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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 343 records · Page 19

Data for Post-Access Report: Tidal Energy Resource Characterization and Model Validation via the Assessment of Cost-effective Spatially Distributed Current Measurements from microFloat Swarms

This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for producing accurate predictions of tidal energy production over larger arrays of tidal turbines. The data contained in this archive includes field observations of water velocity from a series of short surveys in Agate Pass taken on August 20th, 2020 using station-keeping ADCP (acoustic doppler current profiler) measurements, drifting downward-looking ADCPs, and microFloats, gathered by researchers at APL-UW under a previous project. It also includes high-resolution hydrodynamic model runs for the site during that time generated under TEAMER support. An explanatory file (.pdf format) describes the survey and field data structure. Processed data is stored in .mat format. Survey summary: start time, number of floats, water level. microFloat data: - Cleaned data for each float in survey, - Time series of position (lat., lon.), depth (relative to surface), and horizontal velocity (u, v) Drifting ADCP data: - Cleaned data for each drifting ADCP in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) Stationary ADCP data: - Cleaned data for each station-keeping data set in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) FVCOM (Finite Volume Coastal Ocean Model) model outputs: Water level and velocity, as well as derived variables (e.g., power density) from the final refined model simulations for the Agate Pass subdomain. Contained in NetCDF and ASCII files for the duration of August 18th and 20th 2020 field surveys. Additional scripts for processing the data and generating the figures in the report are included.

16 TIDAL AND WAVE POWER↗

Practically Accessible All-Solid-State Batteries Enabled by Organosulfide Cathodes and Sulfide Electrolytes

The combination of organic electrode materials and sulfide electrolytes is expected to enable the development of all-solid-state organic batteries featuring high energy density and long-term sustainability. In this work, thiuram hexasulfide is reported as a low-cost and high-capacity organic cathode for solid-state batteries based on sulfide electrolytes, delivering a capacity of ~600 mAh g -1 and retaining 80.8 % capacity after 500 cycles. An electrochemically reversible change of the cathode interface was revealed upon cycling. Full cell displays an oscillating stress change up to 0.6 MPa during cycling, predominated by the anode side. The energy density is 1140 Wh kg -1 at the material level and 376 Wh kg -1 at the electrode level, which are among the best-reported organic cathodes to date. A high areal capacity of 10.4 mAh cm -2 is reached with a high mass loading cathode. A dry-film approach is further explored to manufacture sheet-type cells. Free-standing electrolyte film is merely ~48 μm thick and demonstrates an ultralow areal resistance of 3.9 Ω cm 2 , significantly boosts the cell-level energy density and reduces the cell internal resistance.

25 ENERGY STORAGE↗

Enhanced Rate Capability of Ion‐Accessible Ti 3 C 2 T x ‐NbN Hybrid Electrodes

Abstract Although 2D Ti 3 C 2 T x is a good candidate for supercapacitors, the restacking of nanosheets hinders the ion transport significantly at high scan rates, especially under practical mass loading (>10 mg cm −2 ) and thickness (tens of microns). Here, Ti 3 C 2 T x ‐NbN hybrid film is designed by self‐assembling Ti 3 C 2 T x with 2D arrays of NbN nanocrystals. Working as an interlayer spacer of Ti 3 C 2 T x , NbN facilitates the ion penetration through its 2D porous structure; even at extremely high scan rates. The hybrid film shows a thickness‐independent rate performance (almost the same rate capabilities from 2 to 20 000 mV s −1 ) for 3 and 50 µm thick electrodes. Even a 109 µm thick Ti 3 C 2 T x ‐NbN electrode shows a better rate performance than 25 µm thick pure Ti 3 C 2 T x electrodes. This method may pave a way to controlling ion transport in electrodes composed of 2D conductive materials, which have potential applications in high‐rate energy storage and beyond.

Wang, Hao↗

Repurposing Post-Consumer Polyethylene to Access Cross-Linked Polyethylene with Reprocessabilty, Recyclability, and Tunable Properties

Polyethylene (PE) is the most widely produced plastic but accumulation and resistance to degradation has significantly contributed to the plastic waste crisis. Upcycling has presented promising solutions to transform PE waste into value-added products. In this study, mixed post-consumer PE was successfully repurposed into reprocessable and chemically recyclable cross-linked polyethylene (XLPE). This process involved converting PE into telechelic oligomers, followed by repolymerization using a hybrid cross-linking system consisting of a dynamic cross-linker 2,4,6-triethoxy-1,3,5-triazine (TETA) and non-dynamic cross-linker tris(6-isocyanatohexyl)isocyanurate (Tri-HDI). In the resulting XLPE, TETA facilitated iterative reprocessing with minimal property degradation across cycles, whereas Tri-HDI helped preserve functional performance throughout service life. Compared to PE, XLPE exhibited enhanced mechanical properties, reduced creep deformation under application-relevant temperatures, and high temperature structural stability. Notably, copolymerizing PE oligomers with commercial macrodiols was employed to create composite XLPEs, enabling tuning material properties. After use, XLPE can be efficiently and selectively depolymerized under mild conditions, even when mixed with commercial insulator cables. This depolymerization allows for the recovery of the constituent building blocks, enabling purification and subsequent repolymerization for reuse. This approach demonstrates the potential of repurposing plastic waste into sustainable materials and fostering the development of a circular economy.

INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMI↗

Accessing Lanthanide-to-Lanthanide Energy Transfer in a Family of Site-Resolved [Ln III Ln III '] Heterodimetallic Complexes

The ligand H 3 L (6-[3-oxo-3-(2-hydroxyphenyl)propionyl]pyridine-2-carboxylic acid), which exhibits two different coordination pockets, has been exploited to engender and study energy transfer (ET) in two dinuclear [Ln III Ln III '] analogues of interest, [EuYb] and [NdYb]. Their structural and physical properties have been compared with newly synthesised analogues featuring no possible ET ([EuLu], [NdLu], and [GdYb]) and with the corresponding homometallic [EuEu] and [NdNd] analogues, which have been previously reported. Photophysical data suggest that ET between Eu III and Yb III does not occur to a significant extent, whereas emission from Yb III originates from sensitisation of the ligand. In contrast, energy migration seems to be occurring between the two Nd III centres in [NdNd], as well as in [NdYb], in which Yb III luminescence is thus, in part, sensitised by ET from Nd. This study shows the versatility of this molecular platform to further the investigation of lanthanide-to-lanthanide ET phenomena in defined molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

Motion-activated wildlife cameras (or “camera traps”) are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the “species model,” and one that determines if an image is empty or if it contains an animal, the “empty-animal model.” Our species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%–91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91%–94% on out-of-sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths.

59 BASIC BIOLOGICAL SCIENCES↗

A Straightforward Access to Cyclic (Alkyl)(amino)carbene Copper (I) Complexes

Here, the synthesis and characterization of cyclic (alkyl)(amino)carbene, bicyclic (alkyl)(amino)carbene and cyclic (amino)(barrelene)carbene copper (I) complexes is reported. These complexes are obtained via a scalable, versatile, green, and cost/user-friendly strategy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Anthradithiophene Donor Polymer for Organic Solar Cells with a Good Balance between Efficiency and Synthetic Accessibility

Over the past few years, the organic photovoltaics technology (OPV) has reached remarkable power conversion efficiencies (PCEs), mostly thanks to the advent of nonfullerene acceptors as well as to a high level of materials engineering. Yet, the complex materials syntheses behind these results ultimately limit technological readiness. The quest for scalable organic compounds offering high PCE and reasonably low synthetic complexity is a must to close the gap between laboratory R&D and commercial products. The synthesis and full characterization of a new conjugated polymer called PATTD is reported herein, based on a novel anthradithiophene as an electron–rich building block coupled with a commercially available dithienylbenzodithiophenedione as an electron–withdrawing comonomer. Its photovoltaic properties are studied in blends with IT–4F and IDIC as acceptors. PATTD:IT–4F–based photovoltaic devices exhibit a PCE approaching 10% and over 2300 h shelf–life stability. Finally, the PATTD scalability factor (SF), together with the PATTD–based photovoltaic performances, lead to a PCE/SF value equal to 0.297, placing such devices into the innermost circle of OPV materials, achieving one of the best compromises between efficiency and synthetic complexity and at the same time offering promising industrial perspectives.

14 SOLAR ENERGY↗

The Data Mine model for accessible partnerships in data science

Abstract The Data Mine at Purdue University is a pioneering experiential learning community for undergraduate and graduate students of any background to learn data science. The first data‐intensive experience embedded in a large learning community, The Data Mine had nearly 1300 students in academic year (AY) 2022–2023 and nearly 1700 students for AY 2023–2024. The Data Mine embodies data‐infused education, research, and collaboration. Students learn Python, R, SQL, and shell‐scripting, while working on weekly projects within a high‐performance computing (HPC) cluster. In the Corporate Partners cohort, students work on teams of 5–15 students, led by a paid student team leader. Each cohort follows an Agile approach, working on data‐intensive projects provided by industry partners and mentored by company employees. Students develop professional and data skills throughout the academic year, from August through April. Many students return in subsequent years to the program, increasing their tenure with a Corporate Partner. Student teams are inherently interdisciplinary; students from 133 different majors are involved in the program, ranging from new incoming students through PhD level students. These interdisciplinary teams of students bring new perspectives to challenging problems in which data science is a key part of the solution. The interdisciplinary teams foster an environment of synthesis with ideas and solutions. Students come together with different life experiences, different levels of technical skill, but also varying ways they navigate paths to solutions because of the variety of majors represented, resulting in a more creative and robust solution than a traditional data science program. This article is categorized under: Applications of Computational Statistics > Education in Computational Statistics

Betz, Margaret A.↗

Universally Accessible Structural Data on Macromolecular Conformation, Assembly, and Dynamics by Small Angle X-Ray Scattering for DNA Repair Insights.

Structures provide a critical breakthrough step for biological analyses, and small angle X-ray scattering (SAXS) is a powerful structural technique to study dynamic DNA repair proteins. As toxic and mutagenic repair intermediates need to be prevented from inadvertently harming the cell, DNA repair proteins often chaperone these intermediates through dynamic conformations, coordinated assemblies, and allosteric regulation. By measuring structural conformations in solution for both proteins, DNA, RNA, and their complexes, SAXS provides insight into initial DNA damage recognition, mechanisms for validation of their substrate, and pathway regulation. Here, we describe exemplary SAXS analyses of a DNA damage response protein spanning from what can be derived directly from the data to obtaining super resolution through the use of SAXS selection of atomic models. We outline strategies and tactics for practical SAXS data collection and analysis. Making these structural experiments in reach of any basic and clinical researchers who have protein, SAXS data can readily be collected at government-funded synchrotrons, typically at no cost for academic researchers. In addition to discussing how SAXS complements and enhances cryo-electron microscopy, X-ray crystallography, NMR, and computational modeling, we furthermore discuss taking advantage of recent advances in protein structure prediction in combination with SAXS analysis.

Chinnam, Naga Babu↗

Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access

Computing plays a significant role in all areas of high energy physics. The Snowmass 2021 CompF4 topical group's scope is facilities R&D, where we consider "facilities" as the computing hardware and software infrastructure inside the data centers plus the networking between data centers, irrespective of who owns them, and what policies are applied for using them. In other words, it includes commercial clouds, federally funded High Performance Computing (HPC) systems for all of science, and systems funded explicitly for a given experimental or theoretical program. This topical group report summarizes the findings and recommendations for the storage, processing, networking and associated software service infrastructures for future high energy physics research, based on the discussions organized through the Snowmass 2021 community study.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impact of downhole pressure and fluid-access on the effectiveness of wellbore cement expansion additives

Autogenous shrinkage of wellbore cement widely impairs zonal isolation. MgO-based cement expansion additives (CEAs) can mitigate this shrinkage, or even impart net expansion, by creating porosity through displacive crystal growth-processes. However, both MgO hydration and autogenous shrinkage behaviour depend strongly on stress state. Evaluation of CEA performance in wellbore cements therefore requires testing under elevated pressures representative for subsurface environments. We report experiments addressing the chemical and bulk volume changes that occur in cement hydrating at 10 MPa confining pressure and 90 °C. Volumetric response was investigated as function of MgO concentration, external water supply, and pore pressure decrease through water consumption during reaction. Results show the bulk expansion achieved using MgO-based CEAs diminishes markedly with increasing effective confining pressure or, equivalently, upon restricting fluid supply. This reduced expansion-potential under pressure has profound implications for slurry design, notably regarding CEA-concentrations required to counteract micro-annulus formation while maintaining low cement permeability.

36 MATERIALS SCIENCE↗

Triple oxygen and hydrogen stable isotope composition of water in Murchison carbonaceous chondrite accessed by thermogravimetry-enabled laser spectroscopy

For this work, we have developed the capability to measure 17 O/ 16 O in H 2 O and OH - of hydrous minerals by a technique using thermogravimetric analysis coupled with isotope ratio infrared spectroscopy (TGA-IRIS) on a suite of liquid water standards, terrestrial mineral standards, multi-mineral synthetic mixtures of terrestrial samples, and Murchison carbonaceous chondrite. This 17 O/ 16 O analytical capability is combined with the previously developed TGA-IRIS capability of 18 O/ 16 O, which enables us to calculate Δ `17 O values. Additionally, we have made 2 H/ 1 H measurements by TGA-IRIS on the suite of materials. Analyses of 328 standard water samples sealed into silver tubes (0.25 μL, 174 VSMOW and 154 GISP) analyzed over the course of three years yielded δ 18 O values by TGA-IRIS with precision of ±0.30 ‰, δ 17 O of ±0.24 ‰, Δ `17 O of ±0.126 ‰, and δ 2 H ± 7.5 ‰ (± 1 Std. Dev.). TGA-IRIS analyses of a suite of hydrous minerals (oxy-hydroxide, mica, serpentines, sulfide, phyllosillicates) yields similar precision. TGA-IRIS analyses of the CM2 carbonaceous chondrite Murchison resulted in δ 18 O, δ 17 O, Δ `17 O, and δ 2 H values of the H 2 O and/or OH - from its hydrous minerals. Δ `17 O values of Murchison H 2 O range from 1.034 ‰ at 350 °C, to -0.368 ‰ at 650 °C, to -1.75 ‰ at 850 °C. TGA-IRIS can generate Δ `17 O values of H 2 O and/or OH - in hydrous materials that are well within the precision needed for the analysis of meteoritic samples, as well as samples returned from asteroids, such as Ryugu and Bennu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗