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The structures of the crosslinks in supramolecular polymer networks play an important role on their properties and functions. Herein, emissive metallacages are used as crosslinks to prepare metallacage-cored polyurethanes. The mechanical properties including storage modulus, toughness, Young's modulus and breaking strength of polymers are greatly enhanced with the increase of crosslinking densities. Moreover, such polymers not only exhibit good fluorescence in the solid state, but also show self-healing and shape memory properties owing to the dynamic reversible non-covalent bonds in their structures. This study not only offers a convenient strategy to prepare metallacage-crosslinked networks, but also explores their applications as self-healing and shape memory materials, which will promote the study of metallacage-cored supramolecular networks as smart materials.

Multi-behavior session-based recommendation aims to predict the next item, such as a location-based service (LBS) or a product, to be interacted by a specific behavior type (e.g., buy or click) in a session involving multiple types of behaviors. State-of-the-art methods generally model multi-behavior dependencies in item-level, but ignore the potential of discovering useful patterns of multi-behavior transition through feature-level representation learning. Besides, sequential and non-sequential patterns should be properly fused in session modeling to capture dynamic interests within the session. To this end, this paper proposes a Graph Neural Network based Hybrid Model GNNH, which enables feature-level deeper representations of multi-behavior interaction sequences for session-based recommendation. Specifically, we first construct multi-relational item graph (MRIG) and feature graph (MRFG) based on session sequences. On top of the MRIG and MRFG, our model takes advantage of GNN to capture item and feature representations, such that global item-to-item and feature-to-feature relations are fully preserved. Afterwards, each multi-behavior session is modeled by a seamless fusion of interacted item and feature representations, where self-attention and mean-pooling are used to obtain sequential and non-sequential patterns simultaneously. Experiments on two real datasets show that the GNNH model significantly outperforms the state-of-the-art methods.

Travel time estimation (TTE) is an important research topic in many geographic applications for smart city research. However, existing approaches either ignore the impact of transportation modes, or assume the mode information is known for each training trajectory and the query input. In this paper, we propose a multi-task learning model for travel time estimation called MTLM, which recommends the appropriate transportation mode for users, and then estimates the related travel time of the path. It integrates transportation-mode recommendation task and travel time estimation task to capture the mutual influence between them for more accurate TTE results. Furthermore, it captures spatio-temporal dependencies and transportation mode effect by learning effective representations for TTE. It combines the transportation-mode recommendation loss and TTE loss for training. Extensive experiments on real datasets demonstrate the effectiveness of our proposed methods.

So far, most efforts in photocatalysis have been devoted to the separation of photogenerated electron-hole pairs, and possible use of excitons (i.e., electron-hole pairs) for photocatalytic processes has not received much attention. In this work, we studied the effect of metal dots on the excitonic behaviors of two bismuth-based MOFs, Bi-TATB and Bi-BTC (here the tridentate ligands TATB3− and BTC3− represent the carboxylates of 4,4′,4′'-s-triazine-2,4,6-triyl-tribenzoic and 1,3,5-benzenetricarboxylic acids, respectively). The organic ligands (TATB and BTC) display different emission properties from the corresponding Bi based MOFs. Specifically, TATB and BTC display strong fluorescence emission while Bi-TATB and Bi-BTC display strong phosphorescence emission, suggesting the higher efficiency of intersystem crossing for Bi-TATB and Bi-BTC. The reason is attributed to the coordination with Bi, which promotes the singlet→ triplet intersystem crossing of the organic ligand due to the heavy metal effect. The enhanced triplet excited emission of Bi-TATB and Bi-BTC was further confirmed by the detection of 1O2, as 1O2 is well known to be formed due to energy transfer from the triplet state of photosensitizers to the ground-state oxygen (3O2). With above understanding, Bi-TATB and Bi-BTC were finally used to high selective photooxidation of benzyl alcohol to benzaldehyde. This work presents new understanding of the photophysical properties of Bi based MOFs, which provides alternative ideas on designing materials for selective photo-oxidation.

In this work, we provide an alternative way to modulate the type of major reactive oxygen species produced during the photocatalytic process. Polar molecular 4-carboxythiophenolate anion (4CBT) mod...

A triazine-based MOFs [PCN-9(Co)] was synthesized and its photoelectrical, photophysical properties were studied. As a new photocatalyst, PCN-9(Co) displays photocatalytic hydrogen evolution from water under UV–Visible light irradiation. With the introduction of platinum complex, PCN-9-Pt was obtained and platinum complex was believed to coordinate with the N in triazine. The H2 evolution rate of PCN-9-Pt is greatly improved, about 6.8 times higher than that of PCN-9(Co). The reason is due to the fact that platinum complex plays an important role in improving the separation efficiency of photogenerated charge carriers, as verified by PL and EIS results. This result provides a new kind of idea of modifying MOFs materials with molecular complex to improve the photocatalytic activity.

Effective and selective removal of Pb(II) from aqueous solution is highly desirable, but it is still a great challenge. We report here a water stable metal-organic frameworks (CAU-7-TATB), and the ligands contain N, which provides binding sites for metal ions. CAU-7-TATB exhibits fast adsorption kinetics, high adsorption capacity towards Pb(II). More importantly, CAU-7-TATB remains high prior adsorption towards Pb(II) in the presence of interfering ions like Cr(III), Co(II), Ni(II), Mn(II), Zn(II), Mg(II) and Ca(II), which is potentially applicable in removing Pb(II) from industrial water.

The efficient development of selective adsorbents for uranium extraction from seawater is necessary for their potential application in nuclear power generation. The amidoxime-based adsorbents have been recognized as the potential candidates, whereas they still suffer from a much higher affinity towards V(V) present in the seawater over U(VI), leading to the extremely limited commercial use. In this work, we develop a novel mussel-inspired photothermal polyamidoxime (PAO) hydrogel adsorbent, in which polydopamine (PDA) chains are linked to PAO (PDA-PAO) via Michael addition. Dual-crosslinked Fe@PDA-PAO hydrogel structure is constructed by noncovalent bonds between the catechol of PDA chains (e.g. π-π stacking and hydrogen bonds) as well as ionic coordination of Fe3+. PDA contributes to the improved hydrophilicity and high photothermal conversion efficiency. As a result, after immersing in real seawater for 6 weeks, light-irradiated Fe@PDA-PAO hydrogel delivers high uranium sorption capacity (12.67 mg-U/g-Ads) together with high U/V mass ratios (1.17), which are superior to currently available hydrogel adsorbents. Meanwhile, Fe3+ coordination endows Fe@PDA-PAO hydrogel with excellent tensile strength and self-recovery ability, which are of great significance to withstand the harsh conditions of ocean environment for practical applications. The results presented here reveal that Fe@PDA-PAO hydrogel holds tremendous potential for practical applications in the uranium-selective extraction from seawater.

Two transition metal (Co and Ni) ion phosphonates as isostructural organic inorganic hybrids are prepared and investigated in terms of photocatalytic hydrogen evolution from water and CO2 reduction under UV light irradiation. A photocatalytic mechanism of ligand-to-metal charge transfer (LMCT) is proposed.

Extraction of radioactive uranium from the natural seawater is regarded as one of the most promising ways to address the shortage of uranium resources. As a kind of potential uranium adsorbent, more attention has been paid to metal–organic framework materials (MOFs) due to large specific surface area and high ion selectivity. Currently, however, MOF adsorbents are hardly applied to the real seawater in view of the relatively low uranium adsorption capacity and recyclable issues. Herein, we present the monolithic MOF adsorbent with photothermally enhancing uranium adsorption capacity. Carbon sponge (CS) substrate with macroporous open cell structure was used as excellent photothermal conversion material. Zr-MOF (UiO-66-NH2) crystals were in situ grown on the fibrils network of polydopamine (PDA) pre-coated CS to obtain UiO-66-NH2@CS-PDA adsorbent. It is found that UiO-66-NH2 coating with perfect coverage and good adhesion has a high mass loading (>85 wt%). As a result, UiO-66-NH2@CS-PDA adsorbents exhibited the advantage of high-selectivity, high-affinity and cycling stability. Compared with the dark condition, the uranium adsorption amount was increased by 32.37% after 4 weeks in the natural seawater under simulated solar irradiation, which was mainly ascribed to the endothermic behavior of uranium adsorption process. Moreover, the elasticity attribute of CS was essential for sustenance of volume variation buffering during seawater flow. As a recyclable and favorable elastic large-scale monolithic MOF adsorbent, UiO-66-NH2@CS-PDA holds great promise for extracting uranium from the natural seawater.

Background: Diminished Ovarian Reserve (DOR) is a common disease in reproductive-age women in the diagnosis and treatment of infertility. The incidence of DOR increased quickly in recent years and had became one of the most important factors that made the quality of women life decline. Gynecology and reproductive medicine professors have made great efforts to explore good treatment methods all over the world. Traditional Chinese Medicine has made some achievement in treating DOR as a kind of complementary and alternative therapy In Vitro Fertilization (IVF) in recent years, it is indispensable to propose a network meta-analysis (NMA) protocol to discuss the efficacy and safety of TCM in IVF. Methods: A literature search will be conducted in 8 electronic databases. Results: The efficacy and safety of traditional Chinese medicine in preconditioning patients with diminished ovarian reserve that would undergo In Vitro Fertilization will be evaluated. Results: The systematic review will evaluate the efficacy and safety of TCM in IVF. Conclusion: The result of this study will provide reliable evidence of the use of TCM in IVF. INPLASY registration number: INPLASY2020110062. Ethics and dissemination: This review does not require ethical approval.

Two transition metal (Co and Ni) ion phosphonates as isostructural organic inorganic hybrids are prepared and investigated in terms of photocatalytic hydrogen evolution from water and CO2 reduction under UV light irradiation. A photocatalytic mechanism of ligand-to-metal charge transfer (LMCT) is proposed.