Open AccessMathematical Modeling for Determination of Correlation Between Current Density and Dissolved Oxygen in Yeast Microbial Fuel Cell-Based Biosensor
Author(s) -
Marcelinus Christwardana,
Linda Aliffia Yoshi
Publication year - 2020
Publication title -
reaktor
Language(s) - English
Resource type - Journals
eISSN - 2407-5973
pISSN - 0852-0798
DOI - 10.14710/reaktor.20.3.117-121
Subject(s) - mean squared error , correlation coefficient , current (fluid) , exponential function , coefficient of determination , linear regression , biological system , statistics , goodness of fit , current density , mathematics , thermodynamics , physics , mathematical analysis , biology , quantum mechanics
Experiments were conducted to study the correlation between current density and dissolved oxygen (DO) and to develop a model for estimating the value of current density in yeast MFC based DO biosensors. A curve between current density and DO was made, and data analysis was performed using free-online data fitting, namely zunzun.com. One linear regression and nine different exponential models are used as an approach to determine the correlation between current density and DO. The higher DO, the current density will increase rapidly. The most suitable model was chosen to describe the correlation between the current density and the DO. The coefficient of determination (R2), the sum of square absolute (SSQABS), and root mean square error (RMSE) are used to determine goodness or quality of fit. The exponential model shows a better fit to illustrate the correlation between current density and DO, with R2, SSQABS, and RMSE values were 0.9975, 0.4745 and 0.3444, respectively.