Modeling and simulation of transient enhanced diffusion based on interactions of point and extended defects
Başlık çevirisi mevcut değil.
- Tez No: 400935
- Danışmanlar: PROF. SCOTT DUNHAM
- Tez Türü: Doktora
- Konular: Elektrik ve Elektronik Mühendisliği, Electrical and Electronics Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1999
- Dil: İngilizce
- Üniversite: Boston University
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 83
Özet
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Özet (Çeviri)
As device sizes in VLSI technology get smaller, the importance of predictive process modeling increases. One of the biggest challenges in predictive process modeling today lies in modeling of Transient Enhanced Diffusion (TED). TED is the greatly enhanced diffusion of dopants in silicon seen during annealing of the damage created by the ion implantation of the dopants. As one moves to smaller thermal budgets, TED is often the primary source of diffusion and thus determines the final junction depth. It is known that TED is caused by the excess interstitial concentration that persists due to ion implantation. But how this excess interstitial concentration evolves over time and affects the diffusion of dopants remains unclear. Our work attempts to understand the physical processes occurring during ion implant annealing, express them in a mathematical model, integrate this model into a diffusion equation solver and quantitatively match the experimental observations. To this end, we have developed a solid physical model (KPM) for the evolution of extended defects (f311gdefects and dislocation loops) which are observed under TED conditions. We have also developed different versions of KPM that have applicability under different circumstances, and have different levels of computational efficiency. We believe that the range of models developed will give the user the ability to make a compromise between accuracy and computational time. We have applied KPM to f311gdefects that are observed under non-amorphizing implant conditions and we were able to get a good agreement. We have then used this model to predict TED behavior based on marker layer experiments and we found a good match. To extend the model to dislocation loops, we assumed that dislocation loops form by unfaulting of f311gdefects as observed experimentally. We accounted for this transformation in our model and we were able to obtain a good match to the experimental data without any modifications in the f311gdefect model. Our work also involved in developing a computer software that is capable of solving the models that we have postulated. To this end, we have developed DOPDEES, a one-dimensionalmulti purpose partial differential equation initial value solver. To enable faster technology transfer, we have also developed Process Modeling Modules (PMM) which consists a set of scripts that encapsulate the models that we have developed in a ready to use form.
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