CN112365933A - Method for constructing molecular model of biomass coke - Google Patents
Method for constructing molecular model of biomass coke Download PDFInfo
- Publication number
- CN112365933A CN112365933A CN202011553489.7A CN202011553489A CN112365933A CN 112365933 A CN112365933 A CN 112365933A CN 202011553489 A CN202011553489 A CN 202011553489A CN 112365933 A CN112365933 A CN 112365933A
- Authority
- CN
- China
- Prior art keywords
- biomass
- molecular
- coke
- box
- pyrolysis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 239000000571 coke Substances 0.000 title claims abstract description 75
- 239000002028 Biomass Substances 0.000 title claims abstract description 72
- 238000000034 method Methods 0.000 title claims abstract description 46
- 238000000197 pyrolysis Methods 0.000 claims abstract description 71
- 229920005610 lignin Polymers 0.000 claims abstract description 44
- 238000005457 optimization Methods 0.000 claims abstract description 29
- 239000012634 fragment Substances 0.000 claims abstract description 27
- 238000004088 simulation Methods 0.000 claims abstract description 27
- 239000000463 material Substances 0.000 claims description 22
- 238000000329 molecular dynamics simulation Methods 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000006243 chemical reaction Methods 0.000 claims description 8
- 229920002488 Hemicellulose Polymers 0.000 claims description 4
- 229920002678 cellulose Polymers 0.000 claims description 4
- 125000004432 carbon atom Chemical group C* 0.000 claims description 3
- 239000001913 cellulose Substances 0.000 claims description 3
- 230000007935 neutral effect Effects 0.000 claims description 2
- 238000012360 testing method Methods 0.000 claims description 2
- 239000000047 product Substances 0.000 description 25
- 230000008569 process Effects 0.000 description 7
- 229910052799 carbon Inorganic materials 0.000 description 5
- 238000001179 sorption measurement Methods 0.000 description 5
- 125000003118 aryl group Chemical group 0.000 description 4
- 125000004429 atom Chemical group 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 239000000126 substance Substances 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 150000001721 carbon Chemical group 0.000 description 3
- 238000006555 catalytic reaction Methods 0.000 description 3
- 235000010980 cellulose Nutrition 0.000 description 3
- 238000010276 construction Methods 0.000 description 3
- 238000002309 gasification Methods 0.000 description 3
- 238000010438 heat treatment Methods 0.000 description 3
- 230000000737 periodic effect Effects 0.000 description 3
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 2
- 239000003054 catalyst Substances 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000000446 fuel Substances 0.000 description 2
- 238000012900 molecular simulation Methods 0.000 description 2
- 239000012265 solid product Substances 0.000 description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 1
- 125000001931 aliphatic group Chemical group 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 150000004945 aromatic hydrocarbons Chemical class 0.000 description 1
- 238000005452 bending Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000003197 catalytic effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000005229 chemical vapour deposition Methods 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 238000004132 cross linking Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 125000005842 heteroatom Chemical group 0.000 description 1
- 229930195733 hydrocarbon Natural products 0.000 description 1
- 150000002430 hydrocarbons Chemical class 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- WQGWDDDVZFFDIG-UHFFFAOYSA-N pyrogallol Chemical compound OC1=CC=CC(O)=C1O WQGWDDDVZFFDIG-UHFFFAOYSA-N 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 229910052717 sulfur Inorganic materials 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C10/00—Computational theoretical chemistry, i.e. ICT specially adapted for theoretical aspects of quantum chemistry, molecular mechanics, molecular dynamics or the like
Landscapes
- Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to the technical field of biomass energy, and particularly discloses a method for constructing a biomass coke molecular model, which comprises the following steps: 1) performing energy and geometric optimization on a biomass molecular structure model constructed by simulation software; 2) adopting MS software to construct a box, and putting the optimized biomass molecular structure model into the box; 3) performing energy and NPT optimization on the box processed in the step 2) by adopting MS software to obtain a biomass 3D molecular structure model; 4) carrying out pyrolysis simulation on the biomass 3D molecular structure model by using Lammps software to obtain a molecular fragment of a pyrolysis product; 5) extracting coke molecular fragments in the pyrolysis product, constructing a box by adopting MS software, putting the extracted coke molecular fragments into the box, and then performing energy and NPT (non-uniform pressure) optimization on the box to obtain a 3D molecular structure model of the biomass coke. The method is simple to operate, and the workload of constructing the lignin coke molecular structure model is greatly reduced.
Description
Technical Field
The invention relates to the technical field of chemical molecular reaction kinetics and biomass energy, in particular to a method for constructing a molecular model of biomass coke.
Background
The biomass resources in China are rich and widely distributed, and the realization of the efficient utilization of the biomass energy plays an important role in optimizing the energy structure in China and relieving the energy crisis. The biomass coke is a solid product formed by heating biomass under inert atmosphere, dehydrating, devolatilizing and carrying out a series of physicochemical changes. The biomass coke has the characteristics of rich microporous structure, large specific surface area, strong adsorption capacity and the like, so that the biomass coke has wide application: (1) the C content is high, the N, S content is low, and the fuel can be used as high-quality fuel; (2) has strong physical adsorption property, and can be used for producing active carbon; (3) has certain catalytic action and can be used as a catalyst or a catalyst carrier in chemical industry. On the other hand, with the rapid development of computer technology, molecular simulation research in the field of biomass coke gasification, adsorption, and catalysis research is receiving attention. The establishment of a reasonable biomass coke molecular model is the basis for researching the fields of biomass coke gasification, adsorption, catalysis and the like on a molecular level. At higher pyrolysis temperatures, the cellulose and hemicellulose components of biomass can be almost completely decomposed, and biomass char is primarily a solid product resulting from the pyrolysis of lignin. Thus, lignin char can represent, to some extent, the physicochemical properties of biomass char. At present, more scholars have proposed lignin molecular models, such as Adler, Freudenberg, Nimz models, etc., and lignin coke molecular models are rarely reported.
At present, the main method for constructing the biomass coke molecule model is as follows: firstly, pyrolyzing biomass under inert atmosphere to obtain a biomass coke sample; then, performing high-resolution transmission electron microscope (HRTEM) representation on the focusing sample to obtain basic microstructure information of the focus, such as a focal microcrystalline structure, aromatic structure parameters, stacking structure characteristics and the like; finally, information on the position, angle, number of carbon atoms, and the like of the aromatic structural unit is read by the Fringe3D program, and a molecular model of the aromatic structural unit is obtained. However, there are two limitations to constructing biomass coke models using this approach: firstly, the modeling method of the aromatic hydrocarbon stacking structure provided by the method is a simplified method, and changes of C-C chemical bond length possibly caused by the increase of the carbon ring structure are ignored; the aromatic structural units are reduced to a "flake" structure ignoring possible three-dimensional variations thereof; bending structures, cross-linking structures, aliphatic chain structures and organic heteroatoms were not considered in the Fringe3D procedural modeling stage. Secondly, biomass coke is obtained by thermochemical conversion of biomass, coke structures derived from different types of biomass are different, and the characteristics of coke obtained by the same biomass under different pyrolysis process conditions are also greatly different. Therefore, the biomass coke model constructed by the existing method cannot comprehensively describe the physical and chemical structural characteristics of the biomass coke and is difficult to reflect the influence of different pyrolysis process conditions on the coke structure.
In recent years, computer simulation technology is rapidly developed, wherein the molecular dynamics method (ReaxFF MD) based on the ReaxFF reverse stress field combines the advantages of quantum chemistry and the traditional molecular dynamics method, can be used for simulating the chemical reaction process of a complex system without presetting a reaction path, can reflect the influence of conditions such as temperature, pressure, atmosphere and the like, provides possibility for researching the thermal conversion of biomass on a molecular level, and has been widely applied. Therefore, a lignin pyro molecular model construction method based on the ReaxFF MD method is provided.
Disclosure of Invention
In view of the problems and deficiencies of the prior art, it is an object of the present invention to provide a method for constructing a molecular model of biomass coke.
In order to realize the purpose of the invention, the technical scheme adopted by the invention is as follows:
a method of constructing a molecular model of biomass coke, comprising the steps of:
(1) performing energy and geometric optimization on a biomass molecular structure model constructed by simulation software to obtain an optimized biomass molecular structure model;
(2) adopting an Amorphous Cell module in the Material Studio software to construct a box, and putting the optimized biomass molecular structure model into the box;
(3) performing energy optimization and NPT (neutral Studio) optimization on the box processed in the step (2) by adopting Material Studio software until the density of a box system is constant to obtain a biomass 3D molecular structure model;
(4) performing molecular dynamics pyrolysis simulation based on a reverse stress field on the biomass 3D molecular structure model obtained in the step (3) by using molecular dynamics simulation software Lammps to obtain a molecular fragment of a biomass pyrolysis product;
(5) extracting molecular fragments of coke in the biomass pyrolysis product, constructing a box by using an Amorphous Cell module in Material Studio software, putting the extracted molecular fragments of the coke product into the box, and then performing energy optimization and NPT (non-uniform pressure test) optimization on the box until the density of the box system is constant to obtain a 3D molecular structure model of the biomass coke.
According to the method, preferably, the molecular dynamics pyrolysis simulation in step (4) is performed under NVT ensemble, wherein the force field parameters are chop reaction force field parameters.
According to the above method, preferably, the simulation conditions of the molecular dynamics pyrolysis simulation in step (4) are as follows: the pyrolysis simulation temperature is 300-3000K, the pyrolysis time is 50-250 ps, and the time step is 0.1-0.25 ps.
According to the method, preferably, in step (3) and step (5), the NPT optimization parameters are set as: the pressure was set at 0.1 MPa, the temperature at 298K, the calculation time set at 1000 ps, and the time step size was 1 ps.
According to the method, preferably, in the step (3) and the step (5), the energy optimization is performed by using a Discover module in the Material Studio software, and the NPT optimization is performed by using a Forcite module in the Material Studio software.
According to the method, the number of the biomass molecular structure models in the box in the step (2) is preferably 5-50.
According to the above method, preferably, the initial density of the cartridge in the step (2) is not more than 0.3 g/cm3。
According to the above process, preferably, the coke product is a molecular fragment of pyrolysis product having a number of carbon atoms greater than 40.
According to the above method, preferably, the biomass is any one of lignin, cellulose and hemicellulose.
Compared with the prior art, the invention has the following beneficial effects:
the method comprises the steps of constructing a biomass molecular model, performing ReaxFF MD pyrolysis simulation on the biomass molecular model, extracting biomass coke molecular fragments in a pyrolysis product, constructing a 3D molecular structure model of the biomass coke according to the biomass coke molecular fragments and the like to obtain the 3D molecular structure model of the biomass coke, and greatly reduces the workload of constructing the lignin coke molecular structure model; moreover, the method can construct the 3D molecular structure models of the biomass coke under different pyrolysis conditions such as pyrolysis temperature, heating rate and the like according to actual analysis requirements, and provides a new idea for constructing the molecular models of the biomass coke for molecular simulation research in the fields of biomass coke gasification, adsorption and catalysis research; meanwhile, the defects that the workload is large and the structural difference of coke obtained under different pyrolysis conditions is difficult to reflect in the existing method of directly representing coke to further construct a molecular structure model of the biomass coke are effectively solved.
Drawings
FIG. 1 shows Adler lignin (C) in example 1160H180O58) The molecular planar structure model of (1);
FIG. 2 is a graph of box system density over time during NPT optimization in example 1;
FIG. 3 is the Adler lignin 3D molecular structure model after NPT optimization in example 1; wherein, green represents C; red for O; white represents H;
FIG. 4 is a graph of pyrolysis gas, tar, and coke content as a function of temperature for the lignin pyrolysis product of example 1;
FIG. 5 is a graph of the H/C ratio (a) and the O/C ratio (b) of lignin versus temperature for example 1;
FIG. 6 is a schematic representation of the molecular fragment structure of coke in the lignin pyrolysis product at a temperature of 1800K in example 1; wherein, green represents C; red for O; white represents H;
FIG. 7 is a schematic molecular fragment structure of coke in a lignin pyrolysis product at 2000K in example 1; wherein, green represents C; red for O; white represents H;
FIG. 8 is a model of the 3D structure of lignin coke at a temperature of 1800K in example 1; wherein, green represents C; red for O; white represents H;
FIG. 9 is a model of the 3D structure of lignin coke at a temperature of 2000K in example 1; wherein, green represents C; red for O; white represents H.
Detailed Description
Example 1:
a method of constructing a molecular model of biomass coke, comprising the steps of:
(1) using classical Adler lignin (molecular formula is C)160H180O58) For example, a molecular structure model of Adler lignin was constructed using the Material Studio (MS) software (the molecular structure model is shown in FIG. 1). Energy optimization and geometric optimization are respectively carried out on the molecular structure model of the Adler lignin by adopting a Forcite module in Material Studio (MS) software, the energy of the system is ensured to be in the lowest state, and the optimized molecular structure model of the Adler lignin is obtained.
(2) Constructing a box with periodic boundaries by using an Amorphous Cell module in Material Studio software, then putting 10 optimized Adler lignin molecular structure models into the box, and setting the initial density of the box to be 0.1g/cm3To avoid overlapping of atoms.
(3) Adopting a Discover module in the Material Studio software to optimize the energy of the box processed in the step (2) so as to ensure that the system energy is in the lowest stateState; then, the Forcite module in the Material Studio software is utilized to calculate and optimize the NPT (maintaining the atom number, the pressure and the temperature to be constant) of the box until the density of the box system is constant and is 0.45 g/cm3(FIG. 2 is a graph showing the change of the density of the box system with time in the NPT calculation optimization process, and it can be seen from FIG. 2 that the density of the box system tends to be stable after gradually increasing with time, and the final density of the system is constant and is 0.45 g/cm3) And obtaining a 3D molecular structure model of Adler lignin (shown in figure 3). The parameters of the NPT optimization are set as follows: the pressure was set at 0.1 MPa, the temperature at 298K, the calculation time set at 1000 ps, and the time step size was 1 ps.
(4) Performing Molecular dynamics pyrolysis simulation based on a reverse stress field on the 3D Molecular structure model of the Adler lignin obtained in the step (3) under NVT (non-volatile video) by using CHON (chemical vapor deposition) reverse stress field parameters in Molecular dynamics simulation software Lammps (Large-scale Atomic/Molecular massive Parallel Simulator), wherein the reaction conditions of the pyrolysis simulation are set as follows: the temperature of the system is increased from 1000K to 2000K, the temperature increasing rate is 8K/ps, the total pyrolysis time is 125ps, and the time step is 0.25 ps. After the pyrolysis simulation is finished, molecular fragments of the Adler lignin pyrolysis product are obtained (the molecular fragments of the Adler lignin pyrolysis product are stored in a dump file).
Pyrolysis simulation conditions (pyrolysis simulation temperature, pyrolysis time and time step) in the pyrolysis simulation process can be set according to actual simulation requirements, the preferred setting range of the pyrolysis simulation temperature is 300-3000K, the preferred setting range of the pyrolysis time is 50-250 ps, and the preferred setting range of the time step is 0.1-0.25 ps; during actual pyrolysis simulation, appropriate pyrolysis simulation temperature, pyrolysis time and time step length can be selected according to the requirement of constructing a lignin coke molecular model; for example, a molecular structure of a coke product obtained after pyrolysis of lignin at 1500K needs to be constructed, the system temperature can be set to 1500K in the pyrolysis simulation process, the pyrolysis time is 125ps, and the time step is 0.25 ps; moreover, the heating rate in the pyrolysis simulation process can also be set according to the actual simulation requirements.
Analysis of molecular fragments of Adler lignin pyrolysis productsWherein, the molecular fragment with the carbon atom number of 0-4 in the pyrolysis product is pyrolysis gas, the product with the carbon atom number of 5-40 in the pyrolysis product is pyrolysis tar, and the product with the carbon atom number of more than 40 in the pyrolysis product is coke. Fig. 4 is a graph showing the content of pyrolysis gas, tar and coke in the lignin pyrolysis product as a function of temperature, and it can be seen from fig. 4 that the lignin starts to be pyrolyzed at 1300K simulated temperature, the gas and tar products are gradually separated out, and the coke content is gradually reduced. FIG. 5 is a graph showing the changes of H/C ratio and O/C ratio with temperature in the lignin coke, and it can be seen from FIG. 5 that the H/C ratio and the O/C ratio with temperature in the pyrolysis process2O、CO、CO2Iso-oxygenated products and CH4And the separation of hydrocarbon products, the H/C and O/C ratio of lignin coke is increased along with the increase of the temperature.
(5) According to the actual analysis requirements, extracting the molecular fragments of coke in the pyrolysis products of Adler lignin at different pyrolysis temperatures. Taking pyrolysis temperatures of 1800K and 2000K as examples, molecular fragments of coke in Adler lignin pyrolysis products at pyrolysis temperatures of 1800K and 2000K are extracted, respectively, fig. 6 is a schematic diagram of a molecular fragment structure part of coke in lignin pyrolysis products at 1800K, and fig. 7 is a schematic diagram of a molecular fragment structure part of coke in lignin pyrolysis products at 2000K.
Construction of a lignin coke molecular model at a temperature of 1800K: constructing a box with periodic boundaries by using an Amorphous Cell module in the Material Studio software, then placing the extracted coke molecular fragments at a temperature of 1800K into the box, setting the initial density of the box to 0.1g/cm3To avoid overlapping of atoms; adopting a Discover module in Material Studio software to optimize the energy of the box in which the coke molecular fragments are put, so that the system energy is in the lowest state; then, NPT (maintaining the atomic number, pressure and temperature constant) calculation optimization is carried out on the box by using a Forcite module in the Material Studio software until the density of the box system is constant, and a 3D molecular structure model of coke generated by pyrolysis of Adler lignin at 1800K is obtained (as shown in FIG. 8). The parameters of the NPT optimization are set as follows: the pressure was set at 0.1 MPa, the temperature at 298K, the calculation time set at 1000 ps, and the time step size was 1 ps.
Construction of a lignin coke molecular model at a temperature of 2000K: constructing a box with periodic boundaries by using Amorphous Cell module in the Material Studio software, then placing the extracted coke molecular fragments at 2000K temperature into the box, setting the initial density of the box to 0.1g/cm3To avoid overlapping of atoms; adopting a Discover module in Material Studio software to optimize the energy of the box in which the coke molecular fragments are put, so that the system energy is in the lowest state; then, NPT (maintaining the atomic number, pressure and temperature constant) calculation optimization is carried out on the box by using a Forcite module in the Material Studio software until the density of the box system is constant, and a 3D molecular structure model of coke generated by pyrolysis of Adler lignin at 2000K is obtained (as shown in figure 9). The parameters of the NPT optimization are set as follows: the pressure was set at 0.1 MPa, the temperature at 298K, the calculation time set at 1000 ps, and the time step size was 1 ps.
In the above embodiments, the method for constructing the molecular model of biomass coke is described by taking Adler lignin as an example, but the method for constructing the molecular model of biomass coke is not limited to Adler lignin, and the method for constructing the molecular model of biomass coke is also applicable to other biomasses (such as other types of lignin, other celluloses, hemicelluloses, and the like). When coke molecular models of other biomasses are constructed, a molecular structure model of the corresponding biomass is constructed by adopting Material Studio (MS) software in the step (1), and the pyrolysis simulation conditions in the step (4) are adjusted according to actual needs.
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 (9)
1. A method for constructing a molecular model of biomass coke is characterized by comprising the following steps:
(1) performing energy and geometric optimization on a biomass molecular structure model constructed by simulation software to obtain an optimized biomass molecular structure model;
(2) adopting an Amorphous Cell module in the Material Studio software to construct a box, and putting the optimized biomass molecular structure model into the box;
(3) performing energy optimization and NPT (neutral Studio) optimization on the box processed in the step (2) by adopting Material Studio software until the density of a box system is constant to obtain a biomass 3D molecular structure model;
(4) performing molecular dynamics pyrolysis simulation based on a reverse stress field on the biomass 3D molecular structure model obtained in the step (3) by using molecular dynamics simulation software Lammps to obtain a molecular fragment of a biomass pyrolysis product;
(5) extracting molecular fragments of coke in the biomass pyrolysis product, constructing a box by using an Amorphous Cell module in Material Studio software, putting the extracted molecular fragments of the coke product into the box, and then performing energy optimization and NPT (non-uniform pressure test) optimization on the box until the density of the box system is constant to obtain a 3D molecular structure model of the biomass coke.
2. The method of claim 1, wherein the molecular dynamics pyrolysis simulation in step (4) is performed with a CHON reaction force field parameter and the molecular dynamics pyrolysis simulation is performed under NVT ensemble.
3. The method of claim 1, wherein the simulation conditions for the molecular dynamics pyrolysis simulation in step (4) are: the pyrolysis simulation temperature is 300-3000K, the pyrolysis time is 50-250 ps, and the time step is 0.1-0.25 ps.
4. The method of claim 1, wherein in step (3) and step (5), the parameters for NPT optimization are set as: the pressure was set at 0.1 MPa, the temperature at 298K, the calculation time set at 1000 ps, and the time step size was 1 ps.
5. The method of claim 4, wherein in the step (3) and the step (5), the energy optimization is performed by using a Discover module in the Material Studio software, and the NPT optimization is performed by using a Forcite module in the Material Studio software.
6. The method according to any one of claims 1 to 5, wherein the number of the biomass molecular structure models in the cartridge in the step (2) is 5 to 50.
7. The method of claim 6, wherein the initial density of the box in step (2) does not exceed 0.3 g/cm3。
8. The method of claim 7, wherein the coke is a molecular fragment of greater than 40 carbon atoms in the pyrolysis product.
9. The method of claim 1, wherein the biomass is any one of lignin, cellulose, and hemicellulose.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2020114294364 | 2020-12-09 | ||
| CN202011429436 | 2020-12-09 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112365933A true CN112365933A (en) | 2021-02-12 |
Family
ID=74534618
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011553489.7A Pending CN112365933A (en) | 2020-12-09 | 2020-12-24 | Method for constructing molecular model of biomass coke |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112365933A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113358686A (en) * | 2021-06-07 | 2021-09-07 | 广西大学 | Method for analyzing pyrolysis reaction path of palm oil or vegetable insulating oil through molecular simulation and application of method to DGA thermal fault diagnosis of transformer oil |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180032704A1 (en) * | 2015-02-19 | 2018-02-01 | Kabushiki Kaisha Toyota Chuo Kenkyusho | Reaction mechanism generation method and reaction mechanism generation device |
| CN110767267A (en) * | 2019-09-30 | 2020-02-07 | 华中科技大学 | Python-based method for processing ReaxFF force field calculation result data |
| CN111863150A (en) * | 2020-08-27 | 2020-10-30 | 青岛科技大学 | Reaction molecular dynamics-based biomass delignification method |
| US20200365236A1 (en) * | 2019-05-16 | 2020-11-19 | Robert Bosch Gmbh | Graph neural network force field computational algorithms for molecular dynamics computer simulations |
| CN112034064A (en) * | 2020-09-04 | 2020-12-04 | 东南大学 | Asphalt aging mechanism analysis method based on molecular dynamics simulation |
-
2020
- 2020-12-24 CN CN202011553489.7A patent/CN112365933A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180032704A1 (en) * | 2015-02-19 | 2018-02-01 | Kabushiki Kaisha Toyota Chuo Kenkyusho | Reaction mechanism generation method and reaction mechanism generation device |
| US20200365236A1 (en) * | 2019-05-16 | 2020-11-19 | Robert Bosch Gmbh | Graph neural network force field computational algorithms for molecular dynamics computer simulations |
| CN110767267A (en) * | 2019-09-30 | 2020-02-07 | 华中科技大学 | Python-based method for processing ReaxFF force field calculation result data |
| CN111863150A (en) * | 2020-08-27 | 2020-10-30 | 青岛科技大学 | Reaction molecular dynamics-based biomass delignification method |
| CN112034064A (en) * | 2020-09-04 | 2020-12-04 | 东南大学 | Asphalt aging mechanism analysis method based on molecular dynamics simulation |
Non-Patent Citations (4)
| Title |
|---|
| 懒散的鱼与消失的猫: "Materials Studio工具模块介绍", 《CSDN》 * |
| 洪迪昆等: "钙催化苯酚反应的分子动力学模拟", 《化工学报》 * |
| 郁有祝等: "聚酰亚胺高温热解反应的分子动力学模拟", 《四川师范大学学报》 * |
| 郭玉华等: "双酚A型苯并噁嗪树脂热解的ReaxFF反应动力学模拟", 《河南师范大学学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113358686A (en) * | 2021-06-07 | 2021-09-07 | 广西大学 | Method for analyzing pyrolysis reaction path of palm oil or vegetable insulating oil through molecular simulation and application of method to DGA thermal fault diagnosis of transformer oil |
| CN113358686B (en) * | 2021-06-07 | 2024-05-14 | 广西大学 | Method for molecular simulation analysis of pyrolysis reaction path of palm oil or plant insulating oil and method for DGA thermal fault diagnosis of transformer oil |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Mehmood et al. | Helianthus tuberosus as a promising feedstock for bioenergy and chemicals appraised through pyrolysis, kinetics, and TG-FTIR-MS based study | |
| Mian et al. | Kinetic study of biomass pellet pyrolysis by using distributed activation energy model and Coats Redfern methods and their comparison | |
| Chen et al. | Effect of torrefaction pretreatment and catalytic pyrolysis on the pyrolysis poly-generation of pine wood | |
| Zheng et al. | Initial reaction mechanisms of cellulose pyrolysis revealed by ReaxFF molecular dynamics | |
| Zou et al. | Combustion behaviors of pileus and stipe parts of Lentinus edodes using thermogravimetric-mass spectrometry and Fourier transform infrared spectroscopy analyses: Thermal conversion, kinetic, thermodynamic, gas emission and optimization analyses | |
| Lv et al. | Characteristics of corn stalk hemicellulose pyrolysis in a tubular reactor | |
| Liang et al. | Hydrothermal carbonization of forest waste into solid fuel: Mechanism and combustion behavior | |
| Wang et al. | Enhancing biogas production of corn stover by fast pyrolysis pretreatment | |
| Bai et al. | Effects of combined pretreatment with rod-milled and torrefaction on physicochemical and fuel characteristics of wheat straw | |
| Ayala-Cortés et al. | Exploring the influence of solar pyrolysis operation parameters on characteristics of carbon materials | |
| Yin et al. | Effect of char structure evolution during pyrolysis on combustion characteristics and kinetics of waste biomass | |
| Diao et al. | Synergistic effect of physicochemical properties and reaction temperature on gasification reactivity of walnut shell chars | |
| Hu et al. | Influence of interactions between biomass components on physicochemical characteristics of char | |
| Huang et al. | Pyrolytic characteristics of biomass acid hydrolysis residue rich in lignin | |
| Zhuang et al. | Upgrading biochar by co-pyrolysis of heavy bio-oil and apricot shell using response surface methodology | |
| Kang et al. | Enhanced fuel characteristics and physical chemistry of microwave hydrochar for sustainable fuel pellet production via co-densification | |
| WO2018227842A1 (en) | Catalyst used for producing aromatic-rich biofuel, and method for preparing same | |
| Athira et al. | Thermochemical conversion of sugarcane bagasse: composition, reaction kinetics, and characterisation of by-products | |
| Gan et al. | Co-pyrolysis of municipal solid waste and rice husk gasification tar to prepare biochar: An optimization study using response surface methodology | |
| Shen et al. | Rapid pyrolysis of pulverized biomass at a high temperature: the effect of particle size on char yield, retentions of alkali and alkaline earth metallic species, and char particle shape | |
| Cao et al. | Investigation of the relevance between thermal degradation behavior and physicochemical property of cellulose under different torrefaction severities | |
| CN112365933A (en) | Method for constructing molecular model of biomass coke | |
| Xu et al. | Combustion behaviors and characteristic parameters determination of sassafras wood under different heating conditions | |
| Ibrahim | Bio-energy production from rice straw: A review | |
| Tu et al. | A new index for hydrochar based on fixed carbon content to predict its structural properties and thermal behavior |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210212 |
|
| RJ01 | Rejection of invention patent application after publication |