Cost-Effective and Rapid Detection of Tetrodotoxin Using Indium Tin Oxide Electrodes via In Vitro Electrophysiology and Electrochemistry

Lithium-based batteries are today’s most favourable systems to provide energy for battery-powered applications such as (Hybrid) Electric Vehicles ((H)EVs), laptops and smartphones. Generally, (commercial) Li-ion batteries are two-electrode systems. Therefore, only the battery potential or impedance can be measured across the negative and positive electrode. However, for research purposes and to design more sophisticated Battery Management Systems (BMS) it is of interest to distinguish between both electrodes by using reference electrodes (RE), making it possible to measure the electrochemical characteristics of the individual electrodes. RE have already been introduced in many studies1,2. However, Electrochemical Impedance Spectroscopic (EIS) measurements on three-electrode Li-ion battery systems are prone to measurement artefacts. The majority of the research on EIS measurement artefacts focuses on the cell geometry and/or the position of the RE3,4. In the present contribution, new results are presented which show that EIS artefacts in the high frequency range can be compensated by averaging two distinctive EIS measurements. This strikingly results in artefact-free EIS measurements, especially in the high frequency range of the impedance spectra. This new method has been applied to pouch-type Li-ion batteries with integrated metallic lithium-based micro-reference electrodes1,2. Fig. 1 shows EIS measurements, revealing the high-frequency artefacts as well as the compensated EIS measurements. The EIS measurements of the battery (Bat), and those of the positive (P) and negative (N) electrode vs a lithium micro-reference electrode are shown in Fig. 1a. In addition, the impedance spectrum of the summation of P and N is shown (P+N), which obviously should end up with the same result as found for Bat in the entire frequency range. However, in the high frequency range a large deviation between Bat and P+N can be observed, indicating that the impedance measurements of the individual electrodes are not correct. This is because the generated excitation current induces a net voltage in the RE due to an unbalance in the measurement setup. Additional EIS measurements have been carried out with the measurement cables in a reversed connection. These results are shown in Fig. 1b and indicated with the subscript r. It can be observed that also these EIS measurements are deviating in the high frequency range but now in the opposite direction. However, averaging the measurements shown in Fig. 1a and b, results in correct impedance spectra for both the individual electrodes and added spectra, as indicated in Fig. 1c and, at a larger magnification, in Fig. 1d. It can indeed be seen that the impedance spectra of the individual electrodes are now artefact-free in the high frequency range and that the summation of P and N are now in perfect agreement with the total battery impedance in the entire frequency range. It can be concluded that high frequency impedance measurement artefacts observed with micro-reference electrodes integrated in Li-ion batteries can perfectly be compensated by averaging two EIS measurements. This results in artefact-free impedance spectra of (commercial) three-electrode batteries without making complicated measurement setups, which can easily be facilitated by conventional electronic circuitry as will be shown in the near future.

There exists a growing need for standardized On-Board Diagnostics (OBD) for electric vehicles [1] to provide accurate health metrics and guarantees to both consumers and manufacturers.Previous work has shown the powerful LIB capacity-based State-of-Health (SoH) estimation capability of Electrochemical Impedance Spectroscopy (EIS) measurements and data-driven models [2] [3]. Since EIS measurements are dependent not only on SoH but also State-of-Charge (SoC) and temperature [4], it is important that the measurements are conducted after the cell reaches an equilibrium, and that these other variables are also tracked. Although EIS measurements are somewhat quicker than some traditional capacity-determination experimental methods, the time taken for such measurements is not insignificant. Therefore, building a pipeline to determin the EIS frequency measurements most important for SoH estimation is an important task in developing a suitable EIS-based OBD. By exploring a frequency range between 0.1 and 200 Hz, we study EIS measurements related to diffusion and charge transfer processes in LIB operation [5], with each process being partially distinguishable due to their varying timescales.In this work, using EIS data collected from 5Ah LIBs with an NMC-111 cathode and a graphite anode at various SoCs (0, 25, 50, 75 and 100%) and cell lifetime (0, 10, 20, 40 and 90 days) as input features, we develop sequential, data-driven health estimation models for LIBs. The 22 cells used for this analysis have been aged over a period of 90 days in two different ways: either through active cycling at different C-rates (0.2 and 1C) and temperatures (0, 25 and 40⁰C), or passive “calendar aging” where the cells are left without use at a specific temperature and SOC. Using feature attribution techniques (Shapley values, feature occlusion, etc.), we find the most influential of the frequency ranges in the EIS measurements that relate strongly with cell performance degradation. To develop a streamlined and efficient SoH estimation framework, we formulate an optimization problem to find the EIS experimental design in terms of frequency ranges that delivers maximum accuracy in SoH estimation at different points in the lifetime of the cell. These streamlined and optimized EIS experimental designs and SoH estimation models can be used directly in the development of rapid and efficient on-board diagnostic tools.

Study of oxygen diffusion in the cathode catalyst layer and gas diffusion layer for polymer electrolyte fuel cells with EIS

Motivation: Self-Assembled Monolayer (SAM) modified electrode has a key role in electrochemical biosensor applications to achieve desired sensing properties such as selective interaction with target protein and anti-fouling properties of non-specific protein. However, the degradation of SAM layer on the electrode can cause the electrochemical response to drift over time. This causes adversary effect on the designed biosensor such as limited shelf life and inconsistent electrochemical signal reading between electrodes. For that matter, it is important to understand the signal drift behaviour and ultimately obtain a SAM-modified electrode with good stability over time. In this study, we observed the signal drift of SAM-modified indium tin oxide electrode on PET substrate (ITO-PET). Three-electrode electrochemical impedance spectroscopy (EIS) measurement was carried to evaluate the electrochemical properties of the ITO-PET substrate over time. Materials and Methods: Commercial ITO-PET (Adafruit, NY, USA) was used as electrode and was modified using Perfluoro-octyltriethoxysilane (Sigma Aldrich, St. Louis, MO, USA) self-assembled monolayer. The ITO-PET substrate was modified by using room temperature RCA-1 silanization process as shown in Figure 1. The modified electrode was rinsed in ethanol and DI water and stored in dark condition with temperature of 5oC. The Electrochemical Impedance Spectroscopy measurements were carried by using Solartron SI1260 impedance analyser tandem with SI1287 potentiostat. with saturated KCl Ag/AgCl (RRPEAGCL2, Pine Research, NC, USA) electrode and Pt wire counter electrode (MW-1032; BASi, West Lafayette, IN, USA). Potassium Ferricyanide (K3Fe(CN)6) (Fischer Scientific, Fair Lawn, NJ, USA) with concentration of 10 mM in 1x PBS was used as redox probe. The EIS run was set at 0.31 Vdc and 10 mV Vac amplitude with frequency ranging from 0.1 – 10000 Hz. Results: We observed significant increase charge transfer resistance (Rct)increase of SAM-ITO sample (4498 ± 460 Ω.cm2) compared to the bare ITO sample (1348 ± 68 Ω.cm2). The signal also maintains its consistency after one week of storage in enclosed dry and dark environment at 5oC with 3% change in average Rct value (133 Ω.cm2). Ongoing work in this study includes the electrochemical signal evaluation of the ITO-SAM electrode exposed to protein such as casein and BSA. Figure 1

This paper presents a method for an online real-time electrochemical impedance spectroscopy (EIS) measurement of batteries using closed-loop control of power converter. Unlike the previously proposed method which allows the measurement of the ac impedance for a single frequency, the presented method in this paper allows for obtaining the EIS for a spectrum of frequencies by using the information included in a single perturbation cycle, or a few cycles of perturbation to obtain a more accurate EIS with a very wide frequency range. This will result in faster EIS measurement for a spectrum of frequencies and under the same battery operating conditions. The presented method utilizes closed-loop control operation for the EIS measurement functionality, which allows for better control of the output voltage and for upgrading the concept to be able to achieve no added perturbation ripple at the output of the system. The presented online real-time EIS measurement method utilizes a power converter with closed-loop control in order to create an output voltage step-function perturbation at a given frequency to generate battery voltage and current responses. By applying Fourier analysis to these responses, an EIS can be obtained for a range of frequencies equal or higher than the perturbation frequency of the step function. In addition, this paper presents a method to eliminate the added perturbation ripple when two or more power converters are used. The theoretical basis and experimental prototype results are provided to illustrate and validate the presented method.

Low frequency inductive loop in EIS measurements of an open-cathode polymer electrolyte fuel cell stack. Impedance of water vapour diffusion in the cathode catalyst layer

Study of current distribution and oxygen diffusion in the fuel cell cathode catalyst layer through electrochemical impedance spectroscopy

In this study, uncertainties during the assessment of the electrochemical impedance spectrum of the polymer electrolyte fuel cell (PEFC) attributed to inductive artefacts at high frequencies and inductive loops at low frequencies as well as oxygen diffusion time constant are discussed. A validated impedance model represented as an equivalent electrical circuit of a PEFC allowed the simulation of the effect of inductive artefacts, inductive loops and oxygen diffusion time constant on electrochemical impedance spectroscopy (EIS) measurements represented in the Nyquist plot. This study considers EIS measurements reported in previous studies and provides an insight into the EIS measurements with positive imaginary components at high frequencies attributed to the intrinsic inductance of the measurement cables during EIS tests and at low frequencies attributed to electrochemical mechanisms (e.g. side reactions with intermediate species) during PEFC operation. In addition, an overview of overlapping mechanisms (charge transfer and oxygen transport resistances during the oxygen reduction reaction) on the PEFC impedance spectrum attributed to oxygen diffusion across the cathode catalyst layer is presented. EIS measurements with positive imaginary components and with overlapping effects could yield to ambiguities when studying or relating electrochemical mechanisms (ion conduction, capacitance, charge transfer and mass transport resistances) of the PEFC through a defined single frequency or a single measured value represented in the Nyquist complex-impedance plot.

Solder paste, when properly stored and handled, is unlikely to immediately start producing defects. Environmental and handling conditions such as temperature and humidity are major factors that could contribute to significant changes in the physical, electrochemical, and mechanical properties of the solder paste during production. Any change in the viscoelastic characteristics can alter the expected behavior of the paste, potentially producing defects such as slumping, poor stencil life, skipping, etc. These changes can be captured by Solder Paste Inspection (SPI), but only after the paste produces defects. What if there was a way to predict solder paste performance prior to SPI defect detection? This study is aimed at correlating Electrochemical Impedance Spectroscopy (EIS) measurements to printing defects as captured by SPI. In this work, the solder paste was exposed to a series of printing and kneading cycles over a 24-hour period in order to accelerate its aging. During the printing cycle, boards with over 6000 apertures were printed repetitively and SPI data was collected along with a corresponding EIS measurement. The final cycle was completed on the second day after leaving the paste to knead overnight. This experiment was repeated one month later after the cartridge was left at room temperature. Through examining the number of defects determined by SPI based on volume, the Defects Per Million Opportunities (DPMO) data was compared to the EIS measurements of both test days. Based upon the results, there was a direct correlation between the DPMO and the EIS measurements; therefore, it was concluded that EIS could be used to determine solder paste quality.

IntroductionIn this paper, we report novel insulin sensors using insulin single-chain antibody (scFv) based on two electrochemical impedance spectroscopy (EIS) methods; faradaic EIS and non-faradaic EIS. For faradaic EIS measurement, varieties of molecular recognition elements (MREs) can be utilized, such as IgG and binding proteins, without consideration of their molecular size. However, a solubilized redox probe is necessary to aid the transfer of electrons and detection is based on the flux of electrons and the obstruction that is present on the electrode surface. Non-faradaic EIS does not require a solubilized redox probe and is based around changes within the electrical double layer. However, there are the limitation of the size for MREs, since the ideal size of MREs should be smaller than the size of electrical double layer (EDL). In this paper, thanks to the small size of scFv as MRE for EIS, we construct two different types of EIS based insulin sensors, and compare the suitability in the use for insulin monitoring, being dedicated for the management of diabetic patients.MethodsDevelopment of this sensor requires immobilization of a molecular recognition element (MRE) that binds with insulin. For this purpose, we have cultivated single-chain insulin antibody by transforming an Escherichia coli strain, harvesting and filtering the protein culture, and purifying the protein culture. Through this cultivation procedure, we obtained insulin scFv that can be immobilized on a gold surface electrode. For faradaic EIS measurement, we employed potassium ferricyanide as the solubilized redox probe to conduct insulin measurement. Binding of insulin concentrations with insulin scFv caused a change in electron flux, which thereby caused changes in charge-transfer resistance (Rct) or impedance. In non-faradaic EIS measurement, ionic liquid is typically used as the buffer to redistribute the dielectric bilayer. Thanks to the small size of insulin scFv, capacitance changes can be directly measured within EDL. Both detection principles were compared by selecting an optimized frequency which best reflects binding between insulin and the MRE.ResultsWe were able to identify an optimized frequency for both detection principles when measuring insulin, establishing a unique change in impedance. A change in Rct was noticed through faradaic EIS when measuring insulin against the insulin scFv. Additionally, at the optimized frequency the sensor had a slope of 701 Ohms/Ln(nM). With the non-Faradaic EIS detection principle, the sensor displayed changes within EDL.DiscussionWe were able to determine that faradaic and non-faradaic EIS could be used to measure changing insulin concentrations when using insulin scFv as the MRE. Differences between both detection principles existed due to the use of a solubilized redox probe for faradaic EIS versus the absence of it when conducing non-Faradaic EIS. Future work will include comparing the sensitivity and selectivity of both detection methods when measuring insulin.

Superhydrophobic hydroxide zinc carbonate (HZC) films were fabricated on aluminum substrate through a convenient in situ deposition process. Firstly, HZC films with different morphologies were deposited on aluminum substrates through immersing the aluminum substrates perpendicularly into aqueous solution containing zinc nitrate hexahydrate and urea. Secondly, the films were then modified with fluoroalkylsilane (FAS: CH3(CF2)6(CH2)3Si(OCH3)3) molecules by immersing in absolute ethanol solution containing FAS. The morphologies, hydrophobicity, chemical compositions, and bonding states of the films were analyzed by scanning electron microscopy (SEM), water contact angle measurement (CA), Fourier transform infrared spectrometer (FTIR), and X‐ray photoelectron spectroscopy (XPS), respectively. It was shown by surface morphological observation that HZC films displayed different microstructures such as microporous structure, rose petal‐like structure, block‐shaped structure, and pinecone‐like structure by altering the deposition condition. A highest water contact angle of 156.2° was obtained after FAS modification. Moreover, the corrosion resistance of the superhydrophobic surface on aluminum substrate was investigated using electrochemical impedance spectroscopy (EIS) measurements. The EIS measurements’ results revealed that the superhydrophobic surface considerably improved the corrosion resistance of aluminum.

Laser surface cladding (LSC) process was used to introduce high chromium‐nitrogen alloys on carbon steel to improve its corrosion resistance. The chemical composition, the resulting microstructure, and the electrochemical behavior in connection with the chemical composition of the surfaces of the cladded layers were analyzed in this study. Potentiodynamic polarization tests and electrochemical impedance spectroscopy (EIS) measurements were performed to evaluate the corrosion resistance of the cladded layers in deaerated solution at pH 4. The surfaces of the samples after EIS measurements were characterized with Auger electron spectroscopy and x‐ray photoelectron spectroscopy. The results showed that the Cr content as high as while the nitrogen concentration as high as were found in the cladded layer. Approximately of Si in all the LSC layers were also detected. The passive film resistance increased and the passive current density decreased with increasing the chromium‐nitrogen content in the cladded layer. Electrolyte analyses after EIS measurements showed that nitrogen atoms in the surface of LSC layer can be electrochemically reduced to . The surface of samples, after EIS measurements, consisted of chromium oxide, chromium nitride; ammonia and silicon oxide were found. The passive films resistance of LSC alloys might partially be attributed to the formation and adsorption of ammonia on the surfaces. The chromium nitride, silicon oxide incorporated with chromium oxide could possible modify the passive film and cause an improvement in corrosion resistance.

Comparison of electrochemical behavior between coarse-grained and fine-grained AISI 430 ferritic stainless steel by Mott–Schottky analysis and EIS measurements

Electrochemical and surface studies on the passivity of nitrogen and molybdenum containing laser cladded alloys in 3.5 wt% NaCl solution

In this study, transfer learning (TL) technique is used in conjunction with deep neural network (DNN) to predict the capacity of lithium-ion batteries. First, the base DNN model is trained and validated based on the source dataset containing electrochemical impedance spectroscopy (EIS) measurement at temperatures of 25 °C and 35 °C. Then, the base DNN model is retrained and validated using different proportions, i.e., the first 50% and 20% of the target dataset, which contains EIS measurement at the temperature of 45 °C. This will create a new model called DNN-TL carrying the knowledge from the base model. The DNN-TL model is used to predict the second proportions, i.e., the second 50% and 80% of the target dataset considered as missing data. The maximum mean absolute percentage error (MAPE), when the first 50% and 20% of the target dataset are used for retraining DNN-TL with no fixed-layer, is found to be 0.605% and 0.999%, respectively, which indicates the accuracy of the model to estimate the capacity of batteries. The average <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R$ </tex-math></inline-formula> -squared of 0.9683 is achieved by DNN-TL with no fixed-layer indicating the goodness of its fit and its capability to follow the actual missing datasets.