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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Quantitative Analysis of Defects in Silicon

The evaluation and prediction of the conversion efficiency for a variety of silicon samples with differences in structural defects, such as grain boundaries, twin boundaries, precipitate particles, dislocations, etc. are discussed. Quantitative characterization of these structural defects, which were revealed by etching the surface of silicon samples, is performed by using an image analyzer. Due to different crystal growth and fabrication techniques the various types of silicon contain a variety of trace impurity elements and structural defects. The two most important criteria in evaluating the various silicon types for solar cell applications are cost and conversion efficiency.

Natesh, R.↗
NASA NTRS1985

Quantitative analysis in megageomorphology

Megageomorphology is the study of regional topographic features and their relations to independent geomorphic variables that operate at the regional scale. These independent variables can be classified as either tectonic or climatic in nature. Quantitative megageomorphology stresses the causal relations between plate tectonic factors and landscape features or correlations between climatic factors and geomorphic processes. In addition, the cumulative effects of tectonics and climate on landscape evolution that simultaneously operate in a complex system of energy transfer is of interst. Regional topographic differentiation, say between continents and ocean floors, is largely the result of the different densities and density contrasts within the oceanic and continental lithosphere and their isostatic consequences. Regional tectonic processes that alter these lithospheric characteristics include rifting, collision, subduction, transpression and transtension.

Mayer, L.↗
NASA NTRS2020

A Sensitive Quantitative Analysis of Abiotically Synthesized Short Homopeptides using Ultraperformance Liquid Chromatography and Time-of-Flight Mass Spectrometry

In the origins of life field understanding the abiotic polymerization of simple organic monomers (e.g., amino acids) into larger biomolecules (e.g., oligopeptides), remains a seminal challenge. Recently, preliminary observations showed a limited set of peptides formed in the presence of the plausible prebiotic phosphorylating agent, diamidophosphate (DAP), highlighting the need for an analytical tool to critically evaluate the ability of DAP to induce oligomerization of simple organics under aqueous conditions. However, performing accurate and precise, targeted analyses of short oligopeptides remains a distinct challenge in the analytical chemistry field. Here, we developed a new technique to detect and quantitate amino acids and their homopeptides in a single run using ultraperformance liquid chromatography-fluorescence detection/time of flight mass spectrometry. Over an 8-minute retention time window, 18 target analytes were identified and quantitated, 16 of which were chromatographically separated at, or near baseline resolution. Compound identity was confirmed by accurate mass analysis using a 10 ppm mass tolerance window. This method featured limits of detection < 5 nM (< 1 fmol on column) and limits of quantitation (LOQs) <15 nM (< 3 fmol on column). The LODs and LOQs were upwards of ∼28x and ∼788x lower, respectively, than previous methods for the same analytes, highlighting the quantifiable advantages of this new method. Both detectors provided good quantitative linearity (R(exp 2) > 0.985) for all analytes spanning concentration ranges ∼3 - 4 orders of magnitude. We performed a series of laboratory experiments to investigate DAP-mediated oligomerization of amino acids and peptides and analyzed experimental products with the new method. DAP readily polymerized amino acids and peptides under a range of simulated environmental conditions. This research underscores the potential of DAP to have generated oligopeptides on the primordial Earth, enhancing prebiotic chemical diversity and complexity at or near the origin of life.

Prebiotic Chemistry and Analytical Chemistry↗
NASA NTRS1995

A field- and laboratory-based quantitative analysis of alluvium: Relating analytical results to TIMS data

Thermal Infrared Multispectral Scanner (TIMS) data were acquired over the McDowell Mountains northeast of Scottsdale, Arizona during August 1994. The raw data were processed to emphasize lithologic differences using a decorrelation stretch and assigning bands 5, 3, and 1 to red, green, and blue, respectively. Processed data of alluvium flanking the mountains exhibit moderate color variation. The objective of this study was to determine, using a quantitative approach, what environmental variable(s), in the absence of bedrock, is/are responsible for influencing the spectral properties of the desert alluvial surface.

Wenrich, Melissa L.↗
NASA NTRS1994

A quantitative analysis of IRAS maps of molecular clouds

We present an analysis of IRAS maps of five molecular clouds: Orion, Ophiuchus, Perseus, Taurus, and Lupus. For the classification and description of these astrophysical maps, we use a newly developed technique which considers all maps of a given type to be elements of a pseudometric space. For each physical characteristic of interest, this formal system assigns a distance function (a pseudometric) to the space of all maps: this procedure allows us to measure quantitatively the difference between any two maps and to order the space of all maps. We thus obtain a quantitative classification scheme for molecular clouds. In this present study we use the IRAS continuum maps at 100 and 60 micrometer(s) to produce column density (or optical depth) maps for the five molecular cloud regions given above. For this sample of clouds, we compute the 'output' functions which measure the distribution of density, the distribution of topological components, the self-gravity, and the filamentary nature of the clouds. The results of this work provide a quantitative description of the structure in these molecular cloud regions. We then order the clouds according to the overall environmental 'complexity' of these star-forming regions. Finally, we compare our results with the observed populations of young stellar objects in these clouds and discuss the possible environmental effects on the star-formation process. Our results are consistent with the recently stated conjecture that more massive stars tend to form in more 'complex' environments.

Wiseman, Jennifer J.↗
NASA NTRS2016

Polarbrdf: A General Purpose Python Package for Visualization Quantitative Analysis of Multi-Angular Remote Sensing Measurements

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wild fire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

CAR↗
DOE OSTI2026

A Multiplexed Quantitative Analysis of Germline Single Amino Acid Variants by Targeted Proteomics in Nondepleted Human Plasma

Single amino acid variants (SAAVs) in protein sequences are often a direct result of single-nucleotide polymorphisms (SNPs). Certain germline SAAVs have shown biological relevance in different disease conditions but lack precise quantification in circulation, which could hinder functional investigations and progress in biomarker development. Here, we have developed a multiplexed liquid chromatography-selected reaction monitoring (LC-SRM) assay that monitors 5 wild-type and variant peptide pairs (Complement Factor B: CFB-R32Q/R32W, Clusterin: CLU-N317H, Fetuin B: FETUB-K360R, and Kininogen: KNG1-L212P) in nondepleted human plasma. The assay was optimized for imprecision, linearity, stability, and calibration assessments with CVs of under 20%. The wild-type and variant peptide pairs were characterized in a set of healthy individual plasma samples. These target identifications were also validated by SNP genotyping with more than 99% accuracy. For all protein targets, we observed significantly lower concentrations of WT species in the presence variant peptides. In CFB, the concentration of R32Q was significantly lower than its counterpart R32W variant and WT species. Furthermore, our results distinguished phenotypes of homozygosity and heterozygosity of the SAAV presence through direct concentration level characterization. These findings provide some insights into how SAAVs affect quantitative assessments of target peptides. The assay demonstrates a platform for proteogenomic analyses with potential applications in both research and clinical settings.

genetics↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Quantitative Analysis and Prediction of Thermal Runaway Metrics of High-Nickel Oxide Cathodes by Machine Learning Models

The pursuit of higher energy density in lithium-ion batteries has made high-nickel (Ni) layered oxides leading cathode candidates for next-generation electric vehicles. However, their poor thermal stability, particularly at Ni contents ≥ 90%, increases the risk of cathode-initiated thermal runaway. Furthermore, we present a data-driven framework combining linear and nonlinear machine learning models to predict key thermal runaway descriptors from a high-throughput differential scanning calorimetry database. With cathode composition and state of charge (SOC) as input features, the ensemble model accurately predicts peak temperature, heat release, and peak heat flow. SHAP analysis identifies Ni content and SOC as the dominant factors controlling thermal runaway temperature, while SOC primarily governs heat release and peak heat flow. Al, Mg, and Mn improve thermal stability by strengthening metal–oxygen bonding and delaying structural transformation, whereas B mainly reduces heat release through surface passivation. Validation with a new cathode composition confirms accurate prediction of SOC-dependent thermal runaway behavior and critical SOC.

25 ENERGY STORAGE↗
DOE OSTI2025

Quantitative analysis of leakage current in III-nitride micro-light-emitting diodes

In this study, the electrical characteristics under forward- and reverse-bias conditions of III-nitride blue and green micro-light-emitting diodes (μLEDs) are analyzed. A fitting model is proposed to determine the contributions of reverse leakage current and the effectiveness of sidewall treatments. Moreover, the forward-bias currents of the μLEDs are examined using the extracted ideality factor to examine the impacts of sidewall defects. The results show that sidewall treatments are highly effective for suppression of leakage currents. From the efficiency perspective, higher wall-plug efficiency (WPE) than external quantum efficiency (EQE) is observed when the operating voltage is lower than the photon voltage in both blue and green 20 × 20 μm 2 devices. This enhancement of the WPE over the EQE is due to the suppression of Shockley–Read–Hall (SRH) nonradiative recombination. These observations indicate that μLEDs with sidewall treatments not only improve optical performance but also further enhance the electrical performance of devices by suppressing the leakage current paths due to SRH nonradiative recombination processes.

42 ENGINEERING↗
DOE OSTI2026

Quantitative analysis of zonal flow influence on turbulent plasmas driven by trapped electrons

The role of zonal flow (ZF) in the turbulence saturation of trapped electron modes (TEM) in magnetically confined plasmas is revisited. Here, in this study, we examine ZF excitation and saturation mechanisms in TEM turbulence using detailed free-energy transfer diagnostics from nonlinear gyrokinetic simulations. When the ion channel becomes subdominant, electrons shift to transferring energy to the zonal component, which results in zonal flows always playing a significant though subdominant role, in the case of the temperature gradient driven TEM. The velocity-space structure of energy transfer reveals that trapped electrons directly couple to ZF. Regarding the saturation physics, the zonal flow advection, drift-wave–drift-wave interactions, and stable modes at the pump waves are compared. When ZF saturation is weak, drift-wave–drift-wave interactions play a larger role in maintaining turbulence saturation. The findings elucidate the roles of nonzonal to zonal flow coupling, stable modes, and nonzonal wave-wave interactions, and provide a basis for improving reduced models of turbulent transport.

Song, Jiheon [Hanyang University, Seoul (Korea, Re↗
DOE OSTI2026

Dataset for Top Model Decision Tree: Selecting Segmentation Models for Reliable Quantitative Analysis in Low- and Ultralow-Dose CryoEM

Motivation Multiple deep learning model architectures can be used to segment bacterial membranes in cryoEM images. However, an AI-based tool advancement is often presented with only a single segmentation model for broad use, and this single model may show inconsistent results across datasets from different users. Here, we present the Top Model Decision Tree, a model screening framework to screen for the best model to generate bacterial inner and outer membrane masks based on user priorities. We use pre-trained segmentation models from YOLOv11, YOLO26, U-Net, Detectron2 and SAM3 fine-tuned on bacterial inner and outer membranes imaged with cryoEM. Run the Framework This notebook must be opened in Google Colab. Mount Google Drive and run with a GPU-based runtime. Open the notebook and follow steps to git clone in folders and files within this repository. There will be a repeating top_model_decision_tree.ipynb (notebook clone) that will not be used. Save your .png binary mask files and .csv table outputs within your Google Drive or download before closing the notebook. The models and all analysis/training scripts are available at [GitHub: https://github.com/Lynnicia/CryoEM_membranes_top_model_decision_tree and https://github.com/Sireesiru/Semantic-Segmentation-of-bacterial-cell-envelope-using-U-Nets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Quantitative Analysis of Rhodobacter sphaeroides Storage Organelles via Cryo-Electron Tomography and Light Microscopy

Bacterial cytoplasmic organelles are diverse and serve many varied purposes. Here, we employed Rhodobacter sphaeroides to investigate the accumulation of carbon and inorganic phosphate in the storage organelles, polyhydroxybutyrate (PHB) and polyphosphate (PP), respectively. Using cryo-electron tomography (cryo-ET), these organelles were observed to increase in size and abundance when growth was arrested by chloramphenicol treatment. The accumulation of PHB and PP was quantified from three-dimensional (3D) segmentations in cryo-tomograms and the analysis of these 3D models. The quantification of PHB using both segmentation analysis and liquid chromatography and mass spectrometry (LCMS) each demonstrated an over 10- to 20-fold accumulation of PHB. The cytoplasmic location of PHB in cells was assessed with fluorescence light microscopy using a PhaP-mNeonGreen fusion-protein construct. The subcellular location and enumeration of these organelles were correlated by comparing the cryo-ET and fluorescence microscopy data. A potential link between PHB and PP localization and possible explanations for co-localization are discussed. Finally, the study of PHB and PP granules, and their accumulation, is discussed in the context of advancing fundamental knowledge about bacterial stress response, the study of renewable sources of bioplastics, and highly energetic compounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Quantitative Analysis of Fission-Product Surrogates in Molten Salt Chloride Aerosols

This work demonstrates laser-induced breakdown spectroscopy (LIBS) applied to a stream of aerosolized salt from molten eutectic LiCl-KCl. We demonstrate analytical capabilities to track fission-product surrogates of Cs, Sr, Pr, and Nd simultaneously, with application to monitor salts in pyroprocessing schemes and molten salt reactors. This work demonstrates limits of detection using LIBS on the order of 100 μg/g, which proves potentially applicable to monitoring fission-product concentrations in pyroprocessing applications. Additionally, this work explores fundamental aspects of plasma temperature and plasma electron density of the aerosolized species during LIBS with a specific focus on potential non-uniform plasma conditions in the aerosol.

74 - ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1977

Quantitative analysis of the Dermott-Gold theory for Uranus's rings

A summary is presented of an investigation which supplements the largely qualitative analysis conducted by Dermott and Gold (1977). Dermott and Gold have attempted to explain the locations of Uranus's rings in terms of resonances between ring particles and pairs of satellites. An equation of motion, analogous to that of a pendulum, is derived, taking into account a study by Wilkens (1933) of possible three-body resonances involving one minor and two major planets. Dermott and Gold had concluded that the observed pattern is probably due primarily to the effect of Ariel-Titania and Ariel-Oberon pairs. However, on the basis of the values derived in the reported investigation it is seen that Miranda plays the key role rather than Ariel, in spite of the small mass of the former. It is concluded that a decisive test of the Dermott-Gold theory has to await further observational details concerning the Uranus's rings.

Aksnes, K.↗