DC Drift Research Articles

External temperature sensor assisted a new low power photoplethysmography readout system for accurate measurement of the bio-signs.

This study presents an external temperature sensor assisted a new low power, time-interleave, wide dynamic range, and low DC drift photoplethysmography (PPG) signal acquisition system to obtain the accurate measurement of various bio signs in real-time. The designed chip incorporates a 2-bit control programmable transimpedance amplifier (TIA), a high order filter, a 3:8 programmable gain amplifier (PGA) and 2 × 2 organic light-emitting diode (OLED) driver. Temperature sensor is used herein to compensate the adverse effect of low-skin-temperature on the PPG signal quality. The analog front-end circuit is implemented in the integrated chip with chip area of 2008 μm × 1377 μm and fabricated via TSMC T18 process. With the standard 1.8 V, the experimental result shows that the measured current sensing range is 20 nA–100 uA. The measured dynamic range of the designed readout circuit is 80 dB. The estimated signal to noise ratio is 60 dB@1 uA, and the measured input referred noise is 60.2 pA/Hz½. The total power consumption of the designed chip is 31.32 µW (readout) + 1.62 mW (OLED driver@100% duty cycle). The non-invasive PPG sensor is applied to the wrist artery of the 40 healthy subjects for sensing the pulsation of the blood vessel. The experimental results show that for every 1 °C decrease in mean ambient temperature tends to 0.06 beats/min, 0.125 mmHg and 0.063 mmHg increase in hear rate (HR), systolic (SBP) and diastolic (DBP), respectively. Similarly, for every 1 °C increase in mean ambient temperature tends to 0.13 beats/min, 0.601 mmHg and 0.121 mmHg increase in HR, SBP and DBP, respectively. The measured accuracy and standard error for the HR estimation are 96%, and − 0.022 ± 2.589 beats/minute, respectively. The oxygen stauration (SpO2) measurement results shows that the mean absolute percentage error is less than 5%. The resultant errors for the SBP and DBP measurement are − 0.318 ± 5.19 mmHg and − 0.5 ± 1.91 mmHg, respectively.Electronic supplementary materialThe online version of this article (10.1007/s00542-020-05106-y) contains supplementary material, which is available to authorized users.

An Online Compensation Method of DC Drift for Three‐Phase Current Reconstruction with DC‐Link Resistance

In a three-phase power convertor system, phase current reconstruction technique using a DC-link resistance can reduce the cost and weight of the diving system. The three-phase current without DC offset in normal condition is introduced in this paper firstly. Based on this premise, the DC-link current offset is considered and the logical relationship between threephase voltage, three-phase current, and DC offset are analyzed and depicted. The DC offset introduced during the sampling processes a distortion into phase current, which is composed of fundamental and harmonic frequency based on FFT analysis. The fundamental component of the distortion shares the same phase angle with counterpart voltage, which distorts power factor and amplitude of three-phase currents. The harmonic components of the distortion can be transformed into 6th harmonic components in synchronous dq axes and undermine the performance of the controlling system. After that, a practical method is proposed to solve this problem, namely sampling the DC offset signal during the period of the zero voltage vectors. An analogy sample circuit is designed and tested. This method can avoid the DC offset from the source. Finally, its effectiveness is verified via simulation and experiment.

Chemoresistive CO2 Gas Sensors Based On La2O2CO3: Sensing Mechanism Insights Provided by Operando Characterization.

Our previous studies demonstrated that rare-earth oxycarbonates Ln2O2CO3 (Ln = La, Nd, and Sm) and rare-earth oxides Ln2O3 (Ln = Nd, Sm, Gd, Dy, Er, and Yb) are sensitive to CO2 and that hexagonal La2O2CO3 is the best among them in terms of sensitivity, stability, and selectivity. In this study, we have conducted a comprehensive operando characterization on a hexagonal La2O2CO3 based sensor for the basic understanding of the sensing mechanism. This was done by performing under actual operating conditions simultaneous DC resistance and work function changes measurements, AC impedance spectroscopy measurements, and simultaneous DC resistance and DRIFT spectroscopy measurements. The results demonstrate that the double Schottky barriers at grain-grain boundaries are dominant contribution to sensor resistance; there is a competitive adsorption between carbonate species and hydroxyl groups, which depends on both CO2 concentration and humidity and leads to the change in height of the Schottky barriers. Finally, we propose a reaction model stating that there are three types of adsorbates, -CO32-, -OH-, and -O2-, and the relative concentration of which is controlled by a reaction with ambient humidity and CO2. This model is able to consistently explain all our experimental findings.

Structural, electrical, optical and dielectric properties of yttrium substituted cadmium ferrites prepared by Co-Precipitation method

The yttrium substituted cadmium ferrites having composition Cd1-xYxFe2O4 (X = 0.00, 0.125, 0.250, 0.375, 0.500) were synthesized by the co-precipitation method and sintered at 1100 °C for 6 h. Structural, morphological, electrical, optical and dielectric characteristics were explored by XRD, SEM, EDS, FTIR, I–V two probes, UV–Vis and LCR techniques.XRD results confirmed the cubic structure of spinel ferrites. A decrease in lattice constants of the prepared samples was observed with the substitution of Y ions and was attributed to the difference in ionic radii of Y3+ (0.95 Å) and Cd2+ (0.97 Å) ions. Cationic distributions, ionic radii of both tetrahedral and octahedral sites, tolerance factor, oxygen positional parameters, bond lengths, interatomic distances, positional parameters and bond length angles were calculated from XRD data. The morphology of the prepared ferrites was studied using SEM and results ratified the XRD results. EDS confirmed the presence of all inserted elements in Cd1-xYxFe2O4 composition. DC resistivity and drift mobility of soft-ferrites were found to be increased from 1.047 × 108–4.822 × 1010 Ω-cm and 5.87 × 10−12 – 1.045 × 10−14 cm2V−1s−1, respectively, at 523 K with yttrium content confirming the behavior of semiconductor materials. The optical band gap energy calculated from the UV–Vis pattern of the Cd1-xYxFe2O4 system was decreased from 3.6011 to 2.8153 eV. DC resistivity and optical band gaps exposed inverse relation. FTIR results revealed lower and upper-frequency absorption bands in the ranges of 419.31–417.01 cm−1 and 540.95–565.70 cm−1, respectively. Dielectric constant and dielectric losses were in decreasing order, while ac conductivity revealed rising behavior with increasing frequency. Results showed the potential of yttrium doped Cd nanoferrites for applications in high-frequency microwave absorbing devices.

A Novel Adaptive Speed Observer Using Neural Network and Sliding-Mode for SPIM Drives

In this paper, a novel Stator Current Based Model Reference Adaptive System (SC_MRAS) speed estimation scheme using neural network (NN) and Sliding Mode (SM) is proposed to improve the performance of the MRAS speed observer for high-performance Six Phases Induction Motor (SPIM) drives, especially at low and zero speed region, where the poor performance of observers is still always a large challenge. In this novel SC_MRAS scheme, a two-layer linear NN, which has been trained online by means of the Total Least Squares (TLS) algorithm, is used as an adaptive model to estimate the stator current and this model is employed in prediction mode. These novel proposed can ensure that the whole drive system achieves faster satisfactory torque and speed control and strong robustness, the observer operate better accuracy and stability both in transient and steady-state operation. Especially, in this proposed observer, the rotor flux, which is needed for the stator current estimation of the adaptive model and providing to the controller, is identified based on adaptive SM technique. The improvement of Rotor Flux Estimation for SC_MRAS-Based Sensorless SPIM Drives help to eliminate the disadvantages in SC_MRAS based observer such as stator resistance sensitivity, and flux open loop integration which may cause dc drift and initial condition problems or instability in the regenerating mode of operation, therefore, enhancing the rotor flux estimation, speed estimation and control accuracy at very low and zero stator frequency operation help improve the overall observer and drive system performance. The indirect field oriented control (IFOC) for speed control of a sensorless SPIM drive using the proposed observer is built by MATLAB/ Simulink. The simulation results are presented under sensorless speed control performance to validate the effectiveness of the proposed estimation and control algorithms.

Study of structural, optical, electrical and magnetic properties of Cu2+doped Zn0.4Co0.6-xCe0.1Fe1.9O4 spinel ferrites

A series of copper (Cu2+) doped Zn0.4Co0.6-xCe0.1Fe1.9O4(x = 0.0, 0.15, 0.30, 0.45, 0.60) nanoparticles were synthesized via co-precipitation route in order to evaluate different properties like the structural, optical, electrical and magnetic through XRD, UV-VIS, SMU with two probes and VSM methods. The XRD patterns confirmed the formation of cubic spinel structure of the prepared samples. Replacement of Co2+ ions with Cu2+ ions have been confirmed by X-ray diffraction patterns. FTIR and UV–Vis also confirmed this replacement. The electrical parameters like DC resistivity, activation energy, and drift mobility have been evaluated to confirm the semiconductor nature of the spinel ferrites. The Curie temperature declines on replacement of Cu2+ ions with Co2+. The magnetic parameters like Bohr magnetic moment, anisotropy constant, initial permeability, Y–K angles, coercivity, and remanence ratio have been measured and determined. The saturation magnetization (Ms) and remanence (Mr) show remarkable decreasing trend with Cu2+ ions concentration.

E-Nose: Multichannel Analog Signal Conditioning Circuit With Pattern Recognition for Explosive Sensing

This paper presents E-Nose, a novel cost-effective, field-deployable portable system that constitutes a 4-channel signal conditioning circuit and multi-coated piezo-resistive micro-cantilever sensors for explosive sensing. E-Nose also features an embedded PCA and K-means based pattern recognition (PR) algorithm for the classification of explosives from non-explosives. The 4-channel configuration is a stack of two 2-channel circuits that are capable of measuring the change in the sensor resistance or capacitance in four optional modes of ΔR-Δ R,ΔR-ΔC,Δ C-ΔR, and ΔC-ΔC by using time multiplexing. The circuit uses a bidirectional AC current excitation method to drive the sensor bridge for significant reduction of DC offset errors, 1/f noise, line noise, and DC drifts. The proposed signal conditioning circuit uses the phase-sensitive synchronous rectification(PSSR) method for AC-to-DC conversion by using balanced demodulation. The circuit can measure a wide range of resistors that range from 100 Ω to 4 MΩ, with a sensitivity of 0.4mV/ppm and the worst relative error of 2.6%. The capacitive measurement range is from 100pF to 100 μF with the worst relative error of 3.3%. The entire data processing and the PR algorithms run on Raspberry Pi (R-Pi), which is integrated into the E-Nose system. The system performance is tested with MEMS cantilevers for the detection of explosive compounds, such as TNT and its derivatives, RDX and PETN in a controlled environment at a concentration that was as low as 16ppb TNT, 56ppb RDX and 134ppb of PETN. Measurements show that the E-Nose can detect explosives with 77% as true positive results without considering the environmental and mixed vapor effects.

Simultaneous measurement of the surface shape and thickness for an optical flat with a wavelength-tuning Fizeau interferometer with suppression of drift error.

Two types of phase-shifting algorithms were developed for simultaneous measurement of the surface and thickness variation of an optical flat. During wavelength tuning, phase-shift nonlinearity can cause a spatially nonuniform error and spatially uniform DC drift error. A 19-sample algorithm was developed that eliminates the effect of the spatially uniform error by expanding the 17-sample algorithm with characteristic polynomial theory. The 19-sample algorithm was then altered to measure the surface shape of the optical flat by rotation of the characteristic diagram. The surface shape and thickness variation were measured with these two algorithms and a wavelength-tuning Fizeau interferometer.

Photonic phase shifter with full tunable range and multi-band frequency-conversion feature based on a PDM-DPMZM

In this paper, a novel photonic phase shifter with − 180° to 180° phase-tunable range and multi-band frequency-conversion feature is proposed. The main device is a single polarization division multiplexing dual-parallel Mach–Zehnder modulator (PDM-DPMZM). The PDM-DPMZM is employed to generate an optical frequency comb (OFC) and a carrier-suppressed single sideband (CS-SSB) in two mutually orthogonal polarizations. Simultaneously, an electrical phase shifter is adopted to control the initial phase of the CS-SSB. The simulation results show, a RF signal with the frequency of 4.3 GHz (C-band) can be down-converted to 1.4 GHz (L-band). Meanwhile, it can also be up-converted to 5.7 GHz (C-band), 10 GHz (LO signal), 14.3 GHz (Ku-band) and 18.6 GHz (K-band) with their phases continuously tuned from − 180° to 180°. Furthermore, the proposed structure features flat power response, frequency-independent operation, simple configuration, easy phase tuning, better ability to cope with DC drift and wide operation bandwidth. The unwanted signal suppression ratio (USSR) and the spurious free dynamic range (SFDR) of the phase shifter are also studied.

Reduced Sensor-Based PMSM Driven Autonomous Solar Water Pumping System

The nonlinear <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V–I</i> characteristic of solar cell, calls for the use of maximum power point tracking (MPPT) method in order to obtain optimum power from solar photovoltaic (PV) array. Conventional MPPT methods require one voltage and one current sensor. This paper proposes a novel single sensor-based MPPT technique for a PV array fed water pumping using a permanent magnet synchronous motor (PMSM) drive. As the use of encoders, is not preferred for submersible water pumping, this paper uses a sensorless speed and position estimation for speed control of PMSM. The estimation of rotor speed and position, is achieved through the estimation of stator flux from voltages and currents in stationary reference frame. As the conventional flux estimators suffer from the problems, such as saturation, dc drift, and distortion, this paper proposes a mix multi-resonant structure for flux estimation. A sensorless speed control decreases the cost and improves the reliability of the solar water pumping system. The energy extracted from the PV array, is used to drive the PMSM, which rotates the pump coupled to it. Suitability of the proposed system is demonstrated under varying insolation conditions through a prototype developed in the laboratory and utilizing a digital signal processor (dSPACE-1202) for controlling the SWP system.

Electrochemical noise signals evaluation to classify the type of corrosion using Synchrosqueezing transform

In this research, the corrosion type evaluation on the 6061-T6 aluminum alloy exposed to three different solutions using the Electrochemical Noise (EN) technique evaluated by the Synchrosqueezing Transform (SST), and the Shannon energy (SSE) methods is presented. The solutions used for the tests were Sulfuric Acid (15% H2SO4), Sodium Chloride (3.5% NaCl), and demineralized Water (diH2O), these solutions were chosen to evaluate the type of corrosion because of each one of them produces a different corrosion type on the Aluminum alloy. To carry out the evaluation, firstly, the EN signals (Electrochemical Potential Noise (EPN) and Electrochemical Current Noise (ECN)) are obtained from probes. After, these signals are evaluated by the SST-SSE method without removing the DC drift. Finally, the EPN and ECN are evaluated using only the SST method. To show the effectiveness of the SST-SSE and SST methods, a comparison with the Wavelet Transform and the Localization Index is carried out.

Gopinath Model-Based Voltage Model Flux Observer Design for Field-Oriented Control of Induction Motor

For field-oriented control (FOC) of induction motors, accurate estimation of flux is important. Among the various flux estimation methods, the voltage model flux observer exhibits superior performance in situations where there is detuning of rotor parameters, such as rotor resistance and mutual inductance, because this model is robust to the detuning of these parameters. However, it is difficult to implement the voltage model, which includes pure integration, because of the dc saturation and dc drift problems. A number of methods have been developed to overcome this problem, including the Gopinath model flux observer, which can completely solve these problems. However, this model has a critical weakness in terms of parameter sensitivity in the mid-speed region because of the property of its characteristic function. In this paper, an analysis of parameter sensitivity of existing flux observers is discussed. A method for a voltage model flux observer design based on the Gopinath model is presented. Through an analysis of the characteristic function of the observer, the voltage model is designed. Finally, the operation of the proposed method is proven by simulations and experiments.

Improved Closed-Loop Flux Observer Based Sensorless Control Against System Oscillation for Synchronous Reluctance Machine Drives

Flux-linkage based sensorless control method is well-known and has been widely used in the control of electrical machines. The closed-loop flux observer (CLFO), which is the adaptive combination of the machine voltage and current models, is commonly adopted. It can cover a wide speed operation range and was considered to be able to solve the dc drift and initial value problem associated to the pure integrator used in the observer. However, it is reported in this paper that this popular CLFO cannot always work as expected. In some situations, dc-offsets cannot be removed by this flux observer, causing large system oscillation at fundamental frequency and is very harmful to the drive system. This important issue has not been reported and discussed in the existing literatures of the CLFO. In this paper, this phenomenon is experimentally illustrated and solution to damp this harmful oscillation is proposed and verified experimentally on a synchronous reluctance machine drive system.

Control system for automated drift compensation of the stand-alone charge amplifier used for low-frequency measurement

A charge amplifier is an electronic current integrator that is frequently employed for converting electrical charges or electrical currents into voltage signals. The charge amplifier is very sensitive to DC drift, since the DC component in the input signal leads to a steady accumulation of charge in the feedback capacitor until the output voltage saturates. Various solutions for automated drift reduction have been proposed, but they either (i) disable measurements of low-frequency signals (mHz range), (ii) non-deterministically reset the charge amplifier output voltage, (iii) cannot compensate for high value drifts (above V/s), or (iv) have a high closed-loop time constant, which decreases the disturbance rejection performance and increases settling time. In this paper, we present a control system for automated drift compensation of the charge amplifier periodic output voltage, which solves the aforementioned problems. The proposed solution (i) efficiently rejects disturbances, (ii) offers fast settling time without affecting the measurement accuracy, (iii) can compensate for drift in a large range (up to tens of V/s), and (iv) is low-cost. The presented solution was tested on a charge amplifier that is part of a custom-made dedicated measurement system for automated high-temperature and low-frequency polarization measurements of dielectric materials. The presented results indicate that the proposed automatic control system efficiently compensates for the drift component of the charge amplifier without affecting the measurement precision. Most importantly, with the modifications presented in this manuscript, this system can be easily adapted for other charge amplifier periodic measurement usage examples.

DC Drift Error Mitigation Method for Three-Phase Current Reconstruction With Single Hall Current Sensor

Magnetic field sensors, such as Hall current sensors, are widely used in permanent-magnet synchronous motors drive system. For the purpose of reducing cost and volume, the phase current reconstruction method is used in the motor drive system with only one current sensor. In this paper, a novel phase current reconstruction method is introduced. By arranging the single current sensor at a novel position, the proposed method is able to sample current in two zero voltage vectors. Then, a novel dc drift error mitigation method is proposed to eliminate the dc drift error in the Hall current sensor, which can influence the motor drive performance. The Clarke coordinate transformation is modified to decouple the dc drift error in the α-β-axis current components. Then, a notch filter is adapted to estimate the dc drift component of the current sampling results, which can compensate the dc drift error in the Hall current sensor. The proposed method is validated by both simulation and experiments.

Flow and clogging of particles in shaking random obstacles.

Transport of three types of particles (passive particles, active particles, and polar particles) is investigated in a random obstacle array in the presence of a dc drift force. The obstacles are static or synchronously shake along the given direction. When the obstacles are static, the average velocity is a peaked function of the dc drift force (negative differential mobility) for low particle density, while the average velocity monotonically increases with the dc drift force (positive differential mobility) for high particle density. Under the same conditions, passive particles are most likely to pass through the obstacles, while polar particles are easily trapped by the obstacles. The polar alignment can strongly reduce the overall mobility of particles. When the obstacles shake along the given direction, the optimal shaking frequency or amplitude can maximize the average velocity. It is more effective to reduce clogging for the transverse shaking than that for the longitudinal shaking.

Implementation Issues of Flux Linkage Estimation on Permanent Magnet Machine Position Sensorless Drive at Low Speed

This paper improves the surface permanent magnet (PM) machine position sensorless drive at low speed. Considering the surface PM machine (SPM) drive, EMF voltage or flux linkage should be estimated for the sensorless drive. Different from EMF voltage, the flux linkage based on the voltage integration is theoretically independent to speed which is suited for the low speed position estimation. In this paper, several improvements on the flux-based sensorless drive are proposed to enhance the low speed dynamic performance. First, a modified voltage integration is develop to remove the flux estimation drift caused by voltage or current offset. This integration contains a high-pass filter (HPF) for the DC drift elimination. In addtion, the filter delay is compensated to maintain the flux phase. Second, inverter deadtime harmonics are decoupled with the knowledge of actual machine phase voltages. It is shown that the position estimation error is decreased for the better low speed performance. According to experimental results, SPM machine sensorless drive is enhanced at 4%~6% speed region from many aspects. They include position signal SNR, position error and drive dynamic response. More importantly, the overall current regulation bandwidth can increase to 1kHz at low speed. It is compatible to standard encoder-based field oriented control (FOC) drives.

Patterning-effect mitigating intensity modulator for secure decoy-state quantum key distribution.

Quantum key distribution (QKD) is a technology that allows two users to exchange cryptographic keys securely. The decoy state technique enhances the technology, ensuring keys can be shared at high bit rates over long distances with information theoretic security. However, imperfections in the implementation, known as side-channels, threaten the perfect security of practical QKD protocols. Intensity modulators are required for high-rate decoy-state QKD systems, although these are unstable and can display a side channel where the intensity of a pulse is dependent on the previous pulse. Here we demonstrate the superior practicality of a tunable extinction ratio Sagnac-based intensity modulator (IM) for practical QKD systems. The ability to select low extinction ratios, alongside the immunity of Sagnac interferometers to DC drifts, ensures that random decoy state QKD patterns can be faithfully reproduced with the patterning effects mitigated. The inherent stability of Sagnac interferometers also ensures that the modulator output does not wander over time.

Fuzzy Logic Enhanced Direct Torque Control with Space Vector Modulation

Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC–SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness. &lt;p class="MsoNormal" style="text-align: justify; text-indent: 36.0pt;"&gt;&lt;span style="font-size: 9.0pt; font-family: 'Arial','sans-serif'; color: black;" lang="EN-US"&gt;Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (V&lt;sub&gt;d&lt;/sub&gt;, V&lt;sub&gt;q&lt;/sub&gt;). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC–SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness. &lt;/span&gt;&lt;/p&gt;

Synthesis and study the physical properties of the nanosized Li0.5AlxFe2.5-xO4 samples

Nanoparticles of Li0.5AlxFe2.5-xO4 (x = 0.00, 0.15, 0.25, 0.35, 0.45) have been synthesized by using a chemical auto-combustion method. The effect of varying Al3+ ions content on the microstructure, magnetic, thermal, and dc electrical conductivity, mobility and activation energy of the as-prepared nanosamples have been studied. The obviously low loss thin hysteresis curve of the M-H relation reveals that the present materials are classified soft magnetic. The dependence of magnetic properties on adding Al3+ ions is explained as due to many factors such as crystallite size, measured density, porosity, expected cation distribution, and magnetocrystalline anisotropy. The cation distributions for all samples have been suggested such that the experimental and theoretical values of magnetic moments and lattice constants are in good consistency. Moreover, the pure Li-ferrite sample of (x = 0) has lower values of thermal conductivity, specific heat capacity, and thermal effusivity; and higher values of thermal diffusivity than those of the Al substituted Liferrite samples. The reasons of this behavior have been discussed. Also, the temperature and the chemical composition dependence of dc conductivity and drift mobility of the prepared samples have been studied.