Towards computational design of zeolite catalysts for CO₂ reduction

Abstract

Carbon dioxide, an energy waste by-product with significant environmental consequences can be utilized and converted into useful chemical products such as formic acid, formaldehyde, methanol or methane, but more energy and cost efficient catalytic processes are required. Here we develop the methodology for the intelligent selection of porous zeolites for dual-adsorption of hydrogen and carbon dioxide as templates for preparing the optimal catalytic environment for carbon dioxide reduction. Useful zeolite catalysts were computationally screened from over 300 thousand zeolite structures using a combination of molecular simulation and machine-learning techniques. Several of the top candidates were very promising energyefficient templates for catalysis with the potential to perform at 50% above conventional reactors. It is also found that an optimal cavity size of around 6 A is required to maximize the change in entropy-enthalpy upon adsorption with a maximum void space >30% to boost product formation per volume of material.

Competitive adsorption of VOCs from binary aqueous mixtures on zeolite ZSM-5

“…2,12,13 Their relevance to these areas stimulates scientists to investigate these materials and many studies have been devolved to clarify the molecular lling patterns of zeolite micropores during the adsorption of a single compound. [14][15][16] Indeed many works deal with the adsorption of VOCs from unary and binary mixtures in gaseous phase onto zeolites. [17][18][19][20] In the latter cases, it was reported that for a given crystalline framework, the adsorption depends on component volatility size, shape, charge, and concentration, initial molar fraction of the gas phase, as well as the Si/Al ratio of the host framework and the nature/amount of the extra-framework species.…”

pyIAST: Ideal adsorbed solution theory (IAST) Python package

“…In addition, pyIAST performs reverse IAST calculations, where one calculates the required gas phase composition to yield a desired adsorbed phase composition. This feature is useful in catalysis, where one seeks to control the adsorbed phase composition to yield the appropriate stochiometry in the adsorbed phase [32].…”

pywindow: Automated Structural Analysis of Molecular Pores

“…Thus, structural characterization is often a key part of computeraided design of porous materials. 2,3 Common structural descriptors for porous networks are the largest cavity diameter (LCD), the largest sphere that can be inserted in the porous material without overlapping with any of the atoms, and the pore limiting diameter (PLD), the largest sphere that can freely diffuse through the porous network without overlapping with any of the atoms. 4 The LCD and PLD, in tandem with the computationally determined pore size distribution (PSD), surface area (SA), and pore volume, are often used to estimate the porous material's performance in silico.…”