Precipitated iron: a limit on gettering efficacy in multicrystalline silicon

A phosphorus diffusion gettering model is used to examine the efficacy of a standard gettering process on interstitial and precipitated iron in multicrystalline silicon. The model predicts a large concentration of precipitated iron remaining after standard gettering for most as-grown iron distributions. Although changes in the precipitated iron distribution are predicted to be small, the simulated post-processing interstitial iron concentration is predicted to depend strongly on the as-grown distribution of precipitates, indicating that precipitates must be considered as internal sources of contamination during processing. To inform and validate the model, the iron distributions before and after a standard phosphorus diffusion step are studied in samples from the bottom, middle, and top of an intentionally Fe-contaminated laboratory ingot. A census of iron-silicide precipitates taken by synchrotron-based X-ray fluorescence microscopy confirms the presence of a high density of iron-silicide precipitates both before and after phosphorus diffusion. A comparable precipitated iron distribution was measured in a sister wafer after hydrogenation during a firing step. The similar distributions of precipitated iron seen after each step in the solar cell process confirm that the effect of standard gettering on precipitated iron is strongly limited as predicted by simulation. Good agreement between the experimental and simulated data supports the hypothesis that gettering kinetics is governed by not only the total iron concentration but also by the distribution of precipitated iron. Finally, future directions based on the modeling are suggested for the improvement of effective minority carrier lifetime in multicrystalline silicon solar cells.

Iron distribution through the developmental stages of Medicago truncatula nodules.

Paramount to symbiotic nitrogen fixation (SNF) is the synthesis of a number of metalloenzymes that use iron as a critical component of their catalytical core. Since this process is carried out by endosymbiotic rhizobia living in legume root nodules, the mechanisms involved in iron delivery to the rhizobia-containing cells are critical for SNF. In order to gain insight into iron transport to the nodule, we have used synchrotron-based X-ray fluorescence to determine the spatio-temporal distribution of this metal in nodules of the legume Medicago truncatula with hitherto unattained sensitivity and resolution. The data support a model in which iron is released from the vasculature into the apoplast of the infection/differentiation zone of the nodule (zone II). The infected cell subsequently takes up this apoplastic iron and delivers it to the symbiosome and the secretory system to synthesize ferroproteins. Upon senescence, iron is relocated to the vasculature to be reused by the shoot. These observations highlight the important role of yet to be discovered metal transporters in iron compartmentalization in the nodule and in the recovery of an essential and scarce nutrient for flowering and seed production.

MtNramp1 mediates iron import in rhizobia-infected Medicago truncatula cells.

Symbiotic nitrogen fixation is a process that requires relatively high quantities of iron provided by the host legume. Using synchrotron-based X-ray fluorescence, we have determined that this iron is released from the vasculature into the apoplast of zone II of M. truncatula nodules. This overlaps with the distribution of MtNramp1, a plasma membrane iron importer. The importance of MtNramp1 in iron transport for nitrogen fixation is indicated by the 60% reduction of nitrogenase activity observed in knock-down lines, most likely due to deficient incorporation of this essential metal cofactor at the necessary levels.

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

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.