Lubricant selection device, friction coefficient estimation device, lubricant selection method, and manufacturing method and program for exterior material for power storage device

Abstract

The present invention stably obtains the friction coefficient between a resin layer and a mold layer with a lubricant layer interposed therebetween with a small amount of calculation. This lubricant selection apparatus comprises a lubricant information input unit that receives input of information about a plurality of lubricant candidates, an energy calculation unit that calculates the interaction energy between a lubricant layer formed by each of the plurality of lubricant candidates and a resin layer, a friction coefficient estimation unit that estimates the friction coefficient between the resin layer and a mold layer with the lubricant layer interposed therebetween on the basis of the interaction energy, and a lubricant selection unit that selects a lubricant from the plurality of lubricant candidates on the basis of the friction coefficient.

Description

[Technical field]

[0001] The present disclosure relates to a lubricant selection device, a friction coefficient estimation device, a lubricant selection method, a manufacturing method for an exterior material for an electricity storage device, and a program. [Background technology]

[0002] In recent years, laminates consisting of a heat-resistant resin layer (substrate layer) / adhesive layer / metal foil layer / adhesive layer / thermoplastic resin layer (sealant layer) have been used as exterior materials for electricity storage devices. By forming such laminates into a three-dimensional shape such as a substantially rectangular parallelepiped shape by stretch molding or deep drawing, a storage space for storing the electricity storage device body is secured.

[0003] A configuration has been proposed in which a matte varnish layer (protective layer) is provided on the outside of a substrate layer to improve protection and moldability (slipperiness) of the exterior material. For example, Patent Document 1 discloses an exterior material for an electricity storage device, which includes a substrate layer made of a heat-resistant resin, a sealant layer as an inner layer, and a metal foil layer disposed between the substrate layer and the sealant layer, and in which a protective layer is laminated on the surface of the substrate layer opposite to the metal foil layer. In the exterior material for an electricity storage device disclosed in Patent Document 1, a lubricant is added to the substrate layer, and the protective layer is formed by the bleed-out lubricant. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2022-20772 Summary of the Invention [Problem to be solved by the invention]

[0005] In the exterior material disclosed in Patent Document 1, the friction coefficient between the base layer and the die via the protective layer affects the moldability. However, there are many substances that can be candidates for the lubricant, and it takes a huge amount of time to select the optimal lubricant through experiments, etc. It is possible to calculate the friction coefficient of the lubricant by simulations such as molecular dynamics, but since friction is a complex physical phenomenon, the amount of calculation is large, and if there are a large number of substances, the amount of calculation becomes enormous. Furthermore, since the friction coefficient calculated by the molecular dynamics method changes with time, it is difficult to obtain a friction coefficient that can be compared and evaluated.

[0006] In view of the above technical problems, one aspect of the present disclosure aims to stably determine the coefficient of friction between a resin layer and a mold layer via a lubricant layer with a small amount of calculation. [Means for solving the problem]

[0007] The present disclosure has the following configuration.

[0008] [1] A lubricant information input unit configured to accept input of information regarding a plurality of lubricant candidates; an energy calculation unit configured to calculate an interaction energy between a lubricant layer formed by each of the plurality of lubricant candidates and a resin layer; a friction coefficient estimation unit configured to estimate a friction coefficient between the resin layer and the die layer via the lubricant layer based on the interaction energy; a lubricant selector configured to select a lubricant from the plurality of candidate lubricants based on the coefficient of friction; A lubricant selection device comprising:

[0009] [2] The lubricant selection device according to [1] above, The friction coefficient estimation unit is configured to estimate the friction coefficient from the interaction energy based on a predetermined regression equation. Lubricant selection device.

[0010] [3] The lubricant selection device according to [2] above, The regression equation represents a correlation between the interaction energy and the friction coefficient. Lubricant selection device.

[0011] [4] The lubricant selection device according to [3] above, The regression equation is derived using the interaction energy and the friction coefficient calculated by molecular dynamics calculation for a lubricant different from the lubricant candidate. Lubricant selection device.

[0012] [5] The lubricant selection device according to [4] above, The regression equation is -3.6×10 -5 is the regression coefficient, Lubricant selection device.

[0013] [6] The lubricant selection device according to any one of [1] to [5] above, The lubricant is used as a lubricant to be added to the resin layer in an exterior material for an electrical storage device, the exterior material including the resin layer, a sealant layer, and a metal foil layer disposed between the resin layer and the sealant layer. Lubricant selection device.

[0014] [7] A lubricant information input unit configured to accept input of information regarding a lubricant; an energy calculation unit configured to calculate an interaction energy between a lubricant layer formed by the lubricant and a resin layer; a friction coefficient estimation unit configured to estimate a friction coefficient between the resin layer and the die layer via the lubricant layer based on the interaction energy; A friction coefficient estimation device comprising:

[0015] [8] The computer: receiving input of information regarding a plurality of potential lubricants; A step of calculating an interaction energy between a lubricant layer formed by each of the plurality of lubricant candidates and a resin layer; a step of estimating a coefficient of friction between the resin layer and the mold layer via the lubricant layer based on the interaction energy; selecting a lubricant from the plurality of candidate lubricants based on the coefficient of friction; A lubricant selection method to be performed.

[0016] [9] A method for producing an exterior material for an electricity storage device, using a lubricant selected by the lubricant selection method described in [8] above, comprising: the resin layer to which the lubricant has been added; a sealant layer; and a metal foil layer disposed between the resin layer and the sealant layer.

[0017]

[10] To the computer: receiving input of information regarding a plurality of potential lubricants; A step of calculating an interaction energy between a lubricant layer formed by each of the plurality of lubricant candidates and a resin layer; a step of estimating a coefficient of friction between the resin layer and the mold layer via the lubricant layer based on the interaction energy; selecting a lubricant from the plurality of candidate lubricants based on the coefficient of friction; A program for executing the above. Effect of the Invention

[0018] According to one aspect of the present disclosure, the friction coefficient between a resin layer and a mold layer via a lubricant layer can be stably determined with a small amount of calculation. [Brief description of the drawings]

[0019] [Figure 1] FIG. 1 is a cross-sectional view showing an example of an exterior material for an electricity storage device. [Diagram 2] FIG. 2 is a block diagram showing an example of the overall configuration of the design support system. [Diagram 3] FIG. 3 is a block diagram showing an example of a hardware configuration of a computer. [Figure 4] FIG. 4 is a block diagram illustrating an example of a functional configuration of the design support system. [Diagram 5] FIG. 5 is a flowchart showing an example of the analysis process. [Figure 6] FIG. 6 is a flowchart showing an example of the selection process. [Figure 7] FIG. 7 is a block diagram showing an example of a functional configuration of a friction coefficient estimation device. [Figure 8] FIG. 8 is a schematic diagram showing an example of a resin layer model. [Figure 9] FIG. 9 is a schematic diagram showing an example of a mold layer model. [Figure 10] Fig. 10(A) is a schematic diagram showing an example of a relaxation simulation of a friction layer model. Fig. 10(B) is a schematic diagram showing an example of a relaxation simulation of a friction layer model. Fig. 10(C) is a schematic diagram showing an example of a relaxation simulation of a friction layer model. Fig. 10(D) is a schematic diagram showing an example of a relaxation simulation of a friction layer model. [Figure 11] FIG. 11 is a diagram showing an example of the calculation results for known lubricants. [Figure 12] Fig. 12(A) is a schematic diagram showing an example of a relaxation simulation of a lubricated surface model. Fig. 12(B) is a schematic diagram showing an example of a relaxation simulation of a lubricated surface model. Fig. 12(C) is a schematic diagram showing an example of a relaxation simulation of a lubricated surface model. Fig. 12(D) is a schematic diagram showing an example of a relaxation simulation of a lubricated surface model. [Figure 13] FIG. 13 is a diagram showing an example of the calculation results of the lubricant candidates. [Figure 14A] FIG. 14A is a graph showing an example of experimental results regarding the friction coefficient of the CPP surface. [Figure 14B] FIG. 14B is a graph showing an example of experimental results regarding the friction coefficient of a PET surface. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functional configurations are denoted by the same reference numerals, and redundant description will be omitted.

[0021] [Embodiment] An embodiment of the present disclosure is a design support system for supporting the design of an exterior material for an electricity storage device. The design support system in this embodiment has a function of selecting a lubricant to be added to a base layer of the exterior material for an electricity storage device.

[0022] <Exterior materials for electricity storage devices> An exterior material for an electricity storage device to be designed in this embodiment will be described with reference to Fig. 1. Fig. 1 is a cross-sectional view showing an example of an exterior material for an electricity storage device in this embodiment.

[0023] 1, an exterior packaging material 91 for an electricity storage device in this embodiment has a structure in which a base material layer 92, a metal foil layer 93, and a sealant layer 94 are laminated together. The base material layer 92 and the metal foil layer 93 are laminated together via an adhesive layer (not shown). Similarly, the metal foil layer 93 and the sealant layer 94 are laminated together via an adhesive layer (not shown).

[0024] The base layer 92 is a member that mainly plays a role in ensuring good formability as an exterior material. The base layer 92 is made of a heat-resistant resin stretched film. An example of the heat-resistant resin is polyethylene terephthalate (PET).

[0025] The metal foil layer 93 is a member mainly serving to impart gas barrier properties that prevent the intrusion of oxygen and moisture to the electrical storage device packaging material 91. The metal foil layer 93 is made of, for example, an aluminum foil, a copper foil, a nickel foil, a stainless steel foil, or the like.

[0026] The sealant layer 94 is a member that mainly serves to impart chemical resistance and heat sealability to the electrical storage device exterior material 91 against highly corrosive electrolytes and the like. The sealant layer 94 is made of an unstretched thermoplastic resin film. One example of an unstretched thermoplastic resin film is non-oriented polypropylene (CPP; Cast Polypropylene). A lubricant mainly made of fatty acid amide is added to the sealant layer 94. The lubricant bleeds out from the sealant layer 94 to form a lubricating layer 95.

[0027] The power storage device exterior material 91 is usually stored in a roll shape. FIG. 1 shows a state in which a first turn of the power storage device exterior material 91-1 and a second turn of the power storage device exterior material 91-2 are stored in close contact with each other from the outside. As shown in FIG. 1, the lubricating layer 95-1 of the power storage device exterior material 91-1 located on the outside is stored in close contact with the base layer 92-2 of the power storage device exterior material 91-2 located on the inside. Therefore, the lubricant forming the lubricating layer 95-1 is transferred to the base layer 92-2, and a lubricating layer is formed on the outside of the base layer 92-2.

[0028] An exterior case for an electricity storage device can be obtained by processing the exterior material 91 for an electricity storage device in this embodiment into a three-dimensional shape such as a substantially rectangular parallelepiped shape by stretch forming, deep drawing, etc. The exterior material 91 for an electricity storage device in this embodiment can also be used as it is without processing.

[0029] An example of the electricity storage device in this embodiment is a lithium ion secondary battery, however, the use of the exterior material 91 for an electricity storage device in this embodiment is not limited to such use.

[0030] <Overall configuration of the design support system> The overall configuration of the design support system in this embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing an example of the overall configuration of the design support system in this embodiment.

[0031] 2, the design support system 1 in this embodiment includes a lubricant selection device 10 and a user terminal 30. The lubricant selection device 10 and the user terminal 30 are connected to each other so as to be able to communicate data with each other via a communication network N1 such as a LAN (Local Area Network) or the Internet.

[0032] The lubricant selection device 10 is an information processing device such as a personal computer, a workstation, or a server that selects a lubricant to be used in manufacturing the exterior material 91 for an electricity storage device. The lubricant selection device 10 receives lubricant information on known lubricants from the user terminal 30, and derives a regression equation for estimating the friction coefficient. The lubricant selection device 10 receives lubricant information on candidate lubricants from the user terminal 30, and selects a lubricant to be used in manufacturing the exterior material 91 for an electricity storage device based on the friction coefficient estimated for each candidate lubricant. The lubricant selection device 10 may select multiple lubricants that can be used in manufacturing the exterior material 91 for an electricity storage device.

[0033] The known lubricant is a lubricant that is known to be usable as a lubricant to be added to the base material layer 92 of the exterior material 91 for an electricity storage device. The candidate lubricant is a lubricant that is a candidate for the lubricant to be added to the base material layer 92 of the exterior material 91 for an electricity storage device.

[0034] The user terminal 30 is an information processing terminal such as a personal computer, a tablet terminal, or a smartphone operated by a user of the design support system 1. The user terminal 30 transmits lubricant information on known lubricants or candidate lubricants to the lubricant selection device 10 in response to an operation by the user. The user terminal 30 receives a lubricant selection result from the lubricant selection device 10 and outputs it to the user.

[0035] 2 is merely an example, and various system configurations are possible depending on the application and purpose. For example, the lubricant selection device 10 may be realized by a plurality of computers, or may be realized as a cloud computing service. In addition, for example, the design support system 1 may be realized by a stand-alone information processing device having the functions that at least two of the lubricant selection device 10 and the user terminal 30 should have.

[0036] <Hardware configuration of the design support system> The hardware configuration of the design support system 1 in this embodiment will be described with reference to FIG.

[0037] <Computer hardware configuration> The lubricant selection device 10 and the user terminal 30 in this embodiment are realized by, for example, a computer. Fig. 3 is a block diagram showing an example of the hardware configuration of a computer 500 in this embodiment.

[0038] 3, the computer 500 includes a CPU (Central Processing Unit) 501, a ROM (Read Only Memory) 502, a RAM (Random Access Memory) 503, a HDD (Hard Disk Drive) 504, an input device 505, a display device 506, a communication I / F (Interface) 507, and an external I / F 508. The CPU 501, the ROM 502, and the RAM 503 form a so-called computer. Each piece of hardware of the computer 500 is connected to each other via a bus line 509. The input device 505 and the display device 506 may be connected to the external I / F 508 for use.

[0039] The CPU 501 is a calculation device that reads out programs and data from a storage device such as a ROM 502 or a HDD 504 onto a RAM 503 and executes processes, thereby realizing overall control and functions of the computer 500 .

[0040] The ROM 502 is an example of a non-volatile semiconductor memory (storage device) that can retain programs and data even when the power is turned off. The ROM 502 functions as a main storage device that stores various programs and data required for the CPU 501 to execute various programs installed in the HDD 504. Specifically, the ROM 502 stores boot programs such as a Basic Input / Output System (BIOS) and an Extensible Firmware Interface (EFI) that are executed when the computer 500 is started, and data such as an Operating System (OS) setting and a network setting.

[0041] The RAM 503 is an example of a volatile semiconductor memory (storage device) in which programs and data are erased when the power is turned off. The RAM 503 is, for example, a dynamic random access memory (DRAM) or a static random access memory (SRAM). The RAM 503 provides a working area in which various programs installed in the HDD 504 are expanded when the CPU 501 executes them.

[0042] The HDD 504 is an example of a non-volatile storage device that stores programs and data. The programs and data stored in the HDD 504 include an OS, which is basic software that controls the entire computer 500, and applications that provide various functions on the OS. Note that the computer 500 may use a storage device that uses a flash memory as a storage medium (e.g., an SSD (Solid State Drive) or the like) instead of the HDD 504.

[0043] The input device 505 includes a touch panel, operation keys or buttons, a keyboard or mouse, a microphone for inputting sound data such as voice, etc., which are used by the user to input various signals.

[0044] The display device 506 is composed of a display such as a liquid crystal display or an organic EL (Electro-Luminescence) display for displaying a screen, a speaker for outputting sound data such as voice, and the like.

[0045] The communication I / F 507 is an interface that connects to a communication network and enables the computer 500 to perform data communication.

[0046] The external I / F 508 is an interface with external devices, such as a drive device 510.

[0047] The drive device 510 is a device for setting the recording medium 511. The recording medium 511 here includes media that record information optically, electrically, or magnetically, such as a CD-ROM, a flexible disk, or a magneto-optical disk. The recording medium 511 may also include semiconductor memories that record information electrically, such as a ROM or a flash memory. This allows the computer 500 to read and / or write data from and to the recording medium 511 via the external I / F 508.

[0048] The various programs to be installed in the HDD 504 are installed, for example, by setting the distributed recording medium 511 in a drive device 510 connected to the external I / F 508 and reading out the various programs recorded in the recording medium 511 by the drive device 510. Alternatively, the various programs to be installed in the HDD 504 may be installed by being downloaded from a network different from the communication network via the communication I / F 507.

[0049] <Functional configuration of the design support system> The functional configuration of the design support system in this embodiment will be described with reference to Fig. 4. Fig. 4 is a block diagram showing an example of the functional configuration of the design support system 1 in this embodiment.

[0050] <Functional configuration of the lubricant selection device> As shown in FIG. 4, the lubricant selection device 10 in this embodiment includes a lubricant information input unit 101, a model construction unit 102, a friction coefficient calculation unit 103, an energy calculation unit 104, a regression equation generation unit 105, a friction coefficient estimation unit 106, an analysis result storage unit 107, and a lubricant selection unit 108.

[0051] The lubricant information input unit 101, model construction unit 102, friction coefficient calculation unit 103, energy calculation unit 104, regression equation generation unit 105, friction coefficient estimation unit 106 and lubricant selection unit 108 are realized by processing executed by the CPU 501 of a program loaded from the HDD 504 onto the RAM 503 shown in Fig. 3. The analysis result storage unit 107 is realized by the HDD 504 shown in Fig. 3.

[0052] The lubricant information input unit 101 accepts input of lubricant information by receiving the lubricant information from the user terminal 30. In the analysis process, the lubricant information input unit 101 accepts input of a known lubricant list including lubricant information on a plurality of known lubricants. In the selection process, the lubricant information input unit 101 accepts input of a candidate lubricant list including lubricant information on a plurality of candidate lubricants.

[0053] The model construction unit 102 constructs a friction layer model that the friction coefficient calculation unit 103 uses in the friction molecular dynamics calculation, and a lubricated surface model that the energy calculation unit 104 uses in the molecular dynamics calculation.

[0054] The model construction unit 102 first constructs a structural model of a lubricant molecule (hereinafter also referred to as a "lubricant molecule model"), a structural model of the base material layer 92 (hereinafter also referred to as a "resin layer model"), and a structural model of a mold used in processing the exterior material 91 for an electricity storage device (hereinafter also referred to as a "mold layer model"). Next, the model construction unit 102 constructs a friction layer model using the lubricant molecule model, the resin layer model, and the mold layer model. In addition, the model construction unit 102 constructs a lubricated surface model using the lubricant molecule model and the resin layer model.

[0055] The friction coefficient calculation unit 103 executes a friction molecular dynamics calculation using the friction layer model constructed by the model construction unit 102. The friction coefficient calculation unit 103 calculates the friction coefficient between the resin layer and the mold layer via the lubricant layer formed of a known lubricant.

[0056] The energy calculation unit 104 executes a molecular dynamics calculation using the lubricant surface model constructed by the model construction unit 102. The energy calculation unit 104 calculates the interaction energy between the lubricant layer formed by the lubricant and the resin layer.

[0057] The regression equation generating unit 105 derives a regression equation that represents the correlation between the friction coefficient for the known lubricant calculated by the friction coefficient calculating unit 103 and the interaction energy for the known lubricant calculated by the energy calculating unit 104. The regression equation generating unit 105 stores the derived regression equation in the analysis result storage unit 107.

[0058] The friction coefficient estimation unit 106 estimates a friction coefficient for the lubricant from the interaction energy for the lubricant calculated by the energy calculation unit 104. The friction coefficient estimation unit 106 estimates a friction coefficient for the lubricant based on the regression equation derived by the regression equation generation unit 105. When the friction coefficient estimation unit 106 estimates a friction coefficient for a known lubricant, the friction coefficient estimation unit 106 stores the friction coefficient in the analysis result storage unit 107.

[0059] The analysis result storage unit 107 stores the analysis result representing the result of the analysis in the analysis process. The analysis result includes the regression equation derived by the regression equation generation unit 105 and the friction coefficient for the known lubricant estimated by the friction coefficient estimation unit 106.

[0060] The lubricant selection unit 108 selects a lubricant to be used in manufacturing the exterior material 91 for an electricity storage device from the lubricant candidate list, based on the friction coefficient of the lubricant candidate estimated by the friction coefficient estimation unit 106. The lubricant selection unit 108 selects a lubricant by comparing the friction coefficient of the lubricant candidate with the friction coefficients of known lubricants stored in the analysis result storage unit 107.

[0061] <Functional configuration of user terminal 30> As shown in FIG. 4, the user terminal 30 in this embodiment includes a lubricant information storage unit 300, a lubricant information generation unit 301, and a result display unit 302.

[0062] The lubricant information generating unit 301 and the result display unit 302 are realized by processing that is executed by the CPU 501 according to a program loaded onto the RAM 503 from the HDD 504 shown in Fig. 3. The lubricant information storage unit 300 is realized by the HDD 504 shown in Fig. 3.

[0063] Lubricant information on substances that can be used as lubricants is stored in the lubricant information storage unit 300. The substances that can be used as lubricants include known lubricants that are used in the production of the exterior material 91 for an electricity storage device and potential lubricants that are not used in the production of the exterior material 91 for an electricity storage device.

[0064] The lubricant information includes identification information for identifying a lubricant molecule. The identification information is, for example, a compound name, a structural formula, SMILES (Simplified Molecular Input Line Entry System) information, ECFP (Extended Connectivity Circular Fingerprints) information, etc. The identification information is not limited to these, and any information capable of identifying a lubricant molecule can be used.

[0065] The lubricant information generating unit 301 receives input of lubricant information in response to a user's operation. The lubricant information generating unit 301 transmits the received lubricant information to the lubricant selecting device 10.

[0066] The result display unit 302 receives the lubricant selection result from the lubricant selection device 10. The result display unit 302 outputs the received lubricant selection result to the display device 506 or the like.

[0067] <Design support system processing procedure> The processing procedure of the lubricant selection method executed by the design support system 1 in this embodiment will be described with reference to Fig. 5 and Fig. 6. The lubricant selection method in this embodiment includes an analysis process (see Fig. 5) for analyzing the relationship between the friction coefficient and the interaction energy, and a selection process (see Fig. 6) for selecting a lubricant based on the analysis result.

[0068] <Analysis processing> 5 is a flowchart showing an example of the analysis process in this embodiment. The analysis process is a process for analyzing the relationship between the interaction energy and the friction coefficient for a known lubricant and deriving a regression equation for estimating the friction coefficient.

[0069] In step S1, the lubricant information generating unit 301 of the user terminal 30 generates a known lubricant list in response to a user operation. The known lubricant list is generated by selecting lubricant information related to a known lubricant from the lubricant information stored in the lubricant information storage unit 300. Next, the lubricant information generating unit 301 transmits the generated known lubricant list to the lubricant selection device 10.

[0070] In the lubricant selection device 10, the lubricant information input unit 101 receives the list of known lubricants from the user terminal 30. Next, the lubricant information input unit 101 accepts the input of the received list of known lubricants. Then, the lubricant information input unit 101 sends the accepted list of known lubricants to the model construction unit 102.

[0071] In step S2, the model construction unit 102 of the lubricant selection device 10 receives the known lubricant list from the lubricant information input unit 101. Next, the model construction unit 102 generates lubricant molecular models of the known lubricants included in the known lubricant list using quantum chemical calculations. In addition, the model construction unit 102 generates a resin layer model corresponding to the base material layer 92 and a mold layer model corresponding to the mold using quantum chemical calculations.

[0072] (lubricant molecular model) Examples of lubricant molecules used in the electrical storage device packaging material 91 include hydrocarbon compounds having a polar group such as an amide group. The molecular weight of such lubricant molecules may be about 100 to 1,000.

[0073] Equation (1) is a general formula representing an example of a lubricant molecule calculated in this embodiment.

[0074] [ka]

[0075] In formula (1), X is an amide group. R1 and R2 are a first end portion bonded to a nitrogen atom of the amide group and a second end portion bonded to a carbon atom of the amide group, respectively. R1 and R2 have at least one of hydrogen, a hydrocarbon, a hydrocarbon containing an amide group, and a hydrocarbon containing a hydroxyl group. The structures of R1 and R2 may be the same or different.

[0076] The lubricant molecule described above is subjected to structural optimization using quantum chemical calculations to obtain a lubricant molecular model. The lubricant molecular model contains information on the molecular structure and the charge of each atom, and can therefore be used appropriately in molecular dynamics calculations.

[0077] (Resin layer model) The resin layer is made of a polymer such as non-oriented polypropylene or polyethylene terephthalate, and may be a single component or a multi-component layer.

[0078] Among the polymer chains in the resin layer as described above, one repeating unit is subjected to structural optimization using quantum chemical calculations, and the optimized repeating unit is repeatedly linked to form a model of one polymer chain in the resin layer. The model of one polymer chain in the resin layer contains information on the molecular structure and the charge of each atom, so it can be appropriately used in molecular dynamics calculations.

[0079] (Mold layer model) The mold layer is made of a single metal or an alloy of multiple metals, such as stainless steel.

[0080] The unit structure of the mold layer as described above is prepared by arranging atoms so as to form the most stable surface and allocating an appropriate charge to each atom. This unit structure is repeated in the planar direction within the range of the periodic boundary cell used in the molecular dynamics calculation to form the mold layer model. The mold layer model has information on the structure and the charge of each atom, so it can be used appropriately in the molecular dynamics calculation.

[0081] In step S3, the model construction unit 102 of the lubricant selection device 10 constructs a friction layer model corresponding to the known lubricant using the lubricant molecular model, the resin layer model, and the mold layer model of the known lubricant. The model construction unit 102 sends the generated friction layer model to the friction coefficient calculation unit 103.

[0082] The friction layer model for performing molecular dynamics calculations may be constructed such that the lubricant molecule model is arranged uniformly between the resin layer model and the mold layer model. The friction layer model is preferably constructed in a periodic boundary cell large enough to accommodate 10 to 100 lubricant molecules.

[0083] As a method for arranging the lubricant molecules in the initial state of the friction layer model, the individual lubricant molecules may be arbitrarily arranged near the resin layer model and the mold layer model so as not to overlap, or a stabilized initial arrangement may be prepared using molecular dynamics calculations or the like.

[0084] In step S4, the friction coefficient calculation unit 103 of the lubricant selection device 10 receives the friction layer model corresponding to the known lubricant from the model construction unit 102. Next, the friction coefficient calculation unit 103 performs a friction molecular dynamics calculation using the received friction layer model.

[0085] The friction coefficient calculation unit 103 performs the friction molecular dynamics calculation under the following conditions, for example. That is, in the friction molecular dynamics calculation, a shear force is applied while a pressure is applied to the mold layer. The conditions of the friction molecular dynamics calculation are not limited to the following.

[0086] Cell size: 50Å×50Å×150Å (periodic boundary cell) Tracking time: 20ns (1 step time 1ps, total number of steps 20 million) Temperature: 300K (assuming room temperature) ·Molecular force field: DREIDING force field - Coulomb interaction calculation method: Particle-Particle Particle-Mesh Ewald method Pressure on mold layer: 0.25MPa Shear speed of mold layer: 10.0mm / s

[0087] In step S5, the friction coefficient calculation unit 103 of the lubricant selection device 10 calculates the friction coefficient between the resin layer and the mold layer via the lubricant layer formed by the known lubricant based on the result of the friction molecular dynamics calculation in step S4. Next, the friction coefficient calculation unit 103 sends the calculated friction coefficient to the regression equation generation unit 105.

[0088] In the friction molecular dynamics calculation, since a shear force is applied to the mold layer while a pressure is applied to the mold layer, friction occurs in the entire friction layer model. In this embodiment, the value obtained by dividing the force in the shear direction of the mold layer by the force in the pressure direction to the mold layer among the forces acting in each direction between the molecules constituting the resin layer and the molecules constituting the mold layer is defined as the "friction coefficient".

[0089] In step S6, the model construction unit 102 of the lubricant selection device 10 constructs a lubricant surface model corresponding to the known lubricant using the lubricant molecular model and the resin layer model of the known lubricant. The model construction unit 102 sends the generated lubricant surface model to the energy calculation unit 104.

[0090] The lubricating surface model for performing molecular dynamics calculations may be constructed by arranging lubricant molecular models uniformly on a resin layer model. The lubricating surface model is preferably constructed in a periodic boundary cell large enough to accommodate 10 to 100 lubricant molecules.

[0091] As a method for arranging the lubricant molecules in the initial state of the lubricant surface model, the individual molecules may be arranged arbitrarily near the resin layer model so as not to overlap, or a stabilized initial arrangement may be prepared using molecular dynamics calculations or the like.

[0092] In step S7, the energy calculation unit 104 of the lubricant selection device 10 receives the lubricant surface model corresponding to the known lubricant from the model construction unit 102. Next, the energy calculation unit 104 performs a molecular dynamics calculation using the received lubricant surface model.

[0093] The energy calculation unit 104 performs molecular dynamics calculations under the following conditions, for example: Note that the conditions for the molecular dynamics calculations are not limited to the following.

[0094] Cell size: 50Å×50Å×150Å (periodic boundary cell) Tracking time: 2ns (1 step time 1ps, total number of steps 2 million) Temperature: 300K (assuming room temperature) ·Molecular force field: DREIDING force field - Coulomb interaction calculation method: Particle-Particle Particle-Mesh Ewald method

[0095] In step S8, the energy calculation unit 104 of the lubricant selection device 10 calculates the interaction energy between the lubricant layer formed by the known lubricant and the resin layer based on the result of the molecular dynamics calculation in step S7. Next, the energy calculation unit 104 sends the calculated interaction energy to the regression equation generation unit 105 and the friction coefficient estimation unit 106.

[0096] In the molecular dynamics calculation, when the lubricant molecules approach and are adsorbed to the resin layer, the total energy of the system becomes stable compared to the case where the lubricant molecules are not adsorbed to the resin layer. In this embodiment, the energy calculated in the stabilized state is defined as "interaction energy".

[0097] The processes from steps S2 to S8 are repeatedly performed for each known lubricant included in the known lubricant list, thereby obtaining pairs of friction coefficients and interaction energies for all known lubricants included in the known lubricant list.

[0098] In step S9, the regression equation generating unit 105 of the lubricant selecting device 10 receives the friction coefficient for each known lubricant from the friction coefficient calculating unit 103. The regression equation generating unit 105 also receives the interaction energy for each known lubricant from the energy calculating unit 104.

[0099] Next, the regression equation generating unit 105 generates analysis data by combining the friction coefficient and the interaction energy for the same known lubricant. The regression equation generating unit 105 then derives a regression equation that represents the correlation between the friction coefficient and the interaction energy based on the generated analysis data. The regression equation generating unit 105 stores the derived regression equation in the analysis result storage unit 107.

[0100] In step S10, the friction coefficient estimation unit 106 of the lubricant selection device 10 reads out the regression equation stored in the analysis result storage unit 107. Next, the friction coefficient estimation unit 106 receives the interaction energy for each known lubricant from the energy calculation unit 104. Then, the friction coefficient estimation unit 106 estimates a friction coefficient for each known lubricant based on the read out regression equation. The friction coefficient estimation unit 106 stores the estimated friction coefficient in the analysis result storage unit 107.

[0101] <<Selection process>> 6 is a flowchart showing an example of the selection process in this embodiment. The selection process is a process for estimating a friction coefficient for a candidate lubricant using a regression equation derived in the analysis process, and selecting a lubricant to be used in manufacturing the exterior material 91 for an electricity storage device.

[0102] In step S11, the lubricant information generating unit 301 of the user terminal 30 generates a lubricant candidate list in response to a user operation. The lubricant candidate list is generated by selecting lubricant information to be a lubricant candidate from the lubricant information stored in the lubricant information storage unit 300. Next, the lubricant information generating unit 301 transmits the generated lubricant candidate list to the lubricant selection device 10.

[0103] In the lubricant selection device 10, the lubricant information input unit 101 receives the lubricant candidate list from the user terminal 30. Next, the lubricant information input unit 101 accepts the input of the received lubricant candidate list. Then, the lubricant information input unit 101 sends the accepted lubricant candidate list to the model construction unit 102.

[0104] In step S12, the model construction unit 102 of the lubricant selection device 10 receives the lubricant candidate list from the lubricant information input unit 101. Next, the model construction unit 102 generates lubricant molecular models of the lubricant candidates included in the lubricant candidate list using quantum chemical calculations. The generated lubricant molecular models are similar to the lubricant molecular models of known lubricants.

[0105] In step S13, the model construction unit 102 of the lubricant selection device 10 constructs a lubricant surface model corresponding to the lubricant candidate using the lubricant molecular model and the resin layer model of the lubricant candidate. The resin layer model may be the one generated in step S2 of the analysis process. The generated lubricant surface model is the same as the lubricant surface model corresponding to the known lubricant. The model construction unit 102 sends the generated lubricant surface model to the energy calculation unit 104.

[0106] In step S14, the energy calculation unit 104 of the lubricant selection device 10 receives the lubricant surface model corresponding to the lubricant candidate from the model construction unit 102. Next, the energy calculation unit 104 performs a molecular dynamics calculation using the received lubricant surface model. The conditions of the molecular dynamics calculation are the same as those in step S7.

[0107] In step S15, the energy calculation unit 104 of the lubricant selection device 10 calculates the interaction energy between the lubricant layer formed by the lubricant candidate and the resin layer based on the result of the molecular dynamics calculation in step S14. Next, the energy calculation unit 104 sends the calculated interaction energy to the friction coefficient estimation unit 106.

[0108] In step S16, the friction coefficient estimation unit 106 of the lubricant selection device 10 reads out the regression equation stored in the analysis result storage unit 107. Next, the friction coefficient estimation unit 106 receives the interaction energy for the candidate lubricant from the energy calculation unit 104. Then, the friction coefficient estimation unit 106 estimates a friction coefficient for the candidate lubricant based on the read out regression equation. The friction coefficient estimation unit 106 sends the estimated friction coefficient to the lubricant selection unit 108.

[0109] The processes from steps S12 to S16 are repeatedly performed for each lubricant candidate included in the lubricant candidate list, thereby obtaining estimated values ​​of the friction coefficient for all lubricant candidates included in the lubricant candidate list.

[0110] In step S17, the lubricant selection unit 108 of the lubricant selection device 10 receives the friction coefficients for each lubricant candidate from the friction coefficient estimation unit 106. Next, the lubricant selection unit 108 reads out the friction coefficients for each known lubricant stored in the analysis result storage unit 107.

[0111] Next, the lubricant selection unit 108 compares the friction coefficients of the received lubricant candidates with the friction coefficients of the read known lubricants. Next, the lubricant selection unit 108 selects a lubricant to be used in manufacturing the exterior material 91 for an electricity storage device based on the comparison result of the friction coefficients.

[0112] The lubricant selection unit 108 selects a lubricant candidate having a friction coefficient smaller than the friction coefficients of all known lubricants. When there are multiple lubricant candidates having friction coefficients smaller than the friction coefficients of all known lubricants, the lubricant selection unit 108 may select the lubricant candidate having the smallest friction coefficient. Alternatively, the lubricant selection unit 108 may select all lubricant candidates having friction coefficients smaller than the friction coefficients of all known lubricants.

[0113] In step S18, the lubricant selection unit 108 of the lubricant selection device 10 transmits the lubricant selection result to the user terminal 30. The lubricant selection result includes a selected lubricant list including lubricant information related to the lubricant selected in step S17. If no lubricant was selected in step S17 (i.e., if there was no lubricant candidate with a friction coefficient smaller than the friction coefficients of all known lubricants), the lubricant selection result includes information indicating that no lubricant was selected.

[0114] In the user terminal 30, the result display unit 302 receives the lubricant selection result from the lubricant selection device 10. Next, the result display unit 302 outputs the received lubricant selection result to the display device 506 or the like.

[0115] Based on the lubricant selection result, the user determines the lubricant to be used in manufacturing the electricity storage device exterior material 91. The user may carry out an experiment or the like using the lubricant selected by the lubricant selection device 10, and determine the lubricant to be used in the manufacturing based on the experiment result.

[0116] The lubricant determined by the user is added to a resin for forming a base layer 92 of an exterior material 91 for an electricity storage device. The exterior material 91 for an electricity storage device is manufactured by sequentially laminating the base layer 92 to which the lubricant has been added, a metal foil layer 93, and a sealant layer 94. The manufactured exterior material 91 for an electricity storage device is wound into a roll and stored, whereby the lubricant bleeds out from the base layer 92 over time, forming a lubricating layer 95.

[0117] <Effects of the embodiment> The lubricant selection device 10 in this embodiment estimates the friction coefficient between the resin layer and the mold layer through the lubricant layer formed by the lubricant molecules based on the interaction energy between the lubricant molecules and the resin layer. The interaction energy between the lubricant molecules and the resin layer can be stably calculated with less calculation amount than the friction coefficient related to the lubricant molecules. Therefore, according to the lubricant selection device 10 in this embodiment, the friction coefficient between the resin layer and the mold layer through the lubricant layer can be stably calculated with less calculation amount.

[0118] The lubricant selection device 10 in this embodiment calculates the friction coefficient between the resin layer and the mold layer through the lubricant layer formed by the lubricant molecules from the interaction energy between the lubricant molecules and the resin layer based on a regression equation that represents the relationship between the interaction energy and the friction coefficient for a known lubricant. Therefore, the lubricant selection device 10 in this embodiment can stably determine the friction coefficient between the resin layer and the mold layer through the lubricant layer with a small amount of calculation.

[0119] The lubricant selected by the lubricant selection device 10 in this embodiment may be used as a lubricant to be added to a resin layer in an electrical storage device exterior material including a resin layer, a sealant layer, and a metal foil layer disposed between the resin layer and the sealant layer. Since the lubricant has a smaller friction coefficient than known lubricants, the electrical storage device exterior material including a resin layer to which the lubricant has been added has improved formability. Therefore, the lubricant selection device 10 in this embodiment can produce an electrical storage device exterior material with improved formability.

[0120] [Variations] In the above embodiment, the lubricant selection device 10 is configured to estimate the friction coefficient for each of a plurality of candidate lubricants and select a lubricant based on the estimated friction coefficient. In this modification, the lubricant selection device 10 in the embodiment is configured as a friction coefficient estimation device that estimates the friction coefficient for one lubricant.

[0121] <Functional configuration of the friction coefficient estimation device> The friction coefficient estimation device in this modified example will be described with reference to Fig. 7. Fig. 7 is a block diagram showing an example of the functional configuration of the friction coefficient estimation device in this modified example.

[0122] 7, like the lubricant selection device 10 in the embodiment, the friction coefficient estimation device 20 in this modification includes a lubricant information input unit 101, a model construction unit 102, a friction coefficient calculation unit 103, an energy calculation unit 104, a regression equation generation unit 105, a friction coefficient estimation unit 106, and an analysis result storage unit 107. That is, the friction coefficient estimation device 20 differs from the lubricant selection device 10 in that it does not include the lubricant selection unit 108.

[0123] In this modification, the lubricant candidate list received by the lubricant information input unit 101 includes information about only one lubricant candidate. Therefore, the energy calculation unit 104 calculates the interaction energy for the only lubricant candidate, and the friction coefficient estimation unit 106 estimates and outputs the friction coefficient for the only lubricant candidate.

[0124] <Effects of modified versions> The friction coefficient estimation device 20 in this modification estimates the friction coefficient between the resin layer and the mold layer through the lubricant layer formed by the lubricant molecules based on the interaction energy between the lubricant molecules and the resin layer. Therefore, the friction coefficient estimation device 20 in this embodiment can stably obtain the friction coefficient between the resin layer and the mold layer through the lubricant layer with a small amount of calculation.

[0125] [Example] Examples will be described below to specifically explain the above embodiment. Note that the above embodiment is not limited to the following examples.

[0126] (lubricant molecule) As the lubricant molecules whose general formula is shown in formula (1), those of formulas (2) to (7) were used.

[0127] [ka]

[0128] Formula (2) is a structural formula representing erucamide (EA). Formula (3) is a structural formula representing oleamide (OA). Formula (4) is a structural formula representing behenamide (BA). Formula (5) is a structural formula representing stearamide (SA). Formula (6) is a structural formula representing ethylene bis oleamide (EBOA). Formula (7) is a structural formula representing ethylene bis stearamide (EBSA).

[0129] The following simulation was carried out for the lubricant molecules shown in formulas (2) to (7).

[0130] <Simulation> (Resin layer) Figure 8 is a schematic diagram showing an example of a resin layer model used in the simulation. As shown in Figure 8, in the simulation, a resin layer was used in which 20 PET molecules with a degree of polymerization of 20 were randomly arranged using random numbers in a cell of 50 Å × 50 Å × 20 Å.

[0131] (Mold layer) Fig. 9 is a schematic diagram showing an example of a mold layer model used in the simulation. As shown in Fig. 9, the (111) surface of iron is used as the mold layer in the simulation.

[0132] <Building models of lubricant molecules, resin layer, and mold layer (Step S2)> The stable structure and charge of each atom were determined for the unit structure of the lubricant molecule and the resin layer by quantum chemical calculation. After optimizing the structure to calculate the stable structure for each of the lubricant molecule and the resin layer, the atomic charge in the structure was calculated. In addition, for the mold layer model, iron atoms were arranged to form a (111) plane, and the charge of each atom was set to 0.

[0133] The stable structures of the lubricant molecules and the resin layer were calculated using the following combination of parameters / basis functions in the density functional theory: ωB97xd / 6-31+G *The atomic charges in the determined stable structure were calculated by Mulliken population analysis. The Gaussian (registered trademark) 16 program package from Gaussian Corporation was used for these quantum chemical calculations.

[0134] <Constructing the friction layer model (Step S3)> A lubricant molecular model was placed on the mold layer model, and a resin layer model was further placed on the lubricant molecular model to construct a friction layer model.

[0135] <<Performing friction molecular dynamics calculations (Step S4)>> The friction molecular dynamics calculations were carried out in the following two steps. The first step was to carry out preparatory calculations (hereafter referred to as "relaxation simulation") to bring the artificially constructed friction layer model closer to its natural state. The second step was to carry out actual calculations (hereafter referred to as "friction simulation") to track the movement of the actual friction layer from the constructed friction layer model.

[0136] (Mitigation simulation) Using a lubricant molecular model and a resin layer model, which include information representing a stable structure and the charge of each atom, an initial state of the friction layer model, which is the initial structure of the friction simulation, was constructed. In this embodiment, a relaxation simulation was performed on the friction layer model in the initial state in order to reproduce a state in which the lubricant molecules are evenly distributed between the resin layer and the mold layer at room temperature (300K).

[0137] The conditions for the relaxation simulation were set as follows: The DREIDING force field was used as the molecular force field. The cutoff method was used for the Lennard-Jones interaction. The cutoff distance was set to 12 Å, at which the interaction can be considered negligible. The Nose-Hoover method was used as the temperature control method, and simulations were performed using an NVT ensemble with the number of particles (N), volume (V), and temperature (T) kept constant. For molecular dynamics calculations, the 29Oct20 version of the free software LAMMPS (Large-scale Atomic / Molecular Massively Parallel Simulator) was used.

[0138] 10(A) to (D) are schematic diagrams showing an example of a relaxation simulation of a friction layer model. First, as shown in Fig. 10(A), unit structures of a mold layer were arranged in a periodic boundary cell of 50 Å × 50 Å × 150 Å to form a mold layer 81. The positions of atoms in the mold layer 81 were fixed so that they would not change during the relaxation simulation.

[0139] Next, as shown in Fig. 10(B), lubricant molecules 82 were randomly arranged above the surface of the mold layer 81. In experiments, it was found from past measurements that a lubricant layer with a thickness of about two molecular layers was formed. In order to compare with the physical property values ​​obtained in the experiment, the number of lubricant molecules 82 was adjusted so that when a lubricant layer 84 shown in Fig. 10(D) was formed, the film thickness in a thermal equilibrium state at room temperature was about two molecular layers.

[0140] 10(C) and (D), a downward force is applied to the resin layer 83 and the lubricant molecules 82, and a molecular dynamics calculation is performed under a room temperature condition of 300 K, causing the resin layer 83 and the lubricant molecules 82 to descend, forming a lubricant layer 84 on the surface of the mold layer 81, which is used as a friction layer model. Here, FIG. 10(C) shows the structure of the friction layer model in the middle of the molecular dynamics calculation, and FIG. 10(D) shows the structure of the friction layer model after 30 ps of calculation.

[0141] (Friction simulation) The friction simulation conditions were set as follows: The DREIDING force field was used as the molecular force field. The cutoff method was used for the Lennard-Jones interaction. The cutoff distance was set to 12 Å, which can be considered to be negligible. The Particle-Particle Particle-Mesh Ewald method was used to calculate the long-range Coulomb interaction. The Nose-Hoover method was used as the temperature control method, and simulations were performed using an NVT ensemble with constant particle number (N), volume (V), and temperature (T). Friction was reproduced by applying a vertical upward pressure of 0.25 MPa and a horizontal shear rate of 10.0 mm / s to the mold layer. The free software LAMMPS was used for molecular dynamics calculations.

[0142] In the friction simulation, the structure and behavior of the friction layer at 300K were reproduced and analyzed.

[0143] <Calculation of friction coefficient (Step S5)> Fig. 11 is a diagram showing the calculation results for known lubricants. Fig. 11 shows the friction coefficient (calculated value) calculated for each lubricant molecule. Here, erucic acid amide (EA) shown in No. 1-1 is a lubricant molecule that serves as a reference for friction. In other words, lubricant molecules that show a friction coefficient smaller than that of erucic acid amide (EA) were determined to be lubricant molecules that can form a lubricating layer with better friction.

[0144] According to the friction coefficients (calculated values) shown in FIG. 11, for example, if a lubricant molecule called stearic acid amide (SA) shown in No. 1-4 is used, it is predicted that a lubricating layer that reduces friction will be formed.

[0145] <Constructing a lubricated surface model (Step S6)> A lubricated surface model was constructed by placing a lubricant molecular model on top of the resin layer model.

[0146] <<Performing molecular dynamics calculations (Step S7)>> The molecular dynamics calculations were carried out in the following two steps. The first step was to carry out preparatory calculations (hereafter referred to as "relaxation simulation") to bring the artificially constructed lubricating surface model closer to the natural state. The second step was to carry out actual calculations (hereafter referred to as "lubricating surface simulation") to track the movement of the actual lubricating surface from the constructed lubricating surface model.

[0147] (Mitigation simulation) Using a lubricant molecular model and a resin layer model, which include information representing a stable structure and the charge of each atom, an initial state of the lubricant surface model, which is the initial structure of the lubricant surface simulation, was constructed. In this embodiment, a relaxation simulation was performed on the initial state of the lubricant surface model in order to reproduce a state in which the lubricant molecules are evenly distributed on the resin at room temperature (300K).

[0148] The conditions for the relaxation simulation were set as follows: The DREIDING force field was used as the molecular force field. The cutoff method was used for the Lennard-Jones interaction. The cutoff distance was set to 12 Å, at which the interaction can be considered negligible. The Nose-Hoover method was used as the temperature control method, and simulations were performed using an NVT ensemble with constant particle number (N), volume (V), and temperature (T). The free software LAMMPS was used for molecular dynamics calculations.

[0149] 12(A) to (D) are schematic diagrams showing an example of a relaxation simulation of a lubricated surface model. First, as shown in Fig. 12(A), a resin layer was placed in a periodic boundary cell of 50 Å × 50 Å × 150 Å to form a resin layer 86. The positions of atoms in the resin layer 86 were fixed so that they would not change during the relaxation simulation.

[0150] Next, as shown in Fig. 12(B), lubricant molecules 87 were randomly arranged above the surface of resin layer 86. Previous measurements in experiments had revealed that a lubricant layer with a thickness of about two molecular layers was formed. In order to compare with the physical property values ​​obtained in the experiment, the number of lubricant molecules 87 was adjusted so that when lubricant layer 88 shown in Fig. 12(D) was formed, the film thickness in a thermal equilibrium state at room temperature would be about two molecular layers.

[0151] 12(C) and (D), a downward force was applied to the lubricant molecules 87, and a molecular dynamics calculation was performed under the room temperature condition of 300 K, causing the lubricant molecules 87 to descend and forming a lubricant layer 88 on the surface of the resin layer 86, which was used as a lubricated surface model. Here, Fig. 12(C) shows the structure of the lubricant surface model in the middle of the separation dynamics calculation, and Fig. 12(D) shows the structure of the lubricant surface model of the lubricant layer 88 after 30 ps of calculation.

[0152] (Lubrication surface simulation) The conditions for the lubricated surface simulation were set as follows: The DREIDING force field was used as the molecular force field. The cutoff method was used for the Lennard-Jones interaction. The cutoff distance was set to 12 Å, at which the interaction can be considered negligible. The Particle-Particle Particle-Mesh Ewald method was used to calculate the long-range Coulomb interaction. The Nose-Hoover method was used as the temperature control method, and simulations were performed using an NVT ensemble with the number of particles (N), volume (V), and temperature (T) kept constant. The free software LAMMPS was used for molecular dynamics calculations.

[0153] In the lubricated surface simulation, the structure and behavior of the lubricated surface at 300K were reproduced and analyzed.

[0154] <<Calculation of interaction energy (Step S8)>> For all known lubricants, the interaction energy between each lubricant molecule and the resin layer was calculated. The calculated interaction energies for each lubricant molecule are shown in Figure 11.

[0155] <Deriving the regression equation (Step S9)> In the calculation of the friction coefficient (step S5), the friction coefficient (calculated value) was obtained when a certain lubricant molecule was used, and in the calculation of the interaction energy (step S8), the interaction energy was obtained when the same lubricant molecule was used. By repeating these steps for the lubricant molecules shown in Figure 11, the friction coefficients (calculated values) and interaction energies were obtained for all known lubricants.

[0156] A regression equation that shows the correlation between the friction coefficient (calculated value) and the interaction energy was derived by analyzing the calculation results shown in Figure 11. The derived regression equation is shown in Equation (8).

[0157]

number

[0158] Here, μ is the friction coefficient calculated from the friction molecular dynamics calculation, and E is the interaction energy calculated from the molecular dynamics calculation.

[0159] <Estimation of friction coefficient (Step S10)> For all known lubricants, the interaction energies were fitted to the regression equation shown in Equation (8) to estimate the friction coefficient for each known lubricant. The friction coefficients (estimated values) estimated for each known lubricant are shown in Figure 11.

[0160] The estimated friction coefficient for a known lubricant is the criterion for judging whether a candidate lubricant is a suitable lubricant. If the estimated friction coefficient for a candidate lubricant is smaller than the estimated friction coefficients for all known lubricants, it can be judged to be a suitable lubricant. In FIG. 11, the smallest estimated friction coefficient is 0.00126 for ethylene bisstearic acid amide (EBSA) shown in No. 1-6. Therefore, if the estimated friction coefficient for a candidate lubricant is less than 0.00126, it can be judged to be a suitable lubricant, and if it is 0.00126 or more, it can be judged to be an inappropriate lubricant.

[0161] <Constructing a model of lubricant molecules (Step S12)> As lubricant candidates, the lubricant molecules shown in Fig. 13 were selected. Fig. 13 is a diagram showing an example of the calculation results for the lubricant candidates. For the unit structures of all the lubricant molecules selected as lubricant candidates, stable structures and the charges of each atom were obtained by quantum chemical calculation.

[0162] <Constructing a lubricated surface model (Step S13)> For all the lubricant candidates, the process of placing the lubricant molecule model on the resin layer model was repeated to construct a lubricating surface model for each lubricant molecule.

[0163] <<Performing molecular dynamics calculation (Step S14)>> Using the lubricated surface model constructed for all the lubricant candidates, relaxation simulations and lubricated surface simulations were repeatedly performed.

[0164] <<Calculation of interaction energy (Step S15)>> For all lubricant candidates, the interaction energy between each lubricant molecule and the resin layer was calculated. The calculated interaction energies for each lubricant candidate are shown in FIG.

[0165] <Estimation of friction coefficient (Step S16)> For all the lubricant candidates, the interaction energies were fitted to the regression equation shown in Eq. (8) to estimate the friction coefficient for each lubricant candidate. The estimated friction coefficients for each lubricant candidate (estimated values) are shown in Figure 13.

[0166] If the estimated coefficient of friction for a candidate lubricant was smaller than the estimated coefficients of friction for all known lubricants, it was selected as a suitable lubricant. That is, if the estimated coefficient of friction was less than 0.00126, it was judged to be a suitable lubricant, and if it was 0.00126 or more, it was judged to be an unsuitable lubricant. For example, N-oleyl stearamide (NOSA) shown in No. 2-6 was predicted to be a suitable lubricant.

[0167] [Experimental Results] The friction coefficients of the candidate lubricants predicted to be suitable lubricants from the above examples were verified by experiments. In the experiment, the friction coefficients of the sealant layer surface (CPP surface) and the base layer surface (PET surface) were measured. The lubricants used in the experiment were N-oleylstearamide (NOSA), N-stearylstearamide (NSSA), ethylene bisbehenic acid amide (EBBA), and ethylene bislauric acid amide (EBLA), which were predicted to be suitable lubricants from the examples. The same measurements were also performed on erucic acid amide (EA) as a known reference lubricant. In the experiment, the friction coefficients of each lubricant were measured immediately after transfer, one day after transfer, and five days after transfer in order to verify the change over time in the friction coefficient.

[0168] FIG. 14A is a diagram showing an example of experimental results regarding the friction coefficient of a CPP surface. FIG. 14B is a diagram showing an example of experimental results regarding the friction coefficient of a PET surface. As shown in FIG. 14A and FIG. 14B, ethylene bisbehenic acid amide (EBBA) resulted in a worse friction coefficient than erucic acid amide (EA). On the other hand, N-oleyl stearic acid amide (NOSA) had a higher friction coefficient than erucic acid amide (EA) immediately after transfer, but the friction coefficient was lower than that of erucic acid amide (EA) one day after transfer. Therefore, it was confirmed that N-oleyl stearic acid amide (NOSA), which was shown to be a suitable lubricant by the above examples, can reduce the friction coefficient in a shorter time than known lubricants.

[0169] [supplement] Each function of the above-described embodiments can be realized by one or more processing circuits. Here, the term "processing circuit" in this specification includes a processor programmed to execute each function by software, such as a processor implemented by an electronic circuit, and an ASIC (Application Specific Integrated Circuit), DSP (Digital Signal Processor), FPGA (Field Programmable Gate Array), conventional circuit module, and other devices designed to execute each function described above.

[0170] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to these embodiments, and various modifications and changes are possible within the scope of the gist of the present invention described in the claims.

[0171] This application claims priority to Japanese Patent Application No. 2022-172490, filed with the Japan Patent Office on October 27, 2022, the entire contents of which are incorporated herein by reference. [Explanation of symbols]

[0172] 1. Design support system 10 Lubricant selection device 20. Friction coefficient estimation device 30 User terminals 101 Lubricant information input section 102 Model Construction Department 103 Friction coefficient calculation section 104 Energy Calculation Department 105 Regression equation generator 106 Friction coefficient estimation unit 107 Analysis result storage unit 108 Lubricant Selection Section 300 Lubricant information storage unit 301 Lubricant Information Generation Unit 302 Result display section

Claims

1. a lubricant information input unit configured to receive input of information regarding a plurality of lubricant candidates; an energy calculation unit configured to calculate an interaction energy between a lubricant layer formed by each of the plurality of lubricant candidates and a resin layer; a friction coefficient estimation unit configured to estimate a friction coefficient between the resin layer and the die layer via the lubricant layer based on the interaction energy; a lubricant selector configured to select a lubricant from the plurality of candidate lubricants based on the coefficient of friction; A lubricant selection device comprising:

2. 2. The lubricant selection device according to claim 1, The friction coefficient estimation unit is configured to estimate the friction coefficient from the interaction energy based on a predetermined regression equation. Lubricant selection device.

3. 3. The lubricant selection device according to claim 2, The regression equation represents a correlation between the interaction energy and the friction coefficient. Lubricant selection device.

4. 4. The lubricant selection device according to claim 3, The regression equation is derived using the interaction energy and the friction coefficient calculated by molecular dynamics calculation for a lubricant different from the lubricant candidate. Lubricant selection device.

5. 5. The lubricant selection device according to claim 4, The regression equation is −3.6×10 －５ is the regression coefficient, Lubricant selection device.

6. A lubricant selection device according to any one of claims 1 to 5, The lubricant is used as a lubricant to be added to the resin layer in an exterior material for an electrical storage device, the exterior material including the resin layer, a sealant layer, and a metal foil layer disposed between the resin layer and the sealant layer. Lubricant selection device.

7. A lubricant information input unit configured to receive input of information regarding a lubricant; an energy calculation unit configured to calculate an interaction energy between a lubricant layer formed by the lubricant and a resin layer; a friction coefficient estimation unit configured to estimate a friction coefficient between the resin layer and the die layer via the lubricant layer based on the interaction energy; A friction coefficient estimation device comprising:

8. The computer receiving input of information regarding a plurality of potential lubricants; A step of calculating an interaction energy between a lubricant layer formed by each of the plurality of lubricant candidates and a resin layer; a step of estimating a coefficient of friction between the resin layer and the mold layer via the lubricant layer based on the interaction energy; selecting a lubricant from the plurality of candidate lubricants based on the coefficient of friction; A lubricant selection method to be performed.

9. 9. A method for producing an exterior material for an electricity storage device, using a lubricant selected by the lubricant selection method according to claim 8, to produce an exterior material for an electricity storage device, the exterior material including: the resin layer to which the lubricant has been added, a sealant layer, and a metal foil layer disposed between the resin layer and the sealant layer.

10. On the computer, receiving input of information regarding a plurality of potential lubricants; A step of calculating an interaction energy between a lubricant layer formed by each of the plurality of lubricant candidates and a resin layer; a step of estimating a coefficient of friction between the resin layer and the mold layer via the lubricant layer based on the interaction energy; selecting a lubricant from the plurality of candidate lubricants based on the coefficient of friction; A program for executing the above.

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