Effect of matrix composition, sphere size and hormone concentration on diffusion coefficient of insulin for controlled gastrointestinal delivery for diabetes treatment

2017 ◽  
Vol 35 (1) ◽  
pp. 13-25 ◽  
Author(s):  
Fernando Villaverde Cendon ◽  
Regina Maria Matos Jorge ◽  
Regina Weinschutz ◽  
Alvaro Luiz Mathias
2004 ◽  
Vol 22 (7) ◽  
pp. 963-972 ◽  
Author(s):  
John Antoniou ◽  
Caroline N Demers ◽  
Gilles Beaudoin ◽  
Tapas Goswami ◽  
Fackson Mwale ◽  
...  

2011 ◽  
Vol 309-310 ◽  
pp. 63-72 ◽  
Author(s):  
Alain Portavoce ◽  
Ivan Blum ◽  
Lee Chow ◽  
Jean Bernardini ◽  
Dominique Mangelinck

The measurement of diffusion coefficients in today’s materials is complicated by the down scaling of the studied structures (nanometric effects in thin films, nano-crystalline layers, etc.) and by the complex production process conditions of industrial samples or structures (temperature variations, complex solute and point defect distributions, stress gradients, etc.). Often diffusion measurements have to be performed in samples for which initial experimental conditions do not offer the possibility of using conventional diffusion analytical solutions. Furthermore, phenomena involved with diffusion are sometimes so numerous and complex (stress, matrix composition inhomogeneities, time dependence of point defect generation sources, electrical effects, clustering effects, etc…) that the use of analytical solutions to solve the observed diffusion behavior is difficult. However, simulations can be of use in these cases. They are time consuming compared to the use of analytical solutions, but are more flexible regarding initial conditions and problem complexity. The use of simulations in order to model physical phenomena is quite common nowadays, and highly complex models have been developed. However, two types of simulations have to be considered: i) simulations aiming to understand and predict phenomena, and ii) simulations for measurement purposes, aiming to extract the (average) value of a physical parameter from experimental data. These two cases have different constrains. In the second case, that is the subject of this article, one of the most important stress is that the simulation has to precisely scale the experiment (sample size, experiment duration, etc.), sometimes preventing the measurement due to computational time consumption. Furthermore, the simpler the model (small number of parameters) used in the simulation, the more relevant the measurement (minimum error). In this paper, examples of recent works using two- and three-dimensional finite element simulations for diffusion coefficient measurements in thin polycrystalline films and nano-crystalline layers are presented. The possible use of simulations for diffusion coefficient measurements considering GB migration, GB segregation, or triple junctions is also discussed.


1954 ◽  
Vol 46 (11) ◽  
pp. 47-49 ◽  
Author(s):  
C.Y. Lee ◽  
C.R. Wilke

2020 ◽  
Author(s):  
Ana Beloqui ◽  
Francesco Suriano ◽  
Matthias Hul ◽  
Yining Xu ◽  
Véronique Préat ◽  
...  

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