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Helical structures, the foundation of the genetic code, have attracted intense interest in coordination chemistry not only for their ubiquitous appearance in nature, a typical example being the DNA molecule, but also for their practical implications in multidisciplinary areas, such as optical devices, biomimetic chemistry, asymmetric catalysis chemistry, and structural biology. 1 Until now, many single-, double-, triple-, and even multiple-stranded helices as well as circular and cylindrical helices have been prepared and comprehensively discussed. 2 In contrast, the meso-helices are extremely infrequent, 3 although meso-helical motifs are common in nature, such as the tendrils of a variety of plants. The reason may be that it is quite difficult to control the formation of two or more flexures in single-stranded helix. Consequently, the rational design and construction of metalÀorganic frameworks (MOFs) with meso-helical character are still a long-term challenge. To get such meso-helices, the crucial step is to choose multifunctional organic ligands containing appropriate coordination sites linked by a proper spacer with specific positional orientation. 4 With this understanding, we select a semirigid N-heterocyclic ligand 1,4-bis(2-methylbenzimidazol-1-ylmethyl) benzene (bmb) with a rigid spacer of phenyl ring and two freely rotating methylbenzimidazol arms, which may generate two flexures and favor the formation of meso-helical motifs. 4a In addition, the 2-position substituent methyl of benzimidazole ring can greatly enhance the donated electrons ability of the ligand, 5 which should be more likely to afford charming meso-helices.It is well-known that dicarboxylate organic groups are excellent structural constructors. 6 Changes in the flexibility, length, spatial extended direction, and angle of the spacer can lead to remarkable classes of complexes bearing diverse architectures and functions. 7 In view of the development of synthetic strategy, 8 it will be valuable to introduce the dicarboxylates with different spacers into the meso-helices synthetic process based on N-donor ligand bmb, which can result in greater tunability of the meso-helical features and build much more complicated and fascinating MOFs. Moreover, a systematic investigation about the influence of the spacer angles and lengths of dicarboxylate

Five novel metal−organic frameworks with a 1,3,5-tris-(triazol-1-ylmethyl)-2,4,6-trimethylbenzene (tttmb) flexible tripodal block, n a m e l y , { [ C d ( t t t m b ) 5) (H 2 atc = 1,3-adamantanedicarboxylic acid, H 2 tbi = 5-tert-butylisophthalic acid, H 2 bdc = 1,4-benzenedicarboxylic acid, H 3 btc = 1,2,4-benzenetricarboxylic acid, and H 4 btec = 1,2,4,5-benzenetetracarboxylic acid), have been synthesized. Complex 1 exhibits a two-dimensional structure with left-and right-handed helical chains arranged alternately. Complex 2 displays an intricate two-dimensional framework containing three layers with a 3,4,7-connected topology. It is notable that tbi 2− takes on five different coordination modes in 2. Complex 3 presents a 3D 3,4-connected network with a point symbol of (6 3 ) 2 (6 4 •8 2 ) 2 (6 3 •8 3 ). The structure of complex 4 is a self-penetrating 3D 3,4,8-connected framework with left-and right-handed helical chains arranged alternately. Complex 5 shows a 3D pillar-layered framework, which can be simplified as a 3,4,5-connected 3D topology with a Schlafi symbol of (5 3 )(5 2 •6 2 •7•9)(5 5 •6 2 •7 2 •8). Moreover, the investigation of photoluminescence properties reveals that complexes 1−5 show different fluorescent behaviors.

Abstract. Two metal‐organic coordination polymers [Co(bmb)(btc)0.5]n(1) and {[Zn(bmb)0.5(btc)0.5(H2O)]·0.5bmb·H2O}n (2) [H4btc = benzene‐1, 2, 4, 5‐tetracarboxylic acid, bmb = 1, 4‐bis(2‐methylbenzimidazol‐1‐ylmethyl) benzene] were prepared under hydrothermal conditions. Single‐crystal X‐ray diffraction indicates that both complexes have a 2D framework structure with (4·62) (42·62·82) topology. Interestingly, the hydrogen bonds in 2 form a fascinating meso‐helix. The catalytic activity of 1 for oxidative coupling of 2, 6‐dimethylphenol (DMP) and the photoluminescence properties of 2 were investigated. Furthermore, the complexes were investigated by IR spectroscopy and thermogravimetric analysis.

The emergence of the COVID-19 pandemic has hindered the achievement of the global Sustainable Development Goals (SDGs). Pro-environmental behaviour contributes to the achievement of the SDGs, and UNESCO considers college students as major contributors. There is a scarcity of research on college student pro-environmental behaviour and even less on the use of decision trees to predict pro-environmental behaviour. Therefore, this study aims to investigate the validity of applying a modified C5.0 decision-tree model to predict college student pro-environmental behaviour and to determine which variables can be used as predictors of such behaviour. To address these questions, 334 university students in Guangdong Province, China, completed a questionnaire that consisted of seven parts: the Perceived Behavioural Control Scale, the Social Identity Scale, the Innovative Behaviour Scale, the Sense of Place Scale, the Subjective Norms Scale, the Environmental Activism Scale, and the willingness to behave in an environmentally responsible manner scale. A modified C5.0 decision-tree model was also used to make predictions. The results showed that the main predictor variables for pro-environmental behaviour were willingness to behave in an environmentally responsible manner, innovative behaviour, and perceived behavioural control. The importance of willingness to behave in an environmentally responsible manner was 0.1562, the importance of innovative behaviour was 0.1404, and the perceived behavioural control was 0.1322. Secondly, there are 63.88% of those with high pro-environmental behaviour. Therefore, we conclude that the decision tree model is valid in predicting the pro-environmental behaviour of college student. The predictor variables for pro-environmental behaviour were, in order of importance: Willingness to behave in an environmentally responsible manner, Environmental Activism, Subjective Norms, Sense of Place, Innovative Behaviour, Social Identity, and Perceived Behavioural Control. This study establishes a link between machine learning and pro-environmental behaviour and broadens understanding of pro-environmental behaviour. It provides a research support with improving people’s sustainable development philosophy and behaviour.