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At least 1,531 records · Page 85

Surface elevation, snow depth, vegetation height, and color imagery from multiple UAV surveys from 2018 to 2023 across a watershed near Teller road mile marker 27, Seward Peninsula, Alaska

Multiple photogrammetric surveys using an unoccupied aerial system (UAS) were performed across a watershed along Teller road on the Seward Peninsula (Alaska) to investigate terrain, vegetation and snowpack properties. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The multiple photogrammetric surveys used mostly a DJI Matrice 210 UAS with a DJI X5S camera, Ground Control Points (GCPs) surveyed with a Real Time Kinematic (RTK)-GPS, and a structure from motion (SfM) technique for photogrammetric reconstruction. Digital Surface elevation Models (DSMs) were inferred at various times of year, including near peak in plant and leaf density (July 19 2017), close to peak in snow depth (April 1 2019 and April 11 2022), and at low plant and leaf density of tall after the first bare-ground date (June 9 2019). Snow and canopy height were obtained by subtracting DSMs from a Digital Terrain Model (DTM) proxy inferred from the June 9 2019 survey. The derived products include ortho-mosaiced RGB map, DSMs, a DTM proxy, snow depth (April 2019 and 2022) and canopy height (July 2017). Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.csv), image (*.jpg), and GeoTiff (*.tif) formats. This metadata document contains a description of the survey and processing steps and the inferred products.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Subsurface electrical conductivity across the BEO site inferred using a capacitively coupled resistivity survey in May 2013, Utqiagvik, Alaska

Multiple transects across and around the Barrow Environmental Observatory (BEO) site were surveyed using a capacitively coupled resistivity tool to infer the subsurface electrical conductivity in the top ~6 m in order to improve the understanding of heterogeneity in ice and salinity content. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The acquisition was performed in May 2013 using a capacitively coupled resistivity tool (OhmMapper from Geometrics, Inc) mounted behind a sled hooked to a snowmobile. Twenty-eight ~750 m long transects cover the NGEE intensive site (polygon areas A, B, C, D) in the BEO with a measurement (apparent resistivity for 5 different geometries) taken every 1.5 to 2 m. The survey also includes other transects that have been acquired along Electrical Resistivity Tomography (ERT) transects previously acquired at the site (Site 0, AB, and BD), and several long transects (up to 7 km each) around the BEO site crossing several Drained Thawed Lake Basins (DTLB). The various transects acquired during this survey cover a distance of about 100 km. All the datasets are provided with the acquisition geometry and the associated subsurface apparent electrical conductivity. In addition, the 28 transects at the BEO intensive site were inverted to infer the subsurface electrical conductivity. Unprocessed and processed data products are included in this package. This metadata document contains a description of the survey and processing steps and the inferred products.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska, and 2) multiple areas in the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Bottom‐Up Synthesis of Metallic CoNi Nanoplatelets with Magnetic Vortex‐Like Spin Configurations

Magnetic nanoplatelets hold significant potential for various technical applications due to their ability to switch between a fully magnetized state with high magnetization and a vortex‐like configuration that eliminates stray fields in the absence of an external field. This study presents the synthesis of uniform CoNi nanoplatelets through the topotactic reduction of metal hydroxides using hydrogen plasma. The reduction process is analyzed via magnetometry, leveraging the transition from paramagnetic hydroxide to ferromagnetic metal. Lorentz transmission electron microscopy and scanning transmission X‐ray microscopy confirm the presence of magnetic vortex‐like structures in isolated Co 0.85 Ni 0.15 nanoplatelets at ambient temperature. Additionally, micromagnetic simulations are conducted to further explore the magnetic properties of the nanoplatelets, revealing the formation of magnetic vortex remanent states at diameters between 200 nm and 1 μm and a thickness of around 12 nm. Notably, structural defects and thickness variations do not directly destabilize the magnetic vortex configurations.

Kräenbring, Mena‐Alexander [Faculty of Physics and↗

Evaluating CO 2 mitigation strategies in SAF biorefineries: Techno-economic and life cycle analysis

The aviation sector requires scalable decarbonization strategies, and lignocellulosic sustainable aviation fuel (SAF) represents a promising pathway. This study comparatively evaluates the techno-economic analysis and life cycle assessment (LCA) of three CO 2 management strategies integrated within a U.S.-based gasification–Fischer–Tropsch SAF biorefinery: (i) catalytic hydrogenation of captured CO 2 to methanol, (ii) geological CO 2 sequestration, and (iii) mineralization to sodium bicarbonate (NaHCO 3 ). Techno-economic analysis indicates that methanol synthesis requires approximately 26% higher capital investment and 33% higher operating costs than mineralization. Although methanol co-production generates the highest gross revenue, NaHCO 3 production reduces the SAF minimum selling price by approximately 38% relative to both methanol synthesis and geological sequestration pathways, reflecting a more balanced cost allocation through mineral co-product valorization. Geological sequestration lowers operating costs by nearly 50% compared with methanol synthesis but remains highly dependent on carbon credit mechanisms. LCA reveals substantial divergence in climate performance. Relative to methanol synthesis, sequestration improves net greenhouse gas performance by approximately 163%, transitioning the system from net-positive to net-negative emissions. Mineralization further enhances carbon mitigation, achieving roughly 85% greater carbon reduction than sequestration and over sixfold improvement relative to methanol synthesis within the defined system boundary. Sensitivity analysis identified hydrogen price, co-product market value, and process emissions as dominant drivers. Under baseline assumptions, CO 2 mineralization is found to offer the most balanced pathway.

Carbon capture and storage↗

Controlling Preferred Grain Orientation in Vapor-Deposited Metal-Halide Perovskite Thin Films

Metal-halide perovskites are promising semiconductor materials for light-absorber layers in solar cells due to their optimized band gap, defect tolerance, and relative ease of synthesis. In this work, we demonstrate the viability of vapor transport deposition (VTD), a solvent-free processing method, to realize polycrystalline films of both lead iodide (PbI 2 ) and methylammonium lead iodide (MAPbI 3 ) perovskites showing preferential crystallographic orientation. Notable is the difference in perovskite film texturing observed for sequentially and co-deposited VTD films of MAPbI 3 , as well as the lack of strong preferential orientation in solution-processed MAPbI 3 films. While sequential deposition of the perovskite precursors PbI 2 and methylammonium iodide (MAI) leads to a MAPbI 3 film with a limited preferential grain orientation, co-deposited MAPbI 3 films mirror the orientation of excess PbI 2 present in the film. The latter is confirmed by the similar dependence of preferential orientation for PbI 2 and co-deposited MAPbI 3 on underlayer roughness, as well as the emergence of preferential orientation in MAPbI 3 only when excess PbI 2 is present. Both MAPbI 3 and PbI 2 films show a strong preferred lattice orientation on smooth substrates, while on rougher substrates, this orientation is disrupted. Furthermore, these results are interpreted as excess PbI 2 frustrating the diffusion of MAI in the film, which would otherwise disrupt the preferred orientation, pointing to a notable difference in lattice orientation arising from processing technique and conditions.

Deposition↗

A low-latency graph computer to identify metastable particles at the Large Hadron Collider for real-time analysis of potential dark matter signatures

Abstract Image recognition is a pervasive task in many information-processing environments. We present a solution to a difficult pattern recognition problem that lies at the heart of experimental particle physics. Future experiments with very high-intensity beams will produce a spray of thousands of particles in each beam-target or beam-beam collision. Recognizing the trajectories of these particles as they traverse layers of electronic sensors is a massive image recognition task that has never been accomplished in real time. We present a real-time processing solution that is implemented in a commercial field-programmable gate array using high-level synthesis. It is an unsupervised learning algorithm that uses techniques of graph computing. A prime application is the low-latency analysis of dark-matter signatures involving metastable charged particles that manifest as disappearing tracks.

47 OTHER INSTRUMENTATION↗

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗

Phosphatidic acid: an emerging versatile class of cellular mediators

Abstract Lipids function not only as the major structural components of cell membranes, but also as molecular messengers that transduce signals to trigger downstream signaling events in the cell. Phosphatidic acid (PA), the simplest and a minor class of glycerophospholipids, is a key intermediate for the synthesis of membrane and storage lipids, and also plays important roles in mediating diverse cellular and physiological processes in eukaryotes ranging from microbes to mammals and higher plants. PA comprises different molecular species that can act differently, and is found in virtually all organisms, tissues, and organellar membranes, with variations in total content and molecular species composition. The cellular levels of PA are highly dynamic in response to stimuli and multiple enzymatic reactions can mediate its production and degradation. Moreover, its unique physicochemical properties compared with other glycerophospholipids allow PA to influence membrane structure and dynamics, and interact with various proteins. PA has emerged as a class of new lipid mediators modulating various signaling and cellular processes via its versatile effects, such as membrane tethering, conformational changes, and enzymatic activities of target proteins, and vesicular trafficking.

Biochemistry & Molecular Biology↗

Materials Dynamics

The Materials Dynamics area of leadership focuses on understanding process-structure-properties-performance (PSPP) relationships for the extreme conditions of dynamic loading. This research encompasses controlled synthesis of materials to meet dynamic performance requirements and entails computational coupling across length and time scales for three-dimensional microstructure modeling. For this leadership area, we define dynamic loading as strain rates ≥ 10 3 /s and often, high pressures. A key grand challenge of this area is to predict and measure the evolution of microstructural phases, defect structures, and electronic structure under dynamic conditions while also measuring local temperature to understand transition states. Solving this challenge will require agile, multi-dimensional data analysis and interpretation capability.

36 MATERIALS SCIENCE↗

CO2 Electrolyzer to Produce Formic Acid Using Flue Gas at Industry Relevant Current Density

The electrochemical conversion of carbon dioxide (CO2) into valuable fuels and feedstocks has gained great attention recently due to the global urgency to mitigate the rapid climate change. A wide variety of chemicals can be obtained through the electrochemical CO2 reduction reaction (CO2RR). Among all the chemicals generated through CO2RR, formic acid has attracted great interest because of its wide applications in silage preservation in agriculture, as an antibacterial agent in animal food additives, as a chemical additive in leather and tanning processing, as a chemical component in textile dyeing and finishing, as a reagent in pharmaceutical and chemical synthesis, and as deicing agents and a component in drilling fluids. Recently, the use of formic acid as a feedstock for biorefineries has also attracted increasing interest.

Yang, Hongzhou↗

UH cosmic rays - Possible origin in massive stars

The origin of the Z greater than 28, ultraheavy (UH) cosmic rays in supernova explosions of massive stars, at least about 10 solar masses, is considered. For Z greater than 70, the UH data are dominated by an r-process source distribution, but for the elements just beyond iron, Z from 29 to 36, the data cannot be explained by any single process of nucleosynthesis. This problem is solved naturally in a massive-star model by secondary neutron-capture reactions occurring during core helium burning (a limited s-process) and during explosive carbon burning. Interstellar-propagation calculations have been performed with these episodes of synthesis as source distributions, and the results offer an explanation for the current UH cosmic-ray data. Further, the heavy-element synthesis during explosive carbon burning is re-examined by using more realistic initial conditions given by the post-helium-burning configuration of the star. These results are compared with earlier work and the UH cosmic-ray data. Some effects of preferential acceleration, based upon ionization potential, are considered, and experimental tests for this model are discussed.

Wefel, J. P.↗

A model for sunspot associated emission at 6 cm wavelength

Two-dimensional maps of total intensity and circular polarization of a sunspot region at 6 cm have been calculated using a simple model for the chromosphere-corona transition region and observations of the longitudinal component of the photospheric magnetic field. The calculations are in good agreement with the high resolution observations of the same sunspot region at 6 cm, obtained with the Westerbork Synthesis Radio Telescope. It is shown that the 6 cm radiation is predominantly due to gyroresonance absorption process at the second and third harmonics of the gyrofrequency (H = 900-600 G). Estimates of the conductive flux and the electron density in the transition region above the sunspot are also given.

Alissandrakis, C. E.↗

Matrix Synthesis and Characterization

The role of NASA in the area of composite material synthesis; evaluation techniques; prediction analysis techniques; solvent-resistant tough composite matrix; resistance to paint strippers; acceptable processing temperature and pressure for thermoplastics; and the role of computer modeling and fiber interface improvement were discussed.

Source record↗

Interferometry theory for the block 2 processor

Presented is the interferometry theory for the Block 2 processor, including a high-level functional description and a discussion of data structure. The analysis covers the major processing steps: cross-correlation, fringe counter-rotation, transformation to the frequency domain, phase calibration, bandwidth synthesis, and extraction of the observables of amplitude, phase, phase rate, and delay. Also included are analyses for fractional bitshift correction, station clock error, ionosphere correction, and effective frequencies for the observables.

Thomas, J. B.↗

Solid-state combustion synthesis of ceramics and alloys in reduced gravity

Possible microgravity effects are explored in the combustion synthesis of ceramics and alloys from their constituent elements. Molten intermediates are typically present during the combustion process, thereby offering the chance for natural convection to take place. Numerical simulations suggest that the combustion front in concert with gravity may act as a partial zone-refinement mechanism which is attempting to sweep out porosity in the sample. Contrary to suggestions by dimensional analysis, no effects on the combustion rate are seen. An analytical model of the combustion velocity as a function of the gravitational field and the spreading rate of molten material gives the correct order of magnitude of the gravity effect as measured by centrifuge experiments.

Valone, S. M.↗

Digital test signal generation: An accurate SNR calibration approach for the DSN

A new method of generating analog test signals with accurate signal to noise ratios (SNRs) is described. High accuracy will be obtained by simultaneous generation of digital noise and signal spectra at a given baseband or bandpass limited bandwidth. The digital synthesis will provide a test signal embedded in noise with the statistical properties of a stationary random process. Accuracy will only be dependent on test integration time with a limit imposed by the system quantization noise (expected to be 0.02 dB). Setability will be approximately 0.1 dB. The first digital SNR generator to provide baseband test signals is being built and will be available in early 1991.

Gutierrez-Luaces, B. O.↗

[ ] or SUCCESS is Not Enough: Current Technology and Future Directions in Proof Presentation

Automated theorem provers for first order logic are now around for several decades. Over the last few years, their deductive power to solve hard problems has increased tremendously. The annual CASC system competitions [Se97] give a clear picture of this situation. However, today's automated theorem provers are restricted "more by general usability than by raw deductive power." As a result of this, there are only very few serious applications of automated theorem provers. There are numerous features which a theorem prover lacks for real-world applicability. An automated theorem prover (as it is currently seen) is nothing more than a fast and elaborate search procedure. In that sense, an ATP can compared to a formulated race car, cool and fast, but virtually unusable for shopping groceries around the corner. Many important features are missing, or are optimized for speed rather than for applicability. [Schol] identifies important features which are needed for practical usability like detection of non-theorems, handling of modal/inductive proof tasks, control of the prover, and proof output. In this paper, we will focus solely on the last point, the presentation of the ATP's result to the user. In the rest of this paper, we will first discuss the general importance of providing feedback to the user, then we will describe the system ExplainIt!, a part of the deductive synthesis system AMPHION/NAV. In the conclusions we will relate proof presentation to other ways of post-processing a proof found by an ATP and stress their role in the future of automated deduction.

Schumann, Johann↗

Reconfigurability in MDO Problem Synthesis

Integrating autonomous disciplines into a problem amenable to solution presents a major challenge in realistic multidisciplinary design optimization (MDO). We propose a linguistic approach to MDO problem description, formulation, and solution we call reconfigurable multidisciplinary synthesis (REMS). With assistance from computer science techniques, REMS comprises an abstract language and a collection of processes that provide a means for dynamic reasoning about MDO problems in a range of contexts. The approach may be summarized as follows. Description of disciplinary data according to the rules of a grammar, followed by lexical analysis and compilation, yields basic computational components that can be assembled into various MDO problem formulations and solution algorithms, including hybrid strategies, with relative ease. The ability to re-use the computational components is due to the special structure of the MDO problem. The range of contexts for reasoning about MDO spans tasks from error checking and derivative computation to formulation and reformulation of optimization problem statements. In highly structured contexts, reconfigurability can mean a straightforward transformation among problem formulations with a single operation. We hope that REMS will enable experimentation with a variety of problem formulations in research environments, assist in the assembly of MDO test problems, and serve as a pre-processor in computational frameworks in production environments. This paper, Part 1 of two companion papers, discusses the fundamentals of REMS. Part 2 illustrates the methodology in more detail.

Alexandrov, Natalia M.↗