Synthesis, Characterization and Crystal Structure of a One-dimensional Diamagnetic Metal-radical Complex: [Zn(NIT4py)2(DTB)2(H2O)2]

A novel one-dimensional complex [Zn(NIT4py)₂(DTB)₂(H₂O)₂] (1), with mixed ligands [where NIT4py is 2-(4′-pyridyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide and DTB is 3,5-dinitrobenzoate] has been synthesized and characterized by elemental analyses, i.r., u.v.–vis spectra, thermogravimetric analysis, X-ray single crystal diffraction and magnetic measurements. The complex crystallizes in the triclinic crystal system and space group Pî. The Zn ^II ion is in a distorted octahedral environment: two nitrogen atoms from two NIT4py entities, two oxygen atoms from two DTB units in the basal plane; and two oxygen atoms from the two water molecules in the axial position. The [Zn(NIT4py)₂(DTB)₂(H₂O)₂] units are connected as a one dimension chain by the intermolecular hydrogen bonds. The complex exhibits intramolecular antiferromagnetic interactions between the two radicals.     

二氢茉莉酮酸甲酯的简便合成方法

本文报道二氢茉莉酮酸甲酯的简便合成方法。先由丁二酸和庚酰氯反应得到2-戊基-1,3-环戊二酮(1),再用甲醇醚化1,可得到2-戊基-3-甲氧基-环戊-2-烯酮(2)。2与丙二酸二甲酯反应生成(2-戊基-3-酮-1-环戊烯-)基乙酸甲酮(3)。最后,催化氢化3,便可得到二氢茉莉酮酸甲酯(4)。     

A new quantum group associated with a ‘nonstandard’ braid group representation

A new quantum group is derived from a nonstandard braid group representation by employing the Faddeev-Reshetikhin-Takhtajan constructive method. The classical limit is not a Lie superalgebra, despite relations like x ²–y ²=0. We classify all finite-dimensional irreducible representations of the new Hopf algebra and find only one- and two-dimensional ones.     

Effects of simultaneously doped and deposited Ag on the photocatalytic activity and surface states of TiO2

Ag-TiO2 catalysts with different Ag contents were prepared via a sol-gel method in the absence of light. Based on the characterizations of XRD, photoluminescence (PL), surface photovoltage spectroscopy (SPS), field-induced surface photovoltage spectroscopy (FISPS), and XPS as well as the evaluation of the photocatalytic activity for degrading rhodamine B(RhB) solutions, it was found that the Ag dopant promoted the phase transformation as well as had an inhibition effect on the growth of anatase crystallite. The PL and SPS intensities were decreased with increasing Ag content, indicating that the Ag dopant could effectively inhibit the recombination of the photoinduced electrons and holes. However, the active sites capturing the photoinduced electrons reduced, while the Ag content exceeded 5 mol %. At rather low Ag dopant concentrations, the migration and diffusion of Ag+ ions were predominant, while at rather high Ag dopant concentrations, the migration, diffusion, and reduction of Ag ions simultaneously occurred. The Ag-TiO2 photocatalysts with appropriate content of Ag (Ag species concentration is from about 3 to 5 mol %) possessed abundant electron traps so as to be favorable for the separation of the photoinduced electron-hole pairs, which could greatly enhance the activity of the photocatalysts. From the results of FISPS measurements, it could be found that the impurity bands and abundant surface states were introduced into the interfacial layer of TiO2 because of Ag simultaneously doping and depositing, which could improve the absorption capability for visible light of the photocatalysts.     

五阶非线性下零色散附近的调制不稳定性

在同时考虑光纤损耗、高阶色散以及高阶非线性情况下,从广义非线性薛定谔方程出发,研究了零色散附近的调制不稳定性,分析了四阶色散和五阶非线性对增益谱的影响.结果表明：当光脉冲工作在零色散附近时,四阶色散对调制不稳定性起决定作用,它使反常色散区的增益谱变宽.在光纤正常色散区,正（负）五阶非线性使增益谱的谱宽和峰值增大（减小）;但在反常色散区,五阶非线性仅改变增益谱的峰值,几乎不影响谱宽.     

透极远红外光学材料制备及性能研究

在一定的温度、压力等条件下,采用有机材料(聚四氟乙烯)和无机晶体(KBr、CsI),通过热合技术研制出样品几何尺寸为Φ20mm×3-5mm、透射波段分别为15-38μm(PE-KBr)和15-60μm(PE-CsI)的透极远红外复合光学材料。抗腐蚀性能测试结果表明,材料耐强酸、强碱及部分有机溶剂。机械性能分析表明材料在小于115℃范围内可安全使用。极远红外透过率测试结果表明,在1-15μm波段,平均透过率小于15%,15-38μm和15-60μm极远红外波段,平均透过率大于50%,并对影响材料透过率的因素进行了分析。     

Visible Light-Driven Alkyne-Grafted Ethylene-Bridged Azobenzene Chromophores for Photothermal Utilization

Molecular photoswitches are considered to be important candidates in the field of solar energy storage due to their sensitive and reversible bidirectional optical response. Nevertheless, it is still a daunting challenge to design a molecular photoswitch to improve the low solar spectrum utilization and quantum yields while achieving charging and discharging of heat without solvent assistance. Herein, a series of visible-light-driven ethylene-bridged azobenzene (b-Azo) chromophores with different alkyne substituents which can undergo isomerization reactions promoted in both directions by visible light are reported. Their visible light responsiveness improves their solar spectrum utilization while also having high quantum yields. In addition, as the compounds are liquids, there is no need to dissolve the compounds in order to exploit this switching. The photoisomerization of b-Azo can be adjusted by alkyne-related substituents, and hexyne-substituted b-Azo is able to store and release photothermal energy with a high density of 106.1 J·g⁻¹, and can achieve a temperature increase of 1.8 °C at a low temperature of −1 °C.     

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.