Machine learning (ML) using data sets of atomic and molecular force fields (FFs) has made
significant progress and provided benefits in the fields of chemistry and material science …

Pyrolysis, as a thermochemical conversion of biomass, is a superior biofuel production
procedure. The determining procedure for the optimal operational parameters, biomass …

Adsorption of CO 2 on porous carbons has been identified as one of the promising methods
for carbon capture, which is essential for meeting the sustainable developmental goal (SDG) …

Porous carbons as solid adsorbent materials possess effective porosity characteristics that
are the most important factors for gas storage. The chemical activating routes facilitate …

To achieve highly efficient and environmentally degradable adsorbents for Congo red (CR)
removal, we synthesized a dual-network nanocomposite cryogel composed of …

Kaolin-based zeolites have high adsorption capacity due to their combination of
mesoporous and microporous structures. In this research, artificial neural networks (ANN) …

This research focuses on modeling CO2 absorption into alkanolamine solvents using
multilayer perceptron (MLP), radial basis function network (RBF), Support Vector Machine …

To develop more efficient catalysts and discover new materials to work towards efficient
solutions to the growing environmental problems, machine learning (ML) offers viable new …

The ever-increasing carbon emission requires the development of advanced carbon capture
and storage technology. As one of the most promising approaches, the adsorption of CO 2 …

Porous adsorbents have common characteristics, such as high porosity and a large specific
surface area. These characteristics, attributed to the internal structure of the material …