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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 1,153 records · Page 64

Atom Probe Tomography Analysis of Mica

Laser-assisted atom probe tomography (APT) is a relatively new, powerful technique for sub-nanometric mineral and biomineral analysis. However, the laser-assisted APT analysis of highly anisotropic and chemically diverse minerals, such as phyllosilicates, may prove especially challenging due to the complex interaction between the crystal structure and the laser pulse upon applying a high electric field. Micas are a representative group of nonswelling clay minerals of relevance to a number of scientific and technological fields. In this study, a Mg-rich biotite was analyzed by APT to generate preliminary data on nonisotropic minerals and to investigate the effect of the crystallographic orientation on mica chemical composition and structure estimation. Here, the difference in results obtained for specimens extracted from the (001) and ( hk 0) mica surfaces indicate the importance of both experimental parameters and the crystallography. Anisotropy of mica has a strong influence on the physicochemical properties of the mineral during field evaporation and the interpretation of APT data. The promising results obtained in the present study open the way to future innovative APT applications on mica and clay minerals and contribute to the general discussion on the challenges for the analysis of geomaterials by atom probe tomography.

3D reconstructions↗

Nanoscale Three-Dimensional Imaging of Degradation in Composite Si-Containing Anodes

The use of silicon (Si) in next-generation lithium-ion battery (LIB) anodes has the potential to dramatically improve electrochemical performance over current LIB graphite (Gr) anodes, due to silicon’s higher specific capacity.1 However, widespread implementation of Si-containing anodes is inhibited by issues such as significant Si volume expansion during lithiation and an unstable solid-electrolyte interphase (SEI), resulting in unreliable performance and poor cycle life. Currently, composite anodes with both Si and graphite active materials are used to increase capacity and mitigate some of the limitations associated with Si. In composite electrodes with a heterogeneous distribution of components with varying electrical properties (including Si, Gr, conductive carbon additive, and binder), it is important to understand the local distribution of each component to correlate with electrochemical processes, particularly localized degradation and heterogeneous aging, and to optimize performance. To investigate Si-containing composite anodes in the nanoscale, we use scanning spreading resistance microscopy (SSRM), a form of scanning probe microscopy (SPM) that probes local electronic resistivity. By examining the intrinsic electronic resistivity contrast between the anode components, separate phases can be distinguished and understood within the composite structure.2 This work studies the effect of electrochemical cycling in two different electrolytes on component distribution and aging by comparing the electrical and structural evolution of composite Si-graphite electrodes and SEI before and after charge-discharge cycling. 1. W. J. Zhang. A review of the electrochemical performance of alloy anodes for lithium-ion batteries J. Power Sources 196 13–24 (2011). 2. C. Stetson, Z. Huey, A. Downard, Z. Li, B. To, A. Zakutayev, C.-S. Jiang, M. Al-Jassim, D. Finegan, S.-D. Han and S. DeCaluwe: Three-Dimensional Mapping of Resistivity and Microstructure of Composite Electrodes for Lithium-Ion Batteries. ACS Nano Letters Accepted (2020).

ADVANCED PROPULSION SYSTEMS↗

Engineered Endosymbionts that Modulate Primary Macrophage Function and Attenuate Tumor Growth by Shifting the Tumor Microenvironment

Modulating gene expression in macrophages can be used to improve tissue regeneration and redirect tumor microenvironments (TMEs) toward positive therapeutic outcomes. We have developed Bacillus subtilis as an engineered endosymbiont (EES) capable of residing inside the eukaryotic host cell cytoplasm and controlling the fate of macrophages. Secretion of mammalian transcription factors (TFs) from B. subtilis that expresses listeriolysin O (LLO; allowing the EES to escape destruction by the macrophage) modulated expression of surface markers, cytokines, and chemokines, indicating functional changes in a macrophage/monocyte cell line. The engineered B. subtilis LLO TF strains were evaluated in murine bone marrow-derived macrophages (BMDMs) by flow cytometry, chemokine/cytokine profiling, metabolic assays, and RNA-Seq delivery of TFs by the EES shifted BMDM gene expression, production of cytokine and chemokines, and metabolic patterns, indicating that the TF strains could guide primary macrophage function. Thereafter, the ability of the TF strains to alter the TME was characterized in vivo in an orthotopic murine model of triple-negative breast cancer to assess therapeutic effects. The TF strains altered the TME by shifting immune cell composition and attenuating tumor growth. Additionally, multiple doses of the TF strains were well-tolerated by the mice. The use of B. subtilis LLO TF strains as EES showed promise as a unique cancer immunotherapy by directing the immune function intracellularly. The uses of EES could be expanded to modulate other mammalian cells over a range of biomedical applications.

60 APPLIED LIFE SCIENCES↗

Cosmic ray spectrum of protons plus helium nuclei between 6 and 158 TeV from HAWC data

Here, a measurement with high statistics of the differential energy spectrum of light elements in cosmic rays, in particular, of primary H plus He nuclei, is reported. The spectrum is presented in the energy range from 6 to 158 TeV per nucleus. Data was collected with the High Altitude Water Cherenkov (HAWC) Observatory between June 2015 and June 2019. The analysis was based on a Bayesian unfolding procedure, which was applied on a subsample of vertical HAWC data that was enriched to 82% of events induced by light nuclei. To achieve the mass separation, a cut on the lateral age of air shower data was set guided by predictions of CORSIKA/QGSJET-II-04 simulations. The measured spectrum is consistent with a broken power-law spectrum and shows a kneelike feature at around E = 24.0$^{+3.6}_{-3.1}$ TeV , with a spectral index γ = -2.51 ± 0.02 before the break and with γ = -2.83 ± 0.02 above it. The feature has a statistical significance of 4.1σ. Within systematic uncertainties, the significance of the spectral break is 0.8σ.

79 ASTRONOMY AND ASTROPHYSICS↗

Automating the Analysis of Large Language Models Responses through Zero-Shot Question Answering

Recent advancements in Large Language Models (LLMs) have shown significant potential in various applications, yet their evaluation, particularly in zero-shot question answering scenarios, remains a challenging task. In this study, our objective was to explore precision metrics for Large Language Models (LLM) and design and implement a software pipeline to automatically evaluate LLMs' outputs under zero-shot question answering. Zero-shot question answering involves a model providing answers to questions about topics it hasn't seen during training. It leverages the principles of zero-shot learning by relying on semantic understanding and generalization from related knowledge. The data used was metadata from medical databases on congenital heart disease. We explored eleven LLM metrics and selected three for our evaluation: BLEU, BERTScore, and MoverScore. BLEU calculates a score based on the overlap of n-grams (contiguous sequences of n items, typically words) between the machine-generated translation and the reference translations. Higher BLEU scores indicate better correspondence between the machine-generated and human-generated translations. BERTScore is a metric used to evaluate the quality of machine-generated text by measuring the similarity of token embeddings produced by BERT (Bidirectional Encoder Representations from Transformers) between the generated text and reference text. MoverScore is a metric that quantifies the dissimilarity between the distributions of word embeddings from machine-generated text and reference text, emphasizing semantic similarity over exact token overlap. We also introduced HBKI, a composite metric summarizing these approaches. We tested five models —GPT-3, Llama-2, Gemini 1.5 Pro, Solar 10.7B, and Mixtral-8x7b. Our software pipeline, designed and implemented using Object-Oriented Programming principles, allows users to customize the selection and extraction of features for topics of interest in their own research. Our results show that MoverScore delivered the most precise evaluation of the LLM's outputs, while Mixtral-8x7b achieved the best overall performance in extracting metadata from the databases.

97 MATHEMATICS AND COMPUTING↗

Speculations about plessite

Metallographic examination and microprobe analysis of plessite areas in meteorites - iron and nickel concentration in meteorites

NICKEL↗