An Unmanned Surface Vehicle (USV): Development of an Autonomous Boat with a Sensor Integration System for Bathymetric Surveys.

A reliable yet economical unmanned surface vehicle (USV) has been developed for the bathymetric surveying of lakes. The system combines an autonomous navigation framework, environmental sensors, and a multibeam echosounder to collect submerged topography, temperature, and wind speed and monitor the vehicle's status during prescribed path-planning missions. The main objective of this research is to provide a methodological framework to build an autonomous boat with independent decision-making, efficient control, and long-range navigation capabilities. Integration of sensors with navigation control enabled the automatization of position, orientation, and velocity. A solar power integration was also tested to control the duration of the autonomous missions. The results of the solar power compared favorably with those of the standard LiPO battery system. Extended and autonomous missions were achieved with the developed platform, which can also evaluate the danger level, weather circumstances, and energy consumption through real-time data analysis. With all the incorporated sensors and controls, this USV can make self-governing decisions and improve its safety. A technical evaluation of the proposed vehicle was conducted as a measurable metric of the reliability and robustness of the prototype. Overall, a reliable, economic, and self-powered autonomous system has been designed and built to retrieve bathymetric surveys as a first step to developing intelligent reconnaissance systems that combine field robotics with machine learning to make decisions and adapt to unknown environments.

Non-Invasive Glucose Monitoring Using Optical Sensor and Machine Learning Techniques for Diabetes Applications.

Diabetes is a major public health challenge affecting more than 451 million people. Physiological and experimental factors influence the accuracy of non-invasive glucose monitoring, and these need to be overcome before replacing the finger prick method. Also, the suitable employment of machine learning techniques can significantly improve the accuracy of glucose predictions. One aim of this study is to use light sources with multiple wavelengths to enhance the sensitivity and selectivity of glucose detection in an aqueous solution. Multiple wavelength measurements have the potential to compensate for errors associated with inter- and intra-individual differences in blood and tissue components. In this study, the transmission measurements of a custom built optical sensor are examined using 18 different wavelengths between 410 and 940 nm. Results show a high correlation value (0.98) between glucose concentration and transmission intensity for four wavelengths (485, 645, 860 and 940 nm). Five machine learning methods are investigated for glucose predictions. When regression methods are used, 9% of glucose predictions fall outside the correct range (normal, hypoglycemic or hyperglycemic). The prediction accuracy is improved by applying classification methods on sets of data arranged into 21 classes. Data within each class corresponds to a discrete 10 mg/dL glucose range. Classification based models outperform regression, and among them, the support vector machine is the most successful with F1-score of 99%. Additionally, Clarke error grid shows that 99.75% of glucose readings fall within the clinically acceptable zones. This is an important step towards critical diagnosis during an emergency patient situation.

Enhanced Controllability of Fries Rearrangements Using High-Resolution 3D-Printed Metal Microreactor with Circular Channel.

High-resolution 3D-printed stainless steel metal microreactors (3D-PMRs) with different cross-sectional geometry are fabricated to control ultrafast intramolecular rearrangement reactions in a comparative manner. The 3D-PMR with circular channel demonstrates the improved controllability in rapid Fries-type rearrangement reactions, because of the superior mixing efficiency to rectangular cross-section channels (250 µm × 125 µm) which is confirmed based on the computational flow dynamics simulation. Even in case of very rapid intramolecular rearrangement of sterically small acetyl group occurring in 333 µs of reaction time, the desired intermolecular reaction can outpace to the undesired intramolecular rearrangement using 3D-PMR to result in high conversion and yield.

High Sensitivity, Wearable, Piezoresistive Pressure Sensors Based on Irregular Microhump Structures and Its Applications in Body Motion Sensing.

A pressure sensor based on irregular microhump patterns has been proposed and developed. The devices show high sensitivity and broad operating pressure regime while comparing with regular micropattern devices. Finite element analysis (FEA) is utilized to confirm the sensing mechanism and predict the performance of the pressure sensor based on the microhump structures. Silicon carbide sandpaper is employed as the mold to develop polydimethylsiloxane (PDMS) microhump patterns with various sizes. The active layer of the piezoresistive pressure sensor is developed by spin coating PEDOT: PSS on top of the patterned PDMS. The devices show an averaged sensitivity as high as 851 kPa(-1) , broad operating pressure range (20 kPa), low operating power (100 nW), and fast response speed (6.7 kHz). Owing to their flexible properties, the devices are applied to human body motion sensing and radial artery pulse. These flexible high sensitivity devices show great potential in the next generation of smart sensors for robotics, real-time health monitoring, and biomedical applications.

Droplet-based electro-coalescence for probing threshold disjoining pressure.

In this work, we investigate the coalescence of emulsion droplets in a controlled electric field. Two contacting droplets stabilized by surfactants can be forced to coalesce into a combined one when the applied voltage is above a critical value. The critical voltages change with the types, concentrations of surfactants and temperature. By exploring the drainage of a thin oil film trapped between emulsions, we interpret that the coalescence occurs as the electric compression overcomes the disjoining pressure barrier and squeezes the film to a critical thickness. Based on this, we have devised an approach to probe the threshold disjoining pressure which can help predict the emulsion stability and surfactant efficacy quantitatively. We have confirmed the validity of our approach for measuring the threshold disjoining pressure by comparing the result with other proven tests that involve centrifugation and thermal heating. Our approach is simple, reliable and robust in predicting emulsion stability and will facilitate the design of emulsion-based formulations by accelerating the testing of emulsion stability.

Inkjet-printed microelectrodes on PDMS as biosensors for functionalized microfluidic systems.

Microfluidic systems based on polydimethylsiloxane (PDMS) have gained popularity in recent years. However, microelectrode patterning on PDMS to form biosensors in microchannels remains a worldwide technical issue due to the hydrophobicity of PDMS and its weak adhesion to metals. In this study, an additive technique using inkjet-printed silver nanoparticles to form microelectrodes on PDMS is presented. (3-Mercaptopropyl)trimethoxysilane (MPTMS) was used to modify the surface of PDMS to improve its surface wettability and its adhesion to silver. The modified surface of PDMS is rendered relatively hydrophilic, which is beneficial for the silver droplets to disperse and thus effectively avoids the coalescence of adjacent droplets. Additionally, a multilevel matrix deposition (MMD) method is used to further avoid the coalescence and yield a homogeneous pattern on the MPTMS-modified PDMS. A surface wettability comparison and an adhesion test were conducted. The resulting silver pattern exhibited good uniformity, conductivity and excellent adhesion to PDMS. A three-electrode electrochemical biosensor was fabricated successfully using this method and sealed in a PDMS microchannel, forming a lab-on-a-chip glucose biosensing system.

High performance organic transistor active-matrix driver developed on paper substrate.

The fabrication of electronic circuits on unconventional substrates largely broadens their application areas. For example, green electronics achieved through utilization of biodegradable or recyclable substrates, can mitigate the solid waste problems that arise at the end of their lifespan. Here, we combine screen-printing, high precision laser drilling and thermal evaporation, to fabricate organic field effect transistor (OFET) active-matrix (AM) arrays onto standard printer paper. The devices show a mobility and on/off ratio as high as 0.56 cm(2)V(-1)s(-1) and 10(9) respectively. Small electrode overlap gives rise to a cut-off frequency of 39 kHz, which supports that our AM array is suitable for novel practical applications. We demonstrate an 8 × 8 AM light emitting diode (LED) driver with programmable scanning and information display functions. The AM array structure has excellent potential for scaling up.