Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “electrocatalyst”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Formate-Induced Dissolution and Reprecipitation of a Copper Electrocatalyst during Electrochemical CO 2 Reduction Reaction

Catalyst size, morphology, and crystal structure play crucial roles in determining the activity and selectivity of electrochemical CO 2 reduction reactions, which are known to change during the reaction process. A comprehensive understanding of how, when, and why these parameters evolve under operational conditions is essential for developing stable, efficient, and selective catalysts. In this study, we reveal that formate, one of the reaction products, contributes to the degradation of copper catalysts through a ligand-assisted dissolution mechanism. Utilizing in situ electrochemical atomic force microscopy and ex-situ scanning and transmission electron microscopies, we observed a significant reduction in the size of copper nanoparticles, which decreased from over 30 nm to less than 10 nm in diameter within 60 min of CO 2 RR. The temporal production of formate correlated with the particle size changes. Furthermore, analysis of the electrolyte using inductively coupled plasma optical emission spectroscopy confirmed the dissolution of copper nanoparticles. Control experiments involving various reaction products (H 2 , CO, and HCOO – ) demonstrated that formate significantly promotes copper dissolution, thereby highlighting its role in the ligand-assisted dissolution mechanism of copper electrocatalysts. In conclusion, our findings provide critical insights into copper catalyst behavior during electrochemical CO 2 reduction, facilitating the design of more resilient and effective electrocatalysts.

Catalysts↗
DOE OSTI2026

Insights into Native Single-Atom Electrocatalyst Site Structures

Single-atom electrocatalysts consisting of metal atoms embedded in a carbon matrix are promising next-generation catalysts for green hydrogen production and utilization, CO2 reduction, low-temperature CO oxidation, ammonia production, plastic decomposition, and electrochemical energy storage. The origins of activity and stability for the single-atom sites are still debatable, however, because of constrained insights into their local structure resulting from idealized models and experiments derived from a large number of individual sites. Insights into structural variations around single atomic sites are therefore critical for the continued development of these next-generation catalysts. While electron microscopy commonly provides atomic-scale information about these materials, the beam sensitivity of individual sites makes structural determination by conventional low-voltage (60 keV) techniques challenging. Here, we introduce ultralow-voltage electron ptychography, performed at 30 keV, that enables determination of the lattice structure around individual metal sites in a well-defined single-atom electrocatalyst system while essentially eliminating knock-on structural modifications. Pairing these atomic-scale, site-specific measurements with computational methods will broaden our understanding of the activity and stability of these materials, which will accelerate the development of the next generation of catalysts.

Zachman, Michael [ORNL] (ORCID:0000000319101357)↗
DOE OSTI2025

Single-Phase Spinel NiCo 2 O 4 as Highly Active and Stable Electrocatalysts for Urea Oxidation Reaction in Urea Electrolysis

Exploring and designing a stable and active catalyst for the urea electro-oxidation reaction (UOR, CO(NH 2 ) 2 + 6OH – → CO 2 + N 2 + 5H 2 O + 6e – ) is crucial for the long-term sustainability of ecological systems and clean energy production. We found that spinel NiCo 2 O 4 is a stable and active electrocatalyst for UOR at a relatively low anodic potential without triggering the competing oxygen evolution reaction (OER). A urea electrolysis cell (CO(NH 2 )2 + H 2 O → CO 2 + N 2 + 2H 2 ) utilizing a spinel NiCo 2 O 4 anode and a commercial Pt cathode was further characterized through galvanostatic polarization tests, demonstrating excellent structural stability at various current densities. Post-mortem analysis of long-term urea electrolysis measurements suggested that NiCo 2 O 4 electrocatalysts maintained a stable spinel structure. However, redistribution of Ni 3+ to Ni 2+ valence on the catalyst surface was observed, in contrast to the intact Co valence, indicating that (i) Ni sites are active toward urea adsorption and sequential electro-oxidation; (ii) while urea oxidation proceeds primarily through the direct electro-oxidation mechanism, chemical reactions between the Ni 3+ site and urea occur during long-term electrochemical UOR operation. Density functional theory (DFT) simulations were used to calculate the adsorption energies of urea molecules on NiO, Co 3 O 4 , and NiCo 2 O 4 , revealing the importance of regulating the configuration of adsorbed urea molecules on the NiCo 2 O 4 surface.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Leveraging data mining, active learning, and domain adaptation for efficient discovery of advanced oxygen evolution electrocatalysts

Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study presents a multistage machine learning (ML) approach to streamline the discovery and optimization of complex multimetallic catalysts. Our method integrates data mining, active learning, and domain adaptation throughout the materials discovery process. Unlike traditional trial-and-error methods, this approach systematically narrows the exploration space using domain knowledge with minimized reliance on subjective intuition. Then, the active learning module efficiently refines element composition and synthesis conditions through iterative experimental feedback. The process culminated in the discovery of a promising Ru-Mn-Ca-Pr oxide catalyst. Our workflow also enhances theoretical simulations with domain adaptation strategy, providing deeper mechanistic insights aligned with experimental findings. By leveraging diverse data sources and multiple ML strategies, we demonstrate an efficient pathway for electrocatalyst discovery and optimization. This comprehensive, data-driven approach represents a paradigm shift and potentially benchmark in electrocatalysts research.

Science & Technology - Other Topics↗
DOE OSTI2024

How is Rational Design of Electrocatalysts Crucial for Maximizing CO2 Electroreduction Performance?

The invited talk "How is Rational Design of Electrocatalysts Crucial for Maximizing CO2 Electroreduction Performance?” was presented in the symposium "Electrocatalysis for Sustainable Energy and Biomass Conversion: Fundamentals, Applications, and Perspectives”, Division of Catalysis Science and Technology, 2024 ACS Fall Meeting. The presentation briefly introduces NETL facilities and our Electrochemical Carbon Conversion portfolio to audiences. The talk primarily discusses how the geometry and surface composition of copper- and tin-based electrocatalysts would maximize the CO2 conversion to sustainable, carbon-neutral gas and liquid products in different device configurations. Ex situ and in situ characterization results are additionally discussed to correlate the structural, physico-chemical, and electronic properties with CO2 reduction activity and selectivity.

Nguyen Phan, Thuy Duong↗
DOE OSTI2024

Sulfur-Doped Carbon Support Boosts CO2RR Activity of Ag Electrocatalysts

For presentation at the 70th AVS International Symposium and Exhibition. In this work, we show that the activity of Ag electrocatalysts for electrochemical CO2 to CO conversion is improved when supported on sulfur-doped (S-doped) carbon materials. S-doped carbon support was created by treating the heavily sputtered, highly oriented pyrolytic graphite (HOPG) in H2S at elevated temperatures, as confirmed by the S 2p X-ray photoelectron spectroscopy (XPS) peak. Scanning tunneling microscopy (STM) images indicated that Ag nanoparticles supported on S-doped HOPG had similar size distributions as those supported on sulfur-free (S-free) HOPG. While both catalysts reached > 90% CO Faradaic efficiency (FECO) at E = -1.3 V vs. the reversible hydrogen electrode (RHE) in the CO2 reduction reaction (CO2RR), Ag catalysts supported on S-doped HOPG demonstrated 70% higher CO turnover frequency (TOFCO = 3.4 CO/atomAg/s) than those supported on S-free HOPG (TOFCO = 2.0 CO/atomAg/s). Preliminary calculations based on density functional theory (DFT) indicated a more favorable energetic pathway of CO2-to-CO at the C-S-Ag interface, tentatively consistent with experiments. These results hint at a new approach to design active and selective electrocatalysts for CO2 conversion.

Deng, Xingyi↗
DOE OSTI2025

Electrocatalyst Engineering and Device Benchmarking for Low Temperature CO2 Electrolysis

This oral presentation is for an invited talk in Division of Energy and Fuels, Symposium: "CO2 Conversion and Utilization-II: Electrochemical CO2 Conversion to Fuels and Valuable Chemicals" at ACS Spring 2025 (March 23-27, 2025) in San Diego, CA. The presentation will primarily discuss the crucial role of electrocatalyst design in the CO2 conversion to sustainable, carbon-neutral gas and liquid products. Some preliminary benchmarking studies of off-the-shelf electrocatalysts will be also shown in different device configurations to achieve good selectivity at industrially relevant current densities.

CO2 electrochemical reduction↗
DOE OSTI2025

Data Science-Driven Discovery of Multimetallic Oxygen-cycle Electrocatalysts for Enhanced Energy Conversion

The overarching objective of this effort has been to combine state-of-the-art data science techniques, first principles analyses, and molecular-level characterization of electrocatalyst structure and reactivity to identify both in-situ mechanisms for degradation and transformation of electrocatalysts with highly complex catalytic structures and the impact of these transformations on catalytic activity. The primary catalysts of interest have been multielemental alloys, including high entropy alloys (HEA’s), which are characterized by a high degree of disorder and up to 20 different elements within a single nanoparticle. We have applied these strategies primarily to energy-critical oxygen cycle electrocatalytic reactions, including oxygen reduction (ORR), but we have also considered extensions to non-electrochemical chemistries such as ammonia synthesis and decomposition. We have made strong progress in the development of computational methods on both the level of machine learning methods development as well as first principles-based treatments of HEA’s, and we have leveraged these insights to propose promising HEA catalysts for the ORR. On the experimental side, we developed new HEA synthesis and characterization protocols relevant to these reactions and developed a database combining our experimental results with corresponding computational tools.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimization of Ag Electrocatalyst Performance for CO2 to CO Conversion: Pairing Atomic Simulations with Experiments

Density-functional theory- based calculations that complement our series of experimental efforts on optimizing Ag electrocatalyst performance for CO2 to CO conversion were presented. Three key findings are drawn out from the combined UHV surface science, STM and electrochemical measurements: (1) Using a series of Ag nanoparticles with 2-6 nm average diameters, CO2 reduction reaction (CO2RR) activity increases, with particle between 2 nm and ∼4 nm demonstrating the highest combination of activity and selectivity; (2) Electronic metal−support interactions (EMSIs) between Ag and C dramatically improve CO2RR performance as evidenced by a scaling relationship between particle size and the relative Ag−C EMSIs strength, which improves the CO2-to-CO Faradaic efficiency of sub-2 nm Ag particles from 2 to ∼100% and increases the CO turnover frequency ∼15-fold compared with similarly sized bare Ag particles; (3) The performance Ag electrocatalysts is improved when supported on S-doped C materials. Computational modeling of 1−10 nm Ag particles predicts a nearly identical size-dependent trend with maximum CO2RR activity predicted for 3.7nm particles. The calculations support the promotional effect of C materials, showing a large charge transfer of 1.02 e from Ag clusters to defective C and a 0.41 eV less endergonic step of forming COOH intermediate on Ag/defective-C compared to the Ag/C system. Calculations indicate a more favorable energetic pathway of CO2-to-CO at the C-S-Ag interface, consistent with experiments.

CO2 utilization↗
DOE OSTI2026

Towards Spatial Control of Reaction Selectivity on Photocatalysts using Area Selective Atomic Layer Deposition on Model Dual Site Electrocatalyst Platform

Photocatalytic water splitting is a promising route to low-cost H2; however, this approach is currently limited by solar-to-hydrogen (STH) conversion efficiencies in the sub-10% range. Z-scheme water splitting, in which H2 and O2 evolving particles are operated in separate compartments and electronically coupled by a soluble redox mediator, offers improvements in STH efficiency but introduces high rates of undesired side and back reactions. Nanoscopic oxide coatings (e.g., CrOx, and SiOx) have previously been used to selectively block undesired reactants from reaching active sites; however, a coating encapsulating the entire photocatalyst particle limits activity as the particle can no longer facilitate both half reactions. In contrast to photodeposition, which may produce non-uniform overlayers due to the difficulty of controlling local electrochemical reactivity on the surface, area-selective atomic layer deposition (AS-ALD) can be used to deposit conformal ultrathin oxide coatings while preserving access to non-growth areas of a substrate surface. To develop this technique for Z-scheme photocatalysts, we performed AS-ALD of TiO2 on a dual site planar electrocatalyst based on interdigitated arrays of Pt and Au. Self-assembled monolayers of 1-octadecanethiol (ODT) were used to block growth on the Au array, resulting in a patterned surface in which only the Pt sites were encapsulated with TiO2. These electrocatalysts demonstrated localized reaction selectivity for hydrogen evolution reaction (HER) over the TiO2/Pt sites, while the uncoated Au sites retained activity towards Fe(II)/Fe(III) redox (FeRR). Under independent potential control, these microelectrodes showed that selectively deposited TiO2 coatings can suppress the rate of back reactions on neighboring active sites by an order of magnitude compared to uncoated control samples.

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

Anolyte Buffering and CO Coverage Effects in the Electrochemical Reduction of CO at Cu Electrocatalysts

Electrolytic CO reduction was investigated at copper electrocatalysts in zero-gap membrane electrode assemblies as a function of buffering agents and cofeeding with CO 2 or Ar. Results show an acetate Faradaic efficiency (FE) of 90% at 300 mA cm −2 using pure CO feeds and phosphate-buffered anolyte near pH 8. When using CO feeds with more alkaline anolytes, the hydrogen evolution reaction becomes the dominant reduction reaction, independent of the buffer. Product distributions of cofeeding experiments with CO and CO 2 show that increasing CO 2 cofeeding results in increased selectivity toward ethylene (42% FE) in near-neutral KHCO 3 anolytes or ethanol (40% FE) in alkaline KOH anolytes. Evaluation of several commercial anion exchange membranes shows similar selectivity trends, suggesting product selectivity is dominated by the local pH and surface coverage of CO. Based on these results, we propose pH buffering and CO coverage behaviors that facilitate high selectivities to acetate.

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

Tantalum oxide stabilized molybdenum-doped ruthenium oxide electrocatalysts for PEM water electrolysis

Proton exchange membrane (PEM) water electrolysis offers key advantages, including high current density, high efficiency, and compact system architecture for hydrogen production. However, its widespread implementation is limited by the scarcity and high cost of Ir-based anodic catalysts. Herein, we report an Ir-free electrocatalyst for the acidic oxygen evolution reaction (OER): tantalum oxide (TaO x )–coated molybdenum-doped RuO 2 (TaO x -MoRuO 2 ). The catalyst exhibits a low overpotential of 180 mV at 10 mA cm -2 and excellent durability, with a degradation rate of 0.034 mV h -1 over a 150-hour test at 50 mA cm -2 —surpassing other Ru-based catalysts evaluated under similar conditions. A PEM electrolyzer employing TaO x -MoRuO 2 as the anode maintained stable operation for 100 hours at 500 mA cm -2 . In conclusion, the TaO x coating layer suppresses Ru and Mo dissolution, thus enhancing their stability likely via interfacial electronic reconfiguration of Ru and Mo mediated by bridging oxygen atoms.

Durability↗
DOE OSTI2024

Machine learning-guided design, synthesis, and characterization of atomically dispersed electrocatalysts

The recent integration of machine learning into materials design has revolutionized the understanding of structure–property relationships and optimization of material properties beyond the trial-and-error paradigm. On one hand, machine learning has significantly accelerated the development of atomically dispersed metal-nitrogen-carbon (M-N-C) electrocatalysts, which traditionally heavily relied on heuristic approaches. On the other hand, the primary challenge of leveraging machine learning to expedite M-N-C materials discovery lies in the cost associated with data collection. Here, we review recent machine learning integration strategies for M-N-C catalyst development, including discussions on the typical algorithms such as symbolic regression and convolutional neural networks employed for the theoretical design, synthesis optimization via active learning, and advanced microscopy characterization. Subsequently, we provide our perspective on potential near-future directions for furthering machine learning-assisted development of new M-N-C catalysts and elucidating the complex physicochemical mechanisms governing the selectivity, activity, and durability in this class of materials.

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

Stable Metal–Organic Electrocatalysts for Anion-Exchange Membrane Water Electrolyzers by Defect Engineering

Developing efficient and durable catalysts for the alkaline oxygen evolution reaction (OER) is vital to achieving practical anion-exchange membrane water electrolyzers (AEMWE) for green hydrogen production. In this work, we break the activity-stability trade-off of electrocatalysis by defect engineering of Ni-based metal-organic electrocatalysts (Ni-benzene dicarboxylate; Ni-BDC) through coordinating ferrocenecarboxylates (Fc) to the metal sites. Experimental results collectively reveal that the defect MOF (Ni-BDC:Fc_5:1) exhibits a high OER turnover frequency of 0.75 O 2 s -1 at 300 mV overpotential. Operando Raman spectroscopy and isotope-labelling electrochemical mass spectrometry measurements indicate the structure of Ni-BDC:Fc_5:1 is also more stable in service than that of pure Ni-BDC. The high activity and stability could be attributed to the moderate defects (i.e., unsaturated Ni sites) in the structure that not only increase the intrinsic activity and stability of the local active environment by inhibiting lattice oxygen exchange, but also electrochemically activates the bulk of the catalysts by creating a porous network that facilitates internal H 2 O/OH - conduction with enhanced electronic conduction. Accordingly, an AEMWE employing Ni-BDC:Fc_5:1 as the OER catalyst delivers an industrial-level current density of 1 A cm -2 at 1.73 V cell and can be steadily operated for more than 120 hours.

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

Compositional Phase Control in High-Entropy Alloy Electrocatalysts

High-entropy alloys (HEAs) provide uniquely tunable structural and electronic properties that enable robust electrocatalysis. While compositional manipulation of HEAs is well-known, systematically controlling the crystalline phase and morphology remains a challenge that could provide new avenues for controlling reactive sites and physical properties. Here, we show the preferential stabilization of mixed fcc/bcc to fcc phases by controlling the Au content in quinary AuPdFeCoNi HEA nanoparticles. This systematic structural and compositional control, when investigated with an ensemble of electronic, X-ray synchrotron, and surface techniques, allows us to identify the critical short- (few-Å) and medium- (6–10 Å) range structural motifs that deliver exceptional hydrogen evolution reaction (HER) catalysis. Specifically, these HEAs exhibit both outstanding durability (240 h) and high mass activity (50 A/mg PGM ) normalized to noble metal content, outperforming commercial Pt/C (3.18 A/mg PGM ). This structural control over HEA morphology, and its direct association with changes in specific metallic oxidation states and pair–pair atomic structural features, provides new means and strategies for finely designing robust and sustainable electrocatalysts with a majority nonprecious metal composition.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Three–Dimensional Nanoscale View of Electrocatalyst Degradation in Hydrogen Fuel Cells

The loss of platinum (Pt) electrochemically active surface area (ECSA) is a critical degradation mode that often becomes a limiting factor for heavy-duty proton exchange membrane fuel cell vehicles. High surface area carbon supports have been shown to improve Pt dispersion and limit detrimental ionomer-electrocatalyst interactions due to their large interior pore volume. Here, in this work, using automated scanning transmission electron tomography, the degradation of nanoparticles located on the interior versus exterior surfaces of the carbon support is compared following a catalyst-specific accelerated stress test (AST) of 90,000 voltage cycles between 0.6 V to 0.95 V. The results reveal a notable increase in median particle size for both interior and exterior Pt catalyst particles, with a slightly higher increase in particle size distribution and loss of specific surface area for the particles located on the exterior carbon surface. The fraction of Pt nanoparticles that reside within the interior of the carbon support also increased following the AST test, accompanied by evidence of an increase in average carbon mesopore size. Here, the results shed light on the degradation mechanisms affecting electrochemical properties and the enhanced particle accessibility at lower relative humidity.

08 HYDROGEN↗
DOE OSTI2025

Machine Learning‐Guided Discovery of High‐Entropy Perovskite Oxide Electrocatalysts via Oxygen Vacancy Engineering

Abstract High‐entropy perovskite oxides (HEPOs) have recently emerged as multifunctional catalysts. However, the HEPOs’ structural and compositional complexity hinders the easy and accurate extrapolation of activity indicators, which are essential for establishing structure‐property correlations. Here, OxiGraphX, is introduced as a novel graph neural network (GNN) model designed to capture the complex relationships among structure, composition, and atomic chemical environments for accurate prediction of oxygen vacancy formation energies (OVFEs) in HEPOs. By integrating machine learning (ML), density functional theory (DFT), and experimental validation, this work demonstrates an efficient framework for rapidly and accurately screening HEPO electrocatalysts for oxygen evolution reaction (OER). The OxiGraphX predicts OVFEs with a precision exceeding existing data, enabling the identification of compositions of higher oxygen vacancy content (OVC) and, thus, higher catalytic activity. Furthermore, the model explores latent spaces that translate effectively into experimental domains, bridging computational predictions with real‐world applications. This approach accelerates the discovery of high‐performance HEPO catalysts while providing deeper insights into their catalytic mechanisms.

Chemistry↗