Coupling reaction yield intelligent prediction method based on attention convolutional neural network

A convolutional neural network, intelligent prediction technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as labor, time, and money

Pending Publication Date: 2021-09-10
HENAN UNIVERSITY
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Problems solved by technology

Especially in the field of chemistry, the experimental reaction process is time-consuming, labor-intensive, and cost

Method used

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  • Coupling reaction yield intelligent prediction method based on attention convolutional neural network
  • Coupling reaction yield intelligent prediction method based on attention convolutional neural network
  • Coupling reaction yield intelligent prediction method based on attention convolutional neural network

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Embodiment Construction

[0051] Such as Figure 1-4 As shown, the present invention proposes a method for intelligent prediction of coupling reaction yield based on attention convolutional neural network, and the specific steps include data acquisition of chemical component feature descriptors, model construction and intelligent prediction of yield.

[0052] Step 1) data acquisition of chemical component feature descriptors; need to use relevant chemical software (the chemical software used in the present invention is Spartan), input reagent structure and reaction components in the software interface, so that the software automatically extracts feature descriptors to describe each response. Its specific implementation steps include:

[0053] (1.1) All variables in the Buchwald-Hartwig amination reaction, including 15 halides, 4 ligands, 3 substrates, and 23 additives, were input sequentially in the Spartan software, and the variables were arranged and combined after extracting feature descriptors.

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Abstract

The invention discloses a coupling reaction yield intelligent prediction method based on an attention convolutional neural network. The method comprises the steps of data acquisition, model construction and yield intelligent prediction. The method comprises the following specific implementation steps: 1) calculating and extracting feature descriptors of compounds by utilizing chemical related software, and performing subsequent processing by taking the feature descriptors as original data of a training set and a test set; 2) importing the feature descriptor data into a convolutional neural network, and fusing an attention mechanism into a convolutional neural network model; 3) training the acquired data by using a built attention convolutional neural network model, and storing the model when the value of a loss function MSE of the model is minimum; 4) enabling a user to adjust model parameters by himself/herself to achieve the optimal prediction effect; and (5) loading the trained model, and carrying out intelligent prediction on test data. According to the coupling reaction yield intelligent prediction method, a chemical owner can be assisted to rapidly predict the coupling reaction yield, and the chemical synthesis process is greatly accelerated.

Description

technical field [0001] The invention belongs to the field of organic chemical synthesis based on deep learning, in particular to an intelligent prediction method for coupling reaction yield based on attentional convolutional neural network. Background technique [0002] Coupling reaction (Coupled Reaction) is a process in which two organic chemical units (Molecules) undergo a chemical reaction to obtain an organic molecule. Coupling reactions have many ways and are widely used in organic synthesis. The coupling reaction in the narrow sense is a C-C bond formation reaction involving an organometallic catalyst. According to different types, it can be divided into cross-coupling and self-coupling reactions. Cross-coupling refers to the connection of two different fragments into one molecule. Coupling means that two identical fragments form one molecule. [0003] The reaction mechanism of the coupling reaction usually starts with the oxidative addition of an organohalogenated ...

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Application Information

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IPC IPC(8): G16C20/70G16C20/10G06N3/04G06N3/08
CPCG16C20/70G16C20/10G06N3/08G06N3/045
Inventor 彭李超杨晓慧侯贺讯董晶王治华赵彦保
Owner HENAN UNIVERSITY
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