This paper describes a model to predict mechanical strength distribution of silicon wafers. A generalized expression, based on a multimodal Weibull distribution, is proposed to describe the strength of a brittle material with surface, edge, and bulk flaws. The specific case of a cast, unpolished photovoltaic (PV) wafer is further analyzed. Assuming that surface microcracks constitute the dominant mechanism of wafer breakage, this model predicts the strength distribution of PV silicon that matches well the experimental results available in the literature.
This work is a continuation of the research recently presented in [1] and [2] on the determination of residual thermal stresses in graphite/polyimide composites with and without externally applied bending loads. In the previous work [1, 2] a combined experimental and numerical methodology for the determination of the residual stresses in unidirectional graphite/PMR-15 composites based on X-ray diffraction (XRD) measurements of residual strains in embedded aluminum (Al) and silver (Ag) inclusions has been presented. In this research, the previously developed approach has been applied to evaluate the residual thermal interlaminar stresses in an 8 harness satin (8HS) woven graphite/PMR-15 composite. First, residual thermal stresses have been measured by XRD in aluminum inclusions embedded between the rst and second plies of a four-ply 8HS woven graphite/PMR-15 composite. The measurements have been conducted with the composite specimens subjected to four-point bending deformations. Second, viscoelastic computations of interlaminar residual stresses in the composite have been performed using classical laminated plate theory (CLPT) following the manufacturing procedure. Third, the residual strains and stresses in the inclusions have been numerically predicted using the viscoelastic Eshelby model for multiple spherical inclusions. Finally, the interlaminar residual stresses in the composite have been extracted from the XRD strains in the Al inclusions, again using the viscoelastic Eshelby model, and
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.