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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Thermodynamic and Kinetic Activity Descriptors for the Catalytic Hydrogenation of Ketones

Activity descriptors are a powerful tool for the design of catalysts than can efficiently utilize H 2 with minimal energy losses. In this study, we develop the use of hydricity and H - self-exchange rates as thermodynamic and kinetic descriptors for the hydrogenation of ketones by molecular catalysts. Two complexes with known hydricity, HRh(dmpe) 2 and HCo(dmpe) 2 , were investigated for the catalytic hydrogenation of ketones under mild conditions (1.5 atm, 25 °C). The rhodium catalyst proved to be an efficient catalyst for a wide range of ketones, whereas the cobalt catalyst could only hydrogenate electron-deficient ketones. Using a combination of experiment and electronic structure theory, thermodynamic hydricity values were established for 46 alkoxide/ketone pairs in both MeCN and THF solvent. Through comparison of the hydricities of the catalysts and substrates, it was determined that catalysis was only observed for catalyst/ketone pairs with an exergonic H - transfer step. Mechanistic studies revealed that H - transfer was rate-limiting step for catalysis, allowing for the experimental and computation construction of linear free-energy relationships (LFERs) for H - transfer. Further analysis revealed the LFERs could be reproduced using Marcus theory, in which the H - self-exchange rates for the HRh/Rh + and ketone/alkoxide pairs were used to predict the experimentally measured catalytic barriers within 2 kcal mol -1 . Finally, these studies significantly expand the scope of catalytic reactions that can be analyzed with a thermodynamic hydricity descriptor and firmly establish Marcus theory as a valid approach to develop kinetic descriptors for designing catalysts for H - transfer reactions.

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

Intermetallic alloy structure–activity descriptors derived from inelastic X-ray scattering

Synchrotron spectroscopy and Density Functional Theory (DFT) are combined to develop a new descriptor for the stability of adsorbed chemical intermediates on metal alloy surfaces. This descriptor probes the separation of occupied and unoccupied d electron density in platinum and is related to shifts in Resonant Inelastic X-ray Scattering (RIXS) signals. Simulated and experimental spectroscopy are directly compared to show that the promoter metal identity controls the orbital shifts in platinum electronic structure. The associated RIXS features are correlated with the differences in the band centers of the occupied and unoccupied d bands, providing chemical intuition for the alloy ligand effect and providing a connection to traditional descriptions of chemisorption. The ready accessibility of this descriptor to both DFT calculations and experimental spectroscopy, and its connection to chemisorption, allow for deeper connections between theory and characterization in the discovery of new catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2020

w19_OMEC Scientific Highlight [Slides]

Scientific Achievement: Revealed the effect of graphite substrate on H binding / hydrogen evolution reaction (HER) activity of organic molecular electrocatalysts (OMECs); and demonstrated the effect of molecular modification on calculated HER activity descriptor. Significance and Impact: Understanding of HER processes is important for discovering low-cost OMECs for hydrogen production and energy application; design of OMEC structures remains challenging due to the unexplored redox properties of organic molecules; and density functional theory (DFT) has been proposed to provide needed insights into HER activity for improved materials design. Research Details: DFT calculations on the binding energy of HER intermediates are used for predicting reduction potentials and and calculated H adsorption energy as activity descriptor; and LANL Institutional Computing (IC) resources are essential for successful project execution given the size of structures involved in modeling molecule-support interaction.

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

Tuning Active Site Flexibility by Defect Engineering of Graphene Ribbon Edge‐hosted Fe−N 3 Sites

Abstract Nitrogen‐doped, carbon‐supported transition metal catalysts are excellent for several reactions. Structural engineering of M−N x sites to boost catalytic activity is rarely studied. Here, we demonstrate that the structural flexibility of Fe−N 3 site is vital for tuning the electronic structure of Fe atoms and regulating the catalytic transfer hydrogenation (CTH) activity. By introducing carbon defects, we construct Fe−N 3 sites with varying Fe−N bond lengths distinguishable by X‐ray absorption spectroscopy. We investigate the CTH activity by density‐functional theory and microkinetic calculations and reveal that the vertical displacement of the Fe atom out of the plane of the support, induced by the Fe−N 3 distortion, raises the Fe orbital and strengthens binding. We propose that the activity is controlled by the relaxation of the reconstructed site, which is further affected by Fe−N bond length, an excellent activity descriptor. We elucidate the origin of the CTH activity and principles for high‐performing Fe−N−C catalysts by defect engineering.

Yang, Piaoping↗
DOE OSTI2023

Tuning Active Site Flexibility by Defect Engineering of Graphene Ribbon Edge–hosted Fe–N3 Sites

Nitrogen-doped, carbon-supported transition metal catalysts are excellent for several reactions. Structural engineering of metal-Nx sites to boost catalytic activity is rarely studied. Here, we demonstrate that the structural flexibility of Fe-N3 site is vital for tuning the electronic structure of Fe atoms and regulating the catalytic transfer hydrogenation (CTH) activity. By introducing carbon defects, we construct Fe-N3 sites with varying Fe-N bond lengths distinguishable by X-ray absorption spectroscopy. We investigate the CTH activity by density functional theory and microkinetic calculations and reveal that the vertical displacement of the Fe atom out of the plane of the support, induced by the Fe-N3 distortion, raises the Fe [[EQUATION]]orbital and strengthens binding. We propose that the activity is controlled by the relaxation of the reconstructed site, which is further affected by Fe-N bond length, an excellent activity descriptor. Furthermore, we elucidate the origin of the CTH activity and principles for high-performing Fe-N-C catalysts by defect engineering.

09 BIOMASS FUELS↗
DOE OSTI2022

Electrocatalysis in Alkaline Media and Alkaline Membrane-Based Energy Technologies

Hydrogen energy-based electrochemical energy conversion technologies offer the promise of enabling a transition of the global energy landscape from fossil fuels to renewable energy. Here, we present a comprehensive review of the fundamentals of electrocatalysis in alkaline media and applications in alkaline-based energy technologies, particularly alkaline fuel cells and water electrolyzers. Anion exchange (alkaline) membrane fuel cells (AEMFCs) enable the use of nonprecious electrocatalysts for the sluggish oxygen reduction reaction (ORR), relative to proton exchange membrane fuel cells (PEMFCs), which require Pt-based electrocatalysts. However, the hydrogen oxidation reaction (HOR) kinetics is significantly slower in alkaline media than in acidic media. Understanding these phenomena requires applying theoretical and experimental methods to unravel molecular-level thermodynamics and kinetics of hydrogen and oxygen electrocatalysis and, particularly, the proton-coupled electron transfer (PCET) process that takes place in a proton-deficient alkaline media. Extensive electrochemical and spectroscopic studies, on single-crystal Pt and metal oxides, have contributed to the development of activity descriptors, as well as the identification of the nature of active sites, and the rate-determining steps of the HOR and ORR. Among these, the structure and reactivity of interfacial water serve as key potential and pH-dependent kinetic factors that are helping elucidate the origins of the HOR and ORR activity differences in acids and bases. Additionally, deliberately modulating and controlling catalyst-support interactions have provided valuable insights for enhancing catalyst accessibility and durability during operation. The design and synthesis of highly conductive and durable alkaline membranes/ionomers have enabled AEMFCs to reach initial performance metrics equal to or higher than those of PEMFCs. We emphasize the importance of using membrane electrode assemblies (MEAs) to integrate the often separately pursued/optimized electrocatalyst/support and membranes/ionomer components. Operando/in situ methods, at multiscales, and ab initio simulations provide a mechanistic understanding of electron, ion, and mass transport at catalyst/ionomer/membrane interfaces and the necessary guidance to achieve fuel cell operation in air over thousands of hours. We hope that this Review will serve as a roadmap for advancing the scientific understanding of the fundamental factors governing electrochemical energy conversion in alkaline media with the ultimate goal of achieving ultralow Pt or precious-metal-free high-performance and durable alkaline fuel cells and related technologies.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Cation-doped ZnS catalysts for polysulfide conversion in lithium–sulfur batteries

Catalytic conversion of polysulfides is regarded as a crucial approach to enhancing kinetics and suppressing the shuttle effect in lithium-sulfur (Li-S) batteries. However, the activity prediction of Li-S catalysts remains elusive owing to the lack of mechanistic understanding of activity descriptors. Here, we report a volcano-shaped relationship between polysulfide adsorption ability and catalytic activity. In conjunction with theoretical analysis, we distinguish catalytic and anchoring effects to delineate the role of adsorption and emphasize the passivation of catalysts. These findings enable us to develop a composite catalyst, Co0.125Zn0.875S, which shows higher performance than simple binary compounds. Such a fundamental understanding of the intrinsic link between polysulfide adsorption and catalytic activity offers a rational viewpoint for designing Li-S catalysts and tuning their activities.

Shen, Zihan↗
DOE OSTI2023

Epitaxial Design of Complex Nickelates as Electrocatalysts for the Oxygen Evolution Reaction

Abstract The oxygen evolution reaction (OER) is a crucial process in electrochemical water splitting, a promising technology to renewably yield hydrogen gas from water. Designing and developing earth‐abundant, efficient, and stable OER electrocatalysts to replace the most widely used but scarce RuO 2 and IrO 2 are thus of critical interest. Recently, ABO 3 ‐structured perovskite oxides, especially rare‐earth nickelates, are extensively studied for their potential use as OER electrocatalysts. In particular, the epitaxial synthesis of complex oxide thin films allows flexible and precise control over the materials so that their structure–stability–property relationships can be established. Using nickelate thin films as model systems, this review illustrates how epitaxial design allows researchers to test different hypotheses and proposed descriptors, as well as formulate new design principles. Following a brief introduction to the background of OER mechanisms, proposed activity descriptors, and synthesis methods, various epitaxial design strategies are surveyed including strain tuning, composition control, surface termination/orientation selection, defect engineering, and interface design. These have led to precise control over the atomic structures and electronic properties of nickelates which in turn determine their electrochemical performance. Finally, the remaining challenges and perspectives toward a deeper understanding and use of complex oxides as OER catalysts are discussed.

Choi, Min‐Ju↗
DOE OSTI2024

Biomimetic Control over Bimetallic Nanoparticle Structure and Activity via Peptide Capping Ligand Sequence

Here, the controlled design of bimetallic nanoparticles (BNPs) is a key goal in tailoring their catalytic properties. Recently, biomimetic pathways demonstrated potent control over the distribution of different metals within BNPs, but a direct understanding of the peptide effect on the compositional distribution at the interparticle and intraparticle levels remains lacking. We synthesized two sets of PtAu systems with two peptides and correlated their structure, composition, and distributions with the catalytic activity. Structural and compositional analyses were performed by a combined machine learning-assisted refinement of X-ray absorption spectra and Z-contrast measurements by scanning transmission electron microscopy. The difference in the catalytic activities between nanoparticles synthesized with different peptides was attributed to the details of interparticle distribution of Pt and Au across these markedly heterogeneous systems, comprising Pt-rich, Au-rich, and Au core/Pt shell nanoparticles. The total amount of Pt in the shells of the BNPs was proposed to be the key catalytic activity descriptor. This approach can be extended to other systems of metals and peptides to facilitate the targeted design of catalysts with the desired activity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cooperative Effects Drive Water Oxidation Catalysis in Cobalt Electrocatalysts through the Destabilization of Intermediates

A barrier to understanding the factors driving catalysis in the oxygen evolution reaction (OER) is understanding multiple over- lapping redox transitions in the OER catalysts. The complexity of these transitions obscure the relationship between the coverage of adsorbates and OER kinetics, leading to an experimental challenge in measuring activity descriptors, such as binding energies, as well as adsorbate interactions, which may destabilize intermediates and modulate their binding energies. Herein, we utilize a newly designed optical spectroelectrochemistry system to measure these phenomena in order to contrast the behavior of two electrocatalysts, cobalt oxyhydroxide (CoOOH) and cobalt-iron hexacyanoferrate (cobalt-iron Prussian blue, CoFe-PB). Three distinct optical spectra are observed in each catalyst, corresponding to three separate redox transitions, the last of which we show to be active for the OER using time-resolved spectroscopy and electrochemical mass spectroscopy. By combining predictions from density functional theory with parameters obtained from electroadsorption isotherms, we demonstrate that a destabilization of catalytic intermediates occurs with increasing coverage. In CoOOH, a strong (~0.34 eV/ monolayer) destabilization of a strongly bound catalytic intermediate is observed, leading to a potential offset between the accumulation of the intermediate and measurable O 2 evolution. We contrast these data to CoFe-PB, where catalytic intermediate generation and O 2 evolution onset coincide due to weaker binding and destabilization (~0.19 eV/monolayer). By considering a correlation between activation energy and binding strength, we suggest that such adsorbate driven destabilization may account for a significant fraction of the observed OER catalytic activity in both materials. Finally, we disentangle the effects of adsorbate interactions on state coverages and kinetics to show how adsorbate interactions determine the observed Tafel slopes. Crucially, the case of CoFe-PB shows that, even where interactions are weaker, adsorption remains non-Nernstian, which strongly influences the observed Tafel slope.

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

Rational Selection of Transition-Metal Oxide Electrocatalysts from Structure Electronic Structure-Activity Relations: The Role of Defects, Strain, and Sub-Surface Layering

This BES research investigates the physicochemical properties of metal oxides and how they affect electrocatalytic functionalities. The goal is to develop a predictive framework for realizing top-performing electrocatalytic materials for energy-critical reactions. The hypothesis is that well-defined thin films allow detailed mapping of structural-activity relationships because flat surfaces are more straightforward to characterize. Furthermore, the well-defined nature of thin-film metal oxides allows precise tuning of structural and chemical variables for structure-activity-relationship mapping. The proposed research has two technical objectives. The first is to experimentally assess whether the binding energies of surface oxygen can serve as an activity descriptor for oxygen electrocatalysis on metal oxides and then how to control them by tuning the structure and chemical variables. The second is to find the rate-limiting process in oxygen electrocatalysis and other small-molecule reactions. Similar mechanistic insights have been developed on well-defined platinum surfaces but not yet on oxides. This research addresses this gap and uses electrochemistry and X-ray photoemission spectroscopy to study oxide surface chemistry. The obtained insights are collectively analyzed to reveal how the oxides’ structural and chemical variables affect kinetics and can be used to design more active electrocatalysts for energy-critical reactions.

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

Operando methods: A new era of electrochemistry

One of the grand challenges facing electrochemistry is to directly resolve the complex nature of (electro)catalyst active sites and capture real-time “movies” of reaction dynamics, i.e. “watching chemistry in action”. The need for such fundamental understanding has stimulated the development of operando/in situ methods, which have greatly enhanced our ability to identify activity descriptors of electrocatalysts and establish structure–property relationships of energy materials. Here, this review summarizes the frontiers of operando electrochemical liquid-cell scanning transmission electron microscopy and correlative synchrotron X-ray methods, which are complementary tools to comprehensively investigate reaction dynamics across multiple spatiotemporal scales. In an effort to encourage greater adoption of advanced operando methods by the general electrochemistry community, this review points out the need to benchmark electrochemistry in confined and heterogenous liquid environment with minimal beam-induced damage. We anticipate that multimodal operando methods will become indispensable for understanding interfacial reaction mechanisms for the broad chemistry and energy materials communities.

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

Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning

Here, we show that unsupervised machine learning (ML) using principal component analysis (PCA) provides a straightforward pathway for developing accurate and interpretable electronic-structure descriptors of the chemical and catalytic properties of materials. We demonstrate the approach by finding chemisorption descriptors for metal alloys and surface oxygens on metals and metal oxides. In both cases, the principal component (PC) descriptors yield ML models that predict the material’s chemical properties with competitive accuracy compared to ML models built using established descriptors. Importantly, interpreting the electronic-structure patterns captured by each PC descriptor via signal reconstruction suggests potential design motifs for future electronic-structure descriptor design and allows us to identify links between a material’s geometric and catalytic properties. Ultimately, we show that the unsupervised ML approach provides a route to find electronic-structure descriptors of the catalytic properties of materials that readily connect to geometric structure and composition.

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

Trends and descriptors of heterogeneous hydroformylation activity and selectivity of RhM 3 (M = Fe, Co, Ni, Cu and Zn) catalysts

Here monometallic Rh/MCM-41 and bimetallic RhM 3 /MCM-41 (M = Fe, Co, Ni, Cu, or Zn) catalysts are synthesized and tested for vapor-phase ethylene hydroformylation reaction. Co is found to exhibit a significant promotion effect on the selectivity of hydroformylation to C 3 oxygenates, followed by Fe and Cu, with Ni and Zn showing a negative effect. DFT calculations reveal that the addition of a secondary metal can provide a new type of site, being able to selectively tune the binding energies of reaction intermediates, and thus lead to different catalytic performances.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Pushing Cu uphill of the volcano curve: Impact of a WC support on the catalytic activity of copper toward the hydrogen evolution reaction

Here, the adsorption of atomic H and H 2 on copper mono- and submonolayers supported on hexagonal WC(0001) surfaces has been investigated using density functional theory with the Perdew–Burke–Ernzerhof exchange correlation functional and D2 van der Waals corrections. Results evidence the impact of the termination of the carbide substrate on fundamental properties of Cu adatoms, and, hence, on the stability of molecular and atomic hydrogen, defining copper's catalytic activity for hydrogen evolution reaction. Using H adsorption energy as a descriptor, catalytic activity of Cu adlayers for hydrogen evolution reaction was estimated using traditional volcano curves and a curve, obtained at low hydrogen coverage. Obtained results evidence that copper adlayers supported on the WC may present a viable low-cost alternative to noble metal-based catalysts, with improved catalytic activity compared to that of copper. This, potentially, can be a useful basis for designing and developing novel functional materials with predetermined catalytic properties.

08 HYDROGEN↗
NASA NTRS2014

On the Relationship Between Global Land-Ocean Temperature and Various Descriptors of Solar-Geomagnetic Activity and Climate

Examined are sunspot cycle- (SC-) length averages of the annual January-December values of the Global Land-Ocean Temperature Index ( ) in relation to SC-length averages of annual values of various descriptors of solar-geomagnetic activity and climate, incorporating lags of 0-5 yr. For the overall interval SC12-SC23, the is inferred to correlate best against the parameter incorporating lag = 5 yr, where the parameter refers to the resultant aa value having removed that portion of the annual aa average value due to the yearly variation of sunspot number (SSN). The inferred correlation between the and is statistically important at confidence level cl > 99.9%, having a coefficient of linear correlation r = 0.865 and standard error of estimate se = 0.149 degC. Excluding the most recent cycles SC22 and SC23, the inferred correlation is stronger, having r = 0.969 and se = 0.048 degC. With respect to the overall trend in the , which has been upwards towards warmer temperatures since SC12 (1878-1888), solar-geomagnetic activity parameters are now trending downwards (since SC19). For SC20-SC23, in contrast, comparison of the against SC-length averages of the annual value of the Mauna Loa carbon dioxide ( ) index is found to be highly statistically important (cl >> 99.9%), having r = 0.9994 and se = 0.012 degC for lag = 2 yr. On the basis of the inferred preferential linear correlation between the and , the current ongoing SC24 is inferred to have warmer than was seen in SC23 (i.e., >0.526 degC), probably in excess of 0.68 degC (relative to the 1951-1980 base period).

Wilson, Robert M.↗
DOE OSTI2022

Enhanced descriptor identification and mechanism understanding for catalytic activity using a data-driven framework: revealing the importance of interactions between elementary steps

We report accurate identification of descriptors for catalytic activities has long been essential to the in-depth understanding of catalysis and recently to set the basis for catalyst screening. However, commonly used methods suffer from low accuracy in predictability. This study reports an enhanced approach to accurately identify the descriptors from a kinetic dataset using a machine learning (ML) surrogate model. CO hydrogenation to methanol over Cu-based catalysts was taken as a case study. Our model captures not only the contribution from individual elementary steps but also the interaction between relevant steps within a reaction network, which was found to be essential for high accuracy. As a result, six effective descriptors are identified, which are accurate enough to ensure the trained gradient boosted regression (GBR) model for good prediction of the methanol turnover frequency (TOF) over metal (M)-doped Cu(111) model surfaces (M = Au, Cu, Pd, Pt, Ni). More importantly, going beyond the purely mathematical ML model, the catalytic role of each identified descriptor can be revealed by using model-agnostic interpretation tools, which enhances the insight into the promoting effect of alloying. The trained GBR model outperforms the conventional derivative-based methods in terms of both the predictability and the mechanism understanding. It opens alternative possibilities toward accurate descriptor-based rational catalyst optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗