Anion-Controlled Assembly of a Silver-Responsive Bifunctional Coordination Polymer with Detection and Large Adsorption Capacity.

The recognition and adsorption of silver ions (Ag+) from industrial wastewater are necessary but still challenging. Herein, we constructed four Zn(II)-based coordination polymers (CPs), namely, [Zn(btap)2(NO3)2]n (1), [Zn(btap)(SO4)(H2O)3]n (2), {[Zn(btap)2(H2O)2]·(ClO4)2}n (3), and [Zn(btap)Cl2]n (4), by using 3,5-bis(triazol-1-yl)pyridine (btap) with different anionic Zn(II) salts. The crystal structures of 1-4, varying from one-dimensional beaded (1) and zigzag chain (2) to two-dimensional sql (3) and bex (4) typologies, were regulated by the coordination modes of btap and the counter-anions. The water stability, pH stability, thermostability, and luminescent properties of the CPs were investigated. The luminescence performances in a series of cations and anions were also explored. Considering the high density of chloride groups in the structure, 4 showed luminescence sensing for Ag+ [KSV = 9188.45 M-1 and a limit of detection (LOD) of 4.9 µM], as well as an excellent ability for Ag+ adsorption in aqueous solution (maximum adsorption capacity, 653.3 mg/g). Additionally, anti-interference experiments revealed that 4 had excellent recognition and adsorption capacities for Ag+ even when multiple ions coexisted. Moreover, XRD, EDS, and XPS analyses confirmed that the coordination of Ag+ with chloride groups in 4 resulted in excellent adsorption capacity and prevented ligand-to-ligand electron transfer, showing excellent detection ability. Suitable coordination sites were introduced to interact strongly with Ag+, along with detection and large adsorption capacity. Our strategy can effectively design and develop multifunctional CP-based materials, which are applicable in removal processes and environmental protection, by regulating anions in the self-assembly and introducing CP functional groups.

Anion-controlled Zn(II) coordination polymers with 1-(tetrazo-5-yl)-3-(triazo-1-yl) benzene as an assembling ligand: synthesis, characterization, and efficient detection of tryptophan in water.

Tryptophan regulates and participates in various physiological systems in the human body, and its excessive intake has harmful effects. Therefore, detecting and monitoring tryptophan in water and distinguishing it from other amino acids are necessary. In addition to their excellent luminescence, coordination polymer-based sensors have good stability and high sensitivity and selectivity for sensing applications. In this work, two luminescent coordination polymers (CPs), [Zn(ttb)Cl]n (1) and [Zn2(ttb)2(OH)(NO3)]n (2), were obtained through the solvothermal reaction of different Zn(II) salts with a rarely studied multidentate N-donor ligand, 1-(tetrazo-5-yl)-3-(triazo-1-yl) benzene (Httb). Crystallographic investigations revealed that the structure of 1 exhibits a 2D fes net with Cl- anions acting as terminal charge balancers, and that of 2 features a 3D ant net with NO3- anions in a rare monodentate bridging (µ2-O-η1:η1) mode. In terms of stability tests, 2 has better thermal and water stability than 1. Although both show good fluorescence performance, specific tryptophan detection, and excellent anti-interference ability, 2 has higher KSV (111 852.6 M-1), a lower limit of detection (LOD = 23.6 nM), and a better recovery rate than 1. Cytotoxicity experiments proved that 2 has extremely low toxicity and thus has great potential for in vivo detection. Therefore, CP 2 is a suitable candidate for advanced practical applications for the efficient sensing of tryptophan in water. The luminescence of the ligands was also calculated using DFT theory and further discussed through experiments. The quenching mechanism that occurs after tryptophan addition was explored through Hirshfeld surface analysis.

[Discussion on current state and research strategies of inter-disciplines of acupuncture-moxibustion and artificial intelligence].

At present, the breakthrough of the key techniques of artificial intelligence (AI), including image recognition, deep learning, neural network, Robot technique, etc., greatly promote the development of discipline crossing and medicine. In the present paper, we make an in-depth discussion about the future application of inter-discipline techniques of acupuncture-moxibustion and AI. We think that some of the current instruments have been part of the new acupuncture-moxibustion devices and may have the potential to intersect with the AI discipline. Relying on these existing devices and those of meridian detection, we can obtain relatively objective data, and further conduct meridian-syndrome differentiation and big data collection to possibly realize remote medical treatment. In addition, we may also develop an AI system for studying the underlying mechanisms of acupuncture and moxibustion therapies. Nevertheless, there still exist a lot of problems and challenges in clinical, teaching and scientific researches. It is recommended that the discipline of acupuncture-moxibustion should be intersected with the AI subject and formulate appropriate development strategies, promoting a faster and better development of acupuncturology.