2 resultados para thermodynamic analysis

em Universidad Politécnica de Madrid


Relevância:

40.00% 40.00%

Publicador:

Resumo:

In this work the spectrally resolved, multigroup and mean radiative opacities of carbon plasmas are calculated for a wide range of plasma conditions which cover situations where corona, local thermodynamic and non-local thermodynamic equilibrium regimes are found. An analysis of the influence of the thermodynamic regime on these magnitudes is also carried out by means of comparisons of the results obtained from collisional-radiative, corona or Saha–Boltzmann equations. All the calculations presented in this work were performed using ABAKO/RAPCAL code.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

An important aspect of Process Simulators for photovoltaics is prediction of defect evolution during device fabrication. Over the last twenty years, these tools have accelerated process optimization, and several Process Simulators for iron, a ubiquitous and deleterious impurity in silicon, have been developed. The diversity of these tools can make it difficult to build intuition about the physics governing iron behavior during processing. Thus, in one unified software environment and using self-consistent terminology, we combine and describe three of these Simulators. We vary structural defect distribution and iron precipitation equations to create eight distinct Models, which we then use to simulate different stages of processing. We find that the structural defect distribution influences the final interstitial iron concentration ([Fe-i]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetically limited and bulk [Fe-i] predictions can vary by an order of magnitude or more, and (2) solubility-limited, in which iron evolution is near thermodynamic equilibrium and the Models yield similar results. This rigorous analysis provides new intuition that can inform Process Simulation, material, and process development, and it enables scientists and engineers to choose an appropriate level of Model complexity based on wafer type and quality, processing conditions, and available computation time.