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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 1,333 records · Page 74

Coal-derived carbon anodes for lithium-ion batteries: Development, challenges, and prospects

Lithium-ion battery (LIB) development has increased rapidly, requiring low-cost anode materials with a high capacity, high-rate performance, and stable lifespan. Carbon-based anodes possess various exceptional morphologies and structures, making them promising candidates for meeting the technical demands; however, conventional synthetic carbon anode processes need expensive feedstocks that increase anode cost and limit commercialization. Coal, the most affordable and abundant carbon resource, has attracted increasing attention as the primary feedstock for producing high-value carbon anode materials. This article reviews the lithium storage mechanisms, characteristics, and productions of some high-valuable carbon anode materials for LIBs from coal and coal derivatives. The high-value carbon anode materials reviewed in this article are graphite, graphene, mesophase microbeads (MCMB), carbon fiber, and hard carbons. Furthermore, the remaining challenges and prospects of using coal-derived carbon materials to create high-performance and low-cost lithium-ion batteries are also discussed.

25 ENERGY STORAGE↗

Optimization of catholyte for halide-based all-solid-state batteries

Halide solid electrolytes gain significant attention due to their high ionic conductivity, low processing temperature, dry air compatibility, and high-voltage stability. However, low cathode active material (CAM) loading in the composite cathode constrains the realization of high energy density for halide-based all-solid-state batteries. In this study, three halide materials, raw Li 3 YBrCl 5 (LYBC-R, <30μm), milled LYBC (LYBC-M, <5 μm) and freeze-dried Li 3 InCl 6 (LIC, <500 nm), were used as catholytes, combined with LYBC-M as the electrolyte and LiIn alloy as the anode. The CAM:catholyte ratio was investigated as well as stack pressure and operating temperature. Our study demonstrates that particle size of the catholyte plays an important role only for high CAM loading or high C-rate cycling. At moderate CAM loading (65 and 70wt% LiNi 0.83 Mn 0.06 Co 0.11 O 2 ) and 0.1 C-rate, all the three catholytes perform well, providing initial discharge capacities >177 mAh/g. At high CAM loading (85wt%) and 0.1 C-rate, a cathode with the nano-scale LIC catholyte provides discharge capacity of 175 mAh/g, while the larger particle size catholytes suffer significantly reduced capacity. Both LYBC and LIC catholytes provided capacity retention >80% after 200 cycles at 0.5C. These results imply that cathode particle size is critically important for performance at high CAM loading. Furthermore, both electrolyte and cathode were tape cast to scale up size and prepare realistic layer thicknesses. A small amount of binder was used in both layers, to balance the electrochemical performance and mechanical properties. Further, the discharge capacity of a tape cell was 152mA h/g at 0.1C with a capacity retention of 81.8% after 20 cycles at 0.5C. The results demonstrate the excellent performance of LYBC as an electrolyte, and provide guidance for halide-based cathode design.

25 ENERGY STORAGE↗

Wastepaper-derived porous carbon supported cobalt nanocomposites for all solid-state flexible supercapacitor

The conversion of wastepaper into high-value carbon materials has gained significant attention as a sustainable strategy for energy storage applications. Owing to its low cost, abundance, and intrinsic fibrous structure, wastepaper serves as an attractive precursor for carbon-based electrode materials. In this work, a novel electrode comprising cobalt nanoparticles and Co 3 O 4 embedded in wastepaper-derived porous carbon has been developed for use in a flexible all-solid-state asymmetric supercapacitor. The integration of cobalt nanoparticles and Co 3 O 4 introduces redox-active centres, which enhance the electrochemical activity of the carbon framework. Mean while, the interconnected porous and conductive carbon network enables rapid ion diffusion and efficient electron transport, synergistically improving the overall electrochemical performance. It delivers a high specific capacitance of 61.5 Fg -1 , a power density of 5143 W kg -1 , and an energy density of 9 Wh kg -1 at a current density of 2.5 A/ g. Furthermore, the device maintains outstanding cycling stability, retaining 82.86 % of its capacitance after 10,000 charge-discharge cycles. Practical applicability is confirmed through its ability to power

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ab initio study and assignment of electronic states in molecular RaCl

Radium compounds have attracted recently considerable attention due to both development of experimental techniques for high-precision laser spectroscopy of molecules with short-lived nuclei and amenability of certain radium compounds for direct cooling with lasers. Currently, radium monofluoride (RaF) is one of the most studied molecules among the radium compounds, both theoretically and recently also experimentally. Complementary studies of further diatomic radium derivatives are highly desired to assess the influence of chemical substitution on diverse molecular parameters, especially on those connected with laser cooling, such as vibronic transition probabilities, and those related to violations of fundamental symmetries. Here in this article high-precision ab initio studies of electronic and vibronic levels of diatomic radium monochloride (RaCl) are presented. Recently developed approaches for treating electronic correlation with Fock-space coupled cluster methods are applied for this purpose. Theoretical results are compared to an early experimental investigation by Lagerqvist and used to partially reassign the experimentally observed transitions and molecular electronic levels of RaCl. Effective constants of $\mathscr{P}$-odd hyperfine interaction W a and $\mathscr{P, T}$-odd scalar-pseudoscalar nucleus-electron interaction Ws in the ground electronic state of RaCl are estimated within the framework of a quasirelativistic Zeroth-Order Regular Approximation approach and compared to parameters in RaF and RaOH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In-situ synchrotron X-ray study on microstructure and stress evolutions of electroplated copper upon self-annealing

Background: The self-annealing behavior of electroplated copper (Cu) at room temperature is gaining attention in the microelectronics industry due to its significant impact on reliability issues such as substrate warpage and electrical resistivity. Methods: In this study, in-situ analysis of the microstructure transition and stress relaxation of the electroplated copper upon self-annealing was conducted via synchrotron white X-ray nanodiffraction (beamline 21A, Taiwan Photon Source) and grazing-incidence X-ray diffraction (beamline 17B1, Taiwan Light Source). Significant Findings: Remarkable relaxations of deviatoric stress and absolute strain component along the [002] direction were closely related to the Cu grain growth and crystallographic reorientation at the early stage of selfannealing, and a complete stress/strain relaxation can be achieved with the cessation of microstructure transition. In conclusion, the in-situ synchrotron X-ray studies provided an insight into Cu self-annealing mechanism, offering valuable information for improving Cu interconnect reliability.

Cu Self-annealing↗

Geospatial analysis of freight accessibility and job attraction: The role of interstate ramps, airports, ports, and rail

The number of jobs within an industry is significantly influenced by geographical location, with transportation infrastructure playing a key role. While previous research has largely focused on how access to jobs affects employment, less attention has been given to how transportation infrastructure impacts business operations and job attraction. Here, this study addresses this gap by examining how the ease of transporting products to key transportation facilities affects job numbers in freight-intensive industries. Using job data from the Longitudinal Employment Household Dynamics dataset at the Census Tract level, we applied a non-parametric model to assess the impact of proximity to interstate ramps, rail intermodals, ports, and airports. Our analysis revealed that closer transportation infrastructure generally has a greater impact on employment. Specifically, interstate ramps are crucial for attracting jobs, particularly in rural areas, while airport proximity is essential for industries dealing with high-value, time-sensitive goods, as seen notably in Massachusetts. The importance of transportation facilities varies considerably across states and industries. The findings and method in this study can be used by transportation agencies for freight planning.

99 GENERAL AND MISCELLANEOUS↗

Non-DNA radiosensitive targets that initiate persistent behavioral deficits in rats exposed to space radiation

Predicting future CNS risks for astronauts during deep-space missions will rely substantially on ground-based rodent data with space-relevant ions and behaviors. For rats, the accumulated evidence indicates that less densely ionizing radiation, such as 4 He and 12 C ions, induce behavior deficits at lower doses than densely ionizing ions, such as 48 Ti and 56 Fe. However, this observation conflicts with standard somatic radiobiology, in which densely ionizing ions are generally more effective than less densely ionizing ions, and where the DNA/nucleus is the accepted target for radiation-induced tumorigenesis, cytogenetic aberrations, genetic mutations, and reproductive cell death. To gain deeper insight into the subcellular nature of the radiation targets for behavior risks, we compared the effects of dose, fluence, and linear energy transfer (LET) of 4 He and 56 Fe particles using existing datasets for four distinct behavioral outcomes in rats: elevated plus maze (EPM-anxiety), novel object recognition (NOR-memory), operant responding (OR-response to environmental stimuli), and attentional set-shifting (ATSET-cognitive flexibility). We confirmed that less densely ionizing particles (except protons) showed ~100-fold lower threshold doses than densely ionizing particles for behavioral deficits (0.1–1 cGy for 4 He vs. 15–100 cGy for 56 Fe). However, when analyzed by fluence the behavioral responses converged, indicating that 4 He and 56 Fe were equally effective on a per-track basis. When analyzed by LET, there were ~100-fold differences in the LET for maximum effectiveness for behavioral deficits and DNA endpoints (~1 vs ~100 keV/μm, respectively). These unique features of radiation-induced behavioral deficits (high sensitivity to particles in the 1-keV/μm range, insensitivity to protons in the 0.2 keV/μm range, and isofluence dependence for particles with LET>1 keV/μm) provide evidence in support of a new hypothesis of sub-micron sized radiosensitive targets for behavioral effects consistent with the thickness of plasma membranes and/or small subcellular structures, smaller than a whole synapse. Like our behavior findings, mouse immature oocyte killing which is known to have a plasma membrane target was also better explained by fluence, rather than dose. In contrast, fluence analyses for DNA/nuclear endpoints in somatic cells (e.g., tumor induction, chromosome aberrations) showed opposite results, suggesting that behavior targets are not DNA. Our findings raise questions regarding the identity of subcellular targets and the multi-cellular functional unit for behavior risks, low-dose susceptibility, and generalizability from rat to other species and astronauts.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Predicting phase behavior in high entropy and chemically complex alloys

The interest in high entropy alloys and other metallic compounds with four or more elements at near-equiatomic ratios has drawn attention to the ability to rapidly predict phase behavior of these complex materials, particularly where existing thermodynamic data are lacking. In this paper, we discuss aspects of this from the point of view of predicting without utilizing (or fitting) experimental data. Of particular interest are heuristic approaches that provide prediction of single-phase compositions, more rigorous approaches that tackle the thermodynamics from a more fundamental point of view, and simulation approaches that provide further insight into the behaviors. This paper covers cases of all three of these, in order to examine the strengths and weaknesses of each approach, and to indicate directions where these may be utilized and improved upon. Of particular interest is moving beyond “which composition may form a solid solution,” to recognizing the importance of underlying thermodynamic realities that affect the temperature- and composition-dependent transformations of these materials.

36 MATERIALS SCIENCE↗

RU-net for automatic characterization of TRISO fuel cross sections

During irradiation, phenomena such as kernel swelling and buffer densification may impact the performance of tristructural isotropic (TRISO) particle fuel. Post-irradiation microscopy is often used to identify these irradiation-induced morphologic changes. However, each fuel compact generally contains thousands of TRISO particles. Manually performing the work to get statistical information on these phenomena is cumbersome and subjective. Here, to reduce the subjectivity inherent in that process and to accelerate data analysis, we used convolutional neural networks (CNNs) to automatically segment cross-sectional images of microscopic TRISO layers. CNNs are a class of machine-learning algorithms specifically designed for processing structured grid data. They have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we generated a large irradiated TRISO layer dataset with more than 2,000 microscopic images of cross-sectional TRISO particles and the corresponding annotated images. Based on these annotated images, we used different CNNs to automatically segment different TRISO layers. These CNNs include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net performs best in terms of Intersection over Union (IoU). Using CNN models, we can expedite the analysis of TRISO particle cross sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Preventative studies should begin now for detecting AI-generated microscopy images

With the rapid progress made in artificial intelligence (AI), text, images, and even videos that are often indistinguishable from human-created content can now be easily generated using new AI models. In this essay, we call attention to the potential misuse of advanced AI models to generate microscopy images, as it could challenge reviewers and fraud hunters in an unprecedented way. This concern is more than hypothetical because relevant open-sourced implementations and datasets are widely available. As a result, we urge that preventative studies on methods to detect microscopy image fabrication should begin now before potential misconduct materializes and becomes widespread.

97 MATHEMATICS AND COMPUTING↗

An emerging class of carbon materials: Synthesis and applications of carbon flowers

Porous carbon materials are widely applied in energy storage, gas adsorption, and catalysis applications because of their advantageous properties, such as high surface areas, tunable surface properties, chemical stability, high conductivity, and low cost. Recently, a flower-shaped carbon material, referred to as carbon flowers (CFs), has received attention as an emerging porous carbon material because of its unique shape. In this review, we summarize the synthetic strategies, characterization techniques, and formation mechanisms of CFs from various precursors. We also review the applications of CFs and their pros and cons. Last, we discuss challenges and perspectives for future development of CFs.

36 MATERIALS SCIENCE↗

Wafer-scale growth of two-dimensional, phase-pure InSe

Two-dimensional (2D) indium monoselenide (InSe) has attracted significant attention as an ultrathin III–VI semiconductor with a combination of favorable attributes that are comparable to those of III–V semiconductors and van der Waals 2D transition-metal dichalcogenides. Nevertheless, there has been no demonstration of large-area synthesis of 2D InSe due to the complexity of the binary In-Se system and the difficulties in promoting lateral growth. Here, we report the polymorph-selective synthesis of epitaxial 2D InSe by metal-organic chemical vapor deposition (MOCVD) over 2-in wafers. We achieve polymorph-selective epitaxial growth of InSe on c-plane sapphire via flow modulation to control the Se/In ratio. The layer-by-layer growth allows thickness control with tunable optical properties comparable to those of bulk crystals. We also demonstrate gate-tunable electrical transport with a field-effect mobility comparable to that of single-crystalline flakes. Importantly, these results indicate that InSe grown by MOCVD could be an effective channel material for back-end-of-line integration in logic transistors.

2D materials↗

Atomic-scale investigations of Ti 3 C 2 T x MXene surfaces

The family of two-dimensional (2D) carbides and/or nitrides, also known as MXenes, has generated great excitement within the scientific community and has been proposed for a wide variety of applications since its discovery. Despite this attention, there have been only limited studies of the atomically resolved local electronic and physical structure of MXene surfaces strongly affecting the physicochemical properties of these materials. Here, in this study, we report local structural, spectroscopic, and chemical investigations of the surfaces of Ti 3 C 2 T x flakes using scanning tunneling microscopy and spectroscopy, closely coupled to theoretical studies. Terminal groups are visualized and characterized, along with surface TiO 2 clusters formed upon exposure to air. Fundamental insight into the local electronic and chemical properties associated with different terminal groups on MXenes and their oxidation products is presented.

36 MATERIALS SCIENCE↗

Advancements in cerium/titanium metal-organic frameworks: Unparalleled stability in CO oxidation

Due to the excellent catalytic properties of Ce-based materials, the development of thermally stable metal-organic frameworks (MOFs) based on Ce-oxo clusters has attracted significant attention but remains challenging. In this work, we report the synthesis of an unreported Ce 4 Ti 2 -TMA (Ce IV 4 Ti IV 2 O 4 (OH) 4 (C(CH 3 ) 3 COO) 12 ·3H 2 O·3MeCN) cluster, which serves as an ideal source for the assembly of robust Ce/Ti-MOFs. Using this cluster, we constructed two isostructural MOFs, denoted as NU-3000 and NU-3001. Single-crystal X-ray diffraction analysis confirms these MOFs as mesoporous structures with 12-coordinated Ce 3 Ti 3 nodes. Furthermore, structural analysis reveals a plane triangular node structure that likely contributes to the excellent thermal stability of these MOFs. Finally, both MOFs show catalytic activity toward high-temperature (250°C) CO oxidation and maintain significant porosity, emphasizing the thermal stability of these materials under practical catalytic conditions. Furthermore, the straightforward synthesis of thermally robust Ce/Ti-MOFs from the Ce 4 Ti 2 -TMA cluster will pave the way for future Ce/Ti-MOF-based catalyst development.

36 MATERIALS SCIENCE↗

A foundation model for non-destructive defect identification from vibrational spectra

Defects are ubiquitous in solids and strongly influence materials’ functional properties. However, non-destructive characterization and quantification of defects, especially when multiple types coexist, remain a long-standing challenge. Here, we introduce DefectNet, a foundation machine learning model that predicts the chemical identity and concentration of substitutional point defects with multiple coexisting elements directly from vibrational spectra, specifically phonon density-of-states (PDoS). Trained on over 16,000 simulated spectra from 2,000 semiconductors, DefectNet employs a tailored attention mechanism to identify up to six distinct defect elements at concentrations ranging from 0.2% to 25%. The model generalizes well to unseen crystals across 56 elements and can be fine-tuned on experimental data. Validation using inelastic scattering measurements of SiGe alloys and MgB 2 superconductor demonstrates its accuracy and transferability. Furthermore, our work establishes vibrational spectroscopy as a viable, non-destructive probe for bulk point defect quantification, and highlights the promise of foundation models in data-driven defect engineering.

artificial intelligence↗

Oxygen-deficient ammonium vanadate for flexible aqueous zinc batteries with high energy density and rate capability at -30 °C

Aqueous zinc batteries (AZBs) have received significant attention owing to environmental friendliness, high energy density and inherent safety. However, lack of high-performance cathodes has become the main bottleneck of AZBs development. Here, oxygen-deficient NH 4 V 4 O 10–x ·nH 2 O (NVOH) microspheres are synthesized and used as cathodes for AZBs. The experimental test and theoretical calculations demonstrate that the oxygen vacancies in the lattice lower the Zn 2+ diffusion energy barrier, which enables fast Zn 2+ diffusion and good electrochemical performance in a wide temperature range. The suppressed side reactions also can help to improve the low temperature performance. NVOH shows a high energy density of 372.4 Wh kg –1 and 296 Wh kg –1 at room temperature and –30 °C, respectively. Moreover, NVOH maintains a 100% capacity retention after 100 cycles at 0.1 A g –1 and ~94% capacity retention after 2600 cycles at 2 A g –1 and –30 °C. Investigation into the mechanism of the process reveals that the capacity contribution of surface capacitive behaviors is dominant and capacity attenuation is mainly caused by the decay of diffusion-controlled capacity. As a result, flexible AZBs can steadily power portable electronics under different bending states, demonstrating its great potential in wide-temperature wearable device.

25 ENERGY STORAGE↗

Challenges and future perspectives on sodium and potassium ion batteries for grid-scale energy storage

The energy crisis and environmental pollution require the advancement of large-scale energy storage techniques. Among the various commercialized technologies, batteries have attracted enormous attention due to their relatively high energy density and long cycle life. Nevertheless, the limited supply and uneven distribution of lithium minerals, as well as their high cost, has greatly hindered the application of lithium-ion batteries in large-scale energy storage. Therefore, building next-generation alternative rechargeable batteries that feature low cost, long service life, and high safety is of the utmost importance. Over the past several years, we have witnessed many successful research outcomes for sodium and potassium ion batteries (SIBs and PIBs) in regard to electrode and electrolyte materials. In this Perspective, we summarize the current developments on SIBs/PIBs and their challenges when facing practical applications, including their cost, energy density, ion diffusivity in solids/electrolytes/interphases, cycle life, and safety concerns. Furthermore, we provide an overview of strategies to overcome the remaining challenges for achieving better electrochemical performance. Finally, we outline several possible directions for the future development of these two battery chemistries, with the hope of aiding the transition from the laboratory to next-generation practical applications for SIBs/PIBs batteries in grid-scale energy storage.

Energy Storage↗

Porous Janus materials with unique asymmetries and functionality

Porous Janus materials have attracted widespread attention due to their asymmetry in wettability, charge, pore size or structure, thermal/electrical conductivity, and chemical activity, among other properties. Multifunction integration and unique directional manipulation of liquid, ions, or gas within porous Janus materials enable rapid progress in diverse applications such as water-oil separation, fog collection, personal moisture and healthcare management, energy conversion, desalination, sensor devices, and biomedical applications. Additionally, compared with conventional homogeneous materials, porous Janus materials not only showcase superior performance and energetic potential but also open up new applications by virtue of the synergistic or independent effects of asymmetry. This in-depth review systematically analyzes the research progress of porous Janus materials, highlighting fabrication strategies, synergistic/independent work mechanisms, and emerging advanced applications. Finally, ongoing challenges and outlook for the future research of porous Janus materials are presented.

36 MATERIALS SCIENCE↗