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At least 19 records

CI-MOR Final Report: Analysis and Validation of Critical Infrastructure Models using Model Order Reduction

This report summarizes the research and capabilities developed as part of the project “Analysis and Validation of Critical Infrastructure Models using Model Order Reduction” (CI-MOR) LDRD project. CI-MOR research enables the solution of large, complex optimization models that naturally arise in national security challenges involving critical infrastructures. Specifically, CI-MOR researchers developed methods to (1) rigorously approximate complex, nonlinear optimization formulations, (2) identify alternative near-optimal solutions, (3) accelerate optimization workflows used for complex applications, and (4) rigorously integrate domain knowledge in stochastic-process models. This report provides an overview of the research done in CI-MOR, and we describe application exemplars used to illustrate CI-MOR capabilities. Furthermore, we describe the software developed by CI-MOR that researchers can leverage to analyze new applications.

97 MATHEMATICS AND COMPUTING↗

Metocean Reference Station Best Practices: MORS-1 Case Study

The goal of a Metocean Reference Station should be to aid both near-term development of the offshore wind energy industry as well as long-term climate and energy research. Capitalizing on existing shared-use facilities wherever possible, reference stations should provide data valued by industry users as well as research users in a cost-effective way. Cost-effectiveness is a critical component of developing a reference site, as the real value of the site's data collection efforts is the length of the time series it is able to sustain. This report seeks to lay out the best practices toward developing and maintaining metocean reference stations in the United States. The best practices described here focus on suitable platforms, sensor integration, and long-term operations of the reference station itself, as best practices of operations for individual sensors for the research community or validation enterprises focused on industrial use of metocean data are well described in the literature. This work focuses on potential stations in the United States because the market for reference data and validation facilities is less well defined in the United States, given the young age of the rapidly emerging offshore wind energy industry here.

17 WIND ENERGY↗

MORS Phalax Ad for Systems Analysis

At Lawrence Livermore National Laboratory, applying cutting-edge science and technology to challenging security questions is an everyday thing. Systems Analysis is one way we solve problems—by bringing analytic rigor to missions like strategic deterrence and critical infrastructure defense. Working with the brightest minds in science, technology, and engineering, systems analysts at LLNL bring state-of-the-art analytic tools to bear on problems of national importance. From ensuring the safety, security, and effectiveness of our nation’s nuclear stockpile to shaping the future of inertial fusion energy—if you have a penchant for problem-solving using modeling and analysis tools—we have a place for you.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Oxygen Vacancies Alter Methanol Oxidation Pathways on NiOOH

A thorough comprehension of the mechanism underlying the methanol oxidation reaction (MOR) on Ni-based catalysts is critical for future electrocatalytic design and development. However, the mechanism of MOR on these materials remains a matter of controversy. Herein, we combine in situ surface-enhanced infrared absorption spectroscopy (SEIRAS) and density functional theory (DFT) calculations to identify the active sites and determine the mechanism of MOR on monometallic Ni-based catalysts in alkaline media. The SEIRAS results show that formate and (bi)carbonate are formed after the commencement of the MOR with potential-dependent relative distributions. These spectroscopic results are in good agreement with the DFT-computed reaction profiles over an oxygen vacancy, suggesting that the MOR mainly proceeds through the formate-involving pathway, in which the early consumption of methanol yields formate as the major product, while increasing potential drives further oxidation of formate to (bi)carbonate. We also find a parallel pathway for the generation of (bi)carbonate at high potentials that bypasses the formation of formate. The two main pathways are thermodynamically more feasible than the one predominantly reported in the literature for MOR on NiOOH that involves CHO and/or CO as key intermediates. These DFT results are supported by spectroscopic evidence showing that no band associated with CHO or CO can be detected by SEIRAS, which is attributed to the nature of the oxygen vacancies as the active sites, suppressing deep dehydrogenation of CH 2 O to CHO. Furthermore, this work thus shows the promising role of defect engineering in promoting the electrocatalytic MOR activity and selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stereoselective recognition of morphine enantiomers by μ -opioid receptor

Stereospecific recognition of chiral molecules plays a crucial role in biological systems. The μ-opioid receptor (MOR) exhibits binding affinity towards (-)-morphine, a well-established gold standard in pain management, while it shows minimal binding affinity for the (+)-morphine enantiomer, resulting in a lack of analgesic activity. Understanding how MOR stereoselectively recognizes morphine enantiomers has remained a puzzle in neuroscience and pharmacology for over half-a-century due to the lack of direct observation techniques. To unravel this mystery, we constructed the binding and unbinding processes of morphine enantiomers with MOR via molecular dynamics simulations to investigate the thermodynamics and kinetics governing MOR's stereoselective recognition of morphine enantiomers. Our findings reveal that the binding of (-)-morphine stabilizes MOR in its activated state, exhibiting a deep energy well and a prolonged residence time. In contrast, (+)-morphine fails to sustain the activation state of MOR. Furthermore, the results suggest that specific residues, namely D114 2.50 and D147 3.32 , are deprotonated in the active state of MOR bound to (-)-morphine. This work highlights that the selectivity in molecular recognition goes beyond binding affinities, extending into the realm of residence time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques

Opioids exert their analgesic effect by binding to the µ opioid receptor (MOR), which initiates a downstream signaling pathway, eventually inhibiting pain transmission in the spinal cord. However, current opioids are addictive, often leading to overdose contributing to the opioid crisis in the United States. Therefore, understanding the structure-activity relationship between MOR and its ligands is essential for predicting MOR binding of chemicals, which could assist in the development of non-addictive or less-addictive opioid analgesics. This study aimed to develop machine learning and deep learning models for predicting MOR binding activity of chemicals. Chemicals with MOR binding activity data were first curated from public databases and the literature. Molecular descriptors of the curated chemicals were calculated using software Mold2. The chemicals were then split into training and external validation datasets. Random forest, k-nearest neighbors, support vector machine, multi-layer perceptron, and long short-term memory models were developed and evaluated using 5-fold cross-validations and external validations, resulting in Matthews correlation coefficients of 0.528–0.654 and 0.408, respectively. Furthermore, prediction confidence and applicability domain analyses highlighted their importance to the models’ applicability. Our results suggest that the developed models could be useful for identifying MOR binders, potentially aiding in the development of non-addictive or less-addictive drugs targeting MOR.

Research & Experimental Medicine↗

Surrogate models for plasma displacement and current in 3D perturbed magnetohydrodynamic equilibria in tokamaks

Abstract A numerical database of over one thousand perturbed three-dimensional (3D) equilibria has been generated, constructed based on the MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) computed plasma response to the externally applied 3D field sources in multiple tokamak devices. Perturbed 3D equilibria with the n = 1–4 ( n is the toroidal mode number) toroidal periodicity are computed. Surrogate models are created for the computed perturbed 3D equilibrium utilizing model order reduction (MOR) techniques. In particular, retaining the first few eigenstates from the singular value decomposition (SVD) of the data is found to produce reasonably accurate MOR-representations for the key perturbed quantities, such as the perturbed parallel plasma current density and the plasma radial displacement. SVD also helps to reveal the core versus edge plasma response to the applied 3D field. For the database covering the conventional aspect ratio devices, about 95% of data can be represented by the truncated SVD-series with inclusion of only the first five eigenstates, achieving a relative error (RE) below 20%. The MOR-data is further utilized to train neural networks (NNs) to enable fast reconstruction of perturbed 3D equilibria, based on the two-dimensional equilibrium input and the 3D source field. The best NN-training is achieved for the MOR-data obtained with a global SVD approach, where the full set of samples used for NN training and testing are stretched and form a large matrix which is then subject to SVD. The fully connected multi-layer perceptron, with one or two hidden layers, can be trained to predict the MOR-data with less than 10% RE. As a key insight, a better strategy is to train separate NNs for the plasma response fields with different toroidal mode numbers. It is also better to apply MOR and to subsequently train NNs separately for conventional and low aspect ratio devices, due to enhanced toroidal coupling of Fourier spectra in the plasma response in the latter case.

3D equilibrium↗

PtRu Catalysts on Nitrogen-Doped Carbon Nanotubes with Conformal Hydrogenated TiO 2 Shells for Methanol Oxidation

The methanol oxidation reaction (MOR) is the limiting factor in direct methanol fuel cells (DMFC). There is an urgent need to improve the catalytic activity and stability of MOR catalysts. This study reports a highly active PtRu catalyst for MOR based on a hybrid multifunctional catalyst support consisting of a conformal amorphous hydrogenated TiO 2 shell wrapped around the oxygenated N-doped carbon nanotube core, denoted as PtRu/TiO 2 / ONCNT-400. Both the TiO 2 shell and the subsequent PtRu nanoparticles are deposited by a rapid microwave-assisted synthesis processes. The hydrogenated TiO 2 shell is found to exhibit a strong interaction with the deposited PtRu catalyst nanoparticles and effectively prevent them from agglomeration during the postdeposition thermal annealing to form more active crystalline PtRu alloy catalysts. In addition, the defective hydrogenated TiO 2 shell enhances the PtRu catalyst activity by the synergistic effects of partial charge transfer from TiO 2 to PtRu and high oxophilicity, which improves the kinetics of oxidation of poisonous CO intermediate to CO 2 . The mass activity for MOR and long-cycling stability of the PtRu/TiO 2 /ONCNT-400 catalyst surpass the two benchmark commercial PtRu/C catalysts from Johnson Matthey (JM) and Tanaka KiKinzoku (TKK), respectively. Furthermore, the results demonstrate that PtRu/TiO 2 /ONCNT-400 can serve as an efficient catalyst for MOR in DMFC.

36 MATERIALS SCIENCE↗

Oxidative Self-Assembly of Au/Ag/Pt Alloy Nanoparticles into High-Surface Area, Mesoporous, and Conductive Aerogels for Methanol Electro-oxidation

The ability to assemble nanoparticles (NPs) into functional nanostructures is critical for the advancement of nanoscience. However, common assembling techniques utilize organic ligands or biomolecules, which are detrimental for charge transport and interparticle coupling, which impede the efficient integration of low-dimensional properties. Herein, we report a methodology for the self-supported assembly of ultra-small (3-6 nm) Au/Ag/Pt alloy NPs into large, free-standing alloy superstructures (aerogels) that exhibit direct NP connectivity, high surface area (125 ± 0.43 to142 ± 0.93 m 2 /g) and mesoporosity (21.6 ± 2.2 nm), and superior electrocatalytic activity for methanol oxidation reaction (MOR). Precursor Au/Ag/Pt alloy NPs and hydrogels were synthesized via stepwise galvanic replacement reaction (GRR) of the glutathione (GSH)-coated Ag NPs, followed by oxidative removal of the surfactant ligands. The composition of alloy aerogels was tuned by varying the oxidant/GSH molar ratio, which governs the extent of Ag dealloying with in-situ generated HNO 3 and increases the exposure of Au and Pt on the aerogel surface. The alloy aerogels exhibit superior MOR mass activity, which is 21.4 and 2.5 times higher than those of the precursor NPs and commercial Pt (40 wt.%)/C electrocatalysts, respectively. The MOR surface-specific activity (MOR-SSA) of the aerogels was improved by >17% when the Pt content was increased from 22.4% to 31.2%. The aerogels exhibit improved electronic conductivity, enhanced tolerance for carbonaceous byproducts, and maintained ~94% of the initial MOR activity at -0.3 V for 24 h in an alkaline medium. In conclusion, the interconnected porous superstructure of the aerogel provides a facile conduit for molecules to reach the pristine active surface whereas the presence of oxophilic Au promotes the dissociative adsorption of methanol, enabling the Au/Ag/Pt alloy aerogel a high efficiency, durable electrocatalyst for next generation of energy conversion studies.

36 MATERIALS SCIENCE↗

Densification and Immobilization of AgI-Containing Iodine Waste Forms Using Spark Plasma Sintering

Here in this study, porous Ag-xerogel (Ag-Xero), Ag-faujasite (Ag-FAU) zeolite, and Ag-mordenite (Ag-MOR) zeolite sorbents were loaded with iodine gas [I 2 (g)] under saturated conditions at 150 °C for 24 h, followed by densification and consolidation into monolithic waste forms using spark plasma sintering (SPS). For Ag-Xero materials, SPS pellets were made with as-loaded samples, while others were made with preheated (PH; 500 °C for 2 h) samples to help with densification. SPS processing was conducted at 50 MPa under different temperatures (T = 200–800 °C) for different times (t = 0.5–30 min), where eleven AgI-Xero samples, five AgI-FAU, and two AgI-MOR separate samples were produced. The primary goal was to look for the optimum processing parameters for each material to yield pellets with high iodine retentions, high densities, and low porosities while preventing AgI decomposition. The Ag-Xero showed the highest iodine loadings (qe = 470 mg g –1 ) compared to Ag-FAU (qe = 368 mg g –1 ) and Ag-MOR (qe = 108 mg g –1 ). Measured iodine concentrations were the highest in AgI-Xero pellets without PH, followed by AgI-Xero with PH, AgI-FAU, and then AgI-MOR. Silver utilization (I/Ag on a mol % basis) values were in the order of AgI-MOR ≈ AgI-Xero (no PH) > AgI-Xero (PH) > AgI-FAU. Chemical durabilities of SPS-densified AgI-Xero (PH) pellets were very favorable, with lower releases than SPS pellets made from AgI-Xero samples without PH. These results show promise for iodine waste form production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a Metocean Reference Site near the Massachusetts and Rhode Island Wind Energy Areas

This project developed the first long-term U.S.-based offshore MetOcean Reference Site (MORS-1) by capitalizing on a unique combination of one of the few existing publicly available offshore wind energy metocean observational campaigns in the United States and the only existing research-grade offshore fixed tower. Data collected at MORS-1 has facilitated improved wind resource assessments, improved short-term power production estimates, and reduced costs for sensor validation and calibration efforts, which translate into reduced overall wind energy project risk and cost for developers. Now operational, MORS-1 serves the needs of both industry and researchers using a nonprofit, joint industry-academic partnership model. Led by the Woods Hole Oceanographic Institution, the MORS-1 development effort focused on creating both a recognized organizational structure that will ensure support of the MORS-1 by the wider wind energy industry and research community, and a highly validated data collection and sensor validation facility that will serve as the premier location for cost- and uncertainty-reducing resource characterization and research efforts.

17 WIND ENERGY↗

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]↗

Atomic Ordering-Induced Ensemble Variation in Alloys Governs Electrocatalyst On/Off States

The catalytic behavior of a material is influenced by ensembles—the geometric configuration of atoms. Traditional approaches, mainly utilizing solid-solution alloys in electrocatalysis, have often overlooked the challenges posed by concurrent changes in the electronic structure (i.e. d-band center) when the composition is altered. Here, this study introduces a methodology that distinctly separates the geometric effects (i.e. ensembles) from the electronic structure. We compare the reactivity of compositionally identical, but structurally different Pd 3 Bi ordered intermetallic and solid-solution alloys. Remarkably, we find that Pd 3 Bi intermetallics display nearly no reactivity for the methanol oxidation (MOR), while their solid-solution counterparts have significant reactivity. This highlights a unique case where materials with identical chemical compositions demonstrate drastically different catalytic behavior underscoring the critical importance of ensembles in electrocatalysis. Specifically, Pd 3 Bi intermetallics form smaller ensembles (average coordination number: 4.5 ± 1.6) with almost no measurable MOR activity at room temperature, in contrast to the solid-solution Pd 3 Bi that exhibit larger ensembles (average coordination number: 6.8 ± 0.9) and considerable MOR reactivity (0.5 mA cm −2 Pd ). An ordered Pd 3 Bi alloy, with an intermediate ensemble size (average coordination number: 5.3 ± 1.2), displays moderate MOR activity (0.1 mA cm −2 Pd ), further confirming the direct correlation between ensemble size and catalytic activity. Notably, all Pd 3 Bi alloys maintain similar electronic structures, because the chemical composition of the alloys is fixed, indicating that the differences in reactivity are predominantly from changes to the ensemble size. Our findings offer an approach for precisely controlling catalytic activity through manipulating the geometric configuration of the atoms within an alloy, paving the way for more efficient catalyst design.

alloys↗

Lanthanum-based double perovskite nanoscale motifs as support media for the methanol oxidation reaction

In this report we have not only analyzed the performance of perovskite oxides as support media for the methanol oxidation reaction (MOR) but also examined the impact and significance of various reaction parameters on their synthesis. Specifically, we have generated (a) La 2 NiMnO 6 , LaMnO 3 , and LaNiO 3 nanocubes with average sizes of ~200 nm, in addition to a series of La 2 NiMnO 6 (b) nanocubes possessing average sizes of ~70 and 400 nm and (c) anisotropic nanorods characterized by average diameters of 40-50 nm. All of these samples, when used as supports for Pt nanoparticles, exhibited activities which were at least twice that measured for Pt/C. We have investigated and correlated the effect of varying perovskite (i) composition, (ii) size, and (iii) morphology upon the measured MOR activity. (i) The Ni-containing perovskites yielded generally higher performance metrics than LaMnO 3 alone, suggesting that the presence of Ni is favorable for MOR, a finding supported by a shift in the Pt d-band in XPS. (ii) MOR activity is enhanced as the perovskite size increases in magnitude, suggesting that a growth in the perovskite particle size enables favorable, synergistic metal–support interactions. (iii) A comparison of the nanorods and nanocubes of a similar diameter implied that the one-dimensional morphology achieved a greater activity, a finding which can be attributed not only to the anisotropic structure but also to a desirable surface structure. Overall, these data yield key insights into the tuning of metal–support interactions via rational control over the composition, size, and morphology of the underlying catalyst support.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model reduction methods for nuclear emulators

The field of model order reduction (MOR) is growing in importance due to its ability to extract the key insights from complex simulations while discarding computationally burdensome and superfluous information. We provide an overview of MOR methods for the creation of fast & accurate emulators of memory- and compute-intensive nuclear systems, focusing on eigen-emulators and variational emulators. As an example, we describe how 'eigenvector continuation' is a special case of a much more general and well-studied MOR formalism for parameterized systems. We continue with an introduction to the Ritz and Galerkin projection methods that underpin many such emulators, while pointing to the relevant MOR theory and its successful applications along the way. Here, we believe that this guide will open the door to broader applications in nuclear physics and facilitate communication with practitioners in other fields.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Platinum/Tantalum Carbide Core–Shell Nanoparticles with Sub‐Monolayer Shells for Methanol and Oxygen Electrocatalysis

Abstract Core–shell architectures provide great opportunities to improve catalytic activity, but achieving nanoparticle stability under electrochemical cycling remains challenging. Herein, core–shell nanoparticles comprising atomically thin Pt shells over earth‐abundant TaC cores are synthesized and used as highly durable electrocatalysts for the methanol oxidation reaction (MOR) and the oxygen reduction reaction (ORR) needed to drive direct methanol fuel cells (DMFCs). Characterization data show that a thin oxidic passivation layer protects the TaC core from undergoing dissolution in the fuel cell‐relevant potential range, enabling the use of partially covered Pt/TaC core–shell nanoparticles for MOR and ORR with high stability and enhanced catalytic performance. Specifically, at the anode the surface‐oxidized TaC further enhances MOR activity compared to conventional Pt nanoparticles. At the cathode, the Pt/TaC catalyst feature increases tolerance to methanol crossover. These results show unique synergistic advantages of the core–shell particles and open opportunities to tailor catalytic properties for electrocatalytic reactions.

Chemistry↗

Influence of Al location on formation of silver clusters in mordenite

Formation of zeolite supported Ag 0 clusters depends on a combination of thermodynamically stable atomic configurations, charge balance considerations, and mobility of species on the surface and within pores. Periodic density functional theory (DFT) calculations were performed to evaluate how the location of Al in the mordenite (MOR) framework and humidity control Ag 0 nanocluster formation. Four Al framework sites were studied (T1-T4) and the Al positions in the framework were identified by the shifts in the differential Al…Al pair distribution function (PDF). Furthermore, structural information about the Ag 0 nanoclusters, such as dangling bonds, can be identified by Ag…Ag PDF data. For Ag 0 formation in vacuum MOR structures with a Si:Al ratio of 5:1 with Al in the T1 position resulted in the most framework flexibility and the lowest Ag 0 nanocluster charge, indicating the best result for formation of charge neutral nanoclusters. When water is present, Al in the T3 and T4 positions results in the formation of the smallest average Ag 0 nanoclusters plus greater expansion of the O-T-O bond angle than in vacuum, indicating easier diffusion of the Ag 0 nanoclusters to the surface. Here, the presence of Al in 4-membered rings and in pairs indicates favorable MOR structures for formation of single Ag atoms, despite the existence of synthesis challenges. Therefore, Al in the T2 position is the least favorable for Ag 0 nanocluster formation in both vacuum and in the presence of water. Al in the T1, T3, and T4 positions provides beneficial effects through framework flexibility and changes in nanocluster size or charge that can be leveraged for design of zeolites for formation of metallic nanoclusters.

36 MATERIALS SCIENCE↗