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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29

The role of electric dominance for particle injection in relativistic reconnection

ABSTRACT Magnetic reconnection in relativistic plasmas – where the magnetization $\sigma \gg 1$ – is regarded as an efficient particle accelerator, capable of explaining the most dramatic astrophysical flares. We employ two-dimensional (2D) particle-in-cell simulations of relativistic pair-plasma reconnection with vanishing guide field and outflow boundaries to quantify the impact of the energy gain occurring in regions of electric dominance ($E\gt B$) for the early stages of particle acceleration (i.e. the ‘injection’ stage). Given an injection threshold energy $\epsilon ^\ast =\sigma /4$ for the particles that eventually attain energy $\epsilon _{\rm T}$ by time T, we calculate the mean fractional contribution $\zeta (\epsilon ^\ast ,\epsilon _{\rm T})$ by $E\gt B$ fields to particle energization at the time when the threshold $\epsilon ^\ast$ is reached. We find that $\zeta$ monotonically increases with $\sigma$ and $\epsilon _{\rm T}$; for $\sigma \gtrsim 50$ and $\epsilon _{\rm T}/\sigma \gtrsim 8$, we find that $\gtrsim 80~{{\ \rm per\ cent}}$ of the energy gain obtained before reaching $\epsilon ^\ast =\sigma /4$ occurs in $E\gt B$ regions. We find that $\zeta$ is independent of simulation box size $L_x$, as long as $\epsilon _{\rm T}$ is normalized to the maximum particle energy, which scales as $\epsilon _{\rm max}\propto L_{\rm x}^{1/2}$ in 2D. The distribution of energy gains $\epsilon _{\chi }$ acquired in $E\gt B$ regions can be modelled as $\mathrm{ d}N/\mathrm{ d}\epsilon _{\chi }\propto \epsilon _{\chi }^{-0.35}\exp [-(\epsilon _{\chi }/0.06\, \sigma)^{0.5}]$. Our results help assess the role of electric dominance in relativistic reconnection with vanishing guide fields, which is realized in the magnetospheres of black holes and neutron stars.

Gupta, Sanya (ORCID:0000000151944384)↗

Evaluating the limitations of Bayesian metabolic control analysis

AbstractBayesian Metabolic Control Analysis (BMCA) has emerged as a promising framework for inferring metabolic control coefficients in data-limited scenarios by integrating Bayesian inference with linlog rate laws. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCCs), and concentration control coefficients (CCCs) under varying data availability conditions using three synthetic metabolic network models. Our findings highlight the strengths and weaknesses of BMCA, guiding its application in metabolic engineering and emphasizing the need for methodological refinements.Author summaryUnderstanding how enzymes control metabolic pathways is crucial for optimizing biomanufacturing and synthetic biology applications. Bayesian Metabolic Control Analysis (BMCA) is a promising computational method that integrates Bayesian inference with metabolic control analysis to estimate key control parameters, even in cases with limited experimental data. However, the accuracy and limitations of BMCA remain unclear. In this study, we systematically evaluate BMCA using three synthetic metabolic networks to determine how different types of physiological data impact its predictive performance. We find that BMCA requires flux and enzyme concentration data for accurate predictions, while external metabolite concentrations contribute little. Additionally, BMCA fails to predict elasticity values beyond a magnitude of 1.5 and reliably infer allosteric regulation, even when strong regulatory interactions exist. In addition, BMCA does not accurately rank metabolic control points, which may limit its utility in identifying key enzymes in engineered pathways. Our work provides practical insights into when and how BMCA can be applied, guiding future research in metabolic modeling and control analysis.

Shin, Janis (ORCID:0000000216572455)↗

Eliminating beam-induced depolarizing effects in the hydrogen jet target for high-precision proton beam polarimetry at the electron-ion collider

We analyze beam-induced depolarizing effects in the hydrogen jet target (HJET) at the relativistic heavy ion collider (RHIC), which has been used for absolute hadron beam polarimetry and shall be employed at the electron-ion collider (EIC). The EIC’s higher bunch repetition frequencies and shorter bunch durations shift beam harmonics to frequencies that can resonantly drive hyperfine transitions in hydrogen, threatening to depolarize the target atoms. Using frequency-domain analysis of beam harmonics and hyperfine transition frequencies, we establish a photon emission threshold above which beam-induced fields are too weak to cause significant depolarization. For EIC injection (23.5 GeV) and flattop (275 GeV), beam-induced depolarization through the bunch structure renders operation at the current RHIC magnetic guide field at the target (𝐵 0 =120⁢ mT) untenable. Increasing the magnetic guide field at the target to 𝐵 0 ≈ 400⁢ mT moves all hyperfine transition frequencies to at least 3 times the cutoff frequency, ensuring reliable absolute beam polarimetry with the required 1% precision at the EIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Scalable dark matter searches using integrated photonics

Dark matter (DM) with masses of order an electronvolt or below can have a nonzero coupling to electromagnetism while being compatible with cosmological observations. In these models, the ambient DM behaves as a new classical source in Maxwell’s equations, which can excite potentially detectable electromagnetic (EM) fields in the laboratory. We propose a new integrated-photonics–based approach to search for dark matter candidates in the 0.1–few eV mass range. This approach offers a wide range of wavelength-scale devices like resonators and wave guides that are readily fabricated in large quantities, enabling a scalable and novel search. In particular, we demonstrate that refractive index-modulated resonators, such as etched/grooved microrings, or patterned slabs, support EM modes with efficient coupling to DM. When excited by DM, these modes are read out by coupling the resonators to a wave guide that terminates on a micron-scale–sized single photon detector, such as a single pixel of a low-noise charge-coupled device or a superconducting nanowire. We then estimate the sensitivity of this experimental concept in the context of axionlike particle and dark photon models of DM, demonstrating that nanophotonic confinement and scalability can extend dark matter sensitivity into previously unexplored parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multiloop and multiaxis atomtronic Sagnac interferometry

We report the experimental realization of a large-area and multiaxis atomtronic interferometer in an optical waveguide for rotation sensing. A large enclosed area is achieved through multiloop operation in a guided-atom interferometer using Bose-Einstein condensates. We demonstrate a three-loop interferometer with a total interrogation time of ∼ 0.4 s and an enclosed area of 8.7 mm 2 —the largest reported in a fully guided or one-dimensional setup. High-contrast interference fringes are observed for up to five Sagnac orbits in a smaller loop-area configuration. Our approach enables interleaved rotation measurements about multiple arbitrary axes within the same experimental setup. We present results for area-enclosing interferometers in both horizontal and vertical planes, demonstrating that the interferometer contrast remains comparable across orthogonal orientations of the enclosed area vectors.

74 ATOMIC AND MOLECULAR PHYSICS↗

Quantifying Energy Justice Goals in the Power Sector: Developing and Using Metrics

New policy goals are explicitly guiding the future grid toward greater energy equity. At the same time, policy goals also guide the grid toward decarbonization and resilience, while maintaining cost, security, and reliability cornerstone requirements. In conclusion, these pressures create a dilemma: moving urgently to address climate change and respond to energy disruptions, but also slowly to engage communities on the climate frontlines in earnest.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Computational Modeling of a 3D Printed Recuperator and Subsequent Experimental Loop for Supercritical Carbon Dioxide Cycles

Oak Ridge National Laboratory (ORNL), in collaboration with mechanical-thermal energy storage (mTES) provider EarthEn, a US Department of Energy (DOE) Lab-Embedded Entrepreneurship Program (LEEP) recipient at ORNL’s Innovation Crossroads 2023, is utilizing a state-of-the-art patented 3D printing technique to design an additively manufactured (AM) supercritical CO2 (sCO2) recuperator (REC) for EarthEn’s charge/discharge cycle. The AM REC will be printed at ORNL’s Manufacturing Demonstration Facility using Inconel Alloy 718 and tested on a closed-loop, ∼100 kW scale experimental facility that is under construction. The testing will compare the printed design against a commercial-off-the-shelf Printed Circuit Heat Exchanger (PCHE) REC. The design of the sCO2 facility is guided by a Modelica-based system model which is primarily dependent on the open-source TRANSFORM library developed at ORNL and uses the open-source CoolProp library for thermophysical properties of sCO2 via the External Media library. It is envisioned that an iterative process will be followed between the physical loop and the system model wherein the initial experimental data will be used to tune the model, which in turn will be used to guide future loop operation. Simultaneously, the AM REC is being designed using computer-aided design models, and it is also being analyzed for hydraulic and thermomechanical response using commercial computational fluid dynamics software, Simcenter STAR-CCM+, on highperformance computing resources.1

See, Nate [ORNL] (ORCID:0000000178581202)↗

Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation

Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs) could potentially bridge the gap. Their capacity to store and retrieve data from large databases provides them with a breadth of knowledge across disciplines. However, their generalized knowledge base can lack targeted, industry-specific knowledge. To this end, we present two LLM-based applications based on the GPT-4 architecture: (1) The Composites Guide: a system that provides expert knowledge on composites material and connects users with research and industry professionals who can provide additional support and (2) The Equipment Assistant: a system that provides guidance for manufacturing tool operation and material characterization. By combining the knowledge of general AI models with industry-specific knowledge, both applications are intended to provide more meaningful information for engineers. In this paper, we discuss the development of the applications and evaluate it through a benchmark and two informal user studies. The benchmark analysis uses the Rouge and Bertscore metrics to evaluate our models’ performance against GPT-4o. The results show that GPT-4o and the proposed models perform similarly or better on the ROUGE and BERTScore metrics. The two user studies supplement this quantitative evaluation by asking experts to provide qualitative and open-ended feedback about our model’s performance on a set of domain-specific questions. The results of both studies highlight a potential for more detailed and specific responses with the Composites Guide and the Equipment Assistant.

Kapoor, Gunnika [Oak Ridge National Laboratory (OR↗

Unveiling phase evolution of complex oxides toward precise solid-state synthesis

The precise synthesis of high-purity materials is crucial in accelerating materials discovery. However, the lack of theoretical understanding and practical guidance poses challenges, particularly for materials with compositional and structural complexity. Here, we propose a feasible principle toward synthesizing complex inorganic solids. This principle involves the introduction of an inducer that induces crucial intermediates, which in turn guide the synthesis pathway toward the target materials through structural templating, named inducer-facilitated assembly through structural templating (i-FAST). We validate this principle with three distinct oxides: garnet Li6.5La3Zr1.5Ta0.5O12, perovskite BaCo0.8Sn0.2O3, and pyrochlore Gd1.5La0.5Zr2O7. This structural templating approach enables synthesis along predesigned pathways, forming intermediates that are thermodynamically favored for prior formation and kinetically preferred for the final product, resulting in precisely synthesizing high-purity target materials. This study not only represents a substantial advancement in comprehending the interplay between thermodynamics/kinetics and phase evolution in complex solid synthesis but also provides an effective strategy for guiding exploratory solid-state synthesis.

Yang, Lin↗

Topological photonic crystal fiber

Photonic crystal fibers (PCFs) provide a versatile platform for various applications, thanks to the flexibility with which light guiding can be customized by modifying the fiber geometry. We realize a PCF with guided modes produced by photonic band structure topology rather than conventional mode-trapping mechanisms. The design, which is compatible with the stack-and-draw fabrication process, consists of a cross-sectional photonic topological crystalline insulator with a disclination. A bulk-defect correspondence produces degenerate topological modes, lying below the cladding light line. We use various theoretical methods to confirm their topological origins, including a spectral localizer that makes minimal assumptions about the band structure. Our experiments on the fabricated fiber show it transmitting visible to near-infrared light with low losses of 10 to 20 decibels per kilometer, which do not increase substantially when the fiber is bent. A comparable solid-core PCF of conventional design exhibits substantially higher bending losses. Optical fibers based on topological modes hold promise for improved performance and versatile functionalities.

Zhu, Bofeng [Nanyang Technological Univ. (Singapor↗

CRISPR-prime editing, a versatile genetic tool to create specific mutations with a single nucleotide resolution in Leptospira

ABSTRACT Leptospirosis, caused by pathogenic bacteria from the genusLeptospira, is a global zoonosis responsible for more than one million human cases and 60,000 deaths annually. The disease also affects many domestic animal species. Historically, genetic manipulation ofLeptospirahas been difficult to perform, resulting in limited knowledge on pathogenic mechanisms of disease and the identification of virulence factors. The application of CRISPR/Cas9 and its variations have helped fill these gaps but the generation of knockout mutants remains challenging because double-strand breaks (DSBs) inflicted by Cas9 nuclease are lethal toLeptospiracells. The novel CRISPR prime editing (PE) strategy is the first precise genome-editing technology that allows deletions, insertions, and base substitutions without introducing DSBs. This revolutionary technique utilizes a nickase Cas9 that cleaves a single strand of DNA, coupled with an engineered reverse transcriptase and a modified single-guide RNA (termed prime editing guide RNA) containing an extended 3′ end with the desired edits. We demonstrate the application of CRISPR-PE in both saprophytic and pathogenicLeptospirafrom multiple species and serovars by introducing deletions or insertions into target DNA with a remarkable precision of just one nucleotide. Additionally, we demonstrate the ability to genetically manipulateLeptospira borgpetersenii, a prevalent pathogenic species of humans, domestic cattle, and wildlife animals. Rapid plasmid loss by mutated strains in liquid culture allows for the generation of knockout strains without selective markers, which can be readily used to elucidate virulence factors and develop optimized bacterin and/or live vaccines against leptospirosis. IMPORTANCE Leptospirosis is a geographically widespread bacterial zoonosis. Genetic manipulation of pathogenicLeptospiraspp. has been laborious and difficult to perform, limiting our ability to understand how leptospires cause disease. The application of the CRISPR/Cas9 system toLeptospiraenhanced our ability to generate knockdown and knockout mutants; however, the latter remains challenging. Here, we demonstrate the application of the CRISPR prime editing technique inLeptospira, allowing the generation of knockout mutants in several pathogenic species, with mutations comprising just a single nucleotide resolution. Notably, we generated a mutant in theLeptospira borgpeterseniibackground, a prevalent pathogenic species of humans and cattle. Our application of this method opens new avenues for studying pathogenic mechanisms ofLeptospiraand the identification of virulence factors across multiple species. These methods can also be used to facilitate the generation of marker-less knockout strains for updated and improved bacterin and/or live vaccines.

Microbiology↗

High-quality Acinetobacter genomes recovered from combat wounds via metagenomic sequencing resemble cultured isolate genomes

The ability to accurately characterize wound pathogens is critical to informing clinical decisions for wound infections with complex treatment requirements. Acinetobacter baumannii is an impactful nosocomial pathogen in combat wounds and civilian hospital-acquired infections. An informed understanding of the phylogenetics and epidemiology of A. baumannii infections in military and civilian environments could guide approaches that improve antibiotic treatment regimens for both military and civilian patients. Whole-genome data for bacterial strains can be difficult to obtain due to challenges in culturing isolates from preserved military specimens. Metagenomic sequencing and assembly create opportunities for genomic analysis of pathogens directly from clinical specimens. The ability to perform comparative analyses between metagenome-derived genomes and culture-derived genomes would support a range of comparative bacterial genomic studies. Wound tissue biopsy and effluent samples from combat injuries were subjected to metagenomic sequencing and assembly. In total, 42 microbial metagenome-assembled genomes (MAGs) were obtained directly from metagenomic sequence data, 36 of which were designated “high” quality. Thirty of these genomes corresponded to Acinetobacter, with 29 mapping specifically to A. baumannii. Other observed genera included Bordetella, Citrobacter, Escherichia, and Pseudomonas. Single-copy and multi-copy orthologs were identified across Acinetobacter MAGs and publicly available isolate genomes derived from military and civilian sources. Both MAG and military isolate genomes were annotated with antimicrobial resistance data, and MAG genomes were statistically comparable to genomes obtained from isolates. Our results highlight the potential of de novo metagenome assembly for enabling high-resolution characterization directly from clinical specimens, thereby improving diagnostic precision, guiding antimicrobial stewardship, and enhancing understanding of pathogen evolution across diverse healthcare and battlefield environments.

Acinetobacter baumannii↗

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗

BSMV-mediated genome editing exhibits host-specific heritability: germline transmission in barley and somatic edits in Nicotiana benthamiana

Plant RNA virus–mediated guide RNA (gRNA) delivery represents a transformative advance in genome editing technologies. Unlike conventional transformation methods that rely on labor-intensive tissue culture and regeneration for each individual gRNA delivery, viral vectors can rapidly and systemically transmit gRNAs into pre-established Cas-expressing plants, providing an accelerated route for functional genomics and trait discovery directly in planta . However, key design parameters, including subgenomic promoter choice, transcript architecture, and their effects on viral fitness and editing outcomes, remain to be elucidated for most viral platforms. We developed five Barley stripe mosaic virus (BSMV) vectors, each with distinct subgenomic promoter elements to drive single gRNA expression. These were initially evaluated in Cas9-expressing transgenic Nicotiana benthamiana plants targeting the Phytoene desaturase ( PDS ) gene to compare their editing efficiencies. Single gRNAs expressed under the duplicated γb subgenomic promoter or when fused directly to the γb genome achieved the highest mutation frequencies (up to 90% at 60 days post-inoculation), whereas β1- and β2-driven sgRNAs produced delayed and reduced editing. Thus, promoter selection critically determines gRNA accumulation and the efficacy of BSMV-mediated genome editing. The top-performing design was then applied to Cas9-expressing barley ( Hordeum vulgare ) targeting HvCMF7 (conferring green-white variegation) and HvGW2.1 (impacts grain width and weight). BSMV spread systemically throughout barley, inducing somatic and heritable mutations at frequencies up to 100%, with virus-free edited progeny. In contrast, despite robust somatic editing in N. benthamiana, no heritable mutations were detected indicating species-dependent limitations in germline transmission. Our systematic comparison of subgenomic promoter architectures establishes clear design principles for optimizing viral vector–mediated delivery. Promoter choice and transcript structure critically shape editing efficiency and viral stability. The host-specific boundary for germline editing, defined by efficient heritable editing in barley but not N. benthamiana , highlights where BSMV offers advantages and where alternative vectors or hybrid strategies are required, guiding rational platform selection for diverse crop species and applications. Collectively, these findings establish BSMV as a promising next-generation vector for rapid, tissue culture–free, and transformation-independent genome editing in cereals and other recalcitrant monocots.

barley↗

Data for NB6 HBRR Science Design ORNL/TM-2025/3807

Data for the report (ORNL/TM-2025/3807) that describes the calculations and the Monte Carlo Ray Tracing simulations performed using the McStas package to determine the coatings and geometry for the NB-6 guide. It provides the information to inform the mechanical design, validation tests and verification that it meets the science requirements.

47 OTHER INSTRUMENTATION↗

Management of Risks Associated with Application of Novel Materials in Novel Operating Environments in Novel Reactor Designs

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. These challenges are discussed in the paper, and a potentially applicable modeling approach based on cumulative damage rather than failure rates is briefly illustrated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Wafer-scale waveguide sidewall roughness scattering loss characterization by image processing

Photonic integrated circuits (PICs) are vital for developing affordable, high-performance optoelectronic devices that can be manufactured at an industrial scale, driving innovation and efficiency in various applications. Optical loss of modes in thin film waveguides and devices is a critical measure of their performance. Thin film growth, lithography, masking, and etching processes are imperfect processes that introduce significant sidewall and top-surface roughness and cause dominating optical losses in waveguides and photonic structures. This roughness, as perturbations couple light from guided to far-field radiation modes, leads to scattering losses that can be estimated from theoretical models. Typically, with UV-based lithography, sidewall roughness is significantly larger than wafer-top surface roughness. Atomic force microscopy (AFM) imaging measurement gives a 3D and high-resolution roughness profile, but the measurement is inconvenient, costly, and unscalable for large-scale PICs and at wafer-scale. Here, we evaluate the sidewall roughness profile based on 2D high-resolution scanning electron microscope (SEM) imaging. We characterized the loss on two homemade nitride and oxide films on 3-inch silicon wafers with 12 waveguide devices on each and correlated the scattering loss estimated from a 2D image-based sidewall profile and theoretical Payne model. The lowest loss of guided fundamental transverse electric (TE 0 ) mode is found at 0.075 dB/cm at 633 nm across 24 devices, a record at visible wavelength. Our work shows 100% success (edge continuity span exceeding 95% of image width/height) in edge detection in image processing of all images to estimate autocorrelation function and optical mode loss. These demonstrations offer valuable insights into waveguide sidewall roughness and a comparison of experimental and 2D SEM image processing based loss estimations with applications in loss characterization at wafer-scale PICs.

Khurana, Mohit (ORCID:0000000207898672)↗

Ground surface temperature derived Snow Cover Properties, Seward Peninsula, Alaska, 2019-2023

Snow-ground interface temperatures have been collected at the Teller mile marker 27 and Kougarok mile marker 64 field sites on the Seward Peninsula, Alaska from 2019 through 2023 (with data missing from Fall 2020 through Summer 2021 due to COVID). Temperatures were measured using iButton Link DS1921G-F5# Thermochron miniature temperature sensors and Tinytag TGP-4017 internal sensors deployed across the Kougarok 64 and Teller 27 field sites. These sensors are a cost-efficient way to collect snow-ground interface temperatures at a high spatial resolution, and when paired with air temperature data these measurements can provide insight into fine-scale variability in snowpack characteristics across the study sites. From this data, snow process metrics were calculated at each sensor location based on the methods outlined in Staub and Delaloye, 2017. Metrics are calculated daily for each sensor as well as over the entire season. These metrics include ground surface temperature (°C), the number of days under snow cover (number of days), the insulation effect of snow (unitless), the length of the transitional snow periods (number of days), as well as intermediaries such as temperature variability. Calculating these snow processes relies on the assumption that when snow covers a temperature sensor, it is buffered from diurnal fluctuations in air temperature by the insulating snow layer. More information on the calculated metrics can be found in the User Guide of this dataset, as well as in Staub and Delaloye’s 2017 publication Using Near-Surface Ground Temperature Data to Derive Snow Insulation and Melt Indices for Mountain Permafrost Applications. This dataset includes one daily and one seasonal *.csv file of metrics for every year of data, a daily and a seasonal *.csv data dictionary, and one User Guide document (*.pdf) describing data collection and processing.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort 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↗