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At least 343 records · Page 19

Significance of hydrogen bonding networks in the proton-coupled electron transfer reactions of photosystem II from a quantum-mechanics perspective

The photosynthetic protein complex, photosystem II (PSII), conducts the light-driven water-splitting reaction with unrivaled efficiency. Proton-coupled electron transfer (PCET) reactions at the redox-active tyrosine residues are thought to play a critical role in the water-splitting chemistry. Addressing the fundamental question as to why the tyrosine residue, Y Z , is kinetically competent in comparison with a symmetrically placed tyrosine residue, Y D , is important for the elucidation of the mechanism of PCET in the water-splitting reaction of PSII. Here, using all-quantum-mechanical calculations we study PCET at the Y Z and Y D residues of PSII. We find that when Y Z is in its protein matrix under physiological conditions, the HOMO of Y Z constitutes the HOMO of the whole system. In contrast, the HOMO of Y D is buried under the electronic states localized elsewhere in the protein matrix and PCET at YD requires the transfer of the phenolic proton, which elevates the HOMO of Y D to being the HOMO of the whole system. This leads to the oxidation of Y D albeit on a slower timescale. Our study reveals that the key differences in the electronic structure of Y Z and Y D is primarily determined by the protonation state of the respective hydrogen-bonding partners, D1-His190 and D2-His189, or more generally by the H-bonding network of the protein matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of Alloy-Disorder-Induced Localization on Hole Diffusion in Highly Excited c -Plane and m -Plane (In, Ga) N Quantum Wells

The diffusion coefficient of holes can provide knowledge about carrier localization in (In, Ga)N, where the carrier dynamics are altered by randomly fluctuating potential landscape. In group-III nitrides, the diffusivity of holes is difficult to measure by electrical methods but it can be studied using optical techniques. Here, we investigate the dependence of the hole diffusion coefficient on direction and carrier density in c-plane and m-plane (In, Ga)N structures by employing the light-induced transient-grating technique. We show that the hole diffusion coefficient is anisotropic in the m-plane structure, where it is several times larger along the a crystallographic direction than along the c direction. Such anisotropy is observed within the broad range of carrier densities from 10 18 to 10 20 cm –3 . The diffusivity changes nonmonotonously with increasing photoexcitation, this dependence being different in thick and thin layers. We argue that an unexpectedly high diffusion coefficient at low carrier densities in thick quantum wells can be a signature of efficient hole transport via percolative paths occurring due to compositional disorder. In turn, a decrease of diffusivity with the excitation can reflect the effect of Coulomb blockade of these paths. Lastly, we demonstrate that disorder impacts carrier diffusivity even at carrier densities above 10 19 cm –3 , where the overflow of localized states must be included to explain the observed increase of the diffusion coefficient with the carrier density.

36 MATERIALS SCIENCE↗

Chiral-Symmetric Higher-Order Topological Phases of Matter

Herein, we introduce novel higher-order topological phases of matter in chiral-symmetric systems (class AIII of the tenfold classification), most of which would be misidentified as trivial by current theories. These phases are protected by “multipole chiral numbers,” bulk integer topological invariants that in 2D and 3D are built from sublattice multipole moment operators, as defined herein. The integer value of a multipole chiral number indicates how many degenerate zero-energy states localize at each corner of a system. These higher-order topological phases of matter are generally boundary-obstructed and robust in the presence of chiral-symmetry-preserving disorder.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗

Multisectoral analysis of drought impacts and management responses to the 2008–2015 record drought in the Colorado Basin, Texas

Abstract. Drought has long posed an existential threat to society. Engineering and technological advancements have enabled the development of complex, interconnected water supply systems that buffer societies from the impacts of drought, enabling growth and prosperity. However, increasing water demand from population growth and economic development, combined with more extreme and prolonged droughts due to climate change, poses significant challenges for governments in the 21st century. Improved understanding of the cascading multisectoral impacts and adaptive responses resulting from extreme drought can aid in adaptive planning and highlight key processes in modeling drought impacts. The record drought spanning 2008 to 2015 in the Colorado Basin in the state of Texas, United States, serves as an outstanding illustration to assess multisectoral impacts and responses to severe, multi-year drought. The basin faces similar water security challenges to those across the western US, such as groundwater depletion and sustainability, resource competition between agriculture and growing urban populations, limited options for additional reservoir expansion, and the heightened risk of more severe and frequent droughts due to climate change. By analyzing rich, high-quality data sourced from nine different local, state, and federal sources, we demonstrate that characterizing regional multisector dynamics is crucial to predicting and understanding future vulnerability and possible approaches to reduce impacts to human and natural systems in the face of extreme drought conditions. This review reveals that, despite the severe hydrometeorological conditions of the drought, the region's advanced economy and existing water infrastructure effectively mitigated economic and societal impacts.

54 ENVIRONMENTAL SCIENCES↗

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

Dynamic spin localization and γ -magnets

Here, we explore an unusual type of quantum matter that can be realized by qubits having different physical origins. Interactions in this matter are described by essentially different coupling operators for all qubits. We show that the simplest such models, which can be realized with localized states in Dirac materials, satisfy integrability conditions that we use to describe pseudospin dynamics in a linearly time-dependent magnetic field. Generalizing to an arbitrary number of qubits, we construct a spin Hamiltonian, which we call the γ -magnet. This system does not conserve polarization of any spin and the net spin polarization. Nevertheless, for arbitrarily strong interactions, nonadiabatic dynamics, and any initial eigenstate, we find that quantum interference suppresses spin flips. This behavior resembles many-body localization but occurs in phase space of many spins rather than real space. This effect may not have a counterpart in classical physics and can be a signature of a new type of spin ordering, which is different from both disordered spin glasses and ordered phases of spin lattices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The quantum Hall effect at a weak magnetic field

Using a weak limit for the hopping integral in one direction in the Hofstadter model, we show that the fermion states in the gaps of the spectrum are determined within the Kitaev chain. The proposed approach allows us to study the behavior of Chern insulators (CI) in different classes of symmetry. We consider the Hofstadter model on the square and honeycomb lattices in the case of rational and irrational magnetic fluxes ϕ, and discuss the behavior of the Hall conductance at a weak magnetic field in a sample of finite size. We show that in the semiclassical limit at the center of the fermion spectrum, the Bloch states of fermions turn into chiral Majorana fermion liquid when the magnetic scale (1/ϕ) is equal to the sample size N. We are talking about the dielectric–metal phase transition, which is determined by the behavior of the Landau levels in 2D fermion systems in a transverse magnetic field. When a magnetic scale, which determines the wave function of fermions, exceeds the size of the sample, a jump in the longitudinal conductance occurs. The wave function describes non-localized states of fermions, the sample becomes a conductor, the system changes from the dielectric state to the metallic one. It is shown, that at 1∕ϕ>N the quantum Hall effect and the Landau levels are not realized, which makes possibility to study the behavior of CI in irrational magnetic fluxes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

A comparison of building system parameters between affordable and market-rate housing in New York City

Low-income households in the United States experience higher than average energy burdens (defined as the proportion of household income spent on energy utilities), and many of these households struggle to simultaneously pay for rent, energy, and basic household necessities. The analysis presented here in this study examines whether the underlying characteristics of buildings and their energy systems could contribute to this disparity for affordable housing residents in New York City. It combines an energy audit dataset of 7,328 multifamily buildings with a database of properties receiving local, state, or federal housing subsidies. The results of this analysis indicate that the building-level installed equipment in large (greater than 50,000 square feet) affordable housing buildings in New York City is more efficient than that in market-rate buildings, but this trend largely disappears when considering overall building characteristics, such as location, size, or age. Significant differences in the types of systems installed in affordable and market-rate housing are also observed, as well as the types of energy efficiency recommendations made by energy auditors. However, these latter data were not normalized by building system characteristics, as that analysis is much more difficult to interpret for categorical data such as heating system type. These findings indicate that retrofit policies and building performance standards focused on affordable housing will likely need to account for underlying differences in building characteristics between affordable and market-rate housing to achieve intended impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Luminescence Quenching via Deep Defect States: A Recombination Pathway via Oxygen Vacancies in Ce-Doped YAG

Luminescence quenching via nonradiative recombination channels limits the efficiency of optical materials such as phosphors and scintillators and therefore has implications for conversion efficiency and device lifetimes. In materials such as Ce-doped yttrium aluminum garnet (YAG:Ce), quenching shows strong dependence on both temperature and activator concentration, limiting the fabrication of high-intensity white-light emitting diodes with high operating temperatures. Here, we reveal by means of first-principles calculations an efficient recombination mechanism in YAG:Ce that involves oxygen vacancies and gives rise to thermally activated concentration quenching. We demonstrate that the key requirements for this mechanism to be active are localized states with strong electron-phonon coupling. These conditions are commonly found for intrinsic defects such as anion vacancies in wide band gap materials. The present findings are therefore relevant to a broad class of optical materials and shine light on thermal quenching mechanisms in general.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An operator-based approach to topological photonics

Abstract Recently, the study of topological structures in photonics has garnered significant interest, as these systems can realize robust, nonreciprocal chiral edge states and cavity-like confined states that have applications in both linear and nonlinear devices. However, current band theoretic approaches to understanding topology in photonic systems yield fundamental limitations on the classes of structures that can be studied. Here, we develop a theoretical framework for assessing a photonic structure’s topology directly from its effective Hamiltonian and position operators, as expressed in real space, and without the need to calculate the system’s Bloch eigenstates or band structure. Using this framework, we show that nontrivial topology, and associated boundary-localized chiral resonances, can manifest in photonic crystals with broken time-reversal symmetry that lack a complete band gap, a result that may have implications for new topological laser designs. Finally, we use our operator-based framework to develop a novel class of invariants for topology stemming from a system’s crystalline symmetries, which allows for the prediction of robust localized states for creating waveguides and cavities.

97 MATHEMATICS AND COMPUTING↗

Ultrafast state-selective tunneling in two-dimensional semiconductors with a phase- and amplitude-controlled THz-scanning tunneling microscope

THz-pulse driven scanning tunneling microscopy (THz-STM) enables access to the ultrafast quantum dynamics of low-dimensional material systems at simultaneous ultrafast temporal and atomic spatial resolution. State-selective tunneling requires precise amplitude and phase control of the THz pulses combined with quantitative near-field waveform characterization. Here, we employ our state-of-the-art THz-STM with multi-MHz repetition rates, efficient THz generation, and precisely tunable THz waveforms to investigate a single sulfur vacancy in monolayer MoS2. We demonstrate that 2D transition metal dichalcogenides (TMDs) are an ideal platform for near-field waveform sampling by THz cross-correlation. Furthermore, we determine the THz voltage via QEV scans, which measure the THz rectified charge Q as a function of THz field amplitude E and dc bias Vdc. Mapping the complex energy landscape of localized states with a resolution down to 0.01 electrons per pulse facilitates state-selective tunneling to the HOMO and LUMO orbitals of a charged sulfur vacancy.

Materials Science↗

Phonon-Induced Localization of Excitons in Molecular Crystals from First Principles

The spatial extent of excitons in molecular systems underpins their photophysics and utility for optoelectronic applications. Phonons are reported to lead to both exciton localization and delocalization. However, a microscopic understanding of phonon-induced (de)localization is lacking, in particular, how localized states form, the role of specific vibrations, and the relative importance of quantum and thermal nuclear fluctuations. Here, we present a first-principles study of these phenomena in solid pentacene, a prototypical molecular crystal, capturing the formation of bound excitons, exciton-phonon coupling to all orders, and phonon anharmonicity, using density functional theory, the ab initio GW-Bethe-Salpeter equation approach, finite-difference, and path integral techniques. In this study, we find that for pentacene zero-point nuclear motion causes uniformly strong localization, with thermal motion providing additional localization only for Wannier-Mott-like excitons. Anharmonic effects drive temperature-dependent localization, and, while such effects prevent the emergence of highly delocalized excitons, we explore the conditions under which these might be realized

74 ATOMIC AND MOLECULAR PHYSICS↗

Ag-doped As–S–Se chalcogenide glasses: a correlative study of structural and dielectrical properties

This work is focused on investigating the effect of Ag doping on the dielectric and structural properties of the As–S–Se glass system and their suitability for potential applications in optoelectronics, such as electronic and switching components. A series of glasses from the system Agx(As40S30Se30)100-x (x = 5 at.% Ag) were prepared with melt-quenching technique. Morphological and compositional analysis was performed by scanning electron microscopy and energy-dispersive X-ray spectroscopy. Raman spectroscopy measurements have shown structural modifications of the glass network upon Ag doping, with creation of new Ag–(S,Se)–As structures, resulting in increased number of defect states. Variations in dielectric permittivity (e') and dielectric loss (e") were investigated in a wide frequency and temperature range, and explained by dominant dipolar and electronic polarization, as well as correlated with the observed structural changes. Improvement in dielectric properties is observed upon doping with Ag. Furthermore, the low dielectric tangent loss at high frequencies for all glassy samples points to a beneficial ability of the material to absorb energy of the external electric field. Good thermal stability of these glasses is confirmed by the calculated temperature coefficient of the dielectric permittivity. Density of localized states in all glasses was determined from AC conductivity and the dielectric tangent loss using a correlated barrier hopping model, and found to increase with Ag concentration. The overall results suggest that Ag doping enhances the electrical and optical quality of this type of glasses, making them suitable as nonlinear optical materials and their applications in devices.

36 MATERIALS SCIENCE↗

Metallic to hopping conduction transition in Ta{sub 2}O{sub 5−x}/TaO{sub y} resistive switching device

In this Letter, a comprehensive analysis of how the metallic behavior transition to hopping was presented by studying the transport mechanisms of low resistance states (LRS) in Ta{sub 2}O{sub 5−x}/TaO{sub y} resistive switching devices at very low temperatures. Three types of conduction behaviors were reported through temperature-dependent measurements ranging from 5 K to 250 K. Memory cells at low LRS show metallic behavior due to the formation of metallic filament. The temperature dependence of resistance at medium LRS exhibits an interesting phenomenon that a positive temperature coefficient transfers into a negative one at temperature of 20 K. Detailed analysis reveals that this phenomenon is caused by the coexistence of extended and localized states, with metallic conduction at higher temperatures and variable-range hopping at lower temperatures. Carrier transport at high LRS is dominated by electrons hopping conduction with nearest-neighboring hopping conduction changing into variable-range hopping as temperature decreases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Economic Impact of Permitting Timelines on Geothermal Power in California, Nevada, and Utah

The United States has great geothermal power potential; however, only a small fraction of this resource has been utilized for power generation. Various barriers, including technical, financial, and regulatory permit delays, are attributed to the lower penetration of geothermal energy into the national grid. Unpredictable environmental reviews and permitting timelines are some of the non-technical barriers that can cause delays in geothermal exploration and utilization plans. This document provides an assessment of the potential economic impact of permitting costs and timelines on geothermal power in California, Nevada, and Utah. Development of geothermal resources requires multi-layered regulatory permitting by local, state, and federal agencies. In this study, we collected and reviewed permit timelines and associated cost data for several existing geothermal power plants as well as for geothermal projects currently undergoing permitting processes for exploration and development activities in California, Nevada, and Utah. We interviewed several geothermal developers and staff from multiple permitting agencies to obtain insight from both sides (i.e., people applying for permits and people processing those applications for California Environmental Quality Act [CEQA] and National Environmental Policy Act [NEPA] reviews and other regulatory compliance). The intent of this project was also to identify informative pathways for the geothermal stakeholder community by which the permitting process could be streamlined.

15 GEOTHERMAL ENERGY↗

Estimating Return on Investment for Energy Technical Assistance Programs

The U.S. Department of Energy's Office of State and Community Energy Programs engaged the National Laboratory of the Rockies to assess the return on investment (ROI) of technical assistance (TA) programs that support state, local, and Tribal energy planning. Although TA delivers value through capacity building, stakeholder engagement, and knowledge transfer, these benefits are often intangible and challenging to monetize. This study reviews existing ROI frameworks and synthesizes the most relevant elements into a hybrid approach tailored to energy TA programs. The proposed framework integrates monetary and non-monetary outcomes through early logic model development, baseline data collection, and the use of proxies for intangible benefits. As a case study, this paper applies this approach to the Communities Local Energy Action Program (Communities LEAP), demonstrating how ROI can inform program design, data strategy, and performance assessment. Findings underscore that ROI should be applied selectively and planned from the outset to ensure data alignment and attribution accuracy. The framework offers TA practitioners a structured approach that can be leveraged for future programs to evaluate and communicate the multifaceted value of TA investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗