Influence of Electrode Connection Tracks on Biological Cell Measurements by Impedance Spectroscopy

The limit of detection of a biological sensor is an important parameter because, when it is optimized, it allows the detection of a reduced number of biological cells and the reduction of the detection time. This parameter can be improved upon with a reduction in electrode size, but the rate of detection is similarly reduced as well. To avoid this problem, we propose a sensor matrix composed of 20 × 20 µm² coplanar square electrodes with a standard clean room manufacturing process. However, it was observed that the exposition of electrode connection tracks to the solution reduces the normalized impedance variation. In this pursuit, we propose in this paper an analysis of electrode connection tracks on the normalized impedance variation and cutoff frequencies to biological cell measurements by impedance spectroscopy. The experimental results were obtained using the E4990A Keysight impedance analyser (Keysight Technologies, Santa Rosa, CA, USA) with a frequency band ranging from 100 Hz to 12 MHz, thus allowing for good measurement accuracy. Therefore, it was found that, for the measurements between the electrodes with 9 µm of connection tracks in contact with the solution, the normalized impedance variation was from 3.7% to 4.2% for different measurements, while, for the electrodes with 40 µm of connection tracks in contact with the solution, the normalized impedance variation was from 1.8% to 2.1% for different measurements.

Artefacts Removal to Detect Visual Evoked Potentials in Brain Computer Interface Systems

The interference of artefacts with evoked scalp electroencephalogram (EEG) responses is a problem in event related brain computer interface (BCI) system that reduces signal quality and interpretability of user's intentions. Many strategies have been proposed to reduce the effects of non-neural artefacts, while the activity of neural sources that do not reflect the considered stimulation has been neglected. However discerning such activities from those to be retained is important, but subtle and difficult as most of their features are the same. We propose an automated method based on a combination of a genetic algorithm (GA) and a support vector machine (SVM) to select only the sources of interest. Temporal, spectral, wavelet, autoregressive and spatial properties of independent components (ICs) of EEG are inspected. The method selects the most distinguishing subset of features among this comprehensive fused set of information and identifies the components to be preserved. EEG data were recorded from 12 healthy subjects in a visual evoked potential (VEP) based BCI paradigm and the corresponding ICs were classified by experts to train and test the algorithm. They were contaminated with different sources of artefacts, including electromyogram (EMG), electrode connection problems, blinks and electrocardiogram (ECG), together with neural contributions not related to VEPs. The accuracy of ICs classification was about 88.5% and the energetic residual error in recovering the clean signals was 3%. These performances indicate that this automated method can effectively identify and remove main artefacts derived from either neural or non-neural sources while preserving VEPs. This could have important potential applications, contributing to speed and remove subjectivity of the cleaning procedure by experts. Moreover, it could be included in a real time BCI as a pre-processing step before the identification of the user’s intention.

The treatment of zinc-cyanide electroplating rinse water using an electrocoagulation process

This paper investigates the treatment of zinc-cyanide electroplating rinse water using an electrocoagulation process (ECP). The effects of operating parameters such as electrode material, current density (2.5–40 A/m2), operating time (0–60 min), initial pH (5–12) and electrode connection mode (monopolar parallel (MP-P), monopolar series and bipolar series) on the ECP were evaluated to find the optimum operating conditions. At 20 A/m2, 60 min, the highest removal efficiencies were obtained with 85 and 99% for Fe and 64 and 33% for Al electrodes, for cyanide and zinc, respectively. The optimum operating conditions were found to be 30 A/m2 and 40 min, for the Fe electrode at the original pH (9.5) of the rinse water. Considering efficiency and economy, the MP-P connection mode was determined as the optimum connection mode.

Improved Performance of the Piezoelectric Monomorph with Perpendicular Electrode Connections for Sensing and Energy Harvesting

Piezoelectric monomorph, which has only one element, is a potential structure for piezoelectric applications in some extreme conditions. But as the restriction of the strain neutral layer, the traditional parallel electrode connection is not effective for sensing and energy harvesting. In this paper, perpendicular electrode connections were designed to utilize the nonuniform shear piezoelectric effect in the cross section of the monomorph, which made the monomorph avoid the restriction of the strain neutral layer. The PZT5 ceramic monomorph was preliminarily studied in this experiment. By comparing seven forms of perpendicular electrode connections with the traditional parallel electrode connection, the whole superposed perpendicular electrode connection is considered as the optimal output way for the monomorph. It can produce 13 V peak-to-peak (pk-pk) voltage in open circuit and 14.56 μW maximum power with the matching resistance, which are much more than the parallel electrode connection 0.78 V and 0.14 μW.

Effects of operational parameters on defluoridation efficiency using electrocoagulation process

The aim of this study is to examine the effect of operational parameters on fluoride removal using electrocoagulation method. For this purpose, various operational parameters including initial pH, initial fluoride concentration, applied current, reaction time, electrode connection mode, anode material, electrolyte salt, electrolyte concentration, number of electrodes and interelectrode distance were investigated. The highest defluoridation efficiency achieved at initial pH 6. In the case of initial fluoride concentration, maximum removal efficiency (98.5%) obtained at concentration of 25mg/l. The increase of applied current and reaction time improved defluoridation efficiency up to 99%. The difference of fluoride removal efficiencies between monopolar and bipolar series and monopolar parallel were significant, especially at reaction time of 5 min. When aluminum used as anode material, higher removal efficiency (98.5%) achieved compared to that of iron anode (67.7%). The best electrolyte salt was NaCl with the maximum defluoridation efficiency of 98.5% compared to KNO3 and Na2SO4. The increase of NaCl had no effect on defluoridation efficiency. Number of electrodes had little effect on the amounts of Al3+ ions released in the solution and as a result defluoridation efficiency. Almost the same fluoride removal efficiency obtained for different interelectrode distances.