阳极真空弧沉积装置及弧特性初步诊断

介绍一种新的真空弧沉积实验装置。在１５～４０Ａ的电流范围内，对Ａ１弧等离子体的特性进行了初步诊断。在２５Ａ弧电流下，电子温度为０．４～０．８ｅＶ，电子浓度为１０１５～１０１７ｍ－３。     

Facile Synthesis of Tricyclic 1,2,4-Oxadiazolines-Fused Tetrahydro-Isoquinolines from Oxime Chlorides with 3,4-Dihydroisoquinoline Imines

A mild and efficient strategy for the synthesis of tricyclic 1,2,4-oxadiazolines-fused tetrahydro-isoquinolines derivatives via [3 + 2] cycloaddition reaction is reported. The reactions provided the functionalized tricyclic 1,2,4-oxadiazolines in high yields (up to 96%). This protocol is simple and easy to handle. Moreover, a gram-scale experiment further highlights the synthetic utility. The chemical structure of the product was determined by X-ray single-crystal structure analysis. A possible mechanism for this transformation is proposed to explain the reaction process.     

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.     

Growth regulation of luminescent gold nanoparticles directed from amphiphilic block copolymers:highly-controlled nanoassemblies toward tailored in-vivo transport

The understanding of amphiphilic block copolymers(ABC)in encapsulation and transport of inorganic nanomedicines is highly desired.Still,it remains limited due to the challenges in the fabrication of nanoassemblies(NAs)with highly-controlled shape and loading of nanoparticles.Herein,through growth regulation of luminescent gold nanoparticles(Au NPs)by different reductants with ABC pluronic F127 as a template,a straightforward strategy is reported for in-situ fabrication of three wellcontrolled gold NAs(Au NAs)that display tunable shapes from spherical to elongated nanostructures and controllable surface chemistry and loading of Au NPs with distinct emissions but identical individual Au NP size.The three Au NAs exhibit tailored invivo transport behaviours:those with spherical shape and more hydrophilic surface show longer blood retention with higher tumor-targeting efficiency(~25.3%injection dose/g)and excellent long-term near-infrared tumor imaging even after 96 h postinjection.These findings provide a useful guidance in designing specific nanostructures for future nanomedicine transport.     

Electronic structure of strongly correlated systems: recent developments in multiconfiguration pair-density functional theory and multiconfiguration nonclassical-energy functional theory

Strong electron correlation plays an important role in transition-metal and heavy-metal chemistry, magnetic molecules, bond breaking, biradicals, excited states, and many functional materials, but it provides a significant challenge for modern electronic structure theory. The treatment of strongly correlated systems usually requires a multireference method to adequately describe spin densities and near-degeneracy correlation. However, quantitative computation of dynamic correlation with multireference wave functions is often difficult or impractical. Multiconfiguration pair-density functional theory (MC-PDFT) provides a way to blend multiconfiguration wave function theory and density functional theory to quantitatively treat both near-degeneracy correlation and dynamic correlation in strongly correlated systems; it is more affordable than multireference perturbation theory, multireference configuration interaction, or multireference coupled cluster theory and more accurate for many properties than Kohn–Sham density functional theory. This perspective article provides a brief introduction to strongly correlated systems and previously reviewed progress on MC-PDFT followed by a discussion of several recent developments and applications of MC-PDFT and related methods, including localized-active-space MC-PDFT, generalized active-space MC-PDFT, density-matrix-renormalization-group MC-PDFT, hybrid MC-PDFT, multistate MC-PDFT, spin–orbit coupling, analytic gradients, and dipole moments. We also review the more recently introduced multiconfiguration nonclassical-energy functional theory (MC-NEFT), which is like MC-PDFT but allows for other ingredients in the nonclassical-energy functional. We discuss two new kinds of MC-NEFT methods, namely multiconfiguration density coherence functional theory and machine-learned functionals.

This feature article overviews recent work on active spaces, matrix product reference states, treatment of quasidegeneracy, hybrid theory, density-coherence functionals, machine-learned functionals, spin–orbit coupling, gradients, and dipole moments.     

Interfacial Charge Transfer Induced Electronic Property Tuning of MoS_2 by Molecular Functionalization

The modulation of electrical properties of MoS_2 has attracted extensive research interest because of its potential applications in electronic and optoelectronic devices.Herein,interfacial charge transfer induced electronic property tuning of MoS_2 are investigated by in situ ultraviolet photoelectron spectroscopy and x-ray photoelectron spectroscopy measurements.A downward band-bending of MoS_2-related electronic states along with the decreasing work function,which are induced by the electron transfer from Cs overlayers to MoS_2,is observed after the functionalization of MoS_2 with Cs,leading to n-type doping.Meanwhile,when MoS_2 is modified with 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane(F_4-TCNQ),an upward band-bending of MoS_2-related electronic states along with the increasing work function is observed at the interfaces.This is attributed to the electron depletion within MoS_2 due to the strong electron withdrawing property of F_4-TCNQ,indicating p-type doping of MoS_2.Our findings reveal that surface transfer doping is an effective approach for electronic property tuning of MoS_2 and paves the way to optimize its performance in electronic and optoelectronic devices.     

Anisotropic Superconducting Properties of Kagome Metal CsV_3Sb_5

We systematically measure the superconducting(SC) and mixed state properties of high-quality CsV_3 Sb_5 single crystals with T_c～3.5 K.We find that the upper critical field H_(c2)(T) exhibits a large anisotropic ratio of H_(c2)~(ab)/H_(c2)~c～9 at zero temperature and fitting its temperature dependence requires a minimum two-band effective model.Moreover,the ratio of the lower critical field,H_(c1)~(ab)/H_(c1)~c,is also found to be larger than 1,which indicates that the in-plane energy dispersion is strongly renormalized near Fermi energy.Both H_(c1)(T) and SC diamagnetic signal are found to change little initially below T_c～3.5 K and then to increase abruptly upon cooling to a characteristic temperature of ～2.8 K.Furthermore,we identify a two-fold anisotropy of in-plane angular-dependent magnetoresistance in the mixed state.Interestingly,we find that,below the same characteristic T～2.8 K,the orientation of this two-fold anisotropy displays a peculiar twist by an angle of 60° characteristic of the Kagome geometry.Our results suggest an intriguing superconducting state emerging in the complex environment of Kagome lattice,which,at least,is partially driven by electron-electron correlation.     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.