The influence of thermal cycling on the microstructure and joint strength of Sn3.5Ag0.75Cu （SAC） and Sn63Pb37 （SnPb） solder joints was investigated. SAC and SnPb solder balls were soldered on 0.1 and 0.9 μm Au fi...The influence of thermal cycling on the microstructure and joint strength of Sn3.5Ag0.75Cu （SAC） and Sn63Pb37 （SnPb） solder joints was investigated. SAC and SnPb solder balls were soldered on 0.1 and 0.9 μm Au finished metallization, respectively. After 1000 thermal cycles between -40℃ and 125℃, a very thin intermetallic compound （IMC） layer containing Au, Sn, Ni, and Cu formed at the interface between SAC solder joints and underneath metallization with 0.1 μm Au finish, and （Au, Ni, Cu）Sn4 and a very thin AuSn-Ni-Cu IMC layer formed between SAC solder joints and underneath metallization with 0.9 μm Au finish. For SnPb solder joints with 0.1 μm Au finish, a thin （Ni, Cu, Au）3Sn4 IMC layer and a Pb-rich layer formed below and above the （Au, Ni）Sn4 IMC, respectively. Cu diffused through Ni layer and was involved into the IMC formation process. Similar interfacial microstructure was also found for SnPb solder joints with 0.9μm Au finish. The results of shear test show that the shear strength of SAC solder joints is consistently higher than that of SnPb eutectic solder joints during thermal cycling.展开更多
Pantoprazole sodium, a substituted benzimidazole derivative, is an irreversible proton pump inhibitor which is primarily used for the treatment of duodenal ulcers, gastric ulcers, and gastroesophageal reflux disease (...Pantoprazole sodium, a substituted benzimidazole derivative, is an irreversible proton pump inhibitor which is primarily used for the treatment of duodenal ulcers, gastric ulcers, and gastroesophageal reflux disease (GERD). The monographs of European Pharmacopoeia (Ph. Eur.) and United States Pharmacopoeia (USP) specify six impurities, viz.;impurities A, B, C, D, E and F, respectively for its active pharmaceutical ingredient (API). The identification and synthesis of all impurities except impurity E are well described in the literature;however, there is no report related to impurity E. The prospects to the formation and controlling of impurity E up to -0.03% in the synthesis of pantoprazole sodium sesquihydrate (PAN) were discussed in detail for the first time. The present work described the journey towards the successful development of an optimal preparation procedure of dimer impurity E. The most plausible mechanism involved in the formation of impurity E has been proposed.展开更多
This article concentrates on ground vision guided autonomous landing of a fixed-wing Unmanned Aerial Vehicle(UAV)within Global Navigation Satellite System(GNSS)denied environments.Cascaded deep learning models are dev...This article concentrates on ground vision guided autonomous landing of a fixed-wing Unmanned Aerial Vehicle(UAV)within Global Navigation Satellite System(GNSS)denied environments.Cascaded deep learning models are developed and employed into image detection and its accuracy promoting for UAV autolanding,respectively.Firstly,we design a target bounding box detection network Bbox Locate-Net to extract its image coordinate of the flying object.Secondly,the detected coordinate is fused into spatial localization with an extended Kalman filter estimator.Thirdly,a point regression network Point Refine-Net is developed for promoting detection accuracy once the flying vehicle’s motion continuity is checked unacceptable.The proposed approach definitely accomplishes the closed-loop mutual inspection of spatial positioning and image detection,and automatically improves the inaccurate coordinates within a certain range.Experimental results demonstrate and verify that our method outperforms the previous works in terms of accuracy,robustness and real-time criterions.Specifically,the newly developed Bbox Locate-Net attaches over 500 fps,almost five times the published state-of-the-art in this field,with comparable localization accuracy.展开更多
One unknown impurity （Imp-II） during the analysis of laboratory batches of isoproterenol hydrochloride was detected in the level ranging from 0.04% to 0.12% by high performance liquid chromatography with UV detectio...One unknown impurity （Imp-II） during the analysis of laboratory batches of isoproterenol hydrochloride was detected in the level ranging from 0.04% to 0.12% by high performance liquid chromatography with UV detection. The unknown impurity structure was proposed as 4-[2-（propan-2oylamino）ethyl]benzene-l,2-diol （Imp-II） using the liquid chromatography-mass spectrophotometry （LC-MS） analysis. Imp-II was isolated by semi-preparative liquid chromatography from the impurity-enriched reaction crude sample. Its proposed structure was confirmed by nuclear magnetic spectroscopy such as 1H, 13C, DEPT （1D NMR）, HSQC （2D NMR） and infrared spectroscopy （IR）, and retention time and purity with HPLC followed by the chemical synthesis. Due to less removable nature of Imp-II during the purification, the synthetic process was optimized proficiently to control the formation of Imp-II below to the limit 〈 0.12% in the course of reaction. The new chemical route was developed for the preparation of this impurity in required quantity with purity to use as reference standard. The most probable mechanism for the formation of Imp-II was discussed in details.展开更多
In this paper,a novel deep learning dataset,called Air2Land,is presented for advancing the state‐of‐the‐art object detection and pose estimation in the context of one fixed‐wing unmanned aerial vehicle autolanding...In this paper,a novel deep learning dataset,called Air2Land,is presented for advancing the state‐of‐the‐art object detection and pose estimation in the context of one fixed‐wing unmanned aerial vehicle autolanding scenarios.It bridges vision and control for ground‐based vision guidance systems having the multi‐modal data obtained by diverse sensors and pushes forward the development of computer vision and autopilot algorithms tar-geted at visually assisted landing of one fixed‐wing vehicle.The dataset is composed of sequential stereo images and synchronised sensor data,in terms of the flying vehicle pose and Pan‐Tilt Unit angles,simulated in various climate conditions and landing scenarios.Since real‐world automated landing data is very limited,the proposed dataset provides the necessary foundation for vision‐based tasks such as flying vehicle detection,key point localisation,pose estimation etc.Hereafter,in addition to providing plentiful and scene‐rich data,the developed dataset covers high‐risk scenarios that are hardly accessible in reality.The dataset is also open and available at https://github.com/micros‐uav/micros_air2land as well.展开更多
文摘The influence of thermal cycling on the microstructure and joint strength of Sn3.5Ag0.75Cu （SAC） and Sn63Pb37 （SnPb） solder joints was investigated. SAC and SnPb solder balls were soldered on 0.1 and 0.9 μm Au finished metallization, respectively. After 1000 thermal cycles between -40℃ and 125℃, a very thin intermetallic compound （IMC） layer containing Au, Sn, Ni, and Cu formed at the interface between SAC solder joints and underneath metallization with 0.1 μm Au finish, and （Au, Ni, Cu）Sn4 and a very thin AuSn-Ni-Cu IMC layer formed between SAC solder joints and underneath metallization with 0.9 μm Au finish. For SnPb solder joints with 0.1 μm Au finish, a thin （Ni, Cu, Au）3Sn4 IMC layer and a Pb-rich layer formed below and above the （Au, Ni）Sn4 IMC, respectively. Cu diffused through Ni layer and was involved into the IMC formation process. Similar interfacial microstructure was also found for SnPb solder joints with 0.9μm Au finish. The results of shear test show that the shear strength of SAC solder joints is consistently higher than that of SnPb eutectic solder joints during thermal cycling.
文摘Pantoprazole sodium, a substituted benzimidazole derivative, is an irreversible proton pump inhibitor which is primarily used for the treatment of duodenal ulcers, gastric ulcers, and gastroesophageal reflux disease (GERD). The monographs of European Pharmacopoeia (Ph. Eur.) and United States Pharmacopoeia (USP) specify six impurities, viz.;impurities A, B, C, D, E and F, respectively for its active pharmaceutical ingredient (API). The identification and synthesis of all impurities except impurity E are well described in the literature;however, there is no report related to impurity E. The prospects to the formation and controlling of impurity E up to -0.03% in the synthesis of pantoprazole sodium sesquihydrate (PAN) were discussed in detail for the first time. The present work described the journey towards the successful development of an optimal preparation procedure of dimer impurity E. The most plausible mechanism involved in the formation of impurity E has been proposed.
基金supported by the National Natural Science Foundation of China(No.61973327)。
文摘This article concentrates on ground vision guided autonomous landing of a fixed-wing Unmanned Aerial Vehicle(UAV)within Global Navigation Satellite System(GNSS)denied environments.Cascaded deep learning models are developed and employed into image detection and its accuracy promoting for UAV autolanding,respectively.Firstly,we design a target bounding box detection network Bbox Locate-Net to extract its image coordinate of the flying object.Secondly,the detected coordinate is fused into spatial localization with an extended Kalman filter estimator.Thirdly,a point regression network Point Refine-Net is developed for promoting detection accuracy once the flying vehicle’s motion continuity is checked unacceptable.The proposed approach definitely accomplishes the closed-loop mutual inspection of spatial positioning and image detection,and automatically improves the inaccurate coordinates within a certain range.Experimental results demonstrate and verify that our method outperforms the previous works in terms of accuracy,robustness and real-time criterions.Specifically,the newly developed Bbox Locate-Net attaches over 500 fps,almost five times the published state-of-the-art in this field,with comparable localization accuracy.
文摘One unknown impurity （Imp-II） during the analysis of laboratory batches of isoproterenol hydrochloride was detected in the level ranging from 0.04% to 0.12% by high performance liquid chromatography with UV detection. The unknown impurity structure was proposed as 4-[2-（propan-2oylamino）ethyl]benzene-l,2-diol （Imp-II） using the liquid chromatography-mass spectrophotometry （LC-MS） analysis. Imp-II was isolated by semi-preparative liquid chromatography from the impurity-enriched reaction crude sample. Its proposed structure was confirmed by nuclear magnetic spectroscopy such as 1H, 13C, DEPT （1D NMR）, HSQC （2D NMR） and infrared spectroscopy （IR）, and retention time and purity with HPLC followed by the chemical synthesis. Due to less removable nature of Imp-II during the purification, the synthetic process was optimized proficiently to control the formation of Imp-II below to the limit 〈 0.12% in the course of reaction. The new chemical route was developed for the preparation of this impurity in required quantity with purity to use as reference standard. The most probable mechanism for the formation of Imp-II was discussed in details.
文摘In this paper,a novel deep learning dataset,called Air2Land,is presented for advancing the state‐of‐the‐art object detection and pose estimation in the context of one fixed‐wing unmanned aerial vehicle autolanding scenarios.It bridges vision and control for ground‐based vision guidance systems having the multi‐modal data obtained by diverse sensors and pushes forward the development of computer vision and autopilot algorithms tar-geted at visually assisted landing of one fixed‐wing vehicle.The dataset is composed of sequential stereo images and synchronised sensor data,in terms of the flying vehicle pose and Pan‐Tilt Unit angles,simulated in various climate conditions and landing scenarios.Since real‐world automated landing data is very limited,the proposed dataset provides the necessary foundation for vision‐based tasks such as flying vehicle detection,key point localisation,pose estimation etc.Hereafter,in addition to providing plentiful and scene‐rich data,the developed dataset covers high‐risk scenarios that are hardly accessible in reality.The dataset is also open and available at https://github.com/micros‐uav/micros_air2land as well.
