Method for designing metal organic framework based on molecular fingerprints

Abstract

The invention relates to the field of computational chemistry and nano composite catalytic materials, and discloses a method for designing a metal organic framework based on molecular fingerprints, which comprises the following steps of: 1, acquiring descriptors and adsorption performance parameters of the metal organic framework; a second step of performing regression prediction on different molecular fingerprints by utilizing a machine learning algorithm based on the descriptors and the adsorption performance parameters, and taking molecular fingerprint types as input, the molecular fingerprint types including APFP, Estate, MACCS and PubChem; 3, according to a regression prediction effect, evaluating prediction effects of different types of molecular fingerprints, finding out a fingerprint type with high prediction precision, and obtaining a molecular fingerprint with high prediction precision; 4, counting excellent fingerprint bit numbers by using the molecular fingerprints with high prediction precision; and 5, designing the metal organic framework according to the excellent fingerprint bit number. According to the method, the important fingerprint bit number can be accurately and quickly found, and the design of the metal organic framework is guided.

Description

technical field [0001] The invention relates to the field of computational chemistry and nano-composite catalytic materials, in particular to a method for designing metal-organic frameworks based on molecular fingerprints. Background technique [0002] Propane (C3) is one of the non-methane hydrocarbon compounds, which can be released into the atmosphere through both natural and man-made ways. The natural factors include the production of microorganisms, the emission of vegetation and marine organisms, etc. Combustion of substances, forest fires and traffic emissions, etc. Once this gas is released into the air, it will be oxidized into various toxic aldehydes, ketones and phenols, which pollute the environment and endanger human health. Therefore, it is very important to capture and purify trace amounts of propane in the air. [0003] At present, a class of MOF materials formed by self-assembly of metal clusters and organic links has attracted attention from all walks of ...

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Problems solved by technology

HTCS based on machine learning will also suffer from some limitations, such as a large number of invalid calculations are run, the calculation is expensive and relatively inefficient

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