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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

IL-17A Increases Doxorubicin Efficacy in Triple Negative Breast Cancer

Due to lack of targetable receptors and intertumoral heterogeneity, triple negative breast cancer (TNBC) remains particularly difficult to treat. Doxorubicin (DOX) is typically used as nonselective neoadjuvant chemotherapy, but the diversity of treatment efficacy remains unclear. Comparable to variability in clinical response, an experimental model of TNBC using a 4T1 syngeneic mouse model was found to elicit a differential response to a seven-day treatment regimen of DOX. Single-cell RNA sequencing identified an increase in T cells in tumors that responded to DOX treatment compared to tumors that continued to grow uninhibited. Additionally, compared to resistant tumors, DOX sensitive tumors contained significantly more CD4 T helper cells (339%), γδ T cells (727%), Naïve T cells (278%), and activated CD8 T cells (130%). Furthermore, transcriptional profiles of tumor infiltrated T cells in DOX responsive tumors revealed decreased exhaustion, increased chemokine/cytokine expression, and increased activation and cytotoxic activity. γδ T cell derived IL-17A was identified to be highly abundant in the sensitive tumor microenvironment. IL-17A was also found to directly increase sensitivity of TNBC cells in combination with DOX treatment. In TNBC tumors sensitive to DOX, increased IL-17A levels lead to a direct effect on cancer cell responsiveness and chronic stimulation of tumor infiltrated T cells leading to improved chemotherapeutic efficacy. IL-17A’s role as a chemosensitive cytokine in TNBC may offer new opportunities for treating chemoresistant breast tumors and other cancer types.

4T1↗
DOE OSTI2020

Single-entity electrochemistry at confined sensing interfaces

Measurements at the single-entity level provide more precise diagnosis and understanding of basic biological and chemical processes. Recent advances in the chemical measurement provide a means for ultra-sensitive analysis. Confining the single analyte and electrons near the sensing interface can greatly enhance the sensitivity and selectivity. In this work, we summarize the recent progress in single-entity electrochemistry of single molecules, single particles, single cells and even brain analysis. The benefits of confining these entities to a compatible size sensing interface are exemplified. Finally, the opportunities and challenges of single entity electrochemistry are addressed.

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

A redox-reversible A/B-site co-doped BaFeO 3 electrode for direct hydrocarbon solid oxide fuel cells

Solid oxide fuel cells (SOFCs) can directly convert the chemical energy in fuel to electrical energy with fuel flexibility; however, the conventional nickel-based anodes face great challenges due to coking upon direct oxidation of hydrocarbon fuels and redox instability. Thus, developing new anode materials which can provide high coking resistance as well as redox stability is crucial. In this work, Ba 0.6 La 0.4 Fe 0.8 Mo 0.1 Ni 0.1 O 3-δ (BLFMN) has been synthesized in air using a sol–gel combustion method, resulting in a dual phase consisting of a cubic BLFMN main phase and scheelite BaMoO 4 (BMO 4 ) secondary phase. By heat-treating the BLFMN dual phase in H 2 at 800 °C for 5 h, a metallic nanoparticle-decorated BLFMN triple phase compound comprising cubic BLFMN, cubic BaMoO 3 (BMO 3 ) and in situ exsolved FeNi 3 alloy was obtained. BLFMN was subsequently investigated as an electrode material for La 0.8 Sr 0.2 Ga 0.83 Mg 0.17 O 3-δ (LSGM) electrolyte (300 μm) supported SOFCs. Symmetrical cells using BLFMN as electrodes with the cell configuration of BLFMN//LSGM//BLFMN showed excellent redox reversibility and a peak power density (PPD) of 1.32 W cm -2 at 850 °C when using H 2 as fuel. Single cell with the cell configuration of BLFMN//LSGM//LSCF (La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ ) reached PPD of 1.61 and 0.41 W cm -2 at 850 °C when operating with H 2 and CH 4 fuel, respectively. Moreover, the single cell exhibit excellent stability (over 300 h) upon direct oxidation of hydrocarbon fuels of CH 4 and C 3 H 8 . This study indicates that BLFMN is a promising redox reversible and coking resistant anode for SOFCs.

08 HYDROGEN↗
DOE OSTI2020

Quaternized poly(arylene ether benzonitrile) membranes for vanadium redox flow batteries

In this work, a series of quaternized poly (arylene ether benzonitrile)s (QAxCN; x = percent quaternization) were synthesized for the vanadium redox flow battery (VRFB) application. The presence of highly polar nitrile groups incorporated in the quaternized polymer chain provides desirable polymer properties (low water uptake, high dimensional stability and low VO 2+ permeability) without compromising ion conductivity. VRFB single cells using the aforementioned membranes showed excellent performance. As a result, the cell using a 15 μm-thick QA50CN membrane exhibited superior coulombic efficiency (98.2%) and comparable energy efficiency (86.5%) at 40 mA cm -2 compared to the single cell using Nafion-212 with a coulombic efficiency of 95.5% and an energy efficiency of 86.2%. The cell cycling stability and membrane oxidative stability data confirmed that the QAxCN membranes have the potential to replace Nafion membranes for energy storage in VRFB applications.

25 ENERGY STORAGE↗
DOE OSTI2023

Light-sheet autofluorescence lifetime imaging with a single-photon avalanche diode array

Significance: Fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzyme nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] is a popular method to monitor single-cell metabolism within unperturbed, living 3D systems. However, FLIM of NAD(P)H has not been performed in a light-sheet geometry, which is advantageous for rapid imaging of cells within live 3D samples. Aim: We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM. Approach: A single-photon avalanche diode camera was integrated into a light sheet microscope to achieve optical sectioning and limit out-of-focus contributions for NAD(P)H FLIM of single cells. Results: An NAD(P)H light-sheet FLIM system was built and validated with fluores cence lifetime standards and with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times. NAD(P)H light-sheet FLIM in vivo was demonstrated with live neutrophil imaging in a larval zebrafish tail wound also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light-sheet geometries, indicating a 30× to 6× acquisition speed advantage for the light sheet compared to the laser scanning geometry. Conclusions: FLIM of NAD(P)H is feasible in a light-sheet geometry and is attrac tive for 3D live cell imaging applications, such as monitoring immune cell metabolism and migration within an organism.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Hedgehog–FGF signaling axis patterns anterior mesoderm during gastrulation

Significance Anterior–posterior axis patterning is a fascinating but poorly understood developmental process. Single-cell sequencing was utilized to interrogate patterning abnormalities in a mesoderm-specific Hedgehog (Hh) pathway mutant, which revealed selective anterior mesoderm defects. We found that Hh signaling was required for fibroblast growth factor (FGF) pathway activity in nascent mesoderm during gastrulation. Mouse genetics, cell biology, and genomic experiments indicate that FGF signaling acts downstream of Hh signaling in nascent mesoderm for anterior mesoderm morphogenesis. This work demonstrates the utility of applying single-cell technologies to resolve complex developmental phenotypes. Here, it revealed a role for Hh signaling from the node in organizing anterior mesoderm morphogenesis, independent of its role in left–right determination, by promoting FGF signaling in gastrulating mesoderm.

Guzzetta, Alexander↗
DOE OSTI2024

Single-nuclei transcriptome analysis of channel catfish spleen provides insight into the immunome of an aquaculture-relevant species

The catfish industry is the largest sector of U.S. aquaculture production. Given its role in food production, the catfish immune response to industry-relevant pathogens has been extensively studied and has provided crucial information on innate and adaptive immune function during disease progression. To further examine the channel catfish immune system, we performed single-cell RNA sequencing on nuclei isolated from whole spleens, a major lymphoid organ in teleost fish. Libraries were prepared using the 10X Genomics Chromium X with the Next GEM Single Cell 3’ reagents and sequenced on an Illumina sequencer. Each demultiplexed sample was aligned to the Coco_2.0 channel catfish reference assembly, filtered, and counted to generate feature-barcode matrices. From whole spleen samples, outputs were analyzed both individually and as an integrated dataset. The three splenic transcriptome libraries generated an average of 278,717,872 reads from a mean 8,157 cells. The integrated data included 19,613 cells, counts for 20,121 genes, with a median 665 genes/cell. Cluster analysis of all cells identified 17 clusters which were classified as erythroid, hematopoietic stem cells, B cells, T cells, myeloid cells, and endothelial cells. Subcluster analysis was carried out on the immune cell populations. Here, distinct subclusters such as immature B cells, mature B cells, plasma cells, γδ T cells, dendritic cells, and macrophages were further identified. Differential gene expression analyses allowed for the identification of the most highly expressed genes for each cluster and subcluster. This dataset is a rich cellular gene expression resource for investigation of the channel catfish and teleost splenic immunome.

Science & Technology - Other Topics↗
DOE OSTI2025

591 MHz SRF Cavity Design for the EIC ESR

The Electron-Ion Collider (EIC) is a next generation particle accelerator to be built at Brookhaven National Laboratory, in partnership with Thomas Jefferson National Accelerator Facility. The Electron Storage Ring (ESR) of RIC requires a 10 MW RF storage system to restore beam power lost by a 2.5 A electron beam. The RF system will use 18 single-cell 591 MHz Superconducting RF (SRF) cavities. Effective damping of higher-order-modes (HOMs) is critical to ensure beam stability. This paper presents the design of the single-cell 591 MHz cavity, including cavity geometry optimization, multipacting evaluation, and HOM damping analysis.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Converting methoxy groups on lignin-derived aromatics from a toxic hurdle to a useful resource: a systems-driven approach

Lignin conversion to bioproducts is challenging for several reasons, including the toxicity generated from the abundant methoxy groups released as formaldehyde. Consequently, our project used the best understood methylotroph – for which there is growing knowledge of formaldehyde stress responses – to explore how genetic factors and single-cell phenotypic heterogeneity contribute to growth and production. Our major goals were to (1) understand the fundamentals of Methylobacterium growth on aromatics, (2) identify and understand the basis of physiological basis of single-cell heterogeneity, and (3) develop quantitative models that relate heterogeneity to physiological and evolutionary outcomes.

Source record↗
DOE OSTI2025

Crystalline Peptoid Nanofibers with a Single-Unit Cell Cross Section

Ultranarrow crystalline one-dimensional nanostructures formed from soft materials facilitate precise structural control in nanomaterial design, which is essential for biomedicine and nanotechnology applications. Systematic control of their hierarchical structure is challenging due to the complexities of simultaneously manipulating multiple noncovalent interactions at such small scales. We employed a polypeptoid crystal motif as a supramolecular synthon to engineer ultranarrow crystalline nanofibers constrained to a single lattice axis by incorporating a single ionizable side chain into the hydrophobic core of a nanosheet-forming peptoid. Cryogenic transmission electron microscopy of the nanofibers revealed detailed molecular arrangements of a unit-cell cross-section and the presence of distinct pH-dependent lattice isoforms that resulted in morphological transformations. Molecular dynamics simulations demonstrated that the ionizable side chain plays a critical role in changing the local conformation of the unit cell, which further impacts the dimensionality of hierarchical structures. Moreover, these fibers were readily functionalized with biological ligands to afford one-dimensional (1D) protein arrays. This approach for the high-precision bottom-up assembly of ultranarrow 1D nanostructures offers significant potential for developing novel biomimetic nanostructures.

Lee, Yen Jea↗
DOE OSTI2026

Evaluating Limits of Machine Learning-Assisted Raman Spectroscopy in Classification of Biological Samples

Machine learning (ML)-assisted Raman spectroscopy has become a powerful analytical tool for the classification and identification of analytes; however, technical challenges impacting its detection accuracy have not been thoroughly investigated. This study explores experimental factors affecting classification performance. Among the evaluated ML models, ML algorithms show minimal impact on classification accuracy. Instead, experimental factors, including spectral similarity between tested samples and data quality, dominate detection performance. Increases in spectral noise and spectral similarity significantly reduce classification accuracy. In well-controlled samples with low experimental noise, ML-assisted Raman spectroscopy can discriminate lipid mixtures with a composition difference of 1.85 mol %. To assess the effect of biological heterogeneity, we analyzed single-cell Raman spectra from Saccharomyces cerevisiae strains carrying single, double, or triple gene mutations. Intrinsic cell-to-cell variability introduced substantial spectral differences, severely reducing the accuracy of multiclass classification of these genetically similar strains at the single-cell level. Averaging Raman spectra across multiple cells improved classification accuracy by reducing this spectral variability. We also assess the effectiveness of transfer learning across different Raman spectrometers, specifically by applying an ML model trained on one instrument to another Raman spectrometer. Transfer learning can be improved with proper instrument calibration, highlighting the importance of instrument standardization. Overall, our results demonstrate that data quality and spectral similarity are the primary bottlenecks in ML-assisted Raman spectroscopy. Careful attention to sample preparation, data acquisition, measurement conditions, and instrument calibration is critical to achieving robust and reliable classification performance.

Fungi↗
DOE OSTI2021

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. Here we describe a “follow the tissue” pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Preexisting Type 1 Diabetes Mellitus Blunts the Development of Posttraumatic Osteoarthritis

Type 1 diabetes mellitus (T1DM) affects 9.5% of the population. T1DM is characterized by severe insulin deficiency that causes hyperglycemia and leads to several systemic effects. T1DM has been suggested as a risk factor for articular cartilage damage and loss, which could expedite the development of osteoarthritis (OA). OA represents a major public health challenge by affecting 300 million people globally, yet very little is known about the correlation between T1DM and OA. In addition, current studies that have looked at the interaction between diabetes mellitus and OA have reported conflicting results with some suggesting a positive correlation whereas others did not. In this study, we aimed to evaluate whether T1DM exacerbates the development of spontaneous OA or accelerates the progression of posttraumatic osteoarthritis (PTOA) after joint injury. Histological evaluation of T1DM and control joints determined that T1DM mice displayed cartilage degeneration measurements consistent with mild OA phenotypes. RNA sequencing analyses identified significantly upregulated genes in T1DM corresponding to matrix-degrading enzymes known to promote cartilage matrix degradation, suggesting a role of these enzymes in OA development. Next, we assessed whether preexisting T1DM influences PTOA development subsequent to trauma. At 6 weeks post-injury, T1DM injured joints displayed significantly less cartilage damage and joint degeneration than injured non-diabetic joints, suggesting a significant delay in PTOA disease progression. At the single-cell resolution, we identified increased number of cells expressing the chondrocyte markers Col2a1, Acan, and Cytl1 in the T1DM injured group. Our findings demonstrate that T1DM can be a risk factor for OA but not for PTOA. This study provides the first account of single-cell resolution related to T1DM and the risk for OA and PTOA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Growth and Properties of Vapor Diffused Nb3Sn Coating for Superconducting Radiofrequency Accelerator Cavity Applications

The desire to reduce construction and operating costs of future SRF accelerators motivates the search for higher-performing alternative materials. Nb3Sn (Tc ~ 18.3 K and Hsh ~ 425 mT) is the front runner. The tin vapor diffusion process is currently the technique of choice to produce promising Nb3Sn-coated cavities. Understanding Nb3Sn nucleation and growth in this process is essential to progress. Samples representing different stages of Nb3Sn formation have been produced and studied to elucidate the effects of nucleation, growth, process conditions, and impurities. Nb3Sn films with thickness from a few hundred nm up to ~15 µm were grown and characterized. The microscopic examination of samples suggests the mechanisms of thin film nucleation and growth. Broadly, nucleation deposits tin as a thin surface phase and, under some conditions, a few hundred nanometer sized particles as well. Conditions that impair nucleation promote the formation of defects, such as ?patches?, in subsequent coating growth. Analysis of coated samples is consistent with the model of Nb3Sn grown in which tin diffuses via grain boundaries to Nb3Sn-Nb interface, where the growth Nb3Sn into the niobium bulk takes place. Similar scaling laws are found for grain growth and layer thickness. Non-parabolic layer growth is consistent with significant grain growth, which reduces the number of Sn-transport channels. Examination of patchy region in Nb3Sn coating revealed it to be large single crystalline grains, pointing to impeded Nb3Sn layer growth due to low grain boundary density, resulting in a significantly thin coating in those areas. Examination of RF loss regions from a coated cavity, identified with a thermometry mapping system showed patchy regions and carbonus defects were associated with strong local field-dependent surface resistance. RF measurements of coated cavities were combined with material characterization of witness samples and coated-cavity cutouts to improve the coating process. Understanding obtained and applied to cavity coatings, resulted in single-cell Nb3Sn cavities with a quality factor of ~2 ×1010 up to 15 MV/m accelerating gradient at 4 K, without "Wuppertal" Q-slope. We have also produced Nb3Sn-coated CEBAF 5-cell cavities with accelerating gradients useful for accelerator cryomodules. This dissertation will discuss the genesis of the Nb3Sn coating in a typical tin vapor diffusion process, effects of different process parameters, and its consequences to the coating of single-cell and multi-cell SRF cavities.

Pudasaini, Uttar↗
DOE OSTI2025

A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases

Human diseases are characterized by intricate cellular dynamics. Single-cell transcriptomics provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in silico drug interventions. Here we introduce UNAGI, a deep generative neural network tailored to analyse time-series single-cell transcriptomic data. This tool captures the complex cellular dynamics underlying disease progression, enhancing drug perturbation modelling and screening. When applied to a dataset from patients with idiopathic pulmonary fibrosis, UNAGI learns disease-informed cell embeddings that sharpen our understanding of disease progression, leading to the identification of potential therapeutic drug candidates. Validation using proteomics reveals the accuracy of UNAGI’s cellular dynamics analysis, and the use of the fibrotic cocktail-treated human precision-cut lung slices confirms UNAGI’s predictions that nifedipine, an antihypertensive drug, may have anti-fibrotic effects on human tissues. UNAGI’s versatility extends to other diseases, including COVID, demonstrating adaptability and confirming its broader applicability in decoding complex cellular dynamics beyond idiopathic pulmonary fibrosis, amplifying its use in the quest for therapeutic solutions across diverse pathological landscapes.

Neural Network↗
DOE OSTI2022

Does non-reciprocity break the Shockley–Queisser limit in single-junction solar cells?

The efficiency of single-junction solar cells is bounded by the Shockley–Queisser limit of 41%. However, standard derivation for this limit constrains the system to be reciprocal, and what non-reciprocity can bring for single-junction solar cells remains yet to be clarified. Here, we prove that even with non-reciprocity, the ultimate efficiency of single-junction solar cells is still subject to the Shockley–Queisser limit. Here, we show that the Shockley–Queisser limit does not rely on the detailed balance, but rather is a consequence of the integrated balance between the absorption and emission processes, as required by the second law of thermodynamics.

14 SOLAR ENERGY↗
DOE OSTI2021

HUNTRESS: a fast heuristic for reconstructing phylogenetic trees of tumor evolution (HUNTRESS) v0.1

We introduce HUNTRESS (Histogrammed UNion Tree REconStruction heuriStic), a computational method for tumor phylogeny reconstruction from noisy genotype matrices derived from single-cell sequencing data, whose running time is linear with the number of cells and quadratic with the number of mutations. Provided that the input genotype matrix includes no false positives, each cellular subpopulation is at least a user defined fraction of the total number of cells, and the number of cells are much bigger than the number of mutations considered, HUNTRESS computes the ground truth tumor phylogeny with high probability. On simulated data HUNTRESS is faster than available alternatives with comparable or better accuracy. Additionally, the phylogenies reconstructed by HUNTRESS on two single-cell sequencing data sets agree with the best known evolutionary scenarios for the associated tumors.

Buluc, Aydin↗
DOE OSTI2022

Managing Sn-Supply to Tune Surface Characteristics of Vapor-Diffusion Coating of Nb₃Sn

Nb₃Sn promises better RF performance (Q and E_{acc}) than niobium at any given temperature because of superior superconducting properties. Nb₃Sn-coated SRF cavities are now produced routinely by growing a few microns thick Nb₃Sn films inside Nb cavities via the tin vapor diffusion technique. Sn evaporation and consumption during the growth process notably affect the quality of the coating. Aiming at favorable surface characteristics that could enhance the RF performance, many coatings were produced by varying Sn sources and temperature profiles. Coupon samples were examined using different material characterization techniques, and a selected few sets of coating parameters were used to coat 1.3 GHz single-cell cavities for RF testing. The Sn supply’s careful tuning is essential to manage the microstructure, roughness, and overall surface characteristics of the coating. We summarize the material analysis of witness samples and discuss the performance of several Nb₃Sn-coated single-cell cavities linked to Sn-source characteristics and observed Sn consumption during the film growth process.

Pudasaini, U.↗