Remote substituent effects on bond dissociation energies of para-substituted aromatic silanes

UB3LYP/6-31G(d) and ROMP2/6-311++G(d,2p) methods were used to calculate the Si-X bond dissociation energies (BDEs) of a number of para-substituted aromatic silanes (4-Y-C(6)H(4)-SiH(2)X, where X = H, F, Cl, or Li). It was found that the substituent effect on the Si-H BDE of 4-Y-C(6)H(4)-SiH(3) was small, as the slope (rho(+)()) of the BDE- regression was only 0.09 kJ/mol. In comparison, the substituent effect on the Si-F BDE of 4-Y-C(6)H(4)-SiH(2)F was much stronger, whose rho(+ )()value was -2.34 kJ/mol. The substituent effect on the Si-Cl BDE of 4-Y-C(6)H(4)-SiH(2)Cl was also found to be strong with a rho(+)() value of -1.70 kJ/mol. However, the substituent effect on the Si-Li BDE of 4-Y-C(6)H(4)-SiH(2)Li was found to have a large and positive slope (+9.12 kJ/mol) against. The origin of the above remarkably different substituent effects on the Si-X BDEs was found to be associated with the ability of the substituent to stabilize or destabilize the starting material (4-Y-C(6)H(4)-SiH(2)X) as well as the product (4-Y-C(6)H(4)-SiH(2)* radical) of the homolysis. Therefore, the direction and magnitude of the effects of Y-substituents on the Z-X BDEs in compounds such as 4-YC(6)H(4)Z-X should have some important dependence on the polarity of the Z-X bond undergoing homolysis. This conclusion was in agreement with that from earlier studies (for example, J. Am. Chem. Soc. 1991, 113, 9363). However, it indicated that the proposal from a recent work (J. Am. Chem. Soc. 2001, 123, 5518) was unfortunately not justified.     

Molecular Recognition of Bridged Bis(β-cyclodextrin)s Linked by Phenylenediseleno Tether on the Primary or Secondary Side with Fluorescent Dyes

A Novel β-cyclodextrin dimer,2,2′-o-phenylenediseleno-bridgedbis(β-cyclodextrin)(2),has been synthesized by reaction ofmono-[2-O-(p-tolylsulfonyl)]-β-cyclodextrin and poly(o-phenylenediselenide).The complexation stability constants(K_s)and Gibbs free energy changes(-ΔG°)of dimer 2 with fourfluorescence dyes,that is,ammonium 8-anilino-1-naphthalene-sulfonate(ANS),sodium 6-(p-toluidino)-2-naphthalenesul-fonate(TNS),Acridine Red(AR)and Rhodamine B(RhB)have been determined in aqueous phosphate buffer solution(pH=7.2,0.1 mol·L~(-1)at 25℃ by means of fluorescence spec-     

绿色合成氧化剂高铁酸盐

高铁酸盐是绿色、无污染、高选择性和高活性的强氧化剂，其氧化性能比KMn04、O3和Cl还强，可以氧化醇类、含氮化合物、甚至烃类等有机化合物，高铁酸盐在有机物氧化合成中的应用具有很好的发展前景。本文介绍了有关高铁酸盐的制备方法、性质及有机物氧化合成方面的研究进展。     

A Study on the Pd/a-Si/Ni Seed Layer for Metal-Induced Lateral Crystallization and Poly-Si TFTs

The effect of Pd on the growth rate of metal-induced lateral crystallization (MILC) from Ni seed and the electrical properties of thin-film transistors (TFTs) fabricated on the films crystallized by MILC were investigated. When the Pd metal is placed on the amorphous-silicon/Ni-seed layer, the MILC growth rate is two to three times faster than that of conventional Ni-MILC, without any degradation of TFTs. These results were explained by a stress that is generated by the formation of Pd₂Si     

Butterfly and Nest-Shaped Tp*-W-Cu-S Cluster Monomers and Dimers with Hexamethylenetetramine as Ligand: Anion-Dependent Structures and Nonlinear Optical Properties

The assembly of[Et4N][Tp*WS3](1) with CuX (Tp* =hydridotris(3,5-dimethylpyrazol-1-yl)borate;X =Cl,Br,and I) or[Cu(MeCN)4][PF6]in the presence of tetratopic liga...     

X射线荧光光谱(XRF)法测定绿泥石中镁、铝、硅、磷、钾、钙、钛、铁元素含量

建立了X射线荧光光谱法测定绿泥石中镁、铝、硅、磷、钾、钙、钛、铁元素含量的快速分析方法。以标准物质及标准物质与基准试剂氧化镁、氧化钙人工混合配制标样的方法建立标准工作曲线,重点讨论了熔剂和脱模剂的选取。最佳熔样条件：采用8.0g四硼酸锂和偏硼酸锂混合熔剂(质量比67: 33)+0.8g样品并添加溴化锂作为脱模剂,熔样温度1100℃,熔样时间10min。该方法相对标准偏差(n=12)均小于5.57%,绿泥石样品测定结果与化学法一致,硅酸盐标准物质测定结果均满足不确定度要求。     

Speckle characteristics of simulated deep Fresnel region under shadowing effect

After the three-dimensional self-affine fractal random surface simulation, we use the optical scattering theory to calculate the deep Fresnel region speckle(DFRS) under consideration of the more strict shadowing effect. The evolution of DFRS with the scattering distance and the intensity probability distribution are studied. It is found that the morphology of the scatterer has an antisymmetric relationship with the intensity distribution of DFRS, and the effect of micro-lenses on the scattering surface causes the intensity probability distribution of DFRS to deviate from the Gaussian speckle in the high light intensity area.     

Space-Air-Ground Integrated Mobile Crowdsensing for Partially Observable Data Collection by Multi-Scale Convolutional Graph Reinforcement Learning

Mobile crowdsensing (MCS) is attracting considerable attention in the past few years as a new paradigm for large-scale information sensing. Unmanned aerial vehicles (UAVs) have played a significant role in MCS tasks and served as crucial nodes in the newly-proposed space-air-ground integrated network (SAGIN). In this paper, we incorporate SAGIN into MCS task and present a Space-Air-Ground integrated Mobile CrowdSensing (SAG-MCS) problem. Based on multi-source observations from embedded sensors and satellites, an aerial UAV swarm is required to carry out energy-efficient data collection and recharging tasks. Up to date, few studies have explored such multi-task MCS problem with the cooperation of UAV swarm and satellites. To address this multi-agent problem, we propose a novel deep reinforcement learning (DRL) based method called Multi-Scale Soft Deep Recurrent Graph Network (ms-SDRGN). Our ms-SDRGN approach incorporates a multi-scale convolutional encoder to process multi-source raw observations for better feature exploitation. We also use a graph attention mechanism to model inter-UAV communications and aggregate extra neighboring information, and utilize a gated recurrent unit for long-term performance. In addition, a stochastic policy can be learned through a maximum-entropy method with an adjustable temperature parameter. Specifically, we design a heuristic reward function to encourage the agents to achieve global cooperation under partial observability. We train the model to convergence and conduct a series of case studies. Evaluation results show statistical significance and that ms-SDRGN outperforms three state-of-the-art DRL baselines in SAG-MCS. Compared with the best-performing baseline, ms-SDRGN improves 29.0% reward and 3.8% CFE score. We also investigate the scalability and robustness of ms-SDRGN towards DRL environments with diverse observation scales or demanding communication conditions.     

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.     

An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher

In order to improve the transmission efficiency and security of image encryption, we combined a ZUC stream cipher and chaotic compressed sensing to perform image encryption. The parallel compressed sensing method is adopted to ensure the encryption and decryption efficiency. The ZUC stream cipher is used to sample the one-dimensional chaotic map to reduce the correlation between elements and improve the randomness of the chaotic sequence. The compressed sensing measurement matrix is constructed by using the sampled chaotic sequence to improve the image restoration effect. In order to reduce the block effect after the parallel compressed sensing operation, we also propose a method of a random block of images. Simulation analysis shows that the algorithm demonstrated better encryption and compression performance.