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Results for “Global Optimization”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Interpreting the Operando X-ray Absorption Near-Edge Structure of Supported Cu and CuPd Clusters in Conditions of Oxidative Dehydrogenation of Propane: Dynamic Changes in Composition and Size

Supported subnano-cluster catalysts are highly dynamic, developing true active sites only under the pressures and temperatures of reaction conditions. Operando X-ray absorption near-edge structure (XANES) spectroscopy can track changes in the oxidation state and the local environment of cluster atoms, providing insight into the development of these active sites. While bulk metal, oxide, and hydroxide standards are often used for fitting experimental XANES spectra to obtain average oxidation states, we recently showed that computed cluster standards of relevant compositions are a more suitable basis, producing more accurate fits. Here, we theoretically interpret the operando XANES of supported Cu 3 Pd and Cu 4 clusters during temperature-programmed reaction (TPRx) of oxidative dehydrogenation of propane. We use an expanded basis set including both globally optimized computed clusters and bulk standards. Not only can we track reversible composition/oxidation state change with temperature, but also the irreversible growth of the bulk fraction upon heating, which we attribute to cluster sintering. This has important implications for the mechanism of the catalyzed reaction and the nature of the available active sites. Here, we propose that operando XANES provides most significant insight into the nature of supported cluster catalysts in reaction conditions when interpreted using mixed computed cluster and bulk standards.

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

Mechanism of Stoichiometrically Governed Titanium Oxide Brownian Tree Formation on Stepped Au(111)

Previously observed formation of substoichiometric titanium oxide dendritic structures across terraces of Au(111) is computationally studied and shown to follow the classical fractal formation mechanism of diffusion-limited aggregation (DLA). Globally optimized gas-phase oxide cluster structures are sampled in a variety of landing formations on gold surfaces and shown to favor isomers driving polymerization to Brownian tree fractal structures. Mobility of Ti 3 O 5 monomers is shown to be extremely high, with diffusion barriers of 0.21 eV or less. Through bonding stabilization, polymerization of these monomers is energetically favorable and irreversible on the 111 terrace but geometrically impossible to propagate along the step edge. Simulated scanning tunneling microscopy (STM) images show strong similarity to experiment. By contrast, observation of Ti 3 O 6 aggregating as wires along step edges is explained by the affinity of oxygen to step edges and statistical arguments for aggregation entropy at the step, in addition to low barriers for monomer diffusion and polymerization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Structure and Stability of the Ionic Liquid Clusters [EMIM]n[BF4]n+1- (n = 1 – 9): Implications for Electrochemical Separations

Precise functionalization of electrodes with size-selected ionic liquid (IL) clusters may improve the application of ILs in electrochemical separations. Herein, we report our combined experimental and theoretical investigation of the IL clusters [EMIM]????[BF4]????+1- (n = 1 – 9) and demonstrate their selectivity and efficiency towards targeted adsorption of molecules from solution. The structures and energies of the IL clusters, predicted with global optimization, agree with and help interpret the ion abundances and stabilities measured by high mass resolution electrospray ionization mass spectrometry and collision induced dissociation experiments. The [EMIM][BF4]2- cluster, which was identified as the most stable IL cluster, was selectively soft landed onto a working electrode. Electrochemical impedance spectroscopy revealed a lower charge transfer resistance on the soft-landed electrode containing [EMIM] [BF_4 ]_2^- compared to an electrode prepared by drop casting of IL solution, which contains the full range of IL clusters. Our findings indicate that specific IL clusters may be used to increase the efficiency of electrochemical separations by lowering the overpotentials involved.

Zhang, Jun↗
DOE OSTI2026

CO (2) Electroreduction on Borated Copper Surfaces: Boron Active Sites, Not Copper

Boron-doped copper has recently emerged as an active and stable catalyst for the electrochemical reduction of CO 2 to value-added C 2 products. Here, in this work, we develop a realistic model of CO electroreduction on surface borides of copper under operational conditions, taking into account the effects of electrode potential, electrolyte environment, and pH. We study the possible reconstruction of the electrocatalyst surface using grand canonical DFT and global optimization to obtain a potential-dependent grand canonical ensemble description of metastable, hydrogen-covered catalyst surfaces. Two key surface configurations, low H coverage (LC, −0.6 V SHE ) and high H coverage (HC, −0.8 V SHE ), dominate this ensemble, with the former being kinetically persistent and C 2 selective under strongly reducing conditions. Nonmetallic boron sites on the surface copper boride are found to bind CO more strongly than copper sites, and mechanistic investigation of CO electroreduction pathways presents a surprisingly unconventional case of boron-centered reactivity in contrast to typical copper-centered reactivity. Neighboring boron sites present along boron chains on the surface copper boride are found to facilitate C−C coupling, thereby driving the high C 2 selectivity of this electrocatalyst.

boron-doped copper↗
DOE OSTI2023

Electrocatalytic Hydrogen Evolution at Full Atomic Utilization over ITO-Supported Sub-nano-Pt n Clusters: High, Size-Dependent Activity Controlled by Fluxional Pt Hydride Species

A combination of density functional theory (DFT) and experiments with atomically size-selected Pt n clusters deposited on indium-tin oxide (ITO) electrodes was used to examine the effects of applied potential and Pt n size on the electrocatalytic activity of Pt n (n = 1, 4, 7, 8) for the hydrogen evolution reaction (HER). Activity is found to be negligible for isolated Pt atoms on ITO, increasing rapidly with Pt n size, such that Pt 7 /ITO and Pt 8 /ITO have roughly double the activity per Pt atom compared to atoms in the surface layer of polycrystalline Pt. Both DFT and experiment find that hydrogen under-potential deposition (H upd ) results in Pt n /ITO (n = 4, 7, 8) adsorbing ~2 H atoms/Pt atom at the HER threshold potential, equal to ca. double the Hupd observed for Pt bulk or nanoparticles. Here, the cluster catalysts under electrocatalytic conditions are hence best described as a Pt hydride compound, significantly departing from a metallic Pt cluster. The exception is Pt 1 /ITO, where H adsorption at the HER threshold potential is energetically unfavorable. Theory combines global optimization with grand canonical approaches for the influence of potential, uncovering that several metastable structures contribute to HER, changing with the applied potential. It is hence critical to include reactions of the ensemble of energetically accessible Pt n H x /ITO structures to correctly predict the activity vs. Pt n size and applied potential. For the small clusters, spillover of H ads from the clusters to the ITO support is significant, resulting in a competing channel for loss of H ads , particularly at slow potential scan rates.

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

Off-Stoichiometric Restructuring and Sliding Dynamics of Hexagonal Boron Nitride Edges in Conditions of Oxidative Dehydrogenation of Propane

Boron-containing materials, such as hexagonal boron nitride (h-BN), recently shown to be active and selective catalysts for the oxidative dehydrogenation of propane (ODHP), have been shown to undergo significant surface oxyfunctionalization and restructuring. Although experimental ex situ studies have probed the change in chemical environment on the surface, the structural evolution of it under varying reaction conditions has not been established. Herein, we perform global optimization structure search with a grand canonical genetic algorithm to explore the chemical space of off-stoichiometric restructuring of the h-BN surface under ambient as well as ODHP-relevant conditions. A grand canonical ensemble representation of the surface is established, and the predicted 11B solid-state NMR spectra are consistent with previous experimental reports. In addition, we investigated the relative sliding of h-BN sheets and how it influences the surface chemistry with ab initio molecular dynamics simulations. Furthermore, the B–O linkages on the edges are found to be significantly strained during the sliding, causing the metastable sliding configurations to have higher reactivity toward the activation of propane and water.

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

Spontaneous dynamical disordering of borophenes in MgB2 and related metal borides

Abstract Layered boron compounds have attracted significant interest in applications from energy storage to electronic materials to device applications, owing in part to a diversity of surface properties tied to specific arrangements of boron atoms. Here we report the energy landscape for surface atomic configurations of MgB 2 by combining first-principles calculations, global optimization, material synthesis and characterization. We demonstrate that contrary to previous assumptions, multiple disordered reconstructions are thermodynamically preferred and kinetically accessible within exposed B surfaces in MgB 2 and other layered metal diborides at low boron chemical potentials. Such a dynamic environment and intrinsic disordering of the B surface atoms present new opportunities to realize a diverse set of 2D boron structures. We validated the predicted surface disorder by characterizing exfoliated boron-terminated MgB 2 nanosheets. We further discuss application-relevant implications, with a particular view towards understanding the impact of boron surface heterogeneity on hydrogen storage performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cobalt-based magnetic Weyl semimetals with high-thermodynamic stabilities

Abstract Recent experiments identified Co 3 Sn 2 S 2 as the first magnetic Weyl semimetal (MWSM). Using first-principles calculation with a global optimization approach, we explore the structural stabilities and topological electronic properties of cobalt (Co)-based shandite and alloys, Co 3 MM’X 2 (M/M’ = Ge, Sn, Pb, X = S, Se, Te), and identify stable structures with different Weyl phases. Using a tight-binding model, for the first time, we reveal that the physical origin of the nodal lines of a Co-based shandite structure is the interlayer coupling between Co atoms in different Kagome layers, while the number of Weyl points and their types are mainly governed by the interaction between Co and the metal atoms, Sn, Ge, and Pb. The Co 3 SnPbS 2 alloy exhibits two distinguished topological phases, depending on the relative positions of the Sn and Pb atoms: a three-dimensional quantum anomalous Hall metal, and a MWSM phase with anomalous Hall conductivity (~1290 Ω −1 cm −1 ) that is larger than that of Co 2 Sn 2 S 2 . Our work reveals the physical mechanism of the origination of Weyl fermions in Co-based shandite structures and proposes topological quantum states with high thermal stability.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predicting temperature-dependent ultimate strengths of body-centered-cubic (BCC) high-entropy alloys

This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature, T break , introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay below T break . We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and show how a special case can be formulated to address the identification of HEAs offering attractive ultimate strength. We advocate for the selection of an optimization technique suitable for the problem at hand and the data available, and for properly accounting for the underlying sources of variations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting 3D moisture sorption behavior of materials from 1D investigations

Abstract Moisture in materials can be a source of future outgassing and exacerbate unwanted changes in physical and chemical properties. Here, we investigate the effect of sample size and shape on the moisture transport phenomena through a combined experimental and modeling approach. Several different materials varying in size and shape were investigated over a wide range of relative humidities (0–90%) and temperatures ( $$30{-}70^{\,\circ } \hbox {C}$$ 30 - 70 ∘ C ) using gravimetric type dynamic vapor sorption (DVS). A dynamic triple-mode sorption model, developed previously, was employed to describe the experimental results with good success; the model includes absorption, adsorption, pooling (clustering) of species, and molecular diffusion. Here we show that the full triple-mode sorption model is robust enough to predict the dynamic uptake and outgassing of 3-dimensional (3D) samples using parameters derived from quasi-1D samples. This successful demonstration on three different materials (filled polydimethylsiloxane (PDMS), unfilled PDMS, and ceramic inorganic composite) illustrates that the model is robust at describing the scale-independent physics and chemistry of moisture sorption and diffusion materials. This work demonstrates that while sorption mechanisms manifest in testing of all sample sizes, some of these mechanisms were so subtle that they were overlooked in our initial modeling and assessment, illustrating the importance of multi-scale experiments in the development of robust predictive capabilities. Our study also outlines the challenges and viable solutions for global optimization of a multi-parameter model. The ability to quantify moisture sorption and diffusion, independent of scale, using 1D lab-scale experiments enables prediction of long-term bulk materials behavior in real applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Toward fully automated UED operation using two-stage machine learning model

To demonstrate the feasibility of automating UED operation and diagnosing the machine performance in real time, a two-stage machine learning (ML) model based on self-consistent start-to-end simulations has been implemented. This model will not only provide the machine parameters with adequate precision, toward the full automation of the UED instrument, but also make real-time electron beam information available as single-shot nondestructive diagnostics. Furthermore, based on a deep understanding of the root connection between the electron beam properties and the features of Bragg-diffraction patterns, we have applied the hidden symmetry as model constraints, successfully improving the accuracy of energy spread prediction by a factor of five and making the beam divergence prediction two times faster. The capability enabled by the global optimization via ML provides us with better opportunities for discoveries using near-parallel, bright, and ultrafast electron beams for single-shot imaging. It also enables directly visualizing the dynamics of defects and nanostructured materials, which is impossible using present electron-beam technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Influence of near-surface oxide layers on TiFe hydrogenation: mechanistic insights and implications for hydrogen storage applications

The inevitable formation of passivating oxide films on the surface of the TiFe intermetallic compound limits its performance as a stationary hydrogen storage material. Extensive experimental efforts have been dedicated to the activation of TiFe, i.e. oxide layer removal prior to utilization for hydrogen storage. However, development of an efficient activation protocol necessitates a fundamental understanding of the composition and structure of the air-exposed surface and its interaction with hydrogen, which is currently absent. Therefore, in this study we explored the growth and nature of oxide films on the most exposed TiFe surface (110) in depth using static and dynamic first-principles methods. We identified the lowest energy structures for six oxygen coverages up to approximately 1.12 nm of thickness with a global optimization method and studied the temperature effects and structural evolution of the oxide phases in detail via ab initio molecular dynamics (AIMD). Based on structural similarity and coordination analysis, motifs for TiO 2 and TiFeO 3 as well as Ti(FeO 2 ) x (x = 2, 3 or 5) phases were identified. On evaluating the interaction of the oxidized surface with hydrogen, a minimal energy barrier of 0.172 eV was predicted for H 2 dissociation while H migration from the top of the oxidized surface to the bulk TiFe was limited by several high-lying energy barriers above 1.4 eV. Our mechanistic insights will prove themselves valuable for informed designs towards new activation methods of TiFe and related systems as hydrogen storage materials.

08 HYDROGEN↗
DOE OSTI2023

Reinforcement learning based hybrid bond-order coarse-grained interatomic potentials for exploring mesoscale aggregation in liquid–liquid mixtures

Exploring mesoscopic physical phenomena has always been a challenge for brute-force all-atom molecular dynamics simulations. Although recent advances in computing hardware have improved the accessible length scales, reaching mesoscopic timescales is still a significant bottleneck. Coarse-graining of all-atom models allows robust investigation of mesoscale physics with a reduced spatial and temporal resolution but preserves desired structural features of molecules, unlike continuum-based methods. Here, we present a hybrid bond-order coarse-grained forcefield (HyCG) for modeling mesoscale aggregation phenomena in liquid–liquid mixtures. The intuitive hybrid functional form of the potential offers interpretability to our model, unlike many machine learning based interatomic potentials. We parameterize the potential with the continuous action Monte Carlo Tree Search (cMCTS) algorithm, a reinforcement learning (RL) based global optimizing scheme, using training data from all-atom simulations. The resulting RL-HyCG correctly describes mesoscale critical fluctuations in binary liquid–liquid extraction systems. cMCTS, the RL algorithm, accurately captures the mean behavior of various geometrical properties of the molecule of interest, which were excluded from the training set. The developed potential model along with the RL-based training workflow could be applied to explore a variety of other mesoscale physical phenomena that are typically inaccessible to all-atom molecular dynamics simulations.

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

Force Field X: A computational microscope to study genetic variation and organic crystals using theory and experiment

Force Field X (FFX) is an open-source software package for atomic resolution modeling of genetic variants and organic crystals that leverages advanced potential energy functions and experimental data. FFX currently consists of nine modular packages with novel algorithms that include global optimization via a many-body expansion, acid–base chemistry using polarizable constant-pH molecular dynamics, estimation of free energy differences, generalized Kirkwood implicit solvent models, and many more. Applications of FFX focus on the use and development of a crystal structure prediction pipeline, biomolecular structure refinement against experimental datasets, and estimation of the thermodynamic effects of genetic variants on both proteins and nucleic acids. The use of Parallel Java and OpenMM combines to offer shared memory, message passing, and graphics processing unit parallelization for high performance simulations. Overall, the FFX platform serves as a computational microscope to study systems ranging from organic crystals to solvated biomolecular systems.

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

The long road to ignition: An eyewitness account

This paper reviews the many twists and turns in the long journey that culminated in ignition in late 2022 using the laser heated indirect-drive approach to imploding DT filled targets at the National Ignition Facility (NIF), located at the Lawrence Livermore National Laboratory (LLNL). We describe the early origins of the Laser Program at LLNL and key developments such as the paradigm shifting birth of high energy density physics (HEDP) studies with lasers, changes in choice of laser wavelength, and the development of key diagnostics and computer codes. Fulfilling the requirements of the multi-faceted Nova Technical Contract was a necessary condition for the approval of the NIF, but more importantly, the end of the Cold War and the cessation of nuclear testing were key catalysts in that approval, along with the ready-and-waiting field of HEDP. The inherent flexibility of the field of laser driven inertial confinement fusion played a fundamental role in achieving success at the NIF. We describe how the ultimately successful ignition target design evolved from the original “point design” target, through the lessons of experiment. All key aspects of that original design changed: The capsule's materials and size were changed; the hohlraum's materials, size, laser entrance hole size, and gas fills were also all changed, as were the laser pulse shapes that go along with all those changes. The philosophy to globally optimize performance for stability (by raising the adiabat and thus lowering the implosion convergence) was also key, as was progress in target fabrication, and in increasing NIF's energy output. The persistence of the research staff and the steadfast backing of our supporters were also necessary elements in this success. We gratefully acknowledge seven decades of researcher endeavors and four decades of the dedicated efforts of many hundreds of personnel across the globe who have participated in NIF construction, operation, target fabrication, diagnostic, and theoretical advances that have culminated in ignition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

RANGE: A robust adaptive nature-inspired global explorer of potential energy surfaces

With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directly or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. In conclusion, our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.

Algorithms and data structure↗
DOE OSTI2026

Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: a benchmark Quantum Monte Carlo study

The accurate description of non-covalent interactions is critical for understanding the structure, dynamics, and eventual function of biomolecules. The adenine dimer serves as a benchmark system for computational methods due to its role in nucleic acid structures and its rich conformational landscape. In this study, we employ benchmark diffusion quantum Monte Carlo (DMC) methods to investigate the relative energies and role of electron correlation on a set of adenine dimer conformations generated via a search of the potential energy landscape using the global optimizer algorithm. Relative DMC energies are compared against a wide range of density functional theory (DFT) approximation results. We find that although most of the DFT functionals perform well for low-energy structures, their accuracy varies significantly for higher-energy conformations, including stacked and T-shaped structures. A large fraction of the variation is due to the treatment of the van der Waals interaction. BLYP, B3LYP, and PBE0 significantly improve with added D4 dispersion, while the recent r2SCAN-D4 and ωB97M-V functionals show the least scatter and closest agreement with the DMC. These findings highlight the delicate nature of these interactions in biomolecular systems and provide guidance for simulations of their structure and dynamics and for the development of machine learned interatomic potentials.

Washburn, Laurel [ORNL] (ORCID:0000000324179335)↗
DOE OSTI2024

Functionally graded magnetic materials: a perspective to advance charged particle optics through compositional engineering

Additive manufacturing has ushered in a new paradigm of bottom-up materials-by-design of spatially non-uniform materials. Functionally graded materials have locally tailored compositions to provide optimized global properties and performance. In this letter, we propose an opportunity for the application of graded magnetic materials as lens elements for charged particle optics. A Hiperco50/Hymu80 (FeCo-2 V/Fe-80Ni-5Mo) graded magnetic alloy was successfully additively manufactured via Laser Directed Energy Deposition with spatially varying magnetic properties. The compositional gradient is then applied using computational simulations to demonstrate how a tailored material can enhance the magnetic performance of a critical, image-forming component of a transmission electron microscope.

36 MATERIALS SCIENCE↗