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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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Origin of Heterogeneous Stripping of Lithium in Liquid Electrolytes
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Li metal deposition and stripping in a solid-state battery via Coble creep
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Achieving controllable and reversible snap-through in pre-strained strips of liquid crystalline elastomers
Deformable, elastic materials that buckle in response to external stimuli can display “snap-through”, which involves a transition between different, stable buckled states.
Studying AC-LGAD strip sensors from laser and testbeam measurements
Here, this paper presents the setup assembled to characterize and measure the spatial and timing resolutions of AC-coupled Low Gain Avalanche Diodes (AC-LGADs), using a 1060 nm laser source to deposit initial charges with a defined calibration methodology. The results were compared to those obtained with a 120 GeV proton beam. Despite the differences in the charge deposition mechanism between the laser and proton beam, the spatial and temporal resolutions were found to be compatible between the two sources after calibration. With 4D tracking detectors expected to play a vital role in upcoming collider experiments, we foresee this work as a way to evaluate the performance of semiconductor sensors that can augment testbeam measurements and accelerate R&D efforts. Additionally, simulation studies using Silvaco TCAD and Weightfield2 were carried out to understand the various contributing factors to the total time resolution in AC-LGAD sensors, measured using the laser source.
Sequential excitation scheme for laser stripping for a H − beam
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Anodic Stripping Voltammetry Detection of Bismuth in Highly Alkaline Electrolyte for Battery Separator Testing.
Abstract not provided.
Anodic Stripping Voltammetry Detection of Bismuth Copper and Zinc and its Role in Evaluating Battery Separators.
Abstract not provided.
Applying Anodic Stripping Voltammetry to Complex Wastewater Streams for Rapid Metal Detection (Final Report)
The overall objective of this project is the development of a lab-on-a-chip (LOC) electrochemical sensor capable of accurately measuring heavy metal (lead (Pb), cadmium (Cd), and arsenic (As)) concentrations in complex aqueous streams such as wastewater. The specific goals include: i) identify how heavy metal speciate and transform during the different stages of the wastewater treatment train, and explore pre-treatment methods that will de-complex heavy metals, making them available to ASV, ii) develop appropriate electrodes for ASV using organic/inorganic nanomaterials, and iii) integrate pre-treatment steps and specialized electrodes into an LOC sensor device capable of autonomously determining heavy metal concentrations in complex wastewater streams.
Metal Ion Sensing and Quantification by Anodic Stripping Voltammetry (ASV)for Study of Alkaline Battery Separators.
Abstract not provided.
Far field boundary conditions for two dimensional magnetohydrodynamic strip line modeling
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Detection and characterization of rumble strips in roadway video logs
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Stripping off the implementation complexity of physics-based model predictive control for buildings via deep learning
Over the past decade, model predictive control (MPC) has been considered as the most promising solution for intelligent building operation. Despite extensive effort, transfer of this technology into practice is hampered by the need to obtain an accurate controller model with minimum effort, the need of expert knowledge to set it up, and the need of increased computational power and dedicated software to run it. A promising direction that tackles the last two problems was proposed by approximate explicit MPC where the optimal control policies are learned from MPC data via a suitable function approximator, e.g., a deep learning (DL) model. The main advantage of the proposed approach stems from simple evaluation at execution time leading to low computational footprints and easy deployment on embedded HW platforms. We present the energy savings potential of physics-based (also called 'white-box') MPC applied to an office building in Belgium. Moreover, we demonstrate how deep learning approximators can be used to cut the implementation and maintenance costs of MPC deployment without compromising performance. We also critically assess the presented approach by pointing out the major challenges and remaining open-research questions.
Evaluation of Stripping Resistance of Organoclay-Modified Asphalt Binder and Aggregate Systems Using an Optical Contact Angle Analyzer
Organoclays, often referred to as nanoclays (NCs), are organically modified phyllosilicates. They are derived from naturally occurring clay minerals and possess unique characteristics in improving the physical and mechanical properties of polymers and rubbers. Recently, NCs have drawn interest in the modification of asphalt binders as micro-scale fillers. A few recent studies have revealed that the addition of NCs in asphalt binders improved binders’ stiffness, aging characteristics, and fatigue resistance. This study aims to evaluate the changes in moisture resistance of different NC-modified asphalt binders through the surface free energy (SFE) technique. This technique estimates SFE properties of binders and aggregates from static contact angle (SCA) data measured from an optical contact angle analyzer (OCA). Further, this study examines the changes in chemical compositions (functional groups) of binders due to the addition of selected NCs by using the Fourier Transformation Infrared (FTIR) technique. To this end, a commonly used performance grade (PG) binder (PG 64-22) modified with four different types (shape and size) of NCs, namely, Cloisite® 15 (C-15), Cloisite® 20 (C-20), Cloisite® Na+ (C-Na), and Cloisite® Ca++ (C-Ca) were evaluated in this study. The SFE data of five different types of aggregates from Oklahoma, namely, Davis Limestone (DL), Snyder Granite (SG), Dolese-Cooperton Limestone (DCL), Hanson-Davis Rhyolite (HDR), and Martin-Marietta-Mill-Creek Granite (MMMG), were used to perform their compatibility with the aforementioned NC-modified binders. The FTIR spectra revealed the presence of various alcohols, ethers, and esters in NC-modified asphalt binders. The moisture susceptibility analysis shows that the addition of NC results in an increase of SFE and cohesive energy of an asphalt binder, which are desired for improved moisture resistance. The addition of NC also shows improved compatibility in cases of all aggregates. Among the five aggregates, MMMCG showed the highest compatibility with all binders, followed by DCL, HDR, DL, and SG. In regard to NCs, the C-15 sample showed the highest compatibility followed by C-20, C-Na, and C-Ca.
System and method for shingling wafer strips connected in parallel
A solar device includes a first string of first solar wafers, wherein a plurality of the first solar wafers each overlap with at least one vertically adjacent solar wafer from the first string. Additionally, the solar device includes a second string of second solar wafers, wherein a plurality of the second solar wafers each overlap with at least one vertically adjacent solar wafer from the second string, wherein a plurality of the first solar wafers overlap with one or more of the plurality of second solar wafers to electrically connect horizontally adjacent solar wafers in parallel.
System and method for shingling wafer strips connected in parallel
A solar device includes a first string of first solar wafers, wherein a plurality of the first solar wafers each overlap with at least one vertically adjacent solar wafer from the first string. Additionally, the solar device includes a second string of second solar wafers, wherein a plurality of the second solar wafers each overlap with at least one vertically adjacent solar wafer from the second string, wherein a plurality of the first solar wafers overlap with one or more of the plurality of second solar wafers to electrically connect horizontally adjacent solar wafers in parallel.