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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
DOE OSTI2021

Demystifying the Stern layer at a metal–electrolyte interface: Local dielectric constant, specific ion adsorption, and partial charge transfer

Electric double layer (EDL) represents one of the most basic concepts in electrochemistry and is pertinent to diverse engineering applications ranging from electrocatalysis to energy storage. Whereas phenomenological and coarse-grained models have been long established to describe ionic distributions in the diffuse layer, a faithful prediction of the physicochemical properties of the electrode–electrolyte interface from a molecular perspective remains a daunting challenge. In this work, we investigate the charging behavior of an Ag (111) electrode in NaF aqueous solutions leveraging experimental results and theoretical calculations based on the classical density functional theory for ion distributions in the diffuse layer and on the joint density functional theory (JDFT) for the electronic structure. When the Ag electrode is applied with a negative voltage, the surface charge density can be reasonably described by assuming a neutral Stern layer with the dielectric constant dependent on the local electric field as predicted by the Kirkwood equation. However, the specific adsorption of F− ions must be considered when the electrode is positively charged and the fluoride adsorption can be attributed to both physical and chemical interactions. Qualitatively, F− binding and partial charge transfer are supported by JDFT calculations, which predict an increased binding energy as the voltage increases. Our findings shed insight on the molecular characteristics of the Stern layer and the charge behavior of adsorbed species not specified by conventional EDL models.

Wang, Xuepeng (ORCID:0000000285704546)↗
DOE OSTI2021

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

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

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

Screening of bimetallic electrocatalysts for water purification with machine learning

Electrocatalysis provides a potential solution to NO 3 - pollution in wastewater by converting it to innocuous N 2 gas. However, materials with excellent catalytic activity are typically limited to expensive precious metals, hindering their commercial viability. Here, in response to this challenge, we have conducted the most extensive computational search to date for electrocatalysts that can facilitate NO 3 - reduction reaction, starting with 59 390 candidate bimetallic alloys from the Materials Project and Automatic-Flow databases. Using a joint machine learning- and computation-based screening strategy, we evaluated our candidates based on corrosion resistance, catalytic activity, N 2 selectivity, cost, and the ability to synthesize. We found that only 20 materials will satisfy all criteria in our screening strategy, all of which contain varying amounts of Cu. Our proposed list of candidates is consistent with previous materials investigated in the literature, with the exception of Cu–Co and Cu–Ag based compounds that merit further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computational quantum chemistry of metal–organic frameworks

Metal–organic frameworks (MOFs) have premium exceptional properties for a variety of functions, such as gas separation and storage and catalysis. The large variety of possible inorganometallic nodes and organic linkers provide an almost unlimited number of combinations for assembling MOFs, which makes the experimental characterization and examination of all potentially useful combinations practically impossible. Furthermore, experimental studies of MOFs typically fall short in uncovering crucial details regarding their mechanisms of action or the molecular details responsible for their functional properties, such as the nature of adsorbate binding or the structures of transition states. Computational modeling has, therefore, become an efficient and important tool for strategizing the functionalization of MOFs and explicating the mechanisms of their functions. Furthermore, we review the computational methodologies used for computational studies of MOFs, especially Kohn–Sham density functional theory and combined quantum mechanical and molecular mechanical methods for calculating their structural, electronic, and magnetic properties, as well as for understanding the mechanisms of MOFs' applications to magetic devices, thermal conduction, gas adsorption, separation, storage, and sensing, thermal catalysis, photocatalysis, and electrocatalysis.

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

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗
DOE OSTI2025

Facet-dependent structure and dissociation of water at pristine IrO 2 /water interfaces

Understanding the microscopic structure of water at metal oxide interfaces is crucial for advancing electrocatalysis. IrO 2 , specifically, has shown exceptional activity for electrochemical water oxidation, but we currently lack a fundamental understanding of how the surface structure of IrO 2 impacts water reactivity. In this work, we developed a machine learning potential trained to first-principles accuracy for modeling IrO 2 /water interfaces across different facets: (110), (100), (101), and (001). Using extensive machine learning molecular dynamics simulations, we investigated the spontaneous dissociation of water molecules at these interfaces. Our results reveal a distinct dissociation probability trend: (110) > (100) ≈ (101) > (001), which we attribute primarily to the reaction thermodynamics of surface water dissociation. A strong correlation is observed between the surface Ir–O bond distances and the dissociation probabilities, highlighting the role of surface geometry in modulating reactivity. As a consequence, the interfacial solvation structures and hydrogen bonding environments are dynamically tuned by the varying water dissociation capabilities across facets. This work elucidates how water dissociation energetics depend on surface orientation and interfacial structure, offering atomistic insights into manipulating reaction chemistry at electrocatalytic interfaces.

organic↗
DOE OSTI2019

Renewable electricity storage using electrolysis

Electrolysis converts electrical energy into chemical energy by storing electrons in the form of stable chemical bonds. The chemical energy can be used as a fuel or converted back to electricity when needed. Water electrolysis to hydrogen and oxygen is a well-established technology, whereas fundamental advances in CO 2 electrolysis are still needed to enable short-term and seasonal energy storage in the form of liquid fuels. This paper discusses the electrolytic reactions that can potentially enable renewable energy storage, including water, CO 2 and N 2 electrolysis. Recent progress and major obstacles associated with electrocatalysis and mass transfer management at a system level are reviewed. We conclude that knowledge and strategies are transferable between these different electrochemical technologies, although there are also unique complications that arise from the specifics of the reactions involved.

25 ENERGY STORAGE↗
DOE OSTI2021

Tailoring electrocatalytic activity of in situ crafted perovskite oxide nanocrystals via size and dopant control

Significance The ability to scrutinize the correlation of dimension, composition, and dopant to electrocatalytic performance renders the development of highly active electrocatalysts. This work reports a general and robust strategy for crafting uniform perovskite oxide nanoparticles (i.e., BaTiO 3 and La- and Co-doped BaTiO 3 ) with controlled sizes and dopant compositions by employing amphiphilic star-like diblock copolymers as nanoreactors. Their size- and dopant-dependent oxygen reduction reaction (ORR) performances are unveiled. Particularly, La- and Co-doped BaTiO 3 nanoparticles exhibit markedly improved ORR activities over the pristine counterparts due to reduced free energy barrier of ORR and increased conductivity as substantiated by density functional theory. The nanoreactor strategy could be conveniently extended to yield various functional nanomaterials of interest with tailored sizes and compositions for electrocatalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A multifunctional copper single-atom electrocatalyst aerogel for smart sensing and producing ammonia from nitrate

Despite modern chemistry’s success in providing affordable fertilizers for feeding the population and supporting the ammonia industry, ineffective nitrogen management has led to pollution of water resources and air, contributing to climate change. Here, we report a multifunctional copper single-atom electrocatalyst-based aerogel (Cu SAA) that integrates the multiscale structure of coordinated single-atomic sites and 3D channel frameworks. The Cu SAA demonstrates an impressive faradaic efficiency of 87% for NH 3 synthesis, as well as remarkable sensing performance with detection limits of 0.15 ppm for NO 3 − and 1.19 ppm for NH 4 + . These multifunctional features enable precise control and conversion of nitrate to ammonia in the catalytic process, facilitating accurate regulation of the ammonium and nitrate ratios in fertilizers. We thus designed the Cu SAA into a smart and sustainable fertilizing system (SSFS), a prototype device for on-site automatic recycling of nutrients with precisely controlled nitrate/ammonium concentrations. The SSFS represents a forward step toward sustainable nutrient/waste recycling, thus permitting efficient nitrogen utilization of crops and mitigating pollutant emissions. This contribution exemplifies how electrocatalysis and nanotechnology can be potentially leveraged to enable sustainable agriculture.

Science & Technology - Other Topics↗
DOE OSTI2025

A versatile and practical synthesis of oxygen evolution catalysts

State-of-the-art OER (oxygen evolution reaction) catalyst syntheses require the use of expensive metals (i.e. Ir) with complex and time-consuming synthetic routes, difficulty in control, and impractical yields. Although some reported catalysts show improved performance (i.e. activity, stability, lowering Ir content with Ru), their synthesis is costly and not viable for scale-up. Here we demonstrate a practical, reliable, and scalable one-pot synthesis method for OER catalysts based on borohydride reduction to quickly yield >100 mg of Ir, Ru, and IrRu nanoparticles (1.6 ± 0.2 nm) with outstanding batch-to-batch consistency. Both mono- and bi-metallic compositions exhibit a metal-core/metal-oxide-shell nanoparticle structure. We further demonstrate the versatility of this method by incorporating earth-abundant yttrium, resulting in a catalyst with improved precious metal utilization for OER. This method serves as a robust platform for generating ultrasmall (<2 nm) multi-metal particles useful for electrocatalysis research.

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

Scanning electrochemical probe microscopy investigation of two-dimensional materials

Research interests in two-dimensional (2D) materials have seen exponential growth owing to their unique and fascinating properties. The highly exposed lattice planes coupled with tunable electronic states of 2D materials have created manifold opportunities in the design of new platforms for energy conversion and sensing applications. Still, challenges in understanding the electrochemical (EC) characteristics of these materials arise from the complexity of both intrinsic and extrinsic heterogeneities that can obscure structure–activity correlations. Scanning EC probe microscopic investigations offer unique benefits in disclosing local EC reactivities at the nanoscale level that are otherwise inaccessible with macroscale methods. This review summarizes recent progress in applying techniques of scanning EC microscopy (SECM) and scanning EC cell microscopy (SECCM) to obtain distinctive insights into the fundamentals of 2D electrodes. We showcase the capabilities of EC microscopies in addressing the roles of defects, thickness, environments, strain, phase, stacking, and many other aspects in the heterogeneous electron transfer, ion transport, electrocatalysis, and photoelectrochemistry of representative 2D materials and their derivatives. Perspectives for the advantages, challenges, and future opportunities of scanning EC probe microscopy investigation of 2D structures are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Reevaluation of XPS Pt 4f peak fitting: Ti 3s plasmon peak interference and Pt metallic peak asymmetry in Pt@TiO2 system

The structural, electronic, and electrochemical properties of noble metals supported on transition metal oxides, such as Pt nanoparticles (NPs) supported on TiO2 (Pt@TiO2), have been extensively studied for their relevance to energy technologies, including photocatalysis, electrocatalysis, and electrochemical energy conversion. As the need to lower the amount of Pt and other noble metals used in energy conversion systems becomes urgent, it is essential to accurately quantify the loading of these metals and electronic density redistribution between them and their supports. X-ray photoelectron spectroscopy (XPS) is widely used for the identification and quantification of chemical species. In particular, fitting of the Pt 4f spectra for Pt@TiO2 is frequently performed to determine the chemical environment and oxidation state of Pt, which strongly affect the physical behavior and catalytic performance of this system. Here, we show that neglecting contributions due to the Pt surroundings and the asymmetry of the Pt metal peak in the line shape fitting can lead to severe mischaracterization of the oxidation state of Pt. We quantify the effects of background contributions that stem from the TiO2 support and discuss how factoring in the strong asymmetry of Pt 4f doublets, which stems from the shake-up type processes, affects the interpretation of Pt 4f XPS line shape.

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

Quantifying Stern layer water alignment before and during the oxygen evolution reaction

While water’s oxygen is the electron source in the industrially important oxygen evolution reaction, the strong absorber problem clouds our view of how the Stern layer water molecules orient themselves in response to applied potentials. Here, we report nonlinear optical measurements on nickel electrodes held at pH 13 indicating a disorder-to-order transition in the Stern layer water molecules before the onset of Faradaic current. A full water monolayer (1.1 × 10 15 centimeter −2 ) aligns with oxygen atoms pointing toward the electrode at +0.8 volt and the associated work is 80 kilojoule per mole. Our experiments identify water flipping energetics as a target for understanding overpotentials, advance molecular electrochemistry, provide benchmarks for electrical double layer models, and serve as a diagnostic tool for understanding electrocatalysis.

Science & Technology - Other Topics↗
DOE OSTI2020

Direct Demonstration of Unified Brønsted-Evans-Polanyi Relationships for Proton-Coupled Electron Transfer Reactions on Transition Metal Surfaces

Brønsted-Evans-Polanyi (BEP) relationships, which relate elementary reaction barriers to reaction thermodynamics, have long been discussed in electrochemical science, but demonstration of their existence in heterogeneous electrocatalysis, across many different catalyst surfaces and voltages, is lacking. In this contribution, the BEP model is demonstrated to describe both multiple catalyst surfaces and variable voltages in electrochemical environments. For proton-coupled electron transfer (PCET) to surface nitrogen (N*) and nitric oxide (NO*), reaction energies and activation barriers are calculated using Density Functional Theory (DFT) on a parallel plate capacitor model at three different potentials and for nine different transition metal surfaces. Linear BEP relations that describe all potentials and catalyst surfaces are obtained for these elementary reactions, and the slopes of the correlations are shown to be directly related to the fractional coordinate of the transition states (FCTS) of the reactions. The results, which are explained in terms of Marcus Theory, prove a direct equivalence between unified BEP coefficients, describing both variable catalyst surfaces and voltages, and electrochemical symmetry factors and provide a straightforward means of estimating this quantify for PCET reactions on transition metal surfaces. The resulting relationships, in turn, could lead to predictions of electrocatalytic reactivity trends of enhanced accuracy and efficiency.

Electrochemistry↗
DOE OSTI2023

Predictive Modeling of Electrodeposition in a Single Pore Flow-Through Electrode: From Electronucleation to Coating Thickness Uniformity

The emergence of advanced manufacturing methods capable of producing porous three-dimensional structures has expanded the design space for next-generation functional components. The ability to fabricate ordered 3D foams for use in electrocatalysis reactors has increased the need for controlled deposition of catalytic metals onto porous support materials, such as carbon. However, there is a lack of clear design guidelines for electrodeposition onto 3D substrates, due to the geometric complexity and multi-scale nature of the problem. Furthermore, electro-nucleation phenomena are often overlooked in macro-scale models of current distribution during deposition. Here, a graphite flow-through electrode (FTE) is used as a model system for copper deposition within a single pore. Potential distributions and electro-nucleation phenomena are coupled in a continuum level model by incorporating nucleation size and density as a function of overpotential, determined experimentally using in situ atomic force microscopy (AFM). The model predictions are validated by measuring the coating uniformity in the pore using micro-computed X-ray tomography (μCT). A scaling analysis comprising dimensionless parameters such as the Wagner number is presented. The simplified scaling relationship framework can guide the electrodeposition process and electrode design to optimize plating of porous substrates under fluid flow conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Engineered Catalyst Support with Improved Durability at Higher Weight Percentage of Platinum

Proton Exchange Membrane (PEM) fuel cells are a suitable electrochemical power source for heavy duty vehicle (HDV) applications due to their high efficiency and durability. The cathode of the fuel cell uses a higher geometric loading of platinum (∼0.2 to 0.4 mg Pt /cm 2 ) for the electrocatalysis of the kinetically sluggish Oxygen Reduction Reaction (ORR) which requires higher weight percent loading of the metal (∼50%) on the carbon support to decrease the catalyst layer thickness and hence, the reactant transport losses. The conventionally used supports for platinum catalyst, such as the KetjenBlack TM type high surface area carbon (HSC) features limited mesopore area for the dispersion of Pt nanoparticles leading to increased aggregation and poor durability. Here, we show a new class of carbon materials known as the Engineered Catalyst Support (ECS) developed by Pajarito Powder with higher mesopore fraction for the dispersion of higher weight percentage of Pt nanoparticles. ECS materials can disperse up to 50% Pt by weight of the catalyst thereby enabling lower catalyst layer thickness with higher performance retained after durability test. A comprehensive set of physico-chemical and electrochemical studies in membrane electrode assembly (MEA) are reported to understand the performance and durability of Pt/ECS catalysts.

08 HYDROGEN↗
DOE OSTI2023

Anodic Dissolution Rates Accelerate with Decreasing MoS 2 Nanoflake Thickness

Electrochemical gating of 2D transition metal dichalcogenide (TMD) electrodes is an emerging frontier in the field of semiconductor electrochemistry. In this approach, an applied bias modifies the charge carrier concentration of the 2D TMD, causing band edge shifts and drastic changes in charge transfer rates. However, leveraging this effect for (photo)electrocatalysis is practically limited by the stability of the TMD material under gating conditions. Gerischer showed anodic dissolution of bulk TMD electrodes can occur in the dark and hypothesized that the reaction proceeds via an electron tunneling mechanism from surface states to the TMD conduction band [H. Gerischer, D. Ross, and M. Lubke, Z. Physickalische Chem., 139, 1 (1984)]. Here we investigate this possibility in single MoS 2 nanoflakes using in situ optical microscopy and explore whether Gerischer’s electron tunneling mechanism can explain anodic dissolution rates of thin 2D semiconductors. Here, spatially resolved measurements show anodic dissolution initiates at perimeter edge sites and accelerates exponentially with decreasing layer thickness, consistent with Gerischer’s tunneling mechanism. Interestingly, single layer MoS 2 is impervious to anodic dissolution at applied potentials >200 mV more positive than those required to drive dissolution in bulk and multilayer-thick nanoflakes.

2D semiconductor↗
DOE OSTI2024

Review—In Situ X-ray and Infrared Spectroscopic Studies of Electrochemical Systems

Despite of intense research and a wealth of data, the phenomena occurring during electrocatalysis are still a major obstacle in many chemical processes. Molecular analysis of the electrode/electrolyte interface is needed to correctly describe the reaction through identifying the species involved, their interaction with the environment and kinetics in situ, i.e. while the reaction is taking place. That can be done by coupling the electrochemical system with complementary non-electrochemical techniques. Particularly revealing are in situ X-ray spectroscopic techniques to analyze the electrode itself, providing the information on the changes in the catalyst during the reaction. The synergy of the traditional electrochemical techniques with the complementary spectroscopic methodologies offer understanding of the electrode/electrolyte interface above and beyond traditional experimental mainframe. Here we demonstrate how in situ X-ray absorption spectroscopy (XAS), in situ infrared reflection/absorption spectroscopy (IRRAS), and traditional voltammetric studies can increase our understanding of electrochemical processes during oxidation of ethanol. The results show the pronounced role of electrode surface in determining reaction kineticks and revealed the selectivity of the catalyst to complete oxidation pathway. They further provide understanding of the parameters that enhance its oxidation for future designing catalysts for alcohol oxidation fuel cells.

30 DIRECT ENERGY CONVERSION↗