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The demand to detect toxic arsenic ions in water is increasing due to uncontrolled industrial and human activities. Conventional detection methods are found to be very complex, cumbersome, and nonportable. Here, we propose a novel reduced graphene oxide (RGO)–Fe3O4–leucine-based device with high sensitivity and stability for selective detection of arsenic ions in water. The operating voltage of the device is 2 V, which ensures low power consumption. Fe3O4 and leucine impart a high degree of selectivity toward arsenic ions, and RGO ensures a high surface-to-volume ratio for adsorption. The device is tested against eight metal ions, which are common water contaminants and found to be highly sensitive toward arsenic. The sensitivity of the RGO–Fe3O4–leucine-based device toward arsenic is found to be 140 nA/ppb, which is very high compared to the other ions. The sensor device exhibits a response time of 21 s and is highly stable against adverse humid conditions. The sensor shows high resilience in the degradation of sensing performance for 40 days. Therefore, the RGO–Fe3O4–leucine-based device shows promising results to be used in future portable, low cost, and user-friendly arsenic ion detector systems.

Rapid development of intelligent transportation demands accurate methods for monitoring vehicle overload information. This paper reports a detail analysis on the viability of triboelectric nanogenerator (TENG) as a smart traffic monitoring system. PVDF and silk film were exploited for TENG fabrication for their strong penchant of gaining and loosing electrons. The objective of this paper is two fold. Initially the electrical performance of the fabricated prototype was measured and reported. The prototype exhibited a maximum open circuit voltage of 648 V and an instantaneous power density of 24 mW/mm2. It was also capable to light up 75 commercial green LEDs. Furthermore, a TENG based traffic monitoring system was introduced for monitoring the traffic overload information and for counting the number of vehicles rolled on it. The TENG was used to convert the mechanical energy from the rolling of vehicles into electric pulses. The pulses that were generated by the TENG was incorporated into an interfacing circuit to anticipate the number of vehicles passed by it. The amplitude of those pulses also give a valuable information regarding the weight of vehicles as the generated voltage is proportional to the input force. Different output voltages of 207 V, 367 V and 558 V were produced for different types of vehicles like bicycle, motorbike and four wheeler passenger vehicle respectively depending on their mass. Output voltage was also varied depending on the load carried by vehicles and showed an increasing trend with load. In consequence, the proposed system can substantially be implemented at various automotive toll plazas to corroborate the paid tax and the actual tax that is supposed to be paid on the basis of laden weight of the vehicle.