The formation of cavities in silicon carbide is vitally useful to“smart-cut”and metal gettering in semiconductor industry.In this study,cavities and extended defects formed in helium(He)ions implanted 6H-SiC at room...The formation of cavities in silicon carbide is vitally useful to“smart-cut”and metal gettering in semiconductor industry.In this study,cavities and extended defects formed in helium(He)ions implanted 6H-SiC at room temperature(RT)and 750℃ followed by annealing at 1500℃are investigated by a combination of transmission electron microscopy and high-resolution electron microscopy.The observed cavities and extended defects are related to the implantation temperature.Heterogeneously distributed cavities and extended defects are observed in the helium-implanted 6H-SiC at RT,while homogeneously distributed cavities and extended defects are formed after He-implanted 6H-SiC at 750℃.The possible reasons are discussed.展开更多
Despite the long history of research that has focused on the role of defects on device performance, the studies have not always been fruitful. A major reason is because these defect studies have typically been conduct...Despite the long history of research that has focused on the role of defects on device performance, the studies have not always been fruitful. A major reason is because these defect studies have typically been conducted in a parallel mode wherein the semiconductor wafer was divided into multiple pieces for separate optical and structural characterization, as well as device fabrication and evaluation. The major limitation of this approach was that either the defect being investigated by structural characterization techniques was not the same defect that was affecting the device performance or else the defect was not characterized under normal device operating conditions. In this review, we describe a more comprehensive approach to defect study, namely a series mode, using an array of spatially-resolved optical, electrical, and structural characterization techniques, all at the individual defect level but applied sequentially on a fabricated device. This novel sequential approach enables definitive answers to key questions, such as:(ⅰ) how do individual defects affect device performance?(ⅱ) how does the impact depend on the device operation conditions?(ⅲ) how does the impact vary from one defect to another? Implementation of this different approach is illustrated by the study of individual threading dislocation defects in GaAs solar cells. Additionally,we briefly describe a 3-D Raman thermometry method that can also be used for investigating the roles of defects in high power devices and device failure mechanisms.展开更多
Catastrophic degradation of high power laser diodes is due to the generation of extended defects inside the active parts of the laser structure during the laser operation.The mechanism driving the degradation is stron...Catastrophic degradation of high power laser diodes is due to the generation of extended defects inside the active parts of the laser structure during the laser operation.The mechanism driving the degradation is strongly related to the existence of localized thermal stresses generated during the laser operation.These thermal stresses can overcome the yield strength of the materials forming the active part of the laser diode.Different factors contribute to reduce the laser power threshold for degradation.Among them the thermal transport across the laser structure constitutes a critical issue for the reliability of the device.展开更多
Extended defects such as dislocation networks and general grain boundaries are ubiquitous in metals,and accurate modeling these extensive defects is crucial to elucidate their deformation mechanisms.However,existing m...Extended defects such as dislocation networks and general grain boundaries are ubiquitous in metals,and accurate modeling these extensive defects is crucial to elucidate their deformation mechanisms.However,existing machine learning interatomic potentials(MLIPs)often fall short in adequately describing these defects,as their large characteristic scales exceed the computational limits of firstprinciples calculations.To address this challenge,wepresent acomputational frameworkcombining a defect genome constructed via empirical interatomic potential-guided sampling,with an automated reconstruction technique that enables accurate first-principles modeling of general defects by converting atomic clusters into periodic configurations.The effectiveness of this approach was validated through simulations of nanoindentation,tensile deformation,and fracture in BCC tungsten.This framework enhances the modeling accuracy of extended defects in crystalline materials and provides a robust foundation for advancing MLIP development by leveraging defect genomes strategically.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.U1832133)the Doctor Research Foundation of Southwest University of Science and Technology,China(Grant No.18zx7141).
文摘The formation of cavities in silicon carbide is vitally useful to“smart-cut”and metal gettering in semiconductor industry.In this study,cavities and extended defects formed in helium(He)ions implanted 6H-SiC at room temperature(RT)and 750℃ followed by annealing at 1500℃are investigated by a combination of transmission electron microscopy and high-resolution electron microscopy.The observed cavities and extended defects are related to the implantation temperature.Heterogeneously distributed cavities and extended defects are observed in the helium-implanted 6H-SiC at RT,while homogeneously distributed cavities and extended defects are formed after He-implanted 6H-SiC at 750℃.The possible reasons are discussed.
基金supported by ARO/Electronics (Grant No. W911NF-16-1-0263)the support of Bissell Distinguished Professorship at UNC-Charlotte。
文摘Despite the long history of research that has focused on the role of defects on device performance, the studies have not always been fruitful. A major reason is because these defect studies have typically been conducted in a parallel mode wherein the semiconductor wafer was divided into multiple pieces for separate optical and structural characterization, as well as device fabrication and evaluation. The major limitation of this approach was that either the defect being investigated by structural characterization techniques was not the same defect that was affecting the device performance or else the defect was not characterized under normal device operating conditions. In this review, we describe a more comprehensive approach to defect study, namely a series mode, using an array of spatially-resolved optical, electrical, and structural characterization techniques, all at the individual defect level but applied sequentially on a fabricated device. This novel sequential approach enables definitive answers to key questions, such as:(ⅰ) how do individual defects affect device performance?(ⅱ) how does the impact depend on the device operation conditions?(ⅲ) how does the impact vary from one defect to another? Implementation of this different approach is illustrated by the study of individual threading dislocation defects in GaAs solar cells. Additionally,we briefly describe a 3-D Raman thermometry method that can also be used for investigating the roles of defects in high power devices and device failure mechanisms.
基金funded by the Spanish Government(MAT-2010-20441-C02)
文摘Catastrophic degradation of high power laser diodes is due to the generation of extended defects inside the active parts of the laser structure during the laser operation.The mechanism driving the degradation is strongly related to the existence of localized thermal stresses generated during the laser operation.These thermal stresses can overcome the yield strength of the materials forming the active part of the laser diode.Different factors contribute to reduce the laser power threshold for degradation.Among them the thermal transport across the laser structure constitutes a critical issue for the reliability of the device.
基金sponsored by Nederlandse Organisatie voor WetenschappelijkOnderzoek(The Netherlands Organization for Scientific Research,NWO)domain Science for the use of supercomputer facilities.
文摘Extended defects such as dislocation networks and general grain boundaries are ubiquitous in metals,and accurate modeling these extensive defects is crucial to elucidate their deformation mechanisms.However,existing machine learning interatomic potentials(MLIPs)often fall short in adequately describing these defects,as their large characteristic scales exceed the computational limits of firstprinciples calculations.To address this challenge,wepresent acomputational frameworkcombining a defect genome constructed via empirical interatomic potential-guided sampling,with an automated reconstruction technique that enables accurate first-principles modeling of general defects by converting atomic clusters into periodic configurations.The effectiveness of this approach was validated through simulations of nanoindentation,tensile deformation,and fracture in BCC tungsten.This framework enhances the modeling accuracy of extended defects in crystalline materials and provides a robust foundation for advancing MLIP development by leveraging defect genomes strategically.
