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Enabling hydrogen chemisorption on charged graphene

Two-dimensional (2D) materials, including graphitic derivatives, have long been of interest for hydrogen storage applications, due to their high theoretical storage capacity, low weight, and other useful properties. However, poor kinetics for hydrogen adsorption and surface diffusion as part of the proposed spillover process for hydrogenation have limited their technological potential. Here, we use first-principles calculations to study electronic doping as a means to improve hydrogen chemisorption on graphene, which we use here as a proxy for graphitic derivatives more broadly. We find that positively charged graphene sheets have vastly improved kinetics for hydrogen diffusion and adsorption, while they limit unwanted hydrogen desorption. This combination of effects should favor hydrogen chemisorption via spillover. We connect these trends to the C–H bond, which introduces states near the Fermi level. These states are depopulated as electrons are removed, thereby lowering the bond energy and permitting more facile movement of hydrogen. Our results suggest that spillover mechanisms for hydrogen chemisorption should be revisited if strategies to apply a large charge to graphitic systems can be realized. Moreover, switchable application of the charge may lead to the reversible chemisorption of hydrogen. While the large magnitude of charging required suggests that graphene itself may not be suitable for reversible hydrogen chemisorption, the factors we identify and discuss could significantly boost the prospects of graphitic derivatives and other 2D or layered materials for hydrogen storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards an Energy Future with Ubiquitous Electric Vehicles: Barriers and Opportunities

The electrification of personal transportation holds great potential for lowering greenhouse gas emissions and reducing climate change. The promise of electric vehicles (EVs) to serve these goals has resulted in a broad range of supporting policies aimed at encouraging widespread EV adoption at both the state and federal levels in the United States and around the world. While the EV revolution and prospects of a world with ubiquitous EVs are impacting various industries and many aspects of daily life, strategic interactions between the power grid and EVs are crucial for a successful energy transition. However, managing the interplay between EVs and the power grid remains a challenge. Motivated by that tension, this paper surveys a variety of solutions, policies, and incentives that are focused on effectively managing EV charging behaviors. The paper’s objective is to explore these tools to ensure that EV owners have ultimate control over their personal vehicles while simultaneously allowing the power grid to mitigate adverse network impacts. Furthermore, this paper examines the role of charging infrastructure technology and its strategic placement in facilitating the seamless integration of EVs into the grid. Additionally, the paper highlights financial mechanisms associated with EV integration and discusses the consequences of these mechanisms.

25 ENERGY STORAGE↗

Feasibility Studies and Downselection of New Materials and Manufacturing Technologies for Nuclear Applications

This report is intended to present the results of multi-laboratory collaborative studies on the feasibility and downselection of the structural materials that are newly considered for application to future nuclear energy technologies. The Advanced Materials and Manufacturing Techniques (AMMT) program has been implemented to develop cross-cutting technologies in support of a broad range of nuclear reactor technologies and to maintain U.S. leadership in materials and manufacturing technologies for nuclear energy applications. In line with these program objectives, this collaborative studies aim to explore new materials utilizing advanced manufacturing technologies. The FY23 research scope consists of the feasibility studies on new materials and relevant advanced manufacturing technologies, collection of materials properties data and knowledge through experiments and literature survey, and development and application of decision criteria matrix for downselecting candidate materials and manufacturing technologies. The three-laboratory efforts for FY23 have focused on the three new material groups including oxide dispersion strengthened (ODS) materials, refractory composites and alloys, and high entropy alloys (HEAs) investigated, respectively, by Oak Ridge National Laboratory (ORNL) (work package: CT-23OR130406), Los Alamos National Laboratory (LANL) (CT-23LA130403) and Pacific Northwest National Laboratory (PNNL) (CT-23PN130408). The execution of this multi-lab research aimed to provide the AMMT program a merit-based feasibility study identifying an accelerated development path for these materials. A collaborative approach for achieving this goal was to develop a common materials evaluation criteria matrix and apply to all new candidate materials for the evaluation and prioritization of new materials using advanced manufacturing processes. The decision criteria matrix created is a matrix of criteria which a prospective material is scored against. The evaluation criteria are divided into four categories: Application Space, Environmental Compatibility, Physical & Mechanical Properties, and Manufacturability. Materials are given a score from 1−5 for each criterion, with the highest score (5) essentially mean that a material has the most near-term potential for application. Application of the decision criteria matrix will provide guidance to the future research on new materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The information content of jet quenching and machine learning assisted observable design

Jets produced in high-energy heavy-ion collisions are modified compared to those in proton-proton collisions due to their interaction with the deconfined, strongly-coupled quark-gluon plasma (QGP). In this work, we employ machine learning techniques to identify important features that distinguish jets produced in heavy-ion collisions from jets produced in proton-proton collisions. We formulate the problem using binary classification and focus on leveraging machine learning in ways that inform theoretical calculations of jet modification: (i) we quantify the information content in terms of Infrared Collinear (IRC)-safety and in terms of hard vs. soft emissions, (ii) we identify optimally discriminating observables that are in principle calculable in perturbative QCD, and (iii) we assess the information loss due to the heavy-ion underlying event and background subtraction algorithms. We illustrate our methodology using Monte Carlo event generators, where we find that important information about jet quenching is contained not only in hard splittings but also in soft emissions and IRC-unsafe physics inside the jet. This information appears to be significantly reduced by the presence of the underlying event. We discuss the implications of this for the prospect of using jet quenching to extract properties of the QGP. Since the training labels are exactly known, this methodology can be used directly on experimental data without reliance on modeling. We outline a proposal for how such an experimental analysis can be carried out, and how it can guide future measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A comprehensive review of solar only and hybrid solar driven multigeneration systems: Classifications, benefits, design and prospective

Depending on the application and demands, different products can be generated utilizing multigeneration systems. To drive such systems, solar energy can be used as a primary energy source or in hybridization with other renewable or nonrenewable energy sources. Solar driven multigeneration systems are appealing due to the broad availability of solar energy and related technologies. Here, the objective of this study is to review, categorize and discuss different configurations, benefits, potentials, challenges, future research directions and market perspectives of solar energy-driven multigeneration systems, comprehensively. This study also reviews how solar energy systems can be used to hybridize systems for multigeneration purposes. Regardless of using fossil fuel backup sources, these systems are classified as (1) solar only-driven and (2) hybrid solar-driven, in which solar energy is used together with other renewable sources. Reviewing the literature demonstrates numerous ways to build solar energy-driven multigeneration systems by coupling a variety of different cycles and devices. Such systems offer multiple benefits such as enhancing the efficiency, reducing capital and operating costs and carbon dioxide emission. Hybridizing solar with other renewable energies enables continuous operation and dispatchability management. This review shows that for configuration selection and design, different thermodynamics, economic and environmental aspects should be considered. To advance the solar driven multigeneration systems development, further multidisciplinary research on different aspects of such systems is necessary. Particularly, investigations should focus on building different prototypes and on conducting experimental assessments. Also, new incentives and long-term purchase agreements for the products must be established.

14 SOLAR ENERGY↗

SECARB-USA: A Sub-Basin Framework for Future CO 2 Infrastructure Development

Task 4 of the SECARB-USA Project is designed to evaluate the regional needs and challenges for the development of a safe and environmentally sound CO 2 transport infrastructure. This infrastructure would transport CO 2 capture from power generating plants and/or industrial sources and distribute it to oil fields for associated storage in EOR operations, saline storage, and/or other suitable storage sites. The objective of this report on Sub-Basin Prospective Areas (Deliverable 4.1.a), is to provide the framework for understanding how regional infrastructure development could occur. The sub-basin prospective areas, in conjunction with the locations of CO 2 sources and pipeline infrastructure (for source-sink matching networks), form the basis for the analysis that will be performed in the Techno-Economic Analysis of Infrastructure Buildout Scenarios (Deliverable 4.1.b).

54 ENVIRONMENTAL SCIENCES↗

Geologic hydrogen: From natural occurrences to anthropogenic generation – A review of fundamentals, potential, challenges and prospects

Growing demand for hydrogen is exposing the environmental and economic limits of reforming-based and carbon-managed supply chains, while the scale-up of electrolytic capacity remains capital-constrained. Geologic hydrogen, defined as molecular H₂ generated and stored within the Earth's crust offers a complementary, potentially lower-cost resource, yet exploration is still ad hoc. This review (1) revisits a global inventory of confirmed hydrogen seeps and subsurface occurrences; (2) analyzes the controlling reactions, migration pathways, and trapping conditions governing these occurrences; (3) proposes a process-based geologic hydrogen system concept analogous to, yet distinct from, the petroleum system; and (4) evaluates potential geologic hydrogen systems within the United States as a representative case study. Here, we contrast natural systems powered by serpentinization, mantle degassing or radiolysis with anthropogenic systems that stimulate the same reactions or convert in-situ hydrocarbons. Stable hydrogen accumulations require generation rates that outpace combined physical, chemical and microbial losses; the Bourakébougou field (Mali) exemplifies a self-recharging, free-gas reservoir sustained by meteoric-water serpentinization beneath an efficient caprock. Prospective geologic hydrogen resources are likely to occur in regions where iron-rich lithologies, deep-seated faults, and low-permeability sealing formations coexist. Applying this principle, we highlight three promising hydrogen play types in U.S. geological terrains: ophiolite belts (Appalachian and Californian regions), the Midcontinent Rift and the Lake Superior banded‑iron formations. Multiphysics numerical models and positive-unlabeled machine-learning workflows help to accelerate play screening and de-risk future production; yet, reaction kinetics, stimulation strategies, and full techno-economic and life-cycle assessments remain pivotal knowledge gaps.

Anthropogenic hydrogen generation↗

Cosmology of dark energy radiation

In this work, we quantify the cosmological signatures of dark energy radiation—a novel description of dark energy, which proposes that the dynamical component of dark energy is comprised of a thermal bath of relativistic particles sourced by thermal friction from a slowly rolling scalar field. For a minimal model with particle production emerging from first principles, we find that the abundance of radiation sourced by dark energy can be as large as Ω DER = 0.03, exceeding the bounds on relic dark radiation by three orders of magnitude. Although the background and perturbative evolution of dark energy radiation are distinct from Quintessence, we find that current and near-future cosmic microwave background and supernova data will not distinguish these models of dark energy. We also find that our constraints on all models are dominated by their impact on the expansion rate of the Universe. Considering extensions that allow the dark radiation to populate neutrinos, axions, and dark photons, we evaluate the direct detection prospects of a thermal background comprised of these candidates consistent with cosmological constraints on dark energy radiation. Our study indicates that a resolution of ~6 meV is required to achieve sensitivity to relativistic neutrinos compatible with dark energy radiation in a neutrino capture experiment on tritium. We also find that dark matter axion experiments lack sensitivity to a relativistic thermal axion background, even if enhanced by dark energy radiation, and dedicated search strategies are required to probe new parameter space. We derive constraints arising from a dark photon background from oscillations into visible photons, and find that viable parameter space can be explored with the late dark energy radiation experiment.

79 ASTRONOMY AND ASTROPHYSICS↗

Volume 4: Detection Systems and Ultra-Cold Neutrons

As part of the Sustaining and Enhancing Nuclear Science (SENSe) initiative at Oak Ridge National Laboratory (ORNL), the prospect of adding new detection systems to support High Flux Isotope Reactor (HFIR) operations and to advance scientific research has prompted many ideas and discussions regarding potential features, configurations, locations, and applications. A working group of ORNL staff members was organized to further develop the concepts and recommending one or more configurations to best support future HFIR operations and scientific capacities and to provide order-of-magnitude cost estimates and timing. The areas of investigation included fast access detection systems, non-scattering beamline instruments, shielded detection instruments, and an ultracold neutron source. In each case, the focus was to develop world leading capabilities that would be unmatched by any other facility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

CarbonSAFE Phase II: Optimizing Alabama’s CO 2 Storage in Shelby County, Alabama (Project OASIS), Milestone M3 - Site Specific Drilling Report

The Phase II Storage Complex Feasibility project, entitled "Optimizing Alabama's CO 2 Storage in Shelby County, Alabama (Project OASIS)," is a part of the DOE/NETL's CarbonSAFE initiative. The Project is managed by the Southern States Energy Board (SSEB), and includes participation from Advanced Resources International, Inc. (ARI), Crescent Resource Innovation, Southern Company, Alabama A&M University, Auburn University, and Oklahoma State University. Project OASIS is working to establish the foundation for a commercial-scale geologic storage complex for CO 2 captured from Plant Gaston (home of the National Carbon Capture Center) and surrounding industrial sources of CO 2 located in Shelby County, Alabama. The Project objectives are: • Demonstrate that the subsurface saline formations at the storage complex can store commercial volumes of CO 2 safely and permanently. • Develop a comprehensive Community Benefits Plan. • Develop the infrastructure framework for a CO 2 storage hub. • Develop a rigorous risk registry and to conduct a comprehensive risk assessment. • Develop a monitoring plan. • Develop a comprehensive site characterization plan to support an Underground Injection Control Class VI Permit in a future Phase III program. • Evaluate the commercial viability of the project. Project OASIS is about 30 miles southeast of Birmingham, Alabama within a geologic province called the Valley and Ridge (Figure 1.1). The Valley and Ridge Province comprises a sequence of Paleozoic carbonate and clastic rocks that underwent structural deformation during the Alleghanian Orogeny. Storage prospects occur in relatively flat lying structural panels located between thrust faults. Available geologic studies related to hydrocarbon exploration suggest that Cambro-Ordovician carbonates and Cambrian clastic units offer multiple potential storage intervals, and that regional confining systems are present, such as the tectonically thickened Floyd-Parkwood Shale. The surface property is owned by a timber and land stewardship company, The Westervelt Company, Inc., who worked with the Project Team to select and prepare adequate sites for geologic assessment. The purpose of drilling the Westover Stratigraphic Test Well #2 was to collect geologic data to model the feasibility of commercial scale CO 2 injection and storage. This includes geological and geophysical evaluations, reservoir engineering analyses, and risk assessments.

20 FOSSIL-FUELED POWER PLANTS↗

Life Cycle Inventory Availability: Status and Prospects for Leveraging New Technologies

The demand for life cycle assessments (LCA) is growing rapidly, which leads to an increasing demand of life cycle inventory (LCI) data. While the LCA community has made significant progress in developing LCI databases for diverse applications, challenges still need to be addressed. This perspective summarizes the current data gaps, transparency, and uncertainty aspects of existing LCI databases. Additionally, we survey and discuss novel techniques for LCI data generation, dissemination, and validation. We propose key future directions for LCI development efforts to address these challenges, including leveraging scientific and technical advances such as the Internet of Things (IoT), machine learning, and blockchain/cloud platforms. Adopting these advanced technologies can significantly improve the quality and accessibility of LCI data, thereby facilitating more accurate and reliable LCA studies.

blockchain platforms↗

Machine learning and shallow groundwater chemistry to identify geothermal prospects in the Great Basin, USA

This study discovers various geothermal prospects in the Great Basin, USA based on shallow groundwater chemical (geochemical) data. The geochemical data are expected to include hidden (latent) information that is a proxy for geothermal prospectivity. We processed the sparse geochemical data in the Great Basin at 14,341 locations including 18 attributes. Next, a non-negative matrix factorization with customized k-means clustering is applied to the geochemical data matrix that automatically finds three hidden geothermal signatures representing modestly, moderately, and highly confident geothermal prospects. The algorithm also evaluated the probability of occurrence of these types of resources through the studied region. There is a consistency between regional geothermal prospectivity as estimated by our ML methodology and the traditional play fairway analysis conducted over a portion of the study area. We also identify the dominant data attributes associated with each signature. Finally, our ML analyses allow us to reconstruct attributes from sparse into continuous over the study domain. The predicted continuous attributes can be used for future detailed geothermal explorations in the Great Basin.

15 GEOTHERMAL ENERGY↗

Physics model enhancements in MARLEY version 2

Large next-generation neutrino detectors, such as those designed for accelerator-based oscillation experiments, are expected to have impressive sensitivity to MeV astrophysical neutrinos generated by the Sun and by supernovae. There are also numerous related prospects to search for MeV-scale phenomena beyond the Standard Model. In contrast to detectors constructed with water and hydrocarbon targets, which will be primarily sensitive to electron antineutrinos via inverse beta decay, the upcoming Deep Underground Neutrino Experiment (DUNE) will provide unparalleled capabilities to measure low-energy electron neutrinos from cosmic sources. Interpreting such future measurements in DUNE will require a high-quality simulation of MeV interaction physics in the argon nucleus. The MARLEY (Model of Argon Reaction Low Energy Yields) neutrino event generator has been designed with the goal of delivering the needed simulation capabilities for DUNE and other argon-based neutrino detectors. In this poster, I will present recent improvements to MARLEY's suite of interaction models, which will be released for general use by the neutrino community in version 2 of the software.

Gardiner, Steven James [Fermilab] (ORCID:000000028↗

Physics model enhancements in MARLEY version 2

Large next-generation neutrino detectors, such as those designed for accelerator-based oscillation experiments, are expected to have impressive sensitivity to MeV astrophysical neutrinos generated by the Sun and by supernovae. There are also numerous related prospects to search for MeV-scale phenomena beyond the Standard Model. In contrast to detectors constructed with water and hydrocarbon targets, which will be primarily sensitive to electron antineutrinos via inverse beta decay, the upcoming Deep Underground Neutrino Experiment (DUNE) will provide unparalleled capabilities to measure low-energy electron neutrinos from cosmic sources. Interpreting such future measurements in DUNE will require a high-quality simulation of MeV interaction physics in the argon nucleus. The MARLEY (Model of Argon Reaction Low Energy Yields) neutrino event generator has been designed with the goal of delivering the needed simulation capabilities for DUNE and other argon-based neutrino detectors. In this talk, I will present recent improvements to MARLEY's physics models, which will be released for general use by the neutrino community in version 2 of the software.

Gardiner, Steven James [Fermilab] (ORCID:000000028↗

Exciting prospects for detecting late-time neutrinos from core-collapse supernovae

The importance of detecting neutrinos from a Milky Way core-collapse supernova is well known. An understudied phase is proto-neutron star cooling. For SN 1987A, this seemingly began at about 2 s and is thus probed by only 6 of the 19 events (and only the $\bar{ν}_e$ flavor) in the Kamiokande-II and IMB detectors. With the higher statistics expected for present and near-future detectors, it should be possible to measure detailed neutrino signals out to very late times. Here, we present the first comprehensive study of neutrino detection during the proto-neutron star cooling phase, considering a variety of outcomes, using all flavors, and employing detailed detector physics. For our nominal model, the event yields (at 10 kpc) after 10 s—the approximate duration of the SN 1987A signal—far exceed the entire SN 1987A yield, with ≃ 250 $\bar{ν}_e$ events (to 50 s) in Super-Kamiokande, ≃ 110 ν e events (40 s) in the Deep Underground Neutrino Experiment (DUNE), and ≃10 $ν_μ, ν_τ, \bar{ν}_μ, \bar{ν}_τ$ events (to 20 s) in the Jiangmen Underground Neutrino Observatory. These data would allow unprecedented probes of the proto-neutron star, including the onset of neutrino transparency and hence its transition to a neutron star. If a black hole forms, even at very late times, this can be clearly identified. But will the detectors fulfill their potential for this perhaps once-ever opportunity for an all-flavor, high-statistics detection of a core collapse? Maybe. Further work is urgently needed, especially for DUNE to thoroughly investigate and improve its MeV capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗

Next-generation tunnel FETs: exploring material perspectives and areal tunneling configurations

The end of Dennard scaling, which facilitated proportional increases in computing power without added energy costs until the mid-2000s, has underscored the urgent need for innovative semiconductor devices that can enhance energy efficiency. Tunnel field-effect transistors (TFETs) have emerged as promising candidates to surpass the energy efficiency of conventional metal oxide semiconductor field-effect transistors (MOSFETs). Unlike MOSFETs, which rely on thermionic emission to overcome the source-channel potential barrier, TFETs operate through quantum tunneling, potentially enabling sub-60 mV dec −1 subthreshold swing (SS) for low-voltage operation. However, lateral TFETs have faced challenges in achieving adequate on-state current (I ON ) and a broad SS operation window, limiting their practical utility. This review article advocates for areal TFETs, which utilize face-to-face tunnel junctions that ideally offer step-function current turn-on characteristics and allow I ON to scale with device area rather than width. We highlight recent advancements in integrating 2D materials into tunneling structures, which could facilitate efficient band-to-band tunneling through atomically thin layers, while addressing challenges of gate field screening. We then discuss the nearer-term prospects of epitaxial areal TFETs comprising III–V compound semiconductors and group-IV semiconductors based on recent experimental progress. The review examines both quantum mechanical and semiclassical modeling approaches for TFETs, including techniques to reduce the computational complexity. The article delves into ongoing challenges in material synthesis, interface engineering, device fabrication, and integration pathways, concluding with recommendations for future research directions to overcome the fundamental power density limitations of conventional transistor technology.

2D materials↗

First Results on Dark Matter Substructure from Astrometric Weak Lensing

Low-mass structures of dark matter (DM) are expected to be entirely devoid of light-emitting regions and baryons. Precisely because of this lack of baryonic feedback, small-scale substructures of the Milky Way are a relatively pristine testing ground for discovering aspects of DM microphysics and primordial fluctuations on subgalactic scales. In this work, we report results from the first search for Galactic DM subhalos with time-domain astrometric weak gravitational lensing. The analysis is based on a matched-filter template of local lensing corrections to the proper motion of stars in the Magellanic Clouds. We describe a data analysis pipeline detailing sample selection, background subtraction, and handling outliers and other systematics. For tentative candidate lenses, we identify a signature based on an anomalous parallax template that can unequivocally confirm the presence of a DM lens, opening up prospects for robust discovery potential with full time-series data. We present our constraints on substructure fraction f l ≲5 at 90% CL (and f l ≲2 at 50% CL) for compact lenses with radii r l <1pc, with best sensitivity reached for lens masses M l around 10 7 -10 8 M ⊙ . Parametric improvements are expected with future astrometric data sets; by end of mission, Gaia could reach f l ≲10 -3 for these massive point-like objects, and be sensitive to lighter and/or more extended subhalos for O(1) substructure fractions.

79 ASTRONOMY AND ASTROPHYSICS↗

Plant-based engineering for production of high-valued natural products

Plants are a unique source of complex specialized metabolites, many of which play significant roles in human society. In many cases, however, the availability of these metabolites from naturally occurring sources fails to meet current demands. Thus, there is much interest in expanding the production capacity of target plant molecules. Traditionally, plant breeding, chemical synthesis, and microbial fermentation are considered the primary routes towards large scale production of natural products. Here, in this paper, we explore the advances, challenges, and future of plant engineering as a complementary path. Although plants are an integral part of our food and agricultural systems and sustain an extensive array of chemical constituents, their complex genetics and physiology have prevented the optimal exploitation of plants as a production chassis. We highlight emerging engineering tools and scientific advances developed in recent years that have improved the prospects of using plants as a sustainable and scalable production platform. We also discuss technological limitations and overall economic outlook of plant-based production of natural products.

59 BASIC BIOLOGICAL SCIENCES↗