Self−assembled graphene derivatives used as HTLs for highly efficient inverted perovskite solar cells

The performance of inverted perovskite solar cells (PSCs) based on graphene oxide hole transporting materials is still unsatisfactory due to the high degree of surface oxygen contents and the insulating property. In this study, thickness−controlled and full−coverage graphene oxide films prepared by layer−by−layer self−assembly technique are firstly developed as hole transporting layers (HTLs) in PSCs. Meanwhile, conductivity tunable reduced graphene oxide films are in−situ prepared by an environment−friendly and efficient reductant system. A superior PCE of 16.28% based on rGO as prepared is obtained, resulting in an increment by approximately 33% compared with 12.26% of the device based on GO−1 as mentioned. At the same time, this work reveals an anomalous charge−extraction behavior of PSCs based on GO or rGO HTLs. Competition effect of interfacial recombination, charge transportation and radiation recombination in this process are proposed to analyze the internal mechanisms. This work provides a facile and novel method to prepare GO or rGO films, which can be used as efficient charge−extraction layers and even electrodes in inverted PSCs. Please click Additional Files below to see the full abstract

catena-Poly[[diaqua­(2,2′-bipyridine-κ2 N,N′)zinc]-μ-2,2′-[1,4-phenylene­bis(sulfanedi­yl)]diacetato-κ2 O:O′]

In the polymeric title complex, [Zn(C10H8O4S2)(C10H8N2)(H2O)2]n, the Zn2+ ion lies on a twofold rotation axis and exhibits an octa­hedral environment, in which it is coordinated by two trans O atoms from two symmetry-related 2,2′-[1,4-phenyl­enebis(sulfanedi­yl)]diacetate anions, two N atoms from one 2,2′-bipyridine ligand, and two cis O atoms from water mol­ecules. The dihedral angle between the two pyridine rings is 11.5 (1)°. Adjacent Zn2+ ions are bridged in a monodentate manner by the diacetate anions, forming a chain structure extending parallel to [101], and are further linked into the final three-dimensional structure by O—H⋯O hydrogen bonds between the coordinating water mol­ecules as donor and the non-coordinating carboxyl­ate O atoms as acceptor atoms

Bis[6-(3,5-dimethyl-1H-pyrazol-1-yl)picolinato]manganese(II) trihydrate

In the title complex, [Mn(C11H10N3O2)2]·3H2O, the MnII atom is coordinated by four N atoms and two O atoms in a distorted octa­hedral geometry. The mol­ecules are linked together via hydrogen bonds involving the water molecules. One of these is disordered equally over two positions

Robust Classification with Convolutional Prototype Learning

Convolutional neural networks (CNNs) have been widely used for image classification. Despite its high accuracies, CNN has been shown to be easily fooled by some adversarial examples, indicating that CNN is not robust enough for pattern classification. In this paper, we argue that the lack of robustness for CNN is caused by the softmax layer, which is a totally discriminative model and based on the assumption of closed world (i.e., with a fixed number of categories). To improve the robustness, we propose a novel learning framework called convolutional prototype learning (CPL). The advantage of using prototypes is that it can well handle the open world recognition problem and therefore improve the robustness. Under the framework of CPL, we design multiple classification criteria to train the network. Moreover, a prototype loss (PL) is proposed as a regularization to improve the intra-class compactness of the feature representation, which can be viewed as a generative model based on the Gaussian assumption of different classes. Experiments on several datasets demonstrate that CPL can achieve comparable or even better results than traditional CNN, and from the robustness perspective, CPL shows great advantages for both the rejection and incremental category learning tasks

Simulation Analysis of the Blocking Effect of Transaction Costs in China\u27s Housing Market

To examine the blocking effect of transaction costs on household mobility, we construct a housing consumption model including transaction costs and adopt an analog simulation methodology, analyzing how changes in household income and home prices influence household consumption, savings decisions and the transaction costs blocking effect. We find that changes in housing demand are the fundamental cause of the blocking effect of transaction costs. The more demand changes, the greater the blocking effect is. Besides, increased volatility in home prices worsens the household mobility problem with regards to the blocking effect of transaction costs, while a change in household income does not impact the blocking effect of transaction costs on housing consumption. To expand housing consumption, our findings suggest active measures that should be taken by policymakers to reduce transaction costs and stabilize home prices