Research on the correlation between the dual diffusion behavior of zinc in InGaAs/InP single-photon avalanche photodiodes and device performance

The development of InGaAs/InP single-photon avalanche photodiodes(SPADs)necessitates the utiliza-tion of a two-element diffusion technique to achieve accurate manipulation of the multiplication width and the dis-tribution of its electric field.Regarding the issue of accurately predicting the depth of diffusion in InGaAs/InP SPAD,simulation analysis and device development were carried out,focusing on the dual diffusion behavior of zinc atoms.A formula of X_(j)=k√t-t_(0)+c to quantitatively predict the diffusion depth is obtained by fitting the simulated twice-diffusion depths based on a two-dimensional(2D)model.The 2D impurity morphologies and the one-dimensional impurity profiles for the dual-diffused region are characterized by using scanning electron micros-copy and secondary ion mass spectrometry as a function of the diffusion depth,respectively.InGaAs/InP SPAD devices with different dual-diffusion conditions are also fabricated,which show breakdown behaviors well consis-tent with the simulated results under the same junction geometries.The dark count rate(DCR)of the device de-creased as the multiplication width increased,as indicated by the results.DCRs of 2×10^(6),1×10^(5),4×10^(4),and 2×10^(4) were achieved at temperatures of 300 K,273 K,263 K,and 253 K,respectively,with a bias voltage of 3 V,when the multiplication width was 1.5µm.These results demonstrate an effective prediction route for accu-rately controlling the dual-diffused zinc junction geometry in InP-based planar device processing.

社会资本与关系资本论析

关系是人类社会的普遍存在,关系网络是社会资本的重要载体,这是基本的共识。但是,不同社会制度文化背景下,中西方学者对于社会资本的关注点是不同的,西方学者所探讨的社会资本更多地关注社会关系网络的正功能,如果简单地借用西方学者所提出的社会资本理论来分析中国社会的关系网络,恐会带来不良的社会后果。中国社会的关系网络更多地体现为特殊主义取向、个人私益性、负外部效应的特殊资本形态,简单地说就是所谓的"关系资本",即一种不利于信任、规范、团结等普遍主义现代性因素生长的"关系网络"。

Direct carbothermic reduction of ilmenite concentrates by adding high dosage of Na_(2)CO_(3) in microwave field

A clean and efficient route for the utilization of ilmenite concentrates was proposed by direct carbothermic reduction in microwave field.High dosage of Na_(2)CO_(3),which can be recycled,was added to accelerate the reduction reaction of ilmenite concentrates.After microwave heating in the temperature range of 1073−1123 K for 20 min,the main products were Na_(2)TiO_(3) and metallic Fe with the metallization ratios being as high as 92.67%−93.21%.The reduction products were processed by water leaching,ball-milling in CO2 atmosphere and magnetic separation in turn.The final products after magnetic separation were Fe-rich materials and Ti-rich materials(90.04 wt.%TiO2),which can be used to produce iron and TiCl4 or TiO2.The optimized heating temperature was 1123 K in terms of metallization ratios,magnetic separation and caking property of the reduction products.Besides,the reduction mechanism of ilmenite concentrates with the addition of Na_(2)CO_(3) in microwave field was also proposed.

Reductive kinetics of Panzhihua ilmenite with hydrogen

The hydrogen reduction of Panzhihua ilmenite concentrate in the temperature range of 900?1050 °C was systematicallyinvestigated by thermogravimetric analysis (TG), X-ray diffraction (XRD) and scanning electron microscopy (SEM) methods. It wasshown that the products of the Panzhihua ilmenite reduced at 900 °C were metallic iron and rutile. Above 1000 °C, ferrouspseudobrookite solid solution was generated. During the reduction process, element Mg gradually concentrated to form Mg-rich zonewhich can influence the metallization process. The reduction reaction proceeded topochemically and its related reduction kineticswere also discussed. The kinetics of the reduction indicated that the rate-controlling step was the diffusion process. The apparentactivation energy of the hydrogen reduction of Panzhihua ilmenite was calculated to be 117.56 kJ/mol, which was larger than that ofsynthetic ilmenite under the same reduction condition.

Research on red tide occurrence forecast method based on deep learning

As a marine disaster,red tides have a serious impact on marine fisheries,ecology,economy,human production and life.Red tides have been widely concerned by researchers for a long time.However,due to its complex formation mechanism,red tide forecasting is extremely challenging.Aiming at addressing problem of red tide forecasting,this paper collects the marine monitoring data before and after the occurrence of red tide in Xiamen sea area,and analyzes the correlation between multiple environmental factors and the red tide occurrence by combining the methods of Pearson correlation coefficient,Scatter matrix,and multiple correlation coefficient.The fusion method of LSTM and CNN based on deep learning are applied to mine the temporal dependence of environmental factors and find the local features of sequence data,then predict the occurrence of red tides.In the Xiamen No.1 and Xiamen No.2 datasets,the RMSE and MAE errors of this method are reaching 0.5218 and 0.5043,respectively.The forecast probability of red tide occurrence was further determined through the collaborative comparison model.The final forecast accuracy of the two datasets is 67.58%and 63.49%,respectively.This study provides exploratory experience for the analysis and forecasting of red tides,which proves the feasibility of applying deep learning methods to red tide forecasting.