We report, for the first time, construction of a sulfur electrode in a lithium–sulfur battery by using covalent-organic frameworks (COFs) as a host.

Incorporating a dipole interlayer has been one of the most crucial interfacial engineering strategies in organic and perovskite solar cells. An interfacial dipole brings steep shifts in electronic band structure across interfaces and thus effectively tunes charge carrier transport. However, the origin of the interfacial dipole and its effects on device performance are not entirely clear; they are even controversial in some cases. We devote this Perspective to identifying the electric dipole of various interlayers and correlating the interfacial dipole with device performance on the basis of classical semiconductor device theory. It is important to further consider the chemical nature of interlayers beyond the simplified model of an interfacial dipole to develop a full understanding of interfacial structure, energy bands, and device operation mechanism. Researchers are encouraged to integrate in situ and in operando characterizations with numerical simulations in future studies.

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For the development of multistimuli responsive organogels, the new organic gelator LMWG 1, featuring electroactive TTF and photoresponsive azobenzene groups, was designed and studied. By manipulating the redox state of the TTF group in LMWG 1, the gel-sol transition for organogels with the LMWG 1 can be reversibly tuned by either chemical or electrochemical oxidation/reduction reactions. Alternatively, the photoisomerization of the azobenzene group in LMWG 1 can also trigger the gel-sol transition. Therefore, organogels with LMWG 1 respond not only to thermal stimuli but also to redox reactions and light irradiation.

A simple strategy to construct a stimuli-responsive mechanized zirconium metal-organic framework for on-command cargo release.

A new low-molecular-mass gelator with one TTF and one urea group is described. It was found that the gel formation can be tuned by formation of CT complexes and oxidation.

A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisition devices, as well as seeing increased application in areas such as robotics, autonomous driving, and augmented and virtual reality. Deep learning is now the most powerful tool for data processing in computer vision and is becoming the most preferred technique for tasks such as classification, segmentation, and detection. While deep learning techniques are mainly applied to data with a structured grid, the point cloud, on the other hand, is unstructured. The unstructuredness of point clouds makes the use of deep learning for its direct processing very challenging. This paper contains a review of the recent state-of-the-art deep learning techniques, mainly focusing on raw point cloud data. The initial work on deep learning directly with raw point cloud data did not model local regions; therefore, subsequent approaches model local regions through sampling and grouping. More recently, several approaches have been proposed that not only model the local regions but also explore the correlation between points in the local regions. From the survey, we conclude that approaches that model local regions and take into account the correlation between points in the local regions perform better. Contrary to existing reviews, this paper provides a general structure for learning with raw point clouds, and various methods were compared based on the general structure. This work also introduces the popular 3D point cloud benchmark datasets and discusses the application of deep learning in popular 3D vision tasks, including classification, segmentation, and detection.

Combination drug therapy, [1] a regimen in which multiple drugs with different therapeutic outcomes are used in parallel or in sequence, has become one of the dominant strategies in the clinical treatment of HIV/AIDS, [2] diabetes, [3] and cancer. [4] In cancer therapy, for example, the U.S. Food and Drug Administration (FDA) approved the use in 2006 of Avastin in combination with Carboplatin and Paclitaxel for the initial systemic treatment of patients with lung cancer. Unlike monotherapy, combination therapy maximizes ther-apeutic efficacy against individual targets and is more likely to overcome drug resistance, while increasing the odds of a positive prognosis and reducing harmful side effects.Drug delivery systems, which administer medically active compounds to diseased cells in a targeted and controlled manner, [5] have gained much attention in the past couple of decades. While polymers, [6] dendrimers, [7] micelles, [8] vesicles, [9] and nanoparticles [10] have all been investigated for their use as possible drug delivery systems, most systems provide either delivery of a single drug or the simultaneous delivery [11] of multiple drugs. Using these systems, however, it is difficult to control [12] the administration order, timing, and dosage of each individual drug in a comprehensive manner. While it is possible to deliver a cocktail of drugs using several different co-administered drug delivery systems, this protocol has disadvantages. For example, it is not easy to expose several co-administered drug delivery systems to the same target at the right time, while also controlling the dosage rates and ratios of each individual drug. In order to administer chemotherapeutic combinations and produce synergistic actions, well-organized multidrug release systems, which can provide combination therapies by controlling the release behavior of each drug individually, need to be invented.Mesoporous silica nanoparticles (MSNs) have attracted widespread interest [13] in the past decade for use in integrated functional systems. They have large surface exteriors and porous interiors that can be harnessed as reservoirs for smallmolecule-drug storage. These MSNs are nontoxic to cells and can undergo cellular uptake [14] into acidic lysosomes by endocytosis when they are 100-200 nm in diameter, thus making them a popular candidate [15] for drug delivery systems. In particular, MSNs can be functionalized with molecular, as well as supramolecular, switches in order to control the release of drug molecules in response to external stimuli. Oncommand release systems, which respond to a range of stimuli, including pH changes, [16] light initiation, [17] competitive binding, [18] redox activation, [19] biological triggers, [20] and temperature changes, [21] have been reported by us and others. To the best of our knowledge, however, all the on-command release systems reported to date cannot release multiple drugs in a step-by-step fashion.Cyclodextrins (CDs), because of their abilities to form inclusion complexes with guest molecul...