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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Bioenergetics and mitochondrial transmembrane potential during differentiation of cultured osteoblasts

To evaluate the relationship between osteoblast differentiation and bioenergetics, cultured primary osteoblasts from fetal rat calvaria were grown in medium supplemented with ascorbate to induce differentiation. Before ascorbate treatment, the rate of glucose consumption was 320 nmol. h(-1). 10(6) cells(-1), respiration was 40 nmol. h(-1). 10(6) cells(-1), and the ratio of lactate production to glucose consumption was approximately 2, indicating that glycolysis was the main energy source for immature osteoblasts. Ascorbate treatment for 14 days led to a fourfold increase in respiration, a threefold increase in ATP production, and a fivefold increase in ATP content compared with that shown in immature cells. Confocal imaging of mitochondria stained with a transmembrane potential-sensitive vital dye showed that mature cells possessed abundant amounts of high-transmembrane-potential mitochondria, which were concentrated near the culture medium-facing surface. Acute treatment of mature osteoblasts with metabolic inhibitors showed that the rate of glycolysis rose to maintain the cellular energy supply constant. Thus progressive differentiation coincided with changes in cellular metabolism and mitochondrial activity, which are likely to play key roles in osteoblast function.

NASA Center ARC↗
DOE OSTI2026

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.

14 SOLAR ENERGY↗
DOE OSTI2023

Nanometer-scale electrical potential imaging on absorber of CdSeTe solar cells

Here, we report on nm-scale electrical potential imaging throughout As-doped and Cu-doped CdSeTe absorbers using Kelvin probe force microscopy (KPFM). The potential imaging was conducted both laterally and vertically on beveled films using ion milling at small glancing angle. KPFM images electrical potential on the beveled surface and assesses defect charging in the subsurface region within a screening length from the beveled surface. We found that the grain boundaries were positively charged and that there were significant potential fluctuations in both grain boundary versus grain interior and intragrain. We further found that these potential fluctuations decreased significantly toward the front interface. Time of flight secondary ion mass spectrometry imaging shows that Se content increased toward the front interface, consistent with Se passivation of defects. The potential fluctuation was induced by defect charging, and the results elucidate different details of the defect configurations and grain structures of the films with different CdCl 2 treatment temperatures in the As-doped CdSeTe. The defect configurations in the region near the front interface can be a main factor contributing to the device performance difference. Our potential imaging provides insights about the defects throughout the absorber films, and shows that the potential fluctuation has a direct correlation to the V oc deficit.

14 SOLAR ENERGY↗
NASA NTRS1989

A hexagonal orthogonal-oriented pyramid as a model of image representation in visual cortex

Retinal ganglion cells represent the visual image with a spatial code, in which each cell conveys information about a small region in the image. In contrast, cells of the primary visual cortex use a hybrid space-frequency code in which each cell conveys information about a region that is local in space, spatial frequency, and orientation. A mathematical model for this transformation is described. The hexagonal orthogonal-oriented quadrature pyramid (HOP) transform, which operates on a hexagonal input lattice, uses basis functions that are orthogonal, self-similar, and localized in space, spatial frequency, orientation, and phase. The basis functions, which are generated from seven basic types through a recursive process, form an image code of the pyramid type. The seven basis functions, six bandpass and one low-pass, occupy a point and a hexagon of six nearest neighbors on a hexagonal lattice. The six bandpass basis functions consist of three with even symmetry, and three with odd symmetry. At the lowest level, the inputs are image samples. At each higher level, the input lattice is provided by the low-pass coefficients computed at the previous level. At each level, the output is subsampled in such a way as to yield a new hexagonal lattice with a spacing square root of 7 larger than the previous level, so that the number of coefficients is reduced by a factor of seven at each level. In the biological model, the input lattice is the retinal ganglion cell array. The resulting scheme provides a compact, efficient code of the image and generates receptive fields that resemble those of the primary visual cortex.

Watson, Andrew B.↗
DOE OSTI2024

Dynamic sparse x-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst

Tomographic imaging of time-evolving samples is a challenging yet important task for various research fields. At the nanoscale, current approaches face limitations of measurement speed or resolution due to lengthy acquisitions. We developed a dynamic nanotomography technique based on sparse dynamic imaging and 4D tomography modeling. We demonstrated the technique, using ptychographic x-ray computed tomography as its imaging modality, on resolving the in situ hydration process of polymer electrolyte fuel cell (PEFC) catalyst. The technique provides a 40-time increase in temporal resolution compared to conventional approaches, yielding 28 nm half-period spatial and 12 min temporal resolution. The results allow a quantitative characterization of the water intake process inside PEFC catalysts with nanoscale resolution, which is crucial for understanding their electrochemical mechanisms and optimizing their performance. Our technique enables high-speed operando nanotomography studies and paves the way for wider application of dynamic tomography at the nanoscale.

Science & Technology - Other Topics↗
NASA NTRS1998

Gel stretch method: a new method to measure constitutive properties of cardiac muscle cells

Diastolic dysfunction is an important cause of congestive heart failure; however, the basic mechanisms causing diastolic congestive heart failure are not fully understood, especially the role of the cardiac muscle cell, or cardiocyte, in this process. Before the role of the cardiocyte in this pathophysiology can be defined, methods for measuring cardiocyte constitutive properties must be developed and validated. Thus this study was designed to evaluate a new method to characterize cardiocyte constitutive properties, the gel stretch method. Cardiocytes were isolated enzymatically from normal feline hearts and embedded in a 2% agarose gel containing HEPES-Krebs buffer and laminin. This gel was cast in a shape that allowed it to be placed in a stretching device. The ends of the gel were held between a movable roller and fixed plates that acted as mandibles. Distance between the right and left mandibles was increased using a stepper motor system. The force applied to the gel was measured by a force transducer. The resultant cardiocyte strain was determined by imaging the cells with a microscope, capturing the images with a CCD camera, and measuring cardiocyte and sarcomere length changes. Cardiocyte stress was characterized with a finite-element method. These measurements of cardiocyte stress and strain were used to determine cardiocyte stiffness. Two variables affecting cardiocyte stiffness were measured, the passive elastic spring and viscous damping. The passive spring was assessed by increasing the force on the gel at 1 g/min, modeling the resultant stress vs. strain relationship as an exponential [sigma = A/k(ekepsilon - 1)]. In normal cardiocytes, A = 23.0 kN/m2 and k = 16. Viscous damping was assessed by examining the loop area between the stress vs. strain relationship during 1 g/min increases and decreases in force. Normal cardiocytes had a finite loop area = 1.39 kN/m2, indicating the presence of viscous damping. Thus the gel stretch method provided accurate measurements of cardiocyte constitutive properties. These measurements have allowed the first quantitative assessment of passive elastic spring properties and viscous damping in normal mammalian cardiocytes.

Non-NASA Center↗
DOE OSTI2024

In-line, High-Throughput Quality Monitoring for Fuel Cell and Electrolyzer Components Based on Transmission and Reflection Imaging

During the manufacturing of fuel cell and electrolyzer membranes and membrane electrode assemblies (MEAs), real-time, in-line, high-throughput optical-based quality monitoring methods are essential for detecting defects and monitoring thickness variations, thus improving the performance and increasing the durability of fuel cell and electrolyzer in the hydrogen industry. For the MEAs with very opaque coatings, optical transmission-based imaging has been developed and applied in the Roll-to-Roll system using a flashlight and a high-sensitivity CCD camera. We observed high signal-to-noise ratio images while the Roll-to-Roll system ran at 5 ft/min. The entire sample image could quickly be recovered from the discrete frames using customized Python codes for automatic frame cropping and stitching. We detected significant non-uniformities in our experimental MEAs specimen. For fuel cell and low-temperature electrolysis (LTE) transparent membranes, we used optical reflectance hyperspectral imaging with interference fringe-based thickness mapping. We set up a hyperspectral camera to measure various rolls of commercial membranes. The measurement results are analyzed to find the thickness distribution of each roll and to check for defects. Transmission and reflection imaging-based quality monitoring techniques demonstrated in this project can be widely used in the mass production environment to improve the production yield and performance of hydrogen devices.

DIRECT ENERGY CONVERSION,ENGINEERING↗
NASA NTRS2004

Imaging System For Measuring Macromolecule Crystal Growth Rates in Microgravity

In order to determine how macromolecule crystal quality improvement in microgravity is related to crystal growth characteristics, a team of scientists and engineers at NASA's Marshal Space Flight Center (MSFC) developed flight hardware capable of measuring the crystal growth rates of a population of crystals growing under the same conditions. As crystal growth rate is defined as the change or delta in a defined dimension or length (L) of crystal over time, the hardware was named Delta-L. Delta-L consists of three sub assemblies: a fluid unit including a temperature-controlled growth cell, an imaging unit, and a control unit (consisting of a Data Acquisition and Control Unit (DACU), and a thermal control unit). Delta-L will be used in connection with the Glovebox Integrated Microgravity Isolation Technology (g-LIMIT) inside the Microgravity Science Glovebox (MSG), onboard the International Space Station. This paper will describe the Delta-L imaging system. The Delta-L imaging system was designed to locate, resolve, and capture images of up to 10 individual crystals ranging in size from 10 to 500 microns with a point-to-point accuracy of +/- 2.0 microns within a quartz growth cell observation area of 20 mm x 10 mm x 1 mm. The optical imaging system is comprised of a video microscope camera mounted on computer controlled translation stages. The 3-axis translation stages and control units provide crewmembers the ability to search throughout the growth cell observation area for crystals forming in size of approximately 10 microns. Once the crewmember has selected ten crystals of interest, the growth of these crystals is tracked until the size reaches approximately 500 microns. In order to resolve these crystals an optical system with a magnification of 10X was designed. A black and white NTSC camera was utilized with a 20X microscope objective and a 0.5X custom designed relay lens with an inline light to meet the magnification requirement. The design allows a 500 pm crystal to be viewed in the vertical dimension on a standard NTSC monitor (4:3 aspect ratio). Images of the 10 crystals are collected periodically and stored in sets by the DACU.

Corder, Eric L.↗
NASA NTRS2007

Multispectral Imaging Broadens Cellular Analysis

Amnis Corporation, a Seattle-based biotechnology company, developed ImageStream to produce sensitive fluorescence images of cells in flow. The company responded to an SBIR solicitation from Ames Research Center, and proposed to evaluate several methods of extending the depth of field for its ImageStream system and implement the best as an upgrade to its commercial products. This would allow users to view whole cells at the same time, rather than just one section of each cell. Through Phase I and II SBIR contracts, Ames provided Amnis the funding the company needed to develop this extended functionality. For NASA, the resulting high-speed image flow cytometry process made its way into Medusa, a life-detection instrument built to collect, store, and analyze sample organisms from erupting hydrothermal vents, and has the potential to benefit space flight health monitoring. On the commercial end, Amnis has implemented the process in ImageStream, combining high-resolution microscopy and flow cytometry in a single instrument, giving researchers the power to conduct quantitative analyses of individual cells and cell populations at the same time, in the same experiment. ImageStream is also built for many other applications, including cell signaling and pathway analysis; classification and characterization of peripheral blood mononuclear cell populations; quantitative morphology; apoptosis (cell death) assays; gene expression analysis; analysis of cell conjugates; molecular distribution; and receptor mapping and distribution.

Source record↗
NASA NTRS2007

Tracking of cells with a compact microscope imaging system with intelligent controls

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to auto-focus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

McDowell, Mark↗
NASA NTRS2007

Tracking of Cells with a Compact Microscope Imaging System with Intelligent Controls

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously

McDowell, Mark↗
NASA NTRS2006

Identification Of Cells With A Compact Microscope Imaging System With Intelligent Controls

A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking mic?oscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to autofocus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.

McDowell, Mark↗
NASA NTRS1997

1,25 (OH)2D3 enhances PTH-induced Ca2+ transients in preosteoblasts by activating L-type Ca2+ channels

We previously demonstrated electrophysiologically that 1,25-dihydroxyvitamin D3 [1,25(OH)2D3] shifts the activation threshold of L-type Ca2+ channels in osteoblasts toward the resting potential and prolongs mean open time. Presently, we used single-cell Ca2+ imaging to study the combined effects of 1,25(OH)2D3 and parathyroid hormone (PTH) during generation of Ca2+ transients in fura 2-loaded MC3T3-E1 cells. Pretreatment with 1,25(OH)2D3 concentrations, which alone did not produce Ca2+ transients, consistently enhanced Ca2+ responses to PTH. Enhancement was dose dependent over the range of 1 to 10 nM and was blocked by pretreatment with 5 microM nitrendipine during pretreatment. A 1,25(OH)2D3 analog that activates L-type channels and shifts their activation threshold also enhanced PTH responses. In contrast, an analog devoid of membrane Ca2+ effects did not enhance PTH-induced Ca2+ transients. The PTH-induced Ca2+ transient involved activation of a dihydropyridine-insensitive cation channel that was inhibited by Gd3+. Together, these data suggest that 1,25(OH)2D3 increases osteoblast responsiveness to PTH through rapid modification of L-type Ca2+ channel gating properties, whose activation enhances Ca2+ entry through other channels such as the PTH-responsive, Gd(3+)-sensitive cation channel.

Non-NASA Center↗
NASA NTRS2009

Guaranteeing Failsafe Operation of Extended-Scene Shack-Hartmann Wavefront Sensor Algorithm

A Shack-Hartmann sensor (SHS) is an optical instrument consisting of a lenslet array and a camera. It is widely used for wavefront sensing in optical testing and astronomical adaptive optics. The camera is placed at the focal point of the lenslet array and points at a star or any other point source. The image captured is an array of spot images. When the wavefront error at the lenslet array changes, the position of each spot measurably shifts from its original position. Determining the shifts of the spot images from their reference points shows the extent of the wavefront error. An adaptive cross-correlation (ACC) algorithm has been developed to use scenes as well as point sources for wavefront error detection. Qualifying an extended scene image is often not an easy task due to changing conditions in scene content, illumination level, background, Poisson noise, read-out noise, dark current, sampling format, and field of view. The proposed new technique based on ACC algorithm analyzes the effects of these conditions on the performance of the ACC algorithm and determines the viability of an extended scene image. If it is viable, then it can be used for error correction; if it is not, the image fails and will not be further processed. By potentially testing for a wide variety of conditions, the algorithm s accuracy can be virtually guaranteed. In a typical application, the ACC algorithm finds image shifts of more than 500 Shack-Hartmann camera sub-images relative to a reference sub -image or cell when performing one wavefront sensing iteration. In the proposed new technique, a pair of test and reference cells is selected from the same frame, preferably from two well-separated locations. The test cell is shifted by an integer number of pixels, say, for example, from m= -5 to 5 along the x-direction by choosing a different area on the same sub-image, and the shifts are estimated using the ACC algorithm. The same is done in the y-direction. If the resulting shift estimate errors are less than a pre-determined threshold (e.g., 0.03 pixel), the image is accepted. Otherwise, it is rejected.

Sidick, Erikin↗
DOE OSTI2020

Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. Here we report a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Spatial‐Uniformity–Driven Bayesian Optimization for Rapid Development of Printed Perovskite Solar Cells

Printed metal halide perovskites can enable rapid, roll-to-roll manufacturing of a broad class of optoelectronics—flexible solar cells and imagers among them—while promising cost and speed advantages over incumbent silicon. However, though current methods offer high throughput and patterning capabilities, perovskite films’ spatial heterogeneity remains a challenge for large-area devices. Here, a spatial-uniformity-driven Bayesian optimization (BO) approach is leveraged to accelerate the development of printed perovskite solar cells and improve large-area device performance. Using a BO surrogate model, a 6D design space of ink chemistry and printing physics is explored via extensive iterative experimentation (≈100) informed by an objective function capturing spatial photoluminescence (PL) variance. It is discovered that optimizing for uniformity drives rapid advances in photovoltaic performance, yielding ≈20% power conversion efficiency (PCE) for small area (0.134 cm 2 ) devices and > 16% for large area (1 cm 2 ) devices. This machine-learning approach simultaneously enables rheological comparison of ink formulations that accelerate the leveling of Saffman-Taylor artifacts and improve film uniformity. Here, this showcases uniformity-driven BO as an efficient approach for uncovering the key printing physics and mitigating spatial heterogeneity to enable device scaling beyond small cell areas.

14 SOLAR ENERGY↗
DOE OSTI2023

Engineering and characterization of carbohydrate‐binding modules for imaging cellulose fibrils biosynthesis in plant protoplasts

Abstract Carbohydrate binding modules (CBMs) are noncatalytic domains that assist tethered catalytic domains in substrate targeting. CBMs have therefore been used to visualize distinct polysaccharides present in the cell wall of plant cells and tissues. However, most previous studies provide a qualitative analysis of CBM‐polysaccharide interactions, with limited characterization of engineered tandem CBM designs for recognizing polysaccharides like cellulose and limited application of CBM‐based probes to visualize cellulose fibrils synthesis in model plant protoplasts with regenerating cell walls. Here, we examine the dynamic interactions of engineered type‐A CBMs from families 3a and 64 with crystalline cellulose‐I and phosphoric acid swollen cellulose. We generated tandem CBM designs to determine various characteristic properties including binding reversibility toward cellulose‐I using equilibrium binding assays. To compute the adsorption ( nk on ) and desorption ( k off ) rate constants of single versus tandem CBM designs toward nanocrystalline cellulose, we employed dynamic kinetic binding assays using quartz crystal microbalance with dissipation. Our results indicate that tandem CBM3a exhibited the highest adsorption rate to cellulose and displayed reversible binding to both crystalline/amorphous cellulose, unlike other CBM designs, making tandem CBM3a better suited for live plant cell wall biosynthesis imaging applications. We used several engineered CBMs to visualize Arabidopsis thaliana protoplasts with regenerated cell walls using confocal laser scanning microscopy and wide‐field fluorescence microscopy. Lastly, we also demonstrated how CBMs as probe reagents can enable in situ visualization of cellulose fibrils during cell wall regeneration in Arabidopsis protoplasts.

09 BIOMASS FUELS↗
NASA NTRS2010

Improved Phased Array Imaging of a Model Jet

An advanced phased array system, OptiNav Array 48, and a new deconvolution algorithm, TIDY, have been used to make octave band images of supersonic and subsonic jet noise produced by the NASA Glenn Small Hot Jet Acoustic Rig (SHJAR). The results are much more detailed than previous jet noise images. Shock cell structures and the production of screech in an underexpanded supersonic jet are observed directly. Some trends are similar to observations using spherical and elliptic mirrors that partially informed the two-source model of jet noise, but the radial distribution of high frequency noise near the nozzle appears to differ from expectations of this model. The beamforming approach has been validated by agreement between the integrated image results and the conventional microphone data.

Dougherty, Robert P.↗