Development of Electrostatic Microactuators: 5-Year Progress in Modeling, Design, and Applications

The implementation of electrostatic microactuators is one of the most popular technical solutions in the field of micropositioning due to their versatility and variety of possible operation modes and methods. Nevertheless, such uncertainty in existing possibilities creates the problem of choosing suitable methods. This paper provides an effort to classify electrostatic actuators and create a system in the variety of existing devices. Here is overviewed and classified a wide spectrum of electrostatic actuators developed in the last 5 years, including modeling of different designs, and their application in various devices. The paper provides examples of possible implementations, conclusions, and an extensive list of references.

Deep Q-Learning in Robotics: Improvement of Accuracy and Repeatability

Recent industrial robotics covers a broad part of the manufacturing spectrum and other human everyday life applications; the performance of these devices has become increasingly important. Positioning accuracy and repeatability, as well as operating speed, are essential in any industrial robotics application. Robot positioning errors are complex due to the extensive combination of their sources and cannot be compensated for using conventional methods. Some robot positioning errors can be compensated for only using machine learning (ML) procedures. Reinforced machine learning increases the robot’s positioning accuracy and expands its implementation capabilities. The provided methodology presents an easy and focused approach for industrial in situ robot position adjustment in real-time during production setup or readjustment cases. The scientific value of this approach is a methodology using an ML procedure without huge external datasets for the procedure and extensive computing facilities. This paper presents a deep q-learning algorithm applied to improve the positioning accuracy of an articulated KUKA youBot robot during operation. A significant improvement of the positioning accuracy was achieved approximately after 260 iterations in the online mode and initial simulation of the ML procedure.

Air Quality Effects on Human Health and Approaches for Its Assessment through Microfluidic Chips

Air quality depends on the various gases and particles present in it. Both natural phenomena and human activities affect the cleanliness of air. In the last decade, many countries experienced an unprecedented industrial growth, resulting in changing air quality values, and correspondingly, affecting our life quality. Air quality can be accessed by employing microchips that qualitatively and quantitatively determine the present gases and dust particles. The so-called particular matter 2.5 (PM2.5) values are of high importance, as such small particles can penetrate the human lung barrier and enter the blood system. There are cancer cases related to many air pollutants, and especially to PM2.5, contributing to exploding costs within the healthcare system. We focus on various current and potential future air pollutants, and propose solutions on how to protect our health against such dangerous substances. Recent developments in the Organ-on-Chip (OoC) technology can be used to study air pollution as well. OoC allows determination of pollutant toxicity and speeds up the development of novel pharmaceutical drugs.

Greenhouse Gas Molecule CO2 Detection Using a Capacitive Micromachined Ultrasound Transducer

We manufactured and tested a capacitive micromachined ultrasound transducer (CMUT)-based sensor for CO2 detection at environmentally relevant concentrations using polyethylenimine as a CO2 binding material. The assembly of a sensing chip was 10 × 20 mm, and up to 5 gases can potentially be detected simultaneously using a masking technique and different sensing materials. The limit of detection was calculated to be 0.033 CO2 vol % while the limit of quantification was calculated to be 0.102%. The sensor exhibited a linear response between 0.06% and 0.30% CO2 while concentrations close to those in flue gas can also be measured using dilution with inert gas.

Capacitive micromachined ultrasound transducer (cMUT) for immunosensor design

An affinity sensor based on a capacitive micromachined ultrasound transducer (cMUT) is reported by this Communication. The cMUT micromembrane arrays modified with adsorbed bovine leukemia virus protein gp51 were applied as a biological recognition part. The cMUT-based sensor is shown to be sensitive to the antibodies against bovine leukemia virus protein gp51 (anti-gp51). Two different concentrations of anti-gp51-containing samples and one blank sample without anti-gp51 were tested. The sensitivity of cMUT-based immunosensor is comparable with the sensitivity of a quartz microbalance-based immunosensor. The cMUT array provides a multi-channel system for the measurement of analytical signal. Moreover, two different characteristics--the resonance frequency shift (Deltaf) and the shift of the real part of the electromechanical impedance (DeltaRe)--could have been evaluated simultaneously. Both analytical signals are informative and can be applied for the estimation of immune complex formation. We found the performance of such a system being potentially superior over some other immunosensing techniques. It is more rapid than electrochemical techniques and provides two different informative parameters.