CN113433276A - Quantum chemistry high-throughput screening method of chalcopyrite inhibitor - Google Patents
Quantum chemistry high-throughput screening method of chalcopyrite inhibitor Download PDFInfo
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- CN113433276A CN113433276A CN202110631730.1A CN202110631730A CN113433276A CN 113433276 A CN113433276 A CN 113433276A CN 202110631730 A CN202110631730 A CN 202110631730A CN 113433276 A CN113433276 A CN 113433276A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/15—Medicinal preparations ; Physical properties thereof, e.g. dissolubility
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B03—SEPARATION OF SOLID MATERIALS USING LIQUIDS OR USING PNEUMATIC TABLES OR JIGS; MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
- B03D—FLOTATION; DIFFERENTIAL SEDIMENTATION
- B03D2201/00—Specified effects produced by the flotation agents
- B03D2201/06—Depressants
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B03—SEPARATION OF SOLID MATERIALS USING LIQUIDS OR USING PNEUMATIC TABLES OR JIGS; MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
- B03D—FLOTATION; DIFFERENTIAL SEDIMENTATION
- B03D2203/00—Specified materials treated by the flotation agents; specified applications
- B03D2203/02—Ores
- B03D2203/04—Non-sulfide ores
Abstract
The invention discloses a quantum chemistry high-throughput screening method of a chalcopyrite inhibitor, which comprises the following steps: s1, establishing a molecular database of the flotation reagent; s2, carrying out coarse optimization to obtain an optimized molecule database; s3, respectively making corresponding input files aiming at molecules of the initial structure in neutral and one proton-losing states to obtain a first molecular database; s4, butting molecules and metal ions to form alkyl-functional group-metal to obtain a second molecular database; s5, optimizing and analyzing the molecules to obtain quantum chemical parameters and log files; s6, reading the log file to obtain an output file, and extracting the molecular structure property parameters by analyzing the output file; s7 predicting Gibbs free energy of reaction, and screening the flotation reagent. The invention adopts a quantum chemical method to analyze and screen typical functional group molecules, and avoids the technical problems of low success rate, low screening efficiency, risk of synthesizing unknown toxic substances, huge resource waste and safety problems of the traditional trial and error method.
Description
Technical Field
The invention relates to the technical field of flotation reagents, in particular to a quantum chemistry high-throughput screening method of a chalcopyrite inhibitor.
Background
Flotation is the most important mineral fine particle separation technology in the world, the flotation separation efficiency and the separation capability of minerals depend on the difference of hydrophilicity and hydrophobicity of the surfaces of minerals, and the larger the hydrophobicity difference is, the easier the separation is carried out by flotation.
Chalcopyrite is the most basic and important copper ore resource, has good surface hydrophobicity, so that the chalcopyrite is not easy to be selectively separated from molybdenite, galena, bismuthate and the like which also have good hydrophobicity, and meanwhile, the molybdenite, the galena and the like are also very important metal mineral resources. Therefore, specific flotation inhibitors are required to selectively increase the hydrophilicity of the chalcopyrite surface.
In the prior art, a traditional medicament trial-and-error method is adopted to screen the flotation inhibitor, so that the success rate is low, the screening efficiency is low, the risk of synthesizing unknown toxic substances exists, and huge resource waste and safety problems exist.
Therefore, there is a need to develop a safe, rapid, high-throughput screening method for chalcopyrite inhibitors.
Disclosure of Invention
The invention aims to provide a quantum chemical high-throughput screening method for a chalcopyrite inhibitor, which aims to solve the technical problems of low success rate and low screening efficiency, the risk of synthesizing unknown toxic substances, huge resource waste and safety problems in the prior art of screening the flotation inhibitor by adopting a traditional medicament trial and error method.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a quantum chemistry high-throughput screening method of a chalcopyrite inhibitor comprises the following steps:
s1, establishing a molecular database of the flotation reagent, wherein molecules in the molecular database are alkyl-functional groups formed by combining typical reagent functional groups and alkyl groups;
s2, carrying out coarse optimization on the molecule database obtained in S1 to obtain an optimized molecule database;
s3, taking the molecules in the optimized molecule database obtained in S2 as an initial structure, and respectively making corresponding Gaussian or ORCA input files aiming at the molecules of the initial structure in two states of neutrality and loss of one proton to obtain a first molecule database;
s4, butting molecules in the optimized molecular database obtained in the step S2 with metal ions to form alkyl-functional group-metal to obtain a second molecular database;
s5, optimizing and analyzing molecules in the first sub-database and the second sub-database under the condition that the molecular weight is not lower than B3LYP/DEF2TZVP and the empirical dispersion and calculation level of an SMD solvation model are considered, and obtaining quantum chemical parameters and log files;
s6, reading energy information and wave function information in the log file obtained in the S5 by using NBO software in a GaussView molecular orbit module to obtain an output file, and extracting molecular structure property parameters by analyzing the output file;
s7, predicting the Gibbs free energy of the combination of molecules in the first molecule library and different metal ions according to the molecular structure property parameters obtained in S6, and screening the flotation reagent according to the Gibbs free energy of the reaction.
On the basis of the technical scheme, the invention can be further improved as follows:
further, the alkyl group in S1 is an ethyl group.
By adopting the scheme, the performance-price ratio is higher by adopting the combination of the ethyl short chain and the functional group.
Further, the configurationally stable molecules were screened using molecular dynamics tools of GaussView, Materials students, Jmol, Avogadro, or ChemDraw using molecular dynamics methods.
Further, the metal ions in S4 include Cu2+And Cu+、Fe2+And Fe3+One or more of (a).
By adopting the scheme, the brass ore body is adoptedActive components which may be present as metal ions include monovalent copper ions (Cu)+) Divalent copper ion (Cu)2+) Divalent iron ion (Fe)2+) Trivalent iron ion (Fe)3+)。
Further, the optimization in S5 is specifically: and (3) performing structure optimization on molecules in the first molecular data and the second molecular database by using a method not lower than B3LYP and 6-311G base group under the third-generation empirical dispersion effect under an SMD implicit water solvation model.
Further, the analysis in step S5 specifically includes: and (3) performing vibration analysis and natural charge population analysis on molecules in the first molecular data and the second molecular data base under an SMD implicit hydrosolvent model under the third-generation empirical dispersion effect by using a method not lower than B3LYP and a DEF2TZVP base group.
Further, the molecular structure property parameters in step S6 include: atom species and number, atom Mulliken charge population, natural charge population, APT charge population molecules, corrected thermodynamic free energy, structural electron energy, zero point vibrational energy, and shortest bond length, second shortest bond length of molecules within the second sub-database.
Further, the gibbs free energy of the reaction for predicting the binding of the molecules in the first molecular library with different metal ions in S7 is specifically: and respectively calculating differences of corrected thermodynamic free energies of the molecules in the first molecular library and the molecules in the second molecular libraries corresponding to the molecules in the first molecular library to obtain reaction Gibbs free energies of the molecules in the first molecular library combined with different metal ions.
Further, the step S7 of screening the flotation reagent specifically includes: taking the molecule in the first molecule library and Cu2+Gibbs free energy of reaction G1And Gibbs free energy of reaction G of the molecule with other metal ions2Calculate G1And G2Taking absolute value of the difference, dividing the absolute value by the chemical action energy of 50Kcal/mol, and multiplying the absolute value by 100 to obtain the molecular pair Cu2+And a selectivity score for other metal ions, the flotation agent being screened according to the selectivity score.
Further, the S1 and S4 use GaussView, Materials studio, Jmol, Avogadro or ChemDraw to build a molecular database.
Compared with the prior art, the invention has the beneficial effects that:
the method comprises the steps of firstly establishing a molecular database by utilizing an initial structure formed by butt joint of typical functional groups and alkyl groups, roughly optimizing and screening out a configurationally unstable structure, then changing the charged state of the initial structure to obtain a first molecular database, combining the initial structure with metal ions to obtain a second molecular database, obtaining structural property parameters of molecules in the first molecular database and the second molecular database by adopting a quantum chemistry method, predicting reaction Gibbs free energy of the molecules combined with different metal ions according to the structural property parameters, and obtaining a molecule pair Cu according to the reaction Gibbs free energy2+And the selectivity scores of other metal ions, and the flotation reagents can be quickly selected according to the selectivity scores according to the active components in the actual ore system, so that the technical problems of low success rate, low screening efficiency, risk of synthesizing unknown toxic substances, huge resource waste and safety problems existing in the traditional trial and error method are solved.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
The quantum chemistry high-throughput screening method for the chalcopyrite inhibitor provided by the embodiment comprises the following steps:
s1, establishing a molecular database of flotation reagents by using GaussView, wherein molecules in the molecular database are ethyl-functional groups formed by combining 52 typical reagent functional groups and short-chain ethyl groups, and the specific molecular database is shown in the following table:
table-molecule database list
S2, screening molecules with stable configuration by using a molecular dynamics tool of GaussView and a molecular mechanics method, and performing coarse optimization on the molecular database obtained in S1 to obtain an optimized molecular database;
s3, taking the molecules in the optimized molecule database obtained in S2 as an initial structure, and respectively making corresponding Gaussian or ORCA input files aiming at the molecules of the initial structure in neutral and one-proton-loss states to obtain a first molecule database;
s4 Butt-joining the molecules in the optimized molecular database obtained in S2 with metal ions to form alkyl-functional group-metal, wherein the metal ions are selected from Cu2+、Fe2+Obtaining a second sub database;
s5, optimizing and analyzing molecules in the first sub-database and the second sub-database under the condition that the molecular weight is not lower than B3LYP/DEF2TZVP and the empirical dispersion and calculation level of an SMD solvation model are considered, and obtaining quantum chemical parameters and log files;
wherein the optimization specifically comprises the following steps: performing structure optimization on molecules in the first molecular data and the second molecular database by a method not lower than B3LYP and 6-311G base group under the third-generation empirical dispersion action under an SMD (surface mounted device) implicit water solvation model;
the analysis specifically comprises the following steps: performing vibration analysis and natural charge population analysis on molecules in the first sub-database and the second sub-database under an SMD implicit hydrosolvent model by using a B3LYP method and a DEF2TZVP base group under the consideration of the third-generation empirical dispersion effect;
s6, reading the energy information and the wave function information in the log file obtained in S5 by using NBO software in a GaussView molecular orbit module to obtain an output file, wherein the output file is specifically as follows:
table two output file
Extracting molecular structure property parameters by analyzing the output file, wherein the molecular structure property parameters comprise: atom species and number, atom Mulliken charge population, natural charge population, APT charge population molecules, corrected thermodynamic free energy, structural electron energy, zero point vibration energy, and shortest bond length and next shortest bond length of molecules in the second sub-database;
s7, predicting reaction Gibbs free energy of molecules in the first molecular library combined with different metal ions according to the molecular structure property parameters obtained in S6, and screening flotation reagents according to the reaction Gibbs free energy;
the Gibbs free energy for predicting the reaction of the molecules in the first molecule library combined with different metal ions is specifically as follows: taking corrected thermodynamic free energy of molecules in the first molecular library and molecules in the two second molecular libraries corresponding to the molecules in the first molecular library, and respectively calculating difference values to obtain reaction Gibbs free energy of the molecules in the first molecular library combined with different metal ions;
the step S7 of screening the flotation reagent specifically comprises the following steps: taking the molecule in the first molecule library and Cu2+Gibbs free energy of reaction G1And the molecule and Fe2+Gibbs free energy of reaction G2Calculate G1And G2Taking absolute value of the difference, dividing the absolute value by the chemical action energy of 50Kcal/mol, and multiplying the absolute value by 100 to obtain the molecular pair Cu2+And selectivity scores for other metal ions, and the flotation reagents were screened according to the selectivity scores to obtain the following table.
Scoring drug Selectivity
As shown in table three, drug pair Cu of No. 22+And Fe2+Has the largest selectivity difference, is easy to be combined with copper atoms and not easy to be combined with Fe2+Bonding to Cu2+And Fe2+The optimal flotation effect can be obtained in the chalcopyrite ore system, so the chalcopyrite ore system can be used as a targeted inhibitor of chalcopyrite copper sites.
In the description of the present invention, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A quantum chemistry high-throughput screening method of a chalcopyrite inhibitor is characterized by comprising the following steps:
s1, establishing a molecular database of the flotation reagent, wherein molecules in the molecular database are alkyl-functional groups formed by combining typical reagent functional groups and alkyl groups;
s2, carrying out coarse optimization on the molecule database obtained in S1 to obtain an optimized molecule database;
s3, taking the molecules in the optimized molecule database obtained in S2 as an initial structure, and respectively making corresponding Gaussian or ORCA input files aiming at the molecules of the initial structure in two states of neutrality and loss of one proton to obtain a first molecule database;
s4, butting molecules in the optimized molecular database obtained in the step S2 with metal ions to form alkyl-functional group-metal to obtain a second molecular database;
s5, optimizing and analyzing molecules in the first sub-database and the second sub-database under the condition that the molecular weight is not lower than B3LYP/DEF2TZVP and the empirical dispersion and calculation level of an SMD solvation model are considered, and obtaining quantum chemical parameters and log files;
s6, reading energy information and wave function information in the log file obtained in the S5 by using NBO software in a GaussView molecular orbit module to obtain an output file, and extracting molecular structure property parameters by analyzing the output file;
s7, predicting the Gibbs free energy of the combination of molecules in the first molecule library and different metal ions according to the molecular structure property parameters obtained in S6, and screening the flotation reagent according to the Gibbs free energy of the reaction.
2. The method for quantum chemical high-throughput screening of chalcopyrite inhibitors as claimed in claim 1, wherein the alkyl group in S1 is ethyl.
3. The method for quantum chemical high-throughput screening of chalcopyrite inhibitors according to claim 1, wherein the rough optimization in S2 is specifically: the configurationally stable molecules are screened using molecular dynamics tools of GaussView, Materials students, Jmol, Avogadro, or ChemDraw using molecular dynamics methods.
4. The method for quantum chemical high-throughput screening of chalcopyrite inhibitors as claimed in claim 1, wherein the metal ion in S4 comprises Cu2+And Cu+、Fe2+And Fe3+One or more of (a).
5. The method for quantum chemical high-throughput screening of chalcopyrite inhibitors according to claim 1, wherein the optimization in S5 is specifically: and (3) performing structure optimization on molecules in the first molecular data and the second molecular database by using a method not lower than B3LYP and 6-311G base group under the third-generation empirical dispersion effect under an SMD implicit water solvation model.
6. The method for quantum chemical high-throughput screening of chalcopyrite inhibitors according to claim 1, wherein the analysis in the step S5 is specifically: and (3) performing vibration analysis and natural charge population analysis on molecules in the first molecular data and the second molecular data base under an SMD implicit hydrosolvent model under the third-generation empirical dispersion effect by using a method not lower than B3LYP and a DEF2TZVP base group.
7. The method for quantum chemical high-throughput screening of chalcopyrite inhibitors as claimed in claim 1, wherein the molecular structure property parameters in step S6 include: atom species and number, atom Mulliken charge population, natural charge population, APT charge population molecules, corrected thermodynamic free energy, structural electron energy, zero point vibrational energy, and shortest bond length, second shortest bond length of molecules within the second sub-database.
8. The method for quantum chemical high-throughput screening of chalcopyrite inhibitors according to claim 7, wherein the Gibbs free energy of reaction for predicting the binding of molecules in the first molecular library with different metal ions in S7 is specifically: and respectively calculating differences of corrected thermodynamic free energies of the molecules in the first molecular library and the molecules in the second molecular libraries corresponding to the molecules in the first molecular library to obtain reaction Gibbs free energies of the molecules in the first molecular library combined with different metal ions.
9. The quantum chemical high-throughput screening method of chalcopyrite inhibitor according to claim 1, wherein the screening flotation agent in the step S7 is specifically: taking the molecule in the first molecule library and Cu2+Gibbs free energy of reaction G1And Gibbs free energy of reaction G of the molecule with other metal ions2Calculate G1And G2Taking absolute value of the difference, dividing the absolute value by the chemical action energy of 50Kcal/mol, and multiplying the absolute value by 100 to obtain the molecular pair Cu2+And a selectivity score for other metal ions, the flotation agent being screened according to the selectivity score.
10. The method for quantum chemical high-throughput screening of chalcopyrite inhibitors according to any one of claims 1 to 9, wherein the S1 and S4 establish a molecular database using GaussView, Materials students, Jmol, Avogadro or ChemDraw.
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