Experimental Current-voltage Research Articles

Refinement of the Co-Content function, through an integration of a polynomial fit of I-Isc. Part 2 application to experimental current–voltage curves

In this article Part 2 of this series of articles, the methodology proposed in Part 1, namely, the fitting to a polynomial of the current minus the short-circuit current, i.e., I-Isc, to calculate the Co-Content function CCV,I and extract the five solar cell parameters, i.e., the shunt resistanceRsh, the series resistanceRs, the ideality factorn, the light currentIlig, and the saturation currentIsat, (within the one-diode solar cell model), is implemented on reported Current–Voltage (IV) curves found in the literature, both for laboratory made solar cells, as for and single-crystalline silicon (x-Si), multi-crystalline silicon (m-Si), cadmium telluride (CdTe), copper indium gallium selenide (CIGS), amorphous silicon (a-Si) tandem and triple-junction, amorphous silicon/crystalline silicon, heterojunction with intrinsic thin-layer (HIT), and amorphous silicon/microcrystalline silicon photovoltaic modules.

Parameter Extraction for Photovoltaic Models with Flood-Algorithm-Based Optimization

Accurately modeling photovoltaic (PV) cells is crucial for optimizing PV systems. Researchers have proposed numerous mathematical models of PV cells to facilitate the design and simulation of PV systems. Usually, a PV cell is modeled by equivalent electrical circuit models with specific parameters, which are often unknown; this leads to formulating an optimization problem that is addressed through metaheuristic algorithms to identify the PV cell/module parameters accurately. This paper introduces the flood algorithm (FLA), a novel and efficient optimization approach, to extract parameters for various PV models, including single-diode, double-diode, and three-diode models and PV module configurations. The FLA’s performance is systematically evaluated against nine recently developed optimization algorithms through comprehensive comparative and statistical analyses. The results highlight the FLA’s superior convergence speed, global search capability, and robustness. This study explores two distinct objective functions to enhance accuracy: one based on experimental current–voltage data and another integrating the Newton–Raphson method. Applying metaheuristic algorithms with the Newton–Raphson-based objective function reduced the root-mean-square error (RMSE) more effectively than traditional methods. These findings establish the FLA as a computationally efficient and reliable approach to PV parameter extraction, with promising implications for advancing PV system design and simulation.

Dark current in FTO/CZTS interface: a comprehensive comparison of practical Vs theoretical approach using SCAPS-1D

This study investigates the deposition of Cu2ZnSnS4 (CZTS) thin films on fluorine-doped tin oxide (FTO) and soda-lime glass (SLG) substrates using radio frequency (RF) sputtering at varying temperatures. A comprehensive characterization employing multiple analytical techniques was conducted. X-ray diffraction (XRD) analyses confirmed the amorphous nature of CZTS films being deposited up to 200 °C, while higher temperatures promoted increased crystallinity, with the presence of (112) and (220) planes observed at 300 °C and 400 °C. Rietveld refinement using Profex software revealed an increase in crystallite size with deposition temperature for films grown at 300 °C and 400 °C. Optical characterization through UV–vis spectroscopy unveiled a decrease in band gap energy with increasing deposition temperature, while the Urbach energy, associated with defects and imperfections, exhibited an inverse relationship with band gap and temperature. Experimental current–voltage (I-V) measurements using a Keithley source meter showed variations in the ideality factor with deposition temperature. SCAPS-1D simulations were performed to model the FTO/CZTS interface, incorporating experimental parameters. The simulated I-V behavior demonstrated a transition from recombination to diffusion-dominated current above 1.3 V forward bias. Simulations yielded higher ideality factors due to increased contributions from recombination and diffusion currents. Overall, this study provides insights into the growth, structural, optical, and electrical properties of CZTS thin films deposited by RF sputtering, enabling a comprehensive understanding of the FTO/CZTS heterojunction characteristics and their dependence on deposition temperature.

Feed Forward Modeling: an efficient approach for mathematical modeling of the force frequency relationship in the rabbit isolated ventricular myocyte

Background and Objective. This study addresses the Force-Frequency relationship, a fundamental characteristic of cardiac muscle influenced by β 1-adrenergic stimulation. This relationship reveals that heart rate (HR) changes at the sinoatrial node lead to alterations in ventricular cell contractility, increasing the force and decreasing relaxation time for higher beat rates. Traditional models lacking this relationship offer an incomplete physiological depiction, impacting the interpretation of in silico experiment results. To improve this, we propose a new mathematical model for ventricular myocytes, named ‘Feed Forward Modeling’ (FFM). Methods. FFM adjusts model parameters like channel conductance and Ca2+ pump affinity according to stimulation frequency, in contrast to fixed parameter values. An empirical sigmoid curve guided the adaptation of each parameter, integrated into a rabbit ventricular cell electromechanical model. Model validation was achieved by comparing simulated data with experimental current–voltage (I-V) curves for L-type Calcium and slow Potassium currents. Results. FFM-enhanced simulations align more closely with physiological behaviors, accurately reflecting inotropic and lusitropic responses. For instance, action potential duration at 90% repolarization (APD90) decreased from 206 ms at 1 Hz to 173 ms at 4 Hz using FFM, contrary to the conventional model, where APD90 increased, limiting high-frequency heartbeats. Peak force also showed an increase with FFM, from 8.5 mN mm−2 at 1 Hz to 11.9 mN mm−2 at 4 Hz, while it barely changed without FFM. Relaxation time at 50% of maximum force (t50) similarly improved, dropping from 114 ms at 1 Hz to 75.9 ms at 4 Hz with FFM, a change not observed without the model. Conclusion. The FFM approach offers computational efficiency, bypassing the need to model all beta-adrenergic pathways, thus facilitating large-scale simulations. The study recommends that frequency change experiments include fractional dosing of isoproterenol to better replicate heart conditions in vivo.

Transport properties of interface-type analog memristors

Interface-type, analog memristors have quite a reputation for real-time applications in edge sensorics, edge computing, and neuromorphic computing. The -type conducting BiFeO3 (BFO) is such an interface-type, analog memristor, which is also nonlinear and can therefore not only store, but also process data in the same memristor cell without data transfer between the data-storage unit and the data-processing unit. Here we present a physical memristor model, which describes the hysteretic current-voltage curves of the BFO memristor in the small and large current-voltage range. Extracted internal state variables are reconfigured by the ion drift in the two write branches and are determining the electron transport in the two read branches. Simulation of electronic circuits with the BFO interface-type, analog memristors was not possible so far because previous physical memristor models have not captured the full range of internal state variables. We show quantitative agreement between modeled and experimental current-voltage curves exemplarily of three different BFO memristors in the small and large current-voltage ranges. Extracted dynamic and static internal state variables in the two full write branches and in the two full read branches, respectively, can be used for simulating electronic circuits with BFO memristors, e.g., in edge sensorics, edge computing, and neuromorphic computing. Published by the American Physical Society 2024

Advancements in CIGS/ZnS heterojunction solar cells: Experimental and numerical analysis

This study presents a comprehensive experimental investigation conducted on a CIGS-based solar cell incorporating a ZnS buffer layer. The primary objective was to determine key parameters of the CIGS/ZnS heterojunction, including parasitic resistances (Rs and Rsh), ideality factor (n), and barrier height (ϕB), using experimental current-voltage (I-V) characteristics over a temperature range of 150 K to 300 K under dark conditions. The heterojunction was modelled using a single-diode electrical circuit that accounted for parasitic resistances. Two methods were employed for parameter determination: direct analysis of the (I-V) curves and Cheung's method. Additionally, the charge transport mechanism within the heterojunction is investigated and discussed. Furthermore, the performance of the Al:ZnO/i:ZnO/ZnS/CIGS/Mo solar cell was assessed using the SCAPS-1D simulator, demonstrating an initial solar energy conversion efficiency of 15.01 %. To enhance this efficiency, a hole transport layer (HTL) was integrated between the back electrode and the absorber layer. Extensive studies were conducted to optimize the thickness and doping density of the HTL, including a comparative analysis of different materials used as HTLs. These optimizations resulted in a significant increase in conversion efficiency, reaching up to 28.68 %.

(Digital Presentation) Temporal Evolution of the Threshold Voltage in Organic Thin Film Memory Transistors

We present a procedure to monitor the temporal evolution of the trapped charge in floating gates of organic thin film transistors (OTFTs) based memories in dynamic regimes. The potential applications of organic semiconductors in flexible and wearable electronics and their known features such as low-temperature and solution fabrication make the OTFTs be considered as candidates also in the field of non-volatile memories. Past efforts have been devoted on the preparation and optimization of floating gates [1]. In the present work, we focus on the modelling of this kind of devices, in particular, on a model for the threshold voltage useful in dynamic experiments, such as hysteresis and transient regimes. The information extracted from the modelling and simulation of these devices can be related to technological parameters with the objective of finding a better memory design.Current-voltage curves impacted by hysteresis are usually reproduced assuming the threshold voltage to be constant or piecewise constant. Nevertheless, despite positive outcomes [2], this is not a precise approach since it does not consider the actual temporal evolution of the threshold voltage. Thus, a time dependent threshold voltage is mandatory in order to interpret hysteresis phenomena and transient experiments, which in turn can be associated to trapping and de-trapping mechanisms over time.In this work, a model that describes the evolution of the threshold voltage with the time, which is linked to the variation of the trapped charge in the channel, is proposed.The evolution of the trapped charge is described with a first-order linear differential equation with a term controlled by a time constant t, and another term, similar to the generation term in a typical continuity equation, which is proportional to the drain current flowing through the transistor channel. This model is introduced in a compact model previously developed for OTFTs that include contact effects [3–6]. The resulting model is combined with an evolutionary parameter extraction procedure, which is applied to experimental current–voltage curves taken from the literature that show both contact and hysteresis effects [7]. Figures (a) and (b) show the best fitting of our calculations (solid lines) and experimental output and transfer characteristics (symbols), respectively, of a pentacene-based organic thin film memory transistor using poly (methyl methacrylate) (PMMA) as the insulator [7]. Figures (c) and (d) show the time evolution of the threshold voltage during the experiments (a) and (b), respectively.The authors acknowledge support from the project PID2022-139586NB-44 funded by MCIN/AEI/10.13039/501100011033 and by European Union NextGenerationEU/PRTR.

Addressing challenges inverse problem with convolutional neural networks and regulation techniques: Applications in extraction of physical parameters of semiconductors devices

The instability of the inverse problem is caused by its nonlocal and non-causal nature. This study addresses the inverse problem of determining the physical parameters of semiconductor devices. Based on statistical inversion theory, the probability distribution (posterior distribution) of the SBHs has been estimated by convolutional neural networks. Regularization techniques were then applied to such a distribution to accurately determine the SBHs of semiconductor devices. The results reveal that the fluctuations in the predicted SBHs by convolutional neural networks are similar to the amplitude between the upper and lower envelopes of the free decay curve. The method achieves a maximum relative error below 3.4% when using theoretical diode current–voltage data as input and maintains a relative error of less than 7% when compared to traditional methods when using experimental current–voltage data. Furthermore, the proposed method offers a mathematical interpretation of the inverse problem and demonstrates the capability of the proposed method to extract the physical parameters of semiconductor devices with a small amount of data.

Experimental and Theoretical Investigation of Zr‐Doped CuO/Si Solar Cell

Copper oxide (CuO) is a nanostructured semiconductor material with the potential for solar energy conversion and can be suitable for solar cells when used as a thin film. Herein, nondoped and doped (doping ratios of 1%, 2%, and 3% zirconium [Zr]) CuO thin films on silicon (Si) with the spin‐coating technique are developed. Optical and topological characterizations of CuO thin films are examined by ultraviolet‐visible and X‐ray diffraction. The electrical properties of nondoped and Zr‐doped CuO/Si heterojunctions are investigated with experimental current–voltage measurements in the dark and under illuminated conditions. The electrical behavior of nondoped and Zr‐doped CuO/Si heterojunctions is obtained using the experimental J–V technique and computational Cheung–Cheung and Norde methods. A simulation based on nondoped and Zr‐doped CuO/n‐Si heterojunction solar cells using SCAPS‐1D is completed. Photovoltaic (PV) parameters of experimentally produced and theoretically calculated CuO and Zr‐doped CuO/Si heterojunction solar cells are compared. Accordingly, PV parameters of 1% Zr‐doped CuO/Si solar cells show the highest power conversion efficiency calculated as a function of interfacial defect density and hole carrier concentration.

Surface plasmon resonance effects of Ag@ZnO core–shell nanostructure in UV and visible light for photodiode applications

AbstractHerein, Ag@ZnO core–shell nanostructures were prepared via the wet chemical method and were then dissolved in methanol and drop cast onto a p–Si wafer. Experimental current–voltage measurements of the Ag@ZnO/p–Si heterojunction device were investigated under both visible and UV illumination of 365 and 395 nm. The photocurrent, responsivity, detectivity, and on/off ratio were found to be dependent on the light intensity of visible light and wavelength of UV light. The low photocurrent at low light intensities and its rapid increase at high light intensities was attributed to the recombination of electrons and holes and also to the presence of traps at low light intensities. The responsivity and detectivity of the photodiode reach 1.32 A/W and 5.47 × 1011 Jones, respectively at 365 nm. On the contrary, the high performance under UV light was explained by the surface plasmon resonance between Ag and ZnO.

Fabrication and characterization of TiOx based single-cell memristive devices

Nowadays, remarkable progress has been observed in research into neuromorphic computing systems inspired by the human brain. A memristive device can behaviorally imitate the biological neuronal synapse therefore memristor-based neuromorphic computing systems have been proposed in recent studies. In this study, the memristive behaviors of titanium dioxide sandwiched between two platinum electrodes were investigated. For this purpose, three SiO2/Pt/TiOx/Pt thin films with 7.2 nm, 40 nm, and 80 nm TiOx metal-oxide layers were fabricated using a pulsed laser deposition technique. The fabrication process, structural properties, photoluminescence properties and electrical transport characterization of each thin film have been investigated. All thin films were analyzed in terms of the film stoichiometry and degree of oxidation using high-resolution x-ray photoelectron spectroscopy. By measuring the layer thickness, density, and surface roughness with the x-ray reflectivity technique, by analyzing the structural defects with photoluminescence spectroscopy and by characterizing the quasi-static electrical properties with the conventional two probes technique, we have shown that the fabricated memristive devices have bipolar digital switching properties with high ROFF/RON ratio. This type of switching behavior is applicable in random access memories. Experimental current–voltage behavior in the form of pinched hysteresis loop of the films have been modelled with generalized memristor model.

Determination and validation of polarization losses parameters to predict current/voltage-characteristics for SOFC button cell

Solid Oxide Fuel Cell represents a valid and clean alternative to conventional combined heat and power systems. These devices can convert different kinds of fuels into electricity with high efficiencies (up to 75–80 %) and low CO2 or hazardous emissions. In order to understand and validate Solid Oxide Fuel Cell behavior at different operating conditions, investigations are currently focusing their attention on modeling. In this work, an experimental-based model to study the effect of different hydrogen and temperature conditions on both the polarization processes and its effect on Solid Oxide Fuel Cell performance is presented. Experimental parametric campaigns were carried out using a button anode supported Solid Oxide Fuel Cell with an active area of about 2 cm2. A practical zero-dimensional mathematical model based on low and high voltage approximations of the Butler-Volmer equations was used starting from an experimental current–voltage dataset to obtain polarization curve parameters representing different physical phenomena associated with the cell. To validate the obtained results and gain additional information, electrochemical impedance spectroscopy measurements and distribution of relaxation times analysis were performed both in open circuit voltage and underload at 0.5 A/cm2. Finally, from the fitted parameters, it was possible to derive dimensionless charge transfer coefficients related to the most probable reaction mechanisms occurring in the cell, equal to 2 for the anodic process and 3.5 for the cathodic process. Moreover, from the results the obtained exchange current densities range from 0.024 A/cm2 to 0.048 A/cm2 for O2 reduction and from 0.012 A/cm2 to 0.073 A/cm2 for H2 oxidation and subsequently, the activation energies equal to 100 kJ/mol and 66 kJ/mol for anodic and cathodic electrochemical processes, respectively.

Numerical Analysis of Humidification Condition Effects on Protonic Ceramic Fuel Cell Performance Considering Concentration Overpotential

Protonic ceramic fuel cells (PCFCs) show relatively high performance at intermediate temperature range (400–600 °C) due to high proton conductivity in electrolyte. However, besides proton, other charges such as electron hole and oxygen vacancy can also be conductive in PCFCs. Especially, the hole conductivity will induce a hole current leakage so that current efficiency and power density will decrease. Besides the operating temperature, the conductivities of proton and hole are also strongly affected by the partial pressures of steam and oxygen in the PCFC [1,2]. Higher steam partial pressure leads higher proton conductivity, so that a higher power density can be expected. However, other influences such as concentration overpotential may be non-negligible. Furthermore, the proton and hole current density are affected by defect concentrations differences between two surfaces of the electrolyte membrane. Numerical simulation method is powerful tool for dealing with the complicated conditions in a PCFC mentioned above.In the present study, the influences of steam partial pressure on a BaZr0.8Yb0.2O3− δ (BZYb20) electrolyte are investigated. Specifically, to reveal the currents induced by the electrostatic potential and gas concentrations, Nernst-Planck model is selected. To relatively obviously reveal the steam concentration influences on the PCFC performances, low (3%) and high (69%) humidification conditions of H2 fuel gas are adopted. The results in Fig. 1(a) and 1(b) show the simulation and experimental current-voltage characteristics under 3% and 69% humidification conditions, respectively. The green solid and dotted lines are external and proton current densities considering concentration overpotential influence, respectively. The blue lines express external current density when no concentration overpotential in the numerical model. The red circles are the measured data. At low steam partial pressure, the simulation results well reproduced the experimental data without concentration overpotential consideration. However, an obvious deviation was found between simulation and experimental results when neglecting concentration overpotential in the simulation model. The performances such as open circuit voltage (OCV) and hole current leakage (difference between proton and external current density) are influenced by the steam partial pressure.

Impact of Through-Hole Defects on the Electro-Explosive Properties of Exploding Foil Transducers.

This study examines the impact of surface defects on the electro-explosive properties of metal explosive foil transducers. Specifically, it focuses on the effects of defects in the bridge foil and their influence on the electrical explosion time and transduction efficiency. To analyze these effects, a current-voltage simulation model is developed to simulate the behavior of a defective bridge foil. The simulation results are validated through experimental current-voltage measurements at both ends of the bridge area. The findings reveal that the presence of through-hole defects on the surface of the bridge foil leads to an advancement in the electrical explosion time and a reduction in the transduction efficiency of the bridge foil. A performance comparison is made between the defective bridge foil and a defect-free copper foil. As observed, a through-hole defect with a radius of 20 μm results in a 1 ns advance in the blast time and a 1.52% decrease in energy conversion efficiency. Similarly, a through-hole defect with a radius of 50 μm causes a 51 ns advancement in the blast time and a 13.96% reduction in the energy conversion efficiency. These findings underscore the detrimental effects of surface defects on the electro-explosive properties, emphasizing the importance of minimizing defects to enhance their performance.

Achieving beyond 26.6% efficiency for graded bandgap perovskite solar cell: Theoretical study

The graded energy band gap is an effective method for improving solar spectrum efficiency. To reduce the short-circuit current density (JSC) losses, creation of suitable spike-like alignment at the electron transport (ETL)/perovskite junction is a proper method. Also, simulations model is calibrated with the experimental current-voltage (J–V) and power conversion efficiency (PCE) to validate obtained data. The graded FAPbI3 perovskite solar cell has been proposed, and the effect of (Br, I) on the device efficiency is researched. The results illustrate that iodide values in FAPb (IxBr1-x)3 significantly influence the adjustment of conduction band energy states at the perovskite/ETL interface. The Br flexibility ranging from 0% to 40% allows the target perovskite solar cell (PSC) to produce an optimum conduction band offset (CBO) at the perovskite/ETL interface. The CBO creation between the FAPbI3/ETL causes achieving (open-circuit voltage) VOC to 1.22 V, JSC to 26.9 mA cm−2, and fill factor (FF) to 81.1. Here, we demonstrate that graded energy band gap PSC could achieve steady-state conversion efficiencies of ∼26.63%. According to the results, this enhancement is owing to the proper carrier's transport among the perovskite/ETL junction due to a recombination decrement in the junction with spike-like band alignment.

Simulation of the effect of material properties on yttrium oxide memristor-based artificial neural networks

This paper reports a simulation study concerning the effect of yttrium oxide stoichiometry on output features of a memristor-based single layer perceptron neural network. To carry out this investigation, a material-oriented behavioral compact model for bipolar-type memristive devices was developed and tested. The model is written for the SPICE (Simulation Program with Integrated Circuits Emphasis) simulator and considers as one of its inputs a measure of the oxygen flow used during the deposition of the switching layer. After a thorough statistical calibration of the model parameters using experimental current–voltage characteristics associated with different fabrication conditions, the corresponding curves were simulated and the results were compared with the original data. In this way, the average switching behavior of the structures (low and high current states, set and reset voltages, etc.) as a function of the oxygen content can be forecasted. In a subsequent phase, the collective response of the devices when used in a neural network was investigated in terms of the output features of the network (mainly power dissipation and power efficiency). The role played by parasitic elements, such as the line resistance and the read voltage influence on the inference accuracy, was also explored. Since a similar strategy can be applied to any other material-related fabrication parameter, the proposed approach opens up a new dimension for circuit designers, as the behavior of complex circuits employing devices with specific characteristics can be realistically assessed before fabrication.

Investigation of Peak-to-Valley Current Ratio of GaN/AlN Resonant Tunneling Diodes

Peak-to-valley current ratios (PVCRs) achie-ved in GaN/AlN resonant tunneling diodes (RTDs) are less than 2, significantly less than their counterparts, such as InGaAs/AlAs RTDs (e.g., PVCR <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim$</tex-math> </inline-formula> 12). This has hindered their high-speed applications because the maximum self-oscillation frequency and minimum switching time generally increase and decrease with PVCR. In this article, we investigate the problem of low PVCR in GaN/AlN RTDs with both modeling and experiments. Firstly, we developed a Schrödinger equation-based solver for RTD simulations. While the solver gives reasonable agreement with the experimental current–voltage ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</i> – <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> ) characteristics, such as the positions of resonant peaks, it predicts a much higher PVCR. Then, we conducted temperature dependence studies on GaN/AlN RTDs and compared them with InGaAs/AlAs RTDs. The similarities observed suggest that sequential tunneling with phase randomization, resulting from scattering processes such as optical phonon and interface roughness scattering, is responsible for the large valley currents in GaN/AlN RTDs.

New Approach for Photovoltaic Parameters Extraction for Low-Cost Electronic Devices

This work proposes a new five-parameter model equation for PV devices, which operates as a function of the main representative parameters of PV devices. It is specifically developed for implementation in embedded systems. The methodology presented in this work is notable due to the fact that three of the five parameters can be directly extracted from the experimental current–voltage (I–V) curve, simplifying the iterative process until a pre-set small difference in the determination of the maximum power is achieved. The iterative methodology for extracting the remaining parameters is also described. The proposed methodology is verified by applying it to seven different PV technologies, including crystalline and thin-film technologies. Its parameters are compared with those obtained using the highly precise trust region iterative method. The resulting parameters and the error in the adjustment along the I–V curve are discussed. This methodology demonstrates the capability to accurately adjust the model along the entire I–V curve, determine the maximum power, and is not dependent on highly variable parameters.

Approach to chemical equilibrium of water dissociation for modeling bipolar membranes in acid-base flow batteries

Understanding the behavior of bipolar membranes under forward and reverse bias in multi-ion solutions is essential for their application in acid-base flow batteries (ABFB). To this end, a two-dimensional steady-state model of the bipolar membrane is proposed based on the Nernst-Plank and Poisson equations coupled with water dissociation and acid-base neutralization reactions. The second Wien effect and catalytic activity are included in the water dissociation rate model at the bipolar junction. Experimental current-voltage curves were obtained using linear sweep voltammetry to validate the model. A commercial bipolar membrane was used in NaCl solutions at 0.25 and 0.5 mol L−1 concentrations, a mixture of NaCl-HCl and NaCl-NaOH solutions at different concentrations, and solutions of HCl and NaOH at 0.5 mol L−1 concentration. The catalytic activity coefficient was the only model parameter fitted to the experimental data; all other properties and parameters were obtained from the literature or calculated from the membrane supplier data. The numerical solution of the bipolar membrane model complements the experimental results. It shows a full view of conductivity, ion concentration, and potentials across the bipolar membrane as a function of its polarization.

How do proton-transfer reactions affect current-voltage characteristics of anion-exchange membranes in salt solutions of a polybasic acid? Modeling and experiment

Insufficient understanding of transport mechanism of polybasic acid species (phosphoric, citric, malic, etc.) through anion-exchange membranes (AEMs) hinders the widespread use of electrodialysis for processing salt solutions of such acids, e.g. the recovery of phosphates from mixed solutions. In this paper, we present experimental current-voltage characteristics (CVC) and partial fluxes of H2PO4− and HPO42− across an AEM. These data are simulated using a mathematical model based on the Nernst-Planck-Poisson equations coupled with the kinetic equations for chemical reactions. The model describes the nonstationary transport of phosphate acid species through an AEM and adjacent solution diffusion boundary layers. It is shown that the proton-transfer reactions determine the occurrence of two limiting currents. The electric current sweep rate and the values of dissociation rate constants of acid anions largely affect the values of these limiting currents and generally the shape of the CVC. It is found that due to chemical reactions involving polybasic anions, the formation of their concentration profiles in the membrane occurs much slower than in the case of monobasic salts. Numerical simulation shows that a quasi-stationary CVC is possible only when the current sweep rate is such that measurements are carried out for at least 10 h.