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Synthesis of chiral phosphine derivatives through a copper（I）-catalyzed desymmetric SNAr reaction

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Science China Chemistry 2025年

作者： Shuai Zhang Pei-Zhi liu Yan-Bo Li Qi Zhang Jun-Zhao Xiao Yi-Fan Wang Tian-Yu Wei Jia-Wei Jiang Ye Wang Qian Peng liang Yin Key Laboratory of Fluorine and Nitrogen Chemistry and Advanced Materials Shanghai Institute of Organic Chemistry University of Chinese Academy of Sciences Chinese Academy of Sciences State Key Laboratory of Elemento-Organic Chemistry and Tianjin Key Laboratory of Biosensing and Molecular Recognition College of Chemistry Frontiers Science Center for New Organic Matter Nankai University Haihe Laboratory of Sustainable Chemical Transformations

Axially chiral phosphines are a class of extremely important ligands in asymmetric catalysis. Herein, an unprecedented copper（I）-catalyzed asymmetric SNAr reaction with HP（S）R2is uncovered, which delivers a series of axially chiral phosphine derivatives in high yields with excellent enantioselectivity. Furthermore, the diastereoselective reaction with the kinetic resolution of racemic HP（S）ArR proceeds smoothly, providing the products with moderate diastereoselectivity and excellent enantioselectivity. Control experiments indicate that HP（S）Ph2is much more active than HPPh2and HP（O）Ph2as the pronucleophile in the present reaction. It is found that the SNAr reaction （the first SNAr） proceeds in a desymmetric manner, providing the desired chiral products while a continued SNAr reaction （the second SNAr） slightly occurs in a kinetic resolution manner in the present catalytic system, which enhances the ee of the desired chiral products. DFTcalculations support a concerted reaction pathway rather than a step-wise mechanism. Finally, axially chiral olefin-phosphines produced by the present method work as suitable ligands in Pdcatalyzed asymmetric allylic substitution with C-, N-, and O-nucleophiles and Rh-catalyzed asymmetric addition of arylboronic acid to benzil.

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Deciphering fungal metabolon coupling tandem inverse-electrondemand Diels-Alder reaction and semipinacol rearrangement for the biosynthesis of spiro polycyclic alkaloids

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Science China Chemistry 2025年第01期 288-296页

作者： Shuai liu Wen-Qiang Xu Ying-Tong Di Man-Cheng Tang Ding-Kang Chen ming-ming Cao Yao-Wen Chang Hong-Yu Tang Chun-Mao Yuan Jun-Bo Yang Zhi-Li Zuo Han Guo Zi-Fei Xu Ying Zeng Yun-Dong Wu Xiao-Jiang Hao Key Laboratory of Phytochemistry and Natural Medicines (Chinese Academy of Sciences) Kunming Institute of Botany Chinese Academy of Sciences University of Chinese Academy of Sciences Lab of Computational Chemistry and Drug Design State Key Laboratory of Chemical Oncogenomics Peking University Shenzhen Graduate School Shenzhen Bay Laboratory State Key Laboratory of Microbial Metabolism School of Life Sciences & Biotechnology Shanghai Jiao Tong University State Key Laboratory of Functions and Applications of Medicinal Plants Guizhou Medical University Molecular Biology Experimental Center Germplasm Bank of Wild Species in Southwest China Kunming Institute of Botany Chinese Academy of Sciences Yunnan Key Laboratory for Wild Plant Resources Kunming Institute of Botany Chinese Academy of Sciences Research Unit of Chemical Biology of Natural Anti-Virus Products Chinese Academy of Medical Sciences

In the intricate process of natural product biosynthesis, a metabolon can enhance metabolic flux by associating sequential enzymes. A fungal metabolon, comprising of flavin-dependent monooxygenase Spe F and P450 monooxygenase Spe G, is identified in the biosynthesis of spiro polycyclic alkaloids(+)-notoamide B and its diastereomer(+)-versicolamide B. Using notoamide E as a substance, Spe F/Spe G metabolon can control the stereoselectivity of its 2,3-epoxidation, followed by hydrogen atom ion at C-17 to generate reactive epoxide tau-m A with dienyl iminium unit. Subsequently,(+)-notoamide B and(+)-versicolamide B are produced via tandem nonenzymatic inverse-electron-demand Diels-Alder reaction and semipinacol rearrangement. This provides the first example of metabolon in the biosynthesis of spiro-prenylated indole alkaloids.

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Intrinsic feature extraction using discriminant diffusion mapping analysis for automated tool wear evaluation

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Frontiers of Information Technology & Electronic Engineering 2018年第11期19卷 1352-1361页

作者： Yi-xiang HUANG Xiao liu Cheng-liang liu Yan-ming LI State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Aerospace Equipment Manufacturer Shanghai 200245China

We present a method of discriminant diffusion maps analysis(DDMA) for evaluating tool wear during milling processes. As a dimensionality reduction technique, the DDMA method is used to fuse and reduce the original features extracted from both the time and frequency domains, by preserving the diffusion distances within the intrinsic feature space and coupling the features to a discriminant kernel to refine the information from the high-dimensional feature space. The proposed DDMA method consists of three main steps:(1) signal processing and feature extraction;(2) intrinsic dimensionality estimation;(3) feature fusion implementation through feature space mapping with diffusion distance preservation. DDMA has been applied to current signals measured from the spindle in a machine center during a milling experiment to evaluate the tool wear status. Compared with the popular principle component analysis method, DDMA can better preserve the useful intrinsic information related to tool wear status. Thus, two important aspects are highlighted in this study: the benefits of the significantly lower dimension of the intrinsic features that are sensitive to tool wear, and the convenient availability of current signals in most industrial machine centers.

关键词： Tool condition monitoring Manifold learning Dimensionality reduction Diffusion mapping analysis Intrinsic feature extraction

Effect of W addition on hot deformation and precipitation behaviors of 19Cr2Mo ferritic stainless steel

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Journal of Iron and Steel Research International 2019年第5期26卷 425-434页

作者： Hou-long liu ming-yu Ma Ling-ling liu liang-liang Wei Li-qing Chen State Key Laboratory of Rolling and Automation Northeastern University Shenyang 110819 Liaoning China

The hot deformation behavior of 19Cr2Mo and 19Cr2Mo1W ferritic stainless steels was studied by using uniaxial hot compression tests on a thermomechanical simulator. The hot deformation was carried out at temperature ranging from 800 to 1150℃ and strain rates from 0.01 to 10 s^-1. Microstructure change and precipitation behavior during hot deformation were investigated by optical microscopy, electron probe microanalysis and transmission electron microscopy. The effects of temperature and strain rate on deformation behavior were obtained by a classical equation in Zener-Hollomon parameter. Since W addition to 19Cr2Mo1W steel could refine the size of the precipitates to enhance the precipitation strengthening and also had the effect of solution strengthening, the dynamic recrystallization, dynamic recovery and grain growth of 19Cr2Mo1W ferritic stainless steel were inhibited to a certain extent. The precipitate size of 19Cr2Mo1W steel was finer than that of 19Cr2Mo steel under the same deformation condition, which is due to the fact that the atomic diffusion is suppressed by W addition. W addition increased the amount of Laves phase in 19Cr2Mo1W steel, and thus Laves phase in 19Cr2Mo1W steel could be formed at higher temperature than that in 19Cr2Mo steel.

关键词： Ferritic stainless steel Tungsten Hot deformation behavior Microstructure evolution Precipitation Laves phase

Research and Optimization of GPSR Routing Protocol for Vehicular Ad-Hoc Network

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China Communications 2022年第10期19卷 194-206页

作者： Jianming Cui liang Ma Ruirui Wang ming liu School of Information Engineering Chang'an UniversityXi'an 710064China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029China

Security is one of the most critical issues to Vehicular Ad-hoc Networks (VANETs) since the information transmitted is asynchronous and distributed. Vulnerability and instability are two of the challenges remain to be addressed by the research community and the industry. In this paper, we first proposed a trust reliability based model and extended the GPSR protocol to TM-GPSR protocol. Then, we improved the LET-GPSR protocol based on the link connection time prediction. On this basis, combined the decision index of the TM-GPSR and LET-GPSR protocols, we proposed the RC-GPSR routing protocol. We built the standard testing platform on the NS2 and SUMO, the average end-to-end delay and packet delivery rate of GPSR protocol and the three updates protocols under different node density, node speed, and malicious node ratio are simulated and evaluated. The results showed that under the same conditions, compared with GPSR protocol, RC-GPSR protocol has a lower average end-to-end delay and a higher packet delivery rate, which effectively improves the link stability and security.

关键词： VANET GPSR protocol trust reliability link connection time

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高原铁路某特长隧道独头掘进通风技术分析

山西建筑 2025年第1期51卷 150-153页

作者：梁星刘明杨琨曾强中铁隧道局集团一处有限公司重庆404100

文章面向高原铁路特长隧道,开展通风技术研究,提出一种基于避车洞通风技术、人行通道通风技术的蓄风房通风策略。基于高原铁路特长隧道通风案例,研究了蓄风房技术。文中研究成果供我国高原铁路特长隧道建设单位、运营单位加以参考、借鉴... 详细信息

文章面向高原铁路特长隧道,开展通风技术研究,提出一种基于避车洞通风技术、人行通道通风技术的蓄风房通风策略。基于高原铁路特长隧道通风案例,研究了蓄风房技术。文中研究成果供我国高原铁路特长隧道建设单位、运营单位加以参考、借鉴,以保证特长隧道通风性能,满足相关制度、规范对高原铁路特长隧道的环境要求,并实现铁路通风的节能效果。

关键词：高原铁路特长隧道蓄风房避车洞

Unsupervised noise-robust feature extraction for aerial image classification

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Science China(Technological Sciences) 2020年第8期63卷 1406-1415页

作者： liang Ye LU Shuai WENG Rui HAN ChengZhe liu ming School of Astronautics Harbin Institute of TechnologyHarbin 150001China Academy of Art Harbin University of Science and TechnologyHarbin 150001China Academy of Software and Microelectronics Harbin University of Science and TechnologyHarbin 150001China

The rich data provided by satellites and unmanned aerial vehicles bring opportunities to directly model aerial image features by extracting their spatial and structural *** convolutional autoencoders(CAEs)have been attained a remarkable performance in ideal aerial image feature extraction,they are still challenging to extract information from noisy images which are generated from capture and *** this paper,a novel CAE-based noise-robust unsupervised learning method is proposed for extracting high-level features accurately from aerial images and mitigating the effect of *** from conventional CAEs,the proposed method introduces the noise-robust module between the encoder and the ***,several pooling layers in CAEs are replaced by convolutional layers with stride=*** performance of feature extraction is evaluated by the prediction accuracy and the accuracy loss in image classification experiments.A 5-classes aerial optical scene and a 9-classes hyperspectral image(HSI)data set are utilized for optical image and HSI feature extraction,*** features extracted from aerial images are utilized for image classification by a linear support vector machine(SVM)*** results indicate that the proposed method improves the classification accuracy for noisy images(Gaussian noise 2Dσ=0.1,3Dσ=60)in both optical images(2D 87.5%)and HSIs(3D 85.6%)compared with the traditional CAE(2D 78.6%,3D 84.2%).The accuracy loss in classification experiments increases with the increment of *** with the traditional CAE(2D 15.7%,3D 11.8%),the proposed method shows the lower classification accuracy loss in experiments(2D 0.3%,3D 6.3%).The proposed unsupervised noise-robust feature extraction method attains desirable classification accuracy in ideal input and enhances the feature extraction capability from noisy input.

关键词： aerial image classification convolutional autoencoder feature extraction noise-robust

Defense of Massive False Data Injection Attack via Sparse Attack Points Considering Uncertain Topological Changes

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Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1588-1598页

作者： Xiaoge Huang Zhijun Qin ming Xie Hui liu liang Meng School of Electrical Engineering Guangxi UniversityNanningChina Guangxi Power Grid Co.Ltd. China Southern Grid(CSG)GuilinChina

False data injection attack(FDIA)is a typical cyber-attack aiming at falsifying measurement data for state estimation(SE),which may incur catastrophic consequences on cyber-physical system *** this paper,we develop a deep learning based methodology for detection,localization,and data recovery of FDIA on power systems in a coherent and holistic ***,the multi-modal probability distributions of both measurements and state variables in SE due to ever-changing operating points and structural/topological changes pose great challenges in detecting and localizing *** address this challenge,we first propose an enhanced attack model to launch massive FDIA on limited access ***,we train an auto-encoder(AE)with a Bayesian change verification(BCV)classifier using N-1 contingencies to detect FDIA with unseen N-k operational ***,to avoid model collapse caused by multi-modal measurement distribution,an AE-based generative adversarial network(GAN)is derived to generate a diverse candidate set of normal measurement vectors with various operational ***,we develop a pattern match algorithm to localize and recover the falsified measurements and state variables by comparing the falsified measurement vectors with the normal measurement vectors in the candidate *** studies with IEEE benchmark systems and a modified 415-bus China Southern Grid system are provided to validate the proposed *** shows that the proposed methodology achieves an average 95%accuracy for detection,over 80%accuracy for localization of FDIA,and recovers the measurement and state variables close to their true values.

关键词： False data injection attack auto-encoder generative adversarial network state estimation cyber security

Hybrid architecture design enhances the areal capacity and cycling life of low-overpotential nanoarray oxygen electrode for lithium–oxygen batteries

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Journal of Energy Chemistry 2020年第7期29卷 248-255,I0008页

作者： liang Xiao Duo Wang ming Li Bohua Deng Jinping liu School of Chemistry Chemical Engineering and Life ScienceWuhan University of TechnologyWuhan 430070HubeiChina State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070HubeiChina

Transition metal oxide(TMO)nanoarrays are promising architecture designs for self-supporting oxygen electrodes to achieve high catalytic activities in lithium-oxygen(Li-O2)***,the poor conductive nature of TMOs and the confined growth of nanostructures on the limited surfaces of electrode substrates result in the low areal capacities of TMO nanoarray electrodes,which seriously deteriorates the intrinsically high energy densities of Li-O2 ***,we propose a hybrid nanoarray architecture design that integrates the high electronic conductivity of carbon nanoflakes(CNFs)and the high catalytic activity of Co3 O4 nanosheets on carbon cloth(CC).Due to the synergistic effect of two differently featured components,the hybrid nanoarrays(Co3 O4-CNF@CC)achieve a high reversible capacity of3.14 mA h cm-2 that cannot be achieved by only single ***,CNFs grown on CC induce the three-dimensionally distributed growth of ultrafine Co3 O4 nanosheets to enable the efficient utilization of ***,with the high catalytic efficiency,hybrid Co3 O4-CNF@CC also achieves a more prolonged cycling life than pristine TMO *** present work provides a new strategy for improving the performance of nanoarray oxygen electrodes via the hybrid architecture design that integrates the intrinsic properties of each component and induces the three-dimensional distribution of catalysts.

关键词： Hybrid architecture Nanoarray oxygen electrode Synergistic effect Three-dimensional current collector Lithium-oxygen batteries