Yu Liu

Calixarenes are one kind of phenol-formaldehyde cyclic oligomers, discovered from the Bakelite process. Their intrinsic characteristics, including the unique structural scaffold, facile modification and adjustable inclusion property, show pronounced potential for supramolecular polymerization. In this tutorial review, we summarize the current stage of fabrication of calixarene-based supramolecular polymers. Three types of calixarene-based supramolecular polymers are, respectively, illustrated according to the different activities of calixarenes: (1) calixarene-based supramolecular polycaps, (2) supramolecular polymers with polymeric calixarene scaffolds where the cavities remain unexploited; (3) supramolecular polymers formed by the host-guest interactions offered by calixarene cavities. Furthermore, the stimuli-responsiveness and functions of calixarene-based supramolecular polymers are illustrated, which endow them with a broad range of potential applications as smart, self-healing materials and delivery carriers.

CONSPECTUS: Developments in macrocyclic chemistry have led to supramolecular chemistry, a field that has attracted increasing attention among researchers in various disciplines. Notably, the discoveries of new types of macrocyclic hosts have served as important milestones in the field. Researchers have explored the supramolecular chemistry of several classical macrocyclic hosts, including crown ethers, cyclodextrins, calixarenes, and cucurbiturils. Calixarenes represent a third generation of supramolecular hosts after cyclodextrins and crown ethers. Easily modified, these macrocycles show great potential as simple scaffolds to build podand-like receptors. However, the inclusion properties of the cavities of unmodified calixarenes are not as good as those of other common macrocycles. Calixarenes require extensive chemical modifications to achieve efficient endo-complexation. p-Sulfonatocalix[n]arenes (SCnAs, n = 4-8) are a family of water-soluble calixarene derivatives that in aqueous media bind to guest molecules in their cavities. Their cavities are three-dimensional and π-electron-rich with multiple sulfonate groups, which endow them with fascinating affinities and selectivities, especially toward organic cations. They also can serve as scaffolds for functional, responsive host-guest systems. Moreover, SCnAs are biocompatible, which makes them potentially useful for diverse life sciences and pharmaceutical applications. In this Account, we summarize recent work on the recognition and assembly properties unique to SCnAs and their potential biological applications, by our group and by other laboratories. Initially examining simple host-guest systems, we describe the development of a series of functional host-guest pairs based on the molecular recognition between SCnAs and guest molecules. Such pairs can be used for fluorescent sensing systems, enzymatic activity assays, and pesticide detoxification. Although most macrocyclic hosts prevent self-aggregation of guest molecules, SCnAs can induce self-aggregation. Researchers have exploited calixarene-induced aggregation to construct supramolecular binary vesicles. These vesicles respond to internal and external stimuli, including temperature changes, redox reactions, additives, and enzymatic reactions. Such structures could be used as drug delivery vehicles. Although several biological applications of SCnAs have been reported, this field is still in its infancy. Continued exploration of the supramolecular chemistry of SCnAs will not only improve the existing biological functions but also open new avenues for the use of SCnAs in the fields of biology, biotechnology, and pharmaceutical research. In addition, we expect that other interdisciplinary research efforts will accelerate developments in the supramolecular chemistry of SCnAs.

ADVERTISEMENT RETURN TO ISSUEPREVCommunicationNEXTSteam-Stable Aluminosilicate Mesostructures Assembled from Zeolite Type Y SeedsYu Liu, Wenzhong Zhang, and Thomas J. PinnavaiaView Author Information Department of Chemistry, Michigan State University East Lansing, Michigan 48824 Cite this: J. Am. Chem. Soc. 2000, 122, 36, 8791–8792Publication Date (Web):August 24, 2000Publication History Received11 May 2000Published online24 August 2000Published inissue 1 September 2000https://pubs.acs.org/doi/10.1021/ja001615zhttps://doi.org/10.1021/ja001615zrapid-communicationACS PublicationsCopyright © 2000 American Chemical SocietyRequest reuse permissionsArticle Views3970Altmetric-Citations501LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Aluminosilicate,Mesostructures,Precursors,Water,Zeolites Get e-Alerts

Despite the great success of two-stage detectors, single-stage detector is still a more elegant and efficient way, yet suffers from the two well-known disharmonies during training, i.e. the huge difference in quantity between positive and negative examples as well as between easy and hard examples. In this work, we first point out that the essential effect of the two disharmonies can be summarized in term of the gradient. Further, we propose a novel gradient harmonizing mechanism (GHM) to be a hedging for the disharmonies. The philosophy behind GHM can be easily embedded into both classification loss function like cross-entropy (CE) and regression loss function like smooth-L1 (SL1) loss. To this end, two novel loss functions called GHM-C and GHM-R are designed to balancing the gradient flow for anchor classification and bounding box refinement, respectively. Ablation study on MS COCO demonstrates that without laborious hyper-parameter tuning, both GHM-C and GHM-R can bring substantial improvement for single-stage detector. Without any whistles and bells, the proposed model achieves 41.6 mAP on COCO testdev set which surpass the state-of-the-art method, Focal Loss (FL) + SL1, by 0.8. The code1 is released to facilitate future research.