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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hierarchical median narrow band for level set segmentation of cervical cell nuclei

This paper presents a novel hierarchical nuclei segmentation algorithm for isolated and overlapping cervical cells based on a narrow band level set implementation. Our method applies a new multiscale analysis algorithm to estimate the number of clusters in each image region containing cells, which turns into the input to a narrow band level set algorithm. We assess the nuclei segmentation results on three public cervical cell image databases. Overall, our segmentation method outperformed six state-of-the-art methods concerning the number of correctly segmented nuclei and the Dice coefficient reached values equal to or higher than 0.90. We also carried out classification experiments using features extracted from our segmentation results and the proposed pipeline achieved the highest average accuracy values equal to 0.89 and 0.77 for two-class and three-class problems, respectively. Furthermore, these results demonstrated the suitability of the proposed segmentation algorithm to integrate decision support systems for cervical cell screening.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A Comparative Study of Compressive Effects on the Morphology and Performance of Carbon Paper and Cloth Electrodes in Redox Flow Batteries

Compressing porous carbon electrodes is a common approach to improve flow battery performance, but the resulting impact on electrode structure, fluid dynamics, and cell performance is not well understood. Herein, microtomographic imaging, load cell testing, and flow cell diagnostics are employed to characterize how compression‐induced changes impact pressure drop, polarization, and mass‐transfer scaling. Five different compressions are tested, spanning ranges typically used in literature, for AvCarb 1071 cloth (0%, 9%, 20%, 25%, 32%) and Freudenberg H23 paper (0%, 8%, 12%, 17%, 22%). It is found that the two electrode structures have distinct responses to compression, resulting in differing optimal conditions identified for each material; specifically, the Freudenberg H23 exhibits lower combined ohmic, charge‐transfer, and mass‐transport values at 8% compression, resulting in improved electrochemical performance across all compressive values, as compared to the optimal AvCarb 1071 compression (20%). Overall, Freudenberg H23 exhibits a greater sensitivity to compression with peak electrochemical activity correlating with increased permeability, whereas AvCarb 1071 is insensitive to compressive loads but produces lower electrochemical performance. Herein, the trade‐offs of mechanical robustness on fluid‐dynamic and electrochemical performance between the two electrodes are demonstrated by the aforementioned findings, suggesting each could be used for specific operating environments.

25 ENERGY STORAGE↗
DOE OSTI2021

Ambient Single-Cell Analysis and Native Tissue Imaging Using Laser-Ablation Electrospray Ionization Mass Spectrometry with Increased Spatial Resolution

Laser ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging method that has the potential to transform the field of metabolomics. This is in part due to LAESI-MS being an ambient ionization method that requires minimal sample preparation and uses (endogenous) water for in situ analysis. This application note details the employment of the ‘LAESI microscope’ source to perform spatially resolved MS analysis of cells and MS imaging (MSI) of tissues at high spatial resolution. This source configuration utilizes a long-working distance reflective objective that permits both visualization of the sample and a smaller LAESI laser beam profile than conventional LAESI setups. In this work, we analyzed 200 single cells of Allium cepa (red onion) and imaged Fittonia argyroneura (nerve plant) in high spatial resolution using this source coupled to a Fourier transform mass spectrometer for high mass resolution and high mass accuracy metabolomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Correlative single-cell hard X-ray computed tomography and X-ray fluorescence imaging

Abstract X-ray computed tomography (XCT) and X-ray fluorescence (XRF) imaging are two non-invasive imaging techniques to study cellular structures and chemical element distributions, respectively. However, correlative X-ray computed tomography and fluorescence imaging for the same cell have yet to be routinely realized due to challenges in sample preparation and X-ray radiation damage. Here we report an integrated experimental and computational workflow for achieving correlative multi-modality X-ray imaging of a single cell. The method consists of the preparation of radiation-resistant single-cell samples using live-cell imaging-assisted chemical fixation and freeze-drying procedures, targeting and labeling cells for correlative XCT and XRF measurement, and computational reconstruction of the correlative and multi-modality images. With XCT, cellular structures including the overall structure and intracellular organelles are visualized, while XRF imaging reveals the distribution of multiple chemical elements within the same cell. Our correlative method demonstrates the feasibility and broad applicability of using X-rays to understand cellular structures and the roles of chemical elements and related proteins in signaling and other biological processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Investigating Electric Field and Light Induced Degradation in Perovskite Solar Cells through Nanometer-Scale Potential Imaging

Electric field and light induced degradations in perovskite solar cells were evaluated through nanometer-scale potential imaging across the device by using in-situ Kelvin probe force microscopy (KPFM). We derived the electric field profile from potential profiles at different bias voltages to evaluate the locations and quality of junctions across the device. We found relative changes in electric field peak intensity at the HTL/perovskite and perovskite/ETL interfaces upon stressing devices separately under voltage or light. KPFM results during 12-hour stress/rest cycling under electrical bias show both reversible and irreversible changes in the device's interfacial fields. We also observed change in the electric field profile between control and degraded devices after 100 hours of stress/rest cycling under light. Our results demonstrate how nanometer-scale potential imaging can be used to understand the impacts of external electric fields and light soaking on both irreversible degradation and reversible metastability in perovskite solar cells.

Kelvin probe force microscopy↗
DOE OSTI2021

Super-resolution imaging illuminates new dynamic behaviors of cellulose synthase

Abstract Confocal imaging has shown that CELLULOSE SYNTHASE (CESA) particles move through the plasma membrane as they synthesize cellulose. However, the resolution limit of confocal microscopy circumscribes what can be discovered about these tiny biosynthetic machines. Here, we applied Structured Illumination Microscopy (SIM), which improves resolution two-fold over confocal or widefield imaging, to explore the dynamic behaviors of CESA particles in living plant cells. SIM imaging reveals that Arabidopsis thaliana CESA particles are more than twice as dense in the plasma membrane as previously estimated, helping explain the dense arrangement of cellulose observed in new wall layers. CESA particles tracked by SIM display minimal variation in velocity, suggesting coordinated control of CESA catalytic activity within single complexes and that CESA complexes might move steadily in tandem to generate larger cellulose fibrils or bundles. SIM data also reveal that CESA particles vary in their overlaps with microtubule tracks and can complete U-turns without changing speed. CESA track patterns can vary widely between neighboring cells of similar shape, implying that cellulose patterning is not the sole determinant of cellular growth anisotropy. Together, these findings highlight SIM as a powerful tool to advance CESA imaging beyond the resolution limit of conventional light microscopy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Data supporting manuscript from L. Sheneman, G. Stephanopoulos, A.E. Vasdekis titled "Deep learning classification of lipid droplets in quantitative phase images" as currently under review at PLOS ONE. This includes: 1) raw and binary labeled Quantitative Phase Images (QPI) of Y. lipolytica cells used in the analyses described within the manuscript. 2) various derived data including classifier scores, etc.

Data supporting manuscript from L. Sheneman, G. Stephanopoulos, A.E. Vasdekis titled "Deep learning classification of lipid droplets in quantitative phase images" as currently under review at PLOS ONE. This includes: 1) raw and binary labeled Quantitative Phase Images (QPI) of Y. lipolytica cells used in the analyses described within the manuscript. 2) various derived data including classifier scores, etc.

ANN↗
DOE OSTI2023

Reducing the matrix effect in mass spectral imaging of biofilms using flow-cell culture

The interactions between soil microorganisms and soil minerals play a crucial role in the formation and evolution of minerals and the stability of soil aggregates. Due to the heterogeneity and diversity of the soil environment, the under-standing of the functions of bacterial biofilms in soil minerals at the microscale is limited. A soil mineral-bacterial biofilm system was used as a model in this study, and it was analyzed by time-of-flight secondary ion mass spectrometry (ToF-SIMS) to acquire molecular level information. Static culture in multi-wells and dynamic flow-cell culture in microfluidics of biofilms were investigated. Our results show that more characteristic molecules of biofilms can be observed in SIMS spectra of the flow-cell culture. In contrast, biofilm signature peaks are buried under the mineral components in SIMS spectra in the static culture case. Spectral overlay was used in peak selection prior to performing Principal component analysis (PCA). Comparisons of the PCA results between the static and flow-cell culture show more pronounced molecular features and higher loadings of organic peaks of the dynamic cultured specimens. For example, fatty acids secreted from bacterial biofilm extracellular polymeric substance are likely to be responsible for biofilm dispersal due to mineral treatment up to 48 h. Such findings suggest that the use of microfluidic cells to dynamically culture biofilms be a more suitable method for reducing the matrix effect arisen from the growth medium and minerals as a perturbation fac-tor for improved spectral and multivariate analysis of complex mass spectral data in ToF-SIMS. These results show that the interaction mechanism between biofilms and soil minerals at the molecular level can be better studied using the flow-cell culture and advanced mass spectral imaging techniques like ToF-SIMS.

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

Investigation of Contact Properties and Device Performance for Bifacial Double-Side Textured Silicon Solar Cells With Polysilicon Based Passivating Contacts

We investigate the impact of the surface morphology on the contact properties of phosphorus doped poly-Si layers. If the poly-Si layer on a textured surface remains intact after high-temperature metallization using a fire-through (FT) silver (Ag) paste, the J0,metal is not expected to increase significantly while the specific contact resistivity can improve with a textured surface. The contact properties of the FT Ag contacts to n+ poly-Si deposited on both textured and planar surfaces are investigated by measuring and evaluating ρc and J0,metal. The reasons for differences in contact resistance and recombination are further investigated with SEM imaging. Solar cells with n-type polysilicon based passivating contacts on the rear side are fabricated and characterized. The scientific approach used, and the insights presented in this work, help to understand the mechanisms and behavior of screen-printed and fired-through contacts to polysilicon layers deposited onto textured silicon surfaces.

Padhamnath, Pradeep (ORCID:0000000202510624)↗
DOE OSTI2022

Near Infrared Emitting Semiconductor Polymer Dots for Bioimaging and Sensing

Semiconducting polymer dots (Pdots) are rapidly becoming one of the most studied nanoparticles in fluorescence bioimaging and sensing. Their small size, high brightness, and resistance to photobleaching make them one of the most attractive fluorophores for fluorescence imaging and sensing applications. This paper highlights our recent advances in fluorescence bioimaging and sensing with nanoscale luminescent Pdots, specifically the use of organic dyes as dopant molecules to modify the optical properties of Pdots to enable deep red and near infrared fluorescence bioimaging applications and to impart sensitivity of dye doped Pdots towards selected analytes. Building on our earlier work, we report the formation of secondary antibody-conjugated Pdots and provide Cryo-TEM evidence for their formation. We demonstrate the selective targeting of the antibody-conjugated Pdots to FLAG-tagged FLS2 membrane receptors in genetically engineered plant leaf cells. We also report the formation of a new class of luminescent Pdots with emission wavelengths of around 1000 nm. Finally, we demonstrate the formation and utility of oxygen sensing Pdots in aqueous media.

47 OTHER INSTRUMENTATION↗