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DOE OSTI2019

Site-Selective Probes of Mixed-Node Metal Organic Frameworks for Photocatalytic Hydrogen Generation

Metal organic frameworks (MOFs) have emerged as a novel platform offering new promise for photocatalytic applications. In this work, we report a mixed-node MOF (MOF-74) based on earth-abundant metals (i.e., Co and Fe) as highly active and robust photocatalysts for visible light-driven H 2 generation. Using in situ X-ray absorption spectroscopy which allows us to selectively probe the individual metal node in MOFs, we unambiguously identified the catalytic active sites and captured the key intermediate species under the standard catalytic conditions. We show that both Co and Fe centers in MOF-74 are the reversible active sites, and the accumulation of their reduced states is responsible for the observed induction period for H 2 generation. Moreover, we captured the key intermediate species formed when the reaction reaches equilibrium, which is featured by an elongated Co–O bond at the Co center and a more distorted octahedral geometry at the Fe center with respect to their original geometry. These results not only demonstrate the potential of MOF-74 as a single site catalyst for H 2 generation but also provide new insight into the catalytic mechanism for further development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Node-Solution Microenvironment Governs the Selectivity of Thioanisole Oxidation within Catalytic Zr-Based Metal–Organic Framework

Lewis acidic metal oxides, including zirconia (ZrO 2 ), are catalytically active toward oxidative reactions in the presence of sacrificial oxidants like t-butyl hydroperoxide (TBHP). The structural ambiguity and heterogeneity of the ZrO 2 surface impose challenges to chemists in understanding the reaction mechanism down to atomic-level precision. The inorganic, Zr-oxo nodes of many crystalline metal–organic frameworks (MOFs) structurally mimic ZrO 2 . Herein, we report three novel findings: (A) Zr-based MOF, Zr-MOF-808 is catalytically competent in activating TBHP to induce oxygen atom transfer (OAT) reactions to a model substrate, thioanisole, at room temperature, (B) its reaction mechanism can be derived with greater structural precision owing to the crystallinity of the MOF, and (C) the node-binding agent and other reaction conditions significantly impact the selectivity between the singly oxidized methyl phenyl sulfoxide vs the doubly oxidized sulfone. These findings suggest that both the activity and selectivity of OAT reactions within Zr-MOF-808 are governed by the chemistry occurring at the interface of the node and the surrounding reaction medium. Implications of these findings in OAT reactions and other MOF/metal oxide-catalyzed relevant catalysis are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Role of Metal Selection in the Radiation Stability of Isostructural M-UiO-66 Metal–Organic Frameworks

Robust and versatile metal–organic frameworks (MOFs) have emerged as sophisticated scaffolds to meet the critical needs of the nuclear community, but their performance depends on their underexplored structural integrities in high- radiation fields. The contributions of selected metal nodes in the radiation stability of MOFs within the isostructural M-UiO-66 series (where M = Zr, Ce, Hf, Th, and Pu; Zr-UiO-66 experiments were executed in a previous work) have been determined. Ce-, Hf-, and Th-UiO-66 MOF samples were irradiated via gamma and He-ion methodologies to obtain doses up to 3 MGy and 85 MGy, respectively, the latter strikingly higher than that obtained in most other studies. Appreciable self-irradiation constituted the total absorbed doses, up to 31 MGy of the gamma-irradiated Pu-UiO-66 samples. Structural degradation was ascertained by powder X-ray diffraction, X-ray total scattering, vibrational spectroscopy, and, where possible, N 2 physisorption isotherms. Diffuse reflectance infrared Fourier transform spectroscopy provided atomic-level mechanistic insights to reveal that the node-linker connection was most susceptible to radiation damage. Density functional theory calculations were performed on cluster models to evaluate the binding energy of the linkers to each metal node. Here, while the isostructures disclosed the same breakdown signatures, distinct radiation sensitivity as a function of metal selection was evident and followed the trend Hf-UiO-66 ~ Zr-UiO-66 > Th-UiO-66 > Pu-UiO-66 > Ce-UiO-66. We anticipate that these endeavors will contribute to the rational design of radiation-resistant materials for targeted applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Collectively loading programs in a multiple program multiple data environment

Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture

Metal-organic frameworks (MOFs) exhibit great promise for CO 2 capture. However, finding the best performing materials poses computational and experimental grand challenges in view of the vast chemical space of potential building blocks. Here, we introduce GHP-MOFassemble, a generative artificial intelligence (AI), high performance framework for the rational and accelerated design of MOFs with high CO 2 adsorption capacity and synthesizable linkers. GHP-MOFassemble generates novel linkers, assembled with one of three pre-selected metal nodes (Cu paddlewheel, Zn paddlewheel, Zn tetramer) into MOFs in a primitive cubic topology. GHP-MOFassemble screens and validates AI-generated MOFs for uniqueness, synthesizability, structural validity, uses molecular dynamics simulations to study their stability and chemical consistency, and crystal graph neural networks and Grand Canonical Monte Carlo simulations to quantify their CO 2 adsorption capacities. We present the top six AI-generated MOFs with CO 2 capacities greater than 2m mol g -1 , i.e., higher than 96.9% of structures in the hypothetical MOF dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Punishment diminishes the benefits of network reciprocity in social dilemma experiments

Network reciprocity has been widely advertised in theoretical studies as one of the basic cooperation-promoting mechanisms, but experimental evidence favoring this type of reciprocity was published only recently. When organized in an unchanging network of social contacts, human subjects cooperate provided the following strict condition is satisfied: The benefit of cooperation must outweigh the total cost of cooperating with all neighbors. In an attempt to relax this condition, we perform social dilemma experiments wherein network reciprocity is aided with another theoretically hypothesized cooperation-promoting mechanism—costly punishment. The results reveal how networks promote and stabilize cooperation. This stabilizing effect is stronger in a smaller-size neighborhood, as expected from theory and experiments. Contrary to expectations, punishment diminishes the benefits of network reciprocity by lowering assortment, payoff per round, and award for cooperative behavior. This diminishing effect is stronger in a larger-size neighborhood. An immediate implication is that the psychological effects of enduring punishment override the rational response anticipated in quantitative models of cooperation in networks.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2017

The CMS Data Acquisition - Architectures for the Phase-2 Upgrade

The upgraded High Luminosity LHC, after the third Long Shutdown (LS3), will provide an instantaneous luminosity of 7.5 × 10 34 cm -2 s -1 (levelled), at the price of extreme pileup of up to 200 interactions per crossing. In LS3, the CMS Detector will also undergo a major upgrade to prepare for the phase-2 of the LHC physics program, starting around 2025. The upgraded detector will be read out at an unprecedented data rate of up to 50 Tb/s and an event rate of 750 kHz. Complete events will be analysed by software algorithms running on standard processing nodes, and selected events will be stored permanently at a rate of up to 10 kHz for offline processing and analysis. Here in this paper we discuss the baseline design of the DAQ and HLT systems for the phase-2, taking into account the projected evolution of high speed network fabrics for event building and distribution, and the anticipated performance of general purpose CPU. Implications on hardware and infrastructure requirements for the DAQ “data center” are analysed. Emerging technologies for data reduction are considered. Novel possible approaches to event building and online processing, inspired by trending developments in other areas of computing dealing with large masses of data, are also examined. We conclude by discussing the opportunities offered by reading out and processing parts of the detector, wherever the front-end electronics allows, at the machine clock rate (40 MHz). This idea presents interesting challenges and its physics potential should be studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Analysis of Approximations in Modeling of BWR Bundle Void Distributions

In boiling water reactors, complex heterogeneous bundle designs, control blades adjacent to the corner of bundles, and the presence of boiling can lead to complex internal void distributions. A few approximations exist to model these void distributions. They could be modeled using a 1D axial solver in which each axial node is assumed to be at an average void, or each pin cell could be modeled with its own void concentration. In the latter case, the void could be discretized in pin-centered or coolant-centered channels. The goal of this project was to quantify the effect of using the different approximations for modeling internal void distributions on neutronics calculations. Using 3D void distributions calculated with CTF, Monte Carlo Neutral Particle (MCNP) transport code models were created for GE-9 and GE-14 lattices. For each model, the internal void distribution from CTF at a given axial node was selected, and a lattice calculation was carried out with MCNP. Comparisons between models using a lattice-averaged void, or using a void distribution in coolant-centered channels, showed large differences in reactivity which in some cases were well above 1,000 pcm, and it also showed differences in normalized fission rates greater than 20%. It was also found that using a lattice average void can lead to a significant difference in the estimation of the worth of a control blade. The differences found when comparing results from models using pin-centered and coolant-centered channels were up to 200 pcm in reactivity and up to 1.4% in the normalized fission rates. In addition to these two sets of comparisons, MCNP models were set up so that each subchannel had a saturated liquid component around the fuel pins and a saturated vapor component in the center to approximate annular flow. In comparison to the models using coolant-centered subchannels, up to 1–3% differences in normalized fission rates could be found.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2019

Internal Mammary Chain Sentinel Nodes in Early-Stage Breast Cancer Patients: Toward Selective Removal

Background: Removal of internal mammary chain sentinel nodes (IMCSNs) affects prognosis and treatment of breast cancer, and internal mammary chain radiotherapy (IMCRT) can improve survival for selected patients. This study aimed to determine the effect of IMCSN biopsy on recurrence-free survival (RFS) and overall survival (OS) and to identify predictive factors for IMCSN and distant metastasis. Methods: Patients with IMCSNs were selected from a prospective database for the period 1999–2007. Lymphoscintigraphy was performed after intratumoral technetium-99 m injection, and all sentinel nodes were removed. Both RFS and OS were calculated for subgroups with tumor-positive, tumor-negative, or non-removed IMCSNs. Predictive factors were identified for tumor-positive IMCSNs and distant metastasis by regression analysis. Results: For 287 (85%) of 336 patients, IMCSN biopsy was performed, and metastasis was detected in 38 patients (13%). The patients with tumor-positive IMCSNs had poorer OS than the patients with no IMCSN metastasis or non-removed IMCSNs (p = 0.002). These patients also had worse RFS due to distant metastasis (p = 0.002). Axillary metastasis was predictive for tumor-positive IMCSNs (positive predictive value, 38.5%). The predictive factors for distant metastasis were tumor-positive IMCSNs (hazard ratio [HR], 2.5), non-removed IMCSNs (HR, 2.3), tumor diameter greater than 1.5 cm (HR, 3.5), and age older than 65 years (HR, 3.1; reference, < 50 years). Conclusions: Patients with IMCSNs have worse survival due to distant metastasis. The clinically relevant predictive factor for distant metastasis is tumor larger than 1.5 cm. According to the authors’ current protocol, IMCSN biopsy is performed for patients younger than 70 years who have a tumor larger than 1.5 cm, with the cardiotoxicity of the adjuvant IMCRT weighed against the survival benefit.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Structure- and Physics-Preserving Reductions of Power Grid Models

The large size of multiscale, distribution and transmission, power grids hinders fast systemwide estimation and real-time control and optimization of operations. This paper studies graph reduction methods of power grids that are favorable for fast simulations and follow-up applications. While the classical Kron reduction has been successful in reduced order modeling of power grids with traditional, hierarchical design, the selection of reference nodes for the reduced model in a multiscale, distribution and transmission, network becomes ambiguous. In this work we extend the use of the iterative Kron reduction by utilizing the electric grid's graph topology for the selection of reference nodes, consistent with the design features of multiscale networks. Additionally, we propose further reductions by aggregation of coherent subnetworks of triangular meshes, based on the graph topology and network characteristics, in order to preserve currents and build another power-flow equivalent network. Our reductions are achieved through the use of iterative aggregation of subgraphs that include general tree structures, lines, and triangles. Important features of our reduction algorithms include that (i) the reductions are either equivalent to the Kron reduction or otherwise produce a power-flow equivalent network; (ii) due to the mentioned power-flow equivalence, the reduced network can model the dynamic of the swing equations for a lossless, inductive, steady state network; (iii) the algorithms efficiently utilize hash tables to store the sequential reduction steps. The third feature allows for easy reintroduction of detailed models into the reduced, conceptual network and makes the final reduced order model backward compatible with a sequence of intermediate, partially reduced networks with varying resolution---the ordered sequence of iterative reductions corresponds to a sequence of reduced order models. The performance of our graph reduction algorithms and features of the reduced grids are discussed on a real-word transmission and distribution grid. We produce visualizations of the reduced models through open source libraries and release our reduction algorithms with example code and toy data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Elucidating the mechanism of the UiO-66-catalyzed sulfide oxidation: activity and selectivity enhancements through changes in the node coordination environment and solvent

Benzoic acid modulators that “cap” the Zr 6 -oxo-hydroxo cluster nodes in UiO-66 metal–organic frameworks can be removed to increase the number of “open” sites ( i.e. , those that are terminated with [μ 1 -OH + μ 1 -OH 2 ]) up to 5 per node, enabling the “decapped” materials to exhibit enhanced catalytic activity in the oxidation of methyl phenyl sulfide. Here, computational modeling reveals that the labile Zr-μ 1 -OH groups on these open sites are likely converted into Zr-μ 1 -OOH species that are active in oxidizing the sulfide as well as its sulfoxide product. In solvents such as CH 3 CN and CH 2 Cl 2 , the sulfoxide product can additionally replace the aquo ligands of the Zr-μ 1 -OH 2 moieties to increase the concentration of the sulfoxide adjacent to the active Zr-μ 1 -OOH species, resulting in overoxidation to the sulfone. However, the use of CH 3 OH, a solvent that can compete with the sulfoxide and suppress this binding mode, can retard the overoxidation and lead to higher selectivities for the sulfoxide product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Introducing Nonstructural Ligands to Zirconia-like Metal–Organic Framework Nodes To Tune the Activity of Node-Supported Nickel Catalysts for Ethylene Hydrogenation [Introducing Nonstructural Ligands to Zirconia-like MOF Nodes To Tune the Activity of Node-Supported Nickel Catalysts for Ethylene Hydrogenation]

Previous work has shown that introduction of hexafluoroacetylacetone (Facac) units as nonstructural ligands for the zirconia-like nodes of the eight-connected metal-organic framework (MOF), NU-1000, greatly alters the selectivity of node-supported oxy-nickel clusters for ethylene dimerization vs oligomerization. Here we i explore a related concept: tuning of support/catalyst interactions, and therefore, catalyst activity, via parallel installation of organic modifiers on the support itself. As modifiers we focused on para-substituted benzoates (R-BA – ; R = -NH 2 , -OCH 3 , -CH 3 , -H, -F, and -NO 2 ) where the substituents were chosen to present similar steric demand, but varying electron-donating or electron-withdrawing properties. R-benzoate-engendered shifts in the node-based aqua O-H stretching frequency for NU-1000, as measured by DRIFTS (diffuse-reflectance infrared Fourier-transform spectroscopy), together with systematic shifts in Ni 2p peak energies, as measured by X-ray photoelectron spectroscopy, show that the electronic properties of the support can be modulated. The vibrational and electronic peak shifts correlate with the putative electron-withdrawing vs electron-donating strength of the para-substituted benzoate modifiers. Subsequent installation of node-supported, oxy-Ni(II) clusters for ethylene hydrogenation yield a compelling correlation between log (catalyst turnover frequency) and the electron donating or withdrawing character of the substituent of the benzoate units. Single crystal X-ray diffraction measurements reveal that each organic modifier makes use of only one of two available carboxylate oxygens to accomplish grafting. The remaining oxygen atom is, in principle, well positioned to coordinate directly to an installed Ni(II) ion. We postulate that the unanticipated direct coordination of the catalyst by the node-modifier (rather than indirect modifier-based tuning of support(node)/catalyst electronic interactions) is the primary source of the observed systematic tuning of hydrogenation activity. Here we suggest, however, that regardless of mechanism for communication with active-sites of MOF-supported catalysts, intentional elaboration of nodes via grafted, nonstructural organic species could prove to be a valuable general strategy for fine-tuning supported-catalyst activity and/or selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Virtual sensor supervised learning for cyber-attack neutralization

An industrial asset may have monitoring nodes that generate current monitoring node values. A dynamic, resilient estimator may split a temporal monitoring node space into normal and one or more abnormal subspaces associated with different kinds of attack vectors. According to some embodiments, a neutralization model is constructed and trained for each attack vector using supervised learning and the associated abnormal subspace. In other embodiments, a single model is created using out-of-range values for abnormal monitoring nodes. Responsive to an indication of a particular abnormal monitoring node or nodes, the system may automatically invoke the appropriate neutralization model to determine estimated values of the particular abnormal monitoring node or nodes (e.g., by selecting the correct model or using out-of-range values). The series of current monitoring node values from the abnormal monitoring node or nodes may then be replaced with the estimated values.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Hierarchical effects facilitate spreading processes on synthetic and empirical multilayer networks

In this paper we consider the effects of corporate hierarchies on innovation spread across multilayer networks, modeled by an elaborated SIR framework. We show that the addition of management layers can significantly improve spreading processes on both random geometric graphs and empirical corporate networks. Additionally, we show that utilizing a more centralized working relationship network rather than a strict administrative network further increases overall innovation reach. In fact, this more centralized structure in conjunction with management layers is essential to both reaching a plurality of nodes and creating a stable adopted community in the long time horizon. Further, we show that the selection of seed nodes affects the final stability of the adopted community, and while the most influential nodes often produce the highest peak adoption, this is not always the case. In some circumstances, seeding nodes near but not in the highest positions in the graph produces larger peak adoption and more stable long-time adoption.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Checkpointing using compute node health information

A method is disclosed, as well as an associated apparatus and computer program product, for checkpointing using a plurality of communicatively coupled compute nodes. The method comprises acquiring health information for a first node of the plurality of compute nodes, and determining a first failure probability for the first node using the health information. The first failure probability corresponds to a predetermined time interval. The method further comprises selecting a second node of the plurality of compute nodes as a partner node for the first node. The second node has a second failure probability for the time interval. A composite failure probability of the first node and the second node is less than the first failure probability. The method further comprises copying checkpoint information from the first node to the partner node.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Identifying location of data granules in global virtual address space

An approach is disclosed that identifies a home node of a data granule. The process is performed by an information handling system (a local node) that retrieves a global virtual address directory. The global virtual address directory maps shared virtual addresses to a number nodes that includes the local node with one of the nodes being the home node. The shared virtual addresses correspond to a plurality of memory addresses that are stored in a shared virtual memory that is shared amongst the plurality of nodes. The approach receives a selected shared virtual address, retrieves, from the global virtual address directory, the home node associated with the selected shared virtual address, and accesses the data granule corresponding to the selected shared virtual address from the home node.

Johns, Charles R.↗

DOE OSTI2025

IM3 Projected U.S. Western Interconnection Grid Stress Dataset

This dataset provides projected grid stress and reliability results (including all model inputs and outputs from GO WEST and TEP) for Integrated Multisector, Multiscale Modeling (IM3) Phase 2 simulations across eight different scenarios for the U.S. Western Interconnection through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States from a set of Thermodynamic Global Warming (TGW) simulations. These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 GO WEST is an open-source power grid modeling framework for the U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It covers 28 balancing authorities (BAs) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of the U.S. Western Interconnection (ACTIVSg10k). Users can select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. TEP is an open-source transmission capacity expansion model, built on the GO WEST framework. It utilizes linear programming to optimize transmission capacity addition investment on existing lines within the GO WEST framework. The TEP model only increases the thermal capacity of existing transmission lines and does not add new lines to the system, which leaves the topology preserved. In order to use TEP model, users need to create scenarios with the GO WEST framework. Please refer to README file for a detailed description of the dataset including individual files and references.

Capacity Expansion Model↗