The Zr-based metal–organic frameworks are generally prepared by solvothermal procedure. To overcome the slow kinetics of nucleation and crystallization of Zr-based metal–organic frameworks is of great interest and challenging. Here, we find that an ionic liquid as solvent can significantly accelerate the formation of Zr-based metal–organic frameworks at room temperature. For example, the reaction time is shortened to 0.5 h in 1-hexyl-3-methylimidazolium chloride for Zr-based metal–organic framework formation, while that in the conventional solvent N,N-dimethylformamide needs at least 120 h. The reaction mechanism was investigated in situ by 1H nuclear magnetic resonance, spectroscopy synchrotron small angle X-ray scattering and X-ray absorption fine structure. This rapid, low-energy, and facile route produces Zr-based metal–organic framework nanoparticles with small particle size, missing-linker defects and large surface area, which can be used as heterogeneous catalysts for Meerwein–Ponndorf–Verley reaction.

The colloidal size and rod morphology of nanocrystalline cellulose (NCC) lead to suspensions with useful phase and gelation behaviours as well as complex rheologies. However, these have not been comprehensively evaluated previously. Here we report the detailed phase behaviour of sulphonated NCC aqueous suspensions as a function of concentration and salinity. Four phases - liquid, viscoelastic, repulsive glass and attractive glass/gel - are identified in terms of their distinct rheological behaviours. The liquid-solid transitions (LSTs) are determined rheologically, and these are supported by a simplified model based on the DLVO theory that indicates the importance of charge in determining the phase behaviour. Rheology is also used to investigate the solid-solid transition from a repulsive glass to an attractive gel with increasing salt at high NCC concentrations. A time-dependent aging phenomenon is observed in suspensions with a composition just below the LSTs, and the implications of this on the dynamics occurring during gelation processes are discussed. This work can be directly applied to the development of structure-function relationships and the expanding utilisation of NCC suspensions, whilst also providing a basis for the study of charged colloidal rods more generally and evaluation of theoretical models.

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A phase diagram is developed based on the structure-rheology measurements showing various states of NCC that form as a function of salt and NCC concentration, which go well beyond those previously reported. This extended range of conditions reveals regions where the suspension is a viscous fluid and viscoelastic soft solid, as well as regions of instability that is suggested to arise when there is sufficient salt to reduce the electrical double layer (as explained qualitatively using DLVO theory) but insufficient NCC to form a load bearing network.

With the development of high throughput sequencing and single-cell genomics technologies, many uncultured bacterial communities have been dissected by combining these two techniques. Especially, by simultaneously leveraging of single-cell genomics and metagenomics, researchers can greatly improve the efficiency and accuracy of obtaining whole genome information from complex microbial communities, which not only allow us to identify microbes but also link function to species, identify subspecies variations, study host-virus interactions and etc. Here, we review recent developments and the challenges need to be addressed in single-cell metagenomics, including potential contamination, uneven sequence coverage, sequence chimera, genome assembly and annotation. With the development of sequencing and computational methods, single-cell metagenomics will undoubtedly broaden its application in various microbiome studies.

The lignite biodegradation procedure to produce water-soluble humic materials (WSHM) with a Penicillium stain was established by previous studies in our laboratory. This study researched the effects of WSHM on the growth of Bradyrhizobium liaoningense CCBAU05525 and its nodulation on soybean. Results showed that WSHM enhanced the cell density of CCBAU05525 in culture, and increased the nodule number, nodule fresh weight and nitrogenase activity of the inoculated soybean plants. Then the chemical compounds of WSHM were analyzed and flavonoid analogues were identified in WSHM through tetramethyl ammonium hydroxide (TMAH)-py-GC/MS analysis. Protein expression profiles and nod gene expression of CCBAU05525 in response to WSHM or genistein were compared to illustrate the working mechanism of WSHM. The differently expressed proteins in response to WSHM were involved in nitrogen and carbon metabolism, nucleic acid metabolism, signaling, energy production and some transmembrane transports. WSHM was found more effective than genistein in inducing the nod gene expression. These results demonstrated that WSHM stimulated cell metabolism and nutrient transport, which resulted in increased cell density of CCBAU05525 and prepared the bacteria for better bacteroid development. Furthermore, WSHM had similar but superior functions to flavone in inducing nod gene and nitrogen fixation related proteins expression in CCBAU05525.

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Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.