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DOE OSTI2025

Revisiting the assignment of atomic charges in metal oxides based on core-level x-ray photoelectron spectra: The case of Ti in SrTiO3(001)

We demonstrate that assigning formal charges to transition metal (TM) cations based on core-level (CL) x-ray photoemission binding energies in oxides leads to physically inconsistent pictures of electronic structure. O 2p–TM 3d hybridization is well known to result in significant covalency in TM–O bonds, thereby reducing TM cation charges from their fully ionic values. However, the ionic bonding model remains the working paradigm for assigning TM CL features, and the resulting cation charges are often taken to be representative of the material under study. Here, we show that a more physically meaningful way to assign charges is to extract information about charge distributions utilizing Dirac–Hartree–Fock theory to calculate CL spectra from first principles and then use the resulting wave functions to determine charges based on orbital occupancies. TM cation charges can also be determined using density functional theory and Bader population analysis. We illustrate these two methods using the Ti 2p spectrum for SrTiO3(001) and show that the agreement between them is excellent. Significantly, the resulting Ti charge is considerably lower than the formal charge. The high degree of similarity between the Ti 2p spectrum for SrTiO3 and those for the rutile and anatase polymorphs of TiO2 suggests that the charge densities surrounding Ti in the latter materials are similar to that in SrTiO3. Taking a broader perspective, oxides containing other first-row transition metals also exhibit covalent character, leading to TM cation charges lower than the analogous fully ionic values in these materials as well.

Chambers, Scott A. (ORCID:000000025415043X)↗

DOE OSTI2021

High Resolution Infrared Spectroscopy of Highly Reactive Chemical Intermediates: Berkeley Inspiration and a C.B. Moore Retrospective

One of the long-standing paradoxes in chemistry is that the molecular species of greatest interest are often highly reactive chemical intermediates and thus present only at vanishingly small concentrations under typical steady state conditions. Here, this has proven both a key frustration and powerful motivation for physical chemists in probing such species, particularly for high resolution laser spectroscopic methods in the infrared. Over the past 4-5 decades, this fundamental sensitivity challenge has stimulated the development of many novel techniques for efficient generation, cooling, and infrared probing of such transient chemical intermediates, achieving increasingly sophisticated levels of spectroscopic detail, chemical insight, and a testbed for comparison with first principles ab initio quantum calculations. Two of the pioneering contributors to this scientific arena have been George Pimentel and C. Bradley Moore, both responsible for nourishing DJN’s own enduring fascination with spectroscopic IR study of elusive chemical intermediates. This chapter is not intended to provide a comprehensive review of this large and enormously successful field, but it rather more simply attempts to capture a few selective “Moore-centric” snapshots of the Nesbitt group scientific evolution, specifically in i) advances by Pimentel for the original development of rapid scan flash kinetic spectroscopy based on spectrometers with rapidly rotating IR gratings, ii) the modernization/extension of these methods in the Moore group toward the first high resolution IR laser spectroscopy of singlet/triplet methylene 1,3 CH 2 diradical, and finally to iii) the development of slit supersonic discharge expansion methods at JILA for sub-Doppler infrared laser study of multiple radicals, jet cooled molecular ions, and highly reactive chemical intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Roles of Carburization and Oxidation on Transition-Metal Catalyzed Surface Reactions

Many industrial chemical transformation processes are based on reactions catalyzed by transition metals. In some cases the nano-size particles used as catalysts are synthesized simultaneously or right before the initiation of the main catalytic reaction. Synthesis treatments involve complex processes such as reductions followed by calcinations in oxygenated environments coupled to the presence of gases used for the main reaction. Synthesis details are crucial because they have important consequences on the catalyst shape, size, and chemical composition, and may also affect the structure and composition of the catalyst support. All these effects may alter the main catalyzed reaction in unexpected ways. This work focuses on the synthesis of the overall catalytic system that includes catalyst and support taking place in parallel with the initial stages of the main catalyzed reaction. Two important processes are characterized: carburization and oxidation of the transition metal catalyst during synthesis or initial stages of the main reaction. The objective is to understand how the coking mechanism coupled to surface oxidation and changes in the substrate influence the dry reforming of methane taken as a model reaction. The approach uses first principles computational methods to investigate the catalyst synthesis and characterization and catalytic reaction mechanisms. These studies are complemented with experimental characterization done by the group of Dr. Renu Sharma at the National Institute of Standards and Technology (unfunded collaborator) using high resolution transmission electron microscopy. Specific goals are to identify the role of the synthesis process on the initial nanocatalyst structure and composition, and to determine how that structure and composition may evolve after being exposed to the reactants atmosphere. These studies facilitate a systematic analysis of conditions where the nanoparticle composition can be optimized regarding activity and stability. Moreover, the fundamental study of catalyst/support interactions yields valuable insights for other catalytic processes and is a first step toward controlled nanocatalyst synthesis.

36 MATERIALS SCIENCE↗

NASA NTRS2015

The Importance of the Cathode Plume and Its Interactions with the Ion Beam in Numerical Simulations of Hall Thrusters

Hall2De is a first-principles, 2-D axisymmetric code that solves the equations of motion for ions, electrons, and neutrals on a magnetic-field-aligned grid. The computational domain downstream of the acceleration channel exit plane is large enough to include self-consistently the cathode boundary. In this paper, we present results from numerical simulations of the H6 laboratory thruster with an internally mounted cathode, with the aim of highlighting the importance of properly accounting for the interactions between the ion beam and cathode plume. The anomalous transport of electrons across magnetic field lines in Hall2De is modelled using an anomalous collision frequency, νanom, yielding νanom approximately equal to omega ce (i.e., the electron cyclotron frequency) in the plume. We first show that restricting the anomalous collision frequency to only regions where the current density of ions is large does not alter the plasma discharge in the Hall thruster as long as the interaction between the ion beam and the cathode plume is captured properly in the computational domain. This implies that the boundary conditions must be placed sufficiently far as to not interfere with the electron transport in this region. These simulation results suggest that electron transport across magnetic field lines occurs largely inside the beam and may be driven by the interactions between beam ions and electrons. A second finding that puts in relevance the importance of including the cathode plume in numerical simulations is on the significance of accounting for the ion acoustic turbulence (IAT), now known to occur in the vicinity of the cathode exit. We have included in the Hall2De simulations a model of the IAT-driven anomalous collision frequency based on Sagdeev's model for saturation of the ion-acoustic instability. This implementation has allowed us to achieve excellent agreement with experimental measurements in the near plume obtained during the operation of the H6 thruster at nominal conditions (300V, 20A) and chamber background pressure of approximately 1.5 x 10(exp -5) Torr. In addition, the numerical results obtained with the latter approach exhibit less sensitivity to background pressure than previous attempts at explaining the features of the plasma properties in the near plume.

Lopez Ortega, Alejandro↗

DOE OSTI2024

Next-Generation Materials Design: Quantum Mechanics and Data-Driven Modeling

The future of materials design is rapidly advancing through the combination of quantum mechanics and data-driven modeling. These approaches integrate quantum principles with advanced data analysis, enabling precise insights into material behavior. This talk will highlight recent progress in using these methods for computational design, particularly in high-entropy alloy catalysts, emphasizing the role of hierarchical machine-learning architectures for accurate predictions. Additionally, I will discuss our work on developing machine learning interatomic potentials (MLPs) for single-element metals, metal oxides, and alloys under extreme conditions, focusing on melting behavior and phase properties at high temperatures and pressures. We have also refined our MLP models to capture dynamic surface interactions, such as CO2 and CO adsorption on MgO, using both static and molecular dynamics simulations. These models maintain high accuracy while significantly reducing computational costs compared to first-principles calculations. By enabling efficient and accurate simulations, this work supports broader community adoption, optimizes datasets for materials discovery, and extends the accessible time, size, and environmental conditions beyond the limits of experiments and traditional simulations.

machine learning↗

DOE OSTI2026

Correlation-aware binning for small-angle neutron scattering via Gaussian-process inference

Binning in small-angle neutron scattering (SANS) is typically performed empirically, with fixed parameters chosen for convenience rather than statistical optimality. Such practices often fail to balance statistical precision and spatial resolution, leading to inconsistencies across instruments and datasets. Here we establish a correlation-aware framework that determines the optimal bin width from first principles by extending the classical Freedman–Diaconis (FD) rule to account for inter-bin correlations with a Gaussian process. In this formulation, the scattering intensity is treated as a smooth stochastic field whose statistical coherence is described by a covariance matrix. Analytical expressions of errors derived from this model yield closed-form criteria that separate the total deviation into contributions from counting noise, aliasing distortion and curvature-dependent correlation effects. Expressed in reduced variables, the resulting dimensionless error surface reveals a continuous transition from the uncorrelated FD regime to the correlation-dominated limit, providing a unified description of noise suppression and resolution control. Because the formulation depends only on the profile characteristics of scattering intensity I(Q), specifically its average intensity and first- and second-order derivatives, it applies generally to any SANS measurement regardless of sample, instrument or geometry. Experimental validation using small- and ultra-small-angle neutron scattering data confirms the predicted scaling behavior, demonstrating that correlation-aware inference systematically reduces mean-squared error and enables information-efficient reproducible data reduction across materials and instruments.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗

DOE OSTI2024

Exploring dielectric properties in atomistic models of amorphous boron nitride

Abstract We report a theoretical study of dielectric properties of models of amorphous Boron Nitride, using interatomic potentials generated by machine learning. We first perform first-principles simulations on small (about 100 atoms in the periodic cell) sample sizes to explore the emergence of mid-gap states and its correlation with structural features. Next, by using a simplified tight-binding electronic model, we analyse the dielectric functions for complex three dimensional models (containing about 10.000 atoms) embedding varying concentrations of sp 1 , sp 2 and sp 3 bonds between B and N atoms. Within the limits of these methodologies, the resulting value of the zero-frequency dielectric constant is shown to be influenced by the population density of such mid-gap states and their localization characteristics. We observe nontrivial correlations between the structure-induced electronic fluctuations and the resulting dielectric constant values. Our findings are however just a first step in the quest of accessing fully accurate dielectric properties of as-grown amorphous BN of relevance for interconnect technologies and beyond.

Materials Science↗

DOE OSTI2023

Modeling Short-Range Order in Disordered Rocksalt Cathodes by Pair Distribution Function Analysis

Pair distribution function (PDF) analysis is a powerful technique for the characterization of short-range order (SRO) in disordered materials. Accurate interpretation of experimental PDF data is critically reliant on the development of structural models that can account for local variations in site occupancies and bond lengths. To this end, we outline an approach to model SRO using first-principles calculations based on the cluster-expansion formalism. These methods are validated on neutron scattering data from two disordered rocksalt oxyfluorides, Li 1.3 Mn 0.4 Ti 0.3 O 1.7 F 0.3 and Li 1.3 Mn 0.4 Nb 0.2 Ti 0.1 O 1.7 F 0.3 . For each composition, we demonstrate that an average structure without any SRO fails to reproduce several key features in the experimental PDF. To pinpoint the origin of the suspected SRO in these materials, configurational and displacive effects were separately investigated using two disparate models. Special quasi-random structures were relaxed using density functional theory to account for local changes in bond lengths while maintaining a near-random ionic configuration. This leads to slightly improved accuracy but still misrepresents asymmetry in the first few peaks of the PDF. Monte Carlo simulations were performed to model configurational SRO on a fixed lattice, which by itself is shown to have a minimal influence on the PDF. Instead, we find that it is the bond length relaxations within environments created by SRO which controls the details of the PDF, thereby highlighting the subtle but important coupling between configurational and displacive SRO in disordered materials.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Perpendicular magnetic anisotropy in half-metallic thin-film Co 2 CrAl

Magnetocrystalline anisotropy (MCA) is one of the key parameters investigated in spin-based electronics (spintronics), e.g. for memory applications. Here, we employ first-principles calculations to study MCA in thin film full Heusler alloy Co 2 CrAl. This material was studied in the past, and has been reported to exhibit half-metallic electronic structure in bulk geometry. In our recent work, we showed that it retains a 100% spin-polarization in thin-film geometry, at CrAl atomic surface termination. Here, we show that the same termination results in a perpendicular magnetic anisotropy, while Co surface termination not only destroys the half-metallicity, but also results in in-plane magnetization orientation. In addition, for films thicker than around 20 nm the contribution from magnetic shape anisotropy may become decisive, resulting in in-plane magnetization orientation. To the best of our knowledge, this is one of the first reports of half-metallic thin-film surfaces with perpendicular magnetic anisotropy. Furthermore, this result may be of interest for potential nano-device applications, and may stimulate a further experimental study of this and similar materials.

36 MATERIALS SCIENCE↗

DOE OSTI2019

A Review on Lignin Liquefaction: Advanced Characterization of Structure and Microkinetic Modeling

Lignin liquefaction microkinetics is a move toward a more first principles (i.e., ab initio) based understanding at the molecular level in reaction engineering. While the microkinetic modelling of reactions to obtain kinetic rate parameters of chemical reactions have been widely used in the field of gas phase combustion and heterogeneous catalysis, this approach has not been as thoroughly developed in the area of biomass thermochemical reactions (e.g., lignin pyrolysis, hydrothermal liquefaction). The difficulties in establishing the structure of complex heterogeneous materials, like lignin, is perhaps the main challenge in developing rational microkinetic descriptions of biomass thermochemical reactions. In this manuscript we review the current state of the art and the challenges to develop microkinetic models for lignin liquefaction technologies (e.g., pyrolysis, hydrothermal liquefaction, solvolysis). A general strategy for the development of microkinetic models for lignin liquefaction technologies is discussed. Here, the first hurdle is to obtain sufficiently rich experimental data of lignin underlying polymeric structure and methodologies to use this data to build realistic lignin structural representations. Some analytical techniques for lignin structural characterization and their associated data, as well as a correlation for calculating the degree of macromolecular lignin branching are discussed. The presence of small lignin oligomeric structures and the role of these structures in lignin pyrolysis is also addressed. The ways in which elementary deconstruction and repolymerization reactions occur within this structure to form a liquid intermediate, and how these deconstruction products continue to interact with each other until they are removed from the liquid intermediate is thoroughly discussed. Further, experimental work with model compounds and the effect of reaction parameters (e.g., temperature, pressure, vapor residence time) are reviewed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗

DOE OSTI2022

Path Integral Monte Carlo Simulations of Iron Plasmas (Final Technical Report)

This documents is the final technical report for our grant entitled "Path Integral Monte Carlo Simulations of Iron Plasmas" that focused on developing path integral Monte Carlo (PIMC) computer simulations. This techniques will be developed to study plasmas composed of heavier elements including iron and other third row elements. Equations of state (EOS) and transport properties will be derived in the regime of warm dense matter (WDM) and dense plasmas where existing first-principles methods cannot be applied. While standard density functional theory (DFT) has been used to accurately predict the structure of many solids and liquids up to temperatures on the order of 100,000 K, this method is not applicable at much higher temperature because the number of partially occupied electronic orbitals reaches intractably large numbers or the use of finite-temperature free energy functionals in orbital-free DFT introduces an uncontrolled approximation. Here we focus on PIMC methods that become more and more efficient with increasing temperatures and still include all electronic correlation effects. In this approach, electronic excitations increase the efficiency rather than reduce it. While it had commonly been assumed this method could only be applied to elements without core electrons, we showed that PIMC with free-particle nodes works well for first-row elements (PRL 108 (2012) 115502). Most recently, we extended the applicability range of all-electron PIMC to second-row elements by adopting localized nodal surfaces (PRL 115 (2015) 176403). To simulate third-row elements efficiently under WDM conditions, we propose a new method to remove core electrons by introducing pseudo-nodes. We explain our approach step by step and present preliminary results. We focus our method development on getting PIMC simulations of iron to work because of its fundamental importance for WDM and astrophysics. Then we move on to krypton and copper-doped beryllium, a ICF ablator material. We plan to continue working on key second-row material such as Na, Mg, MgO, Al, silica, and silicon-doped plastic ablators. Our collaborators at LLNL, will use our PIMC EOS data both as comparisons to existing semi-empirical, EOS-generating schemes, and as input for continuum radiation hydrodynamics simulations. We will establish an efficient pipeline from PIMC to macroscopic continuum studies of materials response. An emphasis will be placed on benchmarking such methods for plasmas of heavy elements at the very high temperatures (~100 eV) and low densities that are generated when Hohlraum radiation heats the ablator material in indirect drive laser experiments. Results from changes to the EOS will be of immeasurable importance to the designers at the National Ignition Facility (NIF) and at other facilities. Starting with our EOS of Cu-doped Be, our second collaborator at LLE, will perform real-time simulations of laser fusion experiments at the Omega laser and at the NIF to determine how sensitive the compression path depends on the ablator EOS. Since our collaborator also has experience in performing orbital-free DFT calculations, we propose to compare predictions from this method with PIMC results. In joint publications, we plan to analyze the accuracy of different free-energy functionals in order to understand why existing orbital-free DFT calculations do not predict compression peaks along the shock Hugoniot curve that we see with PIMC. The peaks are caused by the ionization of various electron shells. Their accurate characterization is important to compare with experimental results. We will break new ground by developing PIMC techniques that can simulate iron and all other third row elements in the plasma and WDM regimes. We introduce the concept of pseudo-nodes for the efficient treatment of the core-electrons. The EOS and transport properties will be derived and published online in the form of a new WDM database. Our PIMC EOS calculations will benchmark and possibly replace semi-analytical EOS tables like QEOS or SESAME, which will impact the hydrocode simulation community and will affect the design of NIF targets. Our PIMC results will help to improve the accuracy of orbital-free DFT simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Excitons in Hematite Fe 2 O 3 : Short-Time Dynamics from TD-DFT and Non-Adiabatic Dynamics Theories

We present a first-principles study of the short-time dynamics of excitons in hematite Fe 2 O 3 . We used time-dependent density functional theory (TD-DFT) with an underlying DFT+U treatment of electron interactions to characterize the electronic structure of excitons and nonadiabatic molecular dynamics theory (NA-MD) to determine their recombination (electronic ground-state recovery) and relaxation dynamics. Decoherence-corrected trajectory surface hopping approaches in NA-MD simulations yielded recovery times of ~1.1 to 1.8 ns and “higher-lying” exciton relaxation times of ~60 to 70 fs, in accord with experimentally derived lifetimes. With hematite phonons in the range of ~100 to 700 cm –1 , higher-lying excitons relax within one or two oscillations of the phonons before getting trapped into an electron–hole pair Exc-3 structure on the first excited state potential energy surface. This structure resembles already a pair of polarons (electron polaron plus hole polaron) with associated lattice distortions three (3) basal planes away. On longer time scales, the electron–hole bipolaronic pair hops to structures Exc-5, then Exc-7, then Exc-9, ... with the electron polaron and hole polaron separated by 5, 7, 9, ... basal planes in a process of charge separation. The largest frequency phonon ~672 cm –1 for the Exc-3 exciton structure is associated with the electron polaron moiety of the exciton. This phonon is a good candidate for giving rise to the recently observed and reported postexcitation transient IR absorption peak.

36 MATERIALS SCIENCE↗

DOE OSTI2025

NEXAFS Spectroscopy of P3HT and PBTTT at the Sulfur K-Edge

The sulfur K-edge near-edge X-ray absorption fine-structure (NEXAFS) spectra of the common conjugated polymers P3HT and PBTTT are studied from both experimental and theoretical perspectives. Experimental angle-resolved spectra are measured to characterize both the dominant peaks and the dichroism of the polymers. First-principles calculations using the density functional theory-based many-body X-ray absorption spectroscopy (MBXAS) method are performed for the two polymers as well as for the thiophene and thienothiophene units that make up the conjugated backbones of these polymers. Through this combined approach, we are able to confidently assign the observed peaks to specific molecular orbitals and identify the orientation of their transition dipole moments (TDMs) with respect to the coordinate frame of the polymer backbone. Here, in particular, we are able to establish the character and orthogonal nature of the three main low-energy peaks at: (i) 2473.5 eV, 1s → (S–C)π* with TDM along the π-stacking direction; (ii) 2474.1 eV, 1s → (S–C)σ* with TDM along the backbone; and (iii) 2475.4 eV, 1s → (S–C)σ* with TDM perpendicular to the first two. By performing both gas-phase and solid-state simulations, and with reference to the NEXAFS spectra of thiophene and thienothiophene building blocks, the influences of polymerization and molecular packing are also explored.

Chantler, Paul Alexander [Monash University, Clayt↗

NASA NTRS1998

Transition in Turbine Flows

We have further developed our capabilities to analyze transition in turbine boundary layers from first principles by integrating the nonlinear parabolized stability equations (PSE) with improved initial and boundary conditions. With modified iteration schemes, we are able to proceed deeper into the transition region where skin friction coefficient and heat transfer coefficient significantly increase. Initial and boundary conditions at elevated turbulence levels can be derived by receptivity analysis. Test runs for ERCOFTAC test case T3A at 2.4\% turbulence level provide results in good agreement with the experimental data. The sharper minimum of the skin coefficient also shown by DNS results is likely due to the missing intermittency. The method has been applied to various experimentally studied turbine blades (UTRC, VKI, Zierke, Langston, Hippensteele, and others). The PSE results, though physically reasonable, do not agree as well as expected with the experimental findings. We have, therefore, performed an extensive search for the reasons of the seemingly systematic deviations. A first source of uncertainty has been found in the often insufficient documentation of the experiments (e.g. on blockage by end-wall boundary layers). However, variation of the relevant parameters does not lead to more satisfactory agreement. A second reason has been found in the "standard procedure" which considers a 2D flow at midspan and uses a panel code and subsequent boundary-layer code to obtain the laminar basic flow for the transition analysis. Comparison with the pressure distribution obtained with a 3D design code (RVC3D) shows significant three-dimensionality of the flow (e.g. in the UTRC experiments). The spanwise variation has been neglected in our original PSE code. To overcome this problem, we have developed the PSE/3D for fully 3D boundary layers to account for streamwise and spanwise variations. Since the design code does not provide the boundary-layer flow with sufficient resolution, we have generated the Euler solution and employed a 3D boundary-layer code to obtain the viscous basic flow. Although only the linear stability level of PSE/3D has been implemented so far, the discrepancies with the experiments change but do not disappear. We still find deviations between the computed and experimental variations of C(sub f), and St along the blade for laminar flow. The main reason can be seen by comparing the solution of the boundary-layer code with the viscous results of the design code. The conventional boundary-layer solution exhibits an asymptotic behavior appropriate in external aerodynamics but does not match the steep gradients of the inviscid flow through the passage and consequently provides biased results for C(sub f), and St. An attempt is currently being made to correct this deficiency. Before attempting to perform the transition analysis for the viscous flow provided by the design code, we have analyzed the implementation and "best possible" results. Code and results exhibit flaws that may negatively affect the design and are intolerable for transition analysis. Therefore, we have decided to develop a new code to obtain a reliable basis for stability and transition studies. We expect to report improved results by the time of the meeting.

Herbert, Thorwald↗

DOE OSTI2025

Topological perturbation to a standard dehydrogenation catalyst, Pt 3 Sn

Topological materials, which exhibit protected topological surface states (TSS) near the Fermi level, have been proposed to be good catalysts. Topological catalysis may be more prevalent than we suspect, and not limited to exotic new materials. Here we study a known dehydrogenation catalyst, Pt 3 Sn alloy, which happens to be a topological semimetal, and probe the participation of TSSs in catalytic dehydrogenation of methane catalyzed by this material. Through first principle modeling and detailed analysis of the electronic structure for topological and non-topological surfaces of Pt 3 Sn, we find that TSS get significantly altered by the binding of reaction intermediates, particularly H. However, this effect of TSS on the binding of the reagents is merely perturbative, as the majority of the adsorbate binding is achieved by not-surface-focused electronic states, located much deeper below the Fermi level. Therefore, the reaction energetics and selectivity are predominantly determined by electronic states other than TSS. The fact that TSS are available for the reagent binding does not alone guarantee that the catalysis is strongly driven by TSS. However, TSS are not to be ignored, as small changes in the energetics along the reaction profile can translate into substantial differences in the reaction rate. Hence, in our view, Pt 3 Sn – a topological material – is first and foremost a standard catalyst, with added topological features, and not purely a topological catalyst. Our results point at the need to carefully consider all the bonding effects at the topological material interface.

Chemistry↗

DOE OSTI2024

Quantum surrogate models for uncertainty quantification

Surrogate models are a critical ingredient to computation-based design and validation of many DOE mission-relevant physical systems. When first-principles computation of properties of a physical systems becomes pro hibitive, surrogate models are the only path towards achieving tasks such as uncertainty quantification (UQ), exploration of design space, and validation of design choices. In this project we have developed and demonstrated a new surro gate modeling paradigm for complex models that is data-driven, non-intrusive, and has the potential to be versatile and equipped with performance guaran tees. This combination of features is absent in existing surrogate modeling tools. The framework we have developed in this project exploits a quantum-classical correspondence to establish a quantum system that mimics the dynamics of the classical Hamiltonian system from which data in the form of temporal snapshots is provided. Since quantum dynamics propagates distributions over observables, the framework is naturally suited to propagation of epistemic uncertainties in the form of distributions over initial state and parametric uncertainties. In this project, we take the first step in establishing this novel framework by deriving a quantization and de-quantization procedure, demonstrating the accuracy of the quantum surrogate models these define using two model systems, and defining the next steps in maturing the framework towards a tool applicable to Sandia mission-relevant problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Finite-Temperature Structures of Supported Subnanometer Catalysts Inferred via Statistical Learning and Genetic Algorithm-Based Optimization

Single-atom catalysts (SACs) minimize noble metal utilization and can alter the activity and selectivity of supported metal nanoparticles. However, the morphology of active centers, including single atoms and subnanometer clusters of a few atoms, remains elusive due to experimental challenges. The computational cost to describe numerous cluster shapes and sizes makes direct first-principles calculations impractical. We present a computational framework to enable structure determination for single-atom and subnanometer cluster catalysts. As a case study, we obtained the low energy structures of Pd n (n = 1-21) clusters supported on CeO 2 (111), which are critical components of automobile three-way catalysts. Trained on density functional theory data, a three-dimensional cluster expansion is established using statistical learning to describe the Hamiltonian and predict energies of supported Pdn clusters of any structure. Low energy stable and metastable structures are identified using a Metropolis Monte Carlo-based genetic algorithm in the canonical ensemble at 300 K. We observe that supported single atoms sinter to form bilayer clusters and large cluster isomers share similarities in both shape and energy, and elucidate the significance of the support and microstructure on cluster stability. We discovered a simple surrogate structure-energy model, where the energy per atom scales with the square root of the average first coordination number, which can be used to estimate energies and compare the stability of clusters. Our framework, applicable to any metal/support system, fills an important methodological gap to predict the stability of supported metal catalysts in the subnanometer regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗