CN105205316B - One kind prediction SiCO negative material performance simulation methods - Google Patents
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Abstract
SiCO negative material performance simulation methods are predicted the invention discloses one kind, it is characterised in that carried out in the steps below：1. low carbon content SiCO structure initial models are set up based on atom Shift Method；2. the high-carbon content SiCO structure initial models containing free carbon are set up based on simulated annealing；3. determine that the atomic ratio of SiCO and lithium carries out embedding lithium；4. chemical property calculating is carried out to the SiCO structures after embedding lithium.The present invention has good Accuracy and high efficiency, can effectively improve the development efficiency of new electrode materials.
Description
Technical field
The present invention relates to a kind of analogy method for SiCO materials, particularly a kind of prediction SiCO negative material performance moulds
Plan method.
Background technology
Lithium ion has the series of advantages such as energy height, service life length, lightweight, small volume because of it, causes international electricity
Chi Jie and the common concern and attention of scientific and technological circle.Lithium battery applications mainly include portable unit energy-storage battery and new-energy automobile
Use electrokinetic cell.The former mainly includes 3C Product, i.e. computer, communication and consumption electronic product.Global cellphone subscriber's quantity with
15%-25% or so speed is in increase, and 50%-70% battery all uses the development of the notebook computer of lithium battery, all will
Make the demand of lithium ion battery increases year by year.As countries in the world are more paid attention in strategy to energy security and environmental protection,
Electric automobile the characteristics of its energy-conservation, low emission as the new industry of strategic type to be greatly developed by various countries.Develop new energy vapour
Car, is the strategic demand for breaking away from the dependence to fossil energies such as oil, preserving the ecological environment and ensureing national energy security.
Electrode is the core component of lithium ion battery, and electrode material be determine lithium battery integrated performance it is good and bad it is crucial because
Element, exploitation high performance electrode material of new generation is always the important directions of lithium battery research.The research of lithium cell cathode material is just
Develop towards height ratio capacity, high charge-discharge efficiencies, high circulation performance and relatively low cost direction, it is low temperature pyrogenation carbon, carbon-based compound
The weight that material, Sn-polymetallic orefield, the transition metal nitride of lithium and nanometer new material will be paid close attention to and studied as people
Point.Because carbon as lithium ion battery negative material has the advantages that capacity is high, safety and stability, some current C-base composte materials
Research in terms of for lithium ion battery negative material oneself through making some progress, especially silico-carbo based composites,
The advantage of carbon-based material and silica-base material is combined in a way, shows good development prospect.Recent research indicate that, it is high
The SiCO ceramics of phosphorus content have good chemical property and relatively low cost.But because the research to lithium ion battery is one
It is individual to be related to the multi-disciplinary intersection item such as chemistry, physics, material, the energy and electronics, many, electricity is also there is in development
Exploitation of the development of pole material analysis method to new electrode materials is most important.Because traditional electrode material design method is deposited
In limitations such as cycle length, expense height, it is extremely difficult to seek optimal design by substantial amounts of testing research.
The content of the invention
It is an object of the present invention to provide a kind of prediction SiCO negative material performance simulation methods.The present invention has good
Accuracy and high efficiency, the development efficiency of new electrode materials can be effectively improved.
Technical scheme：One kind prediction SiCO negative material performance simulation methods, it is characterised in that by following steps
It is rapid to carry out：
1. low carbon content SiCO structure initial models are set up based on atom Shift Method；
2. the high-carbon content SiCO structure initial models containing free carbon are set up based on simulated annealing；
3. determine that the atomic ratio of SiCO and lithium carries out embedding lithium；
4. chemical property calculating is carried out to the SiCO structures after embedding lithium.
It is described to set up low carbon content SiCO structure initial models in foregoing prediction SiCO negative material performance simulation methods
Method be to carry out in the steps below：a、SiO2The foundation of crystal model；B, the Si based on replacement criterion8CaO16-aModel is given birth to
Into；C, SiCO crystal Supercell foundation.
In foregoing prediction SiCO negative material performance simulation methods, the high-carbon content SiCO of the foundation containing free carbon
The method of structure initial model is, using Si5CO8As the glassy state proportioning without free carbon, the content of increase carbon, which is obtained, to be had certainly
By the SiCO structures of carbon, Si is expressed as5CxO8；By S=x/7.5-0.1, x≤16 are realized and the characteristic size of free carbon are carried out
Calculate.
In foregoing prediction SiCO negative material performance simulation methods, the simulated annealing is to carry out in the steps below：
(a) operation 20ps NVE simulations, are heated to 6000K by system by atomic velocity demarcation, make it have enough
Energy jumps out local optimum；
(b) operation 500ps NVE simulations, 1000K is cooled to by atomic velocity demarcation by system；Then by system temperature
Degree is stable in 1000K, operation NVE simulation relaxation 500ps；
(c) operation 2000ps NVE simulations, 300K is cooled to by atomic velocity demarcation by system；Then by system temperature
Degree is stable in 300K, operation NVE simulation relaxation 500ps；
Wherein, temperature-rise period dynamics step-length is 1fs, and temperature-fall period dynamics step-length is 0.1fs.
In foregoing prediction SiCO negative material performance simulation methods, the step 3. in embedding lithium method be by by lithium
Atom is added to method in the space of SiCO crystal to simulation SiCO crystal process of intercalation one by one.
In foregoing prediction SiCO negative material performance simulation methods, embedding lithium method is to carry out in the steps below：
1. regular grid space is used, the position of lithium atom and the minimum range of other atoms are inserted in definition<2.6
2. structure after embedding lithium is optimized according to geometry optimization condition, and calculates gross energy；
3. above step is repeated, until embedding lithium quantity reaches set provisioning request.
In foregoing prediction SiCO negative material performance simulation methods, the step 4. in chemical property calculate include
The embedding lithium SiCO lithium diffusion coefficient calculating side for forming energy computational methods, embedding lithium SiCO voltage computational methods and SiCO electrodes
Method.
In foregoing prediction SiCO negative material performance simulation methods, described embedding lithium SiCO formation energy computational methods
It is：The formation of compound can be defined as：
Wherein EdefectiveRepresent by the energy of the former molecular deficient compounds of n x, μxRepresent x atoms in complete chemical combination
Chemical potential；
The formation of material can be after embedding lithium：
ΔfE=Etotal(LixSiCmOn)-(x Etotal(Li)+Etotal(SiCmOn))
Wherein Etotal(LixSiCmOn) value be geometry optimization after LixSiCmOnSilicon atom in structural energy value divided by the structure
Number, Etotal(Li) value is the energy of single Li atoms in body-centered cubic, Etotal(SiCmOn) value be geometry optimization after SiCmOnKnot
Silicon atom number in structure energy value divided by the structure；M=a/8, n=(16-a)/8, x are the corresponding lithium of a silicon atom in system
The number of atom.
In foregoing prediction SiCO negative material performance simulation methods, the voltage computational methods of the embedding lithium SiCO are：It is embedding
Enter reaction with below equation to describe：
The Si of xLi ten8CaO16-a→LixSiCmOn
M=a/8 in formula, n=(16-a)/8；According to Lix1SiCmOn、Lix2SiCmOnElectrode material is calculated with the gross energy of lithium
Expect that voltage is：
In foregoing prediction SiCO negative material performance simulation methods, the lithium diffusion coefficient computational methods of the SiCO electrodes
It is to carry out in the steps below：1. electrode material model and electrode electrolyte interface model are carried out energy-optimised；
2. operation 300ps NVT simulations obtain system initial configuration, and wherein temperature is 10K, time step 1fs, using Nos
é-Hoover heating baths carry out temperature control to system；
System temperature is risen to 500K by 3. operation 200ps NVT simulations, preceding 100ps, and rear 100ps keeps system temperature to exist
500K；Then system temperature is down to 300K by operation 500ps NVT simulations, makes system full relaxation；
4. diffusion coefficient of the lithium ion under 400K, 600K, 800K and 1000K different temperatures is calculated, diffusion coefficient can be by
Einstein relations are obtained,
Wherein, riIt is ion i position vector, N is the sum of diffusion ion.
Compared with prior art, the present invention to micro-nano structure, mechanical property, embedding lithium characteristic and lithium diffusion by carrying out
Calculate, draw structure-chemical property relation, also by the accuracy of the present invention with the contrast verification of experimental result and efficient
Property.Method proposed by the invention provides a kind of important analysis means and work for the exploitation of high-performance lithium battery electrode material
Tool.The present invention has good Accuracy and high efficiency, can effectively improve the development efficiency of new electrode materials.
Brief description of the drawings
Fig. 1 is to replace generation SiCO structure charts by carbon atom；
Fig. 2 is process of intercalation and embedding lithium position view；
Fig. 3 is SiCO structure factor schematic diagram；
Fig. 4 is different carbon content SiCO Young's modulus schematic diagram；
Fig. 5 is to calculate obtained embedding lithium SiC1/4O1/7Charging and discharging curve and with embedding lithium silicon and embedding lithium SiC1.99O0.85Discharge and recharge
Real contrast schematic diagram.
Embodiment
The present invention is further illustrated with reference to the accompanying drawings and examples, but be not intended as to the present invention limit according to
According to.
Embodiment.One kind prediction SiCO negative material performance simulation methods, it is characterised in that carry out in the steps below：
1. low carbon content SiCO structure initial models are set up based on atom Shift Method；
2. the high-carbon content SiCO structure initial models containing free carbon are set up based on simulated annealing；
3. determine that the atomic ratio of SiCO and lithium carries out embedding lithium；
4. chemical property calculating is carried out to the SiCO structures after embedding lithium.
The method for setting up low carbon content SiCO structure initial models is to carry out in the steps below：a、SiO2Crystal mould
The foundation of type, be specially：β-cristobalite (SiO2- cristobalite) belong to cubic crystal structure, space group is P213, each
Structure cell has 24 atoms, wherein 8 Si atoms, 16 oxygen atoms, cell parameter is a=b=c=7.16α=β=γ=
90 °, Si forms tetrahedral structure with O atom；
B, the Si based on replacement criterion8CaO16-aModel is generated, specifically, setting up SiO based on above parameter2Crystal structure,
According to the requirement of different SiCO carbon contents, the oxygen atom of different crystal layer is substituted for carbon atom.For example, to SiO2Crystal structure
Carry out 2,4, the replacement of 8 carbon atoms, Si can be set up respectively4CO7, Si2CO3With tri- kinds of SiCO crystal models of SiCO, such as Fig. 1 institutes
Show；
In c, SiCO crystal Supercell foundation, initial three kinds of SiCO crystal models established above in each structure cell
Atom number be 24, in order to improve the accuracy of calculating, structure one 3 × 3 × 3 by construction unit of the structure cell
Supercell, is used as embedding lithium tial crystalline structure.
The method of the high-carbon content SiCO structure initial model of the foundation containing free carbon is, using Si5CO8It is used as nothing
The glassy state of free carbon is matched (i.e. by 20mol%SiC and 80mol%SiO2Composition), the content of increase carbon, which is obtained, to be had freely
The SiCO structures of carbon, are expressed as Si5CxO8, wherein x >=1；By S=x/7.5-0.1, the feature to free carbon is realized in x≤16
Size is calculated.The simulated annealing is to carry out in the steps below：
(a) operation 20ps NVE (constant system population, volume, energy) simulations, are demarcated system by atomic velocity
6000K is heated to, enough energy is made it have and jumps out local optimum；
(b) operation 500ps NVE simulations, 1000K is cooled to by atomic velocity demarcation by system；Then by system temperature
Degree is stable in 1000K, operation NVE simulation relaxation 500ps；
(c) operation 2000ps NVE simulations, 300K is cooled to by atomic velocity demarcation by system；Then by system temperature
Degree is stable in 300K, operation NVE simulation relaxation 500ps；
Wherein, temperature-rise period dynamics step-length is 1fs, and temperature-fall period dynamics step-length is 0.1fs.Run dynamics simulation
During, every parameters such as 1ps storage primary systems temperature, energy and stress, used for later data analysis.
Can also be specially to the optimization methods of SiCO structures：
A carries out geometry optimization to four kinds of crystal structures according to the minimum principle of gross energy according to following condition；
The kinetic energy that blocks of plane wave base group is 350eV；
It is 5 × 5 × 5 k point iteration from the brief Brillouin zone of process is in harmony；
Convergence precision is 1.5 × 10-5eV·atom-1；
B has been carried out after geometry optimization, and Dynamics Optimization is carried out by following condition；
1ps NVE (constant-energy, constant-volume is carried out under system temperature 800K
Ensemble) simulate, system atomic is jumped out local optimum；
System temperature is dropped into 300K by 800K within the 2ps times, and operation NVE simulates 300 steps at 300k.
The step 3. in embedding lithium method be method by being added to lithium atom one by one in the space of SiCO crystal
To simulation SiCO crystal process of intercalation.Embedding lithium method is specifically carried out in the steps below：
1. regular grid space is used, the position of lithium atom and the minimum range of other atoms are inserted in definition<2.6
2. structure after embedding lithium is optimized according to geometry optimization condition, and calculates gross energy；
3. above step is repeated, until embedding lithium quantity reaches set provisioning request, as shown in Figure 2.
The step 4. in chemical property calculate include embedding lithium SiCO formed energy computational methods, embedding lithium SiCO electricity
Press computational methods and the lithium diffusion coefficient computational methods of SiCO electrodes.
Described embedding lithium SiCO formation energy computational methods are：The formation of compound can be defined as：
Wherein EdefectiveRepresent by the energy of the former molecular deficient compounds of n x, μxRepresent x atoms in complete chemical combination
Chemical potential；
The formation of material can be after embedding lithium：
ΔfE=Etotal(LixSiCmOn)-(x Etotal(Li)+Etotal(SiCmOn))
Wherein Etotal(LixSiCmOn) value be geometry optimization after LixSiCmOnSilicon atom in structural energy value divided by the structure
Number, Etotal(Li) value is the energy of single Li atoms in body-centered cubic, Etotal(SiCmOn) value be geometry optimization after SiCmOnKnot
Silicon atom number in structure energy value divided by the structure；M=a/8, n=(16-a)/8, x are the corresponding lithium of a silicon atom in system
The number of atom.
The voltage computational methods of the embedding lithium SiCO are：Insertion reaction is described with below equation：
xLi+Si8CaO16-a→LixSiCmOn
M=a/8 in formula, n=(16-a)/8；According to Lix1SiCmOn、Lix2SiCmOnElectrode material is calculated with the gross energy of lithium
Expect that voltage is：
The lithium diffusion coefficient computational methods of the SiCO electrodes are to carry out in the steps below：1. to electrode material model and electricity
Pole-electrolyte interface model carries out energy-optimised；
2. operation 300ps NVT (i.e. system population, volume and temperature keep constant) simulation obtains system and initially tied
Structure, wherein temperature are 10K, time step 1fs, and temperature control is carried out to system using Nos é-Hoover heating baths；
System temperature is risen to 500K by 3. operation 200ps NVT simulations, preceding 100ps, and rear 100ps keeps system temperature to exist
500K；Then system temperature is down to 300K by operation 500ps NVT simulations, makes system full relaxation；
4. diffusion coefficient of the lithium ion under 400K, 600K, 800K and 1000K different temperatures is calculated, diffusion coefficient can be by
Einstein relations are obtained,
Wherein, riIt is ion i position vector, N is the sum of diffusion ion.
In order to verify the performance simulation method of the invention proposed, respectively to Si4CO7, Si2CO3With tri- kinds of structures of SiCO
Geometry optimization and molecular dynamics optimization are carried out, SiCO structure factor, Young's modulus, generation energy, charging and discharging curve has been obtained
Deng structure and performance parameters.
1. structure factor
Calculate the structure factor that obtains the embedding lithium structures of SiCO as shown in figure 3, peak and intensity with experimental result very
It is consistent.
2. mechanical property
The Young's modulus for obtaining different carbon content SiCO is calculated in 109-116GPa scopes, with existing various proportioning SiCO poplars
The 97.9-110GPa experiment value scopes of family name's modulus are consistent very much, and its minute differences is main to be made by the factor such as proportioning and fault in material
Into.
3. generate energy
Table 1 lists the generation energy for calculating and obtaining the different embedding lithium SiCO of carbon content, and as a result showing the increase of carbon content can make
Embedding lithium SiCO has smaller generation energy, so as to embody more excellent storage lithium performance；And SiCO storage lithium ability is integrally superior to
SiO2.Conclusions are also consistent with experiment conclusion [1,2].
The embedding lithium SiCO of the different carbon contents of table 1. generation energy
4. charging and discharging curve
Fig. 5 show the embedding lithium SiC for calculating and obtaining1/4O1/7Charging and discharging curve and with embedding lithium silicon and embedding lithium SiC1.99O0.85Fill
The contrast of discharge test [1], result of calculation is more coincide with experimental result, while SiCO embodies the embedding lithium electricity higher than Si
Pressure, this is also consistent with experiment conclusion.
Claims (9)
1. one kind prediction SiCO negative material performance simulation methods, it is characterised in that carry out in the steps below：
1. low carbon content SiCO structure initial models are set up based on atom Shift Method；
2. the high-carbon content SiCO structure initial models containing free carbon are set up based on simulated annealing；
3. determine that the atomic ratio of SiCO and lithium carries out embedding lithium；
4. chemical property calculating is carried out to the SiCO structures after embedding lithium；
The method of the high-carbon content SiCO structure initial model of the foundation containing free carbon is, using Si5CO8As without freedom
The glassy state proportioning of carbon, the content of increase carbon obtains the SiCO structures with free carbon, is expressed as Si5CxO8；Pass through S=x/
7.5-0.1, x≤16, realize and the characteristic size of free carbon is calculated.
2. prediction SiCO negative material performance simulation methods according to claim 1, it is characterised in that described to set up low-carbon
The method of content SiCO structure initial models is to carry out in the steps below：a、SiO2The foundation of crystal model；It is b, accurate based on replacing
Si then8CaO16-aModel is generated；C, SiCO crystal Supercell foundation.
3. prediction SiCO negative material performance simulation methods according to claim 1, it is characterised in that the simulated annealing
Method is to carry out in the steps below：
(a) operation 20ps NVE simulations, are heated to 6000K by system by atomic velocity demarcation, make it have enough energy
Jump out local optimum；
(b) operation 500ps NVE simulations, 1000K is cooled to by atomic velocity demarcation by system；Then it is system temperature is steady
It is scheduled on 1000K, operation NVE simulation relaxation 500ps；
(c) operation 2000ps NVE simulations, 300K is cooled to by atomic velocity demarcation by system；Then it is system temperature is steady
It is scheduled on 300K, operation NVE simulation relaxation 500ps；
Wherein, temperature-rise period dynamics step-length is 1fs, and temperature-fall period dynamics step-length is 0.1fs.
4. prediction SiCO negative material performance simulation methods according to claim 1, it is characterised in that the step 3. in
Embedding lithium method be by the method being added to lithium atom one by one in the space of SiCO crystal to simulation the embedding lithium mistake of SiCO crystal
Journey.
5. prediction SiCO negative material performance simulation methods according to claim 4, it is characterised in that embedding lithium method be by
Following step is carried out：
1. regular grid space is used, position and other atoms of lithium atom are inserted in definition
2. structure after embedding lithium is optimized according to geometry optimization condition, and calculates gross energy；
3. above step is repeated, until embedding lithium quantity reaches set provisioning request.
6. prediction SiCO negative material performance simulation methods according to claim 1, it is characterised in that the step 4. in
Chemical property calculate include embedding lithium SiCO form energy computational methods, embedding lithium SiCO voltage computational methods and SiCO electrodes
Lithium diffusion coefficient computational methods.
7. prediction SiCO negative material performance simulation methods according to claim 6, it is characterised in that described embedding lithium
SiCO formation energy computational methods are：The formation of compound can be defined as：
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The formation of material can be after embedding lithium：
ΔfE=Ftotal(LixSiCmOn)-(xEtotal(Li)+Etotal(SiCmOn)
Wherein Etotal(LixSiCmOn) value be geometry optimization after LixSiCmOnSilicon atom number in structural energy value divided by the structure,
Etotal(Li) value is the energy of single Li atoms in body-centered cubic, Etotal(SiCmOn) value be geometry optimization after SiCmOnStructure energy
Silicon atom number in value divided by the structure；M=a/8, n=(16-a)/8, x are the corresponding lithium atom of a silicon atom in system
Number.
8. prediction SiCO negative material performance simulation methods according to claim 6, it is characterised in that the embedding lithium SiCO
Voltage computational methods be：Insertion reaction is described with below equation：
xLi+Si8CaO16-a→LixSiCmOn
M=a/8 in formula, n=(16-a)/8；According to Lix1SiCmOn、Lix2SiCmOnElectrode material electricity is calculated with the gross energy of lithium
Press and be：
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9. prediction SiCO negative material performance simulation methods according to claim 6, it is characterised in that the SiCO electrodes
Lithium diffusion coefficient computational methods be to carry out in the steps below：
1. electrode material model and electrode electrolyte interface model are carried out energy-optimised；
2. operation 300ps NVT simulations obtain system initial configuration, and wherein temperature is 10K, time step 1fs, using Nos é-
Hoover heating baths carry out temperature control to system；
System temperature is risen to 500K by 3. operation 200ps NVT simulations, preceding 100ps, and rear 100ps keeps system temperature in 500K；
Then system temperature is down to 300K by operation 500ps NVT simulations, makes system full relaxation；
4. diffusion coefficient of the lithium ion under 400K, 600K, 800K and 1000K different temperatures is calculated, diffusion coefficient can be by
Einstein relations are obtained,
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Wherein, riIt is ion i position vector, N is the sum of diffusion ion.
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| CN103979967A (en) * | 2014-05-28 | 2014-08-13 | 厦门大学 | Method for preparing micron-scale worm-like SiCO ceramics |
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| CN101047244A (en) * | 2006-03-27 | 2007-10-03 | 信越化学工业株式会社 | SiCO-Li composite, making method, and non-aqueous electrolyte secondary cell negative electrode material |
| CN103022434A (en) * | 2012-11-23 | 2013-04-03 | 中国科学院宁波材料技术与工程研究所 | Precursor ceramic-carbon nano tube composite material and preparation method thereof |
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