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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Simultaneous Reduction of NOx and Fuel Consumption for Off-Road Powertrains

Simultaneously reducing criteria pollutants and fuel consumption is important for clean air and improving vehicle total cost of ownership. The goal of this effort was focused on a 90% NOx reduction and 10% fuel savings for an off-road 407 kW diesel engine. The baseline was a production Fiat Powertrain 13L engine and aftertreatment system meeting 0.4 g/kW-hr NOx. The baseline system was quantified over the NRTC, RMC, new low load cycle and five field cycles. A next generation engine was built incorporating several fuel-efficient design features, including a higher compression ratio, increased fuel-rail pressure, low-friction piston rings, and a high-efficiency variable-geometry turbocharger. Cylinder deactivation and EGR pump technologies were added to this engine as well. The combination was optimized prior to adding advanced aftertreatment systems, showing the trade-off of engine out NOx and exhaust temperature. Two next-generation catalyst technologies were employed into a LO-SCR plus main SCR system, both with and without an electric heater upstream of the LO-SCR. These catalysts were hydrothermally aged to simulate significant field use. Dual SCR dosing with newly developed controls played a critical role in achieving the proper split between the upstream LO-SCR and the downstream main SCR. Adding a next generation mixer for the downstream SCR proved essential in obtaining the final results. The optimal configuration required adding an electric heater to elevate the exhaust temperature at the LO-SCR for early cycle NOx reduction. The final results showed a 94.8% NOx reduction and 15.7% fuel savings on the composite NRTC.

McCarthy, James [Eaton Corporation]↗
DOE OSTI2024

Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling

We propose a surrogate modeling framework based on dimension reduction to facilitate the quantification of seismic risk of structural systems in performance-based earthquake engineering. The framework adopts incremental dynamic analysis (IDA) for addressing hazard variability, and promotes significant computational efficiency improvement for propagating epistemic uncertainties associated with the structural models. It utilizes both linear and nonlinear dimension reduction approaches, equipped with inverse mappings, to learn a functional between the input parameter space (e.g., the epistemic uncertainties of the structure) to the high-dimensional output space created through the IDA implementation across different ground motions and seismic intensity levels. Polynomial chaos expansion is adopted as the surrogate model to learn this functional in the reduced space. A nine-story steel moment-resisting frame with uncertain structural properties is used as a testbed. Furthermore, we select the seismic fragility curves as a measure of the structure’s seismic performance, since it provides an estimate of the probability of entering specified damage states for given levels of ground shaking.

42 ENGINEERING↗
DOE OSTI2024

S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models

While projection-based reduced order models can reduce the dimension of full order solutions, the resulting reduced models may still contain terms that scale with the full order dimension. Hyper-reduction techniques are sampling-based methods that further reduce this computational complexity by approximating such terms with a much smaller dimension. The goal of this work is to introduce the points selection algorithm developed by Shin and Xiu as a hyper-reduction method. The selection algorithm was originally proposed as a stochastic collocation method for uncertainty quantification. Since the algorithm aims at maximizing a quantity $\mathcal{S}$ that measures both the column orthogonality and the determinant, we refer to the algorithm as S-OPT. Numerical examples are provided to demonstrate the performance of S-OPT and to compare its performance with a gappy proper orthogonal decomposition (POD) algorithm. Here, we found that using the S-OPT algorithm is shown to predict the full order solutions with higher accuracy than gappy POD especially when the number of sampling points is small, although we note that S-OPT shows slow asymptotic convergence with respect to the number of samples for some applications, e.g., Lagrangian hydrodynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Electrical and Spectroscopic Diagnostics as Real‐Time Metallization Indicators During Hydrogen Plasma Smelting Reduction

This study investigates the hydrogen (H 2 ) plasma reduction process of direct-reduced-iron-grade hematite ore at different arc currents (100–200 A) in an Ar–5% H 2 atmosphere at 0.9 bar. Iron ore samples (10 g) were exposed to a plasma arc, and the reduction/metallization kinetics were analyzed over fixed time intervals. Electrical diagnostics revealed that the arc voltage exhibited takeover-mode oscillations which were suppressed at higher currents due to stronger electromagnetic coupling. The voltage dropped significantly as metallization approached ∼95%, linked to increased electrical conductivity of the metallic iron (Fe) in the ore as well as Fe evaporation into the arc, lowering the arc resistance. A simplified Elenbaas–Heller model supported this explanation and confirmed that Fe vapor concentration enhances plasma conductivity. Optical emission spectroscopy focused on the plasma–metal interface revealed the plasma's optically thick nature, as the primary Fe I 526.95 nm line experienced self-absorption. However, weaker Fe I lines (404.58, 438.35 nm) normalized to Ar I 696.5 nm provided a reliable proxy for metallization. These diagnostics, electrical and spectroscopic, effectively track metallization in real-time during H 2 plasma smelting reduction.

08 HYDROGEN↗
DOE OSTI2024

Continuous Flow Photoelectrochemical Reactor with Gas Permeable Photocathode: Enhanced Photocurrent and Partial Current Density for CO 2 Reduction

Photoelectrochemical (PEC) CO 2 reduction using a photocathode is an attractive method for making valuable chemical products due to its simplicity and lower overpotential requirements. However, previous PEC processes have often been diffusion-limited leading to low production rates of the CO 2 reduction reaction, due to inefficient gas diffusion through the liquid electrolyte to the catalyst surface, particularly at high current densities. In this study, a gas-permeable photocathode in a continuous flow PEC reactor is incorporated, which facilitates the direct supply of CO 2 gas to the photocathode-electrolyte interface, unlike dark reaction-based flow reactors. This concept is demonstrated using Ag-TiO 2 on carbon paper, illuminated through a quartz window and flowing liquid electrolyte. CO 2 supply is managed via pressure and flow control on the non-illuminated side of the carbon paper. The photocurrent density is significantly influenced by the flow rates and pressure of CO 2 gas, and the electrolyte flow rates. Compared to the traditional H-cell, the continuous PEC flow reactor achieves ≈10-fold increase in CO faradaic efficiency, 30-fold increase in production rate and 16-fold increase in stability without catalyst modifications. This work provides essential insights into the design and application of continuous gas-liquid flow PEC reactor systems, highlighting their potential for other PEC reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Selective Electrochemical Reduction of CO 2 to Metal Oxalates in Nonaqueous Solutions Using Trace Metal Pb on Carbon Supports Enhanced by a Tailored Microenvironment

In this work, the electroreduction of carbon dioxide (CO 2 ) to oxalate is enabled by incorporating trace metallic lead (Pb) on carbon‐based supports (CBS) with polymer overlayers. These composite materials serve as an efficient electrocatalytic system for the facile conversion and storage of CO 2 , a pernicious atmospheric pollutant. Results from controlled potential electrolysis experiments indicate that 1) trace metallic Pb on the ppb scale is active toward the reductive coupling of CO 2 to oxalate at comparable Faradaic efficiencies to bulk metallic Pb and 2) polymer encapsulation of this trace metallic Pb leads to promotion of CO 2 reduction (CO 2 R) selectively to metal oxalates over other products such as CO. Importantly, metal oxalates are important alternative cementitious materials and precursors for other materials’ synthesis applications. The solid products undergo rigorous spectroscopic characterization, including 13 CO 2 labeling experiments, to ensure the metal oxalates are in fact produced from CO 2 R. These findings serve as a model for leveraging microenvironment effects to enhance activity and selectivity for CO 2 R using trace‐metal catalysts for carbon utilization and storage technologies.

alternative cementitious materials↗
DOE OSTI2026

Enhancing NO Reduction by CO Over NiO/CeO 2 Catalyst by Optimizing the Metal Oxide–Support Interaction

Noble metal catalysts are widely used in three-way catalysts (TWCs) due to their high efficiency, but their scarcity and high cost drive the need for effective, low-cost alternatives. Here, in this work, a series of NiO/CeO 2 catalysts were engineered by modulating the OH content and crystallite size of the CeO 2 support. This approach yielded Ni species ranging from isolated single atoms to small clusters and larger aggregates, with varied NiO/CeO 2 interaction strengths. Evaluation of their performance in NO reduction by CO, CO oxidation, and the water–gas shift reaction revealed that the NiO/CeO 2 -300 catalyst, featuring small CeO 2 crystallites and highly dispersed NiO clusters, delivered superior activity for NO reduction and CO oxidation. It was demonstrated that small NiO clusters, due to their efficient CO adsorption and activation, were more active than Ni single atoms. Furthermore, the presence of water was found to influence the catalyst stability, with NiO clusters less stable than single atoms likely due to the hydroxylation effect leading to the formation of Ni(OH) 2 . Oxygen storage capacity measurements revealed that performance was governed by a combination of CeO 2 crystallite size and the abundance of NiO/CeO 2 interfaces. These findings demonstrated that the catalytic performance of Ni/CeO 2 systems could be maximized by optimizing the Ni nanostructure and its interaction with CeO 2 support, positioning them as a promising, multifunctional nonprecious alternative for three-way catalysis application.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Significance of the 'Insignificant': Non-covalent Interactions in CO 2 Reduction Reactions with 3C-TM (TM=Sc-Zn) Single-Atom Catalysts

With energy shortages and excessive CO 2 emissions driving climate change, converting CO 2 into high-value-added products offers a promising solution for carbon recycling. We investigate CO 2 reduction reactions (CO2RR) catalyzed by 10 single-atom catalysts (SACs), incorporating weak non-covalent interactions, specifically lone pair-π and H-π interactions. The SACs, consisting of transition metals coordinated by three carbon atoms in a defective graphene substrate (3C-TM, TM=Sc-Zn), leverage these interactions to influence the energy fluctuations of intermediates and the limiting potentials of CO 2 RR, without altering the overall reaction pathway. Further, our findings show that SACs based on early transition metals (Sc, Ti, V, Cr) can serve as catalysts for C 1 products, including HCOOH, HCHO, CH 3 OH, and CH 4 , while those based on Fe and Co are suitable for CO formation. Driving force analysis helps bridge theoretical results with experimental observations and propose a modified approach for assessing hydrogen evolution reactions (HER) competition. SACs based on Ni and Cu exhibit moderate HER tolerance, while early transition metals excel in selective CO 2 reduction. We also identify a linear scaling relationship between the free energies of *COOH and *CO. This study offers valuable insights for future experimental studies and large-scale computational screenings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Copper Tantalate by a Sodium-Driven Flux-Mediated Synthesis for Photoelectrochemical CO 2 Reduction

Copper-tantalate, Cu 2 Ta 4 O 11 (CTO), shows significant promise as an efficient photocathode for multi-carbon compounds (C 2+ ) production through photoelectrochemical (PEC) CO 2 reduction, owing to its suitable energy bands and catalytic surface. However, synthesizing CTO poses a significant challenge due to its metastable nature and thermal instability. In this study, this challenge is addressed by employing a flux-mediated synthesis technique using a sodium-based flux to create sodium-doped CTO (Na-CTO) thin films, providing enhanced nucleation and stabilization for the CTO phase. To evaluate the PEC performance and catalytic properties of the films, copper(II) oxide (CuO) at the Na-CTO surface is selectively etched. The etched Na-CTO shows a lower dark current, with decreased contribution from photocorrosion, unlike the non-etched Na-CTO which has remaining CuO on the surface. Furthermore, Na-CTO exhibits 7.3-fold ethylene selectivity over hydrogen, thus highlighting its promising potential as a photocathode for C 2+ production through PEC CO 2 reduction.

copper tantalate↗
DOE OSTI2024

Comparative life cycle assessment of woody biomass processing: air classification, drying, and size reduction powered by bioelectricity versus grid electricity

Sulfur accumulation during biofuel production is pollutive and toxic to conversion catalysts and causes the premature breakdown of processing equipment. Air classification is an effective preprocessing technology for ash and sulfur reduction from biomass feedstocks. Here, a life cycle assessment (LCA) sought to understand the environmental impact of implementing air classification as a sulfur-mitigation technique to improve feedstock quality for pine residues using a grid electricity scenario (GES) versus a bioelectricity scenario (BES). Global warming potential (GWP) for preprocessing was simulated using inventory databases embedded in SimaPro and the Argonne National Laboratory’s GREET model, specifically focusing on comparing the GWP of a GES versus a BES. Overall, the GES had a GWP impact over seven times that of the BES (136 versus 18 kg CO 2 equivalent per tonne of usable feedstock), with steam generation during rotary drying accounting for 57% of the GES’s GWP. Air classification represents 0.4% and 1.6% of the total GWP impact for the GES and BES, respectively. Therefore, air classification can facilitate a 30% reduction in feedstock sulfur content to improve feedstock quality for biofuel conversion and lessen corrosion of equipment while contributing minimal GWP impact during preprocessing.

Air classification↗
DOE OSTI2024

Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning

Many physical processes in science and engineering are naturally represented by operators between infinite-dimensional function spaces. The problem of operator learning, in this context, seeks to extract these physical processes from empirical data, which is challenging due to the infinite or high dimensionality of data. An integral component in addressing this challenge is model reduction, which reduces both the data dimensionality and problem size. In this paper, we utilize low-dimensional nonlinear structures in model reduction by investigating Auto-Encoder-based Neural Network (AENet). AENet first learns the latent variables of the input data and then learns the transformation from these latent variables to corresponding output data. Our numerical experiments validate the ability of AENet to accurately learn the solution operator of nonlinear partial differential equations. Furthermore, we establish a mathematical and statistical estimation theory that analyzes the generalization error of AENet. Finally, our theoretical framework shows that the sample complexity of training AENet is intricately tied to the intrinsic dimension of the modeled process, while also demonstrating the robustness of AENet to noise.

Auto-encoder↗
DOE OSTI2024

Regulating the surface Pt coordination environment in the PtN overlayers on PtCuN hollow nanospheres for efficient oxygen reduction reaction

Engineering the surface Pt coordination environment is a promising strategy for promoting the kinetically sluggish oxygen reduction reaction (ORR) on Pt-based catalysts. Here, in this study, we achieve the compressive strain effect and electronic effect by Cu and N co-doping to synthesize the PtCuN hollow nanospheres with PtN overlayers (PtCuN@PtN HNSs) using a facile solvothermal synthesis. Electrochemical investigations show that the constructed disordered Pt–N coordination structures effectively facilitate the ORR and stabilize Pt atoms in the compressed lattice, whereas an excessive N-doping can lead to the formation of a structurally unstable Pt nitride phase. Theoretical analyses confirm that the oxygen reduction kinetics on the compressed PtN overlayers are regulated by a synergistic effect resulting from N-doping and lattice compression, circumventing the traditional linear scaling relationships (LSR). The optimized PtCuN@PtN HNSs, with the composition of PtCu 0.29 N 1.1 , demonstrate an area-specific activity of 1.98 mA cm –2 and a mass-specific activity of 1.81 A mg Pt –1 .

36 MATERIALS SCIENCE↗
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 OSTI2024

A DFT Comparison of C–C Reductive Coupling from Terminal Cyanido and Cyaphido Complexes of Nickel

The density functional theory study of the thermal C–C reductive coupling from terminal cyanido and hypothetical cyaphido complexes of [Ni(dmpe)] (dmpe = 1,2-bis(dimethylphosphino)ethane) revealed the key reaction intermediate in the reductive C–CP coupling being a σ-CC complex unlike an η 2 -aryl complex in the Ni C–CN system, as already observed in our previous studies. The reaction in THF is endothermic by 4.9 kcal/mol for cyanido with a 32.0 kcal/mol activation barrier and exothermic by 28.5 kcal/mol for cyaphido with an 11.3 kcal/mol activation barrier. To compare our results with the existing experimental data, we chose mesityl as the aryl group and also studied the CP reaction with [Pt(dmpe)] and [Pt(dmpm)] (dmpe = 1,2-bis(dimethylphosphino)methane) fragments. Our findings are consistent with the thermodynamically uphill photolytic C–CP bond activation in phosphaalkynes with Pt and a faster thermal back-reaction with [Pt(dmpe)] compared to that of [Pt(dmpm)]. Furthermore, based on the natural population analysis, when the polarity of the C–C bond is inverted, the sign of ΔG° is also inverted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Direct Air Capture-Compatible Azolate and Amino Acid Ionic Liquids for Electrochemical CO 2 Reduction to CO on a Silver Cathode

Direct air capture (DAC) compatible ionic liquids (ILs) are attractive for integrating CO 2 capture and conversion due to their high CO 2 solubility at low partial pressures, tunable chemisorption mechanisms, low volatility, and wide electrochemical windows. However, very few ILs have high CO 2 uptake at DAC conditions (420 ppm CO 2 ), and even fewer have been evaluated for chemical compatibility and mechanistic continuity for combined capture and electrochemical CO 2 reduction (eCO 2 RR). We demonstrate that two representative DAC-capable ILs, [P 4444 ][Val] (amino acid-based) and [P 66614 ][5-Me-Imd] (azolate-based), exhibit favorable electrochemical reduction behavior. CO and H 2 were the dominant gas-phase products by GC, while 1 H and 13 C NMR confirmed negligible liquid-phase HCOOH. Chronoamperometry at moderate applied potentials (−2.0 to −2.5 V vs Ag/AgCl) in a two-compartment H-cell with a Ag coated carbon paper as the working electrode yielded steady-state current densities of ∼10 mA cm −2 with CO FE of 96% for [P 4444 ][Val] and 95% for [P 66614 ][5-Me-Imd], highlighting the role of viscosity and chemically absorbed CO 2 -IL species to provide highly selective CO formation while suppressing H 2 evolution.

amino acid ionic liquid↗
DOE OSTI2024

Monodisperse Cu Nanoparticles Supported on a Versatile Metal–Organic Framework for Electrocatalytic Reduction of CO 2

Rare-earth metal–organic frameworks (REMOFs) based on polynuclear metal clusters are an emerging class of materials that have shown promise for CO 2 capture and conversion. Here, in this work, copper nanoparticles (CuNPs) were successfully installed on a cluster-based Y(III) MOF to yield a composite material, CuNP-Y-TBAP. The abundance of Cu binding sites on the Y(III) clusters allowed a remarkably high Cu loading to be achieved, and electron microscopy demonstrated that the MOF-supported CuNPs are exceptionally small and monodisperse. CuNP-Y-TBAP was found to be an active heterogeneous catalyst for electrochemical reduction of CO 2 , yielding CO and CH 4 as the primary CO 2 reduction products.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Catalytic Reduction of Carbon Monoxide to Liquid Fuels with Recyclable Hydride Donors

Solar light absorption and catalysis are physically separated processes in natural photosynthesis. Natural cofactors, such as nicotinamide adenine dinucleotides (NADH), transport electrons and hydrogen to regulate and activate enzymes at remote locations. The physical separation of light absorption from catalysis provides some inspiration for artificial photosynthesis. One rather extreme implementation is to use copper wires to transport carriers from photovoltaic cells to dark electrodes, where catalysis occurs. Indeed, with a futuristic electrical grid powered solely by photovoltaics, solar capture could be separated from catalysis by hundreds of miles. An alternative approach, that bares more similarity to natural photosynthesis, employs mobile NADH/NAD + -like species that shuttle between the light absorber and a proximate, yet unilluminated, location where catalysis occurs. Additionally, such a remote approach to solar photocatalysis was recently proposed for the reduction of carbon oxides, CO 2 and CO, to methanol by cascade catalysis. This developing artificial photosynthetic approach offers the promise of catalytic generation of methanol and oxygen gas with sunlight as the sole energy source and CO 2 and water as the only chemical feedstocks. This Viewpoint evaluates the strengths and weaknesses of this approach with an emphasis on CO reduction catalysis with photorecyclable hydride donors while looking forward to what might reasonably be achieved with continued research.

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

Operando Surface-Enhanced Infrared Spectroscopy Connects Interfacial Dynamics with Reaction Kinetics During Electrochemical CO 2 Reduction on Copper

The reaction microenvironment plays a key role in dictating the selectivity of electrochemical CO 2 reduction. However, understanding the chemical nature of this microenvironment under operating conditions remains a substantial challenge. For this study, we employed attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) in operando for simultaneous measurements of reaction kinetics and concentrations of reactants and intermediates at the reaction interface, all under controlled mass transport conditions. These operando measurements enable direct correlations between the reaction microenvironment, mass transport, and kinetics for a Cu electrocatalyst, such as higher local concentrations of CO 2 under faster mass transport corresponding to higher rates of CO 2 reduction. We observed that faster mass transport decreased the *CO coverage at less negative potentials (-0.6 V RHE ) and increased the *CO coverage at more negative potentials (-1.1 V RHE ). We developed a transport-coupled kinetic model that captures these spectroscopic observations and provides insight into the processes controlling interfacial concentrations of reactants and intermediates, aiding future efforts toward tailoring reaction microenvironments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗