Release modelling of nanoencapsulated food ingredients by probabilistic
models: cellular automata and Monte Carlo methods
Bezbradica, MarijaORCID: 0000-0001-9366-5113, Crane, MartinORCID: 0000-0001-7598-3126 and Ruskin, Heather J.
(2020)
Release modelling of nanoencapsulated food ingredients by probabilistic
models: cellular automata and Monte Carlo methods.
In: Jafari, SeidORCID: 0000-0001-6877-9549, (ed.)
Nanoencapsulation in the Food Industry.
Academic Press, Cambridge, Massachusetts, pp. 273-309.
ISBN 9780128156667
Probabilistic modeling methods have found increasing importance in recent years, driven by concurrent growth in computing power with applications in the modeling of many fields of science, engineering, and medicine. This has been due not just to method scope and flexibility, but also in no small part to advance in computing capacity and interconnection speed and commensurate decreases in the costs of these. In this chapter, we review the literature on probabilistic methods with their different and varied forms, and describe the theory of the methods, together with practical applications in the fields of drug delivery systems in the pharmaceutical industry and nanoencapsulation within the food industry.
Item Type:
Book Section
Refereed:
Yes
Uncontrolled Keywords:
Probabilistic models; Monte Carlo simulation; Cellular automata models; Agent-based models