An essential requirement for bio/chemical sensors and electronic nose systems is the ability to detect the intended target at room temperature with high selectivity. We report a reduced graphene oxide (rGO)-based gas sensor functionalized with a peptide receptor to detect dinitrotoluene (DNT), which is a byproduct of trinitrotoluene (TNT). We fabricated the multi-arrayed rGO sensor using spin coating and a standard microfabrication technique. Subsequently, the rGO was subjected to photolithography and an etching process, after which we prepared the DNT-specific binding peptide (DNT-bp, sequence: His-Pro-Asn-Phe-Se r-Lys-Tyr-IleLeu-HisGln-Arg-Cys) and DNT non-specific binding peptide (DNT-nbp, sequence: Thr-Ser-Met-Leu-Leu-Met-Ser-Pro-Lys-His-Gln-Ala-Cys). These two peptides were prepared to function as highly specific and highly non-specific (for the control experiment) peptide receptors, respectively. By detecting the differential signals between the DNT-bp and DNT-nbp functionalized rGO sensor, we demonstrated the ability of 2,4-dinitrotoluene (DNT) targets to bind to DNT-specific binding peptide surfaces, showing good sensitivity and selectivity. The advantage of using the differential signal is that it eliminates unwanted electrical noise and/or environmental effects. We achieved sensitivity of 27 ± 2 × 10⁻⁶ per part per billion (ppb) for the slope of resistance change versus DNT gas concentration of 80, 160, 240, 320, and 480 ppm, respectively. By sequentially flowing DNT vapor (320 ppb), acetone (100 ppm), toluene (1 ppm), and ethanol (100 ppm) onto the rGO sensors, the change in the signal of rGO in the presence of DNT gas is 6400 × 10⁻⁶ per ppb whereas the signals from the other gases show no changes, representing highly selective performance. Using this platform, we were also able to regenerate the surface by simply purging with N₂.

The peer-to-peer (P2P) energy trading is anchored in more efficient usage of electric power by allowing excess electric power from energy prosumers to be harnessed by other end-users. To boost the P2P energy trading, it is of pivotal significance to call on energy prosumers and end-users to actively participate in the trading while sharing information with a greater degree of freedom. In this perspective, this paper purports to implement the P2P energy trading scheme with an optimization model to assist in energy prosumers’ decisions by reckoning on hourly electric power available in the trading via the optimal energy scheduling of the energy trading and sharing system (ETS). On a purely practical level, it is assumed that all trading participants neither join the separate bidding processes nor are forced to comply with the predetermined optimal schedules for a trading period. Furthermore, this paper will be logically elaborated with reference to not only the determination of transaction price for maximizing the benefits of consumers under the different electricity rates but the establishment of additional settlement standards for bridging an imperative gap between optimally planned and actually transacted quantities of the P2P energy trading.

To overcome the hurdles of the ICP-based preconcentrator (i.e., instability and low efficiency) under physiological conditions, we proposed a novel approach by using a sequentially driven ICP process, showing a 13-fold preconcentration factor (PF) in human serum.