11.2
SIMS Quantitative Analysis and Optimization for Ion Implantation Angle Deviation
SIMS Quantitative Analysis and Optimization for Ion Implantation Angle Deviation
Wednesday, November 4, 2015: 8:25 AM
Meeting Room D139 & 140 (Oregon Convention Center )
Summary:
The accuracy of ion implantation is very important in semiconductor manufacturing and will directly affect the performance of the individual devices and even the whole chip. The deviation of IMP energy, dose and angle are often encountered because of the abnormality of implant equipment or process design limit. The ion implantation energy, dose and angle information can be qualitatively and quantitatively analyzed through SIMS [2], which provides a way to diagnose the issue of ion implanter. Based on SIMS analysis results, we can judge whether ion implant results meet the requirements and whether the process design achieves the expected goal. In this paper we report a SIMS data processing method for the analysis of the deviation of ion implantation angle. A term of deviation rate was defined and the related calculation method was introduced, which is proportional to the deviation angles of the ion implanter. And then, a statistical analysis of a large number of data on deviation rates and ion implantation angles showed that the whole sampling data followed normal distribution, and thus the corresponding 3 sigma could be obtained. Using the determined 3 sigma range of the deviation rates, we can define the acceptable range for deviation rate. Further, we can use the actual deviation rate to judge if the implant equipment needs maintenance or not, or suggest the direction for improvement. If the deviation rate out of the corresponding specification, The SIMS full mapping depth profiles analysis by CAMECA Wf is needed. Then the corresponding full mapping deviation rate are obtained, then got the minimum deviation rate Kmin position(X,Y). Base on experiment verification Kmin position(X,Y) is linear correlation with the implanter angle tuning parameter( alpha, beta). Therefore, after set up linear function between (alpha,beta) and (X,Y) the (¡÷alpha, ¡÷beta ) can be obtained directly. The equipment¡¯s maintenance time and cost can thus be minimized. This method can be used as an early detection to find an abnormity in an ion implant tool.
The accuracy of ion implantation is very important in semiconductor manufacturing and will directly affect the performance of the individual devices and even the whole chip. The deviation of IMP energy, dose and angle are often encountered because of the abnormality of implant equipment or process design limit. The ion implantation energy, dose and angle information can be qualitatively and quantitatively analyzed through SIMS [2], which provides a way to diagnose the issue of ion implanter. Based on SIMS analysis results, we can judge whether ion implant results meet the requirements and whether the process design achieves the expected goal. In this paper we report a SIMS data processing method for the analysis of the deviation of ion implantation angle. A term of deviation rate was defined and the related calculation method was introduced, which is proportional to the deviation angles of the ion implanter. And then, a statistical analysis of a large number of data on deviation rates and ion implantation angles showed that the whole sampling data followed normal distribution, and thus the corresponding 3 sigma could be obtained. Using the determined 3 sigma range of the deviation rates, we can define the acceptable range for deviation rate. Further, we can use the actual deviation rate to judge if the implant equipment needs maintenance or not, or suggest the direction for improvement. If the deviation rate out of the corresponding specification, The SIMS full mapping depth profiles analysis by CAMECA Wf is needed. Then the corresponding full mapping deviation rate are obtained, then got the minimum deviation rate Kmin position(X,Y). Base on experiment verification Kmin position(X,Y) is linear correlation with the implanter angle tuning parameter( alpha, beta). Therefore, after set up linear function between (alpha,beta) and (X,Y) the (¡÷alpha, ¡÷beta ) can be obtained directly. The equipment¡¯s maintenance time and cost can thus be minimized. This method can be used as an early detection to find an abnormity in an ion implant tool.