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Recently, the advantages of perovskite solar cells (PSCs) and a significant increase in power conversion efficiency (PCE) have played an essential role in the preference for these materials. Although different methods are used to increase PCE and reduce losses at the interfaces in PSCs, placing a new layer between the absorber/hole transfer layer (HTL) or between the absorber/electron transfer layer (ETL) stands out as one of the most common methods. In this study, considering stability, sustainability, mobility, and non-toxicity, Cs4CuSb2Cl12 (CCSC) perovskite quantum dots (PQDs) were preferred as the interface layer between absorber and HTL in CsPbI3 and formamidinium lead iodide (FAPI)-based PSC devices. While SnO2, Cu2O, and nickel were used as ETL, HTL, and back contact, respectively, CsPbI3 and FAPI perovskites were utilized as absorber materials separately. Simulations were conducted on Solar Cell Capacitance Simulator (SCAPS-1D) software and the current density (J) and voltage characteristics were compared. By choosing different interface layer thicknesses, different radiative recombination coefficients (RRCs), and different defect sites, the cell efficiency of the PQD interlayer solar cells were simulated. Simulations were also carried out using different series resistance (Rs) and different shunt resistance (Rsh) values to show the effect of parasitic losses on cell efficiency, and it was observed that device efficiency increased where Rs was low and Rsh was high. In addition, in FAPI-based structure, with the addition of a PQD layer between the absorber and HTL, it was observed that the short circuit current density increased from 17.6 mA/cm2 to 25.67 mA/cm2, while the cell efficiency increased by 30%. Furthermore, according to the results obtained using CsPbI3 as an absorber, adding a PQD layer between CsPbI3 and HTL increased the short circuit current density from 17.8 mA/cm2 to 20.7 mA/cm2 and cell efficiency by 16%. To sum up, these simulation results demonstrate that inserting a PQD layer between the absorber and HTL significantly enhances the efficiency and charge carrier capacity of solar cells.

Electromyography (EMG) data gives information about the electrical activity related to muscles. EMG data obtained from arm through sensors helps to understand hand gestures. For this work, hand gesture data were taken from UCI2019 EMG dataset obtained from MYO thalmic armband were classied with six dierent machine learning algorithms. Articial Neural Network (ANN), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Naive Bayes (NB), Decision Tree (DT) and Random Forest (RF) methods were preferred for comparison based on several performance metrics which are accuracy, precision, sensitivity, specicity, classication error, kappa, root mean squared error (RMSE) and correlation. The data belongs to seven hand gestures. 700 samples from 7 classes (100 samples per group) were used in the experiments. The splitting ratio in the classication was 0.8-0.2, i.e. 80% of the samples were used in training and 20% of data were used in testing phase of the classier. NB was found to be the best among other methods because of high accuracy (96.43%) and sensitivity (96.43%) and the lowest RMSE (0.189). Considering the results of the performance parameters, it can be said that this study recognizes and classies seven hand gestures successfully in comparison with the literature.

Biosensor, a device used in the detection of an analyte, combines a biological/chemical sensor component with a physicochemical transducer. The sensor and the transducer elements recognize and detect the analyte qualitatively and/or quantitatively [1][2][3]. The biological sensor element may be in the form of tissue, microorganism, organelle, receptor, enzyme, antibody, nucleic acid, molecule, etc., which may be attached to the metal, polymer or glass surface of the electrode through chemical and physical means.A biological sensor element may be relatively short-lived and with complications in handling; therefore, they may be replaced with artificial elements that are components of a receptor-based sensing system. Molecular Imprinting Technology (MIT) is a method that aims to overcome these complications by producing selectively specific artificial receptors. It utilizes molecular imprinting polymer (MIP), formed as a dependable molecular recognition element with room temperature stability that mimicks natural recognition elements, such as antibodies and receptors. MIT is used in the detection, separation and purification of biological and chemical molecules, such as amino acids and proteins, nucleotids, toxins, drugs, etc. A 3D polymeric network is formed between the analyte and monomer through functional hydrogen bonds, dipole-dipole and ionic interactions. After polymerization, upon removal of the analyte, specific recognition sites that are in the shape, size and chemical structure of the analyte are formed in the polymer [4][5][6][7][8][9][10][11].There are examples of MIP based sensors equipped more commonly with SPRS and QCM based transducers [4]. However, they have not been experimented in the detection of small ABSTRACTA molecularly imprinted polymer (MIP)-based impedimetric biosensor was developed for the electrochemical analysis of low-weight biological molecules. Synthetic polymeric matrices with specific and selective recognition sites, which are complementary to the shapes and sizes of the functional groups of analytes, can be prepared using the molecular imprinting method. In this study, a small molecule, tris(hydroxymethyl)aminomethane (TRIS), was used to coat a graphite pencil tip with a TRIS-containing polyacrylamide gel to fabricate a working electrode. The electrode modification and performance were evaluated using cyclic voltammetry and electrochemical impedance spectroscopy. The electrochemical properties of the modified electrodes were observed using an electrochemical cell comprising a Ag/AgCl reference electrode, a Pt wire as the counter electrode, and a pencil graphite tip as the working electrode using a redox-phosphate buffer solution with different concentrations of TRIS and Ethylenediaminetetraacetic acid (EDTA). The I-V and impedance performance of the chemically modified graphite pencil-tip electrodes exhibited decreased conductance and increased impedance correlating with the increase in TRIS concentration. Thus, MIP-based small-molecule biosensor prototypes can be promising eco...

Biosensors are systems that can perform quantitative and/or qualitative analysis of substances in liquid or gas environment through their biological recognition sites and transform the acquired data into detectable signals. Biosensors are able to detect physical changes (i.e. as density, mass concentration, etc.) by means of recognition sites and correlate them with electrical or optical quantities (i.e. current, voltage and impedance). In this study, three molecularly imprinted pencil graphite electrodes with differing numbers of choline recognition sites, at E-1 M, E-3 M and E-5 M concentration, were used as electrochemical biosensors. An increase in choline receptor concentration on the electrode surface was expected to correlate with an increase in PGE surface bound choline and thus lead to electrical changes. The study was conducted in a three-electrode cell with Ag/AgCl as the reference electrode, platinum wire as the counter electrode and PGE as the working electrode. Cyclic voltammetry and electrochemical impedance measurements were conducted in 10 mM phosphate buffer solution containing 5mM K 3 [FeCN 6 ]-3/-4 redox pair. As expected, as increasing amount of choline was bound to the complementary recognition sites on choline imprinted electrodes, a correlating change in current, voltage and impedance was observed. The dynamic detection range for choline expanded as the choline concentration imprinted on the electrodes increased. Using the E-1 M PGE electrode, 72 pM limit of detection, up to 7.2 nM limit of linearity was attained.