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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

“Development and application of analytical detection techniques for droplet-based microfluidics”-A review

Droplet-based microfluidics has emerged as a powerful platform for high-throughput and low-volume analysis and screening. At present, droplet-based microfluidics is transitioning from the proof-of-concept stage to real-world applications. During this process, analytical detection techniques play indispensable roles for successfully implementing droplet-based chemical or biological assays. Here, we provide an overview of recent developments in analytical techniques for droplet analysis and elucidate the advantages and limitations of each technique. We cover the majority of technology categories, including optical detection, electrical detection, mass spectrometry, and nuclear magnetic resonance spectroscopy. Additionally, we highlight new research areas that have been enabled by these technical advances. Finally, we provide perspectives on both future technological directions and potential enabling applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Assessment of Envelope- and Machine Learning-Based Electrical Fault Type Detection Algorithms for Electrical Distribution Grids

This study introduces envelope- and machine learning (ML)-based electrical fault type detection algorithms for electrical distribution grids, advancing beyond traditional logic-based methods. The proposed detection model involves three stages: anomaly area detection, ML-based fault presence detection, and ML-based fault type detection. Initially, an envelope-based detector identifying the anomaly region was improved to handle noisier power grid signals from meters. The second stage acts as a switch, detecting the presence of a fault among four classes: normal, motor, switching, and fault. Finally, if a fault is detected, the third stage identifies specific fault types. This study explored various feature extraction methods and evaluated different ML algorithms to maximize prediction accuracy. The performance of the proposed algorithms is tested in an emulated software–hardware electrical grid testbed using different sample rate meters/relays, such as SEL735, SEL421, SEL734, SEL700GT, and SEL351S near and far from an inverter-based photovoltaic array farm. The performance outcomes demonstrate the proposed model’s robustness and accuracy under realistic conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Electrical Fault Detection, Power Quality, Distributed Energy Resource Use Cases, and Cyber Event Applications with the Cyber Grid Guard System Using Distributed Ledger Technology

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation and are associated with distributed energy resources (DERs). The integrity and confidentiality of data from IEDs is crucial, and distributed ledger technology (DLT) could improve the resilience of microgrids by helping to make these data more secure. The most popular applications using blockchain technology for electrical utilities is in the field is based on energy trading. However, the dynamism of the penetration of customer owned DERs and the deployment of sensors with IEDs have led to the identification of new applications using DLT that are focused on other areas, such as monitoring, operation and management of the grid and its assets. In addition, the majority of studies on electrical grid applications with blockchain were validated with software simulations. Although general monitoring of power systems for using DLT could be evaluated in operational electric grids, other DLT research applications such as defense against cyber-attacks and/or electrical fault detection are not likely to be performed in a real infrastructure because of possible risks to the network/equipment security. This report summarizes the application of power system applications using distributed ledger technology (DLT), providing a secure DLT framework for collecting data from IEDs like power meters and protective relays inside and outside of an electrical substation and/or between two different electrical utilities. In this study, the use case scenarios were created and assessed for different power system application by using DLT. The electrical fault detection for faulted phases (1), power quality monitoring of phase voltage magnitudes, frequency levels and load power factor (2), DERs use case monitoring (3), and cyber-event applications (4) were performed in a test bed with a Cyber-Grid Guard (CGG) system using DLT. It had a real-time simulator with power meters and protective relays in-the-loop. The first section of this report presents a literature review of power system applications using blockchain at research level. The second section shows the theory and equations used on this report. The third section shows the description of the test bed, equipment, architecture, and electrical grid diagrams. The fourth section shows the experimental models and use case scenarios that were performed for the electrical fault detection, power quality, DERs use case, and cyber event applications with the CGG system using DLT. The fifth section shows the results collected from the tests based on comparing the time stamped events of the analog signals from the IEDs, DLT computer and real time simulator. The sixth section performed the discussion of the results for the use case scenarios. Finally, section seven presents the conclusions for this report were presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Electrical substation grid testbed for DLT applications of electrical fault detection, power quality monitoring, DERs use cases and cyber-events

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation, and are associated with customer-owned distributed energy resources (DERs). The integrity and confidentiality of data from these IEDs, like power meters and protective relays, is crucial. Blockchain technology could improve the resilience of microgrids by improving the security of data sharing. The penetration of customer-owned DERs (renewable energy sources) and the increasing deployment of IEDs can lead to integrate power system applications with Distributed Ledger Technology (DLT). In this study, we implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in-the-loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results had shown the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, the ESGT with DERs and the CGG system will be used in other power system applications, based on implementing smart contracts between electrical utilities with customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Data-Driven Probabilistic Anomaly Detection for Electricity Market under Cyber Attacks

Information and communication technologies have been widely used in smart grid for efficient operation. However, these technologies are vulnerable to malicious cyber attacks, which may lead to severe reliability and economic issues. Recently, a variety of data-driven anomaly detection approaches have been explored to detect potential cyber attacks in smart grids. In this paper, we researched on the electricity market data aiming to identify anomalies from the locational marginal prices (LMPs) and provide a new indicator for potential cyber attacks in power grids. Specifically, a novel data-driven probabilistic anomaly detection framework is proposed for electricity market, which consists of three major components: long short-term memory (LSTM) based deterministic electricity price forecasting, probabilistic electricity price forecasting and anomaly detection. This framework is tested on a model-based electricity market simulator under two types of cyber attacks, i.e., load redistribution attack (LRA) and price responsive attack (PRA). Numerical results on the simulated LMPs show that the proposed framework is capable of detecting data anomalies over these attacks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

AC electrical transport detection of magnetic properties of small, granular, and heterogeneous samples

Experimental constraints and sample limitations can preclude ideal measurements of electrical transport properties of materials. In such situations, AC electrical transport methods are often employed due to a significant increase in signal-to-noise ratio they can provide. However, dynamic effects that are not often accounted for may be present that may modify the signals in these measurements. In particular, dynamic filtering effects are prominent in small, granular, and heterogeneous materials. We demonstrate that a lock-in amplifier based circuit can distinguish between these DC transport and AC filtering effects. Here, we further demonstrate that this filtering can reveal distinct signatures of magnetic transitions while providing a measure of sample quality.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Atomic-scale defects generated in the early/intermediate stages of dielectric breakdown in Si/SiO 2 transistors

In this study, electrically detected magnetic resonance and near-zero-field magnetoresistance measurements were used to study atomic-scale traps generated during high-field gate stressing in Si/SiO 2 MOSFETs. The defects observed are almost certainly important to time-dependent dielectric breakdown. The measurements were made with spin-dependent recombination current involving defects at and near the Si/SiO 2 boundary. The interface traps observed are P b0 and P b1 centers, which are silicon dangling bond defects. The ratio of P b0 /P b1 is dependent on the gate stressing polarity. Electrically detected magnetic resonance measurements also reveal generation of E' oxide defects near the Si/SiO 2 interface. Near-zero-field magnetoresistance measurements made throughout stressing reveal that the local hyperfine environment of the interface traps changes with stressing time; these changes are almost certainly due to the redistribution of hydrogen near the interface.

42 ENGINEERING↗
DOE OSTI2020

Variability and origins of grain boundary electric potential detected by electron holography and atom-probe tomography

A number of grain boundary phenomena in ionic materials, in particular, anomalous (either depressed or enhanced) charge transport, have been attributed to space charge effects. Developing effective strategies to manipulate transport behaviour requires deep knowledge of the origins of the interfacial charge, as well as its variability within a polycrystalline sample with millions of unique grain boundaries. Electron holography is a powerful technique uniquely suited for studying the electric potential profile at individual grain boundaries, whereas atom-probe tomography provides access to the chemical identify of essentially every atom at individual grain boundaries. Using these two techniques, we show in this paper that the space charge potential at grain boundaries in lightly doped, high-purity ceria can vary by almost an order of magnitude. We further find that trace impurities (<25 ppm), rather than inherent thermodynamic factors, may be the ultimate source of grain boundary charge. These insights suggest chemical tunability of grain boundary transport properties. A number of grain boundary phenomena in ionic materials, such as anomalous charge transport, have been attributed to space charge effects. Space charge potential at grain boundaries in lightly doped, high-purity ceria is now shown to vary by almost an order of magnitude.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Damage Detection and Electrical Performance Impact of Flat-Flexible Circuits

Flat-flexible circuits or ‘flex circuits’ have varied applications in electronics and in explosive detonation systems. They pose advantages over conventional coaxial cables in their ability to fit into small mechanical envelopes and routings. A typical flex circuit is composed of a laminated assembly of multiple layers of conductor and dielectric materials. Copper, because of its high electrical conductivity, is one of the primary materials used in flex circuit conductors. The conductor must maintain structural integrity and electrical continuity when the flexible circuit is bent during processing or to fit an application envelope. Under some strain conditions a cable may have degraded electrical performance even though visible damage may not be evident. Dislocation density can increase by mechanisms such as dislocation forest hardening, where gliding dislocations in primary slip planes get pinned at obstacles and form Frank-Read sources. Dislocation density increases within the conductor layers may impact electrical resistivity but would not necessarily result in visible mechanical failure. In some detonation applications, such as for building implosion for demolition, the time for signal transmission and voltage used for firing detonators can be critical. If the resistance in a single flex cable within a building demolition array is too high, the resultant demolition shape may be asymmetric, leading to unplanned damage to nearby structures and potential hazards to public safety. This study will apply non-destructive evaluation techniques to evaluate the detectability of damage accumulation in flat, flexible copper-conductor cables and discuss potential implications to their practical use.

42 ENGINEERING↗