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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 163 records · Page 9

Effect of Surface Oxidation and Crystal Thickness on the Magnetic Properties and Magnetic Domain Structures of Cr 2 Ge 2 Te 6

van der Waals (vdW) magnetic materials, such as Cr 2 Ge 2 Te 6 (CGT), show promise for memory and logic applications. This is due to their broadly tunable magnetic properties and the presence of topological magnetic features such as skyrmionic bubbles. A systematic study of thickness and oxidation effects on magnetic domain structures is important for designing devices and vdW heterostructures for practical applications. Here, we investigate thickness effects on magnetic properties, magnetic domains, and bubbles in oxidation-controlled CGT crystals. We find that CGT exposed to ambient conditions for 5 days forms an oxide layer approximately 5 nm thick. This oxidation leads to a significant increase in the oxidation state of the Cr ions, indicating a change in local magnetic properties. This is supported by real-space magnetic texture imaging through Lorentz transmission electron microscopy. By comparing the thickness-dependent saturation field of oxidized and pristine crystals, we find that oxidation leads to a nonmagnetic surface layer that is thicker than the oxide layer alone. We also find that the stripe domain width and skyrmionic bubble size are strongly affected by the crystal thickness in pristine crystals. Finally, these findings underscore the impact of thickness and surface oxidation on the properties of CGT, such as saturation field and domain/skyrmionic bubble size, and suggest a pathway for manipulating magnetic properties through a controlled oxidation process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Monofluorinated acetal electrolyte for high-performance lithium metal batteries

High degree of fluorination for ether electrolytes has resulted in improved cycling stability of lithium metal batteries due to stable solid electrolyte interphase (SEI) formation and good oxidative stability. However, the sluggish ion transport and environmental concerns of high fluorination degree drive the need to develop less fluorinated structures. Here, we depart from the traditional ether backbone and introduce bis(2-fluoroethoxy)methane (F2DEM), featuring monofluorination of the acetal backbone. High coulombic efficiency and stable long-term cycling in Li||Cu half cells can be achieved with F2DEM even under fast Li metal plating conditions. The performance of F2DEM is further compared with diethoxymethane (DEM) and 2-[2-(2,2-difluoroethoxy)ethoxy]-1,1,1-trifluoroethane (F5DEE). A significantly lower overpotential is observed with F2DEM, which improves energy efficiency and enables its application in high-rate conditions. Comparative studies of F2DEM with DEM and F5DEE in anode-free lithium iron phosphate (LiFePO4) LFP pouch cells and high-loading LFP coin cells further show improved capacity retention of F2DEM electrolyte, demonstrating its practical applicability. More importantly, we also extensively investigate the underlying mechanism for the superior performance of F2DEM through various techniques, including X-ray photoelectron spectroscopy, scanning electron microscopy, cryogenic electron microscopy, focused ion beam, electrochemical impedance spectroscopy, and titration gas chromatography. Overall, F2DEM facilitates improved Li deposition morphology with reduced amount of dead Li. This enables F2DEM to show superior performance, especially under higher charging and slower discharging rate conditions.

25 ENERGY STORAGE↗

Advances in supramolecular host-mediated reactivity

Since the trailblazing discoveries of Lehn, Cram and Pedersen, supramolecular chemistry has established itself as a cornerstone of organic chemistry. Supramolecular hosts offer defined microenvironments that mimic the active sites of enzymes, utilizing specific host–guest interactions to enable remarkable rate enhancements and product selectivity. The development of a diverse array of self-assembled hosts, coupled with the increased demand for shorter and greener synthetic routes, have spurred significant progress in the field of supramolecular catalysis. This Review Article covers recent advances in the field, ranging from novel organic reactivity aided by supramolecular hosts to catalytic cooperation between hosts and organometallic compounds or metal nanoparticles. Furthermore, strides have also been made in the synthetic application of these hosts in site-selective substrate modifications and challenging photochemical reactions. These efforts have enabled the incorporation of non-covalent macromolecular catalysis in natural product syntheses, evidencing their unique advantages as a synthetic tool, and their powerful potential for practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SQMS Quantum R&D in Machine Learning, Optimization and Sensing beyond Fundamental Physics Applications

This newly formed team at SQMS under the Ecosystem Thrust is looking to develop capabilities impacting societal advances outside the core domain of HEP and condensed matter physics. We explicitly leverage the experimental and algorithmic innovations developed across all groups as well as connect to broad-scope external projects of the diverse team of PIs. As the inaugural set of projects, we are studying numerically quantum machine learning models inspired by efficiently trainable echo-state and orthogonal neural networks and developing designs for related experiments to be performed on quantum processors based on SQMS SRF cQED technology and Rigetti s transmon arrays. Investigated models exploit ideas and lessons learned from multiple prior work by SQMS team members in a variety of internal and external activities [R1]. Target initial applications include noisy signal processing, potentially captured by quantum sensors or noisy QPUs, as well as simulation and classification of healthcare data. For instance, image reconstruction of the brain s electrical properties by solving the inverse Maxwell equation problem with uncertainty [R2] through a hybrid quantum-classical physics-informed architecture for time-dependent processes [R3]. The group is also investigating the application and development of novel quantum sensors based on magnetic levitation of a superconducting sphere coupled to a superconducting qubit. This coupling enables high-precision measurements of the position of the sphere, which can be used for sensitive detection of forces, enabling practical applications such as gravimetry for geophysics analysis, or accelerometry for GPS-denied navigation [R4] [R1] Rieffel, Eleanor G., Ata Akbari Asanjan, M. Sohaib Alam, Namit Anand, David E. Bernal Neira, Sophie Block, Lucas T. Brady et al. "Assessing and advancing the potential of quantum computing: A NASA case study." Future Generation Computer Systems (2024). [R2] Yu, X., Serrall s, J.E., Giannakopoulos, I.I., Liu, Z., Daniel, L., Lattanzi, R. and Zhang, Z., 2023. Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks. IEEE Journal on Multiscale and Multiphysics Computational Techniques. [R3] Wudarski, Filip, Daniel OConnor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, P. Aaron Lott, and Davide Venturelli. "Hybrid quantum-classical reservoir computing for simulating chaotic systems." arXiv preprint arXiv:2311.14105 (2023). [R4] Higgins, Gerard, Saarik Kalia, and Zhen Liu. "Maglev for dark matter: Dark-photon and axion dark matter sensing with levitated superconductors." Physical Review D 109.5 (2024): 055024.

Venturelli, Davide↗

Deep learning-driven super-resolution in Raman hyperspectral imaging: Efficient high-resolution reconstruction from low-resolution data

Deep learning (DL) has become an indispensable tool in hyperspectral data analysis, automatically extracting valuable features from complex, high-dimensional datasets. Super-resolution reconstruction, an essential aspect of hyperspectral data, involves enhancing spatial resolution, particularly relevant to low-resolution hyperspectral data. Yet, the pursuit of super-resolution in hyperspectral analysis is fraught with challenges, including acquiring ground truth high-resolution data for training, generalization, and scalability. The pressing issue of extended spectral acquisition times, notably for high-resolution scans, is a significant roadblock in hyperspectral imaging. Super-resolution methods offer a promising solution by providing higher spatial resolution data to expedite data collection and yield more efficient outcomes. This paper delves into a practical application of these concepts using Raman imaging, where spectral acquisition times can be prohibitively long. In this context, DL-based super-resolution models demonstrate their efficacy by predicting and reconstructing high-resolution Raman data from low-resolution input, eliminating the need for resource-intensive high-resolution scans. While previous work often relied on substantial high-resolution datasets, this study showcases the ability to achieve similar outcomes even with limited data, presenting a more practical and cost-effective approach. In conclusion, the results offer a glimpse into the transformative potential of this technology to streamline hyperspectral imaging applications by saving valuable time and resources through the successful generation of high-resolution data from low-resolution inputs.

42 ENGINEERING↗

Tailoring Polymer Colloids Derived Porous Carbon Spheres Based on Specific Chemical Reactions

Porous carbon spheres derived from polymer colloids with regular geometry, monodispersed morphology, well-controlled contents and structures play important roles in many areas of application, such as energy storage/conversion, gas adsorption/separation, catalysis, and chemo-photothermal therapy. Suitable polymerization reaction and synthetic strategy are both critical for the obtainment of stable polymer colloids as carbon precursors. Basic polymerization reactions are the cornerstones of synthetic strategies, which directly provides the direct molecular-based design of functionalized polymer/ carbon spheres. Thus, this progress report mainly focuses on the summary of suitable polymerization reactions for colloidal polymer derived porous carbon spheres. Recent advances in the synthetic strategies and applications are also discussed, including their corresponding polymerization reactions. Finally, the perspectives for the development of polymer derived porous carbon spheres are provided based on the controlled synthesis of polymer colloids and optimization over the carbonization process to achieve highly functionalized carbon spheres for practical applications.

36 MATERIALS SCIENCE↗

Nanoengineering of 2D MBenes for energy storage applications: A review

2D transition metal borides (MBenes), a flourishing member of the 2D nanomaterial family, show great potential in a number of study areas. MBenes have received increasing attention thanks to their excellent electrical conductivity, structural and mechanical properties, and chemical stability, which have captivated researchers and sparked further exploration. Extensive theoretical and experimental investigations have unveiled its remarkable potential as electrode materials for electrochemical storage applications, making MBenes a subject of great interest. Despite the growing interest and numerous studies conducted, there is a lack of a comprehensive and systematic appraisal of MBenes' applications in electrochemical energy storage systems. Here, in light of this, firstly, we provide an overview of the current progress in the fabrication and characterization of MAB phases and MBenes. For the synthesis of MBenes, the following fabrication techniques were discussed; liquid-phase exfoliation, solid-state mechanical exfoliation, chemical vapor deposition, high-pressure chemical vapor deposition, microwave-assisted chemical etching, and ultrasound-assisted chemical etching methods. Then, we delve into the captivating potential of MBenes, specifically in the realm of energy storage applications and their role in enhancing electrochemical storage capabilities. The discussion encompasses their application in lithium-ion, lithium-sulfur, and lithium-selenide batteries, supercapacitors and other energy storage systems, providing a comprehensive perspective on their contributions to the energy landscape. Finally, a brief but significant summary of the challenges and opportunities of MBenes in practical applications was summarized. The present review provides a guide and scientific motivation for creating and developing advanced MBene-based nanomaterials, addressing the growing demand for cutting-edge energy storage systems.

25 ENERGY STORAGE↗

Beyond Solvothermal: Alternative Synthetic Methods for Covalent Organic Frameworks

Abstract Covalent organic frameworks (COFs) are crystalline porous organic materials that hold a wealth of potential applications across various fields. The development of COFs, however, is significantly impeded by the dearth of efficient synthetic methods. The traditional solvothermal approach, while prevalent, is fraught with challenges such as complicated processes, excessive energy consumption, long reaction times, and limited scalability, rendering it unsuitable for practical applications. The quest for simpler, quicker, more energy‐efficient, and environmentally benign synthetic strategies is thus paramount for bridging the gap between academic COF chemistry and industrial application. This Review provides an overview of the recent advances in alternative COF synthetic methods, with a particular emphasis on energy input. We discuss representative examples of COF synthesis facilitated by microwave, ultrasound, mechanic force, light, plasma, electric field, and electron beam. Perspectives on the advantages and limitations of these methods against the traditional solvothermal approach are highlighted.

Hu, Jiyun↗

Beyond Solvothermal: Alternative Synthetic Methods for Covalent Organic Frameworks

Abstract Covalent organic frameworks (COFs) are crystalline porous organic materials that hold a wealth of potential applications across various fields. The development of COFs, however, is significantly impeded by the dearth of efficient synthetic methods. The traditional solvothermal approach, while prevalent, is fraught with challenges such as complicated processes, excessive energy consumption, long reaction times, and limited scalability, rendering it unsuitable for practical applications. The quest for simpler, quicker, more energy‐efficient, and environmentally benign synthetic strategies is thus paramount for bridging the gap between academic COF chemistry and industrial application. This Review provides an overview of the recent advances in alternative COF synthetic methods, with a particular emphasis on energy input. We discuss representative examples of COF synthesis facilitated by microwave, ultrasound, mechanic force, light, plasma, electric field, and electron beam. Perspectives on the advantages and limitations of these methods against the traditional solvothermal approach are highlighted.

Hu, Jiyun↗

Hierarchical porous silicon structures with extraordinary mechanical strength as high-performance lithium-ion battery anodes

Abstract Porous structured silicon has been regarded as a promising candidate to overcome pulverization of silicon-based anodes. However, poor mechanical strength of these porous particles has limited their volumetric energy density towards practical applications. Here we design and synthesize hierarchical carbon-nanotube@silicon@carbon microspheres with both high porosity and extraordinary mechanical strength (>200 MPa) and a low apparent particle expansion of ~40% upon full lithiation. The composite electrodes of carbon-nanotube@silicon@carbon-graphite with a practical loading (3 mAh cm −2 ) deliver ~750 mAh g −1 specific capacity, <20% initial swelling at 100% state-of-charge, and ~92% capacity retention over 500 cycles. Calendered electrodes achieve ~980 mAh cm −3 volumetric capacity density and <50% end-of-life swell after 120 cycles. Full cells with LiNi 1/3 Mn 1/3 Co 1/3 O 2 cathodes demonstrate >92% capacity retention over 500 cycles. This work is a leap in silicon anode development and provides insights into the design of electrode materials for other batteries.

25 ENERGY STORAGE↗

Device-Level Multidimensional Thermal Dynamics With Implications for Current and Future Wide Bandgap Electronics

Researchers have been extensively studying wide-bandgap (WBG) semiconductor materials such as gallium nitride (GaN) with an aim to accomplish an improvement in size, weight, and power of power electronics beyond current devices based on silicon (Si). However, the increased operating power densities and reduced areal footprints of WBG device technologies result in significant levels of self-heating that can ultimately restrict device operation through performance degradation, reliability issues, and failure. Typically, self-heating in WBG devices is studied using a single measurement technique while operating the device under steady-state direct current measurement conditions. However, for switching applications, this steady-state thermal characterization may lose significance since the high power dissipation occurs during fast transient switching events. Therefore, it can be useful to probe the WBG devices under transient measurement conditions in order to better understand the thermal dynamics of these systems in practical applications. In this work, the transient thermal dynamics of an AlGaN/GaN high electron mobility transistor (HEMT) were studied using thermoreflectance thermal imaging and Raman thermometry. Also, the proper use of iterative pulsed measurement schemes such as thermoreflectance thermal imaging to determine the steady-state operating temperature of devices is discussed. These studies are followed with subsequent transient thermal characterization to accurately probe the self-heating from steady-state down to submicrosecond pulse conditions using both thermoreflectance thermal imaging and Raman thermometry with temporal resolutions down to 15 ns.

42 ENGINEERING↗

Optimization of Localized High Concentration Electrolytes (LHCE) for Li||LiCoO 2 and Si|| LiCoO 2 Batteries used in Consumer Electronics Applications (Final Report for I3T Project 75934)

This project will optimize localized high concentration electrolyte (LHCE) for Li/LCO and Si/LCO batteries for consumer electronics applications, including select the best solvent and diluent, optimize the ratios of the solvents and the salt concentration. Results will be demonstrated not only in both coin cells, but also in pouch cells, which is required for large-scale commercial applications. This work can provide better understanding that would also benefit other LMB projects, including Li/NMC and Li/S batteries for electric vehicle applications. In the history of rechargeable batteries, all batteries have been first used in small scale consumer electronics, then eventually penetrate to large scale applications such as electrical vehicle or grid. We believe this development route will also be true for LMBs. By developing the best electrolyte for Li/LCO and Si/LCO chemistry, we will not only get the early market entry in consumer electronics, but we can also accumulate experience on the practical application of LMBs which can be used to further develop other types of LMBs for EV and other large-scale applications pursued by DOE.

25 ENERGY STORAGE↗

Correlation function metrology for warm dense matter: Recent developments and practical guidelines

X-ray Thomson scattering (XRTS) has emerged as a valuable diagnostic for matter under extreme conditions, as it captures the intricate many-body physics of the probed sample. Recent advances, such as the model-free temperature diagnostic of Dornheim et al. [Nat. Commun. 13 , 7911 (2022)], have demonstrated how much information can be extracted directly within the imaginary-time formalism. However, since the imaginary-time formalism is a concept often difficult to grasp, we provide here a systematic overview of its theoretical foundations and explicitly demonstrate its practical applications to temperature inference, including relevant subtleties. Furthermore, we present recent developments that enable the determination of the absolute normalization, Rayleigh weight, and density from XRTS measurements without reliance on uncontrolled model assumptions. Finally, we outline a unified workflow that guides the extraction of these key observables, offering a practical framework for applying the method to interpret experimental measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I—Harnessing theory

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question—How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? In conclusion, the analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.

59 BASIC BIOLOGICAL SCIENCES↗

Constructing Crown Ether-Based Supramolecular Adhesives with Ambient-Temperature Applicable and Durable Adhesion

Supramolecular adhesives are attracting considerable attentions owing to their dynamic and reversible bonding, while the complex curing conditions and poor performance under extreme conditions severely restrict their applicability. Herein, a series of tetra-crown ether-terminated polyethylene glycol (TCE-PEG) adhesives are presented in which plenty of supramolecular interactions, including Van der Waals, hydrogen bonding, π–π staking, metal coordination, and electrostatic ones, provide strong adhesion on multiple types of substrates. Highly relevant for practical applications, ultra-strong adhesivity of TCE-PEG can be achieved without requiring additional ultraviolet radiation, heat, or chemical treatment at ambient temperature. It also exhibits durable adhesive behavior, excellent underwater stability, and low-temperature tolerance. Especially, by incorporating ionic polymer fragments of polyethyleneimine hydrochloride, additional hydrogen bonding between secondary amines and crown ether rings can be induced to enhance the lap-shear strength to 7.21 MPa due to the formation of supramolecular cross-linked network. Finally, this work pioneers a rather unique supramolecular approach for easily formed, ultra-strong crown-ether-based adhesives bearing great potential for applications in critical environments of limited heat source and unallowed solvent usage.

36 MATERIALS SCIENCE↗

Scalable quantum computational science: A perspective from block-encodings and polynomial transformations

Significant developments made in quantum hardware and error correction recently have been driving quantum computing toward practical utility. However, gaps remain between abstract quantum algorithmic development and practical applications in computational sciences. In this perspective article, we propose several properties that scalable quantum computational science methods should possess. We further discuss how block-encodings and polynomial transformations can potentially serve as a unified framework with the desired properties. Recent advancements on these topics are presented, including the construction and assembly of block-encodings, and various generalizations of quantum signal processing (QSP) algorithms to perform polynomial transformations. The scalability of QSP methods on parallel and distributed quantum architectures is also highlighted. Promising applications in simulation and observable estimation in chemistry, physics, and optimization problems are presented. We hope this perspective serves as a gentle introduction to state-of-the-art quantum algorithms for the computational science community and inspires future development of scalable quantum computational science methodologies that bridge theory and practice.

Bayesian inference↗

Physics-Informed Neural Network (PINN) Prediction of Mixed Mass-Heat-Crystallization Limited Methane Hydrate Formation and Dissociation in Micro-Confinement

The creation and use of Physics-Informed Neural Networks (PINNs) for simulating the dynamics of methane hydrate formation and dissociation will be presented. The PINN framework's main benefit is its capacity to impose physical consistency with only a partial comprehension of the governing equations. This makes the algorithm especially useful for systems with little experimental evidence or a lack of theoretical knowledge. A strong basis for forecasting methane hydrate behavior over the verified operating ranges of 30.0-80.9 bar pressure and 1.0-4.0 K sub-cooling conditions is provided by the combination of conductive heat transfer equations and mixed mass-transfer–crystallization kinetics. PINNs were more accurate at predicting the mixed mass-heat-crystallization limited kinetics than conventional Artificial Neural Networks (ANNs), demonstrating remarkable predictive accuracy for methane hydrate production over the ANN model. The efficiency of incorporating physical limitations from first principles into machine learning frameworks for methane hydrate crystallizations is reinforced by these findings. For hydrate-related applications in energy generation, carbon sequestration, and climate modelling, our study establishes PINNs as a computational tool that is both scalable and efficient. The proven capacity to close the gap between conventional physics-based simulations and solely data-driven models creates new opportunities for expedited hydrate research and practical applications.

Hartman, Ryan L [NYU Tandon School of Engineering]↗

Life-Cycle Cost Analysis Framework for Water Efficiency Measures

Life-Cycle Cost Analysis Framework for Water Efficiency Measures: Guidance Designed for Federal Agencies (hereafter referred to as “this report”) provides a technical framework for federal agencies to conduct a life-cycle cost analysis (LCCA) for water efficiency projects in accordance with 42 U.S.C. § 8253. This report leverages insights from the 2023 report, PNNL-34006, Water and Wastewater Annual Price Escalation Rates for Selected Cities Across the United States: 2023 Edition (Unger et al. 2023). The primary objective of this report is to provide a framework to assist federal agencies with evaluating the full economic impact of water efficiency projects by assessing both initial investments and long-term operational benefits. An LCCA can provide a comprehensive view of all costs associated with a water efficiency project, including initial investment, ongoing operations and maintenance (O&M), and eventual disposal or replacement, ensuring the most cost-effective solution is selected. The LCCA methodology outlined in this report enables users to compare base case scenarios with potential alternatives using a standardized present value approach. It incorporates key cost components such as energy, water and wastewater, installation, O&M, and equipment replacement. Additionally, the framework introduces relevant evaluation metrics, such as the net savings and the savings-to-investment ratio, to ensure that water efficiency measures are economically justified over the lifespan of the project. To support practical application, this report also describes various water efficiency strategies that may be analyzed using an LCCA, including plumbing retrofits, irrigation upgrades, alternative water use, and cooling system improvements. By applying this framework, federal agencies can ensure compliance with regulatory mandates while maximizing the return on investment and contributing to resilient water management practices. The information provided in this report is aligned with the Federal Energy Management Program (FEMP) life-cycle cost (LCC) methodology, as conveyed in National Institute of Standards and Technology (NIST) Handbook 135 (Kneifel and Webb 2022). This report is intended to provide relatively high-level guidance, acting as a complement to, rather than a substitute for, that resource.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗