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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ni 2 P active site ensembles tune electrocatalytic nitrate reduction selectivity

Here, we demonstrate that active site ensembles on transition metal phosphides tune the selectivity of the nitrate reduction reaction. Using Ni 2 P nanocrystals as a case study, we report a mechanism involving competitive co-adsorption of H* and NO x * intermediates. A near 100% faradaic efficiency for nitrate reduction over hydrogen evolution is observed at -0.4 V, while NH 3 selectivity is maximized at -0.2 V vs. RHE.

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

Electrocatalytic CO 2 reduction by a cobalt porphyrin mini-enzyme

Cobalt-mimochrome VI*a (CoMC6*a), a synthetic mini-enzyme with a cobalt porphyrin active site, is developed as a biomolecular catalyst for electrocatalytic CO 2 reduction in water. The catalytic turnover number reaches ∼14 000 for CO production with a selectivity of 86 : 5 over H 2 production under the same conditions. Varying the applied potential and the p K a of the proton donor was used to gain insight into the basis for selectivity. The protected active site of CoMC6*a is proposed to enhance selectivity for CO 2 reduction under conditions that typically favor H 2 production by related catalysts. CoMC6*a activity and selectivity change only marginally under air, indicating excellent oxygen tolerance.

Salamatian, Alison A. [Univ. of Rochester, NY (Uni↗
DOE OSTI2025

Titanium nitride prepared by the urea-glass synthesis gives an active electrocatalyst for the oxygen reduction reaction

Rock-salt-structured titanium nitride (TiN) has emerged as a leading earth-abundant electrocatalyst for the oxygen reduction reaction (ORR). We compare TiN prepared in three ways starting from urea: the urea–glass method, by a direct reaction between urea and titanium(IV) chloride, and through a discrete monomeric complex. In the urea-glass route, a new-found [Ti 4 (µ-O) 6 (OC(NH 2 ) 2 ) 12 ] 4+ oxo-bridged titanium–urea precursor can be synthesized in a single-pot reaction at room temperature starting from titanium(IV) chloride, urea, and ethanol with a urea-to-titanium ratio of 6. Subsequent annealing of the polymeric gel that results at 750 °C in an N 2 atmosphere yields phase-pure, TiN particles on the 100 µm size scale. TiN can be deposited as an ink with PiperlON®anion exchange dispersion onto a glassy carbon rotating disk electrode (RDE), and of the three synthesis methods, the urea-glass method gives the most active ORR catalyst. The onset potential for ORR activity is −131 mV vs. Hg/HgO, and Koutecký–Levich analysis of linear-sweep voltammetry recorded at varying rotation rates supports a two-electron reduction pathway to H 2 O 2 , with a rate constant of 0.0172 cm s −1 . The higher activity is ascribed to a more oxygen-rich surface—boh defect sites and active oxygen species—afforeded by the oxo-bridged precursor, corrorborated by X-ray photoelectron spectroscopy (XPS) analysis.

Xie, Wanrui [University of Michigan, Ann Arbor, MI↗
DOE OSTI2026

Carbon nanodot precursors enable ultrahigh-loading copper single-atom catalysts for oxygen reduction reaction

Single-atom catalysts (SACs) have attracted significant attention in electrocatalysis due to their high metal utilization and tunable electronic structures; however, their practical implementation is often limited by poor atomic dispersion, low metal loadings (typically < 1 wt%), and insufficient anchoring of single metal atoms on catalyst supports. Herein, we report a simple and versatile strategy to synthesize copper single-atom catalysts (Cu-SACs) with ultrahigh metal loading using citric-acid-derived carbon nanodots as metal-capturing precursors. Through hydrothermal treatment followed by pyrolysis in the presence of urea, atomically dispersed copper atoms coordinated with nitrogen are incorporated into a carbon framework, achieving a Cu loading of up to 20 wt% while maintaining atomic dispersion. Notably, a significant fraction of the copper single atoms exists as Cu+–N2 coordination, which provides under-coordinated and catalytically active sites. The resulting Cu-SAC exhibits promising oxygen reduction reaction (ORR) activity in alkaline media, delivering a limiting current density comparable to that of commercial 20 wt% Pt/C with a predominant four-electron reduction pathway. Despite this high intrinsic activity, durability tests reveal gradual performance degradation under prolonged electrochemical operation, which is attributed to demetallation and aggregation of copper single atoms into metallic nanoparticles. These results demonstrate the potential of carbon nanodot-based platforms for synthesizing high-loading SACs, while underscoring the critical need to simultaneously control carbon porosity and metal–nitrogen coordination to enhance active-site accessibility and durability.

Sharma, Prakhar [University of Kentucky]↗
DOE OSTI2026

Rare‐Earth Reduction in High‐Speed PM‐Assisted Synchronous Reluctance Motors Using Hybrid Magnet Strategies and Design Optimisation for 800 V EVs

The trend towards electrifying transportation systems has stimulated research endeavours aimed at developing electric machines that are not only high speed and efficient but also low‐cost and compact. To support this transition, the US Department of Energy (DOE) has established ambitious targets of $7/kW cost and 12 kW/L power density for the electric drivetrains. This paper attempts to meet these targets by proposing high‐speed permanent magnet assisted synchronous reluctance machine (PMASynRM) topologies enabled by hybrid magnet strategies, combining rare‐earth (RE) magnets with low‐cost, RE‐free alternatives. Modified 2‐layer and 3‐layer U‐shaped rotor configurations, featuring structural reinforcements to withstand high mechanical stress at elevated speeds, are developed. A multi‐objective design optimisation framework is employed to optimise the rotor design, targeting reductions in RE magnet volume, magnet demagnetisation risk and torque ripple while achieving the desired electromagnetic performance. A comprehensive analysis of the optimised rotor designs, compared against a 16,000 rpm, 800 V baseline IPM motor, shows over 70% RE reduction, demagnetisation risk below 3.5% and torque ripple under 10%. Detailed analyses of performance trends across various magnet combinations and rotor configurations highlight the viability of hybrid magnet PMASynRM designs as cost‐effective, robust and energy‐efficient solutions for next‐generation EVs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Reversible oxidation and reduction of gold-supported iron oxide islands at room temperature

Monolayer iron oxides grown on metal substrates have widely been used as model systems in heterogeneous catalysis. By means of ambient-pressure scanning tunneling microscopy (AP-STM), we studied the in situ oxidation and reduction of FeO(111) grown on Au(111) by oxygen (O 2 ) and carbon monoxide (CO), respectively. Oxygen dislocation lines present on FeO islands are highly active for O 2 dissociation. X-ray photoelectron spectroscopy measurements distinctly reveal the reversible oxidation and reduction of FeO islands after sequential exposure to O 2 and CO. Here, our AP-STM results show that excess O atoms can be further incorporated on dislocation lines and react with CO, whereas the CO is not strong enough to reduce the FeO supported on Au(111) that is essential to retain the activity of oxygen dislocation lines.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Exploring non-adiabaticity to CO reduction reaction through ab initio molecular dynamics simulation

Non-adiabatic chemical reaction refers to the electronic excitation during reactions. This effect cannot be modeled by the ground-state Born-Oppenheimer molecular dynamics (BO-MD), where the electronic structure is at the ground state for every step of ions' movement. Although the non-adiabatic effect has been explored extensively in gas phase reactions, its role in electrochemical reactions, such as water splitting and CO 2 reduction, in electrolyte has been rarely explored. On the other hand, electrochemical reactions usually involve electron transport; thus, a non-adiabatic process can naturally play a significant role. In this work, using one-step CO 2 reduction as an example, we investigated the role of the non-adiabatic effect in the reaction. The reaction barriers were computed by adiabatic BO-MD and non-adiabatic real-time time dependent density functional theory (rt-TDDFT). We found that by including the non-adiabatic effect, rt-TDDFT could increase the reaction barrier up to 6% compared to the BO-MD calculated barrier when the solvent model is used to represent water. Simulations were carried out using explicit water molecules around the reaction site under different overpotentials, and similar non-adiabatic effects were found.

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

Order-of-magnitude laser imprint reduction using pre-expanded high-Z coatings on targets driven by a third harmonic Nd:glass laser

A hybrid early time x-ray drive followed by conventional laser direct drive obtained by utilizing a thin high-Z overcoat on plastic ablator targets has proven to be very effective at reducing laser imprint in experiments driven by the Nike krypton-fluoride laser. An inherent low level laser prepulse from that laser system heated and expanded the coating prior to the main pulse. Here, we report on results using a frequency tripled Nd:glass laser system (Omega EP) where the inherent prepulse was several orders of magnitude smaller. By applying a separate prepulse, these experiments allowed us to test if the prepulse is important for mitigating imprint with the high-Z layer. The results show that the high-Z coating is much more effective at reducing laser imprint when it is pre-expanded, in this case, by an externally generated low level soft x-ray prepulse of ∼10 J/cm2. With the x-ray prepulse, laser imprint at spatial wavelengths below 100 μm was reduced by an order of magnitude, similar to that observed with the laser prepulse on Nike. Furthermore, the experiments here establish that high-Z coating is effective in reducing imprint even in the case of a fixed speckle pattern. Rayleigh–Taylor-amplified laser imprint and high-Z layer dynamics were measured using through-foil and side-on x-ray radiography. Pre-expansion times from 30 down to 6 ns were effective, potentially compatible with laser prepulse generation using existing NIF and OMEGA front ends; however, temporal beam smoothing appears to be necessary for the laser prepulse that directly illuminates the high-Z coating. The highest imprint reduction is observed for Pd and Au coatings of at least 400 Å thickness; thicknesses down to 200 Å show a reduction in imprint with an adjusted prepulse.

Karasik, Max (ORCID:0000000162354670)↗
DOE OSTI2021

Stochastic density functional theory: Real- and energy-space fragmentation for noise reduction

Stochastic density functional theory (sDFT) is becoming a valuable tool for studying ground-state properties of extended materials. The computational complexity of describing the Kohn-Sham orbitals is replaced by introducing a set of random (stochastic) orbitals leading to linear and often sub-linear scaling of certain ground-state observables at the account of introducing a statistical error. Schemes to reduce the noise are essential, for example, for determining the structure using the forces obtained from sDFT. Recently, we have introduced two embedding schemes to mitigate the statistical fluctuations in the electron density and resultant forces on the nuclei. Both techniques were based on fragmenting the system either in real space or slicing the occupied space into energy windows, allowing for a significant reduction in the statistical fluctuations. For chemical accuracy, further reduction of the noise is required, which could be achieved by increasing the number of stochastic orbitals. However, the convergence is relatively slow as the statistical error scales as 1 / N &#x3C7; according to the central limit theorem, where N χ is the number of random orbitals. In this paper, we combined the embedding schemes mentioned above and introduced a new approach that builds on overlapped fragments and energy windows. The new approach significantly lowers the noise for ground-state properties, such as the electron density, total energy, and forces on the nuclei, as demonstrated for a G-center in bulk silicon.

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

Effects of surface diffusion in electrocatalytic CO 2 reduction on Cu revealed by kinetic Monte Carlo simulations

We report Kinetic Monte Carlo (KMC) methods are frequently used for mechanistic studies of thermally driven heterogeneous catalysis systems but are underused for electrocatalysis. Here, we develop a lattice KMC approach for electrocatalytic CO 2 reduction. The work is motivated by a prior experimental report that performed electroreduction of a mixed feed of 12 CO 2 and 13 CO on Cu; differences in the 13 C content of C2 products ethylene and ethanol (Δ 13 C) were interpreted as evidence of site selectivity. The lattice KMC model considers the effect of surface diffusion on this system. In the limit of infinitely fast diffusion (mean-field approximation), the key intermediates 12 CO* and 13 CO* would be well mixed on the surface and no evidence of site selectivity could have been observed. Using a simple two-site model and adapting a previously reported microkinetic model, we assess the effects of diffusion on the relative isotope fractions in the products using the estimated surface diffusion rate of CO* from literature reports. We find that the size of the active sites and the total surface adsorbate coverage can have a large influence on the values of Δ 13 C that can be observed. Δ 13 C is less sensitive to the CO* diffusion rate as long as it is within the estimated range. We further offer possible methods to estimate surface distribution of intermediates and to predict intrinsic selectivity of active sites based on experimental observations. This work illustrates the importance of considering surface diffusion in the study of electrochemical CO 2 reduction to multi-carbon products. Our approach is entirely based on a freely available open-source code, so will be readily adaptable to other electrocatalytic systems.

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

Reduction of efficiency droop in c -plane InGaN/GaN light-emitting diodes using a thick single quantum well with doped barriers

We report on c-plane InGaN/GaN single quantum well (QW) light-emitting diodes (LEDs) of different well widths (3 or 9 nm) with and without doped barriers. QW barriers were doped with the aim of reducing the internal electric field (F QW ) in the QW to increase the electron-hole overlap, therefore increasing the recombination rates and resulting in the reduction of the efficiency droop. We, indeed, observed, through biased photocurrent spectroscopy, a reduction in F QW with doped barriers, with F QW being in the same direction of the p-n junction field at zero bias as opposed to the junction field for LEDs without doped barriers. Even with the improvement in the ground state wavefunction overlap, the ground state transition rate remains low for thick QWs. Transitions through excited states were observed for both thick QW LEDs with and without doped barriers. Here, the thick QW LED without doped barriers displayed low external quantum efficiency (EQE), likely as a result of the carrier overflow due to the poor confinement of carriers in the excited states. On the other hand, for LEDs with doped barriers, the flatter band in the QW resulting from the lower F QW reduces the energy separation between the eigenstates, leading to better confinement of carriers in the excited states. With doped barriers, we demonstrated a low efficiency droop 9-nm-thick single QW LED with a peak EQE of 42% at 40 A/cm 2 and an EQE of 36% at 400 A/cm 2 .

42 ENGINEERING↗
DOE OSTI2023

An uncertainty-aware strategy for plasma mechanism reduction with directed weighted graphs

In this work, we present a framework for the analysis and reduction of plasma mechanisms by means of weighted directed graphs, in which reactions and species are both treated as nodes. The methodology consists of two distinct analyses. The first, which is qualitative, relies on graph spatializations via force-directed algorithms to discover the predominant global patterns in the chemical model. The second ranks the reactions based on their shortest paths' lengths from/to the species of interest and their relative contributions to the power balance. Further, this quantitative investigation enables a strategy for mechanism reduction that is fully automatized, as it does not require any expert knowledge, highly effective, as it generates reduced mechanisms that are highly accurate while relying on a small number of processes, and easily interpretable, as the algorithm justifies the importance of the retained reactions by outputting their related chemical pathways. Additionally, the work proposes a methodology extension that employs ensembles of graphs to improve the robustness of the reduced mechanism to reaction parameter uncertainties. The approach, here tested for steady-state predictions of a plasma system characterizing negative hydrogen ion sources, is general and can be used in a wide variety of applications outside the particular nuclear fusion context demonstrated in this work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Noise reduction of stochastic density functional theory for metals

Density Functional Theory (DFT) has become a cornerstone in the modeling of metals. However, accurately simulating metals, particularly under extreme conditions, presents two significant challenges. First, simulating complex metallic systems at low electron temperatures is difficult due to their highly delocalized density matrix. Second, modeling metallic warm-dense materials at very high electron temperatures is challenging because it requires the computation of a large number of partially occupied orbitals. This study demonstrates that both challenges can be effectively addressed using the latest advances in linear-scaling stochastic DFT methodologies. Despite the inherent introduction of noise into all computed properties by stochastic DFT, this research evaluates the efficacy of various noise reduction techniques under different thermal conditions. Our observations indicate that the effectiveness of noise reduction strategies varies significantly with the electron temperature. Furthermore, we provide evidence that the computational cost of stochastic DFT methods scales linearly with system size for metal systems, regardless of the electron temperature regime.

Chemistry↗
DOE OSTI2024

A physics-informed deep learning description of Knudsen layer reactivity reduction

A physics-informed neural network (PINN) is used to evaluate the fast ion distribution in the hot spot of an inertial confinement fusion target. The use of tailored input and output layers to the neural network is shown to enable a PINN to learn the parametric solution to the Vlasov–Fokker–Planck equation in the absence of any synthetic or experimental data. As an explicit demonstration of the approach, the specific problem of Knudsen layer fusion yield reduction is treated. Here, the predictions from the Vlasov–Fokker–Planck PINN are used to provide a non-perturbative solution of the fast ion tail in the vicinity of the hot spot, thus allowing the spatial profile of the fusion reactivity to be evaluated for a range of collisionalities and hot spot conditions. Excellent agreement is found between the predictions of the Vlasov–Fokker–Planck PINN and the results from traditional numerical solvers with respect to both the energy and spatial distribution of fast ions and the fusion reactivity profile, demonstrating that the Vlasov–Fokker–Planck PINN provides an accurate and efficient means of determining the impact of Knudsen layer yield reduction across a broad range of plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Finite-element-based simulations of electrodes for CO 2 cascade reduction reactions

The multielectron reduction of CO 2 to liquid fuels could be a path to scalable energy storage, but reaching this goal requires major advances in catalysis and systems engineering. Cascade catalysis, which couples sequential reactions without isolating intermediates, has emerged as a promising route to enhance selectivity and efficiency in CO 2 reduction (CO 2 R). In this review, we examine how finite-element-based simulations of continuum model [finite element method (FEM)] approaches are being used to analyze and guide CO 2 R cascade systems. We first outline the fundamentals of cascade catalysis and recent advances in catalytic materials (metallic, molecular, and hybrid architectures). We then focus on FEM developments at the electrode and device scales, emphasizing how these models capture transport phenomena, local microenvironments, and geometry-dependent effects. To clarify design principles, we present case studies of cascade electrodes organized in systems without and with integrated semiconductors. We further emphasize the integration of FEM with multiscale frameworks (density functional theory, molecular dynamics, kinetic Monte Carlo) and its role in bridging atomic-level insights with device-level performance. Finally, we identify current limitations and future prospects, including improved boundary conditions, coupling with operando experiments, and machine learning-accelerated model development. Together, these insights provide design principles for next-generation CO 2 R cascade systems for efficient solar fuel production.

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

CO 2 reduction on pure Cu produces only H 2 after subsurface O is depleted: Theory and experiment

Significance Electrochemical reduction of CO 2 to fuels and valuable chemicals is a global imperative to address energy and climate challenges. Despite enormous efforts, there is not yet a commercial process. The best catalyst remains Cu metal, but a great deal of controversy revolves around the role of the presence of oxygen in the material. We combine theory and experiments to show that pure Cu without subsurface oxygen leads to no organic products. Thus, maintaining substantial oxygen at Cu surfaces is essential for long-term reduction of CO 2 to organics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Shipping regulations lead to large reduction in cloud perturbations

Global shipping accounts for 13% of global emissions of SO2, which, once oxidized to sulfate aerosol, acts to cool the planet both directly by scattering sunlight and indirectly by increasing the albedo of clouds. This cooling due to sulfate aerosol offsets some of the warming effect of greenhouse gasses and is the largest uncertainty in determining the change in the Earth’s radiative balance by human activity. Ship tracks—the visible manifestation of the indirect of effect of ship emissions on clouds as quasi-linear features—have long provided an opportunity to quantify these effects. However, they have been arduous to catalog and typically studied only in particular regions for short periods of time. Using a machine-learning algorithm to automate their detection we catalog more than 1 million ship tracks to provide a global climatology. We use this to investigate the effect of stringent fuel regulations introduced by the International Maritime Organization in 2020 on their global prevalence since then, while accounting for the disruption in global commerce caused by COVID-19. We find a marked, but clearly nonlinear, decline in ship tracks globally: An 80% reduction in SO x emissions causes only a 25% reduction in the number of tracks detected.

54 ENVIRONMENTAL SCIENCES↗