A hierarchical, nanoporous TiO2 structure is successfully prepared by a simple in situ hydrolysis method. Used as an anode material, it achieves a sustained high lithium storage performance ...especially at high charge/discharge rates due to its substantially high surface area. The material shows two different major storage modes: a) bulk insertion, and b) pseudo‐capacitive interfacial storage, which is responsible for 64% of the total capacity. In order to kinetically emphasize the interfacial storage even further, we cycle the material directly at high rates, giving 302 mA h g−1 and 200 mA h g−1 of fully reversible discharge capacity at charge/discharge rates of 1 C and 5 C with very high cycle stability. We propose an overall view on the different Li insertion mechanisms of the high‐surface‐area nanoporous TiO2 and emphasize the importance of interfacial storage for electrode applications in Li‐ion batteries.
A hierarchical, nanoporous TiO2 (anatase) with substantially high surface area achieves fully reversible discharge capacities as high as 302 mA h g−1 and 200 mA h g−1 at charge/discharge rates of 1 C and 5 C, respectively. The remarkably improved electrode performance is explained in conjunction with the importance of the interfacial (surface) storage mechanism.
Human gait is a unique behavioral characteristic that can be used to recognize individuals. Collecting gait information widely by the means of wearable devices and recognizing people by the data has ...become a topic of research. While most prior studies collected gait information using inertial measurement units, we gather the data from 40 people using insoles, including pressure sensors, and precisely identify the gait phases from the long time series using the pressure data. In terms of recognizing people, there have been a few recent studies on neural network-based approaches for solving the open set gait recognition problem using wearable devices. Typically, these approaches determine decision boundaries in the latent space with a limited number of samples. Motivated by the fact that such methods are sensitive to the values of hyper-parameters, as our first contribution, we propose a new network model that is less sensitive to changes in the values using a new prototyping encoder-decoder network architecture. As our second contribution, to overcome the inherent limitations due to the lack of transparency and interpretability of neural networks, we propose a new module that enables us to analyze which part of the input is relevant to the overall recognition performance using explainable tools such as sensitivity analysis (SA) and layer-wise relevance propagation (LRP).
A new high-impedance fault (HIF) detection method using time-frequency analysis for feature extraction is proposed. A pattern classifier is trained whose feature set consists of current waveform ...energy and normalized joint time-frequency moments. The proposed method shows high efficacy in all of the detection criteria defined in this paper. The method is verified using real-world data, acquired from HIF tests on three different materials (concrete, grass, and tree branch) and under two different conditions (wet and dry). Several nonfault events, which often confuse HIF detection systems, were simulated, such as capacitor switching, transformer inrush current, nonlinear loads, and power-electronics sources. A new set of criteria for fault detection is proposed. Using these criteria, the proposed method is evaluated and its performance is compared with the existing methods. These criteria are accuracy, dependability, security, safety, sensibility, cost, objectivity, completeness, and speed. The proposed method is compared with the existing methods, and it is shown to be more reliable and efficient than its existing counterparts. The effect of choice of the pattern classifier on method efficacy is also investigated.
In this paper, we review the state of the art in the detection, location, and diagnosis of faults in electrical wiring interconnection systems (EWIS) including in the electric power grid and vehicles ...and machines. Most electrical test methods rely on measurements of either currents and voltages or on high frequency reflections from impedance discontinuities. Of these high frequency test methods, we review phasor, travelling wave and reflectometry methods. The reflectometry methods summarized include time domain reflectometry (TDR), sequence time domain reflectometry (STDR), spread spectrum time domain reflectometry (SSTDR), orthogonal multi-tone reflectometry (OMTDR), noise domain reflectometry (NDR), chaos time domain reflectometry (CTDR), binary time domain reflectometry (BTDR), frequency domain reflectometry (FDR), multicarrier reflectometry (MCR), and time-frequency domain reflectometry (TFDR). All of these reflectometry methods result in complex data sets (reflectometry signatures) that are the result of reflections in the time/frequency/spatial domains. Automated analysis techniques are needed to detect, locate, and diagnose the fault including genetic algorithm (GA), neural networks (NN), particle swarm optimization, teaching-learning-based optimization, backtracking search optimization, inverse scattering, and iterative approaches. We summarize several of these methods including electromagnetic time-reversal (TR) and the matched-pulse (MP) approach. We also discuss the issue of soft faults (small impedance changes) and methods to augment their signatures, and the challenges of branched networks. We also suggest directions for future research and development.
Aside from graph neural networks (GNNs) attracting significant attention as a powerful framework revolutionizing graph representation learning, there has been an increasing demand for explaining GNN ...models. Although various explanation methods for GNNs have been developed, most studies have focused on instance-level explanations, which produce explanations tailored to a given graph instance. In our study, we propose Prototype-bAsed GNN-Explainer ( <inline-formula><tex-math>{\sf PAGE}</tex-math></inline-formula> ) , a novel model-level GNN explanation method that explains what the underlying GNN model has learned for graph classification by discovering human-interpretable prototype graphs . Our method produces explanations for a given class , thus being capable of offering more concise and comprehensive explanations than those of instance-level explanations. First, <inline-formula><tex-math>{\sf PAGE}</tex-math></inline-formula> selects embeddings of class-discriminative input graphs on the graph-level embedding space after clustering them. Then, <inline-formula><tex-math>{\sf PAGE}</tex-math></inline-formula> discovers a common subgraph pattern by iteratively searching for high matching node tuples using node-level embeddings via a prototype scoring function, thereby yielding a prototype graph as our explanation. Using six graph classification datasets, we demonstrate that <inline-formula><tex-math>{\sf PAGE}</tex-math></inline-formula> qualitatively and quantitatively outperforms the state-of-the-art model-level explanation method. We also carry out ystematic experimental studies by demonstrating the relationship between <inline-formula><tex-math>{\sf PAGE}</tex-math></inline-formula> and instance-level explanation methods, the robustness of <inline-formula><tex-math>{\sf PAGE}</tex-math></inline-formula> to input data scarce environments, and the computational efficiency of the proposed prototype scoring function in <inline-formula><tex-math>{\sf PAGE}</tex-math></inline-formula>.
Owing to the increasing complexity of electrical systems, diagnostic techniques of cables used for connecting electrical elements are essential for system maintenance in order to prevent a failure ...that can cause significant impacts on the overall electrical systems. Multicore structures are typically used as control and instrumentation cables in nuclear power plants, and the failure of the control and instrumentation cables can result in a disaster such as a radiation leak. In this paper, a method for the diagnosis of multicore cables is proposed based on the reflectometry. The diagnosis relates to the classification of defective cores in joint, which is one of the weakest parts in cable systems. The reflected signals obtained through reflectometry are converted into images by an advanced image processing algorithm, and the images are classified using artificial neural networks. The proposed method is demonstrated by experimental data using a real-world multicore cable. In the experiment, the faults are emulated similar to real-world defects using a potentiometer. It is expected that the proposed technique will enhance the stability and reliability of multicore cable systems.
This paper presents a technique for the estimation of oscillation parameters via state-space modeling of synchrophasor data. Due to the spectral leakage of synchrophasors estimated by a Fourier ...transform-based algorithm, the oscillation parameters such as magnitude and frequency will be inherently distorted. Therefore, a state-space model of the instantaneous waveform signal under power system oscillation is derived as an exponentially damped sinusoidal (EDS) signal in order to account for the spectral leakage. The oscillation frequency and magnitude are estimated in real-time by using an unscented Kalman filter (UKF) based on the state-space model. The estimation accuracy performance is validated using the simulation data of sub-synchronous oscillation (SSO). In addition, the efficacy of the proposed method's performance is verified by the application of the proposed method to real-world oscillation events in a wind farm and comparison with the time-frequency analysis.
Flow-electrode capacitive deionization (FCDI) is a new electrochemical-based desalination technology that addresses the limitations of preceding CDI processes through the use of a stationary carbon ...electrode and ion-exchange membrane. As with conventional CDI configurations, non-Faradaic reactions (i.e., ion electrosorption) of the electric double layer model is the principal ion separation mechanism of FCDI. This technology also offers the unique ability for continuous ion/salt separation by circumventing constraints with electrode saturation. This paper reviews recent advances in FCDI, discusses the feasibility and applicability of this technique, and suggests potential niche applications for saline water/wastewater treatment and resource recovery. Additionally, it also critically discusses factors that deteriorate FCDI performance, operating conditions, process energy efficiency, and optimization of the electrode, electrolyte, and cell design. The insights from this review will shed light on directions for future FCDI research and inform the implementation of FCDI technology.
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•Comprehensive review of recent advances in flow-electrode capacitive deionization (FCDI)•FCDI process optimization to improve desalination efficiency•Critical energy analysis in comparison with existing desalination technologies•FCDI in desalination, softening, nutrient recovery, and toxic metal removal•Future research directions for expanding practical application of FCDI
A newly synthesized high‐k polymeric insulator for use as gate dielectric layer for organic field‐effect transistors (OFETs) obtained by grafting poly(methyl methacrylate) (PMMA) in poly(vinylidene ...fluoride‐trifluoroethylene) (P(VDF‐TrFE)) via atom transfer radical polymerization transfer is reported. This material design concept intents to tune the electrical properties of the gate insulating layer (capacitance, leakage current, breakdown voltage, and operational stability) of the high‐k fluorinated polymer dielectric without a large increase in operating voltage by incorporating an amorphous PMMA as an insulator. By controlling the grafted PMMA percentage, an optimized P(VDF‐TrFE)‐g‐PMMA with 7 mol% grafted PMMA showing reasonably high capacitance (23–30 nF cm−2) with low voltage operation and negligible current hysteresis is achieved. High‐performance low‐voltage‐operated top‐gate/bottom‐contact OFETs with widely used high mobility polymer semiconductors, poly2,5‐bis(2‐octyldodecyl)‐2,3,5,6‐tetrahydro‐3,6‐dioxopyrrolo 3,4‐cpyrrole‐1,4‐diyl‐alt‐2,2′‐(2,5‐thiophene)bis‐thieno(3,2‐b)thiophene‐5,5′‐diyl (DPPT‐TT), and poly(N,N′‐bis(2‐octyldodecyl)‐naphthalene‐1,4,5,8‐bis(dicarboximide)‐2,6‐diyl‐alt‐5,5′‐(2,2′‐bithiophene)) are demonstrated here. DPPT‐TT OFETs with P(VDF‐TrFE)‐g‐PMMA gate dielectrics exhibit a reasonably high field‐effect mobility of over 1 cm2 V−1 s−1 with excellent operational stability.
A high‐k polymeric insulator is developed by chemically grafting poly(methylmethacrylate) (PMMA) to poly(vinylidenefluoride‐trifluoroethylene) (P(VDF‐TrFE)) for use as a gate dielectric layer in organic field‐effect transistors (OFETs). A device with an optimized P(VDF‐TrFE)‐g‐PMMA ratio (7% grafted ratio) shows a high capacitance of 23‐30 nF cm−2. Poly2,5‐bis(2‐octyldodecyl)‐2,3,5,6‐tetrahydro‐3,6‐dioxopyrrolo3,4‐cpyrrole‐1,4‐diyl‐alt‐2,2′‐(2,5‐thiophene)bis‐thieno(3,2‐b)thiophene‐5,5′‐diyl (DPPT‐TT) OFETs with P(VDF‐TrFE)‐g‐PMMA exhibit high field‐effect mobility of over 1 cm2 V−1 s−1.
In this study, we investigate the performance of a capacitive deionization system using a flow-electrode composed of biochar prepared via pyrolysis at 700 °C in combination with activated carbon. ...Furthermore, we introduce lead, one of the leading heavy metals known, as a model pollutant to further assess the potential applicability of the system. By comparing the adsorption of multiple ions (i.e., sodium, chloride, lead) using activated carbon alone and in combination with the synthesized biochar under homogeneous conditions, enhancement in system performance by approximately 1.83-fold is indicated using the composite flow-electrode. The distinction of biochar was based on its superior electrical efficiency, with higher mass loading leading to further reduction in solution and charge transfer resistances by 80.8 and 98.7%, respectively, and thus the improvement in system deionization. Accordingly, adopting the optimum operational conditions (applied voltage of 0.9 V, and flow-electrode composition of AC35 B10), the FCDI process achieves outstanding performance in desalination and the further removal of heavy-metal lead ions. To the best of our knowledge, this study is the first to apply biochar as a new innovative flow-electrode material in an FCDI system.
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•Integration of biochar for a potent novel flow-electrode of the FCDI process•Enhanced system current efficiency owing to the low impedance of biochar•Superior remediation of lead based on the surface affinity of biochar•Successful treatment of toxic lead-laden saline water via the biochar integrated FCDI
