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DOE OSTI2017

Optimal periodic frequency combs for high-efficiency optical quantum memory based on rare-earth ion crystals

The possibility of enhancing the quantum efficiency of photon echo broadband quantum memory in rare-earth-ion-doped crystals with a frequency comb structure of optical transition inhomogeneous broadening is studied. We have found the optimal parameters of the frequency combs for implementing the pre-assigned quantum efficiency in the chosen spectral range of the optical transitions of rare-earth ions with real parameters. The obtained results allow the conditions to be formulated for increasing the efficiency of broadband quantum memory. The possibilities of experimental implementation of such memory are also discussed. (paper)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Low-dose x-ray tomography through a deep convolutional neural network

Synchrotron-based X-ray tomography offers the potential of rapid large-scale reconstructions of the interiors of materials and biological tissue at fine resolution. However, for radiation sensitive samples, there remain fundamental trade-offs between damaging samples during longer acquisition times and reducing signals with shorter acquisition times. We present a deep convolutional neural network (CNN) method that increases the acquired X-ray tomographic signal by at least a factor of 10 during low-dose fast acquisition by improving the quality of recorded projections. Short exposure time projections enhanced with CNN show similar signal to noise ratios as compared with long exposure time projections and much lower noise and more structural information than low-dose fats acquisition without CNN. We optimized this approach using simulated samples and further validated on experimental nano-computed tomography data of radiation sensitive mouse brains acquired with a transmission X-ray microscopy. We demonstrate that automated algorithms can reliably trace brain structures in datasets collected with low dose-CNN. As a result, this method can be applied to other tomographic or scanning based X-ray imaging techniques and has great potential for studying faster dynamics in specimens.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Algorithmic Improvements for Portable Event-Based Monte Carlo Transport Using the Nvidia Thrust Library

High performance computing environments are progressively moving towards many-core computing architectures. The Los Alamos National Laboratory Trinity machine, available in late 2016, will use both Intel Xeon Haswell processors and Intel Xeon Phi Knights Landing many integrated core (MIC) coprocessors. The Lawrence Livermore National Laboratory Sierra machine, available in 2018, will use an IBM PowerPC architecture along with Nvidia graphics processing units (GPUs). Applications that must work in this supercomputing environment must continue to adapt in order to take advantage of the diverse hardware architectures that are coming. A significant consideration is not only the performance of the application on a given platform but also the portability of the application to other platforms. The algorithmic improvements presented in this paper build upon recently-reported work on event-based Monte Carlo transport in the ALPSMC code that models particle transport in one-dimensional binary stochastic media. That paper discussed the lack of available vectorization in the traditional history-based algorithm used for Monte Carlo transport and presented a data parallel event-based algorithm implemented using the Nvidia Thrust library for portability. The performance of the data parallel event-based algorithm implemented using Thrust was compared to a native CUDA implementation. The conclusions from that work were that the Thrust library abstraction technique caused too significant a loss in performance but that the event-based method was a viable option that should be further investigated. In this paper, we describe algorithmic improvements to the data parallel event-based algorithm previously presented. We made further algorithmic optimizations to the event-based CUDA implementation, most notably: data structure changes, a new conditional particle removal scheme in the event-based process, and the use of multiple GPUs. In addition to improvements to the algorithm, we re-implemented the Thrust version from the now further optimized CUDA version, giving a greater chance for success at a performant abstraction. Finally, we revisited our previous assumptions about the inability of the history-based method to achieve performance on vector style architectures such as the MICs and GPUs, with surprising and promising results. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

InGaP-based quantum well solar cells: Growth, structural design, and photovoltaic properties

Raising the efficiency ceiling of multi-junction solar cells (MJSCs) through the use of more optimal band gap configurations of next-generation MJSC is crucial for concentrator and space systems. Towards this goal, we propose two strain balanced multiple quantum well (SBMQW) structures to tune the bandgap of InGaP-based solar cells. These structures are based on In{sub x}Ga{sub 1−x}As{sub 1−z}P{sub z}/In{sub y}Ga{sub 1−y}P (x > y) and In{sub x}Ga{sub 1−x}P/In{sub y}Ga{sub 1−y}P (x > y) well/barrier combinations, lattice matched to GaAs in a p-i-n solar cell device. The bandgap of In{sub x}Ga{sub 1−x}As{sub 1−z}P{sub z}/In{sub y}Ga{sub 1−y}P can be tuned from 1.82 to 1.65 eV by adjusting the well composition and thickness, which promotes its use as an efficient subcell for next generation five and six junction photovoltaic devices. The thicknesses of wells and barriers are adjusted using a zero net stress balance model to prevent the formation of defects. Thin layers of InGaAsP wells have been grown thermodynamically stable with compositions within the miscibility gap for the bulk alloy. The growth conditions of the two SBMQWs and the individual layers are reported. The structures are characterized and analyzed by optical microscopy, X-ray diffraction, photoluminescence, current-voltage characteristics, and spectral response (external quantum efficiency). The effect of the well number on the excitonic absorption of InGaAsP/InGaP SBMQWs is discussed and analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Dynamic analysis of fully constrained Cable-Driven Parallel Robots for automated prefabricated component installation

This paper presents a dynamic analysis and validation framework to assess a fully constrained six-anchor Cable-Driven Parallel Robot (CDPR) for automated installation of prefabricated facade components. Compared with conventional eight-anchor systems, the six-anchor configuration simplifies setup and reduces cost, but it also reduces control authority, shrinks the wrench-feasible workspace, and tightens orientation limits. Consequently, it is unclear a priori whether dynamically feasible trajectories exist to move the end effector from pickup to the facade. A constrained trajectory optimization is formulated to enforce the system dynamics, cable-tension bounds, and pose/velocity limits, and the framework is evaluated in simulation at three levels: (i) an idealized reference model, (ii) a lab-scale prototype model incorporating measured anchor misalignments and identified damping, and (iii) a full-scale three-story building model with load decomposition for structural feasibility checks. Across these scenarios, the analysis shows that optimal, constraint-satisfying trajectories exist that move the end effector from pickup to installation while maintaining a near-plumb, level orientation at the final pose. Collectively, this multi-scale dynamic analysis and validation framework supports the deployment readiness of the six-anchor CDPR and provides a prototype-based sensitivity case study of how measured anchor placement deviations affect feasibility.

CDPR↗

DOE OSTI2026

Uncertainty quantification and reliability assessment for intermodal freight transportation

Intermodal freight optimization models support cost-effective, low-emission, and timely goods movement by coordinating trucks, rail, and barges. These models determine optimal flows, routing, and modal switches while respecting infrastructure and operational constraints. However, their real-world utility is often undermined by pervasive uncertainties-such as fluctuating transportation costs and emissions, variable terminal capacities, and uncertain freight demand-that distort key performance outcomes, including total system cost, carbon footprint, and transit time reliability. This study presents a structured framework for quantifying uncertainty in intermodal freight transportation (IFT) optimization. The framework evaluates how input uncertainty affects system performance and reliability, a critical need for ensuring that model-based decisions remain robust under real-world variability, especially amid volatile fuel prices, shifting demand, and growing disruptions. It integrates three complementary methods: (1) Sobol-based global sensitivity analysis to identify influential parameters affecting cost, emissions, and transit time, (2) Monte Carlo-based capacity perturbation analysis to assess robustness under probabilistic facility disruptions, and (3) Monte Carlo filtering with Bayesian inference to detect threshold-based performance vulnerabilities. The results highlight diesel truck unit cost as the dominant driver of variability. To improve system resilience, planners should prioritize uncertainty in fuel-related parameters when designing intermodal strategies.

Intermodal freight transportation↗

DOE OSTI2021

Entanglement rearrangement in self-consistent nuclear structure calculations

Background: Entanglement plays a central role in a diverse array of increasingly important research areas, including quantum computation, simulation, measurement, sensing, and communication. Extensive suites of investigations have been performed to better understand entanglement in atomic and molecular quantum many-body systems, while the exploration of entanglement in the structure of nuclei and their reactions is presently in its infancy. Purpose: The goal of this work is to begin investigating the entanglement properties of nuclei from first-principles nuclear many-body calculations. We attempt to identify common features and emergent structures of entanglement that could ultimately lead to new and natural many-body schemes. With an eye toward quantum accelerators in future hybrid-supercomputers, criteria for partitioning nuclear many-body calculations into quantum and classical components may provide advantages in future large-scale computations. Along the way we look for explanations of the relative success of phenomenological models such as the nuclear shell model, and for better ways to match to low-energy nuclear effective field theories and lattice QCD calculations to nuclear many-body techniques that are based upon entanglement. Method: We explore the entanglement between single-particle states in 4 He and 6 He. The patterns of entanglement emerging from different single-particle bases are compared, and possible links with the convergence of observables are explored, in particular, ground-state energies. The nuclear wave functions are obtained by performing active-space no-core configuration-interaction calculations using a two-body nucleon-nucleon interaction derived from chiral effective field theory. Entanglement measures within single-particle bases exhibiting different degrees of complexity are determined, in particular, harmonic oscillator (HO), Hartree-Fock (HF), natural (NAT) and variational natural (VNAT) bases. Specifically, single-orbital entanglement entropy, two-orbital mutual information, and negativity are studied. Results: The entanglement structures in 4 He and 6 He are found to be more localized within NAT and VNAT bases than within a HO basis for the optimal HO parameters we have worked with. In particular a core-valence structure clearly emerges from the full no-core calculation of 6 He. Here, the two-nucleon mutual information shows that the VNAT basis, which typically exhibits good convergence properties, effectively decouples the active and inactive spaces. Conclusions: Measures of one- and two-nucleon entanglement are found to be useful in analyzing the structure of nuclear wave functions, in particular the efficacy of basis states, and may provide useful metrics toward developing more efficient schemes for ab initio computations of the structure and reactions of nuclei, and quantum many-body systems more generally.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

Economic Analysis and Optimal Sizing for behind-the-meter Battery Storage

This paper proposes methods to estimate the potential benefits and determine the optimal energy and power capacity for behind-the-meter BSS. In the proposed method, a linear programming is first formulated only using typical load profiles, energy/demand charge rates, and a set of battery parameters to determine the maximum saving in electric energy cost. The optimization formulation is then adapted to include battery cost as a function of its power and energy capacity in order to capture the trade-off between benefits and cost, and therefore to determine the most economic battery size. Using the proposed methods, economic analysis and optimal sizing have been performed for a few commercial buildings and utility rate structures that are representative of those found in the various regions of the Continental United States. The key factors that affect the economic benefits and optimal size have been identified. The proposed methods and case study results cannot only help commercial and industrial customers or battery vendors to evaluate and size the storage system for behind-the-meter application, but can also assist utilities and policy makers to design electricity rate or subsidies to promote the development of energy storage.

Wu, Di↗

DOE OSTI2016

New Mechanistic Insight from Substrate- and Product-Bound Structures of the Metal-Dependent Dimethylsulfoniopropionate Lyase DddQ

The marine microbial catabolism of dimethylsulfoniopropionate (DMSP) by the lyase pathway liberates ~300 million tons of dimethyl sulfide (DMS) per year, which plays a major role in the biogeochemical cycling of sulfur. Recent biochemical and structural studies of some DMSP lyases, including DddQ, reveal the importance of divalent transition metal ions in assisting DMSP cleavage. While DddQ is believed to be zinc-dependent primarily on the basis of structural studies, excess zinc inhibits the enzyme. We examine the importance of iron in regulating the DMSP β-elimination reaction catalyzed by DddQ as our as-isolated purple-colored enzyme possesses ~0.5 Fe/subunit. The UV–visible spectrum exhibited a feature at 550 nm, consistent with a tyrosinate–Fe(III) ligand-to-metal charge transfer transition. Incubation of as-isolated DddQ with added iron increases the intensity of the 550 nm peak, whereas addition of dithionite causes a bleaching as Fe(III) is reduced. Both the Fe(III) oxidized and Fe(II) reduced species are active, with similar kcat values and 2-fold differences in their Km values for DMSP. The slow turnover of Fe(III)-bound DddQ allowed us to capture a substrate-bound form of the enzyme. Our DMSP–Fe(III)-DddQ structure reveals conformational changes associated with substrate binding and shows that DMSP is positioned optimally to bind iron and is in the proximity of Tyr 120 that acts as a Lewis base to initiate catalysis. The structures of Tris-, DMSP-, and acrylate-bound forms of Fe(III)-DddQ reported here illustrate various states of the enzyme along the reaction pathway. Furthermore, these results provide new insights into DMSP lyase catalysis and have broader significance for understanding the mechanism of oceanic DMS production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Theoretical studies of the global minima and polarizabilities of small lithium clusters

Lithium clusters Lin (n=1-20) have been investigated with density functional theory (DFT) and coupled—cluster (CC) methods. The global-minimum structures are located via an improved basin---hopping algorithm and the lowest energy Lin isomers are confirmed with DFT geometry optimizations, CCSD(T) energy calculations, and by comparing simulated and experimental polarizabilities. The tetrahedral Li4 structure is found to be the basic building block of lithium clusters Lin (n=6-20). Simulated polarizabilities, including thermal effects at room temperature, are in good agreement with measured isotropic polarizabilities.

clusters↗

DOE OSTI2018

Parallelizable adjoint stencil computations using transposed forward-mode algorithmic differentiation

Algorithmic differentiation (AD) is a tool for generating discrete adjoint solvers, which efficiently compute gradients of functions with many inputs, for example for use in gradient-based optimization. AD is often applied to large computations such as stencil operators, which are an important part of most structured-mesh PDE solvers. Stencil computations are often parallelized, for example by using OpenMP, and optimized by using techniques such as cache-blocking and tiling to fully utilize multicore CPUs and many-core accelerators and GPUs. Differentiating these codes with conventional reverse-mode AD results in adjoint codes that cannot be expressed as stencil operations and may not be easily parallelizable. They thus leave most of the compute power of modern architectures unused. We present a method that combines forward-mode AD and loop transformation to generate adjoint solvers that use the same memory access pattern as the original computation that they are derived from and can benefit from the same optimization techniques. The effectiveness of this method is demonstrated by generating a scalable adjoint CFD solver for multicore CPUs and Xeon Phi accelerators.

algorithmic differentiation↗

DOE OSTI2023

Optimization of metal-supported solid oxide electrolysis cells with infiltrated catalysts

We report metal-supported solid oxide electrolysis cells (MS-SOECs) are being developed for steam-to-hydrogen electrolysis, especially for utilization of dynamic or intermittent electrical power from renewable sources. Various aspects of the electrocatalyst processing and composition, and metal support structure were explored. Catalyst materials, infiltration temperature and infiltration cycles were optimized for high performance and durability. Numerous catalyst materials were screened for both oxygen and steam electrodes. The oxygen catalyst had moderate impact on both initial cell performance and durability. Reducing Ni content in the steam electrode had little effect on durability, but reduced initial performance. Ex-situ XRD analysis and cell assessment of catalyst infiltration temperature revealed that the optimal range is 750–850 °C. The best cell performance and durability was achieved with LSCF-SDC oxygen electrocatalyst and SDC-Ni (60:40 vol%) steam electrocatalyst infiltrated 11 times at 800 °C and operated at 700 °C. At low steam content, a significant mass transport limitation on the steam side results in limiting current behavior. Thinner and more porous metal supports were implemented, and found to improve steam mass transport at low steam content, relevant for SOECs operating under high H 2 recycle rate or high steam utilization.

08 HYDROGEN↗

DOE OSTI2018

Ultrathin Pt x Sn 1–x Nanowires for Methanol and Ethanol Oxidation Reactions: Tuning Performance by Varying Chemical Composition

Pt-based alloys denote promising catalysts for the methanol oxidation reaction (MOR) and the ethanol oxidation reaction (EOR), due to their enhanced activity toward alcohol-oxidation reactions and reduced cost as compared with Pt alone. Among all of these binary systems, PtSn has been reported to exhibit superior methanol/ethanol oxidation activity. In this paper, we deliberatively tailor chemical composition, reduce size, and optimize morphology of the catalyst in an effort to understand structure–property correlations that can be used to improve upon the electrocatalytic activity of these systems. Previous work performed by our group suggested that Pt-based catalysts, possessing an ultrathin one-dimensional (1D) structure, dramatically promote both cathodic and anodic reactions with respect to their zero-dimensional (0D) counterparts. Herein, a novel set of ultrathin binary Pt–Sn 1D nanowire (NW) catalysts with rationally controlled chemical compositions, i.e., Pt 9 Sn 1 , Pt 8 Sn 2 , and Pt 7 Sn 3 , has been synthesized using a facile, room-temperature, wet-solution-based method. The crystallinity and chemical composition of these as-prepared samples were initially characterized using XRD, XPS, and EDX. Results revealed that this synthetic protocol could successfully generate PtSn alloys with purposely tunable chemical compositions. TEM and HRTEM verified the structural integrity of our ultrathin 1D NW morphology for our Pt 9 Sn 1 , Pt 8 Sn 2 , and Pt 7 Sn 3 samples. The effects of varying Sn content within these alloy samples toward the electro-oxidation reaction of methanol and ethanol were probed using cyclic voltammetry (CV) in acidic media. Finally, within this series, we find that the optimized chemical composition for both the MOR and the EOR is Pt 7 Sn 3 .

36 MATERIALS SCIENCE↗

DOE OSTI2017

Evolutionary optimization of PAW data-sets for accurate high pressure simulations

We examine the challenge of performing accurate electronic structure calculations at high pressures by comparing the results of all-electron full potential linearized augmented-plane-wave calculations, as implemented in the WIEN2k code, with those of the projector augmented wave (PAW) method, as implemented in Quantum ESPRESSO or Abinit code. In particular, we focus on developing an automated and consistent way of generating transferable PAW data-sets that can closely produce the all electron equation of state defined from zero to arbitrary high pressures. The technique we propose is an evolutionary search procedure that exploits the ATOMPAW code to generate atomic data-sets and the Quantum ESPRESSO software suite for total energy calculations. We demonstrate different aspects of its workability by optimizing PAW basis functions of some elements relatively abundant in planetary interiors. In addition, we introduce a new measure of atomic data-set goodness by considering their performance uniformity over an extended pressure range. - Highlights: • An attempt made to achieve the AE-FLAPW accuracy, at the favorable computational efficiency of the PAW approach for an outspread pressure range. • Provided an automatic and consistent route for developing efficient and transferable PAW data-sets. • Explicated an improved measure for the goodness of data-sets by including uniformity of the data-set performance over an extended pressure range.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Potent HIV‑1 protease inhibitors containing oxabicyclo octanol-derived P2-ligands: Design, synthesis, and X‑ray structural studies of inhibitor-HIV-1 protease complexes

Here, we describe here the design, synthesis, and X-ray structural studies of a new class of HIV-1 protease inhibitors containing 8-oxabicyclo[3.2.1]octanol-derived P2 ligands. We investigated the functional effect of these stereochemically defined fused-poly cyclic ligands on enzyme inhibition and antiviral activity in MT-2 cells. The tricyclic core of 8-oxabicyclo[3.2.1]octan-6-ol is designed to interact with the residues in the S2 subsite of HIV-1 protease. The syntheses of the ligands were carried out using the [5+2]-cycloaddition as the key step. Several inhibitors exhibited potent enzyme inhibitory activity. High resolution room-temperature X-ray structures of inhibitor-bound HIV-1 protease were determined. These structures provided important molecular insights for further design and optimization of inhibitor potency.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

FMX – the Frontier Microfocusing Macromolecular Crystallography Beamline at the National Synchrotron Light Source II

Two new macromolecular crystallography (MX) beamlines at the National Synchrotron Light Source II, FMX and AMX, opened for general user operation in February 2017 [Schneider et al. (2013). J. Phys. Conf. Ser. 425 , 012003; Fuchs et al. (2014). J. Phys. Conf. Ser. 493 , 012021; Fuchs et al. (2016). AIP Conf. Proc. SRI2015 , 1741 , 030006]. FMX, the micro-focusing Frontier MX beamline in sector 17-ID-2 at NSLS-II, covers a 5–30 keV photon energy range and delivers a flux of 4.0 × 10 12 photons s −1 at 1 Å into a 1 µm × 1.5 µm to 10 µm × 10 µm (V × H) variable focus, expected to reach 5 × 10 12 photons s −1 at final storage-ring current. This flux density surpasses most MX beamlines by nearly two orders of magnitude. The high brightness and microbeam capability of FMX are focused on solving difficult crystallographic challenges. The beamline's flexible design supports a wide range of structure determination methods – serial crystallography on micrometre-sized crystals, raster optimization of diffraction from inhomogeneous crystals, high-resolution data collection from large-unit-cell crystals, room-temperature data collection for crystals that are difficult to freeze and for studying conformational dynamics, and fully automated data collection for sample-screening and ligand-binding studies. FMX's high dose rate reduces data collection times for applications like serial crystallography to minutes rather than hours. With associated sample lifetimes as short as a few milliseconds, new rapid sample-delivery methods have been implemented, such as an ultra-high-speed high-precision piezo scanner goniometer [Gao et al. (2018). J. Synchrotron Rad. 25 , 1362–1370], new microcrystal-optimized micromesh well sample holders [Guo et al. (2018). IUCrJ , 5 , 238–246] and highly viscous media injectors [Weierstall et al. (2014). Nat. Commun. 5 , 3309]. The new beamline pushes the frontier of synchrotron crystallography and enables users to determine structures from difficult-to-crystallize targets like membrane proteins, using previously intractable crystals of a few micrometres in size, and to obtain quality structures from irregular larger crystals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

EVI-LOCATE User Manual

One of the longest stages in the deployment of electric vehicle supply equipment (EVSE) is the initial planning of the infrastructure itself. Engineers and fleet experts from the National Renewable Energy Laboratory (NREL) have supported dozens of charging infrastructure site plans over the past couple decades, including the generation of site schematics, determinations of electric capacity, and estimates for likely costs. As the market for electric vehicles (EVs) has matured, this approach should no longer require a time and personnel intensive process. In order to shorten the time taken to develop site plans and cost estimates, NREL developed a tool that fleet managers, facility managers, electricians, EVSE installers, and members of the public can use to develop initial schematics and ballpark pricing for charging station installations. The Electric Vehicle Infrastructure - Locally Optimized Charger Assessment Tool and Estimator (EVI-LOCATE) provides a structured and consistent way for users to enter information about their planned EVSE project in a relatively simple web-based format. EVI-LOCATE then calculates electrical equipment capacity, wiring runs, and project costs. It produces a site diagram optimized around surface characteristics with differential trenching costs for softscape such as grass compared to hardscape such as asphalt that can be adjusted by users in the tool. It also stores the resulting site plans and costs in a dashboard for access at a later date, including plan revisions if necessary. This document guides users through the EVI-LOCATE screens and associated questions. It contains tip text boxes throughout on how best to interface with the tool and find additional information or context. The appendices contain the assumptions and calculations underpinning the tool. Much of the information for EVI-LOCATE was gathered through industry engagements with EVSE installers, invoices from completed EVSE installations, Gordian's RS Means construction data, and the General Services Administration blanket purchase agreement for EVSE. For a visual tutorial of the tool, users can watch EVI-LOCATE Step-by-Step Video. The tool itself is available at https://evi-locate.nrel.gov.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Determining the Adsorption Energetics of 2,3-Butanediol on RuO 2 (110): Coupling First-Principles Calculations With Global Optimizers

As climate change continues to pose a threat to the Earth due to the disrupted carbon cycles and fossil fuel resources remain finite, new sources of sustainable hydrocarbons must be explored. 2,3-butanediol is a potential source to produce butene because of its sustainability as a biomass-derived sugar. Butene is an attractive product because it can be used as a precursor to jet fuel, categorizing this work in the alcohol-to-jet pathway. While studies have explored the conversion of 2,3-butanediol to butene, little is understood about the fundamental reaction itself. We quantify the energetics for three pathways that were reported in the literature in the absence of a catalyst. One of these pathways forms a 1,3-butadiene intermediate, which is a highly exothermic process and thus is unlikely to occur since 2,3-butanediol likely gets thermodynamically trapped at this intermediate. We further determined the corresponding energetics of 2,3-butanediol adsorption on an ensemble of predetermined binding sites when it interacts with a defect-free stoichiometric RuO 2 (110) surface. Within this ensemble of adsorption sites, the most favorable site has 2,3-butanediol covering a Ru 5–coordinated cation. This approach is compared to that obtained using the global optimization algorithm as implemented in the Northwest Potential Energy Surface Search Engine. When using such a global optimization algorithm, we determined a more favorable ground-state structure that was missed during the manual adsorption site testing, with an adsorption energy of -2.61 eV as compared to -2.34 eV when using the ensemble-based approach. We hypothesize that the dehydration reaction requires a stronger chemical bond, which could necessitate the formation of oxygen vacancies. As such, this study has taken the first step toward the utilization of a global optimization algorithm for the rational design of Ru-based catalysts toward the formation of butene from sustainable resources.

09 BIOMASS FUELS↗

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