A comparative study on deposition and molecular regularity of two organosilanes, i.e., commercially available (3-mercaptopropyl)­trimethoxysilane (MPTMS) and newly developed mercaptopropylsilatrane (MPS), was conducted in this work. MPTMS and MPS were applied to modify silicon surfaces to characterize their deposition kinetics, surface morphology, thickness, and elemental composition and the reactivity of thiol end groups based on gold-thiol and thiol-ene chemistries. MPS possesses a tricyclic caged structure and a transannular N → Si dative bond, making it chemically stable and controllable to avoid fast hydrolysis and aggregation in solution. The results indicate that MPS allows faster deposition and better formation of thin and homogeneous films than MPTMS. More importantly, the functional thiol groups on MPS coatings enable immobilization of a large amount of gold nanoparticles and effective thiol-ene photopolymerization with zwitterionic sulfobetaine acrylamide. Postmodification on silanized surfaces with MPS endows excellent plasmonic and antifouling properties, potentially leading to valuable applications to biosensing and biomaterials. The work demonstrated the feasibility and applicability of the functional silatrane molecule for surface silanization in a controlled manner.

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With advancing technology in the miniature microelectromechanical systems (MEMS) sensors, wearable devices are becoming increasingly popular, facilitating convenient activity detection. One particular application is in sports performance monitoring. This article presents a novel real-time jump detection algorithm in skiing and snowboarding using a microelectromechanical systems-based inertial measurement unit, which is integrated with a barometric pressure sensor. The key performance variables of the jump can be extracted and evaluated for training and/or entertainment purposes. In contrast to the existing jump detection algorithms based on acceleration signals, the proposed algorithm uses vertical velocity and air time in addition to acceleration in the vertical direction. The experimental results show that by incorporating the velocity and air time into the detection algorithm, the sensitivity and specificity increase dramatically to 92% and 93%, respectively.