Theoretical Insights into H 2 Activation over Anatase TiO 2 Supported Metal Adatoms
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The synthesis of a piano-stool ruthenium hydride, [(η 5 -C 5 Me 5 )Ru(PmIm)H] (PmIm = (N-(1,3,5-trimethylphenyl)-1-(pyrimidin-2-yl)ethan-1-imine) for the dual purpose of catalytic dihydrogen activation and subsequent hydrogen atom transfer for the formation of weak chemical bonds is described. Introduction of a neutral, potentially redox-active PmIm supporting ligand was designed to eliminate the possibility of deleterious C(sp 2 )–H reductive coupling and elimination that has been identified as a deactivation pathway with related rhodium and iridium catalysts. Treatment of [(η 5 -C 5 Me 5 )RuCl 2 ] n with one equivalent PmIm ligand in the presence of zinc and sodium methoxide resulted in isolation of the diruthenium complex, [(η 5 -C 5 Me 5 )Ru(PmIm)] 2 , arising from C–C bond formation between two PmIm chelates. Addition of H 2 to the ruthenium dimer under both thermal and blue light irradiation conditions furnished the targeted hydride, [(η 5 -C 5 Me 5 )Ru(PmIm)H] which has a relatively weak DFT-calculated Ru–H bond dissociation free energy (BDFE) of 47.9 kcal/mol. Addition of TEMPO to [(η 5 -C 5 Me 5 )Ru(PmIm)H] generated the 17-electron metalloradical, [(η 5 -C 5 Me 5 )Ru(PmIm)], which was characterized by EPR spectroscopy. The C–C bond forming process was reversible as irradiation of [(η 5 -C 5 Me 5 )Ru(PmIm)] 2 generated [(η 5 -C 5 Me 5 )Ru(PmIm)H] and a piano-stool ruthenium complex containing an enamide ligand derived from H-atom ab-straction from the PmIm chelate. Equilibration studies were used to establish an experimental estimate of the effective Ru–H BDFE and a value of 50.8 kcal/mol was obtained, in agreement with the observed loss of H 2 and the DFT-computed value. Here, the ruthenium hydride was an effective catalyst for the thermal catalytic hydrogenation of TEMPO, acridine and a cobalt-imido complex and for the selective reduction of azobenzene to diphenylhydrazine using H 2 as the terminal reductant, highlighting the role of this complex is catalytic weak bond formation using H 2 as the stoichiometric reductant.
Human manganese superoxide dismutase (MnSOD) plays a crucial role in controlling levels of reactive oxygen species (ROS) by converting superoxide (O$^{•–}_{2}$) to molecular oxygen (O 2 ) and hydrogen peroxide (H 2 O 2 ) with proton-coupled electron transfers (PCETs). A key catalytic residue, Tyr34, determines the activity of human MnSOD and also becomes post-translationally inactivated by nitration in various diseases associated with mitochondrial dysfunction. Tyr34 has an unusual pK a due to its proximity to the Mn metal and undergoes cyclic deprotonation and protonation events to promote the electron transfers of MnSOD. Neutron diffraction, X-ray spectroscopy, and quantum chemistry calculations in oxidized, reduced and product inhibited enzymatic states shed light on the role of Tyr34 in MnSOD catalysis. The data identify the contributions of Tyr34 in MnSOD activity that support mitochondrial function and give a thorough characterization of how a single tyrosine modulates PCET catalysis. Product inhibition occurs by an associative displacement mechanism.
Governments procure renewables through a variety of mechanisms. Contracts for difference (CfDs) have been used for more than 50% of the global offshore wind supply. The payments awarded through CfDs are sometimes labelled subsidies, suggesting that they support uneconomic activity. Here, in this study, we argue that the primary role of CfDs is rather risk management by creating a market for electricity supply at stable long-term prices. Similar to its use in other sectors of the economy, this contract type transforms a variable to a fixed price to reallocate volatility risks. Such long-term contracts are often necessary for renewables financing due to limited hedging options in existing markets. Our perspective could imply a shift in perception towards CfDs as a fundamental and lasting market feature. We hope to stimulate a timely discussion about the impact of greater CfD diffusion on electricity market mechanisms, risk allocation and the potential for combining fragmented streams of energy finance, market and policy research.
Abstract Touch-like phantom limb sensations can be elicited through targeted transcutaneous electrical nerve stimulation (tTENS) in individuals with upper limb amputation. The corresponding impact of sensory stimulation on cortical activity remains an open question. Brain network research shows that sensorimotor cortical activity is supported by dynamic changes in functional connections between relevant brain regions. These groups of interconnected regions are functional modules whose architecture enables specialized function and related neural processing supporting individual task needs. Using electroencephalographic (EEG) signals to analyze modular functional connectivity, we investigated changes in the modular architecture of cortical large-scale systems when participants with upper limb amputations performed phantom hand movements before, during, and after they received tTENS. We discovered that tTENS substantially decreased the flexibility of the default mode network (DMN). Furthermore, we found increased interconnectivity (measured by a graph theoretic integration metric) between the DMN, the somatomotor network (SMN) and the visual network (VN) in the individual with extensive tTENS experience. While for individuals with less tTENS experience, we found increased integration between DMN and the attention network. Our results provide insights into how sensory stimulation promotes cortical processing of combined somatosensory and visual inputs and help develop future tools to evaluate sensory combination for individuals with amputations.
Copper clusters feature prominently in both metalloenzymes and synthetic nanoclusters that mediate catalytic redox transformations of gaseous small molecules. Such reactions are critical to biological energy conversion and are expected to be crucial parts of renewable energy economies. However, the precise roles of individual metal atoms within clusters are difficult to elucidate, particularly for cluster systems that are dynamic under operating conditions. Here, we present a metal site-specific analysis of synthetic Cu 4 (μ 4 -S) clusters that mimic the Cu Z active site of the nitrous oxide reductase enzyme. Leveraging the ability to obtain structural snapshots of both inactive and active forms of the synthetic model system, we analyzed both states using resonant X-ray diffraction anomalous fine structure (DAFS), a technique that enables X-ray absorption profiles of individual metal sites within a cluster to be extracted independently. Using DAFS, we found that a change in cluster geometry between the inactive and active states is correlated to Cu site differentiation that is presumably required for efficient activation of N 2 O gas. More precisely, we hypothesize that the Cu δ+ ∙∙∙Cu δ- pairs produced upon site differentiation are poised for N 2 O activation, as supported by computational modeling. These results provide an unprecedented level of detail on the roles of individual metal sites within the synthetic cluster system and how those roles interplay with cluster geometry to impact the reactivity function. We expect this fundamental knowledge to inform understanding of metal clusters in settings ranging from (bio)molecular to nanocluster to extended solid systems involved in energy conversion.
Two-dimensional transition metal carbides and nitrides (MXenes) with layered structure and high conductivity have been effectively utilized in various energy materials, including as a catalytic support of MgH 2 for hydrogen storage. However, the terminal groups formed on the surface during the etching step tend to deactivate reactive Mg metal and add dead mass, thereby deteriorating the catalytic role of MXene in hydrogen sorption of Mg. For this work, we exploited a molten-salt derived MXene with easily modifiable –Cl terminations, compared to conventional –O, –OH and –F groups, and synthesized a composite of Mg and delaminated Ti 2 CCl x MXene to improve the hydrogen storage performance of Mg through charge transfer. This strategy enables the formation of an intimate interface between Mg and MXene, facilitating charge transfer and thereby boosting the catalytic effect. The resulting composite demonstrates significantly enhanced hydrogen sorption kinetics by modulating Mg–H bond strength. This novel approach of modifying surface terminations leverages the unique properties of MXene as a superior support for active materials, offering broader applications in energy materials.
Investigation of the reactivity of the redox-active molybdenum oxide cluster, Cp$^{*}_{2}$Mo 2 O 4 , toward low-valent uranium (Cp$^{*}_{2}$U(bpy), bpy = 2,2'-bupyridine) is reported. Here, structural and spectroscopic analyses provide insight into the interactions of the actinide and metalloligand in the product, [(Cp$^{*}_{2}$Mo 2 O 4 )Cp$^{*}_{2}$U]. Reactivity studies reveal the metalloligand functions as a redox reservoir for uranium.
In November 2022, the HEP Software Foundation and the Institute for Research and Innovation for Software in High-Energy Physics organized a workshop on the topic of Software Citation and Recognition in HEP. The goal of the workshop was to bring together different types of stakeholders whose roles relate to software citation, and the associated credit it provides, in order to engage the community in a discussion on: the ways HEP experiments handle citation of software, recognition for software efforts that enable physics results disseminated to the public, and how the scholarly publishing ecosystem supports these activities. Reports were given from the publication board leadership of the ATLAS, CMS, and LHCb experiments and HEP open source software community organizations (ROOT, Scikit-HEP, MCnet), and perspectives were given from publishers (Elsevier, JOSS) and related tool providers (INSPIRE, Zenodo). This paper summarizes key findings and recommendations from the workshop as presented at the 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023).
Nuclear forensics is an essential activity in support of national counter-nuclear smuggling operations, as it can be used to provide unique and useful data to law enforcement for the prosecution of criminal nuclear smugglers and traffickers. Nuclear forensics can also be used to determine the origin of nuclear materials that have fallen out of regulatory control, allowing for the identification of weaknesses and vulnerabilities in the safeguarding of nuclear materials, while also generating a deterrent effect through attribution to the legal and responsible owners of nuclear materials out of regulatory control. This article describes the benefits of a nuclear forensics capability to any country in possession of nuclear materials, and describes how nuclear forensics can support an investigation into the origin of interdicted nuclear materials, using a case study of a nuclear materials interdiction in Australia to describe how nuclear forensics works in practice.
Hybridizing a hydropower plant with a battery energy storage system is often a very expensive decision. So to make the case for feasibility of hybridization the cost benefit analysis must be comprehensive. Most literature found on this subject only uses one out of many different available value streams to carry out a feasibility analysis. To that end, in this study we propose a multi-objective optimization formulation and a mixed-integer quadratic programming optimization engine that considers multiple different value streams and optimizes hydro-battery hybrid system paired operations to maximize revenue generated from energy arbitrage while simultaneously minimizing the total hydro turbine mileage thus reducing turbine starts and stops and improving turbines life all while following all environmental constraints and not violating any limitations either regulatory or preferential (i.e., to support recreational activities like white water rafting, etc.). In this study we also implemented the developed optimization methodology to a real-world case study of Bagnell dam hydropower facility (8 units totaling 240 MW rated power capacity) which is owned and operated by our industry partner Ameren Energy Inc. The case study outcomes shows that by hybridizing the Bagnell dam hydropower facility with a 60 MW x 2-hr battery energy storage system, the annual benefits can be increased over \$6 million while reducing the annual mileage averaged per turbine and number of start/stops by over 98\% and 85\% respectively.
The raw data (metagenomes and metatranscriptomes) for this study are available in the Joint Genomes Institute Genome Portal (https://genome.jgi.doe.gov/portal/ Project ID 503249) with projects designated by year and product type. The MAG genomes analyzed in this paper are available on NCBI, as bioproject PRJNA800073. Plants and microorganisms form beneficial associations. Understanding plant-microbe interactions will inform microbiome management to enhance crop productivity and resilience to stress. Here, we apply a genome-centric approach to identify ecologically important leaf microbiome members on field-grown switchgrass and miscanthus and to quantify their activities for switchgrass over two growing seasons. We integrate metagenome and metatranscriptome sequencing from 192 leaf samples collected over representative time points in crop phenology. We curated 40 medium- and high-quality metagenome-assembled-genomes (MAGs) and focused analysis on seasonal transcript recruitment to them. Classes represented by these focal MAGs (Actinomycetia, Alpha- and Gamma- Proteobacteria, and Bacteroidota) were active and had increases in transcripts for short-chain dehydrogenase, molybdopterin oxidoreductase, and polyketide cyclase in the late season. The majority of MAGs had activated stress-associated pathways, including trehalose metabolism, indole acetic acid degradation, betaine biosynthesis, and reactive oxygen species degradation, suggesting direct engagement with the host environment. We also detected seasonally activated biosynthetic pathways for terpenes (carotenoids and isoprenoids) and for various non-ribosomal peptide pathways that were poorly annotated. Overall, this study overcame laboratory and bioinformatic challenges associated with field-based leaf metatranscriptome analysis to inform both general and likely specialized activities of these phyllosphere populations. These activities collectively support that leaf-associated bacterial populations are seasonally dynamic, responsive to host cues, and interactively engage in feedback with the plant. This analysis represented quality filtering of metagenomes and metatranscriptomes (data-preparation folder), metagenome assemblies (metagenome-assembly folder) and metagenome-assembled genome binning, curation, refinement, annotation (mag-evaluation folder). Abundances of sequencing libraries were calculated based on reads mapped (mapping folder). Additionallly, analysis of our annotated results are also included (analysis folder).
The RadSource MR system leverages Meta Quest 3's advanced mixed reality capabilities to create a comprehensive spatial planning platform for end-of-life sealed radioactive source recovery operations. The application utilizes the Quest 3's high-resolution passthrough cameras and spatial mapping algorithms to generate accurate 3D environmental models. Core technical components include: (1) Real-time spatial measurement algorithms calculating distances, angles, slopes, and surface areas with sub-centimeter accuracy; (2) Virtual object placement system allowing users to position digital representations of recovery equipment (trailers, containment vessels, protective barriers) within the real environment; (3) Voice recording and annotation system for hands-free documentation in protective equipment; (4) 3D mesh capture and storage capabilities for post-operation analysis and regulatory documentation. (5) Procedure documentation is available for viewing in Mixed Reality, providing an innovative and convenient way to access the information during pre-visit and inspection activities. (6) Support for screen capture for the view for real world and virtual objects together to use it later for planning. The system integrates computer vision techniques for environmental understanding, spatial mathematics for precise measurements, and human-computer interaction principles optimized for hazardous environment operations. Data persistence allows teams to save and share planning sessions across multiple stakeholders while maintaining operational security requirements.
DistOPF is an open-source Python package providing a three-phase, asymmetric optimal power flow (OPF) tool specifically designed for distribution systems. The key inventive features include: - Asymmetrical 3-phase OPF modeling for distribution systems with unbalanced phases - Comprehensive control optimization supporting both active (P) and reactive (Q) power control variables - Built-in visualization and validation tools - Standard test system benchmarking platform for algorithm development and comparison - Modular CSV-based input system using Pandas DataFrames for flexible model specification - Standard power distribution model importer enabling direct conversion from CIM and OpenDSS format to optimization-ready models - Multiple solve interface compatibility (PYOMO, CVXPY, SciPy) with automatic solver selection based on problem type
Abstract Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.
This report is a condensed version of previous reports identifying technical gaps that, if addressed, could be used to ensure the continued safe storage of SNF for extended periods and support licensing activities. This report includes updated gap priority assessments because the previous gap priorities were based on R&D performed through 2017. Much important work has been done since 2017 that requires a change in a few of the priority rankings to better focus the near-term R&D program. Background material, regulatory positions, operational and inventory status, and prioritization schemes are discussed in detail in Hanson et al. (2012) and Hanson and Alsaed (2019) and are not repeated in this report. One exception is an overview of the prioritization criteria for reference. This is meant to give the reader an appreciation of the framework for prioritization of the identified gaps. A complete discussion of the prioritization scheme is provided in Hanson and Alsaed (2019).
The National Renewable Energy Laboratory (NREL), in partnership with ORNL, under the Clean Energy Manufacturing Analysis Center (CEMAC www.manufacturingcleanenergy.org) umbrella, assessed the current state of existing and low-GWP refrigerants for major end-use applications, including HVAC and those outside of the HVAC industry. The project incorporated a market overview, and supply chain assessment to determine the production, distribution, consumption, costs, and potential operating efficiency impacts of new and alternative refrigerants entering the market. Market trends and ongoing research are also documented. This work supplements other DOE efforts to support research activities on refrigerants and their applications including a refrigerant R&D roadmap and outlook into global air conditioning markets (Goetzler et al. 2014, 2016).