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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 199 records · Page 11

Three-Dimensional Mapping of Resistivity and Microstructure of Composite Electrodes for Lithium-Ion Batteries

Nanoparticle silicon–graphite composite electrodes are a viable way to advance the cycle life and energy density of lithium-ion batteries. However, characterization of composite electrode architectures is complicated by the heterogeneous mixture of electrode components and nanoscale diameter of particles, which falls beneath the lateral and depth resolution of most laboratory-based instruments. In this work, we report an original laboratory-based scanning probe microscopy approach to investigate composite electrode microstructures with nanometer-scale resolution via contrast in the electronic properties of electrode components. Applying this technique to silicon-based composite anodes demonstrates that graphite, SiOx nanoparticles, carbon black, and LiPAA binder are all readily distinguished by their intrinsic electronic properties, with measured electronic resistivity closely matching their known material properties. Resolution is demonstrated by identification of individual nanoparticles as small as ~20 nm. Our technique presents future utility in multiscale characterization to better understand particle dispersion, localized lithiation, and degradation processes in composite electrodes for lithium-ion batteries.

25 ENERGY STORAGE↗

Magneto-optical Evidence of the Tilting Effect in Coupled Weyl Bands

Theories have revealed the universality of the band tilting effect in topological Weyl semimetals (WSMs) and its implications for the material physical properties. However, the experimental identification of tilted Weyl bands remains less explored. Here, we report the magneto-optical evidence of the tilting effect in WSM niobium phosphide. Specifically, we observe Landau level transitions with rich features that are well reproduced within a model of coupled tilted Weyl points. Our analysis indicates that the tilting effect relaxes the selection rules and leads to transitions that would otherwise be forbidden in the non-tilt case. Additionally, we observe unconventional interband transitions with flat and negative magnetic field dispersions, highlighting the importance of coupling between Weyl points. Our results not only emphasize the significance of the tilting effect in the optical responses of WSMs but also demonstrate magneto-optics as an effective tool for probing the tilting effect in electronic band structures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Interplay between Mixed and Pure Exciton States Controls Singlet Fission in Rubrene Single Crystals

Singlet fission (SF) is a multielectron process in which one singlet exciton S converts into a pair of separated triplet excitons T. SF is widely studied as it may help overcome the Shockley−Queisser efficiency limit for semiconductor photovoltaic cells. To elucidate and control the SF mechanism, great attention has been given to the identification of intermediate states in SF materials, which often appear elusive due to the complexity and fast time scales of the SF process. Here, we apply 14 fs-1 ms transient absorption techniques to high-purity rubrene single crystals to disentangle the intrinsic fission dynamics from the effects of defects and grain boundaries and to identify reliably the fission intermediates. Our data demonstrates that above-gap excitation directly generates a hybrid vibronically assisted mixture of singlet state and triplet-pair multiexciton [S/TT], which rapidly (<100 fs) and coherently branches into pure singlet or triplet excitations. The relaxation of [S/TT] to S is followed by a relatively slow and temperature-activated (48 meV activation energy) incoherent fission process. The SF competing pathways and intermediates revealed here unify the observations and models presented in previous studies of SF in rubrene and offer alternative strategies for the development of SF-enhanced photovoltaic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In-plane Wilson loop for measurement of quantized non-Abelian Berry flux

Band topology of anomalous quantum Hall insulators can be precisely addressed by computing the Chern numbers of constituent nondegenerate bands, describing the presence of quantized, Abelian Berry flux through the two-dimensional Brillouin zone. Can Berry flux be captured for the SU (2) Berry connection of two -fold degenerate bands in spinful materials preserving space -inversion ($\mathscr{P}$) and time -reversal ($\mathscr{T}$) symmetries without detailed knowledge of underlying basis? We address this question by investigating the correspondence between a non -Abelian generalization of Stokes' theorem and the manifestly gauge -invariant eigenvalues of Wilson loops computed along in -plane contours which preserve the underlying crystalline symmetry. The importance of this correspondence is elucidated by performing natural number resolved classification of ab initio band structures of three-dimensional, Dirac materials. Further, our work underscores how identification of quantized Berry flux, both Abelian and non -Abelian, offers a unified framework for addressing first -order and higher -order topology of insulators and semimetals.

74 ATOMIC AND MOLECULAR PHYSICS↗

Analyzing Potential Failures and Effects in a Pilot-Scale Biomass Preprocessing Facility for Improved Reliability

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.

09 BIOMASS FUELS↗

Solid-state batteries and the critical role of interfaces

The Grand Challenge for the next generation of energy storage technologies is no longer the identification of electroactive cathode or anode materials thanks to extensive worldwide synthesis efforts along with theory and modeling like the Materials Project.1 Instead, the critical challenges revolve around assembling materials in the right architecture to achieve maximum performance and cell life at reasonable temperatures and pressures. Nowhere is this more critical than on the next generation of energy storage technologies revolving around all solid-state batteries. These batteries are the ultimate challenge for materials science requiring new ways to assemble multiple dissimilar materials such that: (1) interfaces are optimized to facilitate ion motion across the different compounds while (2) maintaining chemical stability and (3) simultaneously preserving the crystal structures of each phase during (4) large volume changes due to shuttling of lithium, at (5) room temperature and under (6) atmospheric pressure. To address these requirements will require insights and expertise from research fields outside the traditional lithium-ion battery community such as solid oxide fuel cells, synthesis science, barrier layers, interface formers, sintering, and mechanical properties.

25 ENERGY STORAGE↗

Waste Information Management System with 2019-20 Waste Streams - 20491

The Waste Information Management System (WIMS) 2019-20 was updated to support the Department of Energy (DOE) accelerated cleanup program. The schedule compression required close coordination and a comprehensive review and prioritization of the barriers that impeded treatment and disposition of the waste streams at each site. Many issues related to waste treatment and disposal were potential critical path issues under the accelerated schedule. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE Headquarters in Washington, D.C., needed timely waste forecast and transportation information regarding the volumes and types of radioactive waste that would be generated by DOE sites over the next 35 years. Each local DOE site historically collected, organized, and displayed waste forecast information in separate and unique systems. In order for interested parties to understand and view the complete DOE complex-wide picture, the radioactive waste and shipment information of each DOE site needed to be entered into a common application. The WIMS application was therefore created to serve as a common application to improve stakeholder comprehension and improve DOE radioactive waste treatment and disposal planning and scheduling. WIMS allows identification of total forecasted waste volumes, material classes, disposition sites, choke points, technological or regulatory barriers to treatment and disposal, along with forecasted waste transportation information by rail, truck and intermodal shipments. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, developed and deployed the web-based forecast and transportation system and is responsible for updating the radioactive waste forecast and transportation data on a regular basis to ensure the long-term viability and value of this system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Recent advances and applications of deep learning methods in materials science

Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.

36 MATERIALS SCIENCE↗

FCC feasibility studies: Impact of tracker- and calorimeter-detector performance on jet flavor identification and Higgs physics analyses

The ambitious physics program planned for the Future Circular Collider electron-positron phase imposes stringent constraints on detector performance. This study systematically investigates how different detector configurations impact jet flavor identification and their effects on high-profile physics analyses. Using Higgs boson coupling measurements and searches for invisible Higgs decays as benchmarks, we evaluate the sensitivity of these analyses to variations in tracker and calorimeter detector properties. We examine modifications to single-point resolution, material budget, silicon layer placement, and particle identification capabilities, quantifying their effects on flavor-tagging performance. Additionally, we present the first comprehensive study of Higgs-to-invisible decay detection using full detector simulation, providing insights for optimizing detector designs at lepton colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dispersion interactions in proposed covalent superhydride superconductors

Recent developments in high temperature superconducting materials under high pressure have made numerical evaluation of the superconducting transition temperature (T c ) of predicted materials critically important as a means to identification. Existing methods of calculating T c often do not agree with each other or experiment, often due to the large number of complex factors that contribute to this property; among them is the neglect of dispersion interactions in commonly used density functionals. We evaluate the effect of including dispersion interactions on the predicted superconducting properties of two examples of the covalent superhydride class of very high-T c superconducting materials. In both cases, dispersion is found to have sizable effects, increasing the electron-phonon coupling as compared to the reference case of elemental niobium. A detailed investigation traces the origin of this effect in a 270 GPa $\mathrm {R3m CSH_7}$ structure to structural distortions driven by long-range electron-phonon interactions rather than novel bonding networks.

36 MATERIALS SCIENCE↗

Moving toward automated µFTIR spectra matching for microplastic identification: addressing false identifications and improving accuracy

Abstract Infrared spectroscopy is a widely used tool for studying microplastics and identifying microparticles. Researchers rely on spectral libraries to differentiate between synthetic and natural materials. Unfortunately, spectral library matching is not perfect, and best practices require researchers to use time consuming, manual peak matching to assess spectral matches. Moving toward automated matching requires increased confidence in the matching process. Using spectra matching software may increase the efficiency of particle identification, however some matching strategies may confuse natural materials such as cotton, silk, and plant matter with common classes of synthetics such as polyesters and polyamides. In this experiment, we prepared 22 pristine sample materials from natural and synthetic sources and measured micro-Fourier transform infrared (µFTIR) spectra in transmission mode for each sample using a Thermo Nicolet iN10 MX instrument. The collected spectra were then input into two spectral library matching systems (Omnic Picta and Open Specy), using a total of five identification routines. Next, we placed a subset of four pristine microplastic materials in a biologically active river system for two weeks to simulate environmental samples. These simulated environmental samples were processed using 10% hydrogen peroxide for 24 h to remove organic contamination and then identified using the strongest performing library. We found that libraries with fewer sample spectra produced lower correlation matches and that using derivative correction greatly reduced the number of inaccuracies in identifying materials as either natural or synthetic. We also found that environmental fouling reduced the correlation value of library matches when compared to pristine particles, however the effect was not consistent across the four materials tested. Overall, we found that the accuracy of automated library matching in the tested systems and processing routines varied from 64.1 to 98.0% for distinguishing between natural and synthetic materials, and that a high Hit Quality Index (HQI) did not always correlate with accuracy. These results are important for the microplastic field, demonstrating a need to rigorously test spectral libraries and processing routines with known materials to ensure identification accuracy.

Kozloski, Rachel↗

Examination of 3013 Containers Baseline Surface Features

The Surveillance and Monitoring Program at Los Alamos National Laboratory (LANL) was tasked with evaluating the baseline features of 3013 containers. This baseline is to be used as a basis for comparison for 3013 containers that had been packaged with corrosive plutonium materials. The LANL team evaluated an unwelded container, an unused welded container, and a welded container that had held plutonium metal without any corrosive impurities. These three containers had features with depths no larger than 6 µm and had similar depth distributions. The features observed in the baseline containers were all shallower than those seen in containers packaged with corrosive plutonium materials. This work establishes workflows for feature identification and measurement, as well as establishment of baseline data for future comparison with corroded containers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

University Partnership Program for Scintillator Materials Research

The Scintillation Detection Development (SDD) group of the Particle Physics Division (PPD) at Fermi National Accelerator Laboratory (Fermilab) conducts research and development work in the field of materials that exhibit scintillation properties for use in particle detection and identification in nuclear and high energy physics experiments and applications. SDD has established a University Partnership Program for Scintillator Materials Research (Program), to facilitate collaboration with faculty and students from local universities. The collaboration between the SDD group and Dominican University will address the development of new plastic scintillating materials in two ways: 3.1. Synthesis of new organic fluorescent compounds to test with plastics commonly used in scintillation applications 3.2. Preparation and testing of commercially available plastics known for their resilience to radiation and rarely used in scintillation applications

43 PARTICLE ACCELERATORS↗

Characterization Techniques Investigated for Characterization of Anomalous Materials in Plutonium Oxide – 25666

The DOE has adopted a Dilute and Dispose approach for processing surplus plutonium which consists of blending plutonium oxide with adulterants and packaging it in a form which is acceptable for disposal at the Waste Isolation Pilot Plant. The feed material for the downblend process is intended to be pure plutonium oxide powder, however other objects are occasionally encountered within the oxide, particularly with legacy material. Potential technologies which could assist in the resolution of incidents where such anomalies are encountered have been investigated. Resolution of these incidents requires characterization of the anomalous object so that plutonium oxide processing can resume and so that a disposition pathway can be determined for the anomalous material. Technologies including gamma ray spectroscopy, alpha-gamma coincidence, LiDAR volumetric measurements, and surface conductivity measurements were investigated for this purpose, with a focus on systems which can be easily introduced into the processing environment when an anomaly is encountered, then removed from the environment after resolution to avoid impeding normal processing activities. This places an emphasis on small and portable measurement systems and systems that can operate in a high-background, oxide-processing environment. Gamma ray systems investigated include the GR1™a CZT detector and the MicroGe™a germanium detector, with a focus on detecting characteristic gamma rays from Pu-239 and other actinides. A gamma ray and alpha particle coincidence method was investigated with the goal of identifying actinides in the presence of a gamma ray background produced by adjacent plutonium oxide material. Leica™b BLK360 G1 and Keyence™c LJ-X8300 LiDAR systems were investigated for use in conjunction with mass measurements to gain accurate material density values, and a Foerster Sigmatest™d 2.070 was tested to determine surface conductivity. The combination of these properties would allow improved identification and characterization of a wide variety of potential anomalous material.

Munson, Justin M.↗

Machine-learning-accelerated multimodal characterization and multiobjective design optimization of natural porous materials

Natural porous materials such as nanoporous clays are used as green and low-cost adsorbents and catalysts. The key factors determining their performance in these applications are the pore morphology and surface activity, which are typically represented by properties such as specific surface area, pore volume, micropore content and pH. The latter may be modified and tuned to specific applications through material processing and/or chemical treatment. Characterization of the material, raw or processed, is typically performed experimentally, which can become costly especially in the context of tuning of the properties towards specific application requirements and needing numerous experiments. In this work, we present an application of tree-based machine learning methods trained on experimental datasets to accelerate the characterization of natural porous materials. The resulting models allow reliable prediction of the outcomes of experimental characterization of processed materials (R2 from 0.78 to 0.99) as well as identification of key factors contributing to those properties through feature importance analysis. Furthermore, the high throughput of the models enables exploration of processing parameter–property correlations and multiobjective optimization of prototype materials towards specific applications. We have applied these methodologies to pinpoint and rationalize optimal processing conditions for clays exploitable in acid catalysis. One of such identified materials was synthesized and tested revealing appreciable acid character improvement with respect to the pristine material. Specifically, it achieved 79% removal of chlorophyll-a in acid catalyzed degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical image analysis for graphene layer detection: Enhanced green channel methodology

Graphene, a material of increasing research interest, requires accurate layer identification due to its sensitivity to layer count. Existing methods for graphene layer number identification are either time-consuming or of low accuracy, with high-accuracy methods often requiring expensive processes. This paper aims to address this challenge by proposing a cost-effective and efficient approach. Specifically, the current work highlights only the green channel—one of the three primary color channels (red, green, blue) that make up an optical image—from images of exfoliated graphene flakes for layer count identification. A linear regression is performed between pixel position and substrate green channel value, and this effect is subtracted from the entire optical image to mitigate background effects. By storing the range of green channel values for each type of flake (monolayer, bilayer, or tri-layer) based on a few images, we establish thresholds for identifying different types of layers in a particular setup. Additionally, our methodology allows for flexible threshold tuning using a single reference image, enabling adjustment to changes in detection setup such as illumination level, magnification, or microscope used. Finally, demonstrating high accuracy and flexibility, this methodology presents a suitable technique for graphene layer number identification without the need for large datasets or expensive instruments.

2D materials↗

Multi‐Objective Optimization for Rapid Identification of Novel Compound Metals for Interconnect Applications

Abstract Interconnect materials play the critical role of routing energy and information in integrated circuits. However, established bulk conductors, such as copper, perform poorly when scaled down beyond 10 nm, limiting the scalability of logic devices. Here, a multi‐objective search is developed, combined with first‐principles calculations, to rapidly screen over 15,000 materials and discover new interconnect candidates. This approach simultaneously optimizes the bulk electronic conductivity, surface scattering time, and chemical stability using physically motivated surrogate properties accessible from materials databases. Promising local interconnects are identified that have the potential to outperform ruthenium, the current state‐of‐the‐art post‐Cu material, and also semi‐global interconnects with potentially large skin depths at the GHz operation frequency. The approach is validated on one of the identified candidates, CoPt, using both ab initio and experimental transport studies, showcasing its potential to supplant Ru and Cu for future local interconnects.

Chemistry↗

Signature Analysis Utilizing a Dynamic Molten Salt Reactor Model for MC&A

Moving from traditional fixed fuel nuclear reactor systems to a mobile, dynamic fuel system that has dissolved special nuclear material in a molten salt is a paradigm shift in several respects. One major consideration is how to develop effective nuclear material controls and accounting for these novel reactor systems. The Molten Salt Reactor Experiment is one example of a critical molten salt system and provided a significant reference library based on the documented effort. But it was low thermal power that was not intended to reflect a commercial scale electricity production design. Therefore, to facilitate and assist vendors with domestic licensing considerations, research is underway to identify methods that could be used for domestic safeguards approaches for these novel reactor systems. This research presents the results of a signature analysis of data generated from three simulated scenarios using the molten salt demonstration reactor model defined in the Transient Simulation Framework of Reconfigurable Modules. Each scenario provides 1 hour isotope inventories over a 180 day period. The scenarios investigated provide test cases to examine if direct gamma-ray spectroscopy of the fuel can be used to identify changes comparing a base case (no reactivity control and fixed fission contribution) to an insertion of reactivity (10 pcm no change in fission composition) and a change in fission composition. The analysis demonstrates that monitoring the total count rate in a highly collimated high-resolution photon energy spectrum is sensitive to perturbations imposed into the reactor model. The total photon count rate changes ≈2% for the fission composition change and ≈4.5% for the reactivity insertion compared to the base case. However, both scenarios show an increase in the total photon count rate. The total photon count rate can be used to identify changes due to power (number of fissions) but not due to a change in the material undergoing fission. To distinguish between the two cases of increased power, the photon spectrum would require an intensive analysis technique. A photon peak count rate ratio analysis could be used to identify changes in the fissile material fission generation in the core through identification of a static peak that shows little variation to the source of fission and a highly varying peak. The photon peak strength will ultimately be determined by the isotope’s fission yield. A preliminary analysis investigating the coupling of the isotope’s fission yield and its concentration in the fuel salt derived from the modeling has been performed. A ratio analysis of the photon peak count rates of 140 La to 99 Mo demonstrated that the reactivity insertion creates a distinct difference in the ratio compared to the fission composition change scenario.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗