Study of CO₂ capture by synthesized composite and modelling with machine learning and response surface methodology.

ABSTRACT: This research investigated and optimized the separation of carbon dioxide (CO₂) from natural gas in an adsorption column filled with grafted-beam nanofiber adsorbent. The main purpose of using ANN and RSM models in this manuscript is to compare these two methods in predicting the CO₂ adsorption capacity. In other words, it was made to find a suitable model that has the highest agreement with the experimental data. Also, the other purpose of using the RSM model is to detect the optimized empirical conditions. Moreover, two common ANN models are applied in this work, including a multilayer perceptron (MLP) and radial basis function (RBF). The novelties of this work are explained as follows: (1) detecting the optimized synthesis factors of NF-PAN/PUGMA sorbent which poss

SUBMITTER: Masoumi H 

PROVIDER: S-EPMC12783714 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature