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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantum Monte Carlo Benchmarking of Molecular Adsorption on Graphene-Supported Single Pt Atom

The precise understanding of adsorption energetics and molecular geometry at catalytic sites is fundamental for advancing catalysis, particularly under the constraints of resource efficiency and environmental sustainability. Here, this study benchmarks the performance of density functional theory (DFT) calculations against diffusion Monte Carlo (DMC) calculations for adsorption properties of small gas molecules relevant to CO oxidation—namely O 2 , CO, CO 2 , and atomic oxygen—on a single Pt atom supported by pristine graphene. Our findings reveal that DMC calculations provide a significantly different landscape of adsorption energetics compared to DFT results. Notably, DFT predicts different lowest-energy configurations and spin states, particularly for O 2 , which suggests potential discrepancies in predicting the catalytic behavior. Furthermore, this study identifies the critical issue of CO poisoning, highlighted by the large disparity between the DMC adsorption energies of O 2 (−1.23(2) eV) and CO (−3.37(1) eV), which can inhibit the catalytic process. These results emphasize the necessity for more sophisticated computational approaches in catalysis research, aiming to refine the prediction accuracy of reaction mechanisms and to enhance the design of more effective catalysts.

Ahn, Jeonghwan [University of Illinois at Urbana-C↗
DOE OSTI2026

Frontiers in divalent $f$-block chemistry

Divalent f-block chemistry has undergone rapid expansion in recent years, driven by advances in the stabilization of low-valent lanthanide and actinide complexes. Although f-elements were historically accessed in the +3 or higher oxidation states, the isolation of +2 species has revealed unusual spectroscopic signatures, distinct bonding motifs, and multiple accessible electronic configurations that influence their chemical and physical properties. These developments have generated opportunities in areas including quantum information science, molecular magnetism, catalysis, and luminescence. Computational chemistry has played a pivotal role in interpreting the electronic structure and reactivity of these systems. However, accurately modeling divalent f-block complexes remains challenging because of strong electronic correlation, multiconfigurational character, and the presence of close-in-energy competing electronic states. As experimental capabilities and theoretical methodologies continue to advance, a comprehensive assessment of divalent chemistry is both timely and needed. In this Review, we integrate experimental and theoretical perspectives to provide a systematic analysis of divalent lanthanide and actinide complexes across the f-block series. We critically assess the role of ligands in determining competing ground-state configurations (f n d 1 vs. f n+1 ) resulting in their distinct spectroscopic, magnetic, and bonding properties. Finally, we discuss emerging strategies for predictive modeling and rational design of low-valent f-block molecular systems, with potential applications ranging from dinitrogen reduction to quantum technologies.

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

Effects of water on the kinetics of acetone hydrogenation over Pt and Ru catalysts

We employed an approach combining reaction kinetics measurements at steady state conditions, electronic structure calculations employing density functional theory, and microkinetic modeling for acetone hydrogenation to provide insights into the effects of water on metal catalyst surfaces for the hydrogenation of oxygenates over a wide range of reaction conditions. Elucidation of the repulsive interactions due to adsorbed water molecules at various reaction conditions provides a basis to formulate rate expressions for heterogeneous catalytic processes of biomass oxygenates. Reaction kinetics experiments were carried out at partial pressures of H 2 , acetone, water and helium in the range of 0.51-0.79, 0.02-0.13, 0.08-0.23, 0-0.28 atm, respectively. We show that the addition of water enhances the hydrogenation rate at 353 K and 1 atm on oxophilic metal catalysts such as Ru/C, whereas the same promotional effect of water is not observed for Pt-based catalysts. Microkinetic model predictions for the hydrogenation of acetone on Ru in the absence and presence of water, using enthalpies and entropies obtained from DFT calculations, were in agreement with the experimentally observed reaction orders and activation barriers. The model shows that a water-assisted hydroxypropyl path is expected to be the favored path on Ru with a rate-determining step of H-OH-mediated hydrogenation of C 3 H 6 OH (i.e., the hydroxypropyl intermediate formed by H 2 O-mediated initial hydrogenation of acetone) to produce isopropyl alcohol (IPA). Furthermore, hydrogen, acetone, hydroxypropyl intermediate and hydroxyl species were predicted to be abundant on the Ru surface with a high coverage of nearly 85%. Lastly, the combined studies of computational and experimental catalysis on hydrogenation reactions help to elucidate the mechanistic role of water on metal catalyzed reactions for producing chemical building blocks from biomass-derived oxygenates.

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

Tuning Optical and Electrical Properties of Vanadium Oxide with Topochemical Reduction and Substitutional Tin

Vanadium oxides are widely tunable materials, with many thermodynamically stable phases suitable for applications spanning catalysis to neuromorphic computing. The stability of vanadium in a range of oxidation states enables mixed-valence polymorphs of kinetically accessible metastable materials. Low-temperature synthetic routes to, and the properties of, these metastable materials are poorly understood and may unlock new optoelectronic and magnetic functionalities for expanded applications. In this work, we demonstrate topochemical reduction of α-V 2 O 5 to produce metastable vanadium oxide phases with tunable oxygen vacancies (>6%) and simultaneous substitutional tin incorporation (>3.5%). The chemistry is carried out at low temperature (65 °C) with solution-phase SnCl 2 , where Sn 2+ is oxidized to Sn 4+ as V 5+ sites are reduced to V 4+ during oxygen vacancy formation. Despite high oxygen vacancy and tin concentrations, the transformations are topochemical in that the symmetry of the parent crystal remains intact, although the unit cell expands. Band structure calculations show that these vacancies contribute electrons to the lattice, whereas substitutional tin contributes holes, yielding a compensation doping effect and control over the electronic properties. The SnCl 2 redox chemistry is effective on both solution-processed V 2 O 5 nanoparticle inks and mesoporous films cast from untreated inks, enabling versatile routes toward functional films with tunable optical and electronic properties. The electrical conductance rises concomitantly with the SnCl 2 concentration and treatment time, indicating a net increase in density of free electrons in the host lattice. This work provides a valuable demonstration of kinetic tailoring of electronic properties of vanadium–oxygen systems through top-down chemical manipulation from known thermodynamic phases.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride

Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. Finally, the application of the workflow to zinc telluride, a promising CO 2 reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.

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

Diffusion Model-Guided Inverse Design of Bimetallic Catalysts for Ammonia Decomposition

In the past decade, artificial intelligence and deep learning have played increasingly prominent roles in materials design and discovery. Among these, generative AI models, known for their ability to create unique and complex structures, have emerged as state-of-the-art tools for materials screening due to their high efficiency and low computational cost. In catalysis, one of the major challenges is identifying promising material candidates within an immense chemical space. This challenge can be addressed using generative approaches, such as diffusion-based inverse design models. In this study, we present a machine learning-guided workflow that employed a diffusion model for the inverse design of bimetallic alloy catalysts for low-carbon ammonia decomposition, a key reaction for ammonia emission control and sustainable hydrogen production. Catalyst candidates were evaluated using nitrogen adsorption energy as the key descriptor, inspired by multiscale modeling. The proposed workflow identified low-cost, environmentally friendly catalysts with excellent catalytic performance, which have been validated theoretically and experimentally. Our framework decoupled the generative and property-prediction components, enhancing both flexibility and accuracy in the catalytic material design process.

Adsorption↗
DOE OSTI2022

Computational methods in unraveling the mechanism of metallaphotoredox catalysis

Moving from Guangzhou, China to Maryland, USA in 2017 to pursue a Ph.D. in chemistry was terrifying and exciting at the same time. However, it didn’t take me long to commit to working with a young assistant professor. As an undergraduate, I spent countless hours doing the “wet lab” research on green catalysis, where I developed a strong interest in organometallic catalysis and in using mechanistic-driven approach towards the rational design of novel catalytic systems. Not surprisingly, during the group rotation in my first semester in University of Maryland, the research focus and, in particular, the friendly group atmosphere led to my decision to join the research group of Dr. Osvaldo Gutierrez, who was just starting his 2nd year as an assistant professor.

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

Environmental and Energy Research at the Texas Center for Advanced Scientific Computing and Modeling (CASCaM)

The funding enabled the creation of the (University of North) Texas Center for Advanced Scientific Computing and Modeling (CASCaM). Due to its success, CASCaM has continued to grow beyond the initial team focused on the biological and environmental research discussed herein, with investments by the University of North Texas in new faculty and researchers who contribute to CASCaM research. CASCaM is now a sustainable effort, with researchers across multiple fields including chemistry, physics, biology, mechanical engineering, materials science, and other fields, with multiple researchers engaged in a broad variety of research, including other DOE projects. Over 20 PI’s and ~100 researchers are engaged in CASCaM research. The overall goal of the research effort was to provide greater understanding about carbon capture, storage, and utilization. As part of this effort, the development of computational methods and identification of novel strategies to support the CO2 and CO studies were necessary. Three primary themes were investigated: carbon dioxide and CO catalysis; protein- and amino acid-based strategies towards carbon dioxide capture, storage, and utilization; and, finally, the methodology improvements for modeling carbon dioxide chemistry

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Accelerating catalytic advancements through the precision of high-throughput experiments & calculations

The growing demand for energy-efficient processes to support a sustainable future drives the need for research to rapidly explore chemical and material space through accelerated catalyst discovery initiatives. Recent breakthroughs in high-throughput experimental and computational methods are transforming the catalysis field, surpassing traditional approaches to manipulating variables in catalytic processes. Key advancements in innovation include the integration of machine learning for efficient catalyst screening, high-throughput experimentation, data-driven methodologies employing comprehensive databases, and in situ and in operando techniques for realistic observations. This progress has undoubtedly been intertwined with a collaborative framework across disciplines, reshaping catalyst discovery methods in both industry and academia. This Opinion article presents a multifaceted perspective from coauthors with expertise spanning various stages of the Technology Readiness Level spectrum, highlighting both opportunities and persistent challenges in integrating computational and experimental approaches in catalysis. These challenges span from obtaining high-quality experimental data, scaling simulations to industrially relevant materials and process conditions to navigating the complexity and predictive accuracy of computational models.

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

Nanocluster Active Sites Formed on Heterogeneous Thermal Catalysts and Electrocatalysts by Operando Reactive Environments

Here, in this Viewpoint, we summarize our recent studies in this endeavor, ending with a forward-looking perspective into the remaining challenges and open questions for consideration by the catalysis community. Through a computationally efficient framework of systematically investigating metal atom ejection from and migration onto metal surfaces, leading to the formation of metal atom clusters, we show that the surface of a metal catalyst is dynamic and much less rigid than previously thought. We suggest that the operando formed metal atom clusters are novel active sites, which can dominate the activity of steps or kinks (let aside terraces) from where their constituent atoms were ejected. Through more readily responding to reaction conditions by forming catalytically active clusters, solid metal catalysts approach not only homogeneous catalyst motifs, thus establishing a bridge between homogeneous and heterogeneous catalysis, but also liquid metals which have been suggested to be better than traditional heterogeneous catalysts.

adsorption↗
DOE OSTI2023

High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation

Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases. All calculations are carried out in a cloud environment and support massive computational campaigns. Key features of all components of the AutoRXN workflow are autonomy, stability, and minimum operator interference. We highlight the AutoRXN workflow with the example of an autonomous reaction mechanism exploration of the mode of action of a homogeneous catalyst for the asymmetric reduction of ketones.

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

Chemical transformations and transport phenomena at interfaces

Abstract Interfaces, the boundary that separates two or more chemical compositions and/or phases of matter, alters basic chemical and physical properties including the thermodynamics of selectivity, transition states, and pathways of chemical reactions, nucleation events and phase growth, and kinetic barriers and mechanisms for mass transport and heat transport. While progress has been made in advancing more interface‐sensitive experimental approaches, their interpretation requires new theoretical methods and models that in turn can further elaborate on the microscopic physics that make interfacial chemistry so unique compared to the bulk phase. In this review, we describe some of the most recent theoretical efforts in modeling interfaces, and what has been learned about the transport and chemical transformations that occur at the air–liquid and solid–liquid interfaces. This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Structure and Mechanism > Computational Materials Science Software > Quantum Chemistry Software > Simulation Methods

Hao, Hongxia↗
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 OSTI2026

Mechanistic Studies of an Iron-Catalyzed Intermolecular C–H Amination Reaction under Catalytic Conditions and Having a Large KIE

The conversion of C–H bonds into amines by nitrene insertion is an attractive transformation since it is both atom- and step-economical, and provides a direct route to functionalizing hydrocarbons. Using an iron catalyst [{( tBu pyrr) 2 pyr}Fe(OEt 2 )] (1-OEt 2 ) (( tBu pyrr) 2 pyr 2– = 3,5- t Bu 2 -bis(pyrrolyl)pyridine), we recently demonstrated the catalytic conversion of weak C–H bonds into secondary amines using aryl azides as the nitrene source [Zars, E.; Angew. Chem., Int. Ed. 2023, 62, e202311749]. Here, we describe detailed mechanistic studies of this intermolecular C–H amination reaction under catalytic conditions. We find by Variable Time Normalization Analysis (VTNA) that the conversion of xanthene (2-H 2 ) and 2,4,6-trimethyl-phenyl azide ( Me 3) catalyzed by 1-OEt 2 is an overall 3/2 order process, being 1 st order in 2-H 2 and half order in Me 3. A kinetic isotope effect study (KIE) using 2-d 2 results in a significant decrease in the rate (KIE = 61(15)), which clearly implicates the C–H insertion step as rate-determining. Furthermore, treatment of 1-OEt 2 with one equivalent of N 3 -2,6- i Pr 2 –C 6 H 3 yields the mixed-valence C–N coupled product [( tBu pyrr) 2 pyrFe-N═C(2,6 i Pr 2 –Ph)═N-(2,6 i Pr 2 –Ph))Fe tBu pyrrpyr(2-H-pyrr)] (5 iPr ). Quantum chemical calculations confirm the electronic structure of the mixed-valence dimer in 5 iPr and rationalize the Hammett correlation by a delicate balance in the dinuclearization of the catalytically active monomers. Calculations further indicate significant tunneling for the pivotal H atom abstraction by the iron-imidyl complex. Combining all these results allows us to propose a mechanism consisting of imido formation in equilibrium with a radical-coupled diiron system, followed by stepwise C–H insertion via a linear H atom abstraction transition state and subsequent radical rebound.

azides↗
DOE OSTI2025

Nature of molybdenum carbide surfaces for catalytic hydrogen dissociation using machine-learned potentials: an ensemble-averaged perspective

Molybdenum carbides with an electronic structure similar to noble metals have gained attention as a promising low-cost catalyst for biomass valorization and the hydrogen evolution reaction. However, our fundamental understanding of the catalyst surface and how different phases of these catalysts behave at varying reaction conditions is limited to ground state density functional theory calculations as ab initio molecular dynamics (AIMD) is computationally prohibitive at relevant length and time scales. Here, in this work, we train a multi-atomic cluster expansion (MACE) machine-learned interatomic potentials (MLIP) to study hydrogen dissociation and dynamics over Mo, δ-MoC, α-Mo 2 C, and β-Mo 2 C surfaces at varying temperatures and hydrogen partial pressures. Our simulations identify unique and different molecular and atomic hydrogen adsorption sites on different surfaces that do not depend on the temperature. At low hydrogen pressures, the surface coverage is monolayer, which transitions to two-layer adsorption at higher pressures. We find that atomic hydrogen diffusion and recombinations are preferred over molybdenum atom hollow sites, while the diffusion over carbon-terminated facets was negligible, signifying particularly strong C–H interactions. In contrast, molecular hydrogen adsorption occurs mostly atop Mo or the bridging sites. At a comparable hydrogen loading, β-Mo 2 C (001) is the most active surface for hydrogen dissociation reaction. This work provides insights into the dynamic nature of the hydrogen dissociation chemistry and the diversity of hydrogen adsorption sites on molybdenum carbides.

08 HYDROGEN↗