Method for designing metal organic framework based on molecular fingerprints

A technology of metal-organic frameworks and molecular fingerprints, applied in molecular design, nuclear methods, chemical statistics, etc., can solve problems such as low efficiency and expensive calculations, reduce time and waste of manpower and material resources, and improve screening efficiency.

Pending Publication Date: 2022-07-22
GUANGZHOU UNIVERSITY
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  • Abstract
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  • Claims
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Problems solved by technology

HTCS based on machine learning will also suffer from some limitations, such as a large numb

Method used

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  • Method for designing metal organic framework based on molecular fingerprints
  • Method for designing metal organic framework based on molecular fingerprints
  • Method for designing metal organic framework based on molecular fingerprints

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Experimental program
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Embodiment

[0035] see Figure 1-4 , the method for designing metal-organic frameworks based on molecular fingerprints provided in this embodiment specifically includes the following steps:

[0036] S1. Collect descriptors and adsorption performance parameters of metal-organic frameworks;

[0037] S2. Use the machine learning algorithm to perform regression prediction on different molecular fingerprints, and use the type of molecular fingerprints as input;

[0038] S3. According to the regression prediction effect, evaluate the prediction effect of different types of molecular fingerprints and find the fingerprint type with high prediction accuracy;

[0039] S4. Use molecular fingerprints with high prediction accuracy to count excellent fingerprint tags;

[0040] S5. Design the metal organic framework according to the excellent fingerprint tag;

[0041] In order to better describe this embodiment, a specific example is used for description below.

[0042] S1. Collect descriptors and a...

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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 ...

Claims

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Application Information

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IPC IPC(8): G16C10/00G16C20/50G16C20/70G06N20/10
CPCG16C10/00G16C20/70G16C20/50G06N20/10
Inventor 乔智威黄秋红袁雪迎关雅芳张知科朱鑫梁红
Owner GUANGZHOU UNIVERSITY
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