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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 109 records · Page 6
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 OSTI2022

Automated exploitation of the big configuration space of large adsorbates on transition metals reveals chemistry feasibility

Mechanistic understanding of large molecule conversion and the discovery of suitable heterogeneous catalysts have been lagging due to the combinatorial inventory of intermediates and the inability of humans to enumerate all structures. Here, we introduce an automated framework to predict stable configurations on transition metal surfaces and demonstrate its validity for adsorbates with up to 6 carbon and oxygen atoms on 11 metals, enabling the exploration of ~10 8 potential configurations. It combines a graph enumeration platform, force field, multi-fidelity DFT calculations, and first-principles trained machine learning. Clusters in the data reveal groups of catalysts stabilizing different structures and expose selective catalysts for showcase transformations, such as the ethylene epoxidation on Ag and Cu and the lack of C-C scission chemistry on Au. Deviations from the commonly assumed atom valency rule of small adsorbates are also manifested. This library can be leveraged to identify catalysts for converting large molecules computationally.

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

Highly active, ultra-low loading single-atom iron catalysts for catalytic transfer hydrogenation

Highly effective and selective noble metal-free catalysts attract significant attention. Here, a single-atom iron catalyst is fabricated by saturated adsorption of trace iron onto zeolitic imidazolate framework-8 (ZIF-8) followed by pyrolysis. Its performance toward catalytic transfer hydrogenation of furfural is comparable to state-of-the-art catalysts and up to four orders higher than other Fe catalysts. Isotopic labeling experiments demonstrate an intermolecular hydride transfer mechanism. First principles simulations, spectroscopic calculations and experiments, and kinetic correlations reveal that the synthesis creates pyrrolic Fe(II)-plN 3 as the active center whose flexibility manifested by being pulled out of the plane, enabled by defects, is crucial for collocating the reagents and allowing the chemistry to proceed. The catalyst catalyzes chemoselectively several substrates and possesses a unique trait whereby the chemistry is hindered for more acidic substrates than the hydrogen donors. This work paves the way toward noble-metal free single-atom catalysts for important chemical reactions.

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

Tandem bulk oxygen diffusion and surface reactions in reducible metal oxides control redox cycle dynamics

The interplay between bulk oxygen diffusion and surface reactions in reducible metal oxides is key in heterogeneous catalysts, but direct measurements of oxygen mobility, transient kinetics, and in situ spectroscopies have been lacking. Here, we reveal complex dynamic behavior of ceria-zirconia by H 2 using transient kinetics via mass spectrometry and in situ Raman and near-ambient pressure x-ray photoelectron spectroscopies. Molecular dynamics simulations with a machine learning potential delineate competitive oxygen diffusion mechanisms, with an optimal mobility at intermediate reductions. We expose a compensation between vacancy availability and lattice distortion at intermediate to high reductions and Frenkel defects at low reductions, underscoring a potential deficiency of 16 O/ 18 O exchange experiments in deducing oxygen mobility. Vacancies in proximity require electron localization on Ce atoms further away. The continuous replenishment of surface oxygen results in a varying reduction rate, with H 2 dissociation being the rate-limiting step. Multiscale transient simulations, consistent with experiments, indicate catalysts of potentially spatially varying oxidation states. The approach is broadly applicable to reducible oxide materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Non-topotactic reactions enable high rate capability in Li-rich cathode materials

High-rate cathode materials for Li-ion batteries require fast Li transport kinetics, which typically rely on topotactic Li intercalation/de-intercalation because it minimally disrupts Li transport pathways. In contrast to this conventional view, here we demonstrate that the rate capability in a Li-rich cation-disordered rocksalt cathode can be significantly improved when the topotactic reaction is replaced by a non-topotactic reaction. The fast non-topotactic lithiation reaction is enabled by facile and reversible transition metal octahedral-to-tetrahedral migration, which improves rather than impedes Li transport. Using this concept, we show that high-rate performance can be achieved in Mn- and Ni-based cation-disordered rocksalt materials when some of the transition metal content can reversibly switch between octahedral and tetrahedral sites. Overall, this study provides a new perspective on the design of high-performance cathode materials by demonstrating how the interplay between Li and transition metal migration in materials can be conducive to fast non-topotactic Li intercalation/de-intercalations.

25 ENERGY STORAGE↗
DOE OSTI2021

Resonant amplification of enzymatic chemical oscillations by oscillating flow

Using theory and simulation, we analyzed the resonant amplification of chemical oscillations that occur due to externally imposed oscillatory fluid flows. The chemical reactions are promoted by two enzyme-coated patches located sequentially on the inner surface of a pipe that transports the enclosed chemical solution. In the case of diffusion-limited systems, the period of oscillations in chemical reaction networks is determined by the rate of the chemical transport, which is diffusive in nature and, therefore, can be effectively accelerated by the imposed fluid flows. In this work, we first identify the natural frequencies of the chemical oscillations in the unperturbed reaction–diffusion system and, then, use the frequencies as a forcing input to drive the system to resonance. We demonstrate that flow-induced resonance can be used to amplify the amplitude of the chemical oscillations and to synchronize their frequency to the external forcing. In particular, we show that even 10% perturbations in the flow velocities can double the amplitude of the resulting chemical oscillations. Particularly, effective control can be achieved for the two-step chemical reactions where during the first half-period, the fluid flow accelerates the chemical flux toward the second catalytic patch, while during the second half-period, the flow amplifies the flux to the first patch. The results can provide design rules for regulating the dynamics of coupled reaction–diffusion processes and can facilitate the development of chemical reaction networks that act as chemical clocks.

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

Finite-element-based simulations of electrodes for CO 2 cascade reduction reactions

The multielectron reduction of CO 2 to liquid fuels could be a path to scalable energy storage, but reaching this goal requires major advances in catalysis and systems engineering. Cascade catalysis, which couples sequential reactions without isolating intermediates, has emerged as a promising route to enhance selectivity and efficiency in CO 2 reduction (CO 2 R). In this review, we examine how finite-element-based simulations of continuum model [finite element method (FEM)] approaches are being used to analyze and guide CO 2 R cascade systems. We first outline the fundamentals of cascade catalysis and recent advances in catalytic materials (metallic, molecular, and hybrid architectures). We then focus on FEM developments at the electrode and device scales, emphasizing how these models capture transport phenomena, local microenvironments, and geometry-dependent effects. To clarify design principles, we present case studies of cascade electrodes organized in systems without and with integrated semiconductors. We further emphasize the integration of FEM with multiscale frameworks (density functional theory, molecular dynamics, kinetic Monte Carlo) and its role in bridging atomic-level insights with device-level performance. Finally, we identify current limitations and future prospects, including improved boundary conditions, coupling with operando experiments, and machine learning-accelerated model development. Together, these insights provide design principles for next-generation CO 2 R cascade systems for efficient solar fuel production.

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

Dynamic Catalysis Fundamentals: I. Fast calculation of limit cycles in dynamic catalysis

Dynamic catalysis—the forced oscillation of catalytic reaction coordinate potential energy surfaces (PES)—has recently emerged as a promising method for the acceleration of heterogeneously-catalyzed reactions. Theoretical study of enhancement of rates and supra-equilibrium product yield via dynamic catalysis has, to-date, been severely limited by onerous computational demands of forward integration of stiff, coupled ordinary differential equations (ODEs) that are necessary to quantitatively describe periodic cycling between PESs. Here, we establish a new approach that reduces, by ≳108×, the computational cost of finding the time-averaged rate at dynamic steady state (i.e. the limit cycle for linear and nonlinear systems of kinetic equations). Our developments are motivated by and conceived from physical and mathematical insight drawn from examination of a simple, didactic case study for which closed-form solutions of rate enhancement are derived in explicit terms of periods of oscillation and elementary step rate constants. Generalization of such closed-form solutions to more complex catalytic systems is achieved by introducing a periodic boundary condition requiring the dynamic steady state solution to have the same periodicity as the kinetic oscillations and solving the corresponding differential equations by linear algebra or Newton-Raphson-based approaches. The methodology is well-suited to extension to non-linear systems for which we detail the potential for multiple solutions or solutions with different periodicities. For linear and non-linear systems alike, the acute decrement in computational expense enables rapid optimization of oscillation waveforms and, consequently, accelerates understanding of the key catalyst properties that enable maximization of reaction rates, conversions, and selectivities during dynamic catalysis.

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

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Implementation and Performance

Developing theoretical understanding of complex reactions and processes at interfaces requires using methods that go beyond semilocal density functional theory to accurately describe the interactions between solvent, reactants and substrates. Methods based on many-body perturbation theory, such as the random phase approximation (RPA), have previously been limited due to their computational complexity. However, this is now a surmountable barrier due to the advances in computational power available, in particular through modern GPU-based supercomputers. In this work, we describe the implementation of RPA calculations within BerkeleyGW and show its favorable computational performance on large complex systems relevant for catalysis and electrochemistry applications. Our implementation builds off of the static subspace approximation which, by employing a compressed representation of the frequency dependent polarizability, enables the evaluation of the RPA correlation energy with significant acceleration and systematically controllable accuracy. We find that the computational cost of calculating the RPA correlation energy scales only linearly with system size for systems containing up to 50 thousand bands, and is expected to scale quadratically thereafter. We also show excellent strong scaling results across several supercomputers, demonstrating the performance and portability of this implementation.

algorithmic development↗
DOE OSTI2020

How directed evolution reshapes the energy landscape in an enzyme to boost catalysis

Two steps forward—now look back Whether designed computationally or uncovered in activity screening, enzymes repurposed for biocatalysis rarely start at the peak of proficiency. However, directed evolution can in some cases increase catalytic efficiency of a poor enzyme by many orders of magnitude. Otten et al. used a suite of biochemical techniques to investigate the origins of rate enhancement in a previously evolved model enzyme. Two conformational states are present in the initial, computationally designed enzyme, but only one is active. Shifting the population toward the active state is one factor in increasing catalytic efficiency during evolution. Single mutations do not greatly increase activity, but the synergistic combination of just two out of 17 substitutions can provide most of the rate enhancement seen in the final, evolved enzyme. Science , this issue p. 1442

Science & Technology - Other Topics↗
DOE OSTI2025

Thermodynamic Stability and Site‐Specific Distribution of Graphitic and Pyridinic Nitrogen in Graphene Moiré on Ru(0001)

Abstract Graphene‐like materials are of interest for large‐scale hydrogen storage applications due to their lightweight, durable, and scalable properties. Nitrogen‐doping minimizes kinetic limitations in diffusion and recombination on surfaces, however, the role of graphitic nitrogen (GN) and pyridinic nitrogen (PN) is not well understood. Nitrogen‐doped graphene is synthesized on Ru(0001) using chemical vapor deposition (CVD) of pyridine and ion irradiation. Scanning tunneling microscopy (STM), x‐ray photoelectron spectroscopy (XPS), and density functional theory (DFT) are used to identify the structure, location, and thermodynamic stability of nitrogen species within the graphene moiré. CVD of pyridine results in a low nitrogen concentration (<0.1at%), while the post‐growth nitrogen ion irradiation allows us to increase the concentration further. The concentration of GN and PN is controlled by varying the ion dose and annealing temperature. Comparison of measured and simulated STM images of GN and PN yield an excellent agreement, allowing us to confidently establish that GN is preferentially located near the center of the Atop region, while PN is located in the valley region of the graphene moiré. This report explicitly confirms the site assignments and provides a foundation for the site synthesis and analysis of structural and electronic properties that drive the reactivity of N‐doped graphene.

Gedara, Buddhika S. A. [Physical and Computational↗
DOE OSTI2020

A Preorganized Electric Field Leads to Minimal Geometrical Reorientation in the Catalytic Reaction of Ketosteroid Isomerase

Electrostatic interactions play a pivotal role in enzymatic catalysis and are increasingly modeled explicitly in computational enzyme design; nevertheless, they are challenging to measure experimentally. Using vibrational Stark effect (VSE) spectroscopy, we have measured electric fields inside the active site of the enzyme ketosteroid isomerase (KSI). These studies have shown that these fields can be unusually large, but it has been unclear to what extent they specifically stabilize the transition state (TS) relative to a ground state (GS). In the following, we use crystallography and computational modeling to show that KSI’s intrinsic electric field is nearly perfectly oriented to stabilize the geometry of its reaction’s TS. Moreover, we find that this electric field adjusts the orientation of its substrate in the ground state so that the substrate needs to only undergo minimal structural changes upon activation to its TS. This work provides evidence that the active site electric field in KSI is preorganized to facilitate catalysis and provides a template for how electrostatic preorganization can be measured in enzymatic systems.

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

Nanoscale Surface Structure of Nanometer-Thick Ferroelectric BaTiO 3 Films Revealed by Synchrotron X-ray Scanning Tunneling Microscopy: Implications for Catalytic Adsorption Reactions

Ferroelectric nanomaterials are of interest in catalysis, non-volatile memory, and neuromorphic computing among other applications because of their switchable structure that can alter electronic and interface properties of a single material. The investigation of the role of polarization on the surface structure and chemistry of ferroelectric nanomaterials is a longstanding challenge, as it ideally requires a combination of both nanoscale imaging and chemical spectroscopy. In this work we study a model ferroelectric BaTiO 3 thin film by synchrotron X-ray scanning tunneling microscopy (SX-STM), a unique method which integrates nanoscale surface imaging and chemically sensitive spectroscopy. We find that polarization switching from downward to upward in (001)single crystalline BaTiO 3 thin films increases the intensity of X-ray absorption across Ba M, Ti L and O K edges. Chemical mapping of nanometer sized domains further demonstrates the modulation of surface structures upon polarization switching, as well as confirming the trends observed in single point experiments across the surface. Here, we complement these measurements with ab-initio computational absorption spectroscopy to elucidate the effect of polarization switching on the core-hole excitations using the Bethe-Salpeter equation approach. Our experimental and theoretical results thus confirm a stronger binding strength for the upward polarized surface with molecular O 2 as a model reactant, offering mechanistic evidence that supports previous reports. This work advances the understanding of the surface chemistry and electronic structure of ferroelectrics, which can ultimately aid strategies to design interfaces with tailored properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Interpretable machine learning for knowledge generation in heterogeneous catalysis

Most applications of machine learning in heterogeneous catalysis thus far have used black-box models to predict computable physical properties (descriptors), such as adsorption or formation energies, that can be related to catalytic performance (that is, activity or stability). Here, extracting meaningful physical insights from these black-box models has proved challenging, as the internal logic of these black-box models is not readily interpretable due to their high degree of complexity. Interpretable machine learning methods that merge the predictive capacity of black-box models with the physical interpretability of physics-based models offer an alternative to black-box models. In this Perspective, we discuss the various interpretable machine learning methods available to catalysis researchers, highlight the potential of interpretable machine learning to accelerate hypothesis formation and knowledge generation, and outline critical challenges and opportunities for interpretable machine learning in heterogeneous catalysis.

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

Combining Computational Modeling with Reaction Kinetics Experiments for Elucidating the In Situ Nature of the Active Site in Catalysis

Microkinetic modeling based on density functional theory (DFT) derived energetics is important for addressing fundamental questions in catalysis. The quantitative fidelity of microkinetic models (MKMs), however, is often insufficient to conclusively infer the mechanistic details of a specific catalytic system. Here, this can be attributed to a number of factors such as an incorrect model of the active site for which DFT calculations are performed, deficiencies in the hypothesized reaction mechanism, inadequate consideration of the surface environment under reaction conditions, and intrinsic errors in the DFT exchange-correlation functional. Despite these limitations, we aim at developing a rigorous understanding of the reaction mechanism and of the nature of the active site for heterogeneous catalytic chemistries under reaction conditions. By achieving parity between experimental and modeling outcomes through robust parameter estimation and by ensuring coverage-consistency between DFT calculations and MKM predictions, it is possible to systematically refine the mechanistic model and, thereby, our understanding of the catalytic active site in situ.

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

From thermal catalysis to plasma catalysis: a review of surface processes and their characterizations

The use of atmospheric pressure plasma to enhance catalytic chemical reactions involves complex surface processes induced by the interactions of plasma-generated fluxes with catalyst surfaces. Industrial implementation of plasma catalysis necessitates optimizing the design and realization of plasma catalytic reactors that enable chemical reactions that are superior to conventional thermal catalysis approaches. This requires the fundamental understanding of essential plasma-surface interaction mechanisms of plasma catalysis from the aspect of experimental investigation and theoretical analysis or computational modeling. In addition, experimental results are essential to validate the relative theoretical models and hypotheses of plasma catalysis that was rarely understood so far, compared to conventional thermal catalysis. This overview focuses on two important application areas, nitrogen fixation and methane reforming, and presents a comparison of important aspects of the state of knowledge of these applications when performed using either plasma-catalysis or conventional thermal catalysis. We discuss the potential advantage of plasma catalysis over thermal catalysis from the aspects of plasma induced synergistic effect and in situ catalyst regeneration. In-situ/operando surface characterization of catalysts in plasma catalytic reactors is a significant challenge since the high pressure of realistic plasma catalysis systems preclude the application of many standard surface characterization techniques that operate in a low-pressure environment. Here, we present a review of the status of experimental approaches to probe gas-surface interaction mechanisms of plasma catalysis, including an appraisal of demonstrated approaches for integrating surface diagnostic tools into plasma catalytic reactors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Analysis of Aerothermal Heating Over Reusable Single-Stage to Orbit Vehicles

Using the General Aerodynamic Simulation Program (GASP) with finite-rate surface catalysis and radiative equilibrium surface temperature conditions, a computational study has been conducted to predict three-dimensional aero-convective heating over the proposed reusable single-stage to orbit vehicles. The solutions for three basic classes of usable single-stage-to-orbit vehicles, including wing body, lifting body and vertical lander, are presented and compared to provide information for vehicle design. The free stream conditions used in this study occur at an altitude of 57.5 km, ambient density of 4.129e-4 kg/cubic m, and velocity of 4,849 m/s. The convective heating over the vehicle surface in both laminar and turbulent flow regimes were computed. The Baldwin-Lomax algebraic model with a modified van Driest damping factor was applied in the turbulent flow calculations. A bifurcation model which guarantees the conservation of mass diffusive fluxes was adopted to account for the multi-species mass diffusion. The effects of turbulence and surface catalysis on the surface heating are discussed in detail The solutions indicate the degree of oxygen dissociation over the leeward side is sensitive to the shape of vehicle body. Predicted convective heating over the entire surface of lifting body is strongly affected by the presence of surface catalysis. For wing body and vertical lander, the surface catalysis effect does not appear to be important in the far downstream region, and turbulence is the dominant effect on the heating prediction in this region.

Chen, Y. K.↗
NASA NTRS2004

Montmorillonite, oligonucleotides, RNA and origin of life

Na-montmorillonite prepared from Volclay by the titration method facilitates the self-condensation of ImpA, the 5'-phosphorimidazolide derivative of adenosine. As was shown by AE-HPLC analysis and selective enzymatic hydrolysis of products, oligo(A)s formed in this reaction are 10 monomer units long and contain 67% 3',5'-phosphodiester bonds (Ferris and Ertem, 1992a). Under the same reaction conditions, 5'-phosphorimidazolide derivatives of cytidine, uridine and guanosine also undergo self-condensation producing oligomers containing up to 12-14 monomer units for oligo(C)s to 6 monomer units for oligo(G)s. In oligo(C)s and oligo(U)s, 75-80% of the monomers are linked by 2',5'-phosphodiester bonds. Hexamer and higher oligomers isolated from synthetic oligo(C)s formed by montmorillonite catalysis, which contain both 3',5'- and 2',5'-linkages, serve as catalysts for the non-enzymatic template directed synthesis of oligo(G)s from activated monomer 2-MeImpG, guanosine 5'-phospho-2-methylimidazolide (Ertem and Ferris, 1996). Pentamer and higher oligomers containing exclusively 2',5'-linkages, which were isolated from the synthetic oligo(C)s, also serve as templates and produce oligo(G)s with both 2',5'- and 3',5'-phosphodiester bonds. Kinetic studies on montmorillonite catalyzed elongation rates of oligomers using the computer program SIMFIT demonstrated that the rate constants for the formation of oligo(A)s increased in the order of 2-mer < 3-mer < 4-mer ... < 7-mer (Kawamura and Ferris, 1994). A decameric primer, dA(pdA)8pA bound to montmorillonite was elongated to contain up to 50 monomer units by daily addition of activated monomer ImpA to the reaction mixture (Ferris, Hill and Orgel, 1996). Analysis of dimer fractions formed in the montmorillonite catalyzed reaction of binary and quaternary mixtures of ImpA, ImpC, 2-MeImpG and ImpU suggested that only a limited number of oligomers could have formed on the primitive Earth rather than equal amounts of all possible isomers (Ertem and Ferris, 2000). Formation of phosphodiester bonds between mononucleotides by montmorillonite catalysis is a fascinating discovery, and a significant step forward in efforts to find out how the first RNA-like oligomers might have formed in the course of chemical evolution. However, as has been pointed out in several publications, these systems should be regarded as models rather than a literal representation of prebiotic chemistry (Orgel, 1998; Joyce and Orgel, 1999; Schwartz, 1999).

RNA/chemical synthesis↗