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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Poly-Si Passivating Contacts Hydrogenation by Microwave Annealing

Hydrogenation is a crucial step in the fabrication of high-efficiency silicon solar cells. In this study, we demonstrate the for the first time effectiveness of hydrogen activation via microwave annealing of hydrogen-rich dielectrics coated on poly-Si passivating contacts. This method is compared with conventional hydrogenation techniques, such as annealing in N2 in the presence of a hydrogen-rich source (such as hydrogenated aluminum oxide (AlOx:H), hydrogenated silicon nitride (SiNy:H), or a AlOx:H/SiNy:H stack). Key improvements observed include a reduction in J0 from 30 to <5 fA/cm2, an increase in iVoc from 690 to >730 mV, and an enhancement in effective lifetime (teff) from 0.6 to ~3.5 milliseconds on phosphorus-doped poly-Si/SiO2 passivating contact samples. With a very short annealing time of ~1-2 minutes, the samples passivated by AlOx:H, SiNy:H, or the stack show similar performance to samples subjected to 30 minutes of nitrogen annealing. Photoluminescence (PL) spectra corroborate our findings regarding the hydrogenation of the poly-Si layer and the c-Si substrate, with an increase in PL intensity after microwave annealing. Ultimately, our work suggests that microwave annealing could be a promising addition, offering flexibility to traditional firing hydrogenation processes.

14 SOLAR ENERGY↗
DOE OSTI2024

Stacked membrane bioreactor

Scalable biomaterial-based bioreactors are described. In one embodiment, the bioreactor may comprise perforated plates stacked such that the assembled bioreactor has the necessary manifolds and chambers to transport gas and liquids to a biomaterial contained within the bioreactor, and to remove the reaction products. In another embodiment, single use bioreactors are described. Methods of operating the bioreactors are also described.

Abdullah, Zia↗
DOE OSTI2022

Paw-Net: Stacking ensemble deep learning for segmenting scanning electron microscopy images of fine-grained shale samples

Segmentation of scanning electron microscopy (SEM) images is critical yet time-consuming for geological analyses, as it needs to differentiate the boundaries for different mineral objects to facilitate subsequent analyses, such as porosity calculation. Recently, various machine learning methods, especially convolutional neural networks (CNNs), have been explored to segment SEM images of fine-grained shale samples. However, we found that general CNNs do not yield optimal performance due to insufficient training data and imbalanced objects in SEM images. This work has revised the U-Net architecture, a popular approach for biomedical image analyses, by incorporating a loss function that addresses the imbalance issue. Furthermore, we used the ensemble learning method to train multiple models and combined the results to improve the overall performance of segmentation. We prepared 2162 sub-images from raw SEM images in our experiments and divided them into training, validation, and testing datasets. The overall results show that our method improves the average Intersection over Union (IOU) of mineral objects from 0.49 to 0.58, compared to the original U-Net model. Our method can clearly distinguish each object from others with boundaries, even in highly imbalanced images. Training our models takes less than three minutes using a single GPU, while manual labeling can take up to three hours for each image. Furthermore, the method helps geoscientists gain insights quickly and effectively by building neural network models from a small dataset of SEM images.

58 GEOSCIENCES↗
DOE OSTI2025

Degradation of Fuel Cell Membrane Electrode Assemblies from Buses Operated More than 25,000 h

This study investigates the performance losses and degradation of proton-exchange-membrane fuel-cell stacks taken from the Alameda Contra Costa Transit District (AC Transit) bus system (Alameda and Contra Costa counties, California, United States) that were operated for over 25,000 h. Here, we focus on the origin of differences in electrochemical performance between beginning-of-life (BOL) and end-of-life states as well as diagnostic data acquired during the lifetime of the buses. In doing so, we employ in- and ex- situ characterization methods such as polarization curves, electrochemical impedance spectroscopy, electron microscopy, and X-ray characterization. Uniform degradation of the catalyst layer including Pt agglomeration/migration and electrode thinning was observed in all of the post-teardown measurements compared to BOL materials resulting from years of field operation. Despite these changes, the measured post-teardown performance suggests a sufficient output for the expected load, which indicate factors other than degradation of the membrane-electrode assemblies (MEAs) are likely responsible for the decommissioning of the stacks. The findings indicate that these MEA materials can enable long lifetime in fuel-cell vehicles, if the MEAs are not subjected to adverse operating conditions. The results also highlight the need for more in-vehicle diagnostics to maximize the lifetime of fuel cell vehicle (FCV) powerplants.

25 ENERGY STORAGE↗
DOE OSTI2021

Compact spectroscopy of keV to MeV X-rays from a laser wakefield accelerator

We reconstruct spectra of secondary X-rays from a tunable 250–350 MeV laser wakefield electron accelerator from single-shot X-ray depth-energy measurements in a compact (7.5 × 7.5 × 15 cm), modular X-ray calorimeter made of alternating layers of absorbing materials and imaging plates. X-rays range from few-keV betatron to few-MeV inverse Compton to > 100 MeV bremsstrahlung emission, and are characterized both individually and in mixtures. Geant4 simulations of energy deposition of single-energy X-rays in the stack generate an energy-vs-depth response matrix for a given stack configuration. An iterative reconstruction algorithm based on analytic models of betatron, inverse Compton and bremsstrahlung photon energy distributions then unfolds X-ray spectra, typically within a minute. We discuss uncertainties, limitations and extensions of both measurement and reconstruction methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma

Abstract Background Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managing patients. Objectives To determine if artificial intelligence and machine learning might help to stratify patients with cSCC by risk using more than solely clinical and histopathological factors. Methods We retrieved a retrospective cohort of 104 patients whose cSCCs had been excised with clear margins. Clinical and histopathological risk factors were evaluated. Haematoxylin and eosin-stained slides were scanned and analysed by an algorithm based on the stacked predictive sparse decomposition technique. Cellular morphometric biomarkers (CMBs) were identified via machine learning and used to derive a cellular morphometric risk score (CMRS) that classified cSCCs into clusters of differential prognoses. Concordance analysis, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated and compared with results obtained with the Brigham and Women’s Hospital (BWH) staging system. The performance of the combination of the BWH staging system and the CMBs was also analysed. Results There were no differences among the CMRS groups in terms of clinical and histopathological risk factors and T-stage assignment, but there were significant differences in prognosis. Combining the CMRS with BWH staging systems increased distinctiveness and improved prognostic performance. C-indices were 0.91 local recurrence and 0.91 for nodal metastasis when combining the two approaches. The NPV was 94.41% and 96.00%, the PPV was 36.36% and 41.67%, and accuracy reached 86.75% and 89.16%, respectively, with the combined approach. Conclusions CMRS is helpful for cSCC risk stratification beyond classic clinical and histopathological risk features. Combining the information from the CMRS and the BWH staging system offers outstanding prognostic performance for patients with high-risk cSCC.

Pérez-Baena, Manuel J.↗
DOE OSTI2020

Effect of Natural Fermentation of Sorghum on Resistant Starch Molecular Structure and Fermentation Property

Relevant research results have suggested that fermentation can increase the content of sorghum amylose chains and their retrogradation value. Therefore, this study explored the effect of fermentation pretreatment on the yield, digestibility, molecular structure, and in vitro fermentation property of sorghum-resistant starch by conducting fermentation pretreatment of sorghum and extracting the resistant starch from fermented sorghum with pressure-heat compound enzyme method. The results were as follows. After fermentation pretreatment, the yield of sorghum-resistant starch increased, the digestibility of sorghum-resistant starch reduced, the laminated structure size on the surface of the particles became more uniform, and the stacking mode became more neat and denser. The sorghum-resistant starch prepared before and after fermentation did not produce new chemical groups, and its functional group peak remained unchanged. After fermentation, the weight-average molecular weight of sorghum-resistant starch was elevated, and the percentage content of high- and low-molecular substances increased and decreased, respectively, compared with that of the unfermented sorghum-resistant starch. The percentage content of short-chain branches in the branched chain increased, whereas that of the long-chain branches decreased; the crystallinity of sorghum-resistant starch after fermentation decreased, and the intensity of X-diffraction peak changed slightly before and after fermentation. According to the results of the in vitro fermentation experiments, the fermentation broth of sorghum-resistant starch had the highest content of butyric acid and short-chain fatty acid. Research results reveal that, after fermentation pretreatment, sorghum-resistant starch presented increased yield, more complex molecular structure, heavier molecular weight and more uniform surface morphology, more efficient butyric acid generation, and greater fermentation rate than unfermented sorghum-resistant starch.

Ge, YunFei↗
DOE OSTI2020

Parametric study of optical transmission through plasmonic hole arrays modulated by the phase transition of vanadium dioxide

We have performed comprehensive electromagnetic simulations and preliminary experiments to explore the effects of geometrical and material parameters on the extraordinary optical transmission (EOT) through periodic arrays of subwavelength holes in a bilayer stack consisting of a gold or silver film atop a vanadium dioxide film (Au/Ag + VO 2 ), where the latter undergoes a semiconductor-to-metal phase transition. Using the finite-difference time-domain (FDTD) and finite-element methods (FEM), we vary iteratively the array periodicity, VO 2 film thickness and hole diameters, as well as the refractive index inside the VO 2 -layer holes and the VO 2 optical constants. For each variation, we compare the metallic-to-semiconducting ratios of the zero-order transmission ( T 00 ) peaks and find sharp maxima in these ratios within narrow parameter ranges. The maxima arise from Fabry-Perot and Fano-type resonances that minimize T 00 in the semiconducting phase of the perforated bilayers. At a fixed array period, the primary factors controlling the VO 2 -enabled EOT modulation are the VO 2 thickness, diameter of the VO 2 -layer holes, and absorption in the two VO 2 phases. Besides uncovering the origins of the higher metallic-phase T 00 , this study provides a protocol for optimizing the performance of the bilayer hole arrays for potential uses as dynamically tunable nano-optical devices.

Donev, Eugenii U. (ORCID:000000030555219X)↗
DOE OSTI2026

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Towards stacking fault energy engineering in FCC high entropy alloys

Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many years as a key intrinsic mechanical property, its inference via experimental observations or prediction using, for example, computationally intensive first-principles methods is challenging. This difficulty precludes the explicit use of SFE as an alloy design parameter. In this work, we combine DFT calculations (with necessary configurational averaging), machine-learning (ML) and physics-based models to predict the SFE in the fcc CoCrFeMnNiV-Al high-entropy alloy space. The best-performing ML model is capable of accurately predicting the SFE of arbitrary compositions within this 7-element system. Finally, this efficient model along with a recently developed model to estimate intrinsic strength of fcc HEAs is used to explore the strength–SFE Pareto front, predicting new-candidate alloys with particularly interesting mechanical behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Extended Finite Element Based Approach in Additive Manufacturing Modeling for Optimizing Highly Complex Manifold in Protonic Ceramic Electrochemical Cells

The objective of this project is to develop a novel numerical approach based on the extended finite element method (XFEM) for modeling moving boundaries of material deposited in additive manufacturing (AM) process with improved accuracy and reduced computational cost. One of the major challenges in simulating AM processes is that the boundaries of the computational domain need to change as material is deposited. Previous approaches have achieved this by activating new finite elements, but this requires a high level of mesh refinement to capture small movement of the boundary. XFEM allows the solution boundary to move independently of the mesh, permitting smooth representation of the evolution of the boundary as material is deposited. As a result, this new method will significantly improve the simulation accuracy while reducing the computational cost compared with existing approaches. Furthermore, this project will bring significant improvements for the design and AM process optimization in an iterative fashion among numerical simuation, parameter optimization, and experimental validation. Specifically, this project will support the protonic ceramic electrochemical cells (PCEC) stack development at INL by providing insights into the density, residual stress, thermal and mechanical properties of the PCEC manifold and interconnect, which is critical in enhancing the system lifetime and reducing the overall cost. Upon the success of proposed development and validation of the proposed approach, simulation will be applied to determine an optimal set of AM process parameters for the PCEC manifold production. This project will consolidate Idaho National Laboratory (INL)’s simulation capabilities provided by the MOOSE framework and the Valhalla AM simulation application, with encouraging expansion to emerging PCEC applications and AM technologies at INL and beyond.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Co-design for Particle Applications at Exascale

Co-design across the Exascale Computing Project (ECP) has been critical for both enabling science applications and bringing disparate communities together. Developing and porting applications to the various high-performance computing (HPC) architectures on pre-exascale and exascale computers has been quite challenging due to the diversity of hardware features and software stacks. The Co-design Center for Particle Applications (CoPA) has developed and enhanced the Cabana and PROGRESS/BML libraries to facilitate the creation of new particle applications, make existing particle applications exascale capable, and allow teams to explore new capabilities. Particle methods from atomistic, mesoscale, continuum, through cosmological scales have been built with Cabana, along with new possibilities for application coupling. Similarly, the PROGRESS/BML library has enabled quantum particle applications with linear algebra solvers to use advanced hardware. Across these CoPA-developed libraries, the co-design abstraction layer combines performance portability with math library support to facilitate separation of concerns and directly support science runs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Cross-Cutting Metrology Tools for In Operando Characterization of Carrier Dynamics in Photovoltaic Devices (Final Technical Report)

Understanding the nature of recombination and its dependence on defects and interfaces is essential for engineering materials and contacts for higher V oc and photovoltaic (PV) efficiency. Time-resolved photoluminescence (TRPL) has conventionally been used to evaluate recombination, but not all materials are strongly emissive or otherwise suitable. Time-resolved terahertz spectroscopy is a pump – probe method that presents valuable complementary information, wherein an optical pump pulse photoexcites carriers within the absorber and the transient photoconductivity is probed with a terahertz pulse. Until now, experimental constraints have prohibited the use of terahertz probes to interrogate full device stacks, and measurements were instead made on exfoliated films or films grown on unconventional substrates. However, interfaces are critical to the behavior of photoexcited carriers in solar cells, and the substrates themselves often influence the film growth and bulk properties. Therefore, it is important to probe the behavior of PV absorbers as close as possible to their normal operating conditions. Here we have developed cross-cutting metrology that enable in operando characterization of carrier dynamics and recombination mechanisms in working PV devices. Through a combination of complementary non-contact TRTS and TRPL experiments and modeling, we have obtained key parameters including photoexcited carrier bulk lifetime and interface and back surface recombination velocities with greater precision and accuracy than can be achieved with conventional TRPL alone. By varying pulsed photoexcitation conditions, the contributions of interface and bulk recombination mechanisms can be determined. We have developed and refined this characterization approach by investigating CdTe PVs, which is a well-established technology but with significant margin for further improvements in efficiency. Results were published in Journal of Applied Physics (DOI: 10.1063/5.0064730) and Proceedings of the IEEE PVSC (DOI: 10.1109/PVSC43889.2021.9518559). After validating the approach, we have applied it to correlate recombination rates to processing conditions and material properties, including composition and defects as well as interfaces and surface treatments. Such feedback can inform processing and design choices to enable higher PV efficiency, not only for CdTe, but also CdSe x Te 1-x , CIGS, perovskites, kesterites, and future technologies. A perspective on predicting solar cell performance from terahertz spectroscopy was published in Advanced Energy Materials (DOI: 10.1002/aenm.202102776). The cross-cutting metrology tools developed here will enable determination of the locus and mechanism of performance-limiting recombination in thin film PV devices. This feedback can guide the engineering of PV devices with higher V oc and efficiency, thereby leading to reductions in levelized cost of electricity to meet the SunShot 2030 target of $0.03/kWh for utility-scale PV. Lower costs will enable rapid expansion of renewable electricity generation that is nearly free of carbon emissions. Reducing carbon emissions of the electricity sector is one of the most important solutions to climate change. The project’s specific focus on CdTe PV can benefit First Solar, the US company that is the global leader in CdTe technology, through both technology and workforce development.

14 SOLAR ENERGY↗
DOE OSTI2021

Investigation of HTS Twisted Stacked-Tape Cable (TSTC) Conductor for High-Field, High-Current Fusion Magnets

The critical currents of a twisted single-tape were measured at 4.2 K in fields up to 17 T. It was confirmed that the critical current of a twisted-tape was similar to that of a flat tape in c-axis fields. Based on the single-tape critical-currents, a 40-tape (4-mm width) twisted stacked-tape cable (TSTC) conductor was experimentally evaluated at fields up to 17 T at 4.2 K. It was found that the Lorentz load degradation of the TSTC conductor was negligible at the end of a cyclic test. The TSTC cabling method has been considered to be suitable for developing a high-field high-current REBCO conductor for magnet applications as well as power transmission cables. A method to fabricate the inner legs of a D-shape toroidal field coil using a TSTC conductor has been discussed. This method allows the conductor to properly resist the transverse Lorentz load and mitigate ac loss issues by adopting a parallel-HTS-tape flat cable configuration where necessary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Conductive Metallophthalocyanine Framework Films with High Carrier Mobility as Efficient Chemiresistors

Abstract The poor electrical conductivity of two‐dimensional (2D) crystalline frameworks greatly limits their utilization in optoelectronics and sensor technology. Herein, we describe a conductive metallophthalocyanine‐based NiPc‐CoTAA framework with cobalt(II) tetraaza[14]annulene linkages. The high conjugation across the whole network combined with densely stacked metallophthalocyanine units endows this material with high electrical conductivity, which can be greatly enhanced by doping with iodine. The NiPc‐CoTAA framework was also fabricated as thin films with different thicknesses from 100 to 1000 nm by the steam‐assisted conversion method. These films enabled the detection of low‐concentration gases and exhibited remarkable sensitivity and stability. This study indicates the enormous potential of metallophthalocyanine‐based conductive frameworks in advanced stand‐off chemical sensors and provides a general strategy through tailor‐make molecular design to develop sensitive and stable chemical sensors for the detection of low‐concentration gases.

Yue, Yan↗
DOE OSTI2021

Conductive Metallophthalocyanine Framework Films with High Carrier Mobility as Efficient Chemiresistors

Abstract The poor electrical conductivity of two‐dimensional (2D) crystalline frameworks greatly limits their utilization in optoelectronics and sensor technology. Herein, we describe a conductive metallophthalocyanine‐based NiPc‐CoTAA framework with cobalt(II) tetraaza[14]annulene linkages. The high conjugation across the whole network combined with densely stacked metallophthalocyanine units endows this material with high electrical conductivity, which can be greatly enhanced by doping with iodine. The NiPc‐CoTAA framework was also fabricated as thin films with different thicknesses from 100 to 1000 nm by the steam‐assisted conversion method. These films enabled the detection of low‐concentration gases and exhibited remarkable sensitivity and stability. This study indicates the enormous potential of metallophthalocyanine‐based conductive frameworks in advanced stand‐off chemical sensors and provides a general strategy through tailor‐make molecular design to develop sensitive and stable chemical sensors for the detection of low‐concentration gases.

Yue, Yan↗
DOE OSTI2020

Fluorination and reduction of CaCrO 3 by topochemical methods

Topochemical reactions between CaCrO 3 and polyvinylidene difluoride yield the new fluorinated phase CaCrO 2.5 F 0.5 , which was characterized by powder synchrotron X-ray diffraction, X-ray photoemission spectroscopy, and magnetic susceptibility measurements. The reaction proceeds via reduced oxide intermediates, CaCrO 2.67 and CaCrO 2.5 , in which CrO 6 octahedral and CrO 4 tetrahedral layers are stacked in a different manner along the c axis of CaCrO 3 . These two intermediate phases can be selectively synthesized by the carbothermal reduction with g-C 3 N 4. Both CaCrO 3 and CaCrO 2.5 F 0.5 adopt the same orthorhombic space group, Pbnm ; however, the fluorinated phase has decreased Cr–O–Cr bond angles as compared to the parent compound in both the ab plane and along the c -direction, which indicates an increased orthorhombic distortion due to the fluorination. Overall, while the oxygen vacancies are ordered in both intermediate phases, CaCrO 2.67 and CaCrO 2.5 , a site preference for fluorine in the oxyfluoride phase cannot be confirmed. CaCrO 3 and CaCrO 2.5 F 0.5 undergo antiferromagnetic phase transitions involving spin canting, where the fluorination causes the transition temperature to increase from 90 K to 110 K, as a result of the competition between the increased octahedral tilting and the enhancement of superexchange interactions involving Cr 3+ ions in the CaCrO 2.5 F 0.5 structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗