Surface nanostructuring of alkali-aluminosilicate Gorilla display glass substrates using a maskless process.

This paper reports on the formation of moth-eye nanopillar structures on surfaces of alkali-aluminosilicate Gorilla glass substrates using a self-masking plasma etching method. Surface and cross-section chemical compositions studies were carried out to study the formation of the nanostructures. CFxinduced polymers were shown to be the self-masking material during plasma etching. The nanostructures enhance transmission at wavelengths over 525 nm may be utilized for fluid-induced switchable haze. Additional functionalities associated with nanostructures may be realized such as self-cleaning, anti-fogging, and stain-resistance.

Multiplexable intrinsic Fabry-Perot interferometric fiber sensors for multipoint hydrogen gas monitoring.

This Letter presents an approach to produce multiplexable optical fiber chemical sensor using an intrinsic Fabry-Perot interferometer (IFPI) array via the femtosecond laser direct writing technique. Using the hydrogen-sensitive palladium (Pd) alloy as a functional sensory material, Pd alloy coated IFPI devices can reproducibly and reversibly measure hydrogen concentrations with a detection limit of 0.25% at room temperature. Seven IFPI sensors were fabricated in one fiber and performed simultaneous temperature and hydrogen measurements at seven different locations. This Letter demonstrates a simple yet effective approach to fabricate multiplexable fiber optical chemical sensors for use in harsh environments.

Machine-Learning Assisted Handwriting Recognition Using Graphene Oxide-Based Hydrogel.

Machine-learning assisted handwriting recognition is crucial for development of next-generation biometric technologies. However, most of the currently reported handwriting recognition systems are lacking in flexible sensing and machine learning capabilities, both of which are essential for implementation of intelligent systems. Herein, assisted by machine learning, we develop a new handwriting recognition system, which can be applied as both a recognizer for written texts and an encryptor for confidential information. This flexible and intelligent handwriting recognition system combines a printed circuit board with graphene oxide-based hydrogel sensors. It offers fast response and good sensitivity and allows high-precision recognition of handwritten content from a single letter to words and signatures. By analyzing 690 acquired handwritten signatures obtained from seven participants, we successfully demonstrate a fast recognition time (less than 1 s) and a high recognition rate (∼91.30%). Our developed handwriting recognition system has great potential in advanced human-machine interactions, wearable communication devices, soft robotics manipulators, and augmented virtual reality.

A new strategy to minimize humidity influences on acoustic wave ultraviolet sensors using ZnO nanowires wrapped with hydrophobic silica nanoparticles.

Surface acoustic wave (SAW) technology has been widely developed for ultraviolet (UV) detection due to its advantages of miniaturization, portability, potential to be integrated with microelectronics, and passive/wireless capabilities. To enhance UV sensitivity, nanowires (NWs), such as ZnO, are often applied to enhance SAW-based UV detection due to their highly porous and interconnected 3D network structures and good UV sensitivity. However, ZnO NWs are normally hydrophilic, and thus, changes in environmental parameters such as humidity will significantly influence the detection precision and sensitivity of SAW-based UV sensors. To solve this issue, in this work, we proposed a new strategy using ZnO NWs wrapped with hydrophobic silica nanoparticles as the effective sensing layer. Analysis of the distribution and chemical bonds of these hydrophobic silica nanoparticles showed that numerous C-F bonds (which are hydrophobic) were found on the surface of the sensitive layer, which effectively blocked the adsorption of water molecules onto the ZnO NWs. This new sensing layer design minimizes the influence of humidity on the ZnO NW-based UV sensor within the relative humidity range of 10-70%. The sensor showed a UV sensitivity of 9.53 ppm (mW/cm2)-1, with high linearity (R 2 value of 0.99904), small hysteresis (<1.65%) and good repeatability. This work solves the long-term dilemma of ZnO NW-based sensors, which are often sensitive to humidity changes.