Direct electron transfer reaction of glucose oxidase at bare silver electrodes and its application in analysis

The direct electron transfer reaction of glucose oxidase (GOx) at a bare silver electrode is verified. The electron transfer number n = 2, electron transfer coefficient α = 0.45 and rate constant of the electrochemical reaction K_s = 0.1 s⁻¹ are obtained. This communication presents a multimolecular adsorption model to explain the properties of the direct electron reaction between GOx and bare silver electrodes. The residual valence force may be an important factor to ensure a direct electron transfer reaction on the bare electrode. On the basis of the experimental fact that only biologically active GOx exhibits electrochemical activity in solution, a facile analytical method for analyzing the active GOx concentration is developed. The results determined correspond very well to that of a spectrometric method.     

Labile rhizosphere soil solution fraction for prediction of bioavailability of heavy metals and rare earth elements to plants

A labile rhizosphere soil solution fraction has been recommended to predict the bioavailability of heavy metals and rare earth elements to plants. This method used moist rhizosphere soil in combination with a mixture of 0.01 mol L(-1) of low-molecular-weight organic acids (LMWOAs) as extractant. The extracted soil solutions were fractionated into two colloidal fractions of <0.45 microm (F(3)) and <0.2 microm (F(2)), and one truly dissolved fraction including free metal ions and inorganic and organic complexes (fractionr(0.2 microm, LMWOAs) approximately r(0.45 microm, LMWOAs). In the case of rare earth elements the good correlation was obtained for both the wheat roots and shoots. Generally, the correlation coefficients obtained by LMWAOs were better than that obtained by the first step of BCR method. Therefore, LMWAOs and F(lrss) were strongly recommended to predict the bioavailability of metals in soil pools to plants.     

α''-取代磺酰基-α,β-不饱和酮的不对称催化环加成反应的研究

在手性金属钛配合物催化剂存在下，研究了α′－取代磺酰基－α，β－不饱和酮的不对称催化环加成反应；讨论了α，β－不饱和酮各种取代磺酰基对反应活性和对映选择性的影响；高收率地合成了高光学纯度的环加成产物，并对环加成产物的构型进行了鉴定。     

镓改性ZSM-5沸石中镓活性中心的形成与表征

采用脉冲微反体系研究了经不同程度还原和不同镓含量的GaZSM-5沸石的芳构化性能与吡啶吸附红外光谱特征谱带吸收度的关联，证实了1458 cm~(-1)吸收带的用于表征与Ga物种有关的活性中心，并研究了沸石的硅铝比对Ga中心形成和Ga的价态对芳构化性能的影响。结果表明，对Ga含量相同的样品来说，硅铝比愈低，起始Ga中心生成量愈多，高价态与低价态的Ga中心对丙烷芳构化反应都有促进作用。     

Development of ELISA and immunochromatographic assay for ofloxacin

Two rapid,sensitive and reliable immunoassay methods,namely competitive indirect enzyme-linked immunosorbent assay(CI- ELISA)and colloidal gold-based immunochromatographic assay(CGIA),were developed to detect ofloxacin(OFL).The linear range of the CI-ELISAwas from 0.5 to 128 ng/mL with a limit of detection(LOD)of 0.35 ng/mL.Good recoveries were obtained in analyzing simulated swine urine samples.The CGIA could accurately estimate OFL at concentrations as low as 10 ng/mL in less than 10 min,and test results were read visually without any instrument.     

螺［异苯并呋喃－1（3H），9＇－（9H）－2＇－N，N－二苄胺基－6＇－二乙胺基占吨］－酮－3的合成及晶体结构研究

合成了螺［异苯并呋喃－１（３Ｈ），９＇－（９Ｈ）－２＇－Ｎ，Ｎ－二苄胺基－６＇－二乙胺基占吨］－酮－３，Ｃ＿（３７）Ｈ＿（３４）Ｎ＿２Ｏ＿３，单斜晶系，空间群Ｃｃ，晶体学参数为ａ＝１６．８２６（４），ｂ＝１０．６４８（４），ｃ＝１７．６１８（７），β＝９２．２５（２）°，Ｖ＝３１５４（２），Ｚ＝４，Ｍ＿ｒ＝５６６．７，Ｄ＿ｘ＝１．１９ｇ／ｃｍ３，Ｆ（０００）＝１２００。结构由直接法解出，偏离因子Ｒ＝０．０８０。分子由占吨和异苯并呋喃两部分组成Ｙ形结构，占吨部分相连的苄基的两个苯环位于占吨部分的两侧。     

A Highly diastereoselective synthesis of (1R)-(+)-camphor-based chiral allenes and their asymmetric hydroboration-oxidation reactions

Synthesis of camphor derived chiral allenes and their hydroboration-oxidation reactions are described. Reaction of (1R)-(+)-camphor with alkynyllithium followed by the reduction of the resulted propargyl alcohol derivatives using AlH3 furnished chiral allenes 2a-g in excellent yields with high diastereoselectivity. Reduction of the propargyl alcohols with aluminum hydride proceeded through selective intermolecular anti-addition of hydride ion. The stereochemistry of the chiral allenes 2 was assigned based on lanthanide shift studies and chemical correlations. Diastereoselectivity was observed in the hydroboration-oxidation of 2 which produced a mixture of (E,R) and (E,S) stereoisomers in a ratio of 6:1 to 18:1.     

Synthesis and Characterization of 1,8-bis(ferrocenylmethyl)-5,5,12,12,14-hexamethyl-1,4,8,11-tetraazacyclotetradecane, a Macrocyclic Ligand and its Complexes

A new diferrocenyl-substituted macrocyclic ligand (H₂L) and its complexes ML(M = Cu^II, Ni^II, Zn^II, Cd^II) were prepared and characterized by IR, elemental analysis, absorption spectra and FAB mass spectra. The ferrocenyl-substituted macrocyclic ligand was characterized by single crystal X-ray diffraction analysis. The superconjugative effect of the cyclopentadienyl (CP) rings increase the activity of the hydrogen atoms in the tetra-azacyclotetradecane macrocyclic ligand. The imine nitrogen atoms lose two protons and coordinate to the metal. The electrochemical properties of these compounds are discussed.     

BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules

A broad collection of technologies, including e.g. drug metabolism, biofuel combustion, photochemical decontamination of water, and interfacial passivation in energy production/storage systems rely on chemical processes that involve bond-breaking molecular reactions. In this context, a fundamental thermodynamic property of interest is the bond dissociation energy (BDE) which measures the strength of a chemical bond. Fast and accurate prediction of BDEs for arbitrary molecules would lay the groundwork for data-driven projections of complex reaction cascades and hence a deeper understanding of these critical chemical processes and, ultimately, how to reverse design them. In this paper, we propose a chemically inspired graph neural network machine learning model, BonDNet, for the rapid and accurate prediction of BDEs. BonDNet maps the difference between the molecular representations of the reactants and products to the reaction BDE. Because of the use of this difference representation and the introduction of global features, including molecular charge, it is the first machine learning model capable of predicting both homolytic and heterolytic BDEs for molecules of any charge. To test the model, we have constructed a dataset of both homolytic and heterolytic BDEs for neutral and charged (−1 and +1) molecules. BonDNet achieves a mean absolute error (MAE) of 0.022 eV for unseen test data, significantly below chemical accuracy (0.043 eV). Besides the ability to handle complex bond dissociation reactions that no previous model could consider, BonDNet distinguishes itself even in only predicting homolytic BDEs for neutral molecules; it achieves an MAE of 0.020 eV on the PubChem BDE dataset, a 20% improvement over the previous best performing model. We gain additional insight into the model''s predictions by analyzing the patterns in the features representing the molecules and the bond dissociation reactions, which are qualitatively consistent with chemical rules and intuition. BonDNet is just one application of our general approach to representing and learning chemical reactivity, and it could be easily extended to the prediction of other reaction properties in the future.

Prediction of bond dissociation energies for charged molecules with a graph neural network enabled by global molecular features and reaction difference features between products and reactants.     

烟气中多环芳烃吸附脱除的研究

针对热电厂烟气中排放的多环芳烃（PAHs）污染物，在实验室规模上研究了六种吸附剂对烟气中典型的PAHs, 如萘（Nap）、芴（Flu）、菲（Phe）的吸附脱除行为。考察了吸附剂结构特征与Nap，Flu，Phe高温脱除的相关性，并对煤质活性炭（AC-1）在160 ℃～200 ℃下的吸附等温线进行了研究。结果表明，吸附剂对PAHs的吸附能力与其结构参数中BET表面积和微孔体积具有紧密相关性，而与中孔体积没有明显关系；活性炭表现出很好的脱除烟气中PAHs的作用；吸附剂对PAHs的吸附能力随着PAHs的质量分数增大而增大，随吸附温度的增加而减小；随着PAHs的碳原子数和芳环数增加，其在吸附剂上的吸附能力也增强。