ABSTRACT
In this study, flake-like MoO3-ZnO composite was prepared using a simple and robust electrochemical setup. The composite was characterized by X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, elemental analysis, X-ray photoelectron spectroscopy, thermogravimetric analysis, photoluminescence, zeta potential analysis, and electrochemical impedance study. The modified ZnO shows a remarkable catalytic activity towards the photodegradation of three potentially hazardous dyes, malachite green, crystal violet, and methylene blue. More than 95% of both malachite green and crystal violet degraded within 140 min under visible light irradiation. Scavenger studies reveal that OH· radicals produced by the photo-separated charges on MoO3-ZnO are responsible for the degradation of all three dyes. The photoactive charge carriers show less recombination rate as evidenced by the photoluminescence spectrum due to the interparticle charge migration process. This work suggests a new versatile procedure for the synthesis of MoO3-ZnO composites and establishes its photocatalytic efficacy under visible light with three common pollutant dyes found in wastewater.
Subject(s)
Zinc Oxide , Catalysis , Coloring Agents , Light , PhotolysisABSTRACT
Television (TV) programming attracts ever-growing audiences and dominates the cultural zeitgeist. Viewership and social media engagement have become standard indices of programming success. However, accurately predicting individual episode success or future show performance using traditional metrics remains a challenge. Here we examine whether TV viewership and Twitter activity can be predicted using electroencephalography (EEG) measures, which are less affected by reporting biases and which are commonly associated with different cognitive processes. 331 participants watched an hour-long episode from one of nine prime-time shows (~36 participants per episode). Three frequency-based measures were extracted: fronto-central alpha/beta asymmetry (indexing approach motivation), fronto-central alpha/theta power (indexing attention), and fronto-central theta/gamma power (indexing memory processing). All three EEG measures and the composite EEG score significantly correlated across episode segments with the two behavioral measures of TV viewership and Twitter volume. EEG measures explained more variance than either of the behavioral metrics and mediated the relationship between the two. Attentional focus was integral for both audience retention and Twitter activity, while emotional motivation was specifically linked with social engagement and program segments with high TV viewership. These findings highlight the viability of using EEG measures to predict success of TV programming and identify cognitive processes that contribute to audience engagement with television shows.
