Building intuition of iron evolution during solar cell processing through analysis of different process models

Abstract

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,]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetic ally limited and bulk [Fe,] 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.

Synchrotron-based investigation of transition-metal getterability in n-type multicrystalline silicon

“…The physics underlying PDG are the nucleation and subsequent growth or dissolution of precipitates, the solid solubility, and the diffusivity of metal point defects. 24 This study provides evidence that the trends in these physical driving forces are similar in n-and p-type silicon at PDG process temperature for deep level defects. The nucleation and subsequent growth or dissolution of precipitates do not depend on the base doping type when nucleation occurs at high temperature, 25 but rather on the local temperature-dependent solid solubility, the local dissolved species concentration, the precipitate size, the surface energy, lattice strain, and the morphology of the precipitate.…”

Grain boundary effect on lifetime in high performance multicrystalline silicon during solar cell processing

“…Gettering has a thermal budget high enough to allow impurity diffusion towards the electrically inactive emitter, but also to dissolve precipitates decorating bulk defects. This leads to a competition between the extraction of harmful, interstitial impurity atoms from the bulk and impurity reprecipitation with a different precipitate distribution, possibly leading to new defect mechanisms [9,10]. Subsequent contact firing, usually with a hydrogen rich antireflection coating present, also requires high temperatures.…”

“…Subsequent contact firing, usually with a hydrogen rich antireflection coating present, also requires high temperatures. Even though the firing time is much shorter than the gettering process, it can also affect impurity distribution [9]. During the firing step hydrogen from passivation layers or antireflection coatings is able to diffuse into the bulk and passivate bulk defects, reducing their impact on minority carrier lifetimes [11].…”

Impact of Extended Contact Cofiring on Multicrystalline Silicon Solar Cell Parameters

“…This increase can be attributed to the dissolution of iron precipitates [5]- [7], and also to the re-injection of iron from the emitter into the bulk [8], [9]. However, adequate defect engineering tools can compensate completely or partly this increase thanks to an external gettering into the phosphorus and aluminum layers during the temperature plateau.…”