Compound synthetic route reaction condition prediction system based on ai prediction

Abstract

The invention discloses a compound synthesis route reaction condition prediction system based on ai prediction, and relates to the field of AI. Comprising a database which is used for collecting energy information of chemical bonds among different elements and known condition information of chemical bond fracture and formation; the input module is used for inputting reactants and types of generated compounds into the system; the AI analysis module is used for predicting reaction conditions in combination with database information according to the input of the input module; and the output module is used for outputting the prediction result of the analysis module. Preferably, the database is a local server or a cloud server. According to the method, probability statistics is carried out on the reaction conditions of known chemical reactions on the basis of AI prediction and on the basis of fracture and formation of chemical bonds, so that the reaction conditions of unknown chemical reactions can be predicted, and the efficiency is improved while the manual work is greatly reduced.

Description

Technical Field

[0001] The present invention relates to the field of AI, and in particular to a compound synthesis route reaction condition prediction system based on AI prediction. Background Art

[0002] The reaction conditions of chemical reactions are complex and varied. For the same reaction path, using different reaction conditions often leads to different reaction results. In related technologies, the prediction of chemical reaction conditions is usually based on a large amount of literature research and the experience of chemical engineers, which consumes a lot of manpower and takes too long.

[0003] With the development of artificial intelligence (AI), using artificial intelligence to replace manual labor can not only reduce the intensity of manual labor, but also solve the defects caused by human subjectivity. At the same time, it can greatly improve efficiency when combined with high-computing power chips.

[0004] Therefore, how to use artificial intelligence to reliably predict the reaction conditions of the synthesis route of a compound is a technical problem that needs to be solved urgently.

[0005] To this end, the present invention proposes a compound synthesis route reaction condition prediction system based on AI prediction Summary of the invention

[0006] The purpose of the present invention is to solve the shortcomings of the prior art and propose a compound synthesis route reaction condition prediction system based on AI prediction.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A compound synthesis route reaction condition prediction system based on AI prediction, comprising:

[0009] Databases for collecting information on the energy of chemical bonds between different elements and on the conditions under which known chemical bonds are broken and formed;

[0010] An input module, which is used to input the types of reactants and generated compounds into the system;

[0011] The AI ​​analysis module predicts reaction conditions based on the input from the input module and combined with the database information;

[0012] The output module outputs the prediction results of the analysis module.

[0013] Preferably, the database is a local server or a cloud server.

[0014] Preferably: the working logic of the compound synthesis route reaction condition prediction system based on AI prediction includes the following steps:

[0015] S1: Collect the energy released by breaking chemical bonds between different elements and the energy absorbed by forming chemical bonds, and collect the conditions required for forming and breaking chemical bonds between different elements from known chemical reactions;

[0016] S2: Input reactants and products through the input module;

[0017] S3: The Ai analysis module determines the type and quantity of chemical bond breaking and generation based on the reactants and products, and then makes a judgment based on the data in the database;

[0018] S4: The output module outputs the judgment result to the outside.

[0019] Preferably: the step S3 includes the following steps:

[0020] S31: Based on the reactants and products, determine the types of chemical bond breakage before and after the reaction: A1, A2, ... A n , the energy required to break each chemical bond is X A1 , X A2 ,......X An , types of chemical bonds formed B1, B2, ... B m , the energy released by each chemical bond formation is X B1 , X B2 ,......X Bm and the pressure and catalytic conditions for chemical bond breaking and formation;

[0021] S32: Determine the thermal reaction conditions based on the energy difference before and after the breaking and formation of chemical bonds. According to the known pressure conditions and catalytic conditions for the breaking and formation of chemical bonds in the database, a probability-based calculation method is used to determine the required pressure conditions and catalytic conditions.

[0022] Preferably: in steps S31 and S32, the pressure conditions include high pressure, normal pressure and negative pressure.

[0023] Preferably: in the steps S31 and S32, the catalytic conditions include whether catalysis is required and the type of catalyst required for catalysis.

[0024] Preferably: in the step S32, the judgment logic of the thermal reaction conditions is:

[0025] A1: If The reaction is judged to be an endothermic reaction, which requires high temperature reaction conditions;

[0026] A2: If The reaction is judged to be an exothermic reaction and can be carried out at room temperature.

[0027] Preferably: in the step S33, the judgment logic of the pressure condition is:

[0028] B1: Choose one of the chemical bond breaking situations A i Or one of the chemical bond formation situations B i , and then search the database for A i Break or B i The chemical reaction formed, and the pressure conditions and catalytic conditions of the reaction are obtained, and the pressure conditions and catalytic conditions are probabilistically integrated to obtain the pressure conditions and probability P in the database Y and catalytic conditions and probability P C ;

[0029] B2: P Y , P C The maximum value is taken as the most likely pressure condition and catalytic condition;

[0030] B3: Repeat steps B1-B2 until the P values ​​of all chemical bond breaking and chemical bond forming conditions are Y , P C All obtained;

[0031] B4: Different pressure conditions and catalytic conditions correspond to P Y , P C Take the average, and the one with the largest average is the final reaction condition.

[0032] Preferably: in step B1, the probability comprehensive formula for the pressure condition is: P Y0 A i Break or B i The number of chemical reactions in which the reaction conditions match the pressure conditions, P Y1 A i Break or B i The total number of chemical reactions formed.

[0033] Preferably: in step B1, the probability comprehensive formula for the catalytic conditions is: P C0 A i Break or B i The number of chemical reactions in which the reaction conditions match the catalytic conditions, P C1 A i Break or B i The total number of chemical reactions formed.

[0034] The beneficial effects of the present invention are:

[0035] 1. The present invention uses AI-based prediction to perform probability statistics based on the breaking and forming of chemical bonds and the reaction conditions of known chemical reactions, thereby predicting the reaction conditions of unknown chemical reactions, greatly reducing manual labor and improving efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a working logic diagram of a compound synthesis route reaction condition prediction system based on AI prediction proposed by the present invention. DETAILED DESCRIPTION

[0037] The technical solution of the present invention is further described in detail below in conjunction with specific implementation methods.

[0038] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "set" should be understood in a broad sense, for example, they can be fixedly connected or set, or detachably connected or set, or integrally connected or set. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0039] Embodiment 1:

[0040] A compound synthesis route reaction condition prediction system based on AI prediction, comprising:

[0041] Databases for collecting information on the energy of chemical bonds between different elements and on the conditions under which known chemical bonds are broken and formed;

[0042] An input module, which is used to input the types of reactants and generated compounds into the system;

[0043] The AI ​​analysis module predicts reaction conditions based on the input from the input module and combined with the database information;

[0044] The output module outputs the prediction results of the analysis module.

[0045] The database is a local server.

[0046] The working logic of the compound synthesis route reaction condition prediction system based on AI prediction includes the following steps:

[0047] S1: Collect the energy released by breaking chemical bonds between different elements and the energy absorbed by forming chemical bonds, and collect the conditions required for forming and breaking chemical bonds between different elements from known chemical reactions;

[0048] S2: Input reactants and products through the input module;

[0049] S3: The Ai analysis module determines the type and quantity of chemical bond breaking and generation based on the reactants and products, and then makes a judgment based on the data in the database;

[0050] S4: The output module outputs the judgment result to the outside.

[0051] Embodiment 2:

[0052] A compound synthesis route reaction condition prediction system based on AI prediction, comprising:

[0053] Databases for collecting information on the energy of chemical bonds between different elements and on the conditions under which known chemical bonds are broken and formed;

[0054] An input module, which is used to input the types of reactants and generated compounds into the system;

[0055] The AI ​​analysis module predicts reaction conditions based on the input from the input module and combined with the database information;

[0056] The output module outputs the prediction results of the analysis module.

[0057] The database is a cloud server.

[0058] The working logic of the compound synthesis route reaction condition prediction system based on AI prediction includes the following steps:

[0059] S1: Collect the energy released by breaking chemical bonds between different elements and the energy absorbed by forming chemical bonds, and collect the conditions required for forming and breaking chemical bonds between different elements from known chemical reactions;

[0060] S2: Input reactants and products through the input module;

[0061] S3: The Ai analysis module determines the type and quantity of chemical bond breaking and generation based on the reactants and products, and then makes a judgment based on the data in the database;

[0062] S4: The output module outputs the judgment result to the outside.

[0063] Embodiment 3:

[0064] A compound synthesis route reaction condition prediction system based on AI prediction, comprising:

[0065] Databases for collecting information on the energy of chemical bonds between different elements and on the conditions under which known chemical bonds are broken and formed;

[0066] An input module, which is used to input the types of reactants and generated compounds into the system;

[0067] The AI ​​analysis module predicts reaction conditions based on the input from the input module and combined with the database information;

[0068] The output module outputs the prediction results of the analysis module.

[0069] The database is a local server or a cloud server.

[0070] The working logic of the compound synthesis route reaction condition prediction system based on AI prediction includes the following steps:

[0071] S1: Collect the energy released by breaking chemical bonds between different elements and the energy absorbed by forming chemical bonds, and collect the conditions required for forming and breaking chemical bonds between different elements from known chemical reactions;

[0072] S2: Input reactants and products through the input module;

[0073] S3: The Ai analysis module determines the type and quantity of chemical bond breaking and generation based on the reactants and products, and then makes a judgment based on the data in the database;

[0074] S4: The output module outputs the judgment result to the outside.

[0075] The step S3 includes the following steps:

[0076] S31: Based on the reactants and products, determine the types of chemical bond breakage before and after the reaction: A1, A2, ... A n , the energy required to break each chemical bond is X A1 , X A2 ,......X An , types of chemical bonds formed B1, B2, ... B m , the energy released by each chemical bond formation is X B1 , X B2 ,……X Bm and the pressure and catalytic conditions for chemical bond breaking and formation;

[0077] S32: Determine the thermal reaction conditions based on the energy difference before and after the breaking and formation of chemical bonds. According to the known pressure conditions and catalytic conditions for the breaking and formation of chemical bonds in the database, a probability-based calculation method is used to determine the required pressure conditions and catalytic conditions.

[0078] In the steps S31 and S32, the pressure conditions include high pressure, normal pressure and negative pressure, and the catalytic conditions include whether catalysis is required and the type of catalyst required for catalysis.

[0079] Embodiment 4:

[0080] A compound synthesis route reaction condition prediction system based on AI prediction, comprising:

[0081] Databases for collecting information on the energy of chemical bonds between different elements and on the conditions under which known chemical bonds are broken and formed;

[0082] An input module, which is used to input the types of reactants and generated compounds into the system;

[0083] The AI ​​analysis module predicts reaction conditions based on the input from the input module and combined with the database information;

[0084] The output module outputs the prediction results of the analysis module.

[0085] The database is a local server or a cloud server.

[0086] The working logic of the compound synthesis route reaction condition prediction system based on AI prediction includes the following steps:

[0087] S1: Collect the energy released by breaking chemical bonds between different elements and the energy absorbed by forming chemical bonds, and collect the conditions required for forming and breaking chemical bonds between different elements from known chemical reactions;

[0088] S2: Input reactants and products through the input module;

[0089] S3: The Ai analysis module determines the type and quantity of chemical bond breaking and generation based on the reactants and products, and then makes a judgment based on the data in the database;

[0090] S4: The output module outputs the judgment result to the outside.

[0091] The step S3 includes the following steps:

[0092] S31: Based on the reactants and products, determine the types of chemical bond breakage before and after the reaction: A1, A2, ... A n , the energy required to break each chemical bond is X A1 , X A2 ,......X An , types of chemical bonds formed B1, B2, ... B m , the energy released by each chemical bond formation is X B1 , X B2 ,……X Bm and the pressure and catalytic conditions for chemical bond breaking and formation;

[0093] S32: Determine the thermal reaction conditions based on the energy difference before and after the breaking and formation of chemical bonds. According to the known pressure conditions and catalytic conditions for the breaking and formation of chemical bonds in the database, a probability-based calculation method is used to determine the required pressure conditions and catalytic conditions.

[0094] In the steps S31 and S32, the pressure conditions include high pressure, normal pressure and negative pressure, and the catalytic conditions include whether catalysis is required and the type of catalyst required for catalysis.

[0095] In the step S32, the judgment logic of the thermal reaction conditions is:

[0096] A1: If The reaction is judged to be an endothermic reaction, which requires high temperature reaction conditions;

[0097] A2: If The reaction is judged to be an exothermic reaction and can be carried out at room temperature.

[0098] In step S33, the judgment logic of the pressure condition is:

[0099] B1: Choose one of the chemical bond breaking situations A i Or one of the chemical bond formation situations B i , and then search the database for A i Break or B i The chemical reaction formed, and the pressure conditions and catalytic conditions of the reaction are obtained, and the pressure conditions and catalytic conditions are probabilistically integrated to obtain the pressure conditions and probability P in the database Y and catalytic conditions and probability P C ;

[0100] B2: P Y , P C The maximum value is taken as the most likely pressure condition and catalytic condition;

[0101] B3: Repeat steps B1-B2 until the P values ​​of all chemical bond breaking and chemical bond forming conditions are Y , P C All obtained;

[0102] B4: Different pressure conditions and catalytic conditions correspond to P Y , P C Take the average, and the one with the largest average is the final reaction condition.

[0103] Embodiment 5:

[0104] A compound synthesis route reaction condition prediction system based on AI prediction, comprising:

[0105] Databases for collecting information on the energy of chemical bonds between different elements and on the conditions under which known chemical bonds are broken and formed;

[0106] An input module, which is used to input the types of reactants and generated compounds into the system;

[0107] The AI ​​analysis module predicts reaction conditions based on the input from the input module and combined with the database information;

[0108] The output module outputs the prediction results of the analysis module.

[0109] The database is a local server or a cloud server.

[0110] The working logic of the compound synthesis route reaction condition prediction system based on AI prediction includes the following steps:

[0111] S1: Collect the energy released by breaking chemical bonds between different elements and the energy absorbed by forming chemical bonds, and collect the conditions required for forming and breaking chemical bonds between different elements from known chemical reactions;

[0112] S2: Input reactants and products through the input module;

[0113] S3: The Ai analysis module determines the type and quantity of chemical bond breaking and generation based on the reactants and products, and then makes a judgment based on the data in the database;

[0114] S4: The output module outputs the judgment result to the outside.

[0115] The step S3 includes the following steps:

[0116] S31: Based on the reactants and products, determine the types of chemical bond breakage before and after the reaction: A1, A2, ... A n , the energy required to break each chemical bond is X A1 , X A2 ,……X An , the types of chemical bonds formed are B1, B2, ... B m , the energy released by each chemical bond formation is X B1 , X B2 ,……X Bm and the pressure and catalytic conditions for chemical bond breaking and formation;

[0117] S32: Determine the thermal reaction conditions based on the energy difference before and after the breaking and formation of chemical bonds. According to the known pressure conditions and catalytic conditions for the breaking and formation of chemical bonds in the database, a probability-based calculation method is used to determine the required pressure conditions and catalytic conditions.

[0118] In the steps S31 and S32, the pressure conditions include high pressure, normal pressure and negative pressure, and the catalytic conditions include whether catalysis is required and the type of catalyst required for catalysis.

[0119] In the step S32, the judgment logic of the thermal reaction conditions is:

[0120] A1: If The reaction is judged to be an endothermic reaction, which requires high temperature reaction conditions;

[0121] A2: If The reaction is judged to be an exothermic reaction and can be carried out at room temperature.

[0122] In step S33, the judgment logic of the pressure condition is:

[0123] B1: Choose one of the chemical bond breaking situations A i Or one of the chemical bond formation situations B i , and then search the database for A i Break or B i The chemical reaction formed, and the pressure conditions and catalytic conditions of the reaction are obtained, and the pressure conditions and catalytic conditions are probabilistically integrated to obtain the pressure conditions and probability P in the database Y and catalytic conditions and probability P C ;

[0124] B2: P Y , P C The maximum value is taken as the most likely pressure condition and catalytic condition;

[0125] B3: Repeat steps B1-B2 until the P values ​​of all chemical bond breaking and chemical bond forming conditions are Y , P C All obtained;

[0126] B4: Different pressure conditions and catalytic conditions correspond to P Y , P C Take the average, and the one with the largest average is the final reaction condition.

[0127] In step B1, the probability comprehensive formula for the pressure condition is: P Y0 A i Break or B i The number of chemical reactions in which the reaction conditions match the pressure conditions, P Y1 A i Break or B i The total number of chemical reactions formed.

[0128] In step B1, the probability comprehensive formula for the catalytic conditions is: PC0 A i Break or B i The number of chemical reactions in which the reaction conditions match the catalytic conditions, P C1 A i Break or B i The total number of chemical reactions formed.

[0129] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A compound synthesis route reaction condition prediction system based on AI prediction, characterized in that: The following steps are involved: Databases for collecting information on the energy of chemical bonds between different elements and on the conditions under which known chemical bonds are broken and formed; An input module, which is used to input the types of reactants and generated compounds into the system; The AI ​​analysis module predicts reaction conditions based on the input from the input module and combined with the database information; The output module outputs the prediction results of the analysis module.

2. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 1, characterized in that: The database is a local server or a cloud server.

3. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 1 or 2, characterized in that: The working logic of the compound synthesis route reaction condition prediction system based on AI prediction includes the following steps: S1: Collect the energy released by breaking chemical bonds between different elements and the energy absorbed by forming chemical bonds, and collect the conditions required for forming and breaking chemical bonds between different elements from known chemical reactions; S2: Input reactants and products through the input module; S3: The Ai analysis module determines the type and quantity of chemical bond breaking and generation based on the reactants and products, and then makes a judgment based on the data in the database; S4: The output module outputs the judgment result to the outside.

4. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 3, characterized in that: The step S3 includes the following steps: S31: Based on the reactants and products, determine the types of chemical bond breakage before and after the reaction: A1, A2, ... A n , the energy required to break each chemical bond is X A1 , X A2 ,......X An , the types of chemical bonds formed are B1, B2, ... B m , the energy released by each chemical bond formation is X B1 , X B2 ,……X Bm and the pressure and catalytic conditions for chemical bond breaking and formation; S32: Determine the thermal reaction conditions based on the energy difference before and after the breaking and formation of chemical bonds. According to the known pressure conditions and catalytic conditions for the breaking and formation of chemical bonds in the database, a probability-based calculation method is used to determine the required pressure conditions and catalytic conditions.

5. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 4, characterized in that: In the steps S31 and S32, the pressure conditions include high pressure, normal pressure and negative pressure.

6. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 4, characterized in that: In the steps S31 and S32, the catalytic conditions include whether catalysis is required and the type of catalyst required for catalysis.

7. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 4, characterized in that: In the step S32, the judgment logic of the thermal reaction conditions is: A1: If The reaction is judged to be an endothermic reaction, which requires high temperature reaction conditions; A2: If The reaction is judged to be an exothermic reaction and can be carried out at room temperature.

8. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 4, characterized in that: In step S33, the judgment logic of the pressure condition is: B1: Choose one of the chemical bond breaking situations A i Or one of the chemical bond formation situations B i , and then search the database for A i Break or B i The chemical reaction formed, and the pressure conditions and catalytic conditions of the reaction are obtained, and the pressure conditions and catalytic conditions are probabilistically integrated to obtain the pressure conditions and probability P in the database Y and catalytic conditions and probability P C ; B2: P Y , P C The maximum value is taken as the most likely pressure condition and catalytic condition; B3: Repeat steps B1-B2 until the P values ​​of all chemical bond breaking and chemical bond forming conditions are Y , P C All obtained; B4: Different pressure conditions and catalytic conditions correspond to P Y , P C Take the average, and the one with the largest average is the final reaction condition.

9. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 8, characterized in that: In step B1, the probability comprehensive formula for the pressure condition is: P Y0 A i Break or B i The number of chemical reactions in which the reaction conditions match the pressure conditions, P Y1 A i Break or B i The total number of chemical reactions formed.

10. A compound synthesis route reaction condition prediction system based on AI prediction according to claim 8, characterized in that: In step B1, the probability comprehensive formula for the catalytic conditions is: P C0 A i Break or B i The number of chemical reactions in which the reaction conditions match the catalytic conditions, P C1 A i Break or B i The total number of chemical reactions formed.

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