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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Cryogenic Fluid Technologies for Long Duration In-Space Operations

Reliable knowledge of low-gravity cryogenic fluid management behavior is lacking and yet is critical in the areas of storage, distribution, and low-gravity propellant management. The Vision for Space Exploration mission objectives will require the use of high performance cryogenic propellants (hydrogen, oxygen, and methane). Additionally, lunar missions will require success in storing and transferring liquid and gas commodities on the surface. The fundamental challenges associated with the in-space use of cryogens are their susceptibility to environmental heat, their complex thermodynamic and fluid dynamic behavior in low gravity and the uncertainty of the position of the liquid-vapor interface if the propellants are not settled. The Cryogenic Fluid Management (CFM) project is addressing these issues through ground testing and analytical model development, and has crosscutting applications and benefits to virtually all missions requiring in-space operations with cryogens. Such knowledge can significantly reduce or even eliminate tank fluid boil-off losses for long term missions, reduce propellant launch mass and on-orbit margins, and simplify vehicle operations. The Cryogenic Fluid Management (CFM) Project is conducting testing and performing analytical evaluation of several areas to enable NASA s Exploration Vision. This paper discusses the content and progress of the technology focus areas within CFM.

Motil, Susan M.↗
NASA NTRSDate not supplied

Geometry Systems for Lattice-Based Reconfigurable Space Structures

We describe analytic methods for the design of the discrete elements of ultralight lattice structures. This modular building block strategy allows for relatively simple element manufacturing as well as relatively simple robotic assembly of low mass-density structures on orbit, with potential for disassembly and reassembly into highly varying and large structures. This method also results in a structure that is easily navigable by relatively small, mobile robots. The geometry of the cell can allow for high packing efficiency to minimize wasted payload volume while maximizing structural performance and constructability. We describe the effect of geometry choices on the mechanical properties and automated robotic constructability of a final system. Geometric properties considered include number of attachments per voxel, number of attachments per coefficient of volume, and effects of vertex, edge, and face connectivity of the unit cell. Mechanical properties considered include strength scaling, modulus scaling, and packing efficiency of the lattice. Automated constructibility metrics include volume allowance for an end-effector, strut clearance angle for an end-effector, and packing efficiency. These metrics were applied to six lattice unit cell geometries: cube, cuboctahedron, octahedron, octet, rhombic dodecahedron, and truncated octahedron. A case study is presented to determine the most suitable lattice system for a specific set of strength and modulus scaling requirements while optimizing for ease of robotic assembly.

digital materials↗
NASA NTRSDate not supplied

Oxygen Isotopic Composition of Refractory Inclusions from the Miller Range (MIL) 090019 Carbonaceous Chondrite

Introduction: Primitive meteorites contain Calcium-Aluminum-rich Inclusions (CAIs)that preserve the records of the earliest times in the Solar System. CAIs record O isotopic variations with time and/or location from solar (16O-rich) to planetary (16O-poor) compositions [e.g., 1, 2].However, CAIs were also affected by parent body processing to varying degrees. The goal of this work was to identify the processes that resulted in the fine-scale spatial variations in oxygen isotopic compositions within the most ancient Solar System solids. We report oxygen isotopic composition of CAIs from MIL 090019 CO3.1 carbonaceous chondrite. MIL 090019 contains a high abundance of CAIs showing mineralogical as well as textural variations [3]. Methods: We analyzed 10 CAIs with different mineralogical assemblages, classified as corundum-bearing, grossite-bearing, hibonite-bearing, melilite-bearing, anorthite-bearing inclusions and amoeboid olivine aggregates(AOA’s). The mineralogical and petrological characterization of CAIs was performed using the JOEL Hyperprobe 8530 electron microprobe at NASA JSC. Oxygen isotopic imaging of the CAIs was done using the Cameca NanoSIMS 50L ion microprobe at NASA JSC. We followed the analytical protocol described in [4]. O-isotopic maps of the CAI were acquired by rastering a ~3 pA primary Cs+beam at 16 keVover an area of 20 ×20μm2over a period of ~7 hours. Negative secondary ions of 16O−, 17O−, 18O−, 28Si−, 24Mg16O−, 27Al16O−, and 40Ca16O−were simultaneously acquired using electron multiplier detectors at a mass resolving power sufficient to resolve the 16OH−interference from the 17O−peak, where the contribution of 16OH−was <0.1%.An electron flood gun was used to mitigate sample charging during the analyses. We used San Carlos olivine and Madagascar hibonite as isotopic standards to correct for the instrumental mass fractionation. The O-isotopic ratios were corrected for the quasi simultaneous arrival (QSA) effect and the detector dead time. All reported errors are 1 sigma. Results: The MIL 090019 carbonaceous chondrite hosts refractory inclusions varying in their mineralogies and textures[2, 3]. We found the oxygen isotopic compositions of mineral phases in MIL 090019 CAIs show large variations with Δ17O values varying from -27 to 0‰. A corundum-bearing inclusion records isotopic variations with corundum, melilite, perovskite, and anorthite showing Δ17Ovalues of -20 ±2.5, -10.2 ± 6.5, -10.7 ± 1.3,and -1.2 ± 3.2‰ respectively. A grossite-hibonite-bearing inclusion also records O-isotopic heterogeneity, where grossite, hibonite, Mg-rich spinel, and melilite show -3.7 ± 2.7, -22.9 ± 2.5, -21.4 ± 2.6, and -17.3 ± 2.8‰ respectively, whereas perovskite grains record a heterogenous isotopic composition ranging from -22.6 to -13.9‰. A hibonite-bearing inclusion shows average Δ17Ο values of -17.6 ± 5.3 ‰ and -15.1 ± 4.8 ‰ for hibonite and spinel respectively. The two perovskite grains also show relatively 16O-poor composition (Δ17Ο = -11.8 ± 6.4 ‰ and -8.6 ± 5.2 ‰). Anorthite has ~0.1 wt% Na2O and ~0.52 wt% FeO and a Δ17Ο value of -7.2 ± 5.0 ‰, whereas diopside records a Δ17Ο value of -3.5 ± 5.0 ‰. A hibonite-spinel-rich inclusion contains spinel and hibonite that are16O-rich (Δ17Οvalues -21.3 ± 2.8‰ and -19.4 ± 3.0‰, respectively). Melilite shows heterogenous oxygen isotopic composition, with an inner 16O-rich region and an outer 16O-poor region separated by a sharp boundary, with a bulk Δ17Ο= -16.2 ± 2.1‰, whereas two perovskite grains are relatively 16O-poor (Δ17Ο= -13.2 ± 3.7‰ and -7.1 ± 3.4‰).A spinel-rich inclusion contains perovskite grains with Δ17Οranging from -27.0 to -22.8 ‰and spinel with average Δ17Οvalue of -21.4 ± 2.8 ‰. In a melilite and spinel-rich CAI, perovskite, spinel, diopside, melilite, and Al-Ti-rich pyroxene record Δ17Ο values of-26.9 ± 4.6‰, -22.4 ± 4.3‰,-23.4 ± 4.9, -19.3 ± 3.4, and -19.0 ± 4.3 ‰ respectively. Olivine and spinel components of 2 AOA’s record a 16O-rich composition with Δ17O~-23‰. Discussion: The coexistence of 16O-rich and 16O-poor minerals within CAIs has been attributed to differing degrees of O isotopic exchange, reflecting a wide range of O diffusion rates[5]. However, the O isotopic heterogeneity observed in these CAIs cannot be explained by oxygen diffusion in nebular or parent body settings alone. The isotopic imaging of CAIs from the MIL 090019 meteorite shows variations in the O isotopic composition recorded in their mineral components, suggesting that these CAIs record the oxygen isotopic heterogeneity in the nebular gas from which they condensed. The coexistence of 16O-rich and 16O-poor mineral components in the CAI-forming region suggests that the gas in this region was not well-mixed and consisted of distinct 16O-rich and 16O-poor gaseous reservoirs.

P Mane↗
DOE OSTI2022

Nuclide inventory validation: radiochemical assay data quality and modeling challenges in benchmark models development

Oak Ridge National Laboratory is conducting radiochemical assay experiments, using high-precision analytical protocols validated with a comprehensive quality assurance plan, to expand the nuclide inventory validation basis for high burnup spent nuclear fuel. Preliminary measurement data for key actinides and fission products in two pressurized water reactor spent fuel samples are being used to investigate the impact of measurement data uncertainty on the sample burnup estimation. These measurement data are also being used to examine the impact of assumptions applied when developing best-estimate computational models to simulate fuel irradiation history. The simulations are being performed using depletion capabilities in the SCALE code system. Comparison of calculated and measured nuclide concentrations shows good agreement for the considered nuclides. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

"Designing, simulating, and performing the 100-AV field test for the CIRCLES consortium: Methodology and Implementation of the Largest mobile traffic control experiment to date"

Previous controlled experiments on single-lane ring roads have shown that a single partially autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts the question of how these findings can be generalized to field operational, high-density traffic conditions. To address this question, the Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES) Consortium conducted MegaVanderTest (MVT), a live traffic control experiment involving 100 vehicles near Nashville, TN, USA. This article is a tutorial for developing analytical and simulation-based tools essential for designing and executing a live traffic control experiment like the MVT. It presents an overview of the proposed roadmap and various procedures used in designing, monitoring, and conducting the MVT, which is the largest mobile traffic control experiment at the time. The design process is aimed at evaluating the impact of the CIRCLES AVs on surrounding traffic. The article discusses the agent-based traffic simulation framework created for this evaluation. A novel methodological framework is introduced to calibrate this microsimulation, aiming to accurately capture traffic dynamics and assess the impact of adding 100 vehicles to existing traffic. The calibration model's effectiveness is verified using data from a six-mile section of Nashville's I-24 highway. The results indicate that the proposed model establishes an effective feedback loop between the optimizer and the simulator, thereby calibrating flow and speed with different spatiotemporal characteristics to minimize the error between simulated and real-world data. Finally, We simulate AVs in multiple scenarios to assess their effect on traffic congestion. This evaluation validates the AV routes, thereby contributing to the execution of a safe and successful live traffic control experiment via AVs.

Ameli, Mostafa↗
DOE OSTI2025

Chelation ion chromatography as an automated, and cost-effective analytical technique for REE determination: method development and applications

Rare earth elements (REEs), as critical minerals, have important uses in modern energy and technologies, yet are vulnerable to potential supply chain disruptions. To establish domestic REE supply chain, efficient REE detection methods for resource characterization and mineral processing will be needed to accelerate innovations for domestic REE recovery. This study developed a rapid, novel, and cost-effective for REE detection method using ion chromatography (IC) for aqueous samples. Various REE-targeted eluent gradients and post-column agent compositions were tested on the chelation ion chromatography (CIC) with UV-vis detector for optimal separation and quantification of REEs within approximately 20 min. The single-channel pump to deliver the post-column solution to UV-vis detector was replaced with a 4-channel gradient pump, to increase operation and maintenance efficiencies. After method optimization, resulting calibration curves for more than ten REEs achieved high coefficients of determination (R2>0.999) and low relatively standard deviations (below 3.24%), demonstrating sub-ppm level detection limits (0.0897 to 0.1149 mg/L). The reliability of the CIC method was validated through comparison with inductively coupled plasma mass spectrometry (ICP-MS), showing strong agreement in REE recovery from certified standards. The impact of metal ions and salts on REE recovery using CIC was also systematically investigated. CIC consistently exhibited reliable performance in the presence of salt solutions such as NaCl and Na₂SO₄ (up to 10,000 mg/L). Our study also found the presence of high concentrations of Al ions (at 10,000 mg/L) significantly influenced REE determination, and elevated concentrations of Ca ions affected the recovery of specific REEs, including La, Ce, and Pr. The CIC method was further tested on REE-containing eluents from solvent extraction tests out of fly ash leachates. REE detection from these real processing fluids were reported to achieve 90% to 100% recovery rate from our IC method, compared to ICP-MS results. This study underscores the potential of CIC as a reliable and efficient alternative for REE determination in complex matrices. It also highlights the importance of minimizing select interfering metal ions in solutions to ensure accurate results. The REE CIC method presents a promising, low-maintenance, salt-tolerant, and cost-effective alternative to traditional analytical methods for REE analysis.

detection of rare earth elements (REE)↗
NASA NTRS1985

High thermal capacity cold plate/hot plate

The results of an analytical study to determine the feasibility of a novel two-phase cold plate/hot plate (CPHP) are presented. A key feature of the CPHP is the use of capillary forces to separate the liquid and vapor phases and distribute the liquid over the evaporating/condensing surface. The liquid phase is held by capillary forces in a reservoir and is carried to the evaporating surface by a wick. The reservoir is replenished at intervals from a valved external liquid supply line. In the hot plate mode, liquid accumulates in the reservoir and is removed by an external condensate line. Performance requirements for the device were capability of handling a power density of 4 watts/sq cm, an outlet quality (percentage of vapor flow to total flow) greater than 90 percent, and operation in a 0-g environment. An analytical model of CPHP operation was developed which concentrated on the liquid and vapor flows. It was found that the liquid carrying capillary grooves of rectangular cross-section gave significantly better predicted performance than V-shaped grooves. Using the analytical model, capillary groove width and length, vapor channel dimensions, and other parameters were selected to meet the performance requirements with a 100-percent margin.

Hwangbo, H.↗
DOE OSTI2026

Energy-efficient scientific computing using chemical reservoirs

The rapid growth of computing demands driven by scientific computing, data analytics, and artificial intelligence (AI) advancements has exposed the limitations of traditional digital processing systems. These systems are nearing physical energy barriers, making significant gains in energy efficiency increasingly unattainable. As we advance toward post-exascale computing, disruptive approaches are critical to overcoming these limitations. Among emerging analog solutions, biochemical computing offers a transformative path for achieving orders-of-magnitude improvements in energy efficiency. By leveraging the natural optimization capabilities of chemical reaction networks (CRNs), biochemical systems have the potential to meet high-performance computing needs through natural scalability. However, numerous challenges remain, including theoretical limitations in mapping computational problems to CRNs and practical barriers in implementing biochemical computing devices. In this paper, we present a framework for chemical computation using biochemical systems and introduce key components of our approach for energy-efficient scientific computing. We showcase the feasibility of this framework by solving a system of ordinary differential equations by emulating a chemical reservoir device, demonstrating its potential for addressing modern computing challenges. This work lays a foundational step toward harnessing the computational power of chemistry to design energy-efficient, scalable, high-performance next-generation computing systems.

Johnson, Connah G. M. [Pacific Northwest National ↗
DOE OSTI2022

Prediction of strain, inter-layer interaction and critical current in CORC ® wires under axial strain by T-A modeling

Superconducting conductors on round core (CORC ® ) cables and wires can meet the needs of large high-field magnets, such as particle accelerators and compact nuclear fusion machines, due to their simple cabling process, high current-carrying capacity and reliable operation under high mechanical stresses. Many high-field magnets require CORC ® cables to carry a current of thousands of amperes in a background magnetic field exceeding 20 T. As a result, the large electromagnetic forces will deform the cable in the axial direction due to hoop stress and in the transverse direction by compressive stress. Therefore, it is essential to determine the irreversible deformation limit of the CORC ® cable under axial tensile load and optimize the cabling parameters to potentially extend this limit. Analytical and numerical methods are developed to assess the performance degradation of CORC ® wires under axial tensile load. The strain level, interlayer contact pressure and friction and their impact on the critical current are calculated by combining the mechanical response and the T-A method. Analyzing the results shows that the winding angle of the tape and the Poisson’s ratio of the inner core are key factors affecting the irreversible tensile strain limit of CORC ® wires. The smaller the winding angle and the higher the Poisson’s ratio of the inner core, the higher the irreversible tensile strain limit. For multi-layer CORC ® wires, the initial contact pressure caused by the cabling process must also be considered. The inter-layer interaction is coupled with the tape strain of each layer. The results of this research can serve as a basis for optimizing and designing CORC ® wires with extended irreversible strain limits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Assess and Benchmark Magneto-Inertial Fusion (MIF) Scaling. Final Technical Report for the SNL/Rochester ALPHA Follow-on Project

This project was a follow-on to the Sandia National Laboratories (SNL) and the Laboratory for Laser Energetics (LLE) ARPA-E ALPHA project entitled “Demonstrating Fuel Magnetization and Laser Heating Tools for Low-Cost Fusion Energy”. The primary purpose of this follow-on project was to obtain additional data at the OMEGA facility to help better understand how MagLIF, a platform that has already demonstrated the scientific viability of magneto-inertial fusion, scales across a factor of 1000 in driver energy. A secondary aspect of this project was to extend simulations and analysis at SNL to cover a wider magneto-inertial fusion (MIF) parameter space and test scaling of those models across this wide range of input energies and conditions of the target. This work was successful in improving understanding of how key physics elements of MIF scales and improves confidence in setting requirements for fusion gain with larger drivers. The OMEGA experiments at the smaller scale verified the hypothesis that preheating the fuel plays a significant role in introducing wall contaminants that mix into the fuel and significantly degrade fusion performance. This contamination not only impacts target performance but the optimal input conditions for the target. However, analysis at the Z-scale showed that target performance at high preheat levels is limited by the Nernst effect, which advects magnetic flux from the hot spot, reducing magnetic insulation and consequently reduces the temperature of the fuel. The combination of MagLIF experiments at the disparate scales of OMEGA and Z along with a multiscale 3D simulation analysis has led to new insight into the physical mechanisms responsible for limiting target performance and provides important benchmarks to assess target scaling more generally for MIF schemes. Finally, in addition to the MagLIF related work, a semi-analytic model of liner driven Field Reversed Configuration (FRC) was developed that predicts the fusion gain for such systems. This model was also validated with 2D radiation magneto-hydrodynamic simulations and predicts that fusion gains of near unity could be driven by the Z machine.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Implementing Spatio-Temporal 3D-Convolution Neural Networks and UAV Time Series Imagery to Better Predict Lodging Damage in Sorghum

Unmanned aerial vehicle (UAV)-based remote sensing is gaining momentum in a variety of agricultural and environmental applications. Very-high-resolution remote sensing image sets collected repeatedly throughout a crop growing season are becoming increasingly common. Analytical methods able to learn from both spatial and time dimensions of the data may allow for an improved estimation of crop traits, as well as the effects of genetics and the environment on these traits. Multispectral and geometric time series imagery was collected by UAV on 11 dates, along with ground-truth data, in a field trial of 866 genetically diverse biomass sorghum accessions. We compared the performance of Convolution Neural Network (CNN) architectures that used image data from single dates (two spatial dimensions, 2D) versus multiple dates (two spatial dimensions + temporal dimension, 3D) to estimate lodging detection and severity. Lodging was detected with 3D-CNN analysis of time series imagery with 0.88 accuracy, 0.92 Precision, and 0.83 Recall. This outperformed the best 2D-CNN on a single date with 0.85 accuracy, 0.84 Precision, and 0.76 Recall. The variation in lodging severity was estimated by the best 3D-CNN analysis with 9.4% mean absolute error (MAE), 11.9% root mean square error (RMSE), and goodness-of-fit (R2) of 0.76. This was a significant improvement over the best 2D-CNN analysis with 11.84% MAE, 14.91% RMSE, and 0.63 R2. The success of the improved 3D-CNN analysis approach depended on the inclusion of “before and after” data, i.e., images collected on dates before and after the lodging event. The integration of geometric and spectral features with 3D-CNN architecture was also key to the improved assessment of lodging severity, which is an important and difficult-to-assess phenomenon in bioenergy feedstocks such as biomass sorghum. This demonstrates that spatio-temporal CNN architectures based on UAV time series imagery have significant potential to enhance plant phenotyping capabilities in crop breeding and Precision agriculture applications.

3D-convolution neural networks↗
NASA NTRS1978

Feasibility of wing shielding of the airplane interior from the shock noise generated by supersonic tip speed propellers

A high tip speed turboprop is being considered as a future energy conservative airplane. The high tip speed of the propeller, combined with the speed of the airplane, results in supersonic relative flow on the propeller tips. These supersonic blade sections could generate noise that is a cabin environment problem. The feasibility of using wing shielding to lessen the impact of this supersonic propeller noise was investigated. An analytical model is chosen which considers that shock waves are associated with the propeller tip flow and indicates how they would be prevented from impinging on the airplane fuselage. An example calculation is performed where a swept wing is used to shield the fuselage from significant portions of the propeller shock waves.

Dittmar, J. H.↗
NASA NTRS1982

The JT9D Jet Engine Diagnostics Program

The various engine deterioration phenomena that affect JT9D performance retention were studied, and approaches to improve performance retention of engines were identified. The program included surveys of historical data, monitoring of in service engines, ground and flight testing of instrumented engines, analysis, and analytical modeling. Performance deterioration is made up of both short and long term modes, both of which are flight cycle related phenomena. Short term deterioration occurs primarily during airplane acceptance testing prior to delivery to the airline. This effect is caused by flight load and power induced clearance closures and engine deflections with resulting rubbing of airfoils and seals. Long term deterioration is caused by erosion of airfoils and gas path seals during ground operation and take off and by cyclic induced thermal distortion of the high pressure turbine airfoils. Studies of possible remedial approaches have shown that performance retention within 1 to 2 percent of initial revenue service performance can be achieved with a proper program of hot section and cold section maintenance.

Olsson, W. J.↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

High-throughput screening to predict highly active dual-atom catalysts for electrocatalytic reduction of nitrate to ammonia

Ammonia is an essential chemical owing to its importance in fertilizer production and other industrial applications. Electrocatalytic nitrate reduction to ammonia (NO 3 RR) holds great promise for low-temperature ammonia production while simultaneously addressing nitrate-based environmental concerns. To provide the mechanistic understanding needed to design an effective electrocatalyst, we systematically investigated the catalytic performance of metal-based dual-atom catalysts (DACs) anchored on two-dimensional (2D) expanded phthalocyanine (Pc) for NO 3 RR. We found that NO 3 RR can efficiently produce ammonia on Cr 2 -Pc, V 2 -Pc, Ti 2 -Pc, and Mn 2 -Pc surfaces with low limiting potentials of – 0.02, – 0.25, – 0.34, and – 0.41 V RHE , respectively. Moreover, using the free energy difference of *NO 3 - and *H as a descriptor, we found that the hydrogen evolution reaction is significantly suppressed on the DAC surface due to an ensemble effect in which the two metal atoms cooperate to selectively form ammonia. We performed high-throughput screening to develop an efficient metal-based DAC for NO 3 - reduction, followed by a mechanistic study to elucidate the NO3RR pathway on the DAC. Finally, this work provides design information for advancing sustainable ammonia synthesis under ambient conditions.

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

The evolution of model Rh/Fe 3 O 4 (001) catalysts in hydrogen environments

Single metal atoms dispersed on oxides are a new emerging class of catalysts owing to their unique electronic and chemical properties. Here, in this study, we have prepared a series of model single-atom catalysts possessing well-characterized Rh sites that include Rh adatoms (Rh ad ), mixed surface layers with octahedrally-coordinated Rh (Rh oct ), as well as metallic Rh clusters and nanoparticles (Rh met ) on Fe 3 O 4 (001). Using X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM), we investigated the activity of such model systems towards H2 and their stability in reducing environments. Our results show that the atomically dispersed Rhad and Rhoct species do not activate H 2 , which would result in the formation of surface hydroxyls on Fe 3 O 4 (001). In contrast, the presence of Rh met in H 2 results in the formation of hydroxyls and subsequent etching of the Fe 3 O 4 (001) at higher temperatures (≥ 500 K) due to water formation via the Mars-van Krevelen mechanism. Additionally, such surface etching leads to the release of the Rh oct from the surface lattice and their sintering to Rh met . To bridge the material gap between the surface science models and high surface area catalysts, we perform parallel studies on powder Rh/Fe 3 O 4 catalysts. The XPS characterization shows remarkable similarities between these systems. Further, our surface science studies provide an atomistic picture of the behavior of high surface area catalysts in the H 2 atmosphere.

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

Adsorption and Catalytic Activity of Gold Nanoparticles in Mesoporous Silica: Effect of Pore Size and Dispersion Salinity

The assembled state of nanoparticles (NPs) within porous matrices plays a governing role in directing their biological, electronic, and catalytic properties. However, the effects of the spatial confinement and environmental factors, such as salinity, on the NP assemblies within the pores are poorly understood. In this study, we use adsorption isotherms, spectrophotometry, and small-angle neutron scattering to develop a better understanding of the effect of spatial confinement on the assembled state and catalytic performance of gold (Au) NPs in propylamine-functionalized SBA-15 and MCM-41 mesoporous silica materials (mSiO 2 ). We carry out a detailed investigation of the effect of pore diameter and ionic strength on the packing and spatial distribution of AuNPs within mSiO 2 to get a comprehensive insight into the structure, functioning, and activity of these NPs. We demonstrate the ability of the adsorbed AuNPs to withstand aggregation under high salinity conditions. We attribute the observed preservation of the adsorbed state of AuNPs to the strong electrostatic attraction between oppositely charged pore walls and AuNPs. The preservation of the structure allows the AuNPs to retain their catalytic activity for a model reaction in high salinity aqueous solution, here, the reduction of p-nitrophenol to p-aminophenol, which otherwise is significantly diminished due to bulk aggregation of the AuNPs. This fundamental study demonstrates the critical role of confinement and dispersion salinity on the adsorption and catalytic performance of NPs.

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

Integrated Reference Electrodes in Anion-Exchange-Membrane Electrolyzers: Impact of Stainless-Steel Gas-Diffusion Layers and Internal Mechanical Pressure

Alkaline-membrane electrolyzers operating in pure water might provide scalable low-cost H 2 production but currently lag in performance and durability compared to commercial technologies. Typically, membrane–electrode assemblies (MEAs) are optimized in electrolyzers by changing one parameter at a time and assessing the resulting system performance via two-electrode polarization and impedance measurements. These approaches are limited in their ability to assign performance changes and durability to specific electrodes or processes. We integrate a reference electrode with the MEA to separate anode and cathode responses in both polarization and impedance measurements. Here we illustrate the power of the approach by showing how the fiber diameter of stainless-steel gas-diffusion layers (GDLs) affects performance solely at the anode, while changing the thickness of the cathode GDL simultaneously affects the performance of the anode and cathode due to changes in internal pressure from mechanical compression. This finding was obscured in conventional two-electrode measurements. The work thus guides both high-performance alkaline-membrane water-electrolyzer development and illustrates a useful strategy to study structure–activity relationships in the MEA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗