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At least 361 records · Page 20

Trace explosive residue detection of HMX and RDX in post-detonation dust from an open-air environment

Explosives are often used in industry, geology, mining, and other applications, but it is not always clear what remains after a detonation or the fate and transport of any residual material. The goal of this study was to determine to what extent intact molecules of high explosive (HE) compounds are detectable and quantifiable from post-detonation dust and particulates in a field experiment with varied topography. We focused on HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane), which is less studied in field detonation literature, as the primary explosive material and RDX (1,3,5-Trinitroperhydro-1,3,5-triazine) as the secondary material. The experiment was conducted at Site 300, Lawrence Livermore National Laboratory’s Experimental Test Site, in California, USA. Two 20.4 kg and one 40.8 kg above ground explosions (primarily comprised of LX-14, an HMX-based polymer-bonded high explosive) were detonated on an open-air firing area on separate days. The complex terrain of the firing area (e.g., buildings, berm, low-height obstacles) was advantageous to study HE deposition in relation to plume dynamics. Three types of samples were collected up to 100 m away from each shot: surface swipes of aluminum plates, surface swipes of fixed objects, and filters from air samples. We used atmospheric flow tube-mass spectrometry (AFT-MS) to quantify picogram levels of molecular residue of HE material in the post-detonation dust. An aliquot of sample extract in methanol (e.g., 1 µL of 0.5 mL) was placed onto a resistive material and then thermally desorbed into the AFT-MS. We successfully detected and quantified both HMX and RDX in many of the samples. Based on mass (pg) detected and solution dilution, we back-calculated the mass collected on the swipe or filter (ng per sample). The aerial distribution of molecular residue was consistent with the path of the plume, which was strongly determined by wind speed and direction at the time of each shot. The quantity of material detected appeared to correlate more with distance from the shot and the wind conditions than with shot size. This study demonstrates that the picogram detection levels of AFT-MS are well-suited for quantification of analytes (e.g., HMX and RDX) in environmental samples.

atmospheric flow tube-mass spectrometry (AFT-MS), ↗

Insights from 20 years of the Molecule of the Month

For 20 years, Molecule of the Month articles have highlighted the functional stories of 3D structures found in the Protein Data Bank (PDB). The PDB is the primary archive of atomic structures of biological molecules, currently providing open access to more than 150,000 structures studied by researchers around the world. The wealth of knowledge embodied in this resource is remarkable, with structures that allow exploration of nearly any biomolecular topic, including the basic science of genetic mechanisms, mechanisms of photosynthesis and bioenergetics, and central biomedical topics like cancer therapy and the fight against infectious disease. The central motivation behind the Molecule of the Month is to provide a user-friendly introduction to this rich body of data, charting a path for users to get started with finding and exploring the many available structures. The Molecule of the Month and related materials are updated regularly at the education portal PDB-101 (http://pdb101.rcsb.org/), offering an ongoing resource for molecular biology educators and students around the world.

59 BASIC BIOLOGICAL SCIENCES↗

Drizzle, Turbulence, and Density Currents Below Post Cold Frontal Open Cellular Marine Stratocumulus Clouds

Nine cases of postcold frontal marine stratocumulus clouds exhibiting open cellular mesoscale organization are analyzed to characterize the drizzle, turbulence, and density currents below them. Data collected by the vertically pointing Doppler cloud radar and multiple lidars part of the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site are used in these analyses. A total of 251 drizzle shafts passed over the site with 76 shafts sampled for more than 15 min by the vertically pointing instruments. On average the drizzle shafts were ~18 km wide with below-cloud drizzle water path of ~40 g m −2 , cloud base rain rate of 7.78 mm day −1 , and cloud base drizzle modal diameter of 393 μm. The widths of the drizzle shafts did not exhibit any relationship with the cloud base rain rate, below-cloud drizzle water path, and the total water removed from the cloud. The downdrafts in the lowest 500 m within the drizzle cells strengthened with increasing cloud base rain rates, while the updrafts within drizzle cells did not exhibit this behavior. On average, the surface air density, pressure, water vapor mixing ratio, and wind speed along the background wind during the drizzle shaft were higher by 1.88 g m −3 , 8.60 Pa, 0.24 g kg −1 , and 1.22 m s −1 , respectively, from their background values. On the other hand, the surface air temperature was lower by 0.43 K during the drizzle shaft than its background value. The coincident measurements highlight the drizzle-turbulence-surface coupling in these cloud systems.

59 BASIC BIOLOGICAL SCIENCES↗

Formation of transient high-β plasmas in a magnetized, weakly collisional regime

We present experimental data providing evidence for the formation of transient (~20 μs) plasmas that are simultaneously weakly magnetized (i.e. Hall magnetization parameter ωτ > 1) and dominated by thermal pressure (i.e. ratio of thermal-to-magnetic pressure β > 1). Particle collisional mean free paths are an appreciable fraction of the overall system size. These plasmas are formed via the head-on merging of two plasmas launched by magnetized coaxial guns. The ratio λ gun = μ 0 I gun /ψ gun of gun current I gun to applied magnetic flux ψ gun is an experimental knob for exploring the parameter space of β and ωτ. These experiments were conducted on the Big Red Ball at the Wisconsin Plasma Physics Laboratory. The transient formation of such plasmas can potentially open up new regimes for the laboratory study of weakly collisional, magnetized, high-β plasma physics; processes relevant to astrophysical objects and phenomena; and novel magnetized plasma targets for magneto-inertial fusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Bilayer Crystals of Trapped Ions for Quantum Information Processing

Trapped-ion systems are a leading platform for quantum information processing, but they are currently limited to 1D and 2D arrays, which imposes restrictions on both their scalability and their range of applications. Here, we propose a path to overcome this limitation by demonstrating that Penning traps can be used to realize remarkably clean bilayer crystals, wherein hundreds of ions self-organize into two well-defined layers. These bilayer crystals are made possible by the inclusion of an anharmonic trapping potential, which is readily implementable with current technology. We study the normal modes of this system and discover salient differences compared to the modes of single-plane crystals. The bilayer geometry and the unique properties of the normal modes open new opportunities—in particular, in quantum sensing and quantum simulation—that are not straightforward in single-plane crystals. Furthermore, we illustrate that it may be possible to extend the ideas presented here to realize multilayer crystals with more than two layers. Our work increases the dimensionality of trapped-ion systems by efficiently utilizing all three spatial dimensions, and it lays the foundation for a new generation of quantum information processing experiments with multilayer 3D crystals of trapped ions. Published by the American Physical Society 2024

Physics↗

First EarthCARE CPR Observations of Dynamics–Microphysics Coupling in Marine Cold‐Air Outbreak Clouds

Marine cold-air outbreak (MCAO) clouds begin as shallow cloud streets near the ice edge and evolve into broken open-cell convection downstream. Their rapid transitions in cloud structure and microphysics are closely linked to vertical motions, but this interplay has not previously been observed from space. The EarthCARE satellite, carrying the first spaceborne Doppler radar (Cloud Profiling Radar, CPR), now measures hydrometeor sedimentation velocity and vertical air motion. Using CPR observations over the Norwegian and Barents Seas (December 2024–May 2025), we analyze MCAO and non-MCAO clouds. We find that strong updrafts in MCAO clouds coincide with larger supercooled liquid water (SLW) path (LWP). These conditions are accompanied by increases in sedimentation velocity and its vertical gradient, reflecting rapid riming-driven ice growth. In contrast, non-MCAO clouds show lower riming efficiency at similar LWP due to relatively weaker dynamical support. This emphasizes the importance of dynamics in shaping polar cloud structure and microphysics.

Kim, Jiseob [McGill Univ., Montreal, QC (Canada)] ↗

The Strong Impact of Weak Horizontal Convergence on Continental Shallow Convection

Idealized large-eddy simulation (LES) is a basic tool for studying three-dimensional turbulence in the planetary boundary layer. LES is capable of providing benchmark solutions for parameterization development efforts. However, real small-scale atmospheric flows develop in heterogeneous and transient environments with locally varying vertical motions inherent to open multiscale interactive dynamical systems. These variations are often too subtle to detect them by state-of-the-art remote and in situ measurements, and are typically excluded from idealized simulations. The present study addresses the impact of weak [i.e., O(10-6) s-1] short-lived low-level large-scale convergence/divergence perturbations on continental shallow convection. The results show a strong response of shallow nonprecipitating convection to the applied weak large-scale dynamical forcing. Evolutions of CAPE, mean liquid water path, and cloud-top heights are significantly affected by the imposed convergence/divergence. In contrast, evolving cloud-base properties, such as the area coverage and mass flux, are only weakly affected. To contrast those impacts with microphysical sensitivity, the baseline simulations are perturbed assuming different observationally based cloud droplet number concentrations and thus different rainfall. For the tested range of microphysical perturbations, the imposed convergence/divergence provides significantly larger impact than changes in the cloud microphysics. Simulation results presented here provide a stringent test for convection parameterizations, especially important for large-scale models progressing toward resolving some nonhydrostatic effects.

Meteorology & Atmospheric Sciences↗

Aeroelastic Modeling and Full-Scale Loads Measurements for Investigation of Single-Axis PV Tracker Wind-Driven Dynamic Instabilities

While wind tunnel testing and proprietary industry modeling tools have been used for years to design and develop PV tracker systems, wind induced dynamic failures are becoming more prevalent and high visibility. Designers and manufactures have reacted by developing new systems or add-on products to improve system dynamics adding to overall system costs. To better understand the physics and aeroelastic behavior that leads to dynamic instabilities NREL researches have taken up a first of a kind study to both develop open source aeroelastic modeling tools and measure tracker loads on a single axis full-scale tracker system at a high wind site. These modeling tools can simulate the fluid-structure interaction driving torsional instabilities under a wide range of turbulent inflow conditions and stow angles. The results of these simulations reveal the flow features associated with panel rotation and the induced loads in the structure. The experimental load measurements can be used to validate models and provide a quantifiable understanding of tracker dynamics, critical loads paths, identify instability markers, inform resilient design, and suggest the most favorable stow approach.

14 SOLAR ENERGY↗

Heliostat Aiming Strategies for Arbitrary Flux Profiles for High Temperature Gas-Based Receivers

High temperature gas-based receivers are seen as one potential path toward achieving the next generation of concentrated solar power tower systems. A key challenge associated with high temperature, high pressure heat transfer fluids is the lifetime of receiver containment materials. Achieving the desired lifetime while also designing an efficient receiver requires implementation of unique flux profiles, tailored to place high fluxes at cold fluid injection points. An aimpoint selection methodology was developed in the present study to allow user-defined flux profiles to be prescribed for a receiver. The methodology was implemented in NREL's open-source software SolarPILOT, modifying the existing “image size priority” aimpoint strategy. A case study for a tubular gas-based receiver is presented, examining the effect of various parameters on the ability to replicate the desired flux profile.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Alfalfa Virtual Building Service: Software Engineering Best Practices Applied to Runtime Interaction with Building Energy Models

Buildings are active participants in increasingly complex energy systems. Building Energy Modeling (BEM) has a key role to play in planning and de-risking an equitable energy transition, with BEM-backed "virtual buildings" critical path for diverse applications that include workforce training tools, Hardware-in-the-Loop (HIL) experimentation to study equipment performance under a range of conditions, Control-Hardware-in-the-Loop (CHIL) experimentation to de-risk commercial control implementations at equipment through grid orchestration levels, and integration of dynamic load profiles into grid modeling tools for energy system experimentation at the urban scale. Modeling requirements vary across these applications, but many software engineering tasks do not. The Alfalfa Virtual Building Service (AVBS, see https://github.com/NREL/alfalfa/wiki) is an open-source web service that solves these common tasks robustly in one place, providing a foundational platform for power users to bootstrap their own applications. AVBS abstracts the specifics of runtime interaction with OpenStudio, Modelica, and Spawn of EnergyPlus models behind a unified REST API. Additionally, AVBS provides resources for cloud deployment and scaling to 100s of parallel simulations, a growing library of modular Operational Technology (OT) integrations for emulation of real-world interfaces, and scripts to automate the population of communities of virtual buildings from URBANopt, ResStock and ComStock.

building automation↗

Semi-empirical simulation of in-motion radiation detection systems

The Replicative Assessment of Spectroscopic Equipment (RASE) is an open-source software that uses experimental data as the basis to simulate the response of commercial radiation detectors to sources in various situations, particularly in the context of nuclear security and safeguards applications. Dynamic RASE introduces the capability to simulate scenarios where sources and detector are in relative motion. Position-dependent experimentally acquired gamma spectra are ingested by Dynamic RASE to build maps that describe the detector response over all space. These response maps are used to replicate the time-dependent energy spectra collected as sources move on a path near the detector. Here, a Gaussian process is used to build each map, incorporating a novel kernel adapted to the special case of radiation detection. The approach has been validated against experimental data acquired using a NaI-based detector for 137 Cs and 54 Mn sources. The capability to create accurate simulations using either long-dwell static measurements or dynamic pass-by measurements as source data has been demonstrated. Quantitative relative performance, benefits, and shortcomings are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A muon–ion collider at BNL: The future QCD frontier and path to a new energy frontier of μ + μ – colliders

In this work, we propose the development and construction of a novel muon–ion collider (MuIC) at Brookhaven National Laboratory (BNL) in the USA as an upgrade to succeed the electron–ion collider (EIC) that is scheduled to commence in the early 2030s, by a joint effort of the nuclear and particle physics communities. The BNL facility could accommodate a muon storage beam with an energy up to about 1 TeV with existing magnet technology. When collided with a 275 GeV hadron beam, the MuIC center-of-mass energy of about 1 TeV will extend the kinematic coverage of deep inelastic scattering physics at the EIC (with polarized beams) by more than an order of magnitude in Q 2 and x, opening a new QCD frontier to address many fundamental scientific questions in nuclear and particle physics. This coverage is comparable to that of the proposed Large Hadron–Electron Collider (LHeC) at CERN, but with complementary lepton and hadron kinematics, ion species, and beam polarization. Additionally, the development of a MuIC at BNL will focus the worldwide R&D efforts on muon collider technology and serve as a demonstrator toward a future muon–antimuon collider at O(10) TeV energy, which is an attractive option to reach the next high energy frontier in particle physics at an affordable cost and a smaller footprint than a future circular hadron collider. We discuss here the possible design parameters of the MuIC, kinematic coverage, science cases, and detector design considerations including resolution estimates on DIS kinematic variables. A possible road map toward the future MuIC and muon–antimuon colliders is also presented.

43 PARTICLE ACCELERATORS↗

Scalable Al 2 O 3 –TiO 2 Conductive Oxide Interfaces as Defect Reservoirs for Resistive Switching Devices

Abstract Resistive switching devices herald a transformative technology for memory and computation, offering considerable advantages in performance and energy efficiency. Here, a simple and scalable material system of conductive oxide interfaces is employed, and their unique properties are leveraged for a new type of resistive switching device. An Al 2 O 3 –TiO 2 ‐based valence‐change resistive switching device, where the conductive oxide interface serves both as the bottom electrode and as a reservoir of defects for switching, is demonstrated. The amorphous–polycrystalline Al 2 O 3 –TiO 2 conductive interface is obtained following the technological path of simplifying the fabrication of the 2D electron gases (2DEGs), making them scalable for practical mass integration. Physical analysis of the device chemistry and microstructure with comprehensive electrical analysis of its switching behavior and performance is combined. The origin of the resistive switching is pinpointed to the conductive oxide interface, which serves both as the bottom electrode and as a reservoir of oxygen vacancies. The latter plays a key role in valence‐change resistive switching devices. The new device, based on scalable and complementary metal–oxide–semiconductor (CMOS)‐technology‐compatible fabrication processes, opens new design spaces toward increased tunability and simplification of the device selection challenge.

36 MATERIALS SCIENCE↗

Island scanning pattern optimization for residual deformation mitigation in laser powder bed fusion via sequential inherent strain method and sensitivity analysis

Laser powder bed fusion (L-PBF) has emerged as one of the mainstream additive manufacturing approaches for fabricating metal parts with complex geometries and intricate internal structures. However, large deformation associated with rapid heating and cooling can lead to build failure and requires post-processing which may increase manufacturing cost and prolong the production period. Here in this work, an island scanning pattern design method is proposed to optimize the scanning direction of each island in order to reduce part deformation after cutting off the build platform. The objective of this optimization is to minimize the upward bending of the part after sectioning, which allows the part deformation to satisfy the tolerance requirement or reduce the post heat treatment time. Inherent strain method is employed in the sequential finite element analysis consisting of layer-by-layer activations and sectioning for fast residual distortion prediction. Full sequential sensitivity analysis for the formulated optimization is provided to update the island scanning directions. To show the feasibility and effectiveness of the proposed method, the scanning patterns of a block structure and a connecting rod were designed and parts were fabricated using an open architecture L-PBF machine. The fabrication experiments demonstrated that the residual deformation of both parts fabricated by optimized scanning pattern can be reduced by over 50% compared to the initial scanning patterns, which demonstrate the effectiveness of the proposed method.

36 MATERIALS SCIENCE↗

Analysis of an all-solid state nanobattery using molecular dynamics simulations under an external electric field

Present Li-ion battery (LIB) technology requires strong improvements in performance, energy capacity, charging-time, and cost to expand their application to e-mobility and grid storage. Li-metal is one of the most promising materials to replace commercial anodes such as graphite because of its 10 times higher specific capacity. However, Li-metal has high reactivity with commercial liquid electrolytes; thus, new solid materials are proposed to replace liquid electrolytes when Li-metal anodes are used. We present a theoretical analysis of the charging process in a full nanobattery, containing a LiCoO 2 cathode, a Li 7 P2S 8 I solid-state electrolyte (SSE), a Li-metal anode as well as Al and Cu collectors for the cathode and anode, respectively. In addition, we added a Li 3 P/Li 2 S film as a solid electrolyte interphase (SEI) layer between the Li-anode and SSE. Thus, we focus this study on the SEI and SSE. We simulated the charging of the nanobattery with an external voltage by applying an electric field. We estimated temperature profiles within the nanobattery and analyzed Li-ion transport through the SSE and SEI. Here, we observed a slight temperature rise at the SEI due to reactions forming $PS_{3}^{–}$ and $P_{2}S_{7}^{4}$$^{–}$ fragments at the interfaces; however, this temperature profile changes due to the charging current under the presence of the external electric field ε = 0.75 V Å –1 . Without the external field, the calculated open-circuit voltage (OCV) was 3.86 V for the battery, which is within the range of values of commercial cobalt-based LIBs. This voltage implies a spontaneous fall of available Li-ions from the anode to the cathode (during discharge). The charge of this nanobattery requires overcoming the OCV plus an additional voltage that determines the charging current. Thus, we applied an external potential able to neutralize the OCV, plus an additional 1.6 V to induce the transport of Li + from the cathode up to the anode. Several interesting details about Li + transport paths through the SSE and SEI are discussed.

25 ENERGY STORAGE↗

Mesoscopic finite-size effects of unconventional electron transport in PdCoO 2

A wide range of unconventional transport phenomena has recently been observed in single-crystal delafossite metals. Here, we present a theoretical framework to elucidate electron transport using a combination of first-principles calculations and numerical modeling of the anisotropic Boltzmann transport equation. Using PdCoO 2 as a model system, we study different microscopic electron and phonon scattering mechanisms and establish the mean free path hierarchy of quasiparticles at different temperatures. We treat the anisotropic Fermi surface explicitly to numerically obtain experimentally-accessible transport observables, which bridge between the “diffusive,” “ballistic,” and “hydrodynamic” transport regime limits. Further, we illustrate that the distinction between the “quasiballistic” and “quasihydrodynamic” regimes is challenging and often needs to be quantitative in nature. From first-principles calculations, we populate the resulting transport regime plots and demonstrate how the Fermi surface orientation adds complexity to the observed transport signatures in micrometer-scale devices. Our work provides key insights into microscopic interaction mechanisms on open hexagonal Fermi surfaces and establishes their connection to the macroscopic electron transport in finite-size channels.

36 MATERIALS SCIENCE↗

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗

Integrated System Planning: Emerging Software Requirements in the Power Industry

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

24 POWER TRANSMISSION AND DISTRIBUTION↗