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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Temporal Characterization of Tritium Smear Activities

Tritium collection efficiency varies as a function of smear media. The use of porous smear materials leads to an increase in the measured tritium activity as a function of time when the measurement is performed with liquid scintillation counters. Operational inclusion of the efficiency differences and the time dependence of the tritium smear activity is necessary to preclude inadvertently releasing materials or areas. Thomas Jefferson National Laboratory Radiological Control Department identified a contaminated stainless steel containment vessel that previously housed a target containing more than 37 TBq of tritium. The item was systematically sectioned and surveyed to compare three smear types: water-wetted cotton swabs, water-wetted paper smears, and ethanol-wetted Styrofoam wipes (NUC-Wipes™). The total activity of each section was determined using repeated decontamination. The time dependence of the measured activity was also studied. The measured activity of both paper smears and cotton swabs showed significant time dependence. The cotton swabs also showed significantly reduced collection efficiency. Given the widespread use of both of these media in routine contamination surveys, site operational limits were derived using fitted curves for time dependence and average efficiency results. In conclusion, the use of these more restrictive limits allows for rapid measurement of tritium smears while ensuring regulatory compliance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

In situ synchrotron diffraction of pressure-induced phase transition in DyPO 4 under variable hydrostaticity

In situ synchrotron x-ray diffraction was conducted on polycrystalline DyPO 4 to elucidate the details of the pressure-induced transition from the xenotime polymorph to the monazite polymorph. We used three different pressure-transmitting media (neon, a 16:3:1 methanol-ethanol-water mixture, and potassium chloride) to investigate the effect of hydrostaticity on the phase behavior. Specifically, our data clearly show a hydrostatic onset pressure of the xenotime-monazite transition of 9.1 GPa, considerably lower than the 15.3 GPa previously determined by Raman spectroscopy. Based on (quasi)hydrostatic data taken in a neon environment, third-order Birch-Murnaghan equation-of-state fits give a xenotime bulk modulus of 144 GPa and a monazite bulk modulus of 180 GPa (both with pressure derivatives of 4.0). Structural data and axial compressibilities show that DyPO 4 is sensitive to shear and has an anisotropic response to pressure. More highly deviatoric conditions cause the onset of the transition to shift to pressures at least as low as 7.0 GPa. We attribute early transition to shear-induced distortion of the PO4 tetrahedra. Finally, our characterization of the high-pressure behavior of DyPO 4 under variable hydrostaticity is critical for advancing rare earth orthophosphate fiber coating applications in ceramic matrix composites and may inform future tailoring of phase composition for controlled shear and pressure applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

From ionic clusters dynamics to network constraints in ionic polymer solutions

Physical networks formed by ionizable polymers with ionic clusters as crosslinks are controlled by coupled dynamics that transcend from ionic clusters through chain motion to macroscopic response. Here, the coupled dynamics, across length scales, from the ionic clusters to the networks in toluene swollen polystyrene sulfonate networks, were directly correlated, as the electrostatic environment of the physical crosslinks was altered. The multiscale insight is attained by coupling neutron spin echo measurements with molecular dynamics simulations, carried out to times typical of relaxation of polymers in solutions. The experimental dynamic structure factor is in outstanding agreement with the one calculated from computer simulations, as the networks are perturbed by elevating the temperature and changing the electrostatic environment. In toluene, the long-lived clusters remain stable over hundreds of ns across a broad temperature range, while the polymer network remains dynamic. In conclusion, though the size of the clusters changes as the dielectric constant of the solvent is modified through the addition of ethanol, they remain stable but morph, enhancing the polymer chain dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling the partitioning of amphiphilic molecules and co-solvents in biomembranes

We report amphiphilic co-solvents can have a significant impact on the structure, organization and physical properties of lipid bilayers. Describing the mutual impact of partitioning and induced structure changes is therefore a crucial consideration for a range of topics such as anesthesia and other pharmacokinetic effects, as well as microbial solvent tolerance in the production of biofuels and other fermentation products, where molecules such as ethanol, butanol or acetic acid might be generated. Small-angle neutron scattering (SANS) is a key method for studying lipid and polymer bilayer structures, with many models for extracting bilayer structure (thickness, area per lipid etc.) from scattering data in use today. However, the molecular details of co-solvent partitioning are conflated with induced changes to bilayer structure, making interpretation and modeling of the scattering curves a challenge with the existing set of models. To address this, a model of a bilayer structure is presented which invokes a two-term partition constant accounting for the localization of the co-solvent within the bilayer. This model was validated using a series of SANS measurements of lipid vesicles in the presence of the co-solvent tetrahydrofuran (THF), showing several strategies of how to deploy the two-parameter partition constant model to describe scattering data and extract both structure and partitioning information from the data. Molecular dynamics simulations are then used to evaluate assumptions of the model, provide additional molecular scale details and illustrate its complementary nature to the data fitting procedure. This approach results in estimates of the partition coefficient for THF in 1,2-dimyristoyl-sn-glycero-3-phosphocholine at 35°C, along with an estimate of the fraction of THF residing in the hydrophobic core of the membrane. The authors envision that this model will be applicable to a wide range of other bilayer/amphiphile interactions and provide the associated code needed to implement this model as a fitting algorithm for scattering data in the SasView suite.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structural characterization of a new samarium–sodium heterometallic coordination polymer

Lanthanide-containing materials are of interest in the field of crystal engineering because of their unique properties and distinct structure types. In this context, a new samarium–sodium heterometallic coordination polymer, poly[tetrakis(μ 2 -2-formyl-6-methoxyphenolato)samarium(III)sodium(I)], {[SmNa(C 8 H 7 O 3 ) 4 ]·solvent} n ( Sm-1 ), was synthesized and crystallized via slow evaporation from a mixture of ethanol and acetonitrile. The compound features alternating Sm III and Na I ions, which are linked by ortho -vanillin ( o -vanillin) ligands to form a mono-periodic chain-like coordination polymer. The chains propagate along the [001] direction. Residual electron density of disordered solvent molecules in the void space could not be reasonably modeled, thus the SQUEEZE function was applied. The structural, vibrational, and optical properties are reported.

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

Intelligent Electrochemical Sensors for Precise Identification of Volatile Organic Compounds Enabled by Neural Network Analysis

The volatile organic compounds (VOCs) in a wide spectrum of categories were identified as biomarkers in aquatic environments, playing an important role in marine and freshwater ecology and global atmospheric chemistry. VOCs released from biofuel have also attracted increasing attention. Although the importance has been recognized, the portable detection and analysis methods of VOC in aquatic systems have not yet been well developed and understood. Here, in this work, we innovatively proposed an intelligent electrochemical sensing approach to classify and quantify VOCs in solution. Utilizing the cyclic voltammetry (CV) method with an ionic liquid (IL)-based electrolyte, we analyzed 50 μL samples of various VOC analytes, including acetic acid (AC), acetone, dimethylformamide (DMF), dimethyl sulfoxide (DMSO), ethanol, formaldehyde, formic acid, methanol, methyl formate (MF), toluene, and a formaldehyde-methanol mixture, along with deionized water (DI water). The generated voltammograms were subsequently analyzed using our uniquely designed and optimized 1-D convolutional neural network (1D-CNN). This deep-learning algorithm achieved a 99.09% accuracy in VOC classification validated through fivefold cross-validation and demonstrated an impressive 94.4% test accuracy for methanol detection within a 10 μL error range. For quantification, the system accurately categorized methanol volumes ranging from 0 to 50 μL in 10 μL increments, achieving a 98.18% accuracy. A notable linear correlation (R2 = 95.56%) was found between max current density at the oxidation peak and methanol volume, with the limit of detection (LOD) at 9.3 μL. Such a sensing method exhibits potential for portability, high accuracy, and generalization in the classification and quantification, ultimately reshaping the realm of VOC analysis in solution.

42 ENGINEERING↗
DOE OSTI2024

Evaluating Impacts of Sustainable Aviation Fuel Production with CO2-to-Fuels Technologies on High Renewable Share Power Grid

This paper investigates the impact of Sustainable Aviation Fuel (SAF) production using CO 2 -to-Fuels technologies on a future power grid with a high share of renewable energy. We focus on understanding the implications of the 2050 SAF production goal on the U.S. power system's long-term planning, encompassing generation, transmission, and cost analysis. Via the Regional Energy Deployment System (ReEDS) model, we developed a detailed SAF electricity demand model based on a low-temperature electrolysis-syngas fermentation-ethanol pathway. Four SAF target scenarios which aim to meet 10%, 15%, 20%, and 27% of SAF demand by 2050. These scenarios are exhaustively simulated to assess their impact on the power grid. Our results reveal that increasing SAF demand will result in higher electricity requirements, as well as expanded generator and transmission capacities, leading to an overall rise in system costs. However, these impacts are manageable within the broader context of U.S. capacity expansion plans. This study provides valuable insights into incorporating the CO 2 -to-Fuels electricity demand model and other carbon capture technologies into power system planning, emphasizing their significance in shaping a sustainable energy future.

capacity expansion model↗
DOE OSTI2023

Harvest and nitrogen effects on bioenergy feedstock quality of grass-legume mixtures on Conservation Reserve Program grasslands

Perennial grass mixtures established on Conservation Reserve Program (CRP) lands can be an important source of feedstock for bioenergy production. This study aimed to evaluate management practices for optimizing the quality of bioenergy feedstock and stand persistence of grass-legume mixtures under diverse environments. A 5-year field study (2008–2012) was conducted to assess the effects of two harvest timings (at anthesis vs after complete senescence) and three nitrogen (N) rates (0, 56, 112 kg N ha -1 ) on biomass chemical compositions (i.e., cell wall components, ash, volatiles, total carbon, and N contents) and the feedstock energy potential, examined by the theoretical ethanol yield (TEY) and the total TEY (i.e., the product of biomass yield and TEY, L ha -1 ), of cool-season mixtures in Georgia and Missouri and a warm-season mixture in Kansas. The canonical correlation analysis (CCA) was used to investigate the effect of vegetative species transitions on feedstock quality. Although environmental variations (mainly precipitation) greatly influenced the management effect on chemical compositions, the delayed harvest after senescence generally improved feedstock quality. In particular, the overall cell wall concentrations and TEY of the warm-season mixtures increased by approximately 7%. Additional N supplies improved the total TEY of both mixtures by ~1.6–4.2 L ha -1 per 1.0 kg N ha -1 input but likely lowered the feedstock quality, particularly for the cool-season mixture. The cell wall concentrations of cool-season mixture reduced by approximately 3%–6%. The CCA results indicated that the increased legume compositions (under low N input) likely enhanced lignin but reduced ash concentrations. This field research demonstrated that with proper management, grass-legume mixtures on CRP lands can provide high-quality feedstock for bioenergy productions.

09 BIOMASS FUELS↗
DOE OSTI2024

High temperatures and low soil moisture synergistically reduce switchgrass yields from marginal field sites and inhibit fermentation

‘Marginal lands’ are low productivity sites abandoned from agriculture for reasons such as low or high soil water content, challenging topography, or nutrient deficiency. To avoid competition with crop production, cellulosic bioenergy crops have been proposed for cultivation on marginal lands, however on these sites they may be more strongly affected by environmental stresses such as low soil water content. In this study we used rainout shelters to induce low soil moisture on marginal lands and determine the effect of soil water stress on switchgrass growth and the subsequent production of bioethanol. Five marginal land sites that span a latitudinal gradient in Michigan and Wisconsin were planted to switchgrass in 2013 and during the 2018–2021 growing seasons were exposed to reduced precipitation under rainout shelters in comparison to ambient precipitation. The effect of reduced precipitation was related to the environmental conditions at each site and biofuel production metrics (switchgrass biomass yields and composition and ethanol production). During the first year (2018), the rainout shelters were designed with 60% rain exclusion, which did not affect biomass yields compared to ambient conditions at any of the field sites, but decreased switchgrass fermentability at the Wisconsin Central–Hancock site. In subsequent years, the shelters were redesigned to fully exclude rainfall, which led to reduced biomass yields and inhibited fermentation for three sites. When switchgrass was grown in soils with large reductions in moisture and increases in temperature, the potential for biofuel production was significantly reduced, exposing some of the challenges associated with producing biofuels from lignocellulosic biomass grown under drought conditions.

09 BIOMASS FUELS↗
DOE OSTI2023

Fermentation‐mediated growth, signaling, and defense in plants

Summary While traditionally considered important mainly in hypoxic roots during flooding, upregulation of fermentation pathways in plants has recently been described as an evolutionarily conserved drought survival strategy, with acetate signaling mediating reprograming of transcription and cellular carbon and energy metabolism from roots to leaves. The amount of acetate produced directly correlates with survival through potential mechanisms including defense gene activation, biosynthesis of primary and secondary metabolites, and aerobic respiration. Here, we review root ethanolic fermentation responses to hypoxia during saturated soil conditions and summarize studies highlighting acetate fermentation under aerobic conditions coupled with respiration during growth and drought responses. Recent work is discussed demonstrating long‐distance transport of acetate via the transpiration stream as a respiratory substrate. While maintenance and growth respiration are often modeled separately in terrestrial models, here we propose the concept of ‘Defense Respiration’ fueled by acetate fermentation in which upregulation of acetate fermentation contributes acetate substrate for alternative energy production via aerobic respiration, biosynthesis of primary and secondary metabolites, and the acetylation of proteins involved in defense gene regulation. Finally, we highlight new frontiers in leaf‐atmosphere emission measurements as a potential way to study acetate fermentation responses of individual leaves, branches, ecosystems, and regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Cell wall ester modifications and volatile emission signatures of plant response to abiotic stress

Abstract Growth suppression and defence signalling are simultaneous strategies that plants invoke to respond to abiotic stress. Here, we show that the drought stress response of poplar trees ( Populus trichocarpa ) is initiated by a suppression in cell wall derived methanol (MeOH) emissions and activation of acetic acid (AA) fermentation defences. Temperature sensitive emissions dominated by MeOH (AA/MeOH <30%) were observed from physiologically active leaves, branches, detached stems, leaf cell wall isolations and whole ecosystems. In contrast, drought treatment resulted in a suppression of MeOH emissions and strong enhancement in AA emissions together with volatiles acetaldehyde, ethanol, and acetone. These drought‐induced changes coincided with a reduction in stomatal conductance, photosynthesis, transpiration, and leaf water potential. The strong enhancement in AA/MeOH emission ratios during drought (400%–3500%) was associated with an increase in acetate content of whole leaf cell walls, which became significantly 13 C 2 ‐labelled following the delivery of 13 C 2 ‐acetate via the transpiration stream. The results are consistent with both enzymatic and nonenzymatic MeOH and AA production at high temperature in hydrated tissues associated with accelerated primary cell wall growth processes, which are downregulated during drought. While the metabolic source(s) require further investigation, the observations are consistent with drought‐induced activation of aerobic fermentation driving high rates of foliar AA emissions and enhancements in leaf cell wall O ‐acetylation. We suggest that atmospheric AA/MeOH emission ratios could be useful as a highly sensitive signal in studies investigating environmental and biological factors influencing growth‐defence trade‐offs in plants and ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Influence of Fuel Properties on Gasoline Direct Injection Particulate Matter Emissions Over First 200 s of World-Harmonized Light-Duty Test Procedure Using an Engine Dynamometer and Novel “Virtual Drivetrain” Software

Abstract The influence of fuel properties on particulate matter (PM) emissions from a catalytic gasoline particulate filter (GPF) equipped gasoline direct injection (GDI) engine was investigated using novel “virtual drivetrain” software and an engine mated to an engine dynamometer. The virtual drivetrain software was developed in labview to operate the engine on an engine dynamometer as if it were in a vehicle undergoing a driving cycle. The software uses a physics-based approach to determine vehicle acceleration and speed based on engine load and a programed “shift” schedule to control engine speed. The software uses a control algorithm to modulate engine load and braking to match a calculated vehicle speed with the prescribed speed trace of the driving cycle of choice. The first 200 s of the World-harmonized Light-duty Test Procedure (WLTP) driving cycle was tested using six different fuel formulations of varying volatility, aromaticity, and ethanol concentration. The first 200 s of the WLTP was chosen as the test condition because it is the most problematic section of the driving cycle for controlling PM emissions due to the cold start and cold drive off. It was found that there was a strong correlation between aromaticity of the fuel and the engine-out PM emissions, with the highest emitting fuel producing more than double the mass emissions of the low PM production fuel. However, the post-GPF PM emissions depended greatly on the soot loading state of the GPF. The fuel with the highest engine-out PM emissions produced comparable post-GPF emissions to the lowest PM producing fuel over the driving cycle when the GPF was loaded over three cycles with the respective fuels. These results demonstrate the importance of GPF loading state when aftertreatment systems are used for PM reduction. It also shows that GPF control may be more important than fuel properties, and that regulatory compliance for PM can be achieved with proper GPF control calibration irrespective of fuel type.

Energy & Fuels↗
DOE OSTI2021

A Transported Livengood–Wu Integral Model for Knock Prediction in Computational Fluid Dynamics Simulation

This work describes the development of a transported Livengood–Wu (L–W) integral model for computational fluid dynamics (CFD) simulation to predict autoignition and engine knock tendency. The currently employed L–W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics, and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition (HCCI) combustion for three different fuels, showing good accuracy in prediction of autoignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L–W integral model is coupled with G-equation model to indicate end-gas autoignition and knock tendency in CFD simulations of a direct-injection spark-ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely, Co-Optima alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multivariable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity, and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency—indicated by the fuel energy contained in the autoignited region—of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Shock Tube and Flame Speed Measurements of 2,4,4-Trimethyl-1-Pentene: A Co-Optima Biofuel

Abstract The combustion of 2,4,4-trimethyl-1-pentene (diisobutylene, C8H16), which is a biofuel and a component of surrogate fuels, is examined in this work. Carbon monoxide time–histories and ignition delay times are collected behind reflected shock waves utilizing a shock tube and mid-infrared laser absorption spectroscopy. Measurements were obtained near 10 atm pressure during stoichiometric oxidation of 0.15%C8H16/O2/Ar. Simulated results from chemical kinetic models are provided, and sensitivity analyses are used to discuss differences between models for both ignition delay times and carbon monoxide formation. In addition, laminar burning speeds are obtained at 1 atm, 428 K, and equivalence ratios, phi, between 0.91 and 1.52 inside a spherical chamber facility. Measured burning speeds are found to be less than that of ethanol over the equivalence ratio span. Burning speed measurements are compared to predictions of chemical kinetic mechanisms and are in agreement for the richest conditions; however, at lean conditions, the model predicts a far slower-burning speed. The maximum burning speed occurs at an equivalence ratio of 1.08 with a magnitude of 0.70 m/s. The current work provides the crucial experimental data needed for assessing the feasibility of this biofuel and for the development of future combustion chemical kinetics models.

Energy & Fuels↗
DOE OSTI2020

effect of ambient pressure on the behavior of single-component fuels in a gasoline multi-hole injector

The injection characteristics of neat ethanol and pure isooctane are studied under different ambient pressure and temperature conditions. Injection underflash-boiling conditions can enhance liquid atomization and evaporation, providing the possibility of improvement in the fuel/air mixing. These superheated conditions often introduce phenomena that are not taken into account in the standard modeling of sprays for engine applications. The present work proposes a numerical investigation of the behavior of Engine Combustion Network's 8-hole spray-G injector, starting at the subcooled nominal condition and reducing the ambient pressure at constant low temperature to reach the flare flash-boiling condition. To initialize the properties of the injected fuel, the flow in the nozzle is simulated with a Eulerian approach, handling the two phases with a mixture model and the phase change, due to cavitation and flash boiling, with the Homogenous Relaxation Model. A map of the mixture's kinematic and thermal behavior is obtained at the interface between the injector and the chamber to initialize the Lagrangian simulations. A literature-based vaporization model is implemented to obtain the proper description of the characteristic features of a multi-hole spray under super-heated conditions, like plume-plume interaction. The numerical representation of the spray is validated in terms of penetration and radial spreading on DBI images, reproducing the light attenuation profiles caused by the presence of the liquid spray. Simulations show that coupled nozzle flow and spray calculations capture the spray morphology and shape better compared to calculations performed without considering the nozzle flow simulation details, especially under flare flash conditions.

Nocivelli, Lorenzo↗
DOE OSTI2020

A transported Livengood-Wu integral model for knock prediction in CFD simulation

This work describes the development of a transported Livengood-Wu (L-W) integral model for computational fluid dynamics (CFD) simulation to predict auto-ignition and engine knock tendency. The currently employed L-W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition combustion for three different fuels, showing good accuracy in prediction of auto-ignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L-W integral model is coupled with G-equation model to indicate end-gas auto-ignition and knock tendency in CFD simulations of a direct injection spark ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely Co-Optima Alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multi-variable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency indicated by the fuel energy contained in the auto-ignited region of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.

Yue, Zongyu↗
DOE OSTI2023

Preparation and Characterization Methods of Thin Layer Samples for Standoff Detection

Detection of analytes deposited on surfaces is crucial for many applications: Development of methods to prepare thin layers (e.g. ~5 to 100 µm) is important for both system design and field studies. In this work, solid and liquid analytes were deposited on painted and bare substrates including aluminum, glass, plastic, and concrete using an ExactaCoat ultrasonic spray coater. Laboratory hemispherical reflectance (HRF) spectra were collected for samples with different layer thicknesses so as to characterize both the composition and layer thickness. Preliminary results demonstrate that to prepare homogenous layers on surfaces, parameters such as substrate type, analyte solubility, vapor pressure, paint color, surface porosity, and surface roughness are all important. Liquid chemicals posed several issues during deposition: Diisopropyl methyl phosphonate evaporated from surfaces more quickly than the other chemicals and was thus not detected in the HRF experiments. Less volatile liquids, such as tributylphosphate, remained on the surface for the duration of the test, but a uniform layer thickness could not be obtained as the liquid pooled to one side when mounted at an angle. The deposition of solids (e.g., acetaminophen, caffeine and methylphosphonic acid) from volatile solvents such as chloroform also proved problematic due to streaking caused by rapid solvent evaporation. Solids deposited from ethanol, however, worked well on bare substrates. For most samples plotting the integrated infrared band strength vs. surface thicknesses showed a linear relationship, confirming that the surface loading can be controlled by programming the concentration and the number of passes on the ultrasonic sprayer.

Thin layer, deposition, infrared standoff, Hemisph↗
DOE OSTI2023

CO electroreduction on single-atom copper

Electroreduction of carbon dioxide (CO 2 ) or carbon monoxide (CO) toward C 2+ hydrocarbons such as ethylene, ethanol, acetate and propanol represents a promising approach toward carbon-negative electrosynthesis of chemicals. Fundamental understanding of the carbon–carbon (C-C) coupling mechanisms in these electrocatalytic processes is the key to the design and development of electrochemical systems at high energy and carbon conversion efficiencies. Here, we report the investigation of CO electreduction on single-atom copper (Cu) electrocatalysts. Atomically dispersed Cu is coordinated on a carbon nitride substrate to form high-density copper–nitrogen moieties. Chemisorption, electrocatalytic, and computational studies are combined to probe the catalytic mechanisms. Unlike the Langmuir-Hinshelwood mechanism known for copper metal surfaces, the confinement of CO adsorption on the single-copper-atom sites enables an Eley-Rideal type of C-C coupling between adsorbed (*CO) and gaseous [CO(g)] carbon moxide molecules. The isolated Cu sites also selectively stabilize the key reaction intermediates determining the bifurcation of reaction pathways toward different C 2+ products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗