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Table of Content

    31 October 2021, Volume 27 Issue 5
    Invited Review
    Revealing chemical bond motifs from wavefunction tiles using a dynamic Voronoi Metropolis sampling algorithm
    LIU Yu, LI Yongle, REN Wei
    2021, 27(5):  815-832.  doi:10.12066/j.issn.1007-2861.2311
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    The interpretation of chemical bonds is central to discussions in the physical and chemical sciences. Using quantum mechanics, the molecular orbitals (MOs) theory and valence bond (VB) theory are two of the most commonly applied theories to describe chemical bonds, despite their differences in describing certain electronic structures. In this article, first the history of the study of chemical bonds is reviewed, and thereafter it is focused on that of introducing a new algorithm, dynamic Voronoi Metropolis sampling (DVMS), which has been developed by our group. The research will be reviewed on chemical bonds studied by DVMS over the past few years and its potential applications are also discussed.

    Research Articles
    Calculation method of limit line loss of renewable energy distribution network
    ZHU Yue, GU Jie, WANG Chunyi, MOU Hong, CUI Guozhu, LI Yu, JIN Zhijian
    2021, 27(5):  833-845.  doi:10.12066/j.issn.1007-2861.2191
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    With the advancement of renewable energy technology and increasing demand, the access of distributed generations introduces volatility and uncertainty to the power flow distribution within medium voltage distribution networks. Consequently, the volatile and uncertain nature significantly hinders the accurate line loss calculation and establishment of grid assessment indicators. This study proposes a semi-invariant calculation model that aids realize an efficient calculation approach for limit line loss of the distribution network containing renewable energy. Initially, according to the power flow calculation and statistical data, the semi-invariants of each node and generations in the distribution network are calculated. Next, the distribution function and probability density function of each state index are calculated with the Gram-Charlier (GC) series expansion formula. Finally, the limit line loss of the distribution network is determined according to the confidence interval. IEEE34 node system is chosen as an example in this study to analyse the influence of different node distributed power access on distribution network. The calculation accuracy of line loss calculation model based on semi-invariant method and its calculation speed advantage in large-scale distribution network application is verified.

    Synthesis of alloyed In$_{{\bf 1-}x}$Ga$_{x}$P quantum dots and their application to LEDs
    YE Haiqiao, CAO Fan, DOU Yongjiang, YANG Xuyong
    2021, 27(5):  846-855.  doi:10.12066/j.issn.1007-2861.2186
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    As alternatives to quantum dots based on cadmium, a toxic heavy metal, low-toxicity indium phosphide quantum dots (InP QDs) have shown excellent potential for application in next-generation commercial displays and illumination devices. However, the synthesis of InP QDs with high photoluminescence quantum yields (PL QYs) remains challenging. Therefore, the use of gallium acetylacetonate is proposed as a gallium source to activate surface ligands via acetylacetone at a high temperature to form In$_{1-x}$Ga$_x$P/ZnSe/ZnS with a gradient alloyed core, effectively solving the lattice mismatch between InP and ZnSe. Meanwhile, the gradient alloyed core can reduce the defects among interfaces, such that the PL QY of quantum dots is up to 82% and the external quantum efficiency of the prepared quantum dot light-emitting diode (QLED) reaches 3.1%. Compared to QDs with the traditional InP/ZnSe/ZnS structure, the In$_{1-x}$Ga$_x$P/ZnSe/ZnS QDs yield a PL QY enhancement of 25%, and the external quantum efficiency of the device is nearly doubled. This scheme provides a new method for solving the problems of lowPL QY of InP QDs and poor performance of light-emitting devices.

    Bayesian inference for mixture of nonparametric regression models
    LI Daoyang, HE Youhua
    2021, 27(5):  856-865.  doi:10.12066/j.issn.1007-2861.2189
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    For mixing nonparametric regression models, an inference method is proposed based on the Bayesian framework. In this method, a finite dimensional distribution family of the stochastic process is used as a prior distribution for each nonparametric component, and Bayesian estimators of mixture proportions, each random error's variance, and nonparametric components are constructed respectively. A Markov chain Monte Carlo (MCMC) method is used for posterior inference. The numerical simulations are performed from the perspectives of sample size, relative position of the regression curve, and multiclassification. The results show that, compared with the generalised expectation maximisation (GEM) algorithm, the Bayesian inference method of mixing nonparametric regression can effectively use the prior information to improve the ability of fitting and prediction. Finally, the Bayesian inference method is applied to the experimental data from aphids and infected tobacco plants and solved clustering and regression problems. This also demonstrates the effectiveness and applicability of the method.

    Polyhedral bi-shell CO$_{\bf 3}$O$_{\bf 4}$-ZnO and its CO sensing performance
    YUAN Tongwei, ZHANG Wenshuang, MA Zhiheng, XU Jiaqiang
    2021, 27(5):  866-878.  doi:10.12066/j.issn.1007-2861.2193
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    Herein, Co-doped ZIF (zeolitic imidazolate framework)-8 was synthesised via static precipitation method using methanol as solvent. The synthesised ZIF-8 was subsequently annealed under air atmosphere in a tubular furnace, yielding polyhedral bi-shell Co$_{3}$O$_{4}$-ZnO. The composition, morphology, and thermal stability of the synthesised materials were characterised via X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and thermal gravimetric analyzer (TGA). Results show that the pure ZIF-8 remained stable at relatively low annealing temperature, whereas at higher annealing temperature, ZIF-8 transformed to a collapsed ZnO structure. The polyhedral bi-shell Co$_{3}$O$_{4}$-ZnO (CZO-4) was obtained by annealing 4% Co-doped ZIF-8 at a low temperature, suggesting that Co provides an active site for catalytic oxidation during the oxidation of ZIF-8 and reduces the oxidation barrier of 2-methylimidazole. Meanwhile, the low annealing temperature can provide sufficient forming process for ZnO to retain the rhombic dodecahedron structure. The oxidation growth process, catalysed by Co element, from outside to inside eventually results in the growth of ZnO into the bi-shell structure. When the Co loading is increased to 8%, the formation of bi-shell layer is not obvious (CZO-8). Compared with CZO-8 and ZnO, CZO-4 has better CO sensing performance, high sensitivity ($R_\mathrm a/R_\mathrm g = 21.8$@100$\times $10$^{-6}$ CO), high selectivity (up to 8.7 times of H$_{2}$ response), and long-term stability (stable signal in 42-day tests). This is because CZO-4 has a large specific surface area, gas transport channels, and Co as an active site for CO catalytic oxidation, resulting in an enhancement in gas sensing performance.

    Three-dimensional numerical simulations of suspended metal droplet oscillations in high-frequency, amplitude-modulated, alternating electromagnetic fields
    LIAN Jingjie, GUO Jiahong, LEI Zuosheng
    2021, 27(5):  879-890.  doi:10.12066/j.issn.1007-2861.2201
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    A three-dimensional numerical model for the oscillations of suspended metal droplets in a high-frequency, amplitude-modulated electromagnetic field is built. Numerical simulations of a suspended metal droplet oscillating in the high-frequency, amplitude-modulated electromagnetic field are also performed. The high-frequency, amplitude-modulated electromagnetic field and the flow of the liquid metal droplet are simulated via the finite element method. The free surface of the liquid metal droplet is calculated using the arbitrary Lagrange-Euler (ALE) method. The high-frequency, amplitude- modulated electromagnetic field; the flow of the liquid metal droplet; and the free surface of the oscillating droplet are determined numerically. The shape of the oscillating droplet, as obtained via the numerical simulation, is in good agreement with the experimental results. Furthermore, frequency analyses based on the numerical results of the oscillation of the droplet are in good agreement with the theoretical calculations.

    Local integrability and classification of nilpotent critical points
    WANG Yinzi, HU Zhaoping
    2021, 27(5):  891-906.  doi:10.12066/j.issn.1007-2861.2200
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    The integrability of planar polynomial differential systems and the complete classification of degenerate critical points are both important problems in the qualitative theory of ordinary differential equations. Currently, almost all results on the local integrability are related to a center, focus on real polynomial systems or a $p:-q$ resonant center for polynomial systems in a complex plane. The complete classification of a degenerate critical point is also very difficult, and there are few related studies on this. In this study, by considering polynomial systems with a nilpotent critical point (0, 0), the corresponding theory is established for local integrability and present a method for the complete classification of nilpotent critical points under each integrable condition. Moreover, the necessary and sufficient condition is obtained for the integrability of the quadratic system and a kind of cubic system, and then the nilpotent critical points are completely classified under each integrable condition.

    Integration of Appell function and Humbert function
    WANG Xiaoxia, YUAN Xueying
    2021, 27(5):  907-918.  doi:10.12066/j.issn.1007-2861.2199
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    Appell function and Humbert function are important in the research for double hypergeometric functions. Inspired by the recent work of Brychkov and Saad, who gave some integral representations for the Appell functions, the double hypergeometric function and generalized hypergeometric function are integrated, and some integral representations are established related to double hypergeometric function including some results for Appell function and Humbert function.

    Experiment of ageing effect on tensile strength of compacted Gaomiaozi bentonites
    CHE Yue, SUN Dean
    2021, 27(5):  919-927.  doi:10.12066/j.issn.1007-2861.2198
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    In this study, the effect of ageing on the tensile strength of compacted Gaomiaozi bentonite was investigated under different dry densities and water contents. The dry densities and water contents were maintained constant during curing periods of 0, 7, 15, 30 and 90 days, respectively. The tensile strength was measured using Brazilian tests and the specimens were analyzed through mercury intrusion porosimetry tests. The test results indicate that the tensile strength of Gaomiaozi bentonite decreases significantly in the early stage and tends to stabilize gradually in the later stage with ageing time. At the same water content, the effect of ageing on the tensile strength of the bentonite becomes less significant with the increase in dry density. The effect of ageing on the tensile strength is due to the gradual movement of the water molecules in the soil to the smectite interlayer during the curing periods and the subsequent gradual development of the smectite inter-lamellar water absorption. This process weakens the connection, decreasing the tensile strength. Smectite hydration results in the decrease in the number of macropores and the gradual increase in the number of small pores among the aggregates. Thus, the findings of this study provide a reference for the range of tensile strength of a bentonite block in a nuclear waste repository during storage and placement.

    Preparation of high temperature resistant epoxy composites reinforced by carbon fiber
    LIANG Lei, YU Mingming, WANG Peng
    2021, 27(5):  928-939.  doi:10.12066/j.issn.1007-2861.2194
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    An epoxy resin prepreg system composed of glycidyl amine epoxy resins modified by dimer acid and other polyfunctional epoxy resins with different viscosities was developed. The hot-melt film method was used to obtain epoxy resin prepregs reinforced by carbon fiber and high-temperature-resistant epoxy composites reinforced by carbon fiber. The application period of the resin could last longer than 60 days. The thermal stability temperature of the solidified product was higher than 300 ℃, and its long-term use temperature was higher than 160 ℃. The composite material exhibited good heat resistance. The heat resistance temperature could reach above 160 ℃, which could meet the heat resistance requirements of high-performance epoxy composites reinforced by carbon fiber.

    Classic machine learning for image recognition in wall column construction drawings
    TAO Li, ZHU Jiejiang, CAI Honghao
    2021, 27(5):  940-949.  doi:10.12066/j.issn.1007-2861.2196
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    Drawing review is important in the engineering design field, and efficient and accurate drawing review is a direction for future development. In recent years, the field of artificial intelligence has developed rapidly. This paper proposes an image recognition method based on classic machine learning that aims to use a computer to identify drawings efficiently and improve the efficiency of drawing review. First, the $K$-means algorithm is used to cluster wall column construction drawings, and based on the clustering, the local boundaries are searched, and the characters are divided. Subsequently, the $k$-nearest neighbour (kNN) model is used to identify the characters, and the reinforcement information of the wall column construction drawings is obtained. In addition, this paper proposes the Shadow-Sum method, an algorithm that can efficiently calculate the wall column area in shear wall construction drawings. Experiments are performed by randomly taking two wall column construction drawings. The results reveal that the accuracy of character recognition for the two wall column construction drawings is 99.6% and 99.4%. The recognition error rates for the areas are 0.66% and 0.34%. Column construction drawing identification is beneficial because the main information in wall column construction drawings can be output as editable text, which has certain engineering application value.

    Preparation and tribological properties of silane/graphene oxide composite coating on glass substrate
    LIU Chang, YANG Hongmei, CHEN Jinyang, ZENG Xiangqiong
    2021, 27(5):  950-958.  doi:10.12066/j.issn.1007-2861.2188
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    An anti-friction graphene oxide (GO) coating was prepared on a glass substrate using silane coupling agent 3-(dimethoxymethylsilyl)propylamine and GO with different oxidation degrees using the immersion method. The surface morphology and characteristics of the coating were investigated through Raman spectroscopy, Fourier infrared spectroscopy, and water contact angle tests. The results show that the silane/GO coating can be successfully fabricated, and the surface is uniform with no visible defects. For the tribological test, the coating can significantly improve the anti-friction properties of the substrate. The tribological properties of GO are related to its oxidation degree. The higher the oxidation degree of GO, the better the anti-friction properties.

    Dynamic pricing model based on correlation effect of product promotion for an online retailer
    GAO Junjun, GUO Peng
    2021, 27(5):  959-971.  doi:10.12066/j.issn.1007-2861.2190
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    In addition to the rapid development of e-commerce business, helping enterprises obtain optimal profits through dynamic pricing decisions has become a critical research direction of operations management for online retailers. With the increase in the frequency and variety of promotional activities, there are increasingly strong promotional correlation effects amid products. Therefore, different promotional strategies impact sales at the inter- and intra-category level. This study first applies the Granger-LASSO (least absolute shrinkage and selection operator) test to identify promotional correlation effects. The ADL (advanced distributed learning)-LASSO multi-stage regression is then used to establish a demand forecast model. Finally, the demand model is integrated into the profit function to establish a dynamic pricing model that considers promotional correlation effects. The experimental simulation results indicate that the proposed model can improve the total online profit of Brand U by 13.46%, which is proven to be an effective solution to dynamic pricing decisions for online retailers.

    Shadow banking business, corporate governance and analysts' earnings forecasts
    YAN Endian, GAO Sijia
    2021, 27(5):  972-982.  doi:10.12066/j.issn.1007-2861.2306
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    Shadow banking activities have received extensive attention from academia and supervisory bodies. To study this issue, this paper used data samples on China's listed non-financial enterprises from 2010 to 2017, obtained from the Standard & Poor's Compustat Global database, to examine the relationship between the shadow banking business of non-financial enterprises and the accuracy of analysts' predictions. This study found that the greater the participation of non-financial enterprises in shadow banking, the higher the error rate of analysts' predictions—that is, the lower their prediction accuracy. Further analysis showed that the above relationship was more significant in enterprises whose internal control quality, shareholding ratio of institutional investors, and credit ratings were low; moreover, it was observed that the shadow banking business of non-financial enterprises can increase the accrued earnings management of the enterprises and reduce the quality of information disclosure. The results remained robust after the measures of explanatory variables and explained variables were replaced. This study not only contributes to the literature on the economic consequences of the shadow banking business of non-financial enterprises and the accuracy of analysts' predictions, but also offers important guidance to analysts on being alert to the risks of shadow banking and market regulation.

    Distant supervision for relation extraction via attention CNNs
    XING Yixue, ZHU Yonghua, GAO Haiyan, ZHOU Jin, ZHANG Ke
    2021, 27(5):  983-992.  doi:10.12066/j.issn.1007-2861.2197
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    The process of relation extraction is a significant step in several information extraction systems designed to mine structured facts from text. However, two problems surface when traditional distant supervision methods are employed to conduct the entity relation extraction task. First, the distant supervision heuristic aligns the text in the corpus using existing knowledge marked with entities and relations, after which the alignment results are treated as annotation data; this leads to inevitable labeling errors. Second, current statistical methods rely extensively on natural language processing tools to extract features, and the noise accumulating during the entire process significantly affects the extraction results. In this study, an end-to-end, attention mechanism-based convolutional neural network (CNN) is proposed. First, the attention mechanism is added to the input layer for automatic detection of more subtle clues and learning of parts of sentences that are relevant to relation extraction. Second, the sentence is encoded based on the position feature and word feature, a piecewise CNN (PCNN) is used to extract sentence features and classify relationships, and finally a max-margin loss function with a higher efficiency is used on the network. The accuracy of this method when used on the New York Times dataset is 2.0% higher than that of the classical PCNN+MIL model, and 1.0% higher than that of the classical APCNN+D model. The experimental results therefore demonstrate excellent accuracy of the proposed model when compared with that of other baselinemodels.