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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Continuity of reaction kinetics across the pressure and materials gaps in CO oxidation on FeO–Pt interfaces

Translating atomic-scale insights from surface science studies of model catalysts to practical powder catalysts remains a persistent challenge in heterogeneous catalysis. Here, in this study, we demonstrate mechanistic continuity across the pressure and materials gaps during CO oxidation at the FeO-Pt interface using in situ microscopy, spectroscopy and computational modelling. Under reaction conditions, coordinatively unsaturated Fe (Fe cus ) sites at the interface enable selective O 2 activation on CO-saturated surfaces, circumventing the CO-poisoning limitation of platinum-group metals. We identify parallel reaction pathways involving the *O 2 -*CO intermediate. Remarkably, activation energies remain consistent at 12-15 kJ mol −1 (0.12-0.16 eV) from ultrahigh vacuum to atmospheric pressures and from FeO/Pt(111) model catalysts to FeO/Pt powder catalysts, validating mechanistic insights derived from surface science studies. Our findings show an example of bridging the long-standing divide between model and practical catalyst systems, establishing an effective approach to capture catalytic behaviours under operational conditions and advancing mechanism-driven catalyst design.

03 NATURAL GAS↗
DOE OSTI2021

Modeling the electrical double layer at solid-state electrochemical interfaces

Models of the electrical double layer (EDL) at electrode/liquid-electrolyte interfaces no longer hold for all-solid-state electrochemistry. Here we show a more general model for the EDL at a solid-state electrochemical interface based on the Poisson–Fermi–Dirac equation. By combining this model with density functional theory predictions, the interconnected electronic and ionic degrees of freedom in all-solid-state batteries, including the electronic band bending and defect concentration variation in the space-charge layer, are captured self-consistently. Along with a general mathematical solution, the EDL structure is presented in various materials that are thermodynamically stable in contact with a lithium metal anode: the solid electrolyte Li 7 La 3 Zr 2 O 12 (LLZO) and the solid interlayer materials LiF, Li 2 O and Li 2 CO 3 . Here, the model further allows design of the optimum interlayer thicknesses to minimize the electrostatic barrier for lithium ion transport at relevant solid-state battery interfaces.

25 ENERGY STORAGE↗
DOE OSTI2022

Step Catalysis to Synthesize Fossil-Free Ammonia at Atmospheric Pressure (Final Technical Report)

Affordable fossil-free ammonia synthesis will enable high-yield sustainable crop production for a growing world population while preserving the planet and making the best use of water and land. Simple technology amenable to intermittent operation using renewable energy will be made available through step catalysis activating dinitrogen at atmospheric pressure by nitride formation. Project objectives: (1) At the single particle level, quantify and analyze N2 activation by doped or alloyed manganese macroscopic- and nano particles at atmospheric pressure, (2) Quantify and analyze ammonia synthesis from doped or alloyed metal nitride particles when contacting them with hydrogen at atmospheric pressure, and (3) Integrate experimental data and atomic-level computational models to predict the behavior of metal alloys in nitrogen activation and subsequent ammonia synthesis.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Nitrogen Atom Transfer Catalysis by Metallonitrene C−H Insertion: Photocatalytic Amidation of Aldehydes

Abstract C−H amination and amidation by catalytic nitrene transfer are well‐established and typically proceed via electrophilic attack of nitrenoid intermediates. In contrast, the insertion of (formal) terminal nitride ligands into C−H bonds is much less developed and catalytic nitrogen atom transfer remains unknown. We here report the synthesis of a formal terminal nitride complex of palladium. Photocrystallographic, magnetic, and computational characterization support the assignment as an authentic metallonitrene (Pd−N) with a diradical nitrogen ligand that is singly bonded to Pd II . Despite the subvalent nitrene character, selective C−H insertion with aldehydes follows nucleophilic selectivity. Transamidation of the benzamide product is enabled by reaction with N 3 SiMe 3 . Based on these results, a photocatalytic protocol for aldehyde C−H trimethylsilylamidation was developed that exhibits inverted, nucleophilic selectivity as compared to typical nitrene transfer catalysis. This first example of catalytic C−H nitrogen atom transfer offers facile access to primary amides after deprotection.

Schmidt‐Räntsch, Till↗
DOE OSTI2022

Nitrogen Atom Transfer Catalysis by Metallonitrene C−H Insertion: Photocatalytic Amidation of Aldehydes

Abstract C−H amination and amidation by catalytic nitrene transfer are well‐established and typically proceed via electrophilic attack of nitrenoid intermediates. In contrast, the insertion of (formal) terminal nitride ligands into C−H bonds is much less developed and catalytic nitrogen atom transfer remains unknown. We here report the synthesis of a formal terminal nitride complex of palladium. Photocrystallographic, magnetic, and computational characterization support the assignment as an authentic metallonitrene (Pd−N) with a diradical nitrogen ligand that is singly bonded to Pd II . Despite the subvalent nitrene character, selective C−H insertion with aldehydes follows nucleophilic selectivity. Transamidation of the benzamide product is enabled by reaction with N 3 SiMe 3 . Based on these results, a photocatalytic protocol for aldehyde C−H trimethylsilylamidation was developed that exhibits inverted, nucleophilic selectivity as compared to typical nitrene transfer catalysis. This first example of catalytic C−H nitrogen atom transfer offers facile access to primary amides after deprotection.

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

Tuning Proton Transfer Thermodynamics in SARS-CoV-2 Main Protease: Implications for Catalysis and Inhibitor Design

The catalytic reaction in SARS-CoV-2 main protease is activated by a proton transfer (PT) from Cys145 to His41. The same PT is likely also required for the covalent binding of some inhibitors. Here we use a multiscale computational approach to investigate the PT thermodynamics in the apo enzyme and in complex with two potent inhibitors, N3 and the α-ketoamide 13b. We show that with the inhibitors the free energy cost to reach the charge-separated state of the active-site dyad is lower, with N3 inducing the most significant reduction. We also show that a few key sites (including specific water molecules) significantly enhance or reduce the thermodynamic feasibility of the PT reaction, with selective desolvation of the active site playing a crucial role. The approach presented is a cost-effective procedure to identify the enzyme regions that control the activation of the catalytic reaction and is thus also useful to guide the design of inhibitors.

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

Density Functional Tight-Binding Models for Band Structures of Transition-Metal Alloys and Surfaces across the d -Block

First-principles electronic structure simulations are an invaluable tool for understanding chemical bonding and reactions. While machine-learning models such as interatomic potentials significantly accelerate the exploration of potential energy surfaces, electronic structure information is generally lost. Particularly in the field of heterogeneous catalysis, simulated electron band structures provide fundamental insights into catalytic reactivity. This ab initio knowledge is preserved in semiempirical methods such as density functional tight binding (DFTB), which extend the accessible computational length and time scales beyond first-principles approaches. In this paper here we present Shell-Optimized Atomic Confinement (SOAC) DFTB electronic-part-only parametrizations for bulk and surface band structures of all d-block transition metals that enable efficient predictions of electronic descriptors for large structures or high-throughput studies on complex systems outside the computational reach of density functional theory.

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

Atomic resolution coherent x-ray imaging with physics-based phase retrieval

Coherent x-ray imaging and scattering from accelerator based sources such as synchrotrons continue to impact biology, medicine, technology, and materials science. Many synchrotrons around the world are currently undergoing major upgrades to increase their available coherent x-ray flux by approximately two orders of magnitude. The improvement of synchrotrons may enable imaging of materials in operando at the atomic scale which may revolutionize battery and catalysis technologies. Current algorithms used for phase retrieval in coherent x-ray imaging are based on the projection onto sets method. These traditional iterative phase retrieval methods will become more computationally expensive as they push towards atomic resolution and may struggle to converge. Additionally, these methods do not incorporate physical information that may additionally constrain the solution. In this work, we present an algorithm which incorporates molecular dynamics into Bragg coherent diffraction imaging (BCDI). This algorithm, which we call PRAMMol (Phase Retrieval with Atomic Modeling and Molecular Dynamics) combines statistical techniques with molecular dynamics to solve the phase retrieval problem. We present several examples where our algorithm is applied to simulated coherent diffraction from 3D crystals and show convergence to the correct solution at the atomic scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Institute for Catalysis in Energy Processes (ICEP) (Final Report)

The Institute for Catalysis in Energy Processes (ICEP) was a multi-PI program located at the Northwestern University Center for Catalysis and Surface Science from 2006-2024. Over several renewal cycles and several organizing themes, ICEP addressed fundamental questions in catalysis science. In turn, the scientific questions addressed were directly relevant to the efficient use of the nation’s resources to produce fuels and commodity chemicals, harness alternate energy sources for chemical reactions such as light or electricity, reduce emissions and waste, and minimize the impact of our use of plastics. Selective oxidation, (oxidative) dehydrogenation, deNOx, CO 2 reduction, hydrogen release, polymer decomposition / depolymerization, and many other reactions of intense interest to the US Department of Energy were studied in the center. Major ICEP strengths were in catalyst synthesis, in measurements that elucidated catalyst properties, in reaction mechanisms and kinetics, and in predictive theory and modeling. ICEP researchers were often the inventors or developers of materials and methods that were brought to bear on the Institute’s catalytic systems. Key characterization tools advanced through this project included resonance Raman and related techniques, sum frequency generation, and X-ray standing wave spectroscopy. Center members relied extensively on computational tools such as density functional theory and microkinetic modeling to fully investigate catalyst structures and catalytic mechanisms. ICEP researchers were early developers of atomic layer deposition (ALD) for catalyst synthesis and were early pioneers of metal organic frameworks for catalysis. ICEP innovations are found in areas of intense research such as single-atom catalysts, catalytic deconstruction of plastics, and catalytic MOFs, to name a few. Research areas initiated by ICEP indirectly led to DOE EFRCs, startup companies, and other achievements. Over its 18 years of existence, ICEP involved two different PIs (Stair and Notestein) and 24 senior investigators across several academic disciplines at Northwestern University. There were tight collaborations with Argonne National Laboratory, including specialized equipment and experiments permanently located there. The center supported ~400 person-years of effort by graduate students and postdocs, either directly through DOE support or indirectly by leveraging independent support provided to the trainees, e.g. through the NSF GRFP or internal fellowships. The project resulted in 328 manuscripts and numerous conference presentations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Single-Site Carbon-Supported Metal-Oxo Complexes in Heterogeneous Catalysis: Structure, Reactivity, and Mechanism

When early transition metal complexes are molecularly grafted onto catalyst supports, well-defined, surface-bound species are created, which are highly active and selective single-site heterogeneous catalysts (SSHCs) for diverse chemical transformations. Further, in this minireview, we analyze and summarize a less conventional type of SSHC in which molybdenum dioxo species are grafted onto unusual carbon-unsaturated scaffolds, such as activated carbon, reduced graphene oxide, and carbon nanohorns. The choice of earth-abundant, low-toxicity, versatile metal constituents, and various carbon supports illustrates “catalyst by design” principles and yields insights into new catalytic systems of both academic and technological interest. Here, we summarize experimental and computational investigations of the bonding, electronic structure, reaction scope, and mechanistic pathways of these unusual catalysts.

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

Theoretical Multinary Perovskite Oxides Dataset

Perovskite oxides (ternary chemical formula ABO3) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, the AA'BB'O6 compositions were generated in the a-b+a- Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with DFT using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔHf) and decomposition enthalpies (ΔHd) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated AA'BB'O6 perovskite structures using MP-compatible DFT calculations

Bare, Zachary↗
DOE OSTI2020

Water Structure and Properties at Hydrophilic and Hydrophobic Surfaces

The properties of water on both molecular and macroscopic surfaces critically influence a wide range of physical behaviors, with applications spanning from membrane science to catalysis to protein engineering. Yet, our current understanding of water interfacing molecular and material surfaces is incomplete, in part because measurement of water structure and molecular-scale properties challenges even the most advanced experimental characterization techniques and computational approaches. This review highlights progress in the ongoing development of tools working to answer fundamental questions on the principles that govern the interactions between water and surfaces. One outstanding and critical question is what universal molecular signatures capture the hydrophobicity of different surfaces in an operationally meaningful way, since traditional macroscopic hydrophobicity measures like contact angles fail to capture even basic properties of molecular or extended surfaces with any heterogeneity at the nanometer length scale. Resolving this grand challenge will require close interactions between state-of-the-art experiments, simulations, and theory, spanning research groups and using agreed-upon model systems, to synthesize an integrated knowledge of solvation water structure, dynamics, and thermodynamics.

catalysis (heterogeneous)↗
DOE OSTI2021

Data Science Meets Physical Organic Chemistry

At the heart of synthetic chemistry is the holy grail of predictable catalyst design. In particular, researchers involved in reaction development in asymmetric catalysis have pursued a variety of strategies toward this goal. This is driven by both the pragmatic need to achieve high selectivities and the inability to readily identify why a certain catalyst is effective for a given reaction. While empiricism and intuition have dominated the field of asymmetric catalysis since its inception, enantioselectivity offers a mechanistically rich platform to interrogate catalyst-structure response patterns that explain the performance of a particular catalyst or substrate. In the early stages of an asymmetric reaction development campaign, the overarching mechanism of the reaction, catalyst speciation, the turnover limiting step, and many other details are unknown or posited based on related reactions. Considering the unclear details leading to a successful reaction, initial enantioselectivity data are often used to intuitively guide the ultimate direction of optimization. However, if the conditions of the Curtin-Hammett principle are satisfied, then measured enantioselectivity can be directly connected to the ensemble of diastereomeric transition states (TSs) that lead to the enantiomeric products, and the associated free energy difference between competing TSs (ΔΔ G ‡ = - RT ln[( S )/( R )], where ( S ) and ( R ) represent the concentrations of the enantiomeric products). We, and others, speculated that this important piece of information can be leveraged to guide reaction optimization in a quantitative way. Although traditional linear free energy relationships (LFERs), such as Hammett plots, have been used to illuminate important mechanistic features, we sought to develop data science derived tools to expand the power of LFERs in order to describe complex reactions frequently encountered in modern asymmetric catalysis. Specifically, we investigated whether enantioselectivity data from a reaction can be quantitatively connected to the attributes of reaction components, such as catalyst and substrate structural features, to harness data for asymmetric catalyst design. In this context, we developed a workflow to relate computationally derived features of reaction components to enantioselectivity using data science tools. The mathematical representation of molecules can incorporate many aspects of a transformation, such as molecular features from substrate, product, catalyst, and proposed transition states. Statistical models relating these features to reaction outputs can be used for various tasks, such as performance prediction of untested molecules. Perhaps most importantly, statistical models can guide the generation of mechanistic hypotheses that are embedded within complex patterns of reaction responses. Overall, merging traditional physical organic experiments with statistical modeling techniques creates a feedback loop that enables both evaluation of multiple mechanistic hypotheses and future catalyst design. In this Account, we highlight the evolution and application of this approach in the context of a collaborative program based on chiral phosphoric acid catalysts (CPAs) in asymmetric catalysis.

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

Binding kinetics of harmonically confined random walkers

Diffusion-mediated binding of molecules under the influence of discrete spatially confining potentials is a commonly encountered scenario in systems subjected to explicit fields or implicit fields arising from tethering restraints. Here, in this work, we derive analytical expressions for the mean binding time of two random walkers geometrically confined by means of two harmonic potentials in one- and two-dimensional systems, which show excellent agreement with Brownian dynamics simulations. As a demonstration of its utility, we use this theory to maximize the communication speed in existing DNA walkers, obtaining quantitative agreement with previously reported experimental findings. The analytical expressions derived in this paper are broadly applicable to diverse systems, providing ways to characterize communication processes and optimize the rate of signal propagation for sensing and computing applications at the nanoscale.

36 MATERIALS SCIENCE↗
DOE OSTI2021

DOE Plasma Science Center - Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems (Final Report DE-SC0001939)

Low temperature plasmas (LTPs) are the plasmas of electron-volt (eV) physics and eV technologies. LTPs have characteristic electron temperatures of a few eV and fractional ionizations that are typically small. Since LTPs have electron temperatures commensurate with the threshold energies of excited states in neutral atoms and molecules, power transfer from electrons to these atoms and molecules efficiently produces activated species (e.g., radicals, excited states, photons). Acceleration of ions in the sheaths of LTPs to energies of tens to hundreds of eV enable activation of surface modifying processes – sputtering, etching, deposition. With such properties, LTPs are often and beneficially used in technological devices, ranging from etching and deposition in microelectronics and solar cell fabrication, to hardening of surgical instruments. LTPs harbor fundamental science issues that are intellectually challenging and rewarding. At the same time, there are enormous societal benefits that are enabled by LTPs. The entire present-day and future information technology infrastructure owes its very existence to LTPs. Renewable energy sources, such as solar cell arrays, could not be economically produced in the absence of deposition and etching by LTPs. In acknowledgment of the importance of LTPs, the DOE Office of Fusion Energy Sciences supported the Plasma Science Center for Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems from August 2009 to July 2021, consisting of an initial 5-year grant, 3 funded extensions and 2 no-cost extensions. This is the final report of the Center in which the productivity of the Center is discussed in terms of publications, impact and personnel. High-lights of the research performed in the Center are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Replication Data for: Toward benchmarking theoretical computations of elementary rate constants on catalytic surfaces: formate decomposition on Au and Cu

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

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

Photoinduced Electron and Energy Transfer Pathways and Photocatalytic Mechanisms in Hybrid Plasmonic Photocatalysis

Hybrid plasmonic nanostructures are built on plasmonic metalnanostructures surrounded by catalytic metals or metal oxides. We report that recent studies have shown that hybrid plasmonic nanocatalysts can concurrently utilize thermal energy and photon stimuli and exhibit high catalytic activity, selectivity, and stability that are not attainable in conventional purely thermally activated catalytic processes. The hybrid plasmonic photocatalytic approach has recently emerged as an attractive concept for the conversion of solar energy into chemical energy, the distributed synthesis of valuable chemicals such as ammonia with little to no requirement of external heating, and the development of coke-resistant and selective catalytic processes. The field of hybrid plasmonic photocatalysis has grown tremendously in the last decade. In this review article, the advantages of visible-light-augmented hybrid plasmonic photocatalysis over conventional pure thermally activated heterogeneous catalysis are discussed. Fundamental insights are provided into photocatalytic mechanisms by which the photoexcited charge carriers (electrons and holes) are formed and transferred to adsorbates triggering chemical transformations on the surface of hybrid plasmonic nanocatalysts. Computational modeling used for predicting and understanding the photocatalytic activity and selectivity on hybrid plasmonic nanostructures is also reviewed. The review closes with a discussion of the current challenges, new opportunities, and future outlook for hybrid plasmonic photocatalysis.

36 MATERIALS SCIENCE↗