ABSTRACT
Dimethyl disulfide (DMDS) is a common odor pollutant with an extremely low olfactory threshold. Highly sensitive and selective detection of DMDS in ambient humid air background, by metal oxide semiconductor (MOS) sensors, is highly desirable to address the increased public concern for health risk. However, it has still been a critical challenge up to now. Herein, p-type delafossite CuGaO2 has been proposed as a promising DMDS sensing material owing to its striking hydrophobicity (revealed by water contact angle measurement) and excellent partial catalytic oxidation properties (indicated by mass spectroscopy). The present CuGaO2 sensor shows a selective DMDS response, with satisfied humidity resistance performance and long-term stability at a relatively low operation temperature of 140 °C. An ultrahigh response of 100 to 10 ppm DMDS and a low limit of detection of 3.3 ppb could be achieved via a pulsed temperature modulation strategy. A smart sensing system based on a CuGaO2 sensor has been developed, which could precisely monitor DMDS vapor in ambient humid air, even with the presence of multiple interfering gases, demonstrating the practical application capability of MOS sensors for environmental odor monitoring.
Subject(s)
Disulfides , Gases , Oxides/chemistry , TemperatureABSTRACT
UV photoactivation has been widely employed to trigger the response of semiconductor chemiresistors at room temperature (RT). Generally, continuous UV (CU) irradiation is applied, and an apparent maximal response could be obtained via optimizing UV intensity. However, owing to the conflicting roles of (UV) photoactivation in the gas response process, we do not think the potential of photoactivation has been fully explored. Herein, a pulsed UV light modulation (PULM) photoactivation protocol has been proposed. Pulsed UV-on facilitates the generation of surface reactive oxygen species and refreshes the surface of chemiresistors, while pulsed UV-off avoids the side effects of UV-induced desorption of the target gas and the decline of base resistance. PULM enables decoupling those conflicting roles of CU photoactivation, resulting in a drastic boost of response to trace (20 ppb) NO2 from 1.9 (CU) to 131.1 (PULM UV-off), and a decline of limit of detection from 2.6 ppb (CU) to 0.8 ppb (PULM) for a ZnO chemiresistor. This work highlights that PULM allows full exploitation of the potential of nanomaterials for sensitively detecting trace (ppb-level) toxic gas molecules and opens a new opportunity for designing highly sensitive, low-power consumed RT chemiresistors for ambient air quality monitoring.
ABSTRACT
In 2016, Google proposed a congestion control algorithm based on bottleneck bandwidth and round-trip propagation time (BBR). The BBR congestion control algorithm measures the network bottleneck bandwidth and minimum delay in real-time to calculate the bandwidth delay product (BDP) and then adjusts the transmission rate to maximize throughput and minimize latency. However, relevant research reveals that BBR still has issues such as RTT unfairness, high packet loss rate, and deep buffer performance degradation. This article focuses on its most prominent RTT fairness issue as a starting point for optimization research. Using fluid models to describe the data transmission process in BBR congestion control, a fairness optimization strategy based on pacing gain is proposed. Triangular functions, inverse proportional functions, and gamma correction functions are analyzed and selected to construct the pacing gain model, forming three different adjustment functions for adaptive adjustment of the transmission rate. Simulation and real experiments show that the three optimization algorithms significantly improve the fairness and network transmission performance of the original BBR algorithm. In particular, the optimization algorithm that employs the gamma correction function as the gain model exhibits the best stability.
