Porous film for quantum dot classification, and method for classifying quantum dots using the porous film.

Abstract

To provide a novel method for classifying a quantum dot.SOLUTION: A quantum dot classifying porous membrane includes a porous membrane for classifying a quantum dot.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a porous film for quantum dot classification and a method for classifying quantum dots using the porous film. [Background technology]

[0002] Quantum dots are semiconductor particles with a major axis of approximately 1 nm to 100 nm, and they possess discrete energy levels. The energy state of a quantum dot depends on its size. Therefore, it is possible to adjust the emission wavelength by changing the size of the quantum dot.

[0003] Thus, since the emission wavelength of quantum dots depends on the size of the quantum dot, uniformity of quantum dot size is required to suitably adjust the emission wavelength. One known method for uniformizing quantum dot size is to repeatedly perform centrifugation.

[0004] For example, Patent Document 1 discloses the following method for producing PbS particles, which are an example of quantum dots: In a three-necked flask, lead(II) oxide is placed as a lead (Pb) precursor solution, oleic acid as an organic ligand, and octadecene as a solvent. The flask is purged with nitrogen, and the Pb precursor solution is heated to 90°C in an oil bath to react the lead oxide with oleic acid. After that, the solution is heated to 120°C to generate and grow PbS quantum dots. Separately, an octadecene solution of bistrimethylsilyl sulfide is prepared as a sulfur (S) precursor solution. The S precursor solution is rapidly injected into the Pb precursor solution heated to 120°C and allowed to react. After the reaction is complete, the solution is allowed to cool naturally to room temperature, methanol or acetone is added as a polar solvent, and centrifugation is performed to precipitate the PbS particles. After removing the supernatant, toluene is added to wash and redisperse the PbS particles. It is believed that by repeating this centrifugation and redispersion process multiple times, excess oleic acid and unreacted substances can be removed, and finally, by adding a solvent such as octane, a quantum dot dispersion can be obtained in which quantum dots are dispersed. [Prior art documents]

Patent Document

[0005]

Patent Document 1

Non-Patent Document

[0006]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0007] However, as a method for equalizing the size of quantum dots, the method of repeatedly performing centrifugation has problems in that it takes a long time for the classification of quantum dots and the cost is high.

[0008] Therefore, the main object of the present invention is to provide a novel classification method for quantum dots.

Means for Solving the Problems

[0009] The present inventors examined a classification method using a porous membrane, which is not known as a classification method for quantum dots. As a result, they obtained a new finding that the classification method using a porous membrane can be suitably used as a classification method for quantum dots. The present invention was completed by further examination based on such findings.

[0010] That is, the present invention provides an invention in the following aspects. Item 1. A porous membrane for quantum dot classification, comprising a porous membrane for classifying quantum dots. Item 2. The porous membrane for quantum dot classification according to Item 1, wherein the porous membrane contains a polyamide resin. Item 3. The porous membrane for quantum dot classification according to Item 1 or 2, wherein the shape of the porous membrane is a hollow fiber membrane shape. Item 4. A method for classifying quantum dots, using the porous membrane for quantum dot classification according to any one of Items 1 to 3.

Advantages of the Invention

[0011] According to the present invention, a novel method for classifying quantum dots can be provided.

Brief Description of the Drawings

[0012] [Figure 1] It is a schematic diagram for explaining a method for a classification test of quantum dots using a porous membrane. [Figure 2] It is a schematic diagram of an apparatus used when measuring the bubble point of a porous membrane. [Figure 3] In the examples, it is a graph showing the result of classifying quantum dots using a porous membrane or centrifugation (showing the relationship between particle size (nm) and frequency of existence (%)). [Figure 4] It is a reference image for explaining a method for measuring the particle size distribution (average particle size) of quantum dots. [Figure 5] a is a schematic diagram of a module used when measuring water permeability, and b is a schematic diagram of an apparatus used for measuring water permeability.

Modes for Carrying Out the Invention

[0014] <Porous membrane for quantum dot classification> [Materials that make up porous membranes] The constituent material of the porous membrane for quantum dot classification in the present invention is a resin. That is, the porous membrane for quantum dot classification in the present invention is formed from a resin.

[0015] The resin included in the porous membrane for quantum dot classification is not particularly limited as long as it can form a porous membrane. Examples include polyamide resins, polyimide resins, polyethylene resins, polypropylene resins, polyarylate resins, polysulfone resins, polyethersulfone resins, polyester resins, polyvinyl alcohol resins, polyvinyl acetate resins, ethylene-vinyl alcohol copolymers, polyvinylidene fluoride resins, polytetrafluoroethylene resins, cellulose acetate resins, and polyacrylonitrile resins. Among these, when an organic solvent is used as the dispersion of quantum dots, as will be described later, polyamide resins, polyimide resins, polyethylene resins, polypropylene resins, polyarylate resins, polysulfone resins, polyethersulfone resins, polyester resins, polyvinylidene fluoride resins, and polytetrafluoroethylene resins are preferred, and polyamide resins are more preferred, from the viewpoint of suitably classifying quantum dots and also from the viewpoint of solvent resistance. The type of polyamide resin is not particularly limited, but examples include polyamide homopolymers, polyamide copolymers, or mixtures thereof. Examples of polyamide homopolymers include polyamide 6, polyamide 66, polyamide 46, polyamide 610, polyamide 612, polyamide 11, polyamide 12, polyamide MXD6, polyamide 4T, polyamide 6T, polyamide 9T, and polyamide 10T. Examples of polyamide copolymers include copolymers of polyamide with polyethers such as polytetramethylene glycol or polyethylene glycol. The proportion of the polyamide component in the polyamide copolymer is not particularly limited, but for example, the proportion of the polyamide component is preferably 70 mol% or more, more preferably 80 mol% or more. By satisfying the above range for the proportion of the polyamide component in the polyamide copolymer, even better resistance to organic solvents can be achieved.

[0016] While the presence or absence of crosslinking of the polyamide resin is not a requirement, non-crosslinked polyamide resin is preferred from the viewpoint of reducing manufacturing costs. Furthermore, there are no particular restrictions on the relative viscosity of the polyamide resin, but for example, values ​​of 2.0 to 8.0, preferably 3.0 to 7.0, and more preferably 3.5 to 6.0 are given. Having such a relative viscosity improves moldability and controllability of phase separation during the production of the polyamide porous film, and makes it possible to provide the polyamide porous film with excellent dimensional stability. Here, relative viscosity refers to the value measured using an Ubbelohde viscometer at 25°C with a solution prepared by dissolving 1 g of polyamide resin in 100 mL of 96% sulfuric acid.

[0017] In the present invention, the resin used to form the porous film for quantum dot classification may be of one type or two or more types.

[0018] Among these resins, polyamide resins, particularly polyamide 6, are especially suitable as constituent resins for the porous membrane used for quantum dot classification in the present invention because they easily maintain the bubble point when an organic solvent is used as the dispersion liquid for quantum dots.

[0019] The porous membrane for quantum dot classification of the present invention may, in addition to the resin described above, contain fillers as needed, to the extent that they do not impair the effects of the present invention. By including fillers in the porous membrane, the strength, elongation, and elastic modulus of the porous membrane can be improved. The inclusion of fillers in the porous membrane also provides the effect that the porous membrane is less likely to deform even when high pressure is applied during classification.

[0020] There are no particular restrictions on the type of filler, but examples include fibrous fillers such as glass fibers, carbon fibers, potassium titanate whiskers, zinc oxide whiskers, calcium carbonate whiskers, wollastonite whiskers, aluminum borate whiskers, aramid fibers, alumina fibers, silicon carbide fibers, ceramic fibers, asbestos fibers, gypsum fibers, and metal fibers; silicates such as talc, hydrotalcite, wollastonite, zeolite, sericite, mica, kaolin, clay, pyrophyllite, bentonite, asbestos, and alumina silicate; metal compounds such as silicon oxide, magnesium oxide, alumina, zirconium oxide, titanium oxide, and iron oxide; carbonates such as calcium carbonate, magnesium carbonate, and dolomite; sulfates such as calcium sulfate and barium sulfate; metal hydroxides such as calcium hydroxide, magnesium hydroxide, and aluminum hydroxide; and inorganic materials such as non-fibrous fillers such as glass beads, glass flakes, glass powder, ceramic beads, boron nitride, silicon carbide, carbon black, silica, and graphite. The porous membrane may contain only one type of filler or two or more types. The filler content is not particularly limited, but for example, 5 to 100 parts by mass, preferably 10 to 75 parts by mass, and more preferably 25 to 50 parts by mass of filler per 100 parts by mass of polyamide resin. By including fillers in such a content, the strength, elongation, and elastic modulus of the porous membrane for quantum dot classification can be improved.

[0021] Furthermore, the porous membrane for quantum dot classification of the present invention may contain at least one additive, such as a thickener, antioxidant, surface modifier, lubricant, or surfactant, as needed, for purposes such as controlling pore size or improving membrane performance.

[0022] [Shape of porous membrane] The shape of the porous membrane for quantum dot classification in the present invention is not particularly limited and can be selected from any shape such as a hollow fiber membrane or a flat membrane. A hollow fiber membrane is suitable as the shape of the porous membrane for quantum dot classification in the present invention because it has a large filtration area per unit volume of module and enables efficient classification of quantum dots.

[0023] When the porous membrane for quantum dot classification of the present invention is a hollow fiber membrane, its outer diameter is appropriately set according to the liquid permeability to be provided, as well as the type and size of the quantum dots to be classified. Considering the relationship between the effective membrane area when filled into a module, the membrane strength, the pressure loss of the fluid flowing through the hollow portion, and the buckling pressure, the outer diameter of the porous membrane can be, for example, 300 μm or more, preferably 350 to 4000 μm, and more preferably 400 to 3500 μm. Furthermore, when the porous membrane for quantum dot classification of the present invention is a hollow fiber membrane, its inner diameter is not particularly limited, but can be, for example, 100 to 3000 μm, preferably 150 to 2500 μm, more preferably 200 to 2000 μm, and even more preferably 250 to 1500 μm. In this invention, the outer diameter and inner diameter of the porous membrane (hollow fiber membrane) are determined by observing five porous membranes with an optical microscope at a magnification of 200x, measuring the outer diameter and inner diameter (at the point of maximum diameter) of each porous membrane, and calculating the average value of each.

[0024] The thickness of the porous membrane for quantum dot classification of the present invention is appropriately set according to the shape of the porous membrane for quantum dot classification, the liquid permeability to be provided, and the type and size of the quantum dots to be classified, but for example, it is 50 to 600 μm, preferably 100 to 350 μm. When the porous membrane for quantum dot classification of the present invention is in the shape of a hollow fiber, its thickness is calculated by dividing the value obtained by subtracting the inner diameter from the outer diameter by 2.

[0025] In the porous film for quantum dot classification of the present invention, it is preferable that a dense layer (skin layer) is formed on the surface of at least one of its faces. This configuration makes it easier to cut quantum dots in the range of 2 to 3 nm. In the present invention, "dense layer" refers to a region in which dense micropores are clustered together, and in a scanning electron microscope (SEM) image at a magnification of 10,000x, the presence of pores is substantially not observed. When observing the dense layer with a scanning electron microscope, if the porous film for quantum dot classification is a flat film, it can be cut to an appropriate size, placed on a sample stage, and then observed after vapor deposition of Pt, Au, Pd, etc. Furthermore, when the porous membrane for quantum dot classification is a hollow fiber membrane, if the dense layer present on the outer surface is to be observed, it is sufficient to cut it to an appropriate size, place it on a sample stage, and then perform a vapor deposition treatment with Pt, Au, Pd, etc., as is the case with a flat membrane. However, if the dense layer present on the inner surface is to be observed, the hollow fiber membrane should be cut along its longitudinal direction with a sharp blade such as a scalpel to expose the inner surface, then cut to an appropriate size, place it on a sample stage, and then perform a vapor deposition treatment with Pt, Au, Pd, etc., before observation.

[0026] For example, if the porous membrane for quantum dot classification of the present invention is a hollow fiber membrane, it is sufficient that a dense layer is formed on at least one of the inner surface and the outer surface. Also, for example, if the porous membrane for quantum dot classification of the present invention is in the shape of a flat membrane, it is sufficient that a dense layer is formed on at least one of the outer surface and the back surface. A preferred example of the porous membrane for quantum dot classification of the present invention is one in which the dense layer is provided on only one surface. Furthermore, a preferred example of the porous membrane for quantum dot classification of the present invention being a hollow fiber membrane is one in which a dense layer is provided on the inner surface and no dense layer is provided on the outer surface.

[0027] The porous membrane for quantum dot classification according to the present invention can have a porous structure in areas other than the dense layer. Hereinafter, the areas other than the dense layer may be referred to as the "porous region." Specifically, the porous region refers to the area in which the presence of pores is substantially observed in a scanning electron microscope (SEM) image at a magnification of 2000x.

[0028] In the porous membrane for quantum dot classification of the present invention, when a dense layer is provided, the thickness of the dense layer is not particularly limited, but from the viewpoint of suitably classifying quantum dots, for example, it can be 10 to 2000 nm, preferably 100 to 1500 nm, more preferably 200 to 1000 nm, even more preferably 250 to 900 nm, and particularly preferably 300 to 700 nm. In the present invention, the thickness of the dense layer is a value obtained by measuring the distance (thickness) of the region where the presence of substantially no pores is not observed in an SEM image of the cross-section of the porous membrane for quantum dot classification at a magnification of 10,000x at 10 or more locations, and calculating the average value.

[0029] The porous membrane for quantum dot classification of the present invention preferably has a burst bubble point of 0.3 MPa or higher, and more preferably 0.7 MPa or higher, in a bubble point test in which air pressure is applied in a liquid with a surface tension of 21 mN / m at 20°C. Having such a bubble point allows for more favorable classification of quantum dots. In particular, from the viewpoint of making it easier to cut quantum dots in the range of 2 to 3 nm, the burst bubble point is preferably 0.8 MPa or higher, and more preferably 0.85 MPa or higher. Examples of upper limits for the burst bubble point include 5.0 MPa or lower, 4.0 MPa or lower, 3.0 MPa or lower, 2.0 MPa or lower, 1.5 MPa or lower, or 1.2 MPa or lower.

[0030] In the case where the porous membrane for quantum dot classification in the present invention is a hollow fiber membrane, the burst bubble point is a value measured using the apparatus shown in the schematic diagram of Figure 2, following the procedure below. First, a hollow fiber membrane minimodule for measuring the burst bubble point is prepared. Specifically, 10 hollow fiber membranes are cut to a length of 20 cm, bundled together, bent into a U-shape, and the end on the side of the opening of the hollow fiber membrane, about 1 cm, is heat-sealed to close the hollow part and prepare a bundle of hollow fiber membranes. Next, a 5 cm long flexible nylon tube for air piping (outer diameter 8 mm, inner diameter 6 mm) is prepared, and one of its openings is sealed with a silicone stopper. Next, with the end of the nylon tube with the silicone stopper facing downwards, potting agent (polyurethane resin) is introduced into the nylon tube to a height of about 4 cm. Subsequently, the hollow fiber membrane bundle is inserted into the nylon tube from the heat-sealed end, and a portion of the bundle is immersed in the potting agent. It is then left to stand until the potting agent hardens. After hardening, the hollow fiber membrane bundle is cut above the heat-sealed portion to open the hollow portion of the hollow fiber membrane. At this time, it is visually checked whether the potting agent has entered the hollow portion and whether the potting agent is filled between the hollow fiber membranes. After confirming that the hollow structure is maintained without any problems, the burst bubble point is measured. Next, the burst bubble point of the hollow fiber membrane is measured using the apparatus shown in the schematic diagram of Figure 2. Specifically, 2-propanol (surface tension of 21 mN / m at 20°C) is introduced into a glass container 14, the hollow fiber membrane minimodule 13 prepared above is immersed in it, and the pressure is reduced for several seconds to fill the holes with liquid. Next, the hollow fiber membrane minimodule 13, immersed in 2-propanol, is set up as shown in Figure 2, and air is introduced into the hollow fiber membrane at 0.4 MPa / min to increase the pressure. Initially, bubbles are generated from the hollow fiber membrane, and the pressure is increased until bubbles are generated from approximately the entire hollow fiber membrane. This pressure is then observed and designated as the burst bubble point.

[0031] When the porous membrane for quantum dot classification of the present invention is a flat membrane, the burst bubble point is the value measured by the following procedure. A flat membrane cut out in a circle with a diameter of 40 mm or more is immersed in 2-propanol (surface tension at 20°C: 21 mN / m), and the pressure is reduced for several seconds to fill the pores with liquid. Next, the flat membrane is taken out, and while it is wet with 2-propanol, both sides of the flat membrane are sandwiched between an O-ring with a diameter of 40 mm and a mesh, and these are fixed with a resin jig. Then, a pneumatic pipe is connected to one side of the jig, and while the flat membrane and the jig are immersed in the test liquid, air is sent through the pneumatic pipe into the flat membrane at a rate of 0.4 MPa / min to increase the pressure. First, bubbles are generated from the flat membrane, and the pressure is continuously increased. When bubbles are generated from the entire flat membrane, the pressure is confirmed, and this is taken as the burst bubble point.

[0032] In a bubble point test in which air pressure is applied in a liquid with a surface tension of 21 mN / m at 20°C, a commercially available porous membrane can be used as the porous membrane having a burst bubble point of 0.3 MPa or more. For example, polyamide hollow fiber membranes manufactured by Unitika Ltd., trade name WINSEP (registered trademark), product numbers MF 002, 005, 010, 040, UF 30, 50, 120, etc. can be mentioned.

[0033] The internal pressure water permeability of the porous membrane for quantum dot classification is not particularly limited. From the viewpoint of suitably classifying quantum dots, for example, it is 10 L / m 2 ·bar·h or more, preferably 30 L / m 2 ·bar·h or more, more preferably 50 L / m 2 ·bar·h or more, etc. Regarding the upper limit of the internal pressure water permeability, for example, 7000 L / m 2 ·bar·h or less, 6000 L / m 2 ·bar·h or less, 5000 L / m 2 ·bar·h or less, 1000 L / m 2 ·bar·h or less, 500 L / m 2 ·bar·h or less, or 100 L / m 2 ·bar·h or less can be mentioned. The method for measuring the internal pressure water permeability of the porous membrane for quantum dot classification is as follows.

[0034] In other words, when the porous membrane for quantum dot classification of the present invention is a hollow fiber membrane, the water permeability is a value measured by internal pressure filtration, and is measured by the following procedure. First, the module shown in Figure 5a is prepared. Specifically, first, 10 hollow fiber membranes are cut to a length of 30 cm and bundled together. Next, a rigid nylon tube with an outer diameter of 8 mm, an inner diameter of 6 mm, and a length of 50 mm is prepared, and a rubber stopper about 20 mm in length is inserted into the opening at one end of the tube to seal the opening at that end. Next, a two-component, room-temperature curing epoxy resin is inserted into the opening of the tube opposite to the rubber stopper, filling the space inside the tube with the epoxy resin. After that, the bundle of hollow fiber membranes prepared is bent into a roughly U-shape, and both ends of the hollow fiber membranes are inserted into the tube filled with the epoxy resin until the tips of the ends touch the rubber stopper, and the epoxy resin is allowed to harden in that state. Next, the hardened epoxy resin portion is cut along with the rubber stopper, creating a module with open hollow sections at both ends of the hollow fiber membrane.

[0035] Next, the module is set in the apparatus shown in Figure 5b, and 25°C pure water is flowed through the inside of the hollow fiber membrane of the module under a pressure of approximately 0.3 MPa for a certain period of time. The volume of pure water that permeates to the outside of the hollow fiber membrane is then determined, and the permeability (L / (m)) is calculated according to the following formula. 2 Calculate bar(h).

[0036]

number

[0037] Furthermore, when the polyamide porous membrane of the present invention is a flat membrane, the permeability is measured by dead-end filtration and is measured using the following procedure. A flat membrane cross-flow tester connected to a high-pressure pump (for example, a Sepa-CF flat membrane test cell manufactured by GE Water Technologies) is used to measure a flat-shaped polyamide porous membrane of a predetermined size (19.1 cm × 14.0 cm, effective membrane area in the cell: 155 cm²). 2 Cut the material to the specified length and fix it to the cell. Pure water at 25°C is passed through it, and the pure water that permeates through at a predetermined pressure is collected and its volume (L) is measured. The permeability (L / (m³)) is calculated according to the following formula. 2 Calculate bar(h).

[0038]

number

[0039] <Quantum dots> The quantum dots to be classified by the porous film for quantum dot classification of the present invention are not particularly limited. For example, known quantum dots can be used for classification. Examples of materials constituting quantum dots include semiconductor crystals, nanoparticles such as group IV semiconductors, group III-V and group II-VI compound semiconductors, compound semiconductors composed of three or more combinations of group II, III, IV, V, and VI elements, and halide perovskites. Specifically, examples include semiconductor materials with relatively narrow band gaps such as PbS, PbSe, PbTe, InN, InAs, GaAs, GaSb, SnSSe, SnTe, CdTe, CdSe, ZnSe, Ge, InGaAs, CuInS, CuInSe, CuInGaSe, InSb, Si, InP, and CsPbX2 (where X is a halogen). Among the above, the quantum dot material is preferably a nanoparticle containing Pb, more specifically PbS or PbSe, due to its ease of synthesis and photosensitivity up to the infrared region. Hereinafter, in this specification, nanoparticles made of the material constituting the quantum dot may be referred to as "semiconductor nanoparticles" for convenience. In the present invention, the quantum dot may have a core-shell structure in which the semiconductor nanoparticle is used as the nucleus (core) of the quantum dot and covered with a coating compound.

[0040] In the present invention, the quantum dot can have a structure in which the semiconductor nanoparticles described above form a nucleus covered with a passivation layer (also called a ligand), or a core-shell structure in which the nucleus is covered with a coating compound different from the nucleus, and this core-shell structure is further covered with a passivation layer (ligand). In this case, the coating compound arranged in the shell portion can be any semiconductor of the same or similar type as the quantum dot material (semiconductor nanoparticles), or an inorganic material such as silica. Furthermore, a multi-shell structure in which multiple shell materials are stacked as the shell may also be used. Examples of passivation layers (ligands) can be any organic ligands, inorganic ligands, halogens, etc.

[0041] A specific example of the above-mentioned passive layer (ligand) is butylamine:C4H 11 N, Oleylamine:C 18 H 35 NH2, Stearyl(octadecyl)amine:C 18 H 37 NH2, dodecyl(lauryl)amine:C 12 H 25 NH2, Decylamine:C 10 H 21 NH2, Octylamine:C8H 17 Aliphatic amine compounds such as NH2; fatty acids, oleic acid: C 17 H 33 COOH, Stearic Acid:C 17 H 35 COOH, palmitic acid:C 15 H 31 COOH, myristic acid:C 13 H 27 COOH, Lauryl (dodecanoic acid): C 11 H 23 COOH, Decanoic acid: C9H 19 COOH, octanoic acid: C7H 15 Fatty acid compounds such as COOH; ethanedithiol: C2H6S2, octadecanethiol: C 18 H 37 SH, Hexanedecanethiol:C 16 H 33 SH, Tetradecanethiol:C 14 H29 SH, Dodecanethiol:C 12 H 25 SH, Decanethiol:C 10 H 21 SH, Octanethiol:C8H 17 Thiol compounds such as SH; trioctylphosphine: (C8H 17 )3P, triphenylphosphine: (C6H5)3P, tributylphosphine: (C4H9)3P phosphine oxide system, trioctylphosphine oxide: (C8H 17 Examples include phosphine compounds such as 3P=O, triphenylphosphine oxide (C6H5)3P=O, and tributylphosphine oxide (C4H9)3P=O, as well as fluorine, chlorine, bromine, and iodine.

[0042] The quantum dots to be classified by the porous membrane for quantum dot classification of the present invention are preferably dispersed in a solvent. The solvent is not particularly limited, but examples include ester solvents such as ethyl acetate, propyl acetate, and butyl acetate; ketone solvents such as acetone, methyl ethyl ketone, and methyl isobutyl ketone; ether solvents such as dioxane and tetrahydrofuran; aliphatic hydrocarbon solvents such as n-hexane, cyclohexane, and methylcyclohexane; aromatic hydrocarbon solvents such as toluene and xylene; alcohol solvents such as methanol, ethanol, and isopropanol; amide solvents such as dimethylformamide; and water. In particular, when the constituent material of the porous membrane for quantum dot classification of the present invention is polyamide resin, polyimide resin, polyethylene resin, polypropylene resin, polyarylate resin, polysulfone resin, polyethersulfone resin, polyester resin, polyvinylidene fluoride resin, or polytetrafluoroethylene resin, it is preferable because it facilitates continuous classification of quantum dots even when an organic solvent is used as the solvent.

[0043] In the present invention, the particle size distribution (average particle size) of quantum dots classified by the porous membrane for quantum dot classification of the present invention is not particularly limited and can be appropriately selected according to the classification size (size of pores) of the porous membrane and the desired particle size of the quantum dots after classification. For example, the particle size distribution of the quantum dots to be classified can be 1 to 100 nm. Furthermore, the particle size distribution (average particle size) of quantum dots after classification by the porous membrane for quantum dot classification of the present invention can also be appropriately selected according to the classification size (size of pores) of the porous membrane and the desired particle size of the quantum dots after classification. For example, 1 to 15 nm, 15 to 25 nm, 25 to 50 nm, 50 to 80 nm, 80 to 100 nm, etc. In the present invention, if a quantum dot is a core-shell structure in which a semiconductor nanoparticle serves as the nucleus (core) of the quantum dot and is covered with a coating compound, a structure in which a semiconductor nanoparticle serves as the nucleus and the nucleus is covered with a passivation layer, or a core-shell structure in which the nucleus is covered with a coating compound different from the nucleus and is further covered with a passivation layer (ligand), then the particle size of the quantum dot refers to the particle size of the entire quantum dot including the coating compound, passivation layer, etc.

[0044] In this invention, the particle size distribution (average particle size) of quantum dots is measured as follows. Specifically, the particle size and particle size distribution of quantum dots contained in the filtrate filtered through a porous membrane for quantum dot classification are measured using a transmission electron microscope (TEM). Specifically, the obtained filtrate is dropped onto a grid for a transmission electron microscope (Hi-Res Carbon HRC-C10 manufactured by Ouken Shoji Co., Ltd.), and the solvent is evaporated to prepare a sample for TEM observation. This is observed at a magnification of 1.5 million times using a JEOL Ltd. transmission electron microscope JEM-2100F, and an image is obtained. The major axis (maximum length) and minor axis (minimum length) of 30 to 100 quantum dots that do not overlap in the image (see Figure 4) are measured. The average of the measured major and minor axes is taken as the particle size of the measured quantum dots, and the sum of these particle sizes is divided by the number of measured quantum dots (total number of measurement data) to obtain the average particle size. Furthermore, the standard deviation is calculated using the STDEV.S function in Microsoft Excel, based on the measured particle size data of each quantum dot. The frequency of occurrence of quantum dots with each particle size is calculated by measuring and creating the number of dots per 1 nm interval using the measured particle size data of each quantum dot, and then dividing each number by the total number of measured data points to calculate the frequency of occurrence for each particle size range.

[0045] The standard deviation of the particle size distribution (average particle size) of quantum dots classified by the porous film for quantum dot classification of the present invention is preferably 3.0 nm or less, more preferably 2.0 nm or less, and even more preferably 1 to 1.5 nm. Furthermore, the coefficient of variation CV obtained by dividing the standard deviation by the average particle size is preferably 0.50 or less, more preferably 0.30 or less, and even more preferably 0.22 or less.

[0046] The porous membrane for quantum dot classification of the present invention makes it possible to perform classification with a classification accuracy equivalent to or better than that of conventional classification methods using, for example, centrifugal separation. Therefore, the quantum dots after classification can be suitably used in applications such as bioimaging (fluorescent dyes, biosensors, etc.), electronics and photonics (light-emitting diodes, laser diodes, white lighting, backlights, displays, photonic inks, security inks, solid memory chips, photodetectors, optical amplifiers, transistors, optical switches, logic gates, quantum computers, etc.), and solar cells (dye-sensitized type, organic thin-film type, etc.). [Examples]

[0047] The present invention will be described in detail below with reference to examples and comparative examples. However, the present invention is not limited to the examples.

[0048] <Manufacturing of quantum dot dispersions> A PbS quantum dot dispersion was prepared in an organic solvent by chemical synthesis using the hot injection method, with PbS as semiconductor nanoparticles and oleic acid as the passivation layer. The reagents and procedure used in the preparation are shown below.

[0049] <Reagents> Lead(II) oxide: PbO, 99.999% trace metals basis, manufactured by Sigma-Aldrich. • Hexamethyldisilathian (TMS)2S, Hexamethyldisilathian synthesis grade, manufactured by Sigma-Aldrich. • Oleic acid: OA, Oleic acid technical grade, 90%, manufactured by Sigma-Aldrich. • 1-Octadecene: ODE, 1-Octadecene technical grade, 90%, manufactured by Sigma-Aldrich. Ethanol (99.5%): EtOH, Ethanol (99.5%), Wako 1st Grade, 99.5+%, manufactured by Wako.

[0050] <Manufacturing Procedure> 1) The glove box was pre-filled with nitrogen to reduce the humidity to below 20%. 2) Transfer 6.0 mL of 1-octadecene and a stirring bar to a lidded glass container, then into a glove box, and add 126.6 μL of (TMS) 2S. Stir this mixture using a hot stirrer at 40°C and 735 rpm. This is designated as solution A. 3) Using an electronic balance, 0.2232 g of lead(II) oxide was weighed out and placed in a four-necked flask. Then, 2.0 mL of 1-octadecene, 7.9 mL of oleic acid, and a stirring bar were added to the four-necked flask, and the mixture was stirred for 1 hour at 130°C and 750 rpm under a nitrogen atmosphere using a hot stirrer. This is designated as solution B. 4) Solution A was injected into solution B using a syringe and reacted at 130°C for 50 seconds. This is called solution C. 5) Add solution C to 12 mL of ethanol that had been pre-chilled to 5°C, and shake well to stop the reaction. A PbS quantum dot dispersion was obtained using the above procedure.

[0051] <Porous membrane for quantum dot classification> The following polyamide hollow fiber membranes manufactured by Unitika Ltd. (product names: WINSEP MF002, UF 50, MF 040) were used as porous membranes for quantum dot classification. WINSEP MF 002 (No dense layer (skin layer), porous structure, outer diameter 485 μm, inner diameter 277 μm) WINSEP UF 50 (with dense layer (skin layer) (a dense layer is present on the inner surface, but not on the outer surface; the area outside the dense layer has a porous structure), outer diameter 792 μm, inner diameter 423 μm, dense layer thickness 520 nm) WINSEP MF 040 (No dense layer (skin layer), porous structure, outer diameter 556 μm, inner diameter 282 μm)

[0052] The burst bubble points, molecular weight cutoff (kDa), and internal pressure permeability (L / (m³)) of these porous membranes are as follows: 2 Table 1 shows the results for ·bar·h).

[0053] <Quantum dot classification test> [Classification using porous membranes] The PbS quantum dot dispersion obtained in the production of the quantum dot dispersion described above was diluted 20 times with high-purity toluene. Next, the diluted PbS quantum dot dispersion was subjected to classification by internal pressure filtration using a polyamide hollow fiber membrane. Internal pressure filtration here refers to a method in which the quantum dot dispersion 2 is supplied from the other hollow portion of a hollow fiber polyamide microfiltration membrane 4, which has one end sealed with a jig 5, using a supply syringe 1 and injection needle 3, as shown in Figure 1.

[0054] [Classification using centrifugal separation] The reagents and classification procedure used for classification by centrifugation are shown below.

[0055] <Reagents> • Toluene (Super Dehydrated): For Organic Synthesis, 99.5%+%, manufactured by Wako. Ethanol (99.5%): EtOH, Ethanol (99.5%), Wako 1st Grade, 99.5+%, manufactured by Wako.

[0056] <Classification Procedure> 1) The PbS quantum dot dispersion was divided into 12 equal parts in centrifuge tubes, and each was centrifuged at 14,500 rpm for 3 minutes. 2) Discard the supernatant from each solution, add 0.5 mL of toluene (super-dehydrated) to the precipitate in each solution to disperse it, and then combine the two solutions into one. This reduces the number of centrifuge tubes from 0.5 mL x 12 to 1.0 mL x 6. 3) 1.0 mL of ethanol was added to each sample, and the samples were centrifuged at 14500 rpm for 3 minutes. 4) Discard the supernatant from each solution, disperse the precipitate in 0.5 mL of toluene (super-dehydrated), add 0.5 mL of ethanol, and centrifuge at 14500 rpm for 3 minutes. 5) Discard the supernatant from each sample, add 0.25 mL of toluene (super-dehydrated) to the precipitate to disperse it, and centrifuge at 14500 rpm for 1 hour. 6) The supernatant was collected using a micropipette and transferred to a glass container with a lid for storage. Following the above procedure, a PbS quantum dot dispersion was obtained by classification using centrifugation.

[0057] The particle size distribution (average particle size) of quantum dots was measured as follows. Specifically, the particle size and particle size distribution of quantum dots contained in the filtrate filtered through a porous membrane for quantum dot classification were measured using a transmission electron microscope (TEM). Specifically, the obtained filtrate was dropped onto a grid for transmission electron microscopy (Hi-Res Carbon HRC-C10 manufactured by Ouken Shoji Co., Ltd.), and the solvent was evaporated to prepare a sample for TEM observation. This was observed at a magnification of 1.5 million times using a JEOL Ltd. transmission electron microscope JEM-2100F, and an image was obtained. The major axis (maximum length) and minor axis (minimum length) of 30 to 100 quantum dots that did not overlap in the image (see Figure 4) were measured. The average of the measured major and minor axes was taken as the particle size of the measured quantum dots, and the sum of these particle sizes was divided by the number of measured quantum dots (total number of measurement data) to obtain the average particle size. Furthermore, the standard deviation was calculated using the STDEV.S function in Microsoft Excel, based on the particle size data of each measured quantum dot. The frequency of occurrence of quantum dots with each particle size was calculated by measuring the number of dots per 1 nm interval using the particle size data of each measured quantum dot, and then dividing each number by the total number of measured data points to calculate the frequency of occurrence for each particle size range.

[0058] The results of the quantum dot classification tests described above are shown in Table 1 and Figure 3.

[0059] [Table 1]

[0060] *Measured using 1:2-propanol *2: LMH: L / (m 2 ·bar·h)

[0061] In Examples 1-3, the standard deviation of the average particle size of the quantum dots after classification was 3.0 nm or less, demonstrating that the porous membrane for quantum dot classification of the present invention can be used in a novel quantum dot classification method. Furthermore, while Comparative Example 1 required four centrifugation steps for separation, Examples 1-3 achieved the above standard deviation with only one classification operation, demonstrating a simpler classification method.

[0062] In particular, in Examples 1 and 2, the burst bubble point of the porous membrane for quantum dot classification was 0.7 MPa or higher, which allowed for more favorable classification of quantum dots. Especially in Example 2, the porous membrane for quantum dot classification had a burst bubble point of 0.8 MPa or higher, and a dense layer (skin layer) was formed on the surface of at least one side, which made it easier to cut quantum dots in the range of 2 to 3 nm, allowing for even more favorable classification of quantum dots. [Explanation of symbols]

[0063] 1: Syringe for liquid supply 2: PbS quantum dot separation solution 3: Syringe needle 4: Hollow fiber membrane for quantum dot classification 5: Sealing jig 8: Air inlet 9: Regulator 10: Booster tank 11: Speed ​​Controller 12: Pressure sensor 13: Hollow fiber membrane minimodule 14: Glass container 15:2 Propanol Solution 16: Digital pressure display 17: Two-way valve 18: Module 18a: Hollow fiber membrane 18b: Tube filled with cured epoxy resin 19: Liquid transfer pump 20: Pressure gauge 21: Pressure relief valve 22: Saucer

Claims

1. A porous membrane for classifying quantum dots dispersed in an organic solvent, The porous membrane is formed from an uncrosslinked polyamide resin. A porous membrane for quantum dot classification, wherein the burst bubble point of the porous membrane is 0.7 MPa or higher.

2. The porous film has a dense layer formed on the surface of at least one of its faces, The porous membrane for quantum dot classification according to claim 1, wherein the burst bubble point of the porous membrane is 0.8 MPa or higher.

3. The porous membrane for quantum dot classification according to claim 1 or 2, wherein the shape of the porous membrane is a hollow fiber membrane shape.

4. A method for classifying quantum dots using a porous film for quantum dot classification described in any one of claims 1 to 3.

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