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Results for “Coordinate transformations”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Molecular structures of residual solvent in polyacrylonitrile based electrolytes: Implications for conductivity and stability

Lithium-ion batteries increasingly play significant roles in modern technologies; however, increased energy density also raises concerns about electrolyte safety. Traditional electrolytes that use volatile organic solvents face risks of thermal runaways and fires from electrode shorting. In response, polymer-based solid electrolytes have been developed for replacement. Polyacrylonitrile (PAN) is a promising fire-resistant component for electrolyte fabrication, but its limited solubility necessitates using low-volatility solvents, which are notoriously difficult to remove in subsequent drying processes. Here, we use femtosecond two-dimensional infrared spectroscopy to provide an in-depth understanding of how residual solvent from processing affects the molecular structures and dynamics within a polymer electrolyte. To this end, linear and nonlinear infrared spectroscopies are employed to interrogate the molecular interactions in PAN-based electrolytes containing various contents of N,N-dimethylformamide (DMF). We show that the amount of DMF within the PAN electrolyte affects the Li+ structure. Further, the coordination can proceed through the carbonyl group and/or the amide nitrogen to form antiparallel structures with the nitrile groups of PAN through dipole–dipole interactions. The free motion of DMF is drastically inhibited upon interaction with Li+ and PAN, which decreases the ionic conductivity and potentially affects the stability (resistance toward removal and chemical decomposition). These findings have implications for the design and processing of solid polymer electrolytes.

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

Evidence of a liquid–liquid transition in a glass-forming ionic liquid

A liquid–liquid transition (LLT) is a transformation from one liquid to another through a first-order transition. The LLT is fundamental to the understanding of the liquid state and has been reported in a few materials such as silicon, phosphorus, triphenyl phosphite, and water. Furthermore, it has been suggested that the unique properties of materials such as water, which is critical for life on the planet, are linked to the existence of the LLT. However, the experimental evidence for the existence of an LLT in many molecular liquids remains controversial, due to the prevalence and high propensity of the materials to crystallize. In this work, we show evidence of an LLT in a glass-forming trihexyltetradecylphosphonium borohydride ionic liquid that shows no tendency to crystallize under normal laboratory conditions. We observe a step-like increase in the static dielectric permittivity at the transition. Furthermore, the sizes of nonpolar local domains and ion-coordination numbers deduced from wide-angle X-ray scattering also change abruptly at the LLT. We independently corroborate these changes in local organization using Raman spectroscopy. The experimental access to the evolution of local order and structural dynamics across a liquid–liquid transition opens up unprecedented possibilities to understand the nature of the liquid state.

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

The five-point bootstrap

We study five-point correlation functions of scalar operators in d-dimensional conformal field theories. We develop a new approach to computing the five-point conformal blocks for exchanged primary operators of arbitrary spin by introducing a generalization of radial coordinates, using an appropriate ansatz, and perturbatively solving two quadratic Casimir differential equations. We then study five-point correlators 〈σσϵσσ〉 in the critical 3d Ising model. We truncate the operator product expansions (OPEs) in the correlator by including a finite number of primary operators with conformal dimension below a cutoff ∆ ⩽ ∆ cutoff . We then compute several OPE coefficients involving ϵ and two spinning operators by demanding that the truncated correlator approximately satisfies the crossing relation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Heterobimetallic multi-site concerted proton electron transfer (MS-CPET) promotes coordination-induced O–H bond weakening

Coordination-induced bond weakening of X–H bonds (X = O, N, C) has been observed in a number of low-valent transition metal compounds. However, the impact of an appended electron reservoir on the bond dissociation free energy of the O–H bond (BDFE O–H ) of a substrate bound to a d 0 metal is poorly understood. To gain insight into the ability of separated deprotonation and oxidation sites to decrease the BDFE O–H during proton-coupled electron transfer (PCET) reactions, a bimetallic system in which the sites of proton and electron loss are two distinct metal sites is described. Herein, the interconversion of tris(phosphinoamide) Zr/Co complexes HO–Zr(MesNP i Pr 2 ) 3 CoCN t Bu and O$≡$Zr(MesNP i Pr 2 ) 3 CoCN t Bu via hydrogen atom addition/abstraction was studied. Since the Zr center remains in the d 0 Zr IV state throughout these transformations, the electron transfer process is mediated by the appended redox-active Co 0/I center. A series of open-circuit potential (OCP) measurements on the HO–Zr(MesNP i Pr 2 ) 3 CoCN t Bu and O$≡$Zr(MesNP i Pr 2 ) 3 CoCN t Bu complexes was performed, from which the BDFE O–H was found to be 64 ± 1 kcal mol −1 . The BDFE O–H value was further verified through a series of stoichiometric H atom transfer reactions, stoichiometric protonation/deprotonation reactions, and computational studies.

Chemistry↗
DOE OSTI2020

Molecular Dynamics Simulation of the Structures, Dynamics, and Aggregation of Dissolved Organic Matter

Dissolved organic matter (DOM) plays a significant role in the transport and transformation of pollutants in the aquatic environment. However, the experimental characterization of DOM has been limited mainly to bulk properties, and the molecular-level interactions among various components of DOM remain to be fully characterized. In this study, we use molecular dynamics (MD) simulations to probe the structural properties of model DOM systems at atomic detail. The 200 ns simulations, validated by available experimental data, reveal processes and mechanisms by which chemical species (cations, peptides, lipids, lignin, carbohydrates, and some low-molecular-weight aliphatic and aromatic compounds) aggregate to form complex DOM. The DOM aggregates are dynamic, consisting of a hydrophobic core and amphiphilic exterior. The lipid tails and other hydrophobic fragments form the core, with hydrophilic and amphiphilic groups exposed to water, making DOM accessible to both polar and nonpolar species. Thus, the lipid component acts as a nucleator, whereas cations (especially Ca 2+ ) connect the molecular fragments on the surface by coordinating with the O-containing functional groups of DOM. The structural details revealed here provide new insights including surface accessible atoms, overall assemblage, and interactions among the molecules of DOM for understanding the kinetics and mechanisms through which DOM interacts with metal and other contaminants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Austenitic parent grain reconstruction in martensitic steel using deep learning

In this work we develop a deep convolutional architecture to estimate the prior austenite structure from observed martensite electron backscatter diffraction micrographs. A novel data augmentation strategy randomizes the global reference coordinate system which makes it possible to train our model from only four micrographs. The model is much faster than algorithmic approaches and generalizes well when applied to micrographs of a different material. Empirical evidence suggests the efficacy of the model depends on the scale of the microstructure and receptive field of the vision model. Furthermore, this work demonstrates that modern computer vision approaches are well suited for capturing complex spatial-orientation patterns present in orientation imaging micrographs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Elucidating the mechanism of photochemical CO 2 reduction to CO using a cyanide-bridged di-manganese complex

The complex, [{[Mn(bpy)(CO) 3 ] 2 }(μ-CN)] + (Mn 2 CN + ), has previously been shown to photochemically reduce CO 2 to CO. The detailed mechanism behind its reactivity was not elucidated. In this work, the photoevolution of this reaction is studied in acetonitrile (MeCN) using IR and UV-vis spectroscopy. Samples were excited into the Mn I → π* bpy metal-to-ligand charge transfer (MLCT) absorption band triggering CO loss, and rapid MeCN solvent ligation at the open coordination site. It is concluded that this process occurs selectively at the Mn axial ligation site that is trans to the C-end of the bridging cyanide. Upon further photolysis, the metal–metal bonded dimeric species, [(CO) 3 (bpy)Mn–Mn(bpy)(CO) 3 ] (Mn–Mn) is observed to form under anaerobic conditions. The presence of this dimeric species coincides with the observation of CO production. When oxygen is present, CO 2 photoreduction does not occur, which is attributed to the inability of Mn 2 CN + to convert to the metal–metal bonded dimer. Photolysis experiments, where the Mn–Mn dimer is formed photochemically under argon first and then exposed to CO 2 , reveal that it is the radical species, [Mn(bpy)(CO) 3 ˙] (Mn˙), that interacts with the CO 2 . Since the presence of Mn–Mn and light is required for CO production, [Mn(bpy)(CO) 3 ˙] is proposed to be a photochemical reagent for the transformation of CO 2 to CO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Steady-State Analysis of Microgrid Distributed Control Under Denial of Service Attacks

Distributed control is an effective method to coordinate multiple components in a microgrid. It usually has mandatory requirements for communication graph topology; changing the topology unexpectedly could disrupt the operation of a distributed controller. A denial of service (DoS) attack blocks communication channels to cause variations in communication graph. Unforeseen topology changes render a controller to receive incomplete system information. Control decisions made based on incorrect information can lead to significantly reduced grid supporting capability. As a result, the vital power balance between generation and load may be challenged. Determining power balance requires steady-state power flow analysis; however, the cyber-induced steady-state analysis is not well studied in the literature. Here, in this article, we show that a cyber–physical microgrid with unknown DoS attacks has augmented uncertain power flow equations, whose special structure creates new computational issue to determining power balance. To deal with the issue, we develop a novel cyber-induced microgrid model: the cyber–physical system is transformed into a pure physical model, where the disruption effects of DoS in the cyber layer are shown to be equivalent to the variations of the physical model parameters. With the transformed system, we develop a sufficient condition to ascertain the system power balance under unknown DoS attacks. In addition, practical insights for resilient distributed control design are shown as well.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Effect of surface acidity modulation on Pt/Al 2 O 3 single atom catalyst for carbon monoxide oxidation and methanol decomposition

With ideal metal utilization efficiency and homogeneous active sites, single atom catalysts (SACs) have attracted extensive attention in heterogeneous catalysis field. The performance of SACs is highly dependent on the local coordination environment of metal single atoms. However, few works reported the effect of surface acidity modification on the performance of SACs such as Pt SACs which have been widely studied nowadays. In this work, a Pt/Al 2 O 3 SAC has been successfully prepared using a bayerite Al(OH) 3 as support through simple IWI method for Pt loading. Through post-modification of Pt/Al 2 O 3 with acidic WO 3 and basic MgO, the surface acidity of Pt/Al 2 O 3 was tuned. Here, activity of CO oxidation and methanol decomposition on the modified catalysts has been evaluated. It was found that the catalytic performance was highly related to the surface acidity of Pt SACs. Basic MgO modified Pt/Al 2 O 3 performed better in CO oxidation under the reaction condition with H 2 O. Acidic WO 3 modified Pt/Al 2 O 3 showed superior activity in methanol decomposition. Detailed characterization and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) study suggested that the positive H 2 O effect on CO oxidation was due to the mitigated formation of bicarbonate species on Pt/Al 2 O 3 and WO 3 /Pt/Al 2 O 3 catalysts and the promoted desorption of carbonate species from MgO/Pt/Al 2 O 3 . The superior methanol decomposition performance on WO 3 /Pt/Al 2 O 3 was owing to its abundant oxygen vacancies and high resistance to carbonate accumulation. This study highlights the importance of surface acidity modulation of Pt SACs in heterogeneous catalysis and suggests that fine-tuning the surface acidity can be an effective strategy in new SACs development.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Keystone Solar Future Project (KSFP)

The Keystone Solar Future Project (KSFP, also referred to as “Keystone Project” in the report) implements a cost-effective, secure, reliable, and safe technology platform that paves the way for future interconnected distributed energy resources (DER), creates a framework that enables high penetration of DER, and transforms the DER interconnection process. The project is important and necessary in a few aspects. First, the industry definition of Distributed Energy Resource Management System (DERMS) is not yet validated against field deployments and mostly implemented in small pilots relying on third party integration. Keystone project implements a direct plug and play communication to inverter based DER systems. Secondly, most interconnection application portal is not yet fully integrated with back-end system, thus lacks the capability to drive a complete and accurate modeling of DER assets into the planning and operational systems. Keystone project rolled out a fully integrated modeling process of DERs from interconnection to operational management. Lastly, customers were given an opportunity to learn about the advanced functions of the inverters and take full advantages of their benefits through participation in the pilot program. During the project, the technical effectiveness and economic feasibility of DER management were investigated and demonstrated in real life events and simulation studies. The project highlighted the importance of coordinated DER interconnection, installation and management with the rest of the distribution system.

14 SOLAR ENERGY↗
DOE OSTI2026

Custom-trained Machine-learning Interatomic Potentials: ZnCl2 Aqueous Solution

This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗
DOE OSTI2021

Individual and Collective Strategies to Limit the Impacts of Large Power Outages of Long Duration

As modern society becomes ever more dependent on the availability of electric power, the costs that could arise from individual and social vulnerability to large outages of long duration (LLD-outages) increases. During such an outage, even a small amount of power would be very valuable. Here, this article compares individual and collective strategies for providing limited amounts of electric power to residential customers in a hypothetical New England community during a large electric power outage of long duration. We develop estimates of the emergency load required for survival and assess the cost of strategies to address outages that last 5, 10, and 20 days in either winter or summer. We find that the cost of collective solutions could be as much as 10 to 40 times less than individual solutions (less than $2 per month per home). However, collective solutions would require community-wide coordination, and if local distribution system lines are destroyed, only individual back-up systems could provide contingency power until those lines are repaired. Costs might be reduced if more robust distributed generation were employed that could be operated continuously with the ability to sell power back to the grid. Our cost-effectiveness analysis only assesses what could be done, developing estimates of preparedness cost. A decision about what should be done would require additional input from a range of stakeholders as well as some form of analytical deliberative process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Managing Hanford's Direct Feed Low Activity Waste Program - 20002

The Office of River Protection (ORP) is responsible for the management and completion of the River Protection Project (RPP) mission, which comprises both the Hanford Site tank farms operations and the completion and operation of the Waste Treatment and Immobilization Plant Project. The RPP mission is to safely retrieve, treat, and immobilize Hanford's high-level and low-activity tank waste and close the tank farms to protect the Columbia River. The Direct-Feed Low-Activity Waste (DFLAW) Program is a major subset of the overall RPP mission, providing disposition of low-activity waste. The scope is to retrieve, treat, and immobilize the low-activity waste at the Low-Activity Waste Facility. DFLAW will begin operations no later than December 2023. The DFLAW Program overarches a suite of individual projects, activities, and infrastructure upgrades. The major projects and activities include multiple contractors under both ORP and the Richland Operations Office, underscoring the need for effective integration, coordination, and collaboration. The objectives of the DFLAW Program leadership team are to: - Effectively coordinate and integrate the projects that comprise the DFLAW Program - Manage the interfaces between the projects so that the integrated DFLAW Program is completed successfully - Ensure the DFLAW portfolio of projects operate as required without gaps or conflicts at the interfaces. DOE is accomplishing these objectives through a newly established leadership model that integrates the DOE and contractor work streams and promotes a teamwork model to enable collaborative success. Long considered one of the most formidable cleanup challenges at Hanford, the Department of Energy and its contractors are on the verge of achieving a cleanup commitment that has been decades in the making. DOE is preparing to vitrify (turn to glass) Hanford's chemical and radioactive tank waste using the DFLAW process. The Modified Consent Decree milestone for completing hot commissioning of the Hanford Site's Low- Activity Waste Facility is Dec. 31, 2023. While this milestone may seem distant under normal project management circumstances, it is a relatively short period of time for the operational and cultural transformation necessary to successfully begin treating tank waste at Hanford. Direct feed means separating the waste at a tank farm to remove the more radioactive portion (i.e., solids and cesium) so that the resulting low-activity (less radioactive) waste can be fed directly to the Waste Treatment and Immobilization Plant's Low-Activity Waste Facility. Starting DFLAW will require a singular, intensive leadership focus, along with a sustained, collective commitment to excellence and teamwork by the Department and its contractors. Major upgrades to Hanford's infrastructure will occur prior to startup. Supporting DFLAW operations requires significant integration between the DFLAW facilities - the Waste Treatment Plant, Hanford's tank farms, effluent treatment facilities, disposal facilities - and between all of the site contractors to achieve success. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Cosolvent-tuned interactions in ionic liquids: A vibrational and quantum-chemical study of ethylene glycol ratio effects

Ionic liquids (ILs) are attractive media for CO 2 capture but remain limited by viscosity and cost. Blending ILs with ethylene glycol (EG) is a practical route to mitigate these constraints, yet the molecular origins of cosolvent effects and their dependence on composition are not well resolved. We combine Fourier-transform infrared (FT-IR) spectroscopy with quantum-chemical (DFT) analysis to elucidate how the IL:EG molar ratio modulates intermolecular interactions and electronic structure. Computed vibrational frequencies enable mode assignment and deconvolution of overlapping bands, revealing systematic, ratio-dependent shifts and broadenings in (i) EG O–H stretching, (ii) cation and EG C–H stretchings (imidazolium C2–H, C4–H, C5–H, methyl and ethyl groups, -CH2 of EG), (iii) anion signature modes (e.g., CN motifs), and (iv) EG C–O and C–C stretchings, consistent with the redistribution of hydrogen-bonding networks. Molecular electrostatic potential (MESP) maps quantify attenuation of extreme potential regions with increasing EG, indicating progressive screening of cation–anion electrostatic interactions. Quantum Theory of Atoms in Molecules (QTAIM) identifies emergent bond critical points between EG and the IL ions, while Reduced Density Gradient–Noncovalent Interaction (RDG–NCI) analysis differentiates strong directional hydrogen bonds from dispersive contacts across compositions. Together, these results show that EG fraction controls a switch from predominantly ion–ion to mixed ion–EG coordination, altering local polarity and polarizability that underlie the observed FT-IR trends. The framework provides composition–structure–spectrum relationships that can guide rational selection of IL:EG ratios to balance favorable molecular interactions with practical performance targets in scalable CO 2 capture systems.

DAC↗
DOE OSTI2023

Evidence of Atypical Structural Flexibility of the Active Site Surrounding of an [FeFe] Hydrogenase from Clostridium beijerinkii

[FeFe] hydrogenase from Clostridium beijerinkii (CbHydA1) is an unusual hydrogenase in that it can withstand prolonged exposure to O 2 by reversibly converting into an O 2 -protected, inactive state (Hinact). It has been indicated in the past that an atypical conformation of the “SC 367 CP” loop near the [2Fe] H portion of the six-iron active site (H-cluster) allows the Cys367 residue to adopt an “off-H + -pathway” orientation, promoting a facile transition of the cofactor to Hinact. Here, we investigated the electronic structure of the H-cluster in the oxidized state (H ox ) that directly converts to Hinact under oxidizing conditions and the related CO-inhibited state (H ox -CO). We demonstrate that both states exhibit two distinct forms in electron paramagnetic resonance (EPR) spectroscopy. The ratio between the two forms is pH-dependent but also sensitive to the buffer choice. Our IR and EPR analyses illustrate that the spectral heterogeneity is due to a perturbation of the coordination environment of the H-cluster’s [4Fe4S] H subcluster without affecting the [2Fe] H subcluster. Overall, we conclude that the observation of two spectral components per state is evidence of heterogeneity of the environment of the H-cluster likely associated with conformational mobility of the SCCP loop. Such flexibility may allow Cys367 to switch rapidly between off- and on-H + -pathway rotamers. Consequently, we believe such structural mobility may be the key to maintaining high enzymatic activity while allowing a facile transition to the O 2 -protected state.

08 HYDROGEN↗
DOE OSTI2024

Transmission Interconnection Roadmap: Transforming Bulk Transmission Interconnection by 2035

The U.S. electricity system is amid a rapidly occurring and widespread energy transition. Regional, Tribal, state, and customer demand for new energy resources, combined with favorable policies, is driving a rapid rise of interconnection requests. Interconnection processes will need to evolve to handle this larger number of requests today and into the future, as policy and economic drivers continue to motivate significant resource development. This roadmap identifies and organizes nearer- and longer-term solutions to enable transmission interconnection processes to meet this expected demand, and it is intended for a diverse audience of stakeholders participating within transmission interconnection processes. The roadmap is a result of the Interconnection Innovation e-Xchange (i2X) program launched by the U.S. Department of Energy (DOE) in June 2022 to convene stakeholders and address interconnection challenges. The roadmap is organized into four primary goal areas, each important to the overall i2X mission to enable a simpler, faster, and fairer interconnection of clean energy resources while enhancing the reliability, resiliency, and security of our electric grid. The first goal aims to improve interconnection data transparency, to aid interconnection customers’ ability to screen and site potential projects, better enable third-party modeling, facilitate more process automation, enhance competition while ensuring equitable outcomes, and enable benchmarking, tracking, and auditing of interconnection processes and reforms. The second goal covers solutions to improve queue management practices, affected system studies, fair processes, and workforce development. The third goal incorporates solutions that aim to improve cost allocation, reduce costs to electricity consumers, enhance the coordination between transmission planning and the interconnection process, and optimize the rightsizing of transmission investment through improvements in interconnection studies. The fourth and final goal aims to reduce the performance issues not identified during interconnection studies by updating technical requirements within interconnection studies, models, and tools while also improving industry interconnection standards.

24 POWER TRANSMISSION AND DISTRIBUTION↗