We use the error indicator that is equivalent to a seminorm of the residual. The efficiency of the developed approach is demonstrated by applying it to the inverse magnetotelluric problem, which is a geophysical electromagnetic remote sensing method used in mineral, geothermal, and groundwater exploration. In this application, the transfer function values are needed for shifts in a purely imaginary interval. Thus we consider the interpolating shifts in the same interval as well as in a purely real interval, containing the spectrum of the operator. Numerical tests show an excellent performance of the proposed methods characterized by a significant reduction of computational time without loss of accuracy of the calculated Jacobian.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Smoothed particle hydrodynamics modeling and analysis of oxide reduction process for uranium oxides

A common kinetic feature for oxide reduction chemical/electrochemical processes is oxygen transport via a porous metallic layer, which has been considered as a rate-determining step for reducing uranium oxides to metallic uranium. Accounting this kinetic behavior must involve the resolution of the moving reactive interface between shrinking oxide and expanding metal phases. This study presents a numerical model using smoothed particles hydrodynamics (SPH) to effectively deal with the evolution of the shrinking core reaction interface and oxygen transport via mass transfer of lithium oxide (Li 2 O) species in multiple mass transfer domains. We successfully validated the proposed model against a theoretical derivation for the oxide reduction process handling a shrinking oxide core with molten salt and metal ash medium on a simple planar geometry. Armed with successful validation results, the model examined a realistic reactant geometry to extend the arguments beyond the one-dimensional analyses, allowing the proposed model to apply to general application scenarios with multi-dimensional geometry. Here, this study demonstrated that the proposed model could simulate and evaluate an arbitrary reaction basket design without iterative experimental trials, which is prohibitive for a scaled high-temperature molten salt study in an inert environment. The construct potentially provides not only deep insights on multiphysics behaviors governing the process dynamics but also a robust framework for evaluating and screening candidate basket designs in the most cost-effective manner.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Decoupling size and surface effects of intermetallic CuPd nanocrystals for electrocatalytic nitrate reduction to ammonia

Nitrate pollution poses a major environmental challenge, but its electrochemical conversion to ammonia offers a sustainable waste-to-value solution. Here, in this study, we synthesized monodisperse, size-tunable B2-phase CuPd intermetallic nanocrystals (6–46 nm) and studied their performance in the electrochemical nitrate reduction reaction (eNO 3 RR). By using bromide ions to modulate Pd reduction and applying mild annealing, we achieved phase-pure B2 structures across all sizes. Catalytic testing revealed a volcano-like trend in ammonia yield, peaking at 33 nm nanocubes with a rate of 6.97 mol h −1 g −1 at −0.6 V vs. reversible hydrogen electrode (RHE). This optimum reflects a balance between the increased surface area of smaller particles and the enhanced exposure of active (100) facets in larger ones. Theoretical calculations indicated that the B2-CuPd (100) facet is favorable for nitrate adsorption, thereby supporting the high activity of nanocubes. Our results highlight the critical role of tuning both nanoparticle size and surface structure to maximize eNO 3 RR efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Targeted electrochemical reduction of carcinogenic N -nitrosamines from emission control systems within CO 2 capture plants

N-Nitrosamines are one of the environmentally significant byproducts from aqueous amine-based post-combustion carbon capture systems (CCS) due to their potential risk to human health. Safely mitigating nitrosamines before they are emitted from these CO 2 capture systems is therefore a key concern before widescale deployment of CCS can be used to address worldwide decarbonization goals. Electrochemical decomposition is one viable route to neutralize these harmful compounds. The circulating emission control waterwash system, commonly installed at the end of the flue gas treatment trains to minimize amine solvent emissions, plays an important role to capture N-nitrosamines and control their emission into the environment. The waterwash solution is the last point where these compounds can be properly neutralized before becoming an environmental hazard. In this study, the decomposition mechanisms of N-nitrosamines in a simulated CCS waterwash with residual alkanolamines was investigated using several laboratory-scale electrolyzers utilizing carbon xerogel (CX) electrodes. Hcell experiments revealed that N-nitrosamines were decomposed through a reduction reaction and are converted into their corresponding secondary amines thereby neutralizing their environmental impact. Batch-cell experiments statistically examined the kinetic models of N-nitrosamine removal by a combined adsorption and decomposition processes. The cathodic reduction of the N-nitrosamines statistically obeyed the first-order reaction model. Finally, a prototype flow-through reactor using an authentic waterwash was used to successfully target and decompose N-nitrosamines to below the detectable level without degrading the amine solvent compounds allowing them to be return to the CCS and lower the system operating costs. Furthermore, the developed electrolyzer was able to efficiently remove greater than 98% of N-nitrosamines from the waterwash solution without producing any additional environmentally harmful compounds and offers an effective and safe route to mitigate these compounds from CO 2 capture systems.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Methods identifying cost reduction potential for water electrolysis systems

The electrochemical reduction of water to form hydrogen is an emerging alternative for energy storage, where hydrogen can be used as a transportation fuel, combusted to generate electricity, utilized in a fuel cell, or used as a feedstock for chemical synthesis. Techno-economic analysis (TEA) is a valuable tool for understanding how to inform research directions that could make hydrogen from electrolysis cost competitive with that produced by conventional means like steam methane reforming. The current state of knowledge on TEA of electrolysis systems suggests cost reductions are likely to result from advances in system design and materials, scale-up of manufacturing processes, and learning by doing effects as electrolysis deployment increases. Future directions and opportunities for TEA of electrolysis systems include dispatchable operation in wholesale power markets, optimization of capital cost and system durability, and analysis of pathways for hydrogen to support economy-wide decarbonization.

08 HYDROGEN↗
DOE OSTI2021

Roads less traveled: Nitrogen reduction reaction catalyst design strategies for improved selectivity

Direct electrochemical nitrogen reduction for ammonia production is necessary to reduce the use of fossil fuels from conventional Haber–Bosch methods. Applications of nitrogen reduction electrocatalysts remain inhibited by slow reaction kinetics and low faradaic efficiencies because of competitive H2 production pathways. Current strategies to address this challenge in selectivity have focused on catalyst design, reactor configuration, and electrolyte conditions. This brief review discusses the thermodynamic and kinetic challenges in the field as well as current underused approaches for selective catalyst development including bimetallic catalysts, transition metal nitrides, and carbon supports.

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

A co-kurtosis PCA based dimensionality reduction with nonlinear reconstruction using neural networks

For turbulent reacting flow systems, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the computational cost of device-scale simulations. Principal component analysis (PCA), and its variants, are a widely employed class of methods. Recently, an alternative technique that focuses on higher-order statistical interactions, co-kurtosis PCA (CoK-PCA), has been shown to effectively provide a low-dimensional representation by capturing the stiff chemical dynamics associated with spatiotemporally localized reaction zones. While its effectiveness has only been demonstrated based on a priori analyses with linear reconstruction, in this work, we employ nonlinear techniques to reconstruct the full thermo-chemical state and evaluate the efficacy of CoK-PCA compared to PCA. Specifically, we combine a CoK-PCA-/PCA-based dimensionality reduction (encoding) with an artificial neural network (ANN) based reconstruction (decoding) and examine, a priori, the reconstruction errors of the thermo-chemical state. In addition, we evaluate the errors in species production rates and heat release rates, which are nonlinear functions of the reconstructed state, as a measure of the overall accuracy of the dimensionality reduction technique. We employ four datasets to assess CoK-PCA/PCA coupled with ANN-based reconstruction: zero-dimensional (homogeneous) reactor for autoignition of an ethylene/air mixture that has conventional single-stage ignition kinetics, a dimethyl ether (DME)/air mixture which has two-stage (low and high temperature) ignition kinetics, a one-dimensional freely propagating premixed ethylene/air laminar flame, and a two-dimensional dataset representing turbulent autoignition of ethanol in a homogeneous charge compression ignition (HCCI) engine. Finally, results from the analyses demonstrate the robustness of the CoK-PCA based low-dimensional manifold with ANN reconstruction in accurately capturing the data, specifically from the reaction zones.

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

On the use of a multigrid-reduction-in-time algorithm for multiscale convergence of turbulence simulations

Simulations of turbulent flow present challenges in terms of accuracy and affordability on modern highly-parallel computer architectures. A multigrid-reduction-in-time algorithm is used to provide a framework for separately evolving different scales of turbulence and for parallelizing the temporal domain, thereby increasing the concurrency. It is hypothesized that the space–time locality of the small scales of turbulence can be used to circumvent difficulties in applying temporal multigrid to flows dominated by inertial physics. For algorithms that fall well short of spectral accuracy (fourth-order is used in this work) attention must be paid to the accuracy of features on scales transferred between multigrid levels. Numerical experiments were performed using implicit large-eddy simulation. Results from applying the approach to an infinite-Reynolds number Taylor–Green flow and a double-shear flow at a Reynolds number of 11650 provide strong evidence that the approach has merit. The multigrid-reduction-in-time framework can be used to parallelize the temporal domain of a high-Reynolds-number turbulent flow and permit independent convergence of different scales. Establishing this foundation allows for future research in reducing the wall-clock time to solve turbulent flows while retaining the same accuracy as sequential solvers. In conclusion, current performance results from parallelizing the temporal domain are not competitive with those from sequential-in-time methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Effect of Pressure and Temperature on Carbon Dioxide Reduction at a Plasmonically Active Silver Cathode

Here, carbon dioxide reduction at a plasmonically active silver cathode was investigated by varying the pressure and temperature at multiple applied potentials under both dark and illuminated conditions to understand the mechanism of selectivity changes driven by plasmon-enhanced electrochemical conversion. Carbon dioxide partial pressures (P Co 2 ) from 0.2 to 1 atm were studied during linear sweep voltammetry and chronoamperometry at -0.7, -0.9, and -1.1 V RHE . At a given applied overpotential the total current density increased with increasing P Co 2 in both the dark and the light, but there were significant differences in the Tafel behavior between dark and illuminated conditions. The reduction of CO 2 to carbon monoxide (CO) was found to have first-order behavior with respect to P Co 2 at all applied potentials in both the dark and the light, likely indicating no change in the rate-determining step upon illumination. Activity for the hydrogen (H 2 ) evolution reaction decreased with increasing P Co 2 at slightly different rates in the dark and the light at each applied potential, making it unclear if light is influencing CO or H 2 intermediate adsorbate coverage. Both formate and methanol production showed no dependence on P Co 2 under any conditions, but the true reaction orders may be masked by the much higher activity for CO and H 2 at the silver cathode. The investigation of product distribution with temperature at 14, 22, and 32°C at -0.7, -0.9, and -1.1 V RHE in both the dark and the light demonstrated that the selectivity changes observed upon illumination are not caused by local heating of the cathode surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A modeling comparison of deep greenhouse gas emissions reduction scenarios by 2030 in California

California aims to reduce greenhouse gas (GHG) emissions to 40% below 1990 levels by 2030. We compare six energy models that have played various roles in informing the state policymakers in setting climate policy goals and targets. These models adopt a range of modeling structures, including stock-turnover back-casting models, a least-cost optimization model, macroeconomic/macro-econometric models, and an electricity dispatch model. Results from these models provide useful insights in terms of the transformations in the energy system required, including efficiency improvements in cars, trucks, and buildings, electrification of end-uses, low- or zero-carbon electricity and fuels, aggressive adoptions of zero-emission vehicles (ZEVs), demand reduction, and large reductions of non-energy GHG emissions. Some of these studies also suggest that the direct economic costs can be fairly modest or even generate net savings, while the indirect macroeconomic benefits are large, as shifts in employment and capital investments could have higher economic returns than conventional energy expenditures. These models, however, often assume perfect markets, perfect competition, and zero transaction costs. They also do not provide specific policy guidance on how these transformative changes can be achieved. Greater emphasis on modeling uncertainty, consumer behaviors, heterogeneity of impacts, and spatial modeling would further enhance policymakers' ability to design more effective and targeted policies. Here, this paper presents an example of how policymakers, energy system modelers and stakeholders interact and work together to develop and evaluate long-term state climate policy targets. Lastly, even though this paper focuses on California, the process of dialogue and interactions, modeling results, and lessons learned can be generally adopted across different regions and scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Iron-based sulfur and nitrogen dual doped porous carbon as durable electrocatalysts for oxygen reduction reaction

The widespread use of fuel cell technology is hampered by the use of expensive and scarce platinum metal in electrodes which is required to facilitate the sluggish oxygen reduction reaction (ORR). In this work, a viable synthetic approach was developed to prepare iron-based sulfur and nitrogen dual doped porous carbon (Fe@SNDC) for use in ORR. Benzimidazole, a commercially available monomer, was used as a precursor for N doped carbon and calcined with potassium thiocyanate at different temperatures to tune the pore size, nitrogen content and different types of nitrogen functionality such as pyridinic, pyrrolic and graphitic. The Fe@SNDC–950 with high surface area, optimum N content of about 5 at% and high amount of pyridinic and graphitic N displayed an onset potential and half-wave potential of 0.98 and 0.83 V vs RHE, respectively, in 0.1 M KOH solution. The catalyst also exhibits similar oxygen reduction reaction performance compared to Pt/C (20 wt%) in acidic media. Furthermore, when compared to commercially available Pt/C (20 wt%), Fe@SNDC–950 showed enhanced durability over 6 h and poison tolerance in case of methanol crossover with the concentration up to 3.0 M in oxygen saturated alkaline electrolyte. Finally, our study demonstrates that the presence of N and S along with Fe-N moieties synergistically served as ORR active sites while the high surface area with accessible pores allowed for efficient mass transfer and interaction of oxygen molecules to the active sites contributing to the ORR activity of the catalyst.

08 HYDROGEN↗
DOE OSTI2024

Comparative life cycle analysis on ethylene production from electrocatalytic reduction of carbon dioxide

Ethylene is one of the largest greenhouse gas emitters and the most diversly used commodity chemicals globally. Electrocatalytic reduction of CO 2 to ethylene received great attention from the research society to decarbonize the ethylene production. Here, in this study, a life-cycle analysis is conducted using the Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (GREET) model on the three electrocatalytic CO 2 -reduction pathways (or “e-ethylene” pathways): i) cascade conversion via carbon monoxide intermediate; ii) single-step conversion in membrane electrode assembly (MEA); and iii) single-step conversion in alkaline flow cell. The results showed that the electricity consumption is the lowest for the cascade pathway (164 MJ/kg), thus resulting in the lowest cradle-to-gate carbon intensity [18 kgCO 2 e/kg with United States (US) average grid)] among the three pathways followed by the single-step MEA (32 kgCO 2 e/kg) and then by the single-step alkaline (56 kgCO 2 e/kg). However, all three e-ethylene pathways were significantly more carbon-intensive than their fossil-based counterpart (1.1 kgCO 2 e/kg) due to their excessive energy consumption with the current state of technology. With renewable electricity, all three pathways yielded negative carbon intensity: from -3.1 kgCO 2 e/kg to -1.6 kgCO 2 e/kg depending on the source of CO 2 . The threshold carbon intensity of electricity (TCIE), defined as the upper bound of the carbon intensity of electricity to achieve lower carbon intensity for e-ethylene compared to fossil-based ethylene, is calculated for both current and future state of e-ethylene technologies. The cascade pathway had the highest TCIE out of the three e-ethylene pathways for both current (92 gCO 2 e/kWh) and future (124 gCO 2 e/kWh) state of technologies. However, the carbon intensity of average US grid (i.e., 467 and 303 gCO 2 e/kWh for current and future projections) were higher than the TCIEs of the corresponding timeline. Thus, reducing electricity requirement for e-ethylene pathways and bringing low-carbon generation mix in the United States (US) grid faster than the current projection are both essential to decarbonize ethylene and its downstream chemicals/polymers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Demonstrating the viability of Lagrangian in situ reduction on supercomputers

Performing exploratory analysis and visualization of large-scale time-varying computational science applications is challenging due to inaccuracies that arise from under-resolved data. In recent years, Lagrangian representations of the vector field computed using in situ processing are being increasingly researched and have emerged as a potential solution to enable exploration. However, prior works have offered limited estimates of the encumbrance on the simulation code as they consider “theoretical” in situ environments. Further, the effectiveness of this approach varies based on the nature of the vector field, benefitting from an in-depth investigation for each application area. With this study, an extended version of Sane et al. (2021), we contribute an evaluation of Lagrangian analysis viability and efficacy for simulation codes executing at scale on a supercomputer. We investigated previously unexplored cosmology and seismology applications as well as conducted a performance benchmarking study by using a hydrodynamics mini-application targeting exascale computing. Here, to inform encumbrance, we integrated in situ infrastructure with simulation codes, and evaluated Lagrangian in situ reduction in representative homogeneous and heterogeneous HPC environments. To inform post hoc accuracy, we conducted a statistical analysis across a range of spatiotemporal configurations as well as a qualitative evaluation. Additionally, our study contributes cost estimates for distributed-memory post hoc reconstruction. In all, we demonstrate viability for each application — data reduction to less than 1% of the total data via Lagrangian representations, while maintaining accurate reconstruction and requiring under 10% of total execution time in over 90% of our experiments.

97 MATHEMATICS AND COMPUTING↗