Perovskite solar cells have attracted great research interest as a promising candidate for silicon solar cells. Plenty of work has been reported to use perovskites to semitransparent windows and transparent photovoltaic (TPV) devices to obtain multifunctional systems. However, the narrow bandgap and sharp absorption edge of the typical perovskites prevent them from achieving the highest transparency to satisfy the requirements of aesthetic and integration, and the poor stability and toxic Pb compositions hinder their practical application. Herein, lead-free halide double perovskites with a wide bandgap and indirect bandgap characteristics is introduced to fabricate long-term stable transparent photovoltaic devices exhibiting high visible transmittance (73%) and considerable energy conversion efficiency (1.56%). Through further theoretical calculation and evaluation, a new strategy using indirect bandgap material on TPV devices is proposed to combine the enhancement of these two parameters. This approach will be a significant compliment to near-infrared-absorbing solar cells to selectively harvest light in the invisible region to obtain highly performing multi-junction smart windows on buildings, vehicles and mobile electronics, providing a new reasonable idea to realize TPVs with high efficiency and transparency simultaneously.
Inhalation of airborne engineered nanoparticles (ENPs) is an important pathway for population exposure. While there have been numerous studies of the health impacts of pristine ENPs, the impacts of atmospherically transformed ENPs are largely unknown, despite the certainty that atmospheric processing of ENPs will occur. Here, the oxidative potential (OP) of TiO2, CeO2, and SiO2 nanoparticles which had been coated with atmospheric secondary organic material (SOM) from the OH or O-3 oxidation of alpha-pinene and toluene was investigated. The results indicated that coating of these ENPs with SOM formed at low photochemical ages reduced the OP of redox-active ENPs (TiO2 and CeO2) and increased the OP of redox-inert ENP (SiO2). However, at a given SOM coating thickness, the overall OP of the particles increased by up to 93% with an increased level of photooxidation, regardless of ENP type. The OP suppression and enhancement observed here were attributed to a physical hindrance of ENP-antioxidant interactions by the SOM and an enhanced peroxide content in SOM (brought about by an increased level of photooxidation), respectively. These results imply that the health risk associated with airborne ENPs is strongly related to their time history during their residence time in the atmosphere, and thus, accounting for the impacts of atmospheric processing should be considered critical for making accurate risk assessments of airborne ENPs and for formulating efficient policies with respect to the control of emerging nanotechnologies.
In order to evaluate the volatile organic compounds (VOCs) pollution characteristics in Chengdu and to identify their sources, ambient air sample collection and measurement were conducted at 28 sampling sites covering all districts/counties of Chengdu from May 2016 to January 2017. Meanwhile, a county-level anthropogenic speciated VOCs emission inventory was established by “bottom-up” method for 2016. Then, a comparison was made between the VOCs emissions, spatial variations, and source structures derived from the measurement and emission inventory. Ambient measurements showed that the annual average mixing ratios of VOCs in Chengdu were 57.54 ppbv (12.36 to 456.04 ppbv), of which mainly dominated by alkanes (38.8%) and OVOCs (22.0%). The ambient VOCs in Chengdu have distinct spatiotemporal characteristics, with a high concentration in January at the middle-northern part of the city and a low concentration in September at the southwestern part. The spatial distribution of VOCs estimated by the emission inventory was in good agreement with ambient measurements. Comparison of individual VOCs emissions indicated that the emissions of non-methane hydrocarbon species agreed within ±100% between the two methods. Both positive matrix factorization (PMF) model results and emission inventory showed that vehicle emissions were the major contributor of anthropogenic VOCs in Chengdu (31% and 37%), followed by solvent utilization (26% and 27%) and industrial processes (23% and 30%). The large discrepancies were found between the relative contribution of combustion sources, and the PMF resolved more contributions (20%) than the emission inventory (6%). Overall, this study demonstrates that measurement results and emission inventory were in a good agreement. However, to improve the reliability of the emission inventory, we suggest significant revision on source profiles of oxygenated volatile organic compounds (OVOCs) and halocarbons, as well as more detailed investigation should be made in terms of energy consumption in household.
This study explores how subjectivity is expressed in coherence relations, by means of a distinctive collocational analysis on two Chinese causal connectives: the specific subjective kejian ‘so’, used in subjective argument-claim relations, and the underspecified suoyi ‘so’, which can be used in both subjective argument-claim and objective cause-consequence relations. On the basis of both Horn’s pragmatic Relation and Quality principles and the Uniform Information Density Theory, we hypothesized that the presence of other linguistic elements expressing subjectivity in a discourse segment should be related to the degree of subjectivity encoded by the connective. In line with this hypothesis, the association scores showed that suoyi is more frequently combined with perspective markers expressing epistemic stance: cognition verbs and modal verbs. Kejian, which already expresses epistemic stance, co-occurred more often with perspective markers related to attitudinal stance, such as markers of expectedness and importance. The paper also pays attention to similarities and differences in collocation patterns across contexts and genres.
Xue B, Hu S, Zou L, Cheng J. The Value of Paraphrase for Knowledge Base Predicates, in The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, Ne. AAAI Press; 2020:9346–9353.