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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modeling the Effects of Artificial Drainage on Agriculture-Dominated Watersheds Using a Fully Distributed Integrated Hydrology Model

In agriculture-dominated watersheds where natural drainage is poor, agricultural ditches (narrow engineered channels) and tile drains (perforated pipes) are widely employed to enhance surface and subsurface drainage, respectively. Despite their relatively small scale, these features exert substantial control over the hydro-biogeochemical function of watersheds and their effects need to be represented in the models. We introduce a novel strategy to incorporate the effects of artificial agricultural drainage into a fully distributed basin-scale integrated surface-subsurface hydrology models. In our approach, narrow agriculture ditches for surface drainage are resolved efficiently using ditch-aligned computational meshes that are hydrologically conditioned to ensure connectivity in the stream/ditch network. For tile drainage in the subsurface, we use the physically based Hooghoudt's drainage equation as a subgrid model and route the water drained through tiles to the nearest ditch. Without site-specific calibration, this model reproduced observed streamflow in the Portage River Watershed (>1,000 km 2 ) as recorded by a USGS gauge with good accuracy (normalized KGE = 0.81) and outperformed a calibrated SWAT model (normalized KGE = 0.68). Numerical experiments confirm that artificial drainage reduces surface inundations and effectively controls the water table. At the watershed scale, artificial drainage increases baseflow but has little effect on watershed discharges above the 90th percentile. The strong physical underpinnings and reduced need for calibration allow us to study the impacts of artificial drainage on distributed hydrological response in terms of fluxes and states and provide a platform for investigating watershed-scale nutrient transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Elucidating and predicting the dynamic evolution of water and land systems due to natural and energy-related forcings

Focal Area(s): 3. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI; & 1. Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: Interactions between water, land, and energy systems are complex and occur on a variety of scales, ranging from local to basinal to regional. Accurately predicting the behavior of ground water and surface water systems for 5-10 years and beyond requires an understanding of the current system and the ability to model both the natural system at scale and human-induced forcings related to energy and other activities. Artificial intelligence and machine learning (AI/ML) combined with modern compilation and integration efforts for U.S. groundwater and surface water systems present potential solutions to bolstering detailed physics-based models of these systems. Big data tied with ML and physics-based modeling can drive breakthroughs in understanding the earth system, but research is often impeded by data access (e.g., privacy issues), quality, formats, gaps, multi-source, multi-scale, integration, and spatiotemporal challenges. Effective integration of real data and simulated (synthetic) data that fill gaps is critical. Overcoming these complex data and model integration challenges will enable a transformational approach to acquiring enhanced understanding of environmental systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Nonequilibrium Solvent Effects during Photodissociation in Liquids: Dynamical Energy Surfaces, Caging and Chemical Identity

In the gas phase, potential energy surfaces can be used to provide insight into the details of photochemical reaction dynamics. In solution, however, it is unclear what potential energy surfaces, if any, can be used to describe even simple chemical reactions such as the photodissociation of a diatomic solute. In this paper, we use mixed quantum/classical (MQC) molecular dynamics (MD) to study the photodissociation of $Na$ $^+_2$ in both liquid Ar and liquid tetrahydrofuran (THF). We examine both the gas-phase potential surfaces and potentials of mean force (PMF), which assume that the solvent remains at equilibrium with the solute throughout the photodissociation process and show that neither resemble a nonequilibrium dynamical energy surface that is generated by taking the time integral of work. For the photodissociation of $Na$ $^+_2$ in liquid Ar, the dynamical energy surface shows clear signatures of solvent caging, and the degree of caging is directly related to the mass of the solvent atoms. For $Na$ $^+_2$ in liquid THF, local specific interactions between the solute and solvent lead to changes in chemical identity that create a kinetic trap that effectively prevents the molecule from dissociating. Here, the results show that nonequilibrium effects play an important role even in simple solution-phase reactions, requiring the use of dynamical energy surface to understand such chemical events.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Stabilizing high-Ni cathodes with gradient surface Ti-enrichment

High-Ni cathodes are being intensely pursued worldwide for electric vehicles and other energy-dense applications due to their high capacity and low cost. However, structural instabilities during electrochemical cycling and when subjected to thermal treatment have been the major issues hindering their practical deployment. We here report a rational design of coating-integrated-into-synthesis protocol for fabricating surface Ti-enriched LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811#Ti) material. The coating to intermediates is crucial to obtain high structural ordering, both in the bulk and surface of high-Ni cathodes, and the Ti substitute has a unique tri-valence (Ti 3+ ) in a gradient surface distribution. Further, the simulations of projected density of states in the atomistic understanding further certify significantly enhanced stability of lattice oxygen for the NMC811 through such a Ti 3+ -based structure reinforcement. Consequently, the NMC811#Ti cathode delivers a high capacity up to 200mAhg -1 at 0.1 C, along with superior stabilities during air-storage and thermal treatment (up to 297°C at the fully charged state under differential scanning calorimetric measurements). The corresponding NMC811#Ti||graphite full cell exhibits a desired 83.6% capacity retention after 1000 cycles at 0.5 C in a voltage range of 2.8–4.3V. This work demonstrates a delicate surface reinforcement to stabilize high-Ni cathodes for long-life and safe lithium-ion batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bridging Structural and Chemical Insights: Integrating In Situ Electron Microscopy and X-ray Spectroscopy for Catalysis Research

Environmental transmission electron microscopy probes the local structure, composition, and chemistry of materials under gas environments, while ambient-pressure X-ray photoelectron spectroscopy provides ensemble chemical and electronic structure information in gaseous conditions. Both techniques utilize similar differential pumping schemes to mitigate electron scattering by the gas phase, allowing for unique opportunities to correlate gas–surface interactions across comparable pressure ranges. Their integration has advanced the understanding of various catalytic reactions, including the water–gas-shift reaction, CO oxidation, and surface passivation dynamics. In conclusion, this Mini-Review discusses their methodological advancements, challenges, and potential for further integration with other in situ techniques to address complex catalytic phenomena and guide catalyst design.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Surface-Functionalized, Two-Dimensional Polymer Electrochromic Layers as Ultrafast, Multi-State Infrared Optical Gates

Electrochromic devices have widespread application potential, but the currently available switching speeds limit broad real-world implementation of this technology. Here, we report surface-engineered two-dimensional polymers with ionophilic pores that offer unprecedented switching speeds in solid-state, two-terminal, electrochromic devices. In particular, we demonstrate that a crystalline donor–acceptor 2DP functionalized with ethylene glycol oligomers exhibits multistate infrared absorption that is 4× faster (t c = 320 ms) with 3× coloration efficiency (491 cm 2 C –1 ) compared to an alkyl functionalized 2DP constructed from the same chromophores. The functionalized nanoporous surfaces enable rapid switching in these materials under either oxidative or reductive conditions, allowing us to access a range of robust, stable optical responses in a single electrochromic layer. These attributes led us to leverage surface-functionalized 2DPs as multistate infrared logic gates. Collectively, this work demonstrates that surface engineering of nanoporous crystalline lattices is a promising approach to co-optimize the electronic and ionic conductivities required to achieve rapidly switchable electrochromic layers. Beyond speed and efficiency, the demonstration of multistate infrared characteristics shows that electrochromic frameworks are useful in integrated optoelectronic circuits. This positions surface-engineered 2DPs as improved electrochromic coatings and a new material platform for photonic information processing and adaptive devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗
DOE OSTI2025

Numerical framework for integrated additive manufacturing-compression molding (AM-CM) of thermoplastic composites

Additive manufacturing-compression molding (AM-CM) has emerged as a transformative technology in advanced composite manufacturing. Additive manufacturing (AM) offers high design flexibility and the ability to produce complex geometries with precisely aligned fibers in the preferred orientation. Compression molding (CM) enhances composite materials by providing excellent dimensional stability, reduced porosity, high production rates, and a smooth surface finish. Despite these advantages, extensive integrated analysis is required to optimize processing conditions for improved fiber orientation distribution (FOD) and porosity control. Here, this study develops a comprehensive numerical model to simulate the AM-CM manufacturing process. The model isolates the effects of both the AM and CM phases while also capturing their integration. Additionally, it accounts for heat transfer, temperature-dependent viscosity, and fiber orientation in the extruded fiber-filled polymer, accurately representing material behavior during processing. This approach enables the analysis of interactions between deposited beads of complex strand shapes and their interface regions after full compression. Moreover, the model predicts key parameters such as polymer flowability, fiber orientation, and temperature evolution in AM-CM parts. By optimizing processing conditions, it facilitates a controlled and predictable microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Innovative laser-based methods for monitoring fuel retention in ITER

This paper addresses the challenge of tritium inventory management in ITER and future fusion reactors, highlighting the importance of accurate tritium measurement and its spatial distribution within the vacuum vessel. Given ITER’s operational constraints, especially the limit on tritium retention, precise measurement is essential for both safety and regulatory compliance. To tackle these questions, the paper presents the T-monitor diagnostic system developed by Forschungszentrum Jülich, which uses Laser-Induced Desorption (LID) in combination with Diagnostic Residual Gas Analysis (DRGA) to measure hydrogen isotope concentrations on the surface of divertor tiles. The system integrates a high-power laser, advanced optical components, and a Fast Scanning Mirror Unit (FSMU) for accurate laser spot positioning with rapid response. Designed to measure in situ tritium retention, the diagnostic provides high-resolution spatial mapping, vital for evaluating detritiation strategies. The laser heating process increases the divertor surface temperature to 1600 K within the laser spot, promoting hydrogen isotope desorption. Accurate measurements require the precise control of laser parameters, including pulse duration and spot size, with a target relative accuracy of 20%. The optical design includes both in-vessel and ex-vessel components, such as durable high-reflectivity mirrors made of gold and copper, selected not only for their infrared performance but also for their transmission of visible wavelengths for observation purposes. To protect optical components from contamination, a pneumatic shutter is used.

Hydrogen isotopes↗
DOE OSTI2024

Regioselective On-Surface Synthesis of [3]Triangulene Graphene Nanoribbons

The integration of low-energy states into bottom-up engineered graphene nanoribbons (GNRs) is a robust strategy for realizing materials with tailored electronic band structure for nanoelectronics. Low-energy zero-modes (ZMs) can be introduced into nanographenes (NGs) by creating an imbalance between the two sublattices of graphene. This phenomenon is exemplified by the family of [n]triangulenes (n ϵ $\mathbb{N}$). Here, we demonstrate the synthesis of [3]triangulene-GNRs, a regioregular one-dimensional (1D) chain of [3]triangulenes linked by five-membered rings. Hybridization between ZMs on adjacent [3]triangulenes leads to the emergence of a narrow band gap, E g,exp ~ 0.7 eV, and topological end states that are experimentally verified using scanning tunneling spectroscopy. Tight-binding and first-principles density functional theory calculations within the local density approximation corroborate our experimental observations. Our synthetic design takes advantage of a selective on-surface head-to-tail coupling of monomer building blocks enabling the regioselective synthesis of [3]triangulene-GNRs. Detailed ab initio theory provides insights into the mechanism of on-surface radical polymerization, revealing the pivotal role of Au-C bond formation/breakage in driving selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Selective Adsorption of Thiol-Containing Molecules on Copper Sulfide Surfaces via Molecule–Surface Disulfide Bridges

Recent results in the fields of nanoenhanced agriculture and expanding interest in prebiotic chemistry have placed increased emphasis on understanding the chemically selective interaction of small molecules with the surfaces of metal sulfides. Here, we present an integrated experimental and computational study of the interaction of thiol-containing molecules with copper sulfide (covellite) surfaces in aqueous media. In situ Fourier-transform infrared (FTIR) measurements and ex situ X-ray photoelectron spectroscopy (XPS) measurements show that molecules bearing free thiol groups, including glutathione and cysteine, bind strongly to CuS (covellite) nanoparticles and to CuS (001) single crystals, while control studies show that similar molecules lacking the free thiol group exhibit much less binding. Additional experiments show that these thiol-containing molecules interact transiently with CuO nanoparticle surfaces but are readily removed by rinsing. The FTIR and XPS experiments demonstrate that adsorption of molecular thiols to CuS surfaces occurs in a chemically selective manner. Further experimental studies and density functional calculations show that the preferred mode of binding is through the surface S atoms, forming a Solid–S–S–Molecule disulfide linkage. While the role of disulfide linkages in controlling structure and function of proteins and other biomolecules is widely known, the formation of surface disulfide linkages as a motif for covalent molecular binding at surfaces has not been established previously.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Photocatalytic Overall Water Splitting at the Integrated Rh–MoRhO x Cluster Heterostructure on InGaN/GaN Nanowires

The quest for efficient solar-driven water splitting, a promising avenue for clean fuel production, faces challenges due to limited solar energy conversion efficiency. Traditional approaches study the overall water splitting as two spatially separate half reactions on two unrelated sites, hindering full utilization of photogenerated charge and water molecules. To overcome these limitations, an integrated cluster heterostructure catalyst on InGaN/GaN semiconductor nanowires is proposed for the effective utilization of photogenerated charge carriers and water molecules on the same redox localization. By establishing the fast charge extraction kinetics based on InGaN/GaN nanowires, the integration of Rh and MoRhOx clusters on the nanowire surface enables simultaneous and fast hydrogen/oxygen evolution reactions at the cluster heterostructure. Furthermore, the integrated strategy can enhance the charge redistribution across the heterostructure between the two clusters, further optimizing adsorption of reaction intermediates on each cluster for boosted photocatalytic water splitting activity. Consequently, the integrated heterostructure triggers a 40-fold increased hydrogen production efficiency in an artificial leaf system. This study provides valuable insights for the rational design of advanced heterostructured photocatalysts for water splitting and beyond.

GaN nanowire↗
DOE OSTI2023

Investigation of Surface and Marine-Cloud Coupling and its Impact on Cloud Droplet Number Concentrations and Cloud Cover Over the Southern Ocean

The proposed work involves characterizing and quantifying both the thermodynamic and dynamical coupling of marine low clouds (MLC) with the sea surface using Atmospheric Radiation Measurement (ARM) observations during MARCUS field campaign and an LES model. ARM data from multiple sensors will be used (e.g., Doppler cloud radar, ceilometer, and microwave radiometer) to characterize the MLC-surface coupling by virtue of the vertical structure and integrated quantities of boundary-layer clouds, aerosols, as well as atmospheric profiles and surface meteorology. We have used a combination of case studies and statistics-based composite analyses to find any linkages between large-scale dynamics, MLC-surface coupling, and cloud and boundary layer properties, the sequence of which reflects the chain of causality. An LES model with explicit aerosol physics, which includes the cycle of aerosols by being consumed as CCN and be regenerated following cloud droplet evaporation, has been run to determine the sources and sinks of Nd and their dependence on the degree of MLC-surface coupling. We have examined the systematic differences in both Nd and cloud occurrence between the two clusters under different meteorological conditions and further examine their respective roles, as well as causal relationships by means of LES modeling. This study helped improve our understanding of the ACI by differentiating the dynamic role of the coupling and cloud physics denoted by Nd, bridging the linkage in the chain toward understanding mechanisms governing the persistence of MLC over the Southern Ocean, solving the long-lasting problem of the cloud cover underestimation over the SO by GCMs. Ample ARM data and LES model have been employed to achieve the objectives of the study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Covalent integration of polymers and porous organic frameworks

Covalent integration of polymers and porous organic frameworks (POFs), including metal-organic frameworks (MOFs), covalent organic frameworks (COFs) and hydrogen-bonded organic frameworks (HOFs), represent a promising strategy for overcoming the existing limitations of traditional porous materials. This integration allows for the combination of the advantages of polymers, i.e., flexibility, processability and chemical versatility etc., and the superiority of POFs, like the structural integrity, tunable porosity and the high surface area, creating a type of hybrid materials. These resulting polymer-POF hybrid materials exhibit enhanced mechanical strength, chemical stability and functional diversity, thus opening up new opportunities for applications across a large variety of fields, such as gas separation, catalysis, biomedical applications, environmental remediation and energy storage. In this review, an overview of synthetic routes and strategies on how to covalently integrate different polymers with various POFs is discussed, especially with a particular focus on methods like polymerization within, on and among POF structures. To investigate the unique properties and functions of these resultant hybrid materials, the characterization techniques, including nuclear magnetic resonance spectroscopy (NMR), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), transmission electron microscopy (TEM) and scanning electron microscopy (SEM), gas adsorption analysis (BET) and computational modeling and machine learning, are also presented. The ability of polymer-POFs to manipulate the pore environments at the molecular level affords these materials a wide range of applications, providing a versatile platform for future advancements in material science. Looking forward, to fully realize the potential of these hybrid materials, the authors highlight the scalability, green synthesis methods, and potential for stimuli-responsive polymer-POF materials as critical areas for future research.

Hossain, Md Amjad↗
DOE OSTI2022

Quantum states of cylindrical surface charge density for modeling plasmonic circuit elements: Nanowires, nanorods, cavities, and waveguides

Nanostructures in the form of ellipsoids, prolate spheroids, rings, and cylinders are known to exhibit resonant surface and cavity modes with applications in nanophotonics and plasmonics and, more recently, in novel quantum experiments, in which control of plasmons and their interactions with plasmons, photons, phonons, excitons, and quantum emitters are desired. Nanorods and nanowires are examples of plasmonic structures with spectral properties of potential use as interconnects and circuit components. Additionally, estimates of the surface properties of these components are needed in circuit design and integrated systems. Here, we present a quantum Hamiltonian for the cylindrical surface charge density. We then study the photon excitation of plasmons on the cylindrical surface and calculate their scattering and radiative decay rate. Nonradiative decay of plasmons induces an efficient heating of the nanoparticle and can photoacoustically excite mechanical oscillations. Computational calculations are also presented for the plasmonic modes and the ensuing excitations of nanomechanical eigenmodes of nanoparticles with near-cylindrical symmetries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Reliable bi-functional nickel-phosphate /TiO2 integration enables stable n-GaAs photoanode for water oxidation under alkaline condition

Abstract Hydrogen is one of the most widely used essential chemicals worldwide, and it is also employed in the production of many other chemicals, especially carbon-free energy fuels produced via photoelectrochemical (PEC) water splitting. At present, gallium arsenide represents the most efficient photoanode material for PEC water oxidation, but it is known to either be anodically photocorroded or photopassivated by native metal oxides in the competitive reaction, limiting efficiency and stability. Here, we report chemically etched GaAs that is decorated with thin titanium dioxide (~30 nm-thick, crystalline) surface passivation layer along with nickel-phosphate (Ni-Pi) cocatalyst as a surface hole-sink layer. The integration of Ni-Pi bifunctional co-catalyst results in a highly efficient GaAs electrode with a ~ 100 mV cathodic shift of the onset potential. In this work, the electrode also has enhanced photostability under 110 h testing for PEC water oxidation at a steady current density J ph > 25 mA·cm −2 . The Et-GaAs/TiO 2 /Ni-Pi║Ni-Pi tandem configuration results in the best unassisted bias-free water splitting device with the highest J ph (~7.6 mA·cm −2 ) and a stable solar-to-hydrogen conversion efficiency of 9.5%.

08 HYDROGEN↗
DOE OSTI2025

Structure and Sulfur: Tuning the Viscoelastic and Surface Properties of Natural Keratin Fibers

Natural keratin fibers, such as wool, possess a complex hierarchical structure that governs their mechanical properties and surface energy. However, the extent to which these characteristics are influenced by combined contributions of structural variations (e.g., fiber diameter, intermediate filament (IF) packing) and chemical composition (e.g., disulfide bond density) remains poorly understood. In this study, we investigate wool fibers from five sheep breeds (Merino, Polwarth, Cheviot, Eider, and Devon) to elucidate how these factors influence viscoelasticity and surface interactions. Using a multimodal approach integrating interfacial and bulk characterization methods, including inverse gas chromatography (IGC), atomic force microscopy-infrared spectroscopy (AFM-IR), X-ray photoelectron spectroscopy (XPS), uniaxial tensile testing, and synchrotron small-angle X-ray scattering (SAXS), we show that the nanometer-thick 18-methyleicosanoic acid (18-MEA) layer is consistently present across all wool types and plays a key role in governing hydrophobicity and surface heterogeneity. A controlled isothermal treatment at 200 °C, designed to cleave disulfide bonds, results in a nearly 40% reduction in specific surface area across all fiber types, accompanied by a significant decrease in tensile strength and 80% reduction in elongation at break for Merino and Devon wool, but limited influence on the mechanical properties of Eider fibers. Furthermore, rate-dependent tensile testing within the elastic regime reveals distinct viscoelastic responses among the fiber types, suggesting that the sulfur-rich protein matrix surrounding IFs and its structure contribute actively to stress partitioning. Altogether, when combined with conclusions from SAXS measurements of IF spacing, our work offers compelling insights into the role of the keratin-associated protein (KAP) matrix in shaping wool fiber mechanics. Differences in mechanical behavior among wool types, despite similar IF spacing or sulfur content, highlight the importance of matrix composition and cross-linking density, suggesting that the molecular architecture of the KAP network may be a dominant factor in determining fiber performance.

X-ray scattering↗
DOE OSTI2023

Mechanical Analysis of Carbon Fiber Retaining Sleeve for A High-speed Outer Rotor SPM Electric Motor Design

Outer rotor motors can be designed with a larger airgap diameter than inner rotor motors for the same overall diameter and therefore provide higher torque which makes them ideal for high torque space constrained applications. This advantage fits well with the increasing demand of high-speed electric machines in many applications due to their inherent high-power density. However, increasing the motor speed results in significant centrifugal loads for the outer rotor motor design. Layers of carbon fiber sleeve winding on the rotor outer surface is necessary to guarantee its structural integrity without introducing too much weight on the motor itself. In this paper, we studied the mechanical stress of a carbon fiber retaining sleeve in a surface permanent magnet outer rotor motor that spins up to 20,000 RPM. Analytical results from finite element method (FEM) confirmed that the maximum stress experienced by the carbon fiber sleeve was under the material’s yield strength. The proposed sleeve will allow this outer rotor motor to operate at high speeds.

Lin, Lianshan↗