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Recent advances of versatile reagents as controllable building blocks in organic synthesis

Chinese Chemical Letters 2024年第2期35卷 24-43页

作者： Shaomin Chen Luigi Vaccaro Yanlong gu Key Laboratory of Material Chemistry for Energy Conversion and Storage Ministry of EducationHubei Key Laboratory of Material Chemistry and Service FailureSchool of Chemistry and Chemical EngineeringHuazhong University of Science and TechnologyWuhan 430074China Laboratory of Green S.O.C. Dipartimento di ChimicaBiologia e BiotecnologieUniversità degli Studi di PerugiaVia Elce di Sotto 8Perugia 06123Italy School of Chemistry and Chemical Engineering The Key Laboratory for Green Processing of Chemical Engineering of Xinjiang BingtuanShihezi UniversityShihezi 832004China

Diversity-oriented synthesis is a powerful and interesting synthetic tool for the rapid construction of structurally complex and privileged scaffolds from readily accessible starting materials.To date,diversity-oriented synthesis mostly relies on the employment of versatile reagents.Versatile reagents can be regulated as controllable and flexible building blocks for multipurpose utilizations.Over the past decade,a variety of multifunctional reagents have been developed.However,most versatile reagents usually need multi-step synthesis,thus restricting their wide application to a large extent.In terms of the practicalities and universalities,we prefer to pay more attention to the utilization of simple and practical versatile reagents with multiple reactivities,mainly including atropaldehyde acetals,aryl methyl ketones,vinylene carbonate,vinyl azides,aryldiazonium salts,rongalite,halodifluoromethyl compounds.Most importantly,these versatile reagents can also play different roles simultaneously in the same reaction,in which their different reactivities are converged into the final target products.Such strategy can not only offer more possibilities for the synthesis of several active pharmaceutical ingredients,but also minimize the occurrence of some side reactions by lessening the varieties of materials.Also,a perspective is given at the end of this review.

关键词： Versatile reagents Divergent synthesis Dual synthons Bond cleavage Tandem reactions

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Efficient energy transfer from self-trapped excitons to Mn^(2+) dopants in CsCdCl_(3):Mn^(2+) perovskite nanocrystals

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International Journal of Minerals,Metallurgy and Materials 2024年第6期31卷 1456-1461页

作者： Anran Zhang Xinquan Zhou Ranran gu Zhiguo Xia State Key Laboratory of Luminescent Materials and Devices Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied TechniquesSchool of Materials Science and EngineeringSouth China University of TechnologyGuangzhou 510641China School of Physics and Optoelectronics South China University of TechnologyGuangzhou 510641China

Mn^(2+)doping has been adopted as an efficient approach to regulating the luminescence properties of halide perovskite nano-crystals(NCs).However,it is still difficult to understand the interplay of Mn^(2+)luminescence and the matrix self-trapped exciton(STE)emission therein.In this study,Mn^(2+)-doped CsCdCl_(3) NCs are prepared by hot injection,in which CsCdCl_(3) is selected because of its unique crystal structure suitable for STE emission.The blue emission at 441 nm of undoped CsCdCl_(3) NCs originates from the defect states in the NCs.Mn^(2+)doping promotes lattice distortion of CsCdCl_(3) and generates bright orange-red light emission at 656 nm.The en-ergy transfer from the STEs of CsCdCl_(3) to the excited levels of the Mn^(2+)ion is confirmed to be a significant factor in achieving efficient luminescence in CsCdCl_(3):Mn^(2+)NCs.This work highlights the crucial role of energy transfer from STEs to Mn^(2+)dopants in Mn^(2+)-doped halide NCs and lays the groundwork for modifying the luminescence of other metal halide perovskite NCs.

关键词： perovskite nanocrystals self-trapped excitons luminescence energy transfer

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Transient Stability Analysis and Design of VSGs with Different DC-Link Voltage Controllers

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 593-604页

作者： Chao Shen Wei gu Wanxing Sheng Keyan Liu School of Electrical Engineering Southeast UniversityNanjingChina Power Distribution Research Department China Electric Power Research InstituteBeijing 100192China

Virtual synchronous control has been widely studied for the advantages of emulating inertia for voltage source converters (VSCs). A constant dc-link voltage is usually assumed in existing literature to estimate transient stability of virtual synchronous generators (VSGs). However, actual power supply in the dc-side of VSGs is limited and different dc-link voltage controllers are needed to achieve power balance between DC side and AC side. Addition of dc-link voltage controller has great influence on transient behavior of VSGs, which has not been investigated by previous research. To fill this gap, this paper gives insights into the effect of dc-link voltage dynamics on transient stability of VSGs. First, two typical kinds of VSGs with dc-link voltage controllers are introduced. Then, mathematical models considering dc-link dynamics are established and the effect of dc-link voltage controllers on transient synchronization stability of VSGs is revealed through equal area criterion (EAC). It is found that dc-link voltage controller would reduce stability margin of VSGs and design-oriented transient stability analysis is carried out quantitively using critical clearing time (CCT). Finally, simulation results are given to validate correctness of theoretical analysis.

关键词： DC-link voltage dynamics equal area criterion(eac) transient synchronization stability virtual synchronous generator(VSG)

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H∞ Robustness for Distributed Control in Autonomous Microgrids Considering Cyber Disturbances

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 696-706页

作者： Ge Cao guannan Lou Wei gu Lina Sheng School of Electrical Engineering Southeast UniversityNanjing 210096China

The physical connections and logical relationships between microgrids and communication networks allow microgrids to develop into typical cyber-physical systems(CPSs).With the extensive use of open communication mechanisms,the impact of cyber disturbances in public communication networks cannot be diminshed.In this paper,a parameter optimal method for a distributed secondary controller based on the robust control theory and consensus algorithm is presented to enhance the robustness of a secondary control system under data disturbance,parameter perturbation,and time delay.First,a distributed secondary control strategy of microgrids is demonstrated that coordinates frequency and voltage restoration and power sharing.Then,considering the impact of cyber events on the secondary control,a distributed robust controller gain design method is proposed to satisfy the H∞ performance index.The solution of the distributed robust control is transformed into a linear matrix in equation problem and latency margin is simultaneously obtained.Finally,a test microgrid CPS is simulated with and without time delay to investigate the impact of cyber events on system operational states and the effectiveness and robustness of the proposed method.

关键词： Cyber disturbance cyber-physical lsystem distributed control microgrid robust H∞control

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Experimental investigation on the gravity driven discharge of cohesive particles from a silo with two outlets

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Particuology 2024年第6期89卷 11-21页

作者： Li Dai Zhulin Yuan Fengxian Fan Conghui gu School of Energy and Power Engineering University of Shanghai for Science and TechnologyShanghai 200093China Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing 210096China Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Energy and Power Jiangsu University of Science and TechnologyZhenjiang 212100China

An experimental study on the gravity driven discharge of cohesive particles from a silo with two outlets was performed.The discharge behaviors under the conditions that a single outlet was open and two outlets were open were investigated by varying the moisture content of the particles and the filling height of the particles in the silo.The results show that the discharge rate of the cohesive particles increases gradually at the beginning,then almost keeps constant,and finally drops obviously.The discharge rate in case of two openings is around 1.1–1.6 times that in case of a single opening.Larger filling height leads to lower discharge rate in case of a single opening but results in higher discharge rate in case of two openings.Furthermore,the avalanche dynamics in case of a single opening was examined,and the mixing behavior of the cohesive particles was evaluated.It is observed that the discharge flow is promoted by the avalanche phenomenon in the silo,generating a general trend that the normalized mass of discharge increases with the filling height at higher moisture contents.In case of a single opening,the transition from mass flow to funnel flow favors the particle mixing,resulting in an increasing mixing index as the moisture content increases.In general,a better performance of mixing can be achieved in case of a single opening compared with in case of two openings.This study provides vital information for fundamental understanding of the gravity driven discharge of cohesive particles from the silo with multiple outlets.

关键词： Cohesive particles Moisture content Discharge rate Avalanche Mixing

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Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories:Data analysis based on EEG and fNIRS

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Journal of Innovative Optical Health Sciences 2024年第3期17卷 41-55页

作者： Xuelin gu Xiaoou Li Banghua Yang College of Medical Instruments Shanghai University of Medicine&Health SciencesShanghai 201318P.R.China School of Mechanical and Electrical Engineering and Automation Shanghai UniversityShanghai 200444P.R.China

The electroencephalogram(EEG)rhythm and functional near-infrared spectroscopy(fNIRS)activation levels have not been compared between a healthy control group(HCG)and methamphetamine user group(MUG)with different addiction histories.This study used 64-electrode EEG and fNIRS to conduct an experiment that analyzed the resting and craving states.The EEG and fNIRS data of 56 participants were collected,including 14 healthy participants,14 methamphetamine users with an addiction history of 0.5–5 years,14 users with an addiction history of 5–10 years,and 14 users with an addiction history of 10–15 years.Isolated effective coherence(iCoh)within the brain network was used to process the EEG data.Statistical analysis was performed to compare differences in iCoh among the delta,theta,alpha,beta,and gamma bands and explore oxyhemoglobin activation levels in the ventrolateral prefrontal cortex,dorsolateral prefrontal cortex,orbitofrontal cortex,and frontopolar prefrontal cortex(FPC)of the control group.Finally,the Kmeans,Gaussian mixed model(GMM),linear discriminant analysis(LDA),support vector machine(SVM),Bayes,and convolutional neural networks(CNN)algorithms were used to classify methamphetamine users based on drug and neutral images.A 3-class accuracy was achieved.Changes in EEG and fNIRS activation levels of HCG and MUG with varied addiction histories were demonstrated.

关键词： Drug addiction history electroencephalogram functional near-infrared spectroscopy isolated effective coherence addiction history classification

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Flexible and Robust Functionalized Boron Nitride/Poly(p‑Phenylene Benzobisoxazole)Nanocomposite Paper with High Thermal Conductivity and Outstanding Electrical Insulation

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Nano-Micro Letters 2024年第2期16卷 423-437页

作者： Lin Tang Kunpeng Ruan Xi Liu Yusheng Tang Yali Zhang Junwei gu Chongqing Key Laboratory of Green Synthesis and Applications College of ChemistryChongqing Normal UniversityChongqing 401331People’s Republic of China Shaanxi Key Laboratory of Macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’an 710072People’s Republic of China

With the rapid development of 5G information technology,thermal conductivity/dissipation problems of highly integrated electronic devices and electrical equipment are becoming prominent.In this work,“high-temperature solid-phase&diazonium salt decomposition”method is carried out to prepare benzidine-functionalized boron nitride(m-BN).Subsequently,m-BN/poly(pphenylene benzobisoxazole)nanofiber(PNF)nanocomposite paper with nacremimetic layered structures is prepared via sol–gel film transformation approach.The obtained m-BN/PNF nanocomposite paper with 50 wt%m-BN presents excellent thermal conductivity,incredible electrical insulation,outstanding mechanical properties and thermal stability,due to the construction of extensive hydrogen bonds andπ–πinteractions between m-BN and PNF,and stable nacre-mimetic layered structures.Itsλ∥andλ_(⊥)are 9.68 and 0.84 W m^(-1)K^(-1),and the volume resistivity and breakdown strength are as high as 2.3×10^(15)Ωcm and 324.2 kV mm^(-1),respectively.Besides,it also presents extremely high tensile strength of 193.6 MPa and thermal decomposition temperature of 640°C,showing a broad application prospect in high-end thermal management fields such as electronic devices and electrical equipment.

关键词： Poly(p-phenylene-2,6-benzobisoxazole)nanofiber Boron nitride Thermal conductivity Electrical insulation

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Byzantine Robust Federated Learning Scheme Based on Backdoor Triggers

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Computers, Materials & Continua 2024年第5期79卷 2813-2831页

作者： Zheng Yang Ke gu Yiming Zuo School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China

Federated learning is widely used to solve the problem of data decentralization and can provide privacy protectionfor data owners. However, since multiple participants are required in federated learning, this allows attackers tocompromise. Byzantine attacks pose great threats to federated learning. Byzantine attackers upload maliciouslycreated local models to the server to affect the prediction performance and training speed of the global model. Todefend against Byzantine attacks, we propose a Byzantine robust federated learning scheme based on backdoortriggers. In our scheme, backdoor triggers are embedded into benign data samples, and then malicious localmodels can be identified by the server according to its validation dataset. Furthermore, we calculate the adjustmentfactors of local models according to the parameters of their final layers, which are used to defend against datapoisoning-based Byzantine attacks. To further enhance the robustness of our scheme, each localmodel is weightedand aggregated according to the number of times it is identified as malicious. Relevant experimental data showthat our scheme is effective against Byzantine attacks in both independent identically distributed (IID) and nonindependentidentically distributed (non-IID) scenarios.

关键词： Federated learning Byzantine attacks backdoor triggers

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Emergent symmetry in quantum phase transition:From deconfined quantum critical point to gapless quantum spin liquid

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Science Bulletin 2024年第2期69卷 190-196页

作者： Wen-Yuan Liu Shou-Shu Gong Wei-Qiang Chen Zheng-Cheng gu Department of Physics The Chinese University of Hong KongHong KongChina Division of Chemistry and Chemical Engineering California Institute of TechnologyPasadena CA 91125USA School of Physical Sciences Great Bay UniversityDongguan 523000China Great Bay Institute for Advanced Study Dongguan 523000China Department of Physics and Shenzhen Institute for Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Advanced Quantum Functional Materials and Devices Southern University of Science and TechnologyShenzhen 518055China

The emergence of exotic quantum phenomena in frustrated magnets is rapidly driving the development of quantum many-body physics,raising fundamental questions on the nature of quantum phase transitions.Here we unveil the behaviour of emergent symmetry involving two extraordinarily representative phenomena,i.e.,the deconfined quantum critical point(DQCP)and the quantum spin liquid(QSL)state.Via large-scale tensor network simulations,we study a spatially anisotropic spin-1/2 square-lattice frustrated antiferromagnetic(AFM)model,namely the J1x-J1y-J2 model,which contains anisotropic nearestneighbor couplings J1x,J1y and the next nearest neighbor coupling J2.For small J1y/J1x,by tuning J2,a direct continuous transition between the AFM and valence bond solid phase is observed.With growing J1y/J1x,a gapless QSL phase gradually emerges between the AFM and VBS phases.We observe an emergent O(4)symmetry along the AFM–VBS transition line,which is consistent with the prediction of DQCP theory.Most surprisingly,we find that such an emergent O(4)symmetry holds for the whole QSL–VBS transition line as well.These findings reveal the intrinsic relationship between the QSL and DQCP from categorical symmetry point of view,and strongly constrain the quantum field theory description of the QSL phase.The phase diagram and critical exponents presented in this paper are of direct relevance to future experiments on frustrated magnets and cold atom systems.

关键词： Tensor network Quantum phase transition Emergent symmetry Quantum spin liquid Deconfined quantum critical point Anisotropic

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Adversarial data splitting for domain generalization

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Science China(Information Sciences) 2024年第5期67卷 28-42页

作者： Xiang gu Jian SUN Zongben XU School of Mathematics and Statistics Xi'an Jiaotong University

Domain generalization aims to learn a model that is generalizable to an unseen target domain,which is a fundamental and challenging task in machine learning for out-of-distribution generalization. This paper proposes a novel domain generalization approach that enforces the learned model to be able to generalize well over the train/val subset splitting of the training dataset. This idea is modeled herein as an adversarial data splitting framework, formulated as a min-max optimization problem inspired by the metalearning approach. The min-max optimization problem is solved by iteratively splitting the training dataset into the training and val subsets to maximize the domain shift measured by the objective function and updating the model parameters to enable the model to generalize well from the training subset to the val subset by minimizing the objective function. This adversarial training approach does not assume the known domain labels of the training data; instead, it automatically investigates the “hard” splitting of the train/val subsets to learn the generalizable model. Extensive experimental results using three benchmark datasets demonstrate the superiority of this approach. In addition, we derive a generalization error bound for the theoretical understanding of our proposed approach.

关键词： domain generalization adversarial learning data splitting meta-learning out of distribution

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