dc.creatorALVES, ANDRESSA A.
dc.creatorQUEIROZ, ??LVARO A.A. de
dc.creatorQUEIROZ, ALFREDO A.A.E. de
dc.creatorBRAZIL MRS MEETING, 19th; INTERNATIONAL UNION OF MATERIALS RESEARCH SOCIETIES - INTERNATIONAL CONFERENCE ON ELECTRONIC MATERIALS
dc.date2022-03-22T13:07:22Z
dc.date2022-03-22T13:07:22Z
dc.dateAugust 30 - September 3, 2021
dc.date.accessioned2023-09-28T14:21:30Z
dc.date.available2023-09-28T14:21:30Z
dc.identifierhttp://repositorio.ipen.br/handle/123456789/32833
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9003052
dc.descriptionIn recent years, the microfluidic approach has received a lot of attention from the scientific community due to the simple and efficient synthesis of highly monodisperse microcapsules used in a variety of applications in biotechnology and medicine such as, for example, materials synthesis, drug encapsulation, among others [1,2]. Thus, in this work, hyperbranched polyglycerol microcapsules (HPGM) were developed using microfluidic technology. Artificial neural network (ANN) feed-forward using multilayer perceptron architecture was trained and applied to model and predict the microfluidic process. The HPGM produced were characterized by scanning electron microscope (SEM), attenuated total reflection-Fourier transform infrared (ATR-FTIR) and thermogravimetric analysis (TGA). The fabricated HPGM showed spherical size and monomodal distribution with an average diameter of 29 ??m. The developed ANN proved to be efficient predictor, showing well agreement with the experimental data (R2=0.9983). Based on these results in this research, it was found that the microfluidic device for producing HPGM was successfully developed since it was possible to synthesize microcapsules with targeted properties, monodispersed with high stability and low porosity. In this way, microfluidic technology guided by ANN can be used to synthesize HPGM for biotechnology processes.
dc.format854-854
dc.publisherAptor Software
dc.rightsopenAccess
dc.titleFabrication of hyperbranched polyglycerols microcapsules from microfluidics guided by artificial neural networks
dc.typeResumo de eventos cient??ficos
dc.coverageI
dc.localS??o Carlos, SP


Este ítem pertenece a la siguiente institución