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At least 1,531 records · Page 85

Domestic Extremism: Countering the Threat Posed to Critical Assets

Domestic extremism has been a growing concern in the United States in recent months, as illustrated in multiple bulletins from the Department of Homeland Security (DHS) warning law enforcement partners of the heightened threat. As concerns about these actors grows, it is important that facilities in the U.S. and internationally that protect critical assets, such as sensitive information, hazardous materials, or critical infrastructure, have effective methods in place to secure those assets. DE has challenged security systems through the threat of insider attack and violence, creating a new threat to be countered in the Office of Radiological Security’s radiological source security mission. In this effort, we used a literature review and focus group discussions with experts in critical asset security and extremism to understand the nature of the domestic extremist threat, to identify best practices in securing assets, recognize potential gaps in security measures to be corrected, and recommend actions and next steps. Twenty-two subject matter experts participated in a series of five focus group sessions. Questions focused on definitions of domestic extremism, potential changes in the threat, best practices in securing facilities, assets, and personnel, and any perceived gaps. Upon completion of the focus groups, notes were analyzed thematically to identify any recurring patterns in the results. In addition, a review of academic, industry, and government literature was conducted to understand the threat, describe the process of radicalization to extremism, and to identify empirically informed practices in prevention and response. Results of this project demonstrated that further work is needed to define domestic extremism in law, regulation, and policy, to help the U.S. develop a consistent response to the threat within organizations. This is especially important, as SMEs emphasized the need for early intervention in prevention efforts, noting that organizations need clear guidance on when and how to intervene. In addition, the need for social media monitoring was discussed, although challenges remain to do so with appropriate respect for privacy and civil liberties concerns.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Emergence of complex-regular eutectic patterns in Al–Ge: Observations from correlative nano-imaging

Eutectic solidification exemplifies nonequilibrium pattern formation, making it a well-studied moving boundary problem. Yet the mechanisms behind the formation of complex-regular microstructures – particularly in highly anisotropic systems with a significant volume fraction of a faceted phase – remain poorly understood. Our understanding of such systems is made complicated by the nonlinear interface kinetics and unique growth dynamics characteristic of faceted phases. To address these challenges, we investigate a model Al–Ge eutectic system, where the faceted Ge phase constitutes a substantial volume fraction (~0.35) and where the two solid phases arrange into so-called “fishbone” or “feather” complex-regular patterns. Using synchrotron-based x-ray nano-imaging and nanotomography with high spatial resolution (22 nm per pixel), we capture in real-time the evolution of the solid–liquid interfaces and the resulting three-dimensional microstructures in this faceted/non-faceted eutectic system. By integrating these observations with electron backscattered diffraction, we elucidate the crystallographic biases on the solidification process and the mechanisms driving the formation of such complex-regular microstructures. These findings inform a new growth model for irregular eutectics in (near-)symmetrical phase diagrams, offering insight on advanced microstructural design and processing strategies. More broadly, we demonstrate how interfacial curvature is generated in irregular eutectic alloys and how it depends on the volume fraction of the faceted phase.

36 MATERIALS SCIENCE↗

Environmental Controls on Water Vapor Deuterium Excess in the Coastal Boundary Layer: An Information Theory Perspective

We use information theory to quantify the environmental controls on water vapor deuterium excess (D-excess) in coastal Southern California from June 2023 through February 2024. Using Shannon entropy, mutual information (MI), and joint mutual information, metrics that capture both linear and nonlinear relationships, we identify the most informative variables and variable combinations governing D-excess across contrasting marine and continental regimes. Relative humidity with respect to sea surface temperature (RHS) is consistently the strongest individual predictor, explaining up to 27% of D-excess variability during marine conditions but only 10% in continental air masses. The Relative humidity(RHS) + sea surface temperature (SST) combination demonstrates synergistic effects, where their joint influence (explaining up to 36% of D-excess variability) exceeds what either variable achieves individually, confirming their coupled influence on deuterium excess. Wind direction complements RHS most effectively during continental conditions. The best three-variable combination (RHS + SST + Planetary Boundary Layer height) explains 38% of D-excess variability in marine air, while no combination exceeds 20% explanatory power during continental periods. Information theory shows that heteroscedasticity in D-excess relationships indicates regime shifts in controlling processes and quantifies fundamental constraints on predictor variables: some environmental factors like surface pressure or water vapor flux contain insufficient information content to explain D-excess variability regardless of their physical relevance. These results highlight the different predictability limits between marine and continental regimes, challenging the adequacy of linear models and providing a rigorous framework for quantifying the information content of isotope-climate relationships with implications for both modern and paleoclimate applications.

information theory↗

Recent advances in the global rare-earth supply chain

The current global rare-earth element (REE) supply chain is highly imbalanced and tightly controlled by just a few countries. Such an imbalance of the critical metals supply chain poses a significant challenge to the energy-transition strategies and the national security of many countries. As such, this issue of MRS Bulletin delves into the materials science aspects of the REE supply chain, including fundamental REE mineralogy, REE separation and extraction, REE mining economics, the environmental impacts of REE mining and processing, and circular economy potential for REEs. This issue of MRS Bulletin is meant to inform the materials science community of some of the constraints on REE production from the mining of ore deposits, through processing technologies, and then finally, the possibility of recycling.

99 GENERAL AND MISCELLANEOUS↗

Modeling of Precipitation over Africa: Progress, Challenges, and Prospects

In recent years, there has been an increasing need for climate information across diverse sectors of society. This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change. Likewise, this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa. By leveraging a large volume of climate model outputs, numerous studies have investigated the model representation of African precipitation as well as underlying physical processes. These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies. This paper provides a review of the progress in precipitation simulation over Africa in state-of-the-science climate models and discusses the major issues and challenges that remain.

CMIP6↗

Energy storage solutions to decarbonize electricity through enhanced capacity expansion modelling

To meet ambitious global decarbonization goals, electricity system planning and operations will change fundamentally. With increasing reliance on variable renewable energy resources, energy storage is likely to play a critical accompanying role to help balance generation and consumption patterns. As grid planners, non-profit organizations, non-governmental organizations, policy makers, regulators and other key stakeholders commonly use capacity expansion modelling to inform energy policy and investment decisions, it is crucial that these processes capture the value of energy storage in energy-system decarbonization. Here we conduct an extensive review of literature on the representation of energy storage in capacity expansion modelling. We identify challenges related to enhancing modelling capabilities to inform decarbonization policies and electricity system investments, and to improve societal outcomes throughout the clean energy transition. Additionally, we further identify corresponding research activities that can help overcome these challenges and conclude by highlighting tangible real-world outcomes that will result from pursuing these research activities. Capacity expansion modelling (CEM) approaches need to account for the value of energy storage in energy-system decarbonization. A new Review considers the representation of energy storage in the CEM literature and identifies approaches to overcome the challenges such approaches face when it comes to better informing policy and investment decisions.

25 ENERGY STORAGE↗

An adaptive and stability-promoting layerwise training approach for sparse deep neural network architecture

This work presents a two-stage adaptive framework for progressively developing deep neural network (DNN) architectures that generalize well for a given training data set. In the first stage, a layerwise training approach is adopted where a new layer is added each time and trained independently by freezing parameters in the previous layers. We impose desirable structures on the DNN by employing manifold regularization, sparsity regularization, and physics-informed terms. We introduce a ε – δ – stability-promoting concept as a desirable property for a learning algorithm and show that employing manifold regularization yields a ε – δ stability-promoting algorithm. Further, we also derive the necessary conditions for the trainability of a newly added layer and investigate the training saturation problem. In the second stage of the algorithm (post-processing), a sequence of shallow networks is employed to extract information from the residual produced in the first stage, thereby improving the prediction accuracy. Numerical investigations on prototype regression and classification problems demonstrate that the proposed approach can outperform fully connected DNNs of the same size. Moreover, by equipping the physics-informed neural network (PINN) with the proposed adaptive architecture strategy to solve partial differential equations, we numerically show that adaptive PINNs not only are superior to standard PINNs but also produce interpretable hidden layers with provable stability. As a result, we also apply our architecture design strategy to solve inverse problems governed by elliptic partial differential equations.

42 ENGINEERING↗

Typologies of actionable climate information and its use

Developing actionable climate information and integrating it into decision-making are two crucial elements for promoting effective societal responses to climate change. However, what constitutes actionable climate information, and how it is used, varies based on the actors, systems, and scales that are relevant to specific decisions. Yet, the terms ‘actionable climate information’ or ‘use of climate information’ are used abstractly. There is a lack of holistic understanding of the various types of information that can be deemed as usable by different users, and the different ways in which they may be used in decision-making. Typologies or generalizable categorizations can help both knowledge producers and users to better envision the entire landscape of climate information and its uses and can help to reduce the time and cost of actionable knowledge production. Through systematic coding and analysis of ~ 4 years of co-production engagements between climate scientists and resource managers, this paper presents empirically derived typologies of actionable climate information and its use, and explores whether certain uses are better informed by specific types of climate information. These typologies provide a valuable starting point for climate information producers, users, and boundary spanners working on climate-informed resource management, to reduce some of the time-intensive elements of the process.

54 ENVIRONMENTAL SCIENCES↗

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↗

p +p - electroproduction off protons in deuterium: measurements of quasi-free cross sections and kinematic probing of final state interactions

In this study, the process of pi+pi- electroproduction off protons bound in deuterium nuclei is explored. The exploration is performed through the analysis of experimental data on electron scattering off the deuteron target, collected in Hall B at Jefferson Lab with the CLAS detector. As a main result, the set of integrated and single-differential cross sections of the reaction yvp(n) -> p'(n')pi+pi- is obtained. The cross sections are extracted in the quasi-free regime, which implies that only events not affected by final state interactions are subject to selection. The measurements are performed in the kinematic region of the invariant mass W from 1.3 GeV to 1.825 GeV and photon virtuality Q2 from 0.4 GeV2 to 1 GeV2. Sufficient experimental statistics allows narrow binning, i.e. 25 MeV in W and 0.05 GeV2 in Q2, while maintaining an adequate statistical uncertainty. The extraction of quasi-free cross sections is accompanied by the kinematic probing of FSI between the reaction final hadrons and the spectator neutron in the aforementioned exclusive channel. In this probing the distributions of missing quantities are used in order to investigate the relative spread of events with FSI along the reaction phase space, trace the difference of FSI manifestations in different reaction topologies, reveal details on alterations of the hadron momentum in FSI, and isolate FSI contributions of various final hadrons. The performed examination is also capable of retrieving information on some underlying FSI mechanisms, among which the process of resonance formation in the intermediate state of pion-neutron interactions is particularly remarkable.

Skorodumina, Iuliia↗

A Simplified Building Modeling Approach for Identifying Whole Building Retrofits

Building Energy Modeling (BEM) is an effective strategy for optimizing new and retrofit building design, evaluating its energy savings potential and rating its energy performance. However, because of the complexity and expense of modeling, only a small percentage of buildings are simulated. Over 80% of buildings are <25,000 ft2, and the cost associated with BEM can be a big deterrent for reaching this subsector, which usually ends up complying with energy codes and qualifying for incentives using prescriptive measures or generalized design guides. Similarly, efficiency considerations for small building retrofits are often identified through deemed measures or Technical Reference Manuals, which though a scalable and convenient approach, can limit innovation in design and optimization of measures. Simplification of the modeling process, where appropriate, can lead to increased energy savings and more informed decision making. This paper will discuss the development of a ruleset for a simplified approach based on the Performance Rating Method (PRM) contained in ASHRAE Standard 90.1. The approach aims to simplify and lower the cost of the energy modeling process in a controlled and documented manner. An anticipated outcome is an increased use of BEM and its effectiveness in the design, retrofit and operation of commercial buildings. In addition, simplification of the modeling process will result in fewer errors from misinterpretations of both program requirements and program intent in simulation software. The paper will discuss the need and advantages of a simplified modeling approach for whole building retrofits and the technical process for achieving the same.

Goel, Supriya↗

Quantum speed limit for the out-of-time-ordered correlator from an open-system perspective

Scrambling, the delocalization of initially localized quantum information, is commonly characterized by the out-of-time-ordered correlator (OTOC). Employing the OTOC–Renyi-2 entropy theorem, we derive a quantum speed limit for the OTOC, which sets a lower bound for the rate with which information can be scrambled. This bound becomes particularly tractable by describing the scrambling of information in a closed quantum system as an effective decoherence process of an open system interacting with an environment. We prove that decay of the OTOC can be bounded by the strength of the system-environment coupling and two-point environmental correlation functions. We validate our analytic bound numerically using the nonintegrable transverse field Ising model. Furthermore, our results provide a universal and model-agnostic quantitative framework for understanding the dynamical limits of information spreading across quantum many-body physics, condensed matter systems, and engineered quantum platforms.

Fermions↗

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Korea Institute of Energy Research [Abstract]

The Korea Institute of Energy Research (KIER) and the National Energy Technology Laboratory (NETL) intend to collaborate under a CRADA to advance the development of oxy-combustion technology, with an emphasis on process modeling, optimization, and techno-economic analysis. This collaboration will result in the development of a full-scale process model of a commercial oxy-fueled circulating fluid bed combustion (oxy-CFBC) plant, informed from pilot-scale data and built using the Institute for the Design of Advanced Energy Systems (IDAES) process systems engineering framework. It will also generate cost comparisons of the optimized oxyCFBC process with an air-CFBC process with and without carbon capture and sequestration.

20 FOSSIL-FUELED POWER PLANTS↗

What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.

54 ENVIRONMENTAL SCIENCES↗

Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics

A large and ever-growing body of geophysical information is measured in campaigns and at specialized observatories as a part of scientific expeditions and experiments. These collections of observed data include many essential climate variables (as defined by the Global Climate Observing System) but are often distinguished by a wide range of additional non-routine measurements that are designed to not only document the state of the environment but also the drivers that contribute to that state. These field data are used not only to further understand environmental processes through observation-based studies but also to provide baseline data to test model performance and to codify understanding to improve predictive capabilities. To address the considerable barriers and difficulty in utilizing these diverse and complex data for observation–model research, the Merged Observatory Data File (MODF) concept has been developed. A MODF combines measurements from multiple instruments into a single file that complies with well-established data format and metadata practices and has been designed to parallel the development of corresponding Merged Model Data Files (MMDFs). Using the MODF and MMDF protocols will facilitate the evolution of model intercomparison projects into model intercomparison and improvement projects by putting observation and model data “on the same page” in a timely manner. The MODF concept was developed especially for weather forecast model studies in the Arctic. The surprisingly complex process of implementing MODFs in that context refined the concept itself. Thus, this article explains the concept of MODFs by providing details on the issues that were revealed and resolved during that first specific implementation. Detailed instructions are provided on how to make MODFs, and this article can be considered a MODF creation manual.

54 ENVIRONMENTAL SCIENCES↗

Advanced Energy Approaches for Mixed-Use Developments in the Front Range Urban Corridor

The primary objective of the document is to present example technical approaches and strategies that planners and developers can reference for all-electric mixed-use developments in the Rocky Mountain Front Range urban corridor that are considering advanced energy performance goals such as high levels of energy efficiency and renewable integration. The strategies are tailored toward the vision for a zero energy, all-electric, district thermal system-connected starter district. In this example, on-site solar generation is emphasized as a strategy that can be combined with electrical and thermal energy storage for enhanced community resilience and demand flexibility. Opportunities for utilizing or adapting these strategies include: sharing with vertical developers for potential integration of strategies into vertical design guidelines; incorporation into Owner Project Requirements (OPRs); providing example strategies to design teams as a starting point for design; informing structure of agenda for a building design charrette; comparing building designs to example strategies at various points in the design process to evaluate design progression. While the technical strategies outlined in this document can help inform the development of guidelines for projects in the Front Range urban corridor, this document does not set requirements for any rating, certification, program, or policy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Additive Manufacturing Design Guidelines for Wind Industry

The purpose of this report is to equip wind industry professionals with the fundamental information needed to best leverage additive manufacturing techniques in their design and manufacturing decisions. Herein an overview of each of the seven families of additive manufacturing is provided, along with typical materials used in each process, current ranges on process speeds, materials and system costs, and examples of systems on the market today. Using the lens of large-scale additive to suit the needs of the wind industry, the processes that are well-suited to large-scale production are down selected from the seven families and additional information with design guidelines specific to each process are detailed. A companion document titled “Relevant Additive Manufacturing Materials for Wind Industry” elaborates on the specifics of relevant material properties and test methods for additive manufacturing materials.

17 WIND ENERGY↗

Reducing Commercial Building Process Loads and Refrigeration Unit Energy Consumption

This resource provides guidance on larger PPLs, many of which are hardwired. Examples include elevators, enterprise servers, freezers, and water fountains with chillers, which are often collectively referred to as "process loads." This resource also outlines how to assess process loads in a building, describes the procedure for identifying which loads to target for reduction, and provides an overview of reduction strategies. In this resource, process loads are broken into five categories - food handling, refrigeration, internal mobility, data center and information technology, and water handling.

commercial buildings↗