Prediction of Bio-Polymer Characteristics by Applying Rentato Panelli Mathematical Model

Abstract

Abstract Recently, the intense interest for bio-polymer for biomedical applications has gone up. This interest was due to patients researchers, and the medical world seeking for effective solutions to their serious challenges, such as the need to repair or, replace, substitute organs or tissues. In current article, Rentato Panelli mathematical equation utilize to understand and track parameters refer to a physical significant, deformation nature and shape memory degree and of two types of bio-polymer derivative mixtures, Avicel 102 and Sodium Starch Glycolate (SSG). Panelli constants were stated by using combination of two, known, bio polymer in term of deformation and shape memory specifications to validate of the equation parameters to predict this characteristics for unknown materials which may be part of human body or cardiovascular artificial parts. Constants and coefficients for equation measured by applying low pressure ranging from 15 to 75 Mpa. The issues emerging from the findings relate specifically to depth in-die analysis. The most interesting findings was the Panelli equation parameters are perfectly valid in representing bio-polymer characteristics under stress. These parameters and characteristics are able to assess the features of the bio-polymer which sometimes become beyond the scope unless defined by using specific instrumentation. In addition, these parameters can decide the applied pressure that achieve particular density in the manufacturing conditions. These parameters determine process conditions that produce desired biomedical engineering application as bio ink for 3D printing, artificial organs, and drug delivery system which is difficult or rather impossible without use classical methods.