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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Compartmentalisation of molecular catalysts for nonorthogonal tandem catalysis

The development of nonorthogonal tandem catalysis enables the use of a combination of arbitrary catalysts to rapidly synthesize complex products in a substainable, efficient, and timely manner. The key is to compartmentalise the molecular catalysts, thereby overcoming inherent incompatibilities between individual catalysts or reaction conditions. This tutorial review analyses the development of the past two decades in the field of nonorthogonal tandem catalysis with an emphasis on compartmentalisation strategies. Here, we highlight design principles of functional materials for compartmentalisation and suggest future directions in the field of nonorthogonal tandem catalysis.

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

Synchrotron Catalysis Consortium (SCC) at NSLS-II: Dedicated Beamline Facilities for In Situ and Operando Characterization of Catalysts

The Synchrotron Catalysis Consortium (SCC) was funded and established in September 2005 at the National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory (BNL). For more than a decade, the SCC was the first of its kind in the United States, with a mission to promote the utilization of synchrotron techniques for cutting-edge catalysis research under in-situ conditions. The consortium consists of three Principal Investigators (Jingguang Chen, Columbia University, Anatoly Frenkel, Stony Brook University/BNL, and Jose Rodriguez, BNL) and scientific staff member Nebojsa Marinkovic. The initial team also included Radoslav Adzic, BNL, and collaborators from academic, national, and industrial laboratories. During the first decade of its operations at three NSLS beamlines (X18A, X18B, and X19A) until the closing of NSLS on September 30, 2014, the primary goal of the SCC team was to provide assistance and to develop new sciences/techniques to the catalysis community...This report outlines a brief history, specifications, techniques, and training and outreach for the facility.

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

Conformational ensembles reveal the origins of serine protease catalysis

Enzymes exist in ensembles of states that encode the energetics underlying their catalysis. Conformational ensembles built from 1231 structures of 17 serine proteases revealed atomic-level changes across their reaction states. By comparing the enzymatic and solution reaction, we identified molecular features that provide catalysis and quantified their energetic contributions to catalysis. Serine proteases precisely position their reactants in destabilized conformers, creating a downhill energetic gradient that selectively favors the motions required for reaction while limiting off-pathway conformational states. The same catalytic features have repeatedly evolved in proteases and additional enzymes across multiple distinct structural folds. In conclusion, our ensemble-function analyses revealed previously unknown catalytic features, provided quantitative models based on simple physical and chemical principles, and identified motifs recurrent in nature that may inspire enzyme design.

Du, Siyuan [Stanford Univ., CA (United States)] (O↗
DOE OSTI2021

Dual active site tandem catalysis of metal hydroxyl oxides and single atoms for boosting oxygen evolution reaction

We report the high voltage in oxygen evolution reaction (OER) often causes structural change in electrocatalysts and forms multiple active sites. Therefore, exploring the synergy of various active sites is extremely significant to develop catalysts for OER with multiple elementary steps. Herein, we adopt the physically adsorbed metal ions method to successfully synthesize a highly-efficient electrocatalyst containing the dual active sites of Fe-NiOOH and NiC4 single atoms (marked as Ni SAs/Fe-NiOOH). The Ni SAs/Fe-NiOOH displays outstanding OER performance with an overpotential of 269 mV to deliver current density of 10 mA/cm 2 that shows 55 mV superior to commercial IrO 2 /CB at the same condition. Experiments and density functional theory calculations indicate that the excellent OER activity of Ni SAs/Fe-NiOOH catalyst is attributed to the synergy of dual active sites of NiC 4 SAs and Fe-NiOOH. A tandem catalysis mechanism is also proposed to reveal the synergism of two active centers, which makes the potential-determining step more facile and accordingly decreases the OER overpotential. This work offers a new concept of tandem catalysis to develop the electrocatalysts with many elemental steps, like OER and oxygen reduction reaction catalysts.

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

Sustainable aviation fuels from biomass and biowaste via bio- and chemo-catalytic conversion: Catalysis, process challenges, and opportunities

Sustainable aviation fuel (SAF) production from biomass and biowaste streams is an attractive option for decarbonizing the aviation sector, one of the most-difficult-to-electrify transportation sectors. Despite ongoing commercialization efforts using ASTM-certified pathways (e.g., lipid conversion, Fischer-Tropsch synthesis), production capacities are still inadequate due to limited feedstock supply and high production costs. New conversion technologies that utilize lignocellulosic feedstocks are needed to meet these challenges and satisfy the rapidly growing market. Combining bio- and chemo-catalytic approaches can leverage advantages from both methods, i.e., high product selectivity via biological conversion, and the capability to build C-C chains more efficiently via chemical catalysis. Herein, conversion routes, catalysis, and processes for such pathways are discussed, while key challenges and meaningful R&D opportunities are identified to guide future research activities in the space. Bio and chemo-catalytic conversion primarily utilize the carbohydrate fraction of lignocellulose, leaving lignin as a waste product. This makes lignin conversion to SAF critical in order to utilize whole biomass, thereby lowering overall production costs while maximizing carbon efficiencies. Thus, lignin valorization strategies are also reviewed herein with vital research areas identified, such as facile lignin depolymerization approaches, highly integrated conversion systems, novel process configurations, and catalysts for the selective cleavage of aryl C–O bonds. The potential efficiency improvements available via integrated conversion steps, such as combined biological and chemo-catalytic routes, along with the use of different parallel pathways, are identified as key to producing all components of a cost-effective, 100% SAF.

09 BIOMASS FUELS↗
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

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

Catalytic Bias in Enzymatic Metal Cofactor-Based Oxidation-Reduction Catalysis

Catalytic bias refers to the relative rate preference of a catalyst for either the forward or reverse direction. In enzymatic metal cofactor-based oxidation-reduction catalysis, the tuning of catalytic bias plays an underlying role in controlling rates of reactivity. For this, enzymes have evolved complex active sites that can exist in multiple oxidation states with differing reduction potentials in order to achieve challenging multi-step, oxidation-reduction reactions. Conceivably, the relative stability of the intermediates that contribute to determining the rate-limiting step of the catalytic cycle could impose catalytic bias, although mechanisms for this concept are just beginning to be realized. As one example, recent work on Clostridium pasteurianum [FeFe]-hydrogenases which catalyze reversible hydrogen oxidation have shown that the differential stabilization/destabilization of active site oxidation states through either static or dynamic protein interactions can preferentially promote either the hydrogen oxidation or proton reduction direction of the reaction. This revealed how an enzymatic cofactor can impose bias in oxidation-reduction catalysis through various tuning mechanisms by protein scaffold interactions. The hypothesis based on achieving catalytic bias through the modulation of cofactor oxidation states critical for the reaction cycle can be extended more generally to other cofactor-based oxidation-reductions catalysts. The current understanding of catalytic bias has significant implications for the design of synthetic catalysts used in industrial settings, as well as providing a greater fundamental understanding of the factors that control metabolic processes in all life.

catalysis↗
DOE OSTI2020

Modifiers versus Channels: Creating Shape-Selective Catalysis of Metal Nanoparticles/Porous Nanomaterials

Shape-selective catalysis is of great research interest for its key role in chemical synthesis. Porous nanomaterials with uniform pore structures, have been proven as ideal supports for metal nanoparticles (MNPs) to generate efficient shape-selective catalysis. However, many widely used commercial irregular porous nanomaterials usually face the challenge to realize satisfactory shape selectivity due to the lack of molecular sieving structures. In this work, we report a concept of creating shape selectivity in MNPs/porous-MNPs using appropriate modifiers. The remained MNPs within the porous nanomaterials can cooperate with the channels to generate selectivity. Such strategy not only applies to regular porous nanomaterials (metal-organic frameworks, zeolites, etc.), but also can be extended to irregular porous nanomaterials (active carbon, P25, etc.). Potentially, the matching among different MNPs, corresponding modifiers and porous nanomaterials makes our strategy promising for wide applications in selective catalytic systems.

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

Multireference Methods are Realistic and Useful Tools for Modeling Catalysis

Abstract Highly correlated systems, in particular those that include transition metals, are ubiquitous in catalysis. The significant static correlation found in such systems is often poorly accounted for using Kohn Sham density functional theory methods, as they are single determinantal in nature. Applications to catalysis of more rigorous and appropriate multiconfigurational methods have been reported in select instances, but their use remains rare. We discuss obstacles that hinder the routine application of multireference (MR) wave function theoretical calculations to catalytic systems and the current state of the art with respect to removing those obstacles.

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

Energy catalysis needs ligands with high oxidative stability

Replacing fossil fuel-based energy by renewable sources is a transition that society needs to make to meet future energy demand and simultaneously address climate change. Coupling renewable energy sources with electrochemical catalysis provides a promising path to carbon-neutral fuels and chemicals when the necessary reducing equivalents and protons are harvested from water. Developing highly active, stable, and inexpensive electrocatalysts for the oxygen evolution reaction (OER) is accordingly a centerpiece of a renewable energy portfolio. Whereas viable OER catalysts are heterogeneous in nature, owing to their oxidative stability, the realization of stable molecular OER catalysts greatly expands the horizon of energy science with the ability to tune OER energetics and mechanisms with fidelity. In this perspective, current challenges in the field of molecular OER catalysis are addressed with promising lines of research that are directed to designing ligands that can withstand the harsh oxidizing environment of OER.

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

Sequential Dosing Strategies for Controlling Selectivity and Plasma-Phase Contributions in Plasma Catalysis

Plasma-assisted catalysis has advanced in recent years, particularly for transforming stable reactants at atmospheric pressure and ambient temperature. However, achieving a deeper understanding of the many plasma and catalytic contributions remains a significant goal, as improving product yield and selectivity in plasma catalysis depends on proper catalyst selection, which is often challenging due to the complex interplay between plasma-phase and plasma-surface reactions. A sequential methodology has emerged as a means to decouple the catalyst activity from plasma-phase reactions. In this approach, nonthermal plasma is used in one step to activate and/or convert a gas phase or surface bound reactant, while in a second step, the catalyst directs product formation under steady-state or temperature-programmed conditions. This review examines studies using this technique for reactions involving N 2 , CO 2 , and SO 2 , offering insights into reaction mechanisms and catalyst behavior/selection for these transformations. These systematic studies provide a framework that can be applied to other plasma-assisted reactions. We also highlight remaining questions, propose directions for future studies, and discuss the potential of applying this methodology to other reaction systems.

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

Plasmonic Hot-Carrier Generation and Catalysis in Ti 3 C 2 O 2 from Real-Time TDDFT Simulations

Photoinduced hot electrons are central to plasmon-driven catalysis. Atomically thin Ti 3 C 2 O 2 , with high carrier density and broad optical absorption, offers a promising platform for plasmon-driven reactions. However, comprehensive investigations of its plasmon resonance, hot-carrier generation, and plasmonic catalytic performance remain limited. In this work, real-time time-dependent density functional theory (rt-TDDFT) was employed to study Ti 3 C 2 O 2 ’s plasmon excitation and hot-carrier generation from nonradiative plasmon damping. The temporal evolution of the dipole moment reveals plasmon resonance in Ti 3 C 2 O 2 , followed by strong plasmon damping that redistributes the stored energy to generate hot carriers. Ti 3 C 2 O 2 with low oxygen vacancy concentration (O v -Ti 3 C 2 O 2 ) exhibits plasmonic behavior resembling the pristine surface, and the plasmon-generated hot electrons can markedly reduce the dissociation barrier of CO 2 at the oxygen vacancy. These findings provide fundamental insights into the plasmonic properties of Ti 3 C 2 O 2 and how they drive its catalytic performance in surface reactions, which is valuable for advancing plasmon-driven catalysis.

CO2 reduction↗
DOE OSTI2023

Species, Pathways, and Timescales for NH 3 Formation by Low-Temperature Atmospheric Pressure Plasma Catalysis

Species, pathways, and timescales for NH3 production by plasma catalysis over transition-metal wools are determined by measuring plasma-derived species densities [N, H, and N 2 (v)], quantitatively correlating consumption of these species with NH 3 formation, and measuring consumption of plasma-derived species at different residence times. These findings are enabled by a capillary flow through Ar/N 2 /H 2 plasma jet reactor setup that allows for the measurement of gas-phase species densities by molecular beam mass spectrometry. Surface-mediated reactions involving N radicals are responsible for NH 3 formation over Fe, Ni, and Ag surfaces. N reacts to form NH 3 with ~100% selectivity over Ni and Ag when H/N > 3 and % H 2 ≥ 0.5. The selectivity to ammonia drops as H and H 2 densities decrease for each catalyst. A comparison between amounts of NH 3 formed and N consumed with and without catalysts present shows that surface reactions enable higher and more selective conversion of N to NH 3 than gas-phase reactions alone. The conversion of N to NH 3 is negligible in the absence of H, demonstrating that H is required to produce NH 3 at these operating conditions. The consumption of N occurs on the same timescale as NH 3 formation, further confirming that reactions involving N contribute to NH 3 formation. Though vibrationally excited N 2 [N 2 (v)] is produced in quantities exceeding N by 100-fold, consumption of N 2 (v) on the catalytic surface does not contribute to NH 3 formation. Furthermore, these findings show that for low-temperature atmospheric pressure plasma catalysis, surface- mediated reactions among radical N and H species drive NH 3 formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A Perspective on Multiscale Modeling of Explicit Solvation-Enabled Simulations of Catalysis at Liquid–Solid Interfaces

Catalysis at liquid-solid interfaces is profoundly influenced by the interfacial solvent structure, which affects catalytic activity, selectivity, and reaction pathways. This perspective discusses state-of-the-art multiscale modeling methods that integrate quantum mechanics and molecular mechanics approaches to apply explicit solvent molecules to capture these interfacial phenomena. Specifically, the construction of multiscale models, the importance of capturing the interfacial solvent structure, and the computational strategies used to achieve this are explored, and the challenges in balancing chemical accuracy with computational expense are highlighted. Additionally, this perspective addresses the limitations of current methods. Opportunities for integrating machine learning are proposed. Here, by advancing the efficiency and user friendliness of multiscale modeling, it is argued that deeper insights into heterogeneous catalysis in liquid phases can be provided, which will ultimately contribute to the development of more efficient catalytic processes.

Ab initio molecular dynamics↗
DOE OSTI2021

Compartmentalization and Photo-Regulating Pathways for Incompatible Tandem Catalysis

This contribution describes an advanced compartmentalized micellar nanoreactor that possesses a reversible photoresponsive feature and its application towards photo-regulating reaction pathways for incompatible tandem catalysis under aqueous conditions. The smart nanoreactor is based on multi-functional amphiphilic poly(2-oxazoline)s and covalently crosslinked with spiropyran upon micelle formation in water. It responds to light irradiation in a wavelength-selective manner switching its morphology as confirmed by dynamic light scattering and cryo-transition electron microscopy. The compartmental structure renders distinct nanoconfinements for two incompatible enantioselective transformations: a rhodium-diene complex-catalyzed asymmetric 1,4-addition occurs in the hydrophilic corona while a Rh-TsDPEN-catalyzed asymmetric transfer hydrogenation proceeds in the hydrophobic core. Control experiments and kinetic studies showed that the gated behavior induced by the photo-triggered reversible spiropyran to merocyanine transition in the cross-linking layer is key to discriminate among substrates/reagents during the catalysis. Here, the smart nanoreactor realized photo-regulation to direct the reaction pathway to give a multi-chiral product with high conversions and perfect enantioselectivities in aqueous media. Our SCM catalytic system, on a basic level, mimics the concepts of compartmentalization and responsiveness Nature uses to coordinate thousands of incompatible chemical transformations into streamlined metabolic processes.

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

Tuning the Conformations of an M4L4 Cage and Their Impact on Catalysis

Enzymes catalyze chemical reactions with remarkable rate enhancements and selectivity. Supramolecular catalysis seeks to understand and emulate these outcomes, leveraging noncovalent interactions, electric fields, and controlled active site microenvironments to enhance catalysis in an enzyme-like fashion. The effects of conformational dynamics on supramolecular catalysts and assemblies are, however, relatively unexplored, despite their crucial role in enzyme rate enhancement. Here, we elucidate the conformational landscape of a model M4L4 supramolecular host through a rational approach: stabilizing a high-energy conformer through distal ligand modification and a transient intermediate state through symmetry-matched guest encapsulation, as well as tuning the conformer distribution through same-charge metal exchange at the host vertices. Each of these structural modifications induces a substantial shift in the host's conformational landscape, offering insights into the rational design of conformationally dynamic cages and enzymes. Although the thermodynamic properties of the dynamic Ga4L412- cage can be influenced by temperature, solvent, and guest binding, we find that conformational change occurs on a time scale that renders it rate-limiting in a model catalytic reaction, precluding rate enhancement through conformational selection. This concept is illustrated by locking the catalytically inactive conformer to a high-energy conformer that is catalytically competent. These findings demonstrate that precise modulation of the conformational landscape of supramolecular hosts provides an effective strategy for controlling their catalytic activity and binding.

Catalysis↗
DOE OSTI2025

Developing machine learning for heterogeneous catalysis with experimental and computational data

Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical properties. In the heterogeneous catalysis communities, machine learning models have mostly been developed using high-throughput quantum chemistry calculations, with only a few case studies resulting in experimentally validated catalyst improvements. This limited success may be due to the use of simplified catalyst structures in computational studies and the lack of comprehensive experimental datasets. In this Review, we bring together studies integrating high-throughput approaches and machine learning for the advancement of solid heterogeneous catalysis, leveraging both experimental and computational data. We systematically analyze trends in the field, based on the descriptors used as model input and output; the materials, devices, or reactions investigated; the dataset size; and the overall achievements. Furthermore, for models reporting unitless R 2 values, we compare the performances based on these mentioned trends.

Computational chemistry↗
DOE OSTI2021

Using computational singular perturbation as a diagnostic tool in ODE and DAE systems: a case study in heterogeneous catalysis

We have extended the computational singular perturbation (CSP) method to differential algebraic equation (DAE) systems and demonstrated its application in a heterogeneous-catalysis problem. The extended method obtains the CSP basis vectors for DAEs from a reduced Jacobian matrix that takes the algebraic constraints into account. Here we use a canonical problem in heterogeneous catalysis, the transient continuous stirred tank reactor (T-CSTR), for illustration. The T-CSTR problem is modelled fundamentally as an ordinary differential equation (ODE) system, but it can be transformed to a DAE system if one approximates typically fast surface processes using algebraic constraints for the surface species. We demonstrate the application of CSP analysis for both ODE and DAE constructions of a T-CSTR problem, illustrating the dynamical response of the system in each case. We also highlight the utility of the analysis in commenting on the quality of any particular DAE approximation built using the quasi-steady state approximation (QSSA), relative to the ODE reference case.

97 MATHEMATICS AND COMPUTING↗