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At least 307 records · Page 17

The Standard Model from String Theory: What Have We Learned?

Amid all candidates of physics beyond the Standard Model, string theory provides a unique proposal for incorporating gauge and gravitational interactions. In string theory, a four-dimensional theory that unifies quantum mechanics and gravity is obtained automatically if one posits that the additional dimensions predicted by the theory are small and curled up—a concept known as compactification. The gauge sector of the theory is specified by the topology and geometry of the extra dimensions, and the challenge is to reproduce all of the features of the Standard Model of particle physics from them. We review the state of the art in reproducing the Standard Model from string compactifications and summarize the lessons drawn from this fascinating quest. We describe novel scenarios and mechanisms that string theory provides to address some of the Standard Model puzzles as well as the most frequent signatures of new physics that could be detected in future experiments. We then comment on recent developments that connect, in a rather unexpected way, the Standard Model with quantum gravity and that may change our field theory notion of naturalness.

Physics↗

Electrochemical Characterization of Bromine Reduction to Tribromide in Individual Nitrobenzene-in-Water Emulsion Droplets

We report an electrochemical study of bromine reduction to tribromide in a single nitrobenzene (NB) droplet during a single collision event. The feasibility of this study is based on the favorable distribution of Br 2 in NB rather than in water, which was demonstrated by voltammetry at the NB/water interface. The NB-in-water emulsions containing the ionic liquids trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)amide (ILPA) as the supporting electrolyte and sodium dodecyl sulfate (SDS) as the surfactant were prepared by a high-power ultrasonication. Its single droplet as an attoliter reactor, colliding on a 25 μm Pt UME, was monitored by chronoamperometry. The spike-type current transients of Br 2 reduction can elucidate the size and size distribution of NB, and measure the diffusion in the droplet as analyzed by a bulk electrolysis model. The frequency of collisions can provide diffusion coefficient of the droplets to the UME. Moreover, the i-t decay behavior can be simulated, which fits well with the experimental one.

25 ENERGY STORAGE↗

Electrolyte Solvation and Ionic Association: Part IX. Structures and Raman Spectroscopic Characterization of LiFSI Solvates

The bis(fluorosulfonyl)imide anion N(SO 2 F) 2 ⁻ (i.e., FSI⁻) (also referred to as bis(fluorosulfonyl)amide (i.e., FSA-) and imidodi(sulphuryl fluoride)) has attracted tremendous interest in recent years for its utility in both lithium salts and ionic liquids for battery electrolyte applications. To facilitate the understanding of the characteristics of this anion, crystal structures are reported here for the uncoordinated anion in LiFSI-based solvates with cryptand CRYPT-222 and tetraglyme (G4). These crystalline solvates were analyzed by Raman spectroscopy to aid in assigning the Raman bands to the modes of ion coordination found in liquid electrolytes. These structures, as well as a thorough review of other relevant crystallographic data, provide insights into the rather remarkable properties of the FSI- anion with regard to solvate formation and electrolyte properties.

25 ENERGY STORAGE↗

Dynamic Disruption Resilience in Intermodal Transport Networks: Integrating Flow Weighting and Centrality Measures

Resilient intermodal freight networks are vital for sustaining supply chains amid increasing threats from natural hazards and cyberattacks. Transportation resilience has been widely studied; understanding how random and targeted disruptions affect structural connectivity and functional performance remains a key challenge. To address this, this study evaluates the robustness of the US intermodal freight network, which consists of rail and water modes, using a simulation-based framework that integrates graph-theoretic metrics with flow-weighted centrality measures. Disruption scenarios are examined, including random failures as well as targeted node and edge removals based on static and dynamically updated degree and betweenness centrality. To reflect more realistic conditions, flow-weighted degree centralities (WDC) and partial node degradation are considered. Two resilience indicators are used: (1) the size of the giant connected component to measure structural connectivity; and (2) flow-weighted network efficiency (NE) to assess freight mobility under disruption. The results show that progressively degrading nodes ranked by WDC to 60% of their original functionality causes a sharper decline in normalized NE, for up to approximately 45 affected nodes, than complete failure (100% loss of functionality) applied to nodes targeted by weighted betweenness centrality or selected at random. This highlights how partial degradation of high-tonnage hubs can produce disproportionately large functional losses. The findings emphasize the need for resilience strategies that go beyond network topology to incorporate freight flow dynamics.

42 ENGINEERING↗

Structuring, stochastic behavior, and charge storage capacity of redox-active microemulsions formulated with mixtures of toluene and ionic liquid as oil phase

Oil/water microemulsions (µEs) are promising electrolytes for redox flow batteries (RFBs) as they simultaneously improve charge capacity and ionic conductivity. Here, we report the successful formulation of bicontinuous µEs where the oil phase is a solution of trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)amide ionic liquid in toluene with redox-active ferrocene. We examined the effect of supporting electrolyte anion (NO 3 – , Cl – , ClO 4 – ) on the structure, reactivity, transport, and electrolytic performance of redox-active µEs. Neutron scattering and nuclear magnetic resonance showed that the domain size increased as Cl – > NO 3 – > ClO 4 – while the ferrocene diffusion coefficient increased as NO 3 – > Cl – > ClO 4 – . Scanning electrochemical microscopy indicated anion-dependent current fluctuations during electrolysis, with ClO 4 – exhibiting the least high-frequency oscillations, which correlate to the highest charge and discharge capacity and reversibility. All ionic liquid containing systems improved the performance of toluene-based µEs, highlighting new design principles for these electrolytes.

diffusion↗

Analysis strategy for ultrafast X-ray photon correlation spectroscopy

We explain an analysis strategy for ultrafast X-ray photon correlation spectroscopy, a technique enabled by X-ray free electron lasers to probe nano- and atomic-scale dynamics in complex systems on nanosecond timescales or faster. Central to the technique is the methodology for extracting contrast in coherent X-ray diffraction patterns, known as speckle patterns. Guided by simulations, we analyze common challenges and examine errors encountered in contrast extraction. A method for accurately determining contrast amid shot noise across a wide range of count rates is presented.

36 MATERIALS SCIENCE↗

Electron-Transfer Activation of Thiophene

The research supported by contract FG02-90ER14146 from the U.S. Department of Energy to Thomas B. Rauchfuss is summarized. Seven research themes are described. The work on thiophenes identified pathways for desulfurization that are initiated by electron transfer or hydrolysis. Using similar half-sandwich platforms, a large family of molecular cyanometallate cages were prepared. These cages exhibit host-guest behavior, with a notable affinity for cesium ions. A series of investigations made pioneering contributions to the understanding of the catalytic properties of the hydrogenase enzymes. Work on molecular metal sulfides focused on elucidating hydrogen activation pathways, relevant to the corresponding reactions that are invoked for metal sulfide heterogeneous catalysts. The theme of proton-activated catalysis was continued with the elucidation of the effects of Bronsted acids and oxidation on inducing H2 activation by metal-amides. The proton-activation theme was shown to be a powerful vehicle for upgrading bio-derives substrates including sugars. The project concluded with emphasis on developing ligand platforms that facilitate the use of earth-abundant metals in homogeneous catalysis.

09 BIOMASS FUELS↗

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗

Co-processing Part 3: LANL Studies Quicker Method to Identify Renewable Carbon Percentages in Fuel Blends [Success Story]

Upgrading bio-oils with petroleum feedstocks at existing refineries—known as “co-processing”—could offer a fast pathway for lowering the carbon footprint of today’s transportation fuels. With equipment and infrastructure already in place, more than 100 refineries across the country are equipped to integrate bio-oil into their processes. But just where might companies insert sustainable bio-oils into existing refinery systems like fluid catalytic crackers and hydrotreaters? If successful, just how much of that renewable or “green” carbon makes it into final fuel products? In this three-part blog series, the National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), and Los Alamos National Laboratory (LANL) offer insights into these pressing coprocessing questions—and others—amid the push to dramatically expand the production of climate-friendly fuels. Read part 1 and part 2.

02 PETROLEUM↗

The Source Physics Experiment (SPE) Science Plan

The Source Physics Experiment (SPE) series is a long-term NNSA research and development effort designed to improve U.S. arms control and nuclear nonproliferation verification and monitoring capabilities. The findings from the SPE will advance the United States’ nuclear explosion monitoring capabilities, particularly with respect to detection, discrimination and determination of yields associated with small nuclear explosions that can be lost amid the noisy seismo-acoustic background from other sources. The data generated from the SPE, a series of well-designed and recorded chemical explosions, will contribute to the development and validation of first-principles explosive source generated seismo-acoustic modeling codes. These codes will then facilitate the update of semi-empirical methods, currently based on historic test site data, such that key explosion observables can be reproduced, thus improving confidence in nuclear test monitoring in new areas and/or under novel emplacement conditions. The overall SPE project is comprised of both the development of the new explosion simulation codes and the chemical explosion test series. The chemical explosion test series will generate the empirical data required to both develop and validate the new simulation codes.

58 GEOSCIENCES↗

Korean Power System Challenges and Opportunities, Priorities for Swift and Successful Clean Energy Deployment at Scale

With South Korea’s electricity demand expected to grow 30% by 2035, transitioning to clean energy resources will be critical in reducing the electric sector emissions and achieving national climate goals. Rapid technological improvements can help keep costs low and maintain grid reliability, if Korea’s government takes a coordinated approach to the clean energy transition. This policy brief identifies key barriers to Korea’s shift toward clean energy, based on the authors’ companion report (A Clean Energy Korea by 2035: Transitioning to 80% Carbon-Free Electricity Generation ), interviews with experts, and the most recent data and literature. It then explores policy solutions for overcoming these technological, economic, and institutional barriers, and suggests market transformation strategies to speed the adoption of clean energy technologies. Amid ongoing cost and technological improvements in wind, solar, and energy storage, advancing this report’s recommended policy actions with maximum coordination among government officials can meaningfully accelerate Korea’s clean energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The development of novel organomanganese hydration catalysts and uranium oxo-imido complexes to provide insights into redox chemistry and bonding properties

This project is focused on the development of novel Mn complexes that will be useful as hydrolysis catalysts for substrates such as nitriles, esters, and amides. This Mn chemistry will provide a useful platform to develop the capabilities that are necessary to synthesize and manipulate air and moisture sensitive compounds while simultaneously exploring the novel chemistry associated a new class of low-valent metal hydroxide complexes. The primary research objective of the proposed Mn chemistry the synthesis of well-defined Mn hydroxide complexes that will use the nucleophilicity of the hydroxide ligand in an anhydrous environment as a catalyst for desirable organic transformations. Several metal-ligand combinations are explored and have been extended to nickel, ruthenium and iron.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automated Model for Improved Mapping of Country-Scale High-Resolution Coastal Bathymetry

Accurate and up-to-date maps of coastal bathymetry are critical for a variety of sectors from vessel navigation to port construction and are increasingly vital to inform coastal infrastructure management amid accelerating sea-level rise and more frequent and severe storm-surge events. The primary challenges to accurate and efficient bathymetric mapping from optical remote sensing are: accurately modeling light attenuation in both the atmosphere and water column; and inefficient data processing pipelines for highresolution satellite imagery. To address the effects of light attenuation within the water-column we have developed a novel physics-based bathymetry model that accounts for variations in water-column inherent optical properties on a pixel-by-pixel basis in optically-shallow aquatic environments, which represents a major advancement. For applications to satellite imagery, we have developed a software package that automatically applies the robust 6S atmospheric correction algorithm, estimates the bottom depth from the physics-based bathymetry model, which corrects for attenuation by suspended particulate matter and colored dissolved organic matter in the water column on a pixel-by-pixel basis, and leverages highperformance computing for rapid application to region-scale (e.g., CONUS) 2-meter resolution imagery datasets. Our approach is tailored to sensors that collect data at two-meter resolution with high return times for frequent updates. We mapped 591 WorldView satellite images for Florida, North Carolina, and Alaska and validated the maps against LiDAR-derived bathymetry data. Results show median RMSE of 1.75, 1.59, and 2.67 meters, respectively. By combining the strengths of Oak Ridge National Laboratory in high-performance computing and remote-sensing science with the water-column modeling expertise of Scripps Institution of Oceanography we advance the state of bathymetric mapping capability.

54 ENVIRONMENTAL SCIENCES↗

eGridGPT: Trustworthy AI in the Control Room

This report outlines the synergy between human decision making and generative artificial intelligence (GenAI), where GenAI supports power system operators by analyzing procedures, suggesting actions, simulating scenarios with physics-based digital twins, and recommending optimal decisions. This report is the first research effort to apply large language models (LLMs), a type of GenAI, in the power grid control room. The authors describe the Electric Grid Generative Pretrained Transformer (eGridGPT), an LLM that virtually assists system operators. Developed with cybersecurity and regulatory requirements in mind, eGridGPT represents an opportunity to responsibly evolve control room technologies to meet the needs of a rapidly changing grid. As an innovative concept, eGridGPT seeks to spearhead productive discussions about the advanced technologies in the control room of the future amid the transition to clean energy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Clustering Acoustic Background Noise in the Stratosphere Using Machine Learning

Infrasound, characterized by low-frequency sound inaudible to humans (<20 Hz), emanates from natural and anthropogenic sources. Its efficacy for monitoring phenomena necessitates robust sensing networks. Traditional ground-based infrasound sensors have limitations due to atmospheric dynamics and noise interference. Balloon-bore sensors have emerged as an alternative, offering reduced noise and improved capabilities. This study bridges clustering algorithms with balloon borne infrasound data, a domain yet to be explored. Employing K-Means, DBSCAN, and GMM algorithms on normalized and reshaped data and only normalized data from a New Zealand-based NASA balloon flight, insights into background noise at stratospheric altitudes were revealed. Despite challenges arising from distinguishing signals amid unique background noise, this research provides vital reference material for noise analysis and calibration. Beyond infrasound event capture, the dataset enriches comprehension of background noise characteristics in the southern hemisphere.

47 OTHER INSTRUMENTATION↗

Assessment of tank designs for hydrogen storage on heavy duty vehicles using metal hydrides

The objective of this project was to evaluate material-based hydrogen storage solutions as a replacement for high-pressure hydrogen gas or liquid hydrogen on Class 7 or 8 tractor fuel cell electric vehicles. The project focused on low-density main-group hydrides, a well-known class of materials for hydrogen storage. Prior research has considered metal amides as storage materials for light-duty vehicles but not for heavy-duty applications. The project established the basis for further development of storage systems of this type for heavy duty vehicles (HDV). Systems analysis of an HDV storage system comprised of a tank and associated balance of plant (piping, coolant tubes, burner) was performed to determine the usable hydrogen capacity. A composite storage material comprised of a metal hydride mixed with a high thermal-conductivity carbon is predicted to have a usable hydrogen volumetric capacity comparable to or exceeding that of 700 bar pressurized hydrogen gas. The gravimetric capacity of this material is also predicted to be competitive with pressurized gas, particularly if costly carbon fiber composite Type III or Type IV tanks are excluded. The storage system design parameters and material properties served as inputs to a second model that simulates fuel cell operation in conjunction with the storage system during an HDV drive cycle. The results show that sufficient hydrogen pressure can be produced to operate a Class 8 HDV, yielding a range of ~480 miles. These results are particularly relevant for high-impact regions, such as the South Coast Air Quality Management District, for which an economical vehicular hydrogen storage system with minimal impact on cargo capacity could accelerate adoption of heavy-duty fuel cell electric vehicles. An additional benefit is that knowledge generated by this project can assist in development of material-based storage for stationary applications such as microgrids and backup power for data centers.

08 HYDROGEN↗

Cyber Resilience and Social Equity: Twin Pillars of a Sustainable Energy Future

This paper examines the intersection of security and accessibility within energy systems amidst the rise of grid modernization and digitization, especially considering the regulatory changes and the imperatives of inclusive energy strategies. It addresses the dual need for secure, resilient infrastructure and a commitment to mitigate energy poverty while maintaining equitable access to energy. Amid escalating cybersecurity and physical threats, the paper advocates for sustainable energy delivery systems that ensure robust defenses without compromising the goals of reducing energy poverty and ensuring energy security. This paper identifies the pressing need for Cyber-Informed Engineering (CIE) and Secure-by-Design (SbD) principles, highlighting how these strategies can protect critical infrastructure and democratize access to secure energy, particularly for disadvantaged communities. The analysis underscores the challenges presented by the expansion of attack surfaces, interoperability requirements, and grid-edge analytics, offering innovative solutions that leverage advanced technologies and data-driven insights. Furthermore, this paper addresses the workforce development gap, emphasizing the necessity for public-private partnerships and vendor engagement in creating a skilled cybersecurity workforce. This paper has a dual focus on both the technological aspect of cybersecurity and the social dimension of equity within the context of sustainable energy development. It suggests a comprehensive examination of how these two critical elements interact and support the overarching goal of a sustainable energy future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Low Power, Radiation Resilient Synchronous Edge Processing for Remote Monitoring

Next-generation space remote sensing systems may be equipped with imaging arrays that sense data at a rate that outstrips the processing capability of any computing hardware that can operate within a satellite’s power budget. This project developed novel convolutional and recurrent neural networks to detect and estimate point-like events amid clutter, and investigated their efficient and accurate implementation on analog in-memory computing systems that are 10-1000× more energy-efficient than digital processors. This project leveraged two memory devices at different levels of technological maturity: a large-scale analog computing prototype using commercial SONOS charge-trap memory, and electrochemical memory (ECRAM) with intrinsic radiation hardness. We experimentally demonstrated end-to-end analog processing of our neural networks on SONOS and characterized the radiation response of both SONOS and ECRAM. We advanced the state-of-the-art in ECRAM precision and reliability, and developed co-design methods to enable accurate long-term operation of SONOS analog accelerators in space radiation environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗