[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

CN107942256A - Battery performance Forecasting Methodology using phosphorus alkene as negative material - Google Patents

Battery performance Forecasting Methodology using phosphorus alkene as negative material Download PDF

Info

Publication number
CN107942256A
CN107942256A CN201711131930.0A CN201711131930A CN107942256A CN 107942256 A CN107942256 A CN 107942256A CN 201711131930 A CN201711131930 A CN 201711131930A CN 107942256 A CN107942256 A CN 107942256A
Authority
CN
China
Prior art keywords
alkali metal
metal atom
negative material
battery
battery performance
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.)
Granted
Application number
CN201711131930.0A
Other languages
Chinese (zh)
Other versions
CN107942256B (en
Inventor
谭心
刘尧尧
李璇
方桂花
郝雪清
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Inner Mongolia University of Science and Technology
Original Assignee
Inner Mongolia University of Science and Technology
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Inner Mongolia University of Science and Technology filed Critical Inner Mongolia University of Science and Technology
Priority to CN201711131930.0A priority Critical patent/CN107942256B/en
Publication of CN107942256A publication Critical patent/CN107942256A/en
Application granted granted Critical
Publication of CN107942256B publication Critical patent/CN107942256B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367Software therefor, e.g. for battery testing using modelling or look-up tables

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Battery Electrode And Active Subsutance (AREA)

Abstract

The present invention relates to a kind of battery performance Forecasting Methodology using phosphorus alkene as negative material.Comprise the following steps:Model construction:Determine the structure and relevant stable structured data of cell negative electrode material, determine different adsorption potentials of the alkali metal atom on negative material surface;Theoretical calculation:Carry out absorption of the alkali metal atom on negative material surface and calculate and migrate calculating;Interpretation of result:Calculated according to absorption as a result, obtaining absorption height, adsorption energy and the system deformation of different adsorption potentials;According to migration result of calculation, the migration activation energy of each transition state and the migration activation energy of each migration path are obtained;Battery performance is predicted:According to adsorption energy of the alkali metal atom on negative material surface, and with alkali metal atom itself combination can compared with, obtain the data of safety of battery;The deformation of system after alkali metal atom is adsorbed according to negative material, obtains the cycle life data of battery;According to migration activation energy of the alkali metal atom on negative material surface, the power intensity data of battery is obtained.

Description

Battery performance Forecasting Methodology using phosphorus alkene as negative material
Technical field
The present invention relates to battery technology field, and in particular to a kind of battery performance prediction side using phosphorus alkene as negative material Method.
Background technology
The eighties in 19th century, lithium ion battery are developed, and commercialization puts goods on the market use, due to lithium ion battery A series of excellent performances, have captured rapidly energy storage device field.At present, lithium ion battery is that modern energy storage field mainly uses Energy storage device.However, reserves of the elemental lithium in nature are less, skewness and expensive, these prevent lithium Ion battery develops to maximization direction.In addition, the negative material of commercial Li-ion battery is graphite mostly, had based on graphite The storage lithium ability (372mAh/g) of limit, further improving for lithium ion battery specific capacity are restricted.
In addition, with the unprecedented development of battery system and extremely wide application, the performance prediction problem of battery system It is one of the problem of battery system is the most key.Battery performance prediction be one compared with abstract concept, be relative to new battery, really A fixed numerical value, battery performance prediction is by SOF (State Of Function functional statuses) this parameter evaluation battery Performance it is fine or not.It is many to influence factor and the evaluation criterion of battery performance, and has certain relevance between these factors, because This is, it is necessary to the method for correctly definition evaluation and detection battery performance.The method of traditional detection battery performance is to pass through battery Pulse charge-discharge test, obtains the cycle-index of battery and the relation in service life, then according to the used discharge and recharge number of battery, Infer the cycle-index of remaining battery, though this method can predict the performance of battery to a certain extent, due to not being with electricity Main Basiss of the key parameter in pond as prediction battery performance, and predict that process steps are cumbersome, and prediction result error is larger.
The factor of influence battery performance is various, therefore it provides method that is a kind of simple and rapidly predicting battery performance It is significant.
The content of the invention
For in the prior art the defects of, the present invention is intended to provide a kind of battery performance using phosphorus alkene as negative material is pre- Survey method.Compared with prior art, Forecasting Methodology provided by the invention has the following advantages:(1) the method for the present invention calculate it is quick, As a result it is accurate, experimental result not only can be verified and parse, but also exploitation and research offer that can be to battery be directly theoretical Instruct.(2) substantial amounts of experiment material and instrument is not required in this method, has the advantages that low cost, high efficiency, free of contamination, saving Human and material resources and financial resources, can promote the fast development of battery.(3) present invention can predict material as alkali metal electricity The battery performance of pond anode, theoretical direction practice, promotes the exploitation of novel battery negative material.
For this reason, the present invention provides following technical solution:
In a first aspect, the present invention provides a kind of Forecasting Methodology of battery performance, comprise the following steps:Build battery cathode material Expect structural model, obtain the rock-steady structure data of negative material;Negative material absorption alkali metal atom model is built afterwards, is carried out Absorption of the alkali metal atom on negative material surface calculates and migration calculates, and then predicts battery performance.
In the further embodiment of the present invention, Forecasting Methodology specifically includes following step:Model construction:Determine battery The structure and relevant stable structured data of negative material, determine different adsorption potentials of the alkali metal atom on negative material surface;Reason By calculating:Carry out absorption of the alkali metal atom on negative material surface and calculate and migrate calculating;Interpretation of result:Calculated according to absorption As a result, obtain absorption height, adsorption energy and the system deformation of different adsorption potentials;According to migration result of calculation, each transition is obtained The migration activation energy of the migration activation energy of state and each migration path;Battery performance is predicted:According to alkali metal atom in negative material The adsorption energy on surface, and with alkali metal atom itself combination can compared with, obtain the data of safety of battery;Inhaled according to negative material The deformation of system after attached alkali metal atom, obtains the cycle life data of battery;According to alkali metal atom on negative material surface Migration activation energy, obtain the power intensity data of battery.
In the further embodiment of the present invention, alkali metal atom includes one in lithium atom, sodium atom and potassium atom Kind is a variety of.
In the further embodiment of the present invention, negative material selects phosphorus alkene.
In the further embodiment of the present invention, cellular crystal structure that phosphorus alkene is made of phosphorus atoms, by upper and lower What two half storey phosphorus atoms formed, upper and lower interlamellar spacing isChoose lattice constant Periodically In the case of boundary condition, calculate the substrate used and surpass born of the same parents for 3 × 3 phosphorus alkene, include 36 P atoms, define x-axis and be located at y-axis In phosphorus alkene plane, z-axis takes perpendicular to phosphorus alkene surface, z-axis directionVacuum layer so that former with alkali metal between ignoring phosphorus alkene Active force between son.
In the further embodiment of the present invention, alkali metal atom existing high symmetrical position bag in phosphorus alkene adsorption Include:One or more in heart position, bridge location and top position.
In the further embodiment of the present invention, in theoretical calculation, the interaction to ion core and valence electron uses Sew and add plane-wave method to describe, exchange correlation functional uses the PBE methods in local density functional, and parameter setting is plane wave It can be 350eV to block, and the energy convergence of ion step is to produce k points in Monkhorst-Pack methods, and k points are set during calculating For 5 × 5 × 1, iterative process energy convergence 1 × 10-4eV;Migration calculates and uses NEB algorithms.
In the further embodiment of the present invention, model construction uses MS softwares, and software for calculation uses VASP softwares.
Above-mentioned technical proposal provided by the invention has the following advantages:
(1) applicant has found by numerous studies:Compared with prior art, Forecasting Methodology provided by the invention has following excellent Point:(1) the method for the present invention calculating is quick, result is accurate, not only can verify and parse experimental result, but also can be to battery Exploitation provide direct theoretical direction with research.(2) substantial amounts of experiment material and instrument is not required in this method, have it is low into Sheet, high efficiency, free of contamination advantage, save human and material resources and financial resources, can promote the fast development of battery.(3) this hair The bright battery performance that can predict material as alkali metal battery anode, theoretical direction practice, promotes novel battery anode material The exploitation of material.
(2) phosphorus alkene formed as a kind of orderly phosphorus atoms for being stripped out from black phosphorus, monoatomic layer, have direct band gap Two-dimensional semiconductor material, there is cellular crystal;It is combined into, is had very high by upper and lower two half storey phosphorus atoms Carrier concentration;When the thickness of phosphorus alkene is in 10nm, carrier mobility can reach 1000cm2·v-1·s-1;Therefore, phosphorus alkene is A kind of very potential electrode material.
The additional aspect and advantage of the present invention will be set forth in part in the description, and will partly become from the following description Obtain substantially, or recognized by the practice of the present invention.
Brief description of the drawings
Fig. 1 is the battery performance Forecasting Methodology flow chart using phosphorus alkene as negative material in the embodiment of the present invention;
Fig. 2 is absorption schematic diagram of the alkali metal atom in the embodiment of the present invention on phosphorus alkene surface;
Fig. 3 is migration path figure of the alkali metal atom in the embodiment of the present invention on phosphorus alkene surface;
Fig. 4 is adsorption energy (Δ E) and absorption of the alkali metal atom in phosphorus alkene surface diverse location in the embodiment of the present invention Ratio (the Δ E/E of energy can be combined with alkali metal atom itselfc);
Fig. 5 is that the alkali metal atom in the embodiment of the present invention is adsorbed in phosphorus alkene surface P-P bond distance's largest deformation;
Fig. 6 is the alkali metal atom in the embodiment of the present invention in migration path and migration energy of the phosphorus alkene surface along H → B → H Measure curve.
Embodiment
The embodiment of technical solution of the present invention will be described in detail below.Following embodiments are only used for clearer Explanation technical scheme, therefore be only used as example, and be not intended to limit the protection scope of the present invention and limit the scope of the invention.
Experimental method in following embodiments, is conventional method unless otherwise specified.
Test material used, is to be commercially available from conventional reagent shop unless otherwise specified in following embodiments.
Quantitative test in following embodiments, is respectively provided with three repeated experiments, and data are the average value of three repeated experiments Or mean+SD.
The present invention provides a kind of Forecasting Methodology of battery performance, comprises the following steps:
Model construction:Determine the structure and relevant stable structured data of cell negative electrode material, determine alkali metal atom negative The different adsorption potentials of pole material surface.Wherein, alkali metal atom includes one kind or more in lithium atom, sodium atom and potassium atom Kind;Negative material selects phosphorus alkene, the cellular crystal structure that phosphorus alkene is made of phosphorus atoms, by upper and lower two half storey phosphorus atoms Composition, upper and lower interlamellar spacing isChoose lattice constantIn the situation of periodic boundary condition Under, calculate the substrate used and surpass born of the same parents for 3 × 3 phosphorus alkene, include 36 P atoms, define x-axis and be located at y-axis in phosphorus alkene plane, z-axis Perpendicular to phosphorus alkene surface, z-axis direction takesVacuum layer so that the effect between ignoring phosphorus alkene between alkali metal atom Power;Alkali metal atom, there are 3 possible symmetrical positions of height, is respectively heart position (H), bridge location (B), top position in phosphorus alkene adsorption (T)。
Theoretical calculation:Carry out absorption of the alkali metal atom on negative material surface and calculate and migrate calculating.Wherein, to ion Real and valence electron interaction is using sewing plus plane-wave method describes, and exchange correlation functional is using in local density functional PBE methods, it can be 350eV that parameter setting, which is that plane wave blocks, and the energy convergence of ion step is with Monkhorst-Pack Method produces k points, and k points are arranged to 5 × 5 × 1 during calculating, iterative process energy convergence 1 × 10-4eV;Migration, which calculates, to be used NEB algorithms
Interpretation of result:Calculated according to absorption as a result, obtaining absorption height, adsorption energy and the system deformation of different adsorption potentials; According to migration result of calculation, the migration activation energy of each transition state and the migration activation energy of each migration path are obtained.
Battery performance is predicted:According to adsorption energy of the alkali metal atom on negative material surface, and with alkali metal atom itself With reference to that can compare, the data of safety of battery is obtained;The deformation of system after alkali metal atom is adsorbed according to negative material, obtains electricity The cycle life data in pond;According to migration activation energy of the alkali metal atom on negative material surface, the power density of battery is obtained Data.In other words, by calculating absorption, migration of the alkali metal atom on phosphorus alkene surface, battery performance is predicted;Especially by The calculating of one property principle, security, cycle life length and the power density size of battery are disclosed from microcosmic angle.
Preferably, model construction uses MS softwares, and software for calculation uses VASP softwares.
Illustrated with reference to embodiment:
Embodiment
The present invention provides a kind of Forecasting Methodology using phosphorus alkene as the battery performance of negative material, specific steps such as Fig. 1 institutes Show:
(1) model construction
Using MS software Materials Visualizer module construction phosphorus alkene models, and by VESTA softwares by structure Data file class switchs to * vasp file formats.Wherein, the cellular crystal structure that phosphorus alkene is made of phosphorus atoms, be by it is upper, Lower two half storey phosphorus atoms composition, upper and lower interlamellar spacing isChoose lattice constantIn the cycle Property boundary condition in the case of, calculating the substrate used as 3 × 3 phosphorus alkene surpasses born of the same parents, includes 36 P atoms, defines x-axis and y-axis position In in phosphorus alkene plane, z-axis takes perpendicular to phosphorus alkene surface, z-axis directionVacuum layer, it is former with alkali metal between phosphorus alkene to ignore Active force between son.
(2) calculating simulation
A. tetra- input files of INCAR, KPOINTS, POTCAR, POSCAR are set, using VASP by the knot in step 1 Structure optimizes, and obtains the rock-steady structure data file (CONTCAR) of crystal.Calculating lattice constant used and consistent accreditation Experiment value error in 2%, interaction to ion core and valence electron using sewing plus plane-wave method (PAW) describes, Exchange correlation functional uses the PBE methods in local density functional (LDA), and it can be 350eV that plane wave, which blocks, the energy that ion walks Convergence is to produce k points in Monkhorst-Pack methods, and k points are arranged to 5 × 5 × 1 during calculating, the convergence of iterative process energy Standard 1 × 10-4eV。
B. by CONTCAR renamed as POSCAR, determine alkali metal atom (lithium atom, sodium atom, potassium atom) in phosphorus alkene The absorption position on surface, as shown in Figure 2;There are 3 possible symmetrical positions of height, difference in phosphorus alkene adsorption for alkali metal atom For heart position (H), bridge location (B), top position (T);Then absorption calculating is carried out, after obtaining stable structure, parameter is analyzed, is wrapped Include adsorption energy Δ E, P-P bond distance's largest deformation.
C. migratory route is selected, migration calculating (setting IMAGES=04, SPRING=-5), choosing are carried out using NEB algorithms The H-B-H migration paths shown in Fig. 3 are selected, analysis result, calculates migration activation energy.
(3) result treatment and analysis
A. by rock-steady structure after VESTA software display optimizations, the absorption of comparative analysis alkali metal atom on phosphorus alkene surface and Caused P-P bond distance's largest deformation;
B. the adsorption energy and adsorption energy for calculating alkali metal atom in phosphorus alkene surface diverse location are tied with alkali metal atom itself Close the ratio of energy;
C. different alkali metal atoms are drawn in the migration path on phosphorus alkene surface and migrate energy curve, calculate alkali metal original Son activates energy in phosphorus alkene surface migration.
(4) battery performance is predicted
The comparative analysis integrated to absorption migration of the alkali metal on phosphorus alkene surface, specifies the change of microstructure to electricity The influence of pond performance, show that phosphorus alkene has higher security and cycle life, larger work(as kalium ion battery negative material Rate, theoretical method is provided for the research and development of heavy-duty battery.
During calculating simulation is carried out, the adsorption gauge of atom is carried out in its different high symmetrical position respectively to phosphorus alkene surface Calculate, it can be respectively 1.63eV, 1.113eV, 0.934eV that inspection information, which obtains lithium, sodium, the potassium atom combination of itself, alkali metal atom If the combination energy between less than two alkali metal atoms of adsorption energy on negative material surface, shows in adsorption process, alkali gold Belong to atom to be easier to be combined with itself, form dendrite in negative material surface aggregation, electrolyte membrance may be punctured, caused Short circuit, battery security are low.Fig. 4 be alkali metal atom phosphorus alkene surface H positions, B, the adsorption energy of T (potassium atom at T not Absorption), data can be seen that adsorption energy of the alkali metal atom on phosphorus alkene surface is more than the combination energy of alkali metal atom itself in figure, Illustrate that alkali metal atom is not easily formed cluster during phosphorus alkene adsorption, the wherein adsorption energy of potassium atom and alkali metal is former The ratio that son itself combines energy is maximum, therefore higher as the kalium ion battery security of anode using phosphorus alkene.
The intensity of variation of geometry is smaller before and after negative material absorption alkali metal, illustrates that negative material was used in battery The constant ability of holding original structure is stronger in journey, i.e. the high rate performance of battery is higher, and cycle life is longer.It can be seen by Fig. 5 It is Li-phosphorus alkene system to go out alkali metal atom in the structure change degree that phosphorus alkene surface same position is adsorbed>Na- phosphorus alkene systems> K- phosphorus alkene systems, in the case of using phosphorus alkene as negative material, the cycle life of battery is lithium ion battery from low to high<Sodium Ion battery<Kalium ion battery.
Diffusion energy barrier of the alkali metal atom on negative material surface is smaller, and it is easier in negative material diffusion into the surface to illustrate, That is the power density of battery is high, beneficial to battery fast charging and discharging.It will be appreciated from fig. 6 that when Li, Na, K atom on phosphorus alkene surface along H → B During Path Migration, required migration activation energy very little, be respectively 0.090eV, 0.045eV, 0.029eV, illustrate each configuration it Between can be spontaneous carry out configuration differentiation.Li → Na → K, migration activation energy of the adatom on phosphorus alkene surface are gradually reduced, say It is bright that alkali metal atom is more and more easily spread in phosphorus alkene surface migration with the increase of atomic number, i.e., cell power density from Low to high is lithium ion battery<Sodium-ion battery<Kalium ion battery.
Battery performance Forecasting Methodology provided by the invention using phosphorus alkene as negative material has the following advantages:(1) this hair Bright method calculates that quick, result is accurate, not only can verify and parse experimental result, and can be to battery exploitation and research Direct theoretical direction is provided.(2) substantial amounts of experiment material and instrument is not required in this method, has low cost, high efficiency, nothing The advantages of pollution, save human and material resources and financial resources, can promote the fast development of battery.(3) present invention can predict Battery performance of the material as alkali metal battery anode, theoretical direction practice, promotes the exploitation of novel battery negative material.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show The description of example " or " some examples " etc. means specific features, structure, material or the spy for combining the embodiment or example description Point is contained at least one embodiment of the present invention or example.In the present specification, schematic expression of the above terms is not It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office Combined in an appropriate manner in one or more embodiments or example.In addition, without conflicting with each other, the skill of this area Art personnel can be tied the different embodiments or example described in this specification and different embodiments or exemplary feature Close and combine.
Although the embodiment of the present invention has been shown and described above, it is to be understood that above-described embodiment is example Property, it is impossible to limitation of the present invention is interpreted as, those of ordinary skill in the art within the scope of the invention can be to above-mentioned Embodiment is changed, changes, replacing and modification.

Claims (8)

1. a kind of Forecasting Methodology of battery performance, it is characterised in that comprise the following steps:
Cell negative electrode material structural model is built, obtains the rock-steady structure data of negative material;Negative material absorption is built afterwards Alkali metal atom model, carries out absorption of the alkali metal atom on negative material surface and calculates and migrate calculating, and then predicts battery Performance.
2. the Forecasting Methodology of battery performance according to claim 1, it is characterised in that specifically include following step:
Model construction:Determine the structure and relevant stable structured data of cell negative electrode material, determine alkali metal atom in anode material Expect the different adsorption potentials on surface;
Theoretical calculation:Carry out absorption of the alkali metal atom on negative material surface and calculate and migrate calculating;
Interpretation of result:Calculated according to absorption as a result, obtaining absorption height, adsorption energy and the system deformation of different adsorption potentials;According to Result of calculation is migrated, obtains the migration activation energy of each transition state and the migration activation energy of each migration path;
Battery performance is predicted:Combined according to adsorption energy of the alkali metal atom on negative material surface, and with alkali metal atom itself It can compare, obtain the data of safety of battery;The deformation of system after alkali metal atom is adsorbed according to negative material, obtains battery Cycle life data;According to migration activation energy of the alkali metal atom on negative material surface, the power intensity data of battery is obtained.
3. the Forecasting Methodology of battery performance according to claim 2, it is characterised in that:
The alkali metal atom includes the one or more in lithium atom, sodium atom and potassium atom.
4. the Forecasting Methodology of battery performance according to claim 2, it is characterised in that:
The negative material selects phosphorus alkene.
5. the Forecasting Methodology of battery performance according to claim 4, it is characterised in that:
The cellular crystal structure that the phosphorus alkene is made of phosphorus atoms, is made of, levels upper and lower two half storey phosphorus atoms Spacing isChoose lattice constant
In the case of periodic boundary condition, calculate the substrate used and surpass born of the same parents for 3 × 3 phosphorus alkene, include 36 P atoms, define x Axis is located in phosphorus alkene plane with y-axis, and z-axis takes perpendicular to phosphorus alkene surface, z-axis directionVacuum layer so that ignore phosphorus alkene it Between active force between alkali metal atom.
6. the Forecasting Methodology of battery performance according to claim 5, it is characterised in that:
The alkali metal atom existing high symmetrical position in the phosphorus alkene adsorption includes:In heart position, bridge location and top position It is one or more.
7. the Forecasting Methodology of battery performance according to claim 2, it is characterised in that:
In the theoretical calculation, interaction to ion core and valence electron is exchanged and closed using sewing plus plane-wave method describes Join functional and use PBE methods in local density functional, it can be 350eV that parameter setting, which is that plane wave blocks, the energy that ion walks Convergence is to produce k points in Monkhorst-Pack methods, and k points are arranged to 5 × 5 × 1 during calculating, the convergence of iterative process energy Standard 1 × 10-4eV;Migration calculates and uses NEB algorithms.
8. according to the Forecasting Methodology of claim 1~7 any one of them battery performance, it is characterised in that:
The model construction uses MS softwares, and the software for calculation uses VASP softwares.
CN201711131930.0A 2017-11-15 2017-11-15 Battery performance prediction method using phosphorus alkene as negative electrode material Active CN107942256B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711131930.0A CN107942256B (en) 2017-11-15 2017-11-15 Battery performance prediction method using phosphorus alkene as negative electrode material

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711131930.0A CN107942256B (en) 2017-11-15 2017-11-15 Battery performance prediction method using phosphorus alkene as negative electrode material

Publications (2)

Publication Number Publication Date
CN107942256A true CN107942256A (en) 2018-04-20
CN107942256B CN107942256B (en) 2021-01-05

Family

ID=61932340

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711131930.0A Active CN107942256B (en) 2017-11-15 2017-11-15 Battery performance prediction method using phosphorus alkene as negative electrode material

Country Status (1)

Country Link
CN (1) CN107942256B (en)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108549790A (en) * 2018-04-28 2018-09-18 云南电网有限责任公司电力科学研究院 A kind of method and system for calculating product concentration after gas molecule is pyrolyzed
CN109002682A (en) * 2018-05-28 2018-12-14 安徽科技学院 A kind of analysis AlH3In the method for phosphorus alkene surface-stable storage
CN110472361A (en) * 2019-08-22 2019-11-19 成都市银隆新能源产业技术研究有限公司 Boron alkene/vulcanization molybdenum composite material configuration analogy method
CN113628691A (en) * 2020-05-08 2021-11-09 上海交通大学 Machine learning method, system and equipment
CN114692417A (en) * 2022-04-07 2022-07-01 仰恩大学 Method for constructing electrode material of variable electric dipole moment LI-S battery with Janus TMD structure
CN116381512A (en) * 2023-06-06 2023-07-04 宁德时代新能源科技股份有限公司 Battery voltage calculation method, battery voltage calculation device, electronic equipment and readable storage medium

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1180449A (en) * 1995-02-08 1998-04-29 彼得·文兹 Electro-adsorption reaction cell
TW200409398A (en) * 2002-11-27 2004-06-01 Univ Nat Cheng Kung Cathode material for solid oxide fuel cell
JP2008159519A (en) * 2006-12-26 2008-07-10 Nippon Steel Corp Fuel cell
CN104778330A (en) * 2015-04-24 2015-07-15 中国石油大学(华东) Theoretical method for screening high-efficiency perovskite sensitizer
CN104866660A (en) * 2015-05-14 2015-08-26 西北师范大学 Method for predicting absorption property of MgO nano-cluster surface vapor state deposition transition metal Au and Pt in absorbing CO molecules
CN105789607A (en) * 2016-05-10 2016-07-20 内蒙古科技大学 Preparation method of lithium titanate anode material doped with rare earth
CN105990460A (en) * 2016-08-04 2016-10-05 戚明海 Solar photovoltaic module with phosphorus-doped layers and manufacturing method thereof
CN106021732A (en) * 2016-05-20 2016-10-12 东南大学 Method for designing organic metal surface battery material
CN107133449A (en) * 2017-04-12 2017-09-05 武汉理工大学 A kind of N, P element doping vario-property VO2The Forecasting Methodology of material phase transformation temperature
CN107210431A (en) * 2015-02-06 2017-09-26 陈忠伟 Method for preparing anode of lithium ion battery
CN107271910A (en) * 2017-06-16 2017-10-20 长沙新材料产业研究院有限公司 A kind of method for predicting the remaining cycle-index of lithium manganate battery

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1180449A (en) * 1995-02-08 1998-04-29 彼得·文兹 Electro-adsorption reaction cell
TW200409398A (en) * 2002-11-27 2004-06-01 Univ Nat Cheng Kung Cathode material for solid oxide fuel cell
JP2008159519A (en) * 2006-12-26 2008-07-10 Nippon Steel Corp Fuel cell
CN107210431A (en) * 2015-02-06 2017-09-26 陈忠伟 Method for preparing anode of lithium ion battery
CN104778330A (en) * 2015-04-24 2015-07-15 中国石油大学(华东) Theoretical method for screening high-efficiency perovskite sensitizer
CN104866660A (en) * 2015-05-14 2015-08-26 西北师范大学 Method for predicting absorption property of MgO nano-cluster surface vapor state deposition transition metal Au and Pt in absorbing CO molecules
CN105789607A (en) * 2016-05-10 2016-07-20 内蒙古科技大学 Preparation method of lithium titanate anode material doped with rare earth
CN106021732A (en) * 2016-05-20 2016-10-12 东南大学 Method for designing organic metal surface battery material
CN105990460A (en) * 2016-08-04 2016-10-05 戚明海 Solar photovoltaic module with phosphorus-doped layers and manufacturing method thereof
CN107133449A (en) * 2017-04-12 2017-09-05 武汉理工大学 A kind of N, P element doping vario-property VO2The Forecasting Methodology of material phase transformation temperature
CN107271910A (en) * 2017-06-16 2017-10-20 长沙新材料产业研究院有限公司 A kind of method for predicting the remaining cycle-index of lithium manganate battery

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
GEN-CAI GUO 等: ""First-Principles Study of Phosphorene and Graphene Heterostructure as Anode Materials for Rechargeable Li Batteries"", 《PHYSICAL CHEMISTRY LETTERS》 *
VADYM V. KULISH 等: ""Phosphorene as an anode material for Na-ion batteries: a first-principles study"", 《PHYSICAL CHEMISTRY CHEMICAL PHYSICS》 *
XIAO LIU 等: ""A first-principles study of sodium adsorption and", 《PHYSICAL CHEMISTRY CHEMICAL PHYSICS》 *
谭心 等: ""碱金属在石墨烯表面吸附、迁移行为的第一性原理研究"", 《原子与分子物理学报》 *

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108549790A (en) * 2018-04-28 2018-09-18 云南电网有限责任公司电力科学研究院 A kind of method and system for calculating product concentration after gas molecule is pyrolyzed
CN109002682A (en) * 2018-05-28 2018-12-14 安徽科技学院 A kind of analysis AlH3In the method for phosphorus alkene surface-stable storage
CN109002682B (en) * 2018-05-28 2021-08-10 安徽科技学院 AlH analysis3Method for stable storage on surface of phospholene
CN110472361A (en) * 2019-08-22 2019-11-19 成都市银隆新能源产业技术研究有限公司 Boron alkene/vulcanization molybdenum composite material configuration analogy method
CN113628691A (en) * 2020-05-08 2021-11-09 上海交通大学 Machine learning method, system and equipment
CN113628691B (en) * 2020-05-08 2024-07-12 上海交通大学 Machine learning method, system and equipment
CN114692417A (en) * 2022-04-07 2022-07-01 仰恩大学 Method for constructing electrode material of variable electric dipole moment LI-S battery with Janus TMD structure
CN114692417B (en) * 2022-04-07 2024-04-23 仰恩大学 LI-S battery electrode material construction method with Janus TMD structure variable electric dipole moment
CN116381512A (en) * 2023-06-06 2023-07-04 宁德时代新能源科技股份有限公司 Battery voltage calculation method, battery voltage calculation device, electronic equipment and readable storage medium
CN116381512B (en) * 2023-06-06 2023-10-27 宁德时代新能源科技股份有限公司 Battery voltage calculation method, battery voltage calculation device, electronic equipment and readable storage medium

Also Published As

Publication number Publication date
CN107942256B (en) 2021-01-05

Similar Documents

Publication Publication Date Title
CN107942256A (en) Battery performance Forecasting Methodology using phosphorus alkene as negative material
Chen et al. Efficient fast-charging of lithium-ion batteries enabled by laser-patterned three-dimensional graphite anode architectures
Wang et al. Gas sensing technology for the detection and early warning of battery thermal runaway: a review
Zhang et al. In situ optical spectroscopy characterization for optimal design of lithium–sulfur batteries
Jeon Wettability in electrodes and its impact on the performance of lithium-ion batteries
Liu et al. Bridging multiscale characterization technologies and digital modeling to evaluate lithium battery full lifecycle
Röder et al. Multi-scale simulation of heterogeneous surface film growth mechanisms in lithium-ion batteries
He et al. Sodiation kinetics of metal oxide conversion electrodes: a comparative study with lithiation
Berhaut et al. Multiscale multiphase lithiation and delithiation mechanisms in a composite electrode unraveled by simultaneous operando small-angle and wide-angle X-ray scattering
Yuan et al. Review on mechanisms and continuum models of multi-phase transport phenomena in porous structures of non-aqueous Li-Air batteries
Gavilán-Arriazu et al. Kinetic Monte Carlo simulations applied to Li-ion and post Li-ion batteries: a key link in the multi-scale chain
Li et al. Understanding the gap between academic research and industrial requirements in rechargeable zinc‐ion batteries
Li et al. Electrochemical performance investigation of LiFePO4/C0. 15-x (x= 0.05, 0.1, 0.15 CNTs) electrodes at various calcination temperatures: Experimental and Intelligent Modelling approach
JP5299523B2 (en) Cation determination method
Vorauer et al. Impact of solid-electrolyte interphase reformation on capacity loss in silicon-based lithium-ion batteries
Brieske et al. Modeling the volumetric expansion of the lithium-sulfur battery considering charge and discharge profiles
Liu et al. Mesoscale physicochemical interactions in lithium–sulfur batteries: progress and perspective
Xiong et al. Improvement of electrochemical homogeneity for lithium-ion batteries enabled by a conjoined-electrode structure
Lian et al. Modeling lithium plating onset on porous graphite electrodes under fast charging with hierarchical multiphase porous electrode theory
Ma et al. Study on lithium plating caused by inconsistent electrode decay rate during aging of traction batteries
Qiu et al. Multiscale computations and artificial intelligent models of electrochemical performance in Li‐ion battery materials
JP7295050B2 (en) Lithium-ion secondary battery control device and lithium-ion secondary battery control method
Johannes et al. Electronic structure and properties of Li-insertion materials: Li 2 Ru O 3 and Ru O 2
Song et al. Correlating Solid Electrolyte Interphase Composition with Dendrite‐Free and Long Life‐Span Lithium Metal Batteries via Advanced Characterizations and Simulations
Madabattula et al. Degradation diagnostics for Li4Ti5O12-based lithium ion capacitors: Insights from a physics-based model

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
GR01 Patent grant
GR01 Patent grant