Microsystem Technologies最新文献

The research presents an enhanced energy detector using windowing groups, machine learning, and parallel Fast Fourier Transforms to alleviate spectrum congestion in fifth-generation wireless services. Specifically designed for non-stationary signals with low signal-to-noise ratios, this technique addresses key challenges by improving Detection Probability (Pd) and augmenting FFT resolution. By applying specific weighting factors to samples within the sensing frame, the Probability of Detection (Pd) is increased. The Machine Learning algorithm dynamically adjusts the weighting factor multipliers based on the prevailing signal-to-noise conditions. Implementing parallel FFTs for sample groups further enhances resolution. Diverse windowing methods and grouping strategies significantly boost detection probability, especially for non-stationary signals under low SNRs. Compared to the conventional energy detector with 56% detection probability, the proposed method achieves 76–97% probability at − 15 dB SNR proving its efficiency in improving signal detection under challenging conditions.

This paper represents the design and simulation of tunable bandstop filters by integrated with an RF MEMS shunt switch. The transformation of the bandpass filter to the bandstop filter is also done in this paper. The bandpass and bandstop filters are designed utilizing ECE-shaped DGS resonators within the coplanar waveguide (CPW) structure. Three different types of RF MEMS switches are proposed and investigated. The switch with low pull in voltage and better RF characteristics is considered for integration with filters The BPF exhibits an insertion loss of under 1.6 dB. It offers a relative 3-dB bandwidth of 60% and a 30-dB bandwidth of 77%. In the case of the BSF, it effectively achieves a 20 dB stop band at 20.5 GHz, maintaining a return loss of only 0.3 dB. The tunability of the filter is observed by integrating a MEMS capacitive shunt switch onto the transmission line. A pull in voltage of 4 V is achieved with a high capacitance ratio of 63.9.The simulation and parametric analysis of the RF MEMS switch is carried out by COMSOL and the RF performance of the switch, tunability of the filters are studied with the help of the HFSS FEM tools. The mechanical resonance frequency, other RF performance and tunability of the filters attained a frequency range (18–27 GHz). So the proposed switch and filters are suitable for K band applications, especially for satellite communications applications.

A major limitation of most linear motors is limited travel range and low load capacity. In this research, a large motion range piezoelectric Inchworm Motor (IM) is realised which not only harnesses the prominent advantages of piezo-actuator but the four-legged design simultaneously offers reliable self-locking capability in a compact form-factor. The displacement deformation of each element of the motor (clamps, extender) is determined using finite element analysis (FEA) through force distribution analysis. Appropriate clamping force adjustment method on the rail/stator of the motor is adopted using load cell followed by multiple linear regression modelling to dynamically consider the clamping force and inherent non-linearities of piezo-actuators (PAs). The hardware prototype is fabricated and the experiment results verify the validity of the data driven model. Clamping error analysis, step length dependent stability profile and dynamic driving force has been carried out to characterize the IM. Performance evaluation of the motor has been researched at different voltages, frequencies and loads to assess its operating profile. Mechanical output suggests that the prototype achieves a maximum no load speed of 39.64 mm/sec under clamping force of 2 N at 100 V and frequency of 2000 Hz with 30% duty cycle. With load of 700 g, 0.46 mm/sec speed is obtained under a clamping force of 8 N. In addition, bidirectional control signal mechanism for the IM has been also developed, tested and implemented in real-time environment. The proposed large driving force prototype designed is highly suitable for industrial linear translation systems requiring high resolution, large strokes, and heavy loads capacities.

The flexible ultrasonic scalpels are currently required for surgical treatment of deep-seated areas of the living body. One of the surgical treatments for early-stage gastric cancer is surgery to remove the superficial layers of the stomach. Endoscopic surgery is used for early-stage gastric cancer. Polypectomy, one of the endoscopic surgical methods, involves hooking a snare over the affected area, squeezing, and applying a high-frequency electric current to burn it off. On the other hand, ultrasonic scalpels are effective at lower temperatures than conventionally used electrocautery scalpels, and have the advantage of having less thermal effect on tissues other than the affected area. However, due to the challenges associated with the propagation of ultrasonic waves, the use of flexible wires for this purpose in current research is limited. In this study, we attempted to observe the characteristics of ultrasonic wave propagation to the wire in the snare, which is a part of the electrocautery used in the polypectomy. The development of flexible ultrasonic scalpels will be advanced when ultrasonic propagation with less energy loss to the strand wire can be realized. In addition, Finite Element Method analysis was performed to identify the heat sources generated when ultrasonic vibration is applied to a stranded wire and to investigate a solution. Additionally, to find conditions where ultrasonic energy propagation is strong and heat generation is minimal, the partial single lines model was examined. The analysis confirmed that heat was generated by friction between strands of stranded wire.

Micro-hotplates have provided the possibilities of miniaturization, low power consumption, and high integration for widespread application in MEMS sensors, such as the MEMS-based metal oxide gas sensors. However, thermal crosstalk among micro-heating areas has greatly restricted the design of a micro-hotplate. Although the issue of thermal crosstalk is annoying between independent working areas, it can reduce power consumption to a certain extent. This paper proposed a dual working area micro-hotplate based on thermal crosstalk through the foundation of an electro-thermal analysis model. It especially proposes a strategy of introducing optimized parameters from a single working area to a dual working area. Besides, evaluation for thermal crosstalk was achieved by setting the temperature of one working area as constant and monitoring the power of the other working area when it reaches a certain temperature. The results indicated that the designed dual working area micro-hotplate can save at least a quarter of the heating power compared with the single working area micro-hotplate at the same working temperature of 300 (^circ textrm{C}) and other same parameter settings. Within the acceptable limits of mechanical deformation, the heating efficiency of the micro-hotplate is improved from 4.10 mW/(mm(^2).(^circ textrm{C})) to 2.99 mW/(mm(^2) (^circ textrm{C})). It was demonstrated that the introduction of thermal crosstalk can significantly reduce the power consumption of the micro-hotplate, providing a viable solution for enhancing the properties of MOX gas sensor array.

Kenics static mixer (KSM), which comprises helical blades twisted 180° in left and right-hand directions alternatively and connected 90° to each other, has been widely used in macroscale because of its excellent mixing performance. Despite the high mixing efficiency, it is hard to apply in microscale conditions since it is difficult to fabricate the helical blades with conventional manufacturing methods and still mainly stays in the simulation stage. In this study, the Inkjet 3D printing method, which provides a rapid and cost-effective manufacturing method in one step without considering the complex three-dimensional structures for microfluidics, was adopted to build the Kenics static mixer and the Fibonacci’s golden ratio theory that caused a small pressure loss in spiral motion was introduced into the helical blade design. Both simulations and experiments were conducted to characterize the mixing performance of the 3D printed KSM and compared with the slanted groove micromixer (SGM) and Y-shaped micromixer. The results demonstrated the superiority (mixing efficiency > 90%) of the 3D printed KSM proposed in this study.

The installation of Renewable Energy Sources (RESs) has increased tremendously over the past few decades. Due to the large-scale grid integration of RESs, many countries have had to modify their grid codes. For smooth operation during contingencies, the grid code mandates Low Voltage Ride-Through (LVRT) operation of the inverter, requiring it to remain connected for a stipulated duration and provide necessary support to the grid. In this article, an Instantaneous Power Theory-Fuzzy Intelligent Controller (IPT-FIC) based improved LVRT strategy is implemented to control a grid-connected Photovoltaic (PV) inverter. This enhanced strategy efficiently provides the necessary active and reactive power support to the grid during faults or voltage sags. The IPT-FIC is proposed to make the controller intelligent, accurate, and faster. Simulations were performed in a MATLAB/SIMULINK 2021 environment, and the feasibility of the proposed technique was verified through the dSPACE DS1103 driven Hardware-in-the-Loop (HIL) platform, achieving an accuracy level of 96.67%. The proposed technique improves system response time during transient scenarios by 19.88%. The technique ensures the active power loss is limited to 7.91% during LVRT operation while maintaining a very low ride-through time.

The development of flexible capacitive pressure sensors has recently drawn significant interest among researchers for emerging wearable electronic devices, monitoring applications, and smart systems. However, it still poses enormous difficulty to design capacitive sensors with excellent sensitivity. Few studies have reported the use of interdigitated electrodes (IDE) designs to improve the sensitivity of sensors. In our study, we selected graphene-infused natural rubber (NRG) as the sensing dielectric layer owing to its excellent cyclic pressure loading response as well as its high flexibility and conductivity. Here, we reported the impedance response of different graphene contents in natural rubber (NR) with the optimization of different geometrical parameters of IDEs. The electrical properties of silver IDEs are simulated using COMSOL Multiphysics. The impedance characteristics of NRG and its capability for detecting a wide variety of pressures and bending angles are analyzed using a Digilent Analog Discovery impedance analyzer. Understanding these properties and how they can be affected is vital in designing highly sensitive capacitive pressure sensors. Simulations were used to show the voltage potential, electrical field, and capacitance developed between the individual digits of the electrodes. The impedance analysis was helpful in computing the electrical conductivity of the NRG. The impedance analysis showed that the NRG sensing material improved in conductivity (≈0.006 S/m) and capacitance (≈0.30 pF) with a graphene loading of 5 wt.%. In this novel work, a capacitive-based pressure sensor incorporating unvulcanized NR and 5 wt.% graphene nanoplatelet as the sensing material was successfully fabricated with a sensor sensitivity of 0.004 kPa⁻¹ for the low-force detection region of 40 kPa.

A highly sensitive and novel antenna sensor is designed for evaluating concentration of glucose in the human blood. The proposed sensor is constructed on an FR4 substrate layer of dimensions 20 mm × 30 mm × 1.6 mm with dielectric constant value of 4.3 resonance at 5 GHz with a quality factor of 471. In order to predict the amount of glucose, a human finger phantom model is developed in the electromagnetic simulator. The glucose levels are varied in various degrees from 0 to 1000 mg/dL and the resulting frequency shifts are measured by placing the phantom at various locations at different angles on the developed antenna sensor. When the phantom is located at 0⁰ on the proposed sensor, a total frequency shift of 24 MHz, FDR of 24 kHz/(mg/dL) and sensitivity of 0.48x({10}^{-3}{(mg/dL)}^{-1}) are observed enabling the proposed sensor to detect diabetic conditions in the patients with high precision. The performance of the proposed sensor is analyzed for different real human finger positions and the resulting resonant frequencies are measured to verify the sensor’s performance in real-time scenario. The proposed sensor shows the average measurement error of about 1.9875% to detect glucose concentration levels.

In the field of control engineering, there has been a growing emphasis on systems with feedback loops that involve stochastic factors. Simultaneously, with the advancements in probability theory, feedback loops with stochastic processes have gained practicality due to their customizability and the potential for practical applications. Essentially, the effect of adding additive random signals in linear feedback systems can be viewed as the introduction of filtered stochastic noise. However, when random signals enter the feedback loop multiplicatively, a richer set of state behaviors emerges. This study utilizes multiplicative feedback loops to construct Markov chains and provides a probabilistic modeling approach to investigate the stability and asymptotic behavior of Markov feedback loops, offering insights for microsystems. This paper derives properties of such stochastic processes and provides corresponding theoretical proofs. The theoretical foundation of this probabilistic modeling can be applied in economics, biological variation processes, epidemic control predictions, and linear perturbation models, offering a theoretical perspective for feedback systems with uncertain triggers.