Advances in Density Functional Calculations: Overcoming Convergence Challenges in Mesoporous Structures

Density functional theory (DFT) investigations can be further expanded to explore novel porous nanomaterials by examining the energetics of these materials as a function of pore size, pore surface functionalization, and loading. The inherent complexity and low symmetry of modified porous nanomaterials present significant numerical challenges, particularly in achieving smooth electronic minimization and convergence. These challenges become even more pronounced when dealing with spin-polarized simulations or models containing rare earth or transition metal elements. In this presentation, we will discuss our innovative strategies for achieving convergence in complex nanoporous materials, such as mesoporous silica and nanoporous graphitic carbonitride (Figure ۱) [۱‒۴]. Our approach includes techniques like pre-optimizing the geometry with molecular dynamics, coarse-graining methods, and optimizing essential building blocks through preliminary simulations.

کلیدواژه ها:

Nanoporous materials ، Polysilsesquioxane ، Density functional calculations ، Machine learning ، Artificial intelligence.