Current-voltage Data Research Articles

The pre-exponential voltage-exponent as a sensitive test parameter for field emission theories.

For field electron emission (FE), an empirical equation for measured current Im as a function of measured voltage Vm has the form Im = CVmk exp[–B/Vm], where B is a constant and C and k are constants or vary weakly with Vm. Values for k can be extracted (i) from simulations based on some specific FE theory, and in principle (ii) from current–voltage measurements of sufficiently high quality. This paper shows that a comparison of theoretically derived and experimentally derived k-values could provide a sensitive and useful tool for comparing FE theory and experiment, and for choosing between alternative theories. Existing methods of extracting k-values from experimental or simulated current–voltage data are discussed, including a modernized ‘least residual’ method, and existing knowledge concerning k-values is summarized. Exploratory simulations are reported. Where an analytical result for k is independently known, this value is reliably extracted. More generally, extracted k-values are sensitive to details of the emission theory used, but also depend on assumed emitter shape; these two influences will need to be disentangled by future research, and a range of emitter shapes will need examination. Other procedural conclusions are reported. Some scientific issues that this new tool may eventually be able to help investigate are indicated.

Facile synthesis of nickel cobaltite quasi-hexagonal nanosheets for multilevel resistive switching and synaptic learning applications

High-density memory devices are essential to sustain growth in information technology (IT). Furthermore, brain-inspired computing devices are the future of IT businesses such as artificial intelligence, deep learning, and big data. Herein, we propose a facile and hierarchical nickel cobaltite (NCO) quasi-hexagonal nanosheet-based memristive device for multilevel resistive switching (RS) and synaptic learning applications. Electrical measurements of the Pt/NCO/Pt device show the electroforming free pinched hysteresis loops at different voltages, suggesting the multilevel RS capability of the device. The detailed memristive properties of the device were calculated using the time-dependent current–voltage data. The two-valued charge-flux properties indicate the memristive and multilevel RS characteristics of the device. Interestingly, the Pt/NCO/Pt memristive device shows a compliance current (CC)-dependent RS property; compliance-free RS was observed from 10−2 to 10−4 A, and the compliance effect dominated in the range of 10−5–10−6 A. In CC control mode, the device demonstrated three resistance states during endurance and retention measurements. In addition, the device was successful in mimicking biological synaptic properties such as potentiation-depression- and spike-timing-dependent plasticity rules. The results of the present investigation demonstrated that solution-processable NCO nanosheets are potential switching materials for high-density memory and brain-inspired computing applications.

Non-intrusive identification of harmonic polluting loads in a smart residential system

Smart meter technology has been developed rapidly in modern industrial environment in the context of smart grid connected residential load system. For the smart meter’s application, knowledge about instantaneous load pattern is crucial. Non-intrusive load monitoring (NILM) is a well-known method to assess the power consumption of individual load as well as its operating behavior.​ Since the modern household appliances can inject unwanted harmonics to the system, identification of harmonic polluting loads has also become an issue for such load monitoring schemes. In this article, an improved technique to identify the harmonic polluting loads has been presented using only input aggregated voltage–current data of a residential system. A search-based optimization, i.e., Artificial Bee Colony (ABC) algorithm is used in the proposed load monitoring technique. Unlike the existing methods, this technique does not require any heavy training mechanism for the system. The algorithm is verified using the PLAID datasets and results are compared to some state-of-the-art techniques. Suitable simulations and experimentally created dataset analysis have been carried out on a residential system to demonstrate the ability of the proposed methodology.

Information extraction from Murphy–Good plots of tungsten field electron emitters

This study introduces an easy methodology to test and analyze experimental field electron emission current-voltage data from metallic single-tip emitters; this novel and easy methodology is called the Murphy–Good plots. Tungsten electron emitters were used as an example and were prepared by the electrochemical etching process. The current-voltage characteristics are obtained in high vacuum levels and using a traditional field emission microscope. Murphy–Good plots are used to apply the well-known field electron emission orthodoxy test to the experimental data and then to extract the emitters’ characterization parameters if the test is passed. The novelty in using this type of plots lies in its independency on any correction factors, unlike the traditional Fowler–Nordheim and Millikan–Lauritsen plots, in addition to its simple theoretical form. The results are calculated using a simple web tool that applies the field electron emission orthodoxy test to any type of the current-voltage analysis plots and then to extract the characterization parameters of the emitters.

Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis

The Tafel slope is a key parameter often quoted to characterize the efficacy of an electrochemical catalyst. In this paper, we develop a Bayesian data analysis approach to estimate the Tafel slope from experimentally-measured current-voltage data. Our approach obviates the human intervention required by current literature practice for Tafel estimation, and provides robust, distributional uncertainty estimates. Using synthetic data, we illustrate how data insufficiency can unknowingly influence current fitting approaches, and how our approach allays these concerns. We apply our approach to conduct a comprehensive re-analysis of data from the CO2 reduction literature. This analysis reveals no systematic preference for Tafel slopes to cluster around certain "cardinal values” (e.g. 60 or 120 mV/decade). We hypothesize several plausible physical explanations for this observation, and discuss the implications of our finding for mechanistic analysis in electrochemical kinetic investigations.

An adaptive differential evolution with decomposition for photovoltaic parameter extraction.

Photovoltaic (PV) parameter extraction plays a key role in establishing accurate and reliable PV models based on the manufacturer's current-voltage data. Owning to the characteristics such as implicit and nonlinear of the PV model, it remains a challenging and research-meaningful task in PV system optimization. Despite there are many methods that have been developed to solve this problem, they are often consuming a great deal of computing resources for more satisfactory results. To reduce computing resources, in this paper, an advanced differential evolution with search space decomposition is developed to effectively extract the unknown parameters of PV models. In proposed approach, a recently proposed advanced differential evolution algorithm is used as a solver. In addition, a search space decomposition technique is introduced to reduce the dimension of the problem, thereby reducing the complexity of the problem. Three different PV cell models are selected for verifying the performance of proposed approach. The experimental result is firstly compared with some representative differential evolution algorithms that do not use search space decomposition technique, which demonstrates the effectiveness of the search space decomposition. Moreover, the comparison results with some reported well-established parameter extraction methods suggest that the proposed approach not only obtains accurate and reliable parameters, but also uses the least computational resources.

FABRICATION AND CHARACTERIZATION OF NATURAL DYESENSITIZED SOLAR CELLS BASED ON PbS NANOSTRUCTURES

Natural dye-sensitized solar cells were fabricated based on differently shaped Lead Sulfide nanoparticles in a simple cost-effective way. The grown PbS nanoparticles were characterized by TEM, XRD, Optical Absorption, and Photoluminescence study. The natural dye-sensitized solar cell was fabricated using a kind of dye from Clitoria ternatea as a sensitizer. The current-voltage data of the dye-sensitized solar cell was taken under dark and light illuminated conditions. The dye-sensitized solar cell efficiency was measured and the ideality factor, fill factor were also found out. The open-circuit voltage and short circuit current density of the dye-sensitized solar devices based on three different shaped PbS nanoparticles are also obtained and compared.

머신 러닝 방법을 이용한 절연 게이트 쌍극자 트랜지스터의 도핑 농도 최적화 및 영향도 분석

In this study, machine-learning and technology computer-aided design (TCAD) simulation are collaborated for optimizing and analyzing the doping concentration in insulated gate bipolar transistor (IGBT). Stochastic current-voltage data is extracted from TCAD simulation. Theses results are trained in XGBoost algorithms of machine-learing method. From the trained results, targeting the performance of IGBT without additional experiment or numerical simulation is being easy and fast. Therefore, the collaboration of TCAD simulation and machine-learning is effective and useful to save time and cost in the development of semiconductor.

Stable Photoelectrochemical Hydrogen Evolution for 1000 Hours at 14% Efficiency in a Monolithic Device

The development of a fully-integrated, photoelectrochemical (PEC) device coupling water oxidation to hydrogen evolution using a III-V triple-junction photovoltaic (PV) embedded in a Nafion membrane is reported. This architecture is genuinely monolithic, with wireless catalyst integration being achieved via compression of metal sputter-coated, carbon electrodes against the front and back PV contacts. The resulting MEA-type, sandwich structure minimizes the path length for proton conduction through the membrane ionomer, while simultaneously preventing PV light attenuation by the catalyst layer, a common issue for monolithic PEC structures. While the wireless nature of monolithic PEC devices typically prevents the measurement of current flow and faradaic efficiencies, we circumvent this complication through the placement of an electrical shunt between the PV and the cathode catalyst layer, rerouting charge generated at the PV through a potentiostat prior to cathodic proton reduction. Using this device architecture, we demonstrate significant enhancements in device stability and longevity, by transitioning from a liquid-water to water-vapor anode. Our use of a gas-fed anode enables 1000 hours of cumulative device operation at a peak solar-to-hydrogen efficiency of 14%, during simulated, solar illumination at 1 sun and outdoor, diurnal cycling. Vapor-fed water oxidation is shown to reduce drops in device performance by mitigating the corrosion effects that are commonly associated with full-aqueous immersion of the electrochemical and photovoltaic elements in PEC devices. Causes for observed fluctuations in device performance are determined through the collection of real-time, current-voltage data, paired with an analytical method, permitting the deconvolution of PV- and catalyst-driven performance losses. Figure 1

A Zero-Dimensional Electrochemical Model for Organic Flow Cells

We develop and experimentally validate a zero-dimensional model of the electrochemical performance of a flow cell. The model takes into account voltage losses due to Faradaic charge transfer, ohmic and mass transport resistance, as well as the effect of spatial variations in state-of-charge between the cell and electrolyte reservoir. We validate the model by comparing voltage-current data during cycling to equivalent electrochemical measurements from a symmetric cell with organic reactants. With the exception of the mass transfer coefficient, all relevant model parameters are determined independently prior to the experiment using electrochemical impedance spectroscopy and cyclic voltammetry measurements. We find excellent agreement between the model and experiment for constant-current and constant-voltage cycling, across a wide range of current densities (40 – 200 mA/cm2) and volumetric flow rates (~ 10 – 140 mL/min). The relationship between the fitted mass transport coefficient and flow rate conforms to expectations from the literature [1-3], and reasonably approximates the analogous relationship from single-reservoir cell measurements. This work supports the notion that zero-dimensional electrochemical models can yield simple but predictive frameworks for optimizing organic flow battery performance and understanding how reactant decomposition and crossover contribute to capacity fade.

Gaussian Thermionic Emission Model for Analysis of Au/MoS2 Schottky-Barrier Devices

Schottky-barrier inhomogeneities are expected at the metal--transition-metal-dichalcogenide (TMDC) interface and this can impact device performance. However, it is difficult to account for the distribution of interface inhomogeneity as most techniques average over the spot area of the analytical tool (e.g., few hundred micrometers squared for photoelectron-based techniques), or the entire device measured for electrical current-voltage (I-V) measurements. Commonly used models to extract Schottky-barrier heights neglect or fail to account for such inhomogeneities, which can lead to the extraction of incorrect Schottky-barrier heights and Richardson constants that are orders of magnitude away from theoretically expected values. Here, we show that a Gaussian-modified thermionic emission model gives the best fit to experimental temperature-dependent current-voltage (I-V-T) data of van der Waals $\mathrm{Au}$/p-${\mathrm{Mo}\mathrm{S}}_{2}$ interfaces and allow the deconvolution of the Schottky-barrier heights of the defective regions from the pristine region. By the inclusion of a Gaussian-distributed Schottky-barrier height in the macroscopic I-V-T analysis, we demonstrate that interface inhomogeneities due to defects are deconvoluted and well correlated to the impact on the device behavior across a wide temperature range from a room temperature of 300 K down to 120 K. We verify the Gaussian thermionic model across two different types of p-${\mathrm{Mo}\mathrm{S}}_{2}$ (geological bulk crystals and synthetic flux-grown crystals), and finally compare the macroscopic Schottky-barrier heights with the results of a nanoscopic technique, ballistic hole emission microscopy (BHEM). The results obtained using BHEM are consistent with the pristine $\mathrm{Au}$/p-${\mathrm{Mo}\mathrm{S}}_{2}$ Schottky-barrier height extracted from the Gaussian-modified thermionic emission model over hundreds of nanometers. Our findings show that the inclusion of Schottky-barrier inhomogeneities in the analysis of I-V-T data is useful to elucidate the impact of defects (e.g., grain boundaries, metallic impurities, etc.) and hence their influence on device behavior. We also find that the effective Richardson constant, a material-specific constant typically treated as merely a fitting constant, is a useful parameter to check for the validity of the transport model.

Tick-Borne Encephalitis Electrochemical Detection by Multilayer Perceptron on Liquid-Metal Interface.

This work depicts an electrochemical hydrogel-eutectic gallium indium alloy interface for the detection of tick-borne encephalitis (TBE) virus. This interface allows recording of nonlinear current-voltage responses, depending on the composition of the hydrogel. The current-voltage data for the machine learning model are trained by a multilayer perceptron. This model accurately recognizes the TBE antibody, antigen, and an antibody-antigen complex in mixture with interfering bovine serum albumin with 93% accuracy. Thus, this interface can be used as a convenient method for expressed viruses and pathogens detection.

Parameter estimation of photovoltaic models using an improved marine predators algorithm

The abundance of solar energy as one of the clean energy forms offers a great advantage as an alternative to non-renewable energy sources. The photovoltaic system is a promising technology that directly converts sunlight into a direct current. Parameter estimation of photovoltaic systems is a challenging task that has a significant influence on the efficiency of these systems. Most of the existing methods employed for identifying parameters of photovoltaic systems suffer from high computing burdens, fall into local optima, or struggle with the intricate adjustment required of the algorithm parameters to provide the best performance. This paper, therefore, proposes an improved algorithm based on the new metaheuristic marine predators algorithm to extract the optimal values of photovoltaic parameters. The improved marine predators algorithm employs a population improvement strategy to enhance the quality of the solutions by utilizing two different ways to handle the solutions inside the population-based on the population mean fitness. The location of a high-quality solution is improved using an adaptive mutation operation, while the location of a low-quality solution is updated according to the location of the best-obtained solution and the location of a good solution selected from the population. A good solution is chosen from the first half of the population after sorting its solutions in ascending order. The results of several experiments show the superior performance of the proposed algorithm compared to existing algorithms on a range of photovoltaic models. The results show that the proposed algorithm is highly correlated with the measured current–voltage data so that it can offer a useful alternative for parameter estimation of photovoltaic models.

The electric field at the hole-injecting metal/organic interface controls the bias dependence of the current–voltage hole mobility

Based upon the room temperature current–voltage data of some published organic diode structures the unique phenomenon of the decreasing hole mobility, μ, with the increasing applied electric field, E a, is interpreted. The measurable quantity, the hole drift mobility μ d is formulated in terms of E a and the electric field at the hole injecting metal/organic interface, E int, dependent algebraic function multiplied by the intrinsic hole mobility, μ max that is organic morphology dependent but E a independent scaling factor. On account that the intrinsic mobility, μ max, is uncoupled from both E a and E int it is shown that the origin of the negative field hole mobility effect occurs due to E int, that is a linear function of E a. The bias and the space distribution of the internal organic electric field, E, as well as the free hole density, p, for poly(3-hexylthiophene) is calculated in detail. Depending on the organic layer morphology the internal electric field may exhibit, at the particular value of E a, a deep well in the vicinity of the hole injecting metal/organic interface. Then the strong peak of the free hole density exists there the effect of which is spreading some 10 nm into the organic. If E int happens to be E a independent constant, then from the resulting space charge limited current density, the increasing hole drift mobility, μ d, with the increasing applied electric field, E a, is deduced. The published current–voltage data of two distinct metal-substituted phthalocyanine thin films provide an additional confirmation of the described formalism.

Hybrid approach to modeling large area field emitters

Large area field electron emitters, typically consisting of several thousands of nanotips, pose a major challenge since numerical modeling requires enormous computational resources. We propose a hybrid approach where the local electrostatic field enhancement parameters of an individual emitter are determined numerically while electrostatic shielding and anode-proximity effects are incorporated using recent analytical advances. The hybrid model is tested numerically on an ordered arrangement of emitters and then applied to recent experimental results on randomly distributed gold nanocones. Using the current-voltage data of two samples with vastly different emitter densities but having similar nanocone sizes, we show that an appropriate modeling of the emitter apex together with the analytical results on shielding and anode-proximity effects leads to consistent results for the apex radius of curvature. In both cases, the I−V data are approximately reproduced for Ra≃9 nm. Importantly, it is found that anode-proximity plays a significant role in counter-balancing electrostatic shielding, and ignoring this effect results in the requirement of a much smaller value of Ra.

The vortex state in FeSe superconducting thin film

We have investigated the low temperature isothermal current-voltage characteristics of FeSe epitaxial films with thickness of ∼ 360 nm at different magnetic fields parallel to the c axis. At zero magnetic field, with decreasing temperature a Berezinskii–Kosterlitz–Thouless transition, which often appears in two-dimensional (2D) superconductors, is observed. The current dependence of the voltage obeys the scaling relation V ∼ I 3 at the transition temperature K, and the temperature dependence of sheet resistance follows the prediction of the Halperin-Nelson formula in the vicinity of . When a magnetic field with magnitude 0.1 T T is applied, the low temperature isothermal current-voltage data in each field can be scaled onto two different branches by using the scaling relation predicted by the vortex-glass theory. When comparing with the scaling relation, the dimensionality D can only be taken as 2, indicating a vortex-liquid phase to quasi-2D vortex-glass phase transition occurs in the FeSe film. The presence of Berezinskii–Kosterlitz–Thouless transition and the quasi-2D vortex-glass phase are related to the weak coupling between Fe-Se layers in the FeSe film.

Fabrication and comparison of Heterojunction solar cells from CdS/PbS nanoparticles and CdS/PbS bulk

PbS nanoparticles and CdS nanoparticles are grown by chemical methods. Also bulk PbS is grown by simple chemical methods without using any capping agent. The material formation is identified from XRD.TEM image shows the formation of different shaped PbS nanoparticles, CdS nanoparticles, and bulk PbS. Three different heterojunction solar cells are fabricated by CdS and PbS samples using a spin coating technique. Finally, gold is evaporated on PbS film. Current-voltage characteristics data for three heterojunction solar cells are taken under dark and illumination conditions. For each fabricated solar cell open-circuit voltage (VOC), short circuit current density (ISC), fill factor (FF), and power conversion efficiency() are measured. Finally, a comparison of the characteristics is done for different fabricated heterojunction solar cells.

A random forest-based approach for fault location detection in distribution systems

Finding the fault location in distribution network is difficult in comparison to transmission network based upon high branching and high impedances composed of the contact with environmental factors when a fault occurs. For this matter, the possible faulty section is identified and then the fault location is determined with the proposed algorithms in this study. Wavelet transform is applied to the current–voltage data along with feature extraction methods, and then, Random Forest is used for identifying the faulty section and estimating the fault location. To approve the validation, the algorithms are applied to IEEE-34 node test feeder. Single-phase to ground faults regarding different impedance values at different points of the feeder have been effectively detected by using single measurement point data from the sending end of the feeder.

Valence band offset determination of CdSeTe and CdMgTe alloys with CdTe using X-ray photoemission spectroscopy

A limited series of uniform composition CdSeTe alloys and a CdMgTe alloy were grown via molecular beam epitaxy and measured with x-ray photoemission spectroscopy to determine valence band offsets (VBO) with CdTe. We present an alternative to the Kraut method for VBO determination in ternary alloy systems, which does not require determination of the valence band maxima, often a significant source of error in VBO determination. VBOs determined using two different etching sources agreed well with temperature dependent current-voltage data as well as with recent theoretical work, and a linear fit of the VBO data presented here predicts a VBO between CdTe/CdSe a factor two to three times smaller than previously reported.

Quantitative Ion Probe Measurements for Application in a Rotating Detonation Engine

Rotating detonation engines (RDEs) are characterized by extremely high temperatures and pressures, with operating frequencies on the order of several kilohertz. This creates an environment that is challenging to implement research diagnostics. The two most common diagnostics implemented in RDEs operating at speeds capable of defining the detonation wave are dynamic pressure transducers and ion probes. In the case of dynamic pressure transducers, hardware cost and excessive temperatures often dictate remotely coupled transducers, such as a semi-infinite tube pressure configuration in order to improve survivability. Ion probes, on the other hand, are much more robust and can be installed directly within the combustion annulus. However, the information obtained by ion probes in RDEs has been largely qualitative, with their primary use being wave tracking for speed and directionality. This paper presents methodology for determining quantitative ion concentrations from raw ion probe current–voltage data, using known geometry and appropriate electrostatic probe theory. Data are presented from a combustion-driven shock tube, demonstrating applicability of various probe theories and providing comparisons with values determined from a Zeldovich–Neumann–Döring simulation using the Shock and Detonation Toolbox. Results are considered from the perspective of future implementation of a flush-mounted device within the combustion annulus of an RDE.