Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/155224
Title: Simulasi Model Biosensor Berbasis Satu Enzim dengan Pengaruh Bilangan Damköhler
Other Titles: Simulation of The Biosensor Model Based on One Enzyme with the Effect of Damköhler Number
Authors: Kartono, Agus
Rustami, Erus
Amin, M. Syahrul
Issue Date: 2024
Publisher: IPB University
Abstract: Model matematika biosensor berbasis satu enzim dengan faktor bilangan Damköhler menggambarkan rasio antara laju difusi dan reaksi biosensor. Model ini melibatkan dua persamaan difusi dan reaksi waktu dengan mekanisme laju reaksi Michaelis-Menten. Persamaan diferensial parsial diubah menjadi bentuk tak berdimensi dengan parameter baru, dan diselesaikan menggunakan metode numerik beda hingga secara eksplisit, diprogram dengan Octave/Matlab. Hasil perhitungan numerik menunjukkan kekekalan massa antara substrat dan produk, membuktikan validitas solusi numerik model ini. Solusi numerik menggambarkan konsentrasi substrat dan produk dalam lapisan enzimatik serta respons arus biosensor. Perubahan parameter dapat mempengaruhi laju difusi dan reaksi. Model ini diharapkan dapat dikembangkan lebih lanjut untuk jenis enzim dan analit tertentu, serta nilai parameter divalidasi dengan data eksperimen untuk mengoptimalkan model biosensor.
The mathematical model of a single-enzyme-based biosensor with the Damköhler number factor describes the ratio between diffusion rate and reaction rate in the biosensor. This model involves two time-dependent diffusion and reaction equations with the Michaelis-Menten reaction rate mechanism. The partial differential equations are transformed into a dimensionless form with new parameters and solved using the explicit finite difference numerical method, programmed in Octave/Matlab. The numerical results show mass conservation between substrate and product, validating the numerical solution of this model. The numerical solution depicts the concentration of substrate and product within the enzymatic layer and the current response generated by the biosensor. Changes in parameters can affect the diffusion and reaction rates. This model is expected to be further developed for specific types of enzymes and analytes, with parameter values validated against experimental data to optimize the biosensor model.
URI: http://repository.ipb.ac.id/handle/123456789/155224
Appears in Collections:UT - Physics

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