Method for predicting physical properties of rubber composition

Abstract

To provide a latex using a comprehensive analysis of the latex and a method for evaluating a rubber product to be obtained.SOLUTION: A method for predicting physical properties of a rubber composition includes: a process A of obtaining one or more analysis results selected from predetermined constituent molecules (1) to (154) in a latex composition as a test material; and a process B of predicting physical properties of a rubber composition obtained from the latex composition as the test material on the basis of the analysis results.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a method for predicting physical properties of a rubber composition.

[0002] The present invention relates to a method for evaluating a latex composition, and more particularly to a method for evaluating a latex composition using comprehensive mass analysis of constituent molecules of the latex composition, a method for selecting evaluation markers, and a method for predicting the quality and / or properties of a rubber composition using these evaluations. [Background technology]

[0003] Natural rubber is a rubber material produced primarily from the sap of the rubber tree (Hevea brasiliensis), known as latex (Non-Patent Document 1). Natural rubber is known to have superior mechanical properties compared to petroleum-derived synthetic rubber, and is used in a wide range of industries, including transportation equipment and medical care (Non-Patent Document 2). For example, natural rubber is used in the tires of large trucks and aircraft due to its excellent abrasion resistance and elasticity.

[0004] Natural rubber contains the main component cis-polyisoprene and non-rubber components such as proteins, sugars, lipids, etc. It has been reported that the non-rubber components include allergens (Non-Patent Document 3) and components that affect the viscosity and stability of solid natural rubber (Non-Patent Document 4). [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Mooibroek, H.; Cornish, K. Alternative Sources of Natural Rubber. Applied Microbiology and Biotechnology 2000,53(4),355-365.https: / / doi.org / 10.1007 / s002530051627. [Non-patent document 2] Toki, S.; Che, J.; Rong, L.; Hsiao, BS; Amnuaypornsri, S.; Nimpaiboon, A.; Sakdapipanich, J. Entanglements and Networks to Strain-Induced Crystallization and Stress-Strain Relations in Natural Rubber and Synthetic Polyisoprene at Various Temperatures.Macromolecules 2013, 46(13), 5238-5248. https: / / doi.org / 10.1021 / ma400504k. [Non-patent document 3] Yeang, HY; Arif, SAM; Yusof, F.; Sunderasan, E. Allergenic Proteins of Natural Rubber Latex. Methods 2002, 27(1), 32-45. https: / / doi.org / 10.1016 / S1046-2023(02)00049-X. [Non-patent document 4] Nimpaiboon,A.;Sriring,M.;Kumarn,S.;Sakdapipanich,J.Reducing and Stabilizing the Viscosity of Natural Rubber by Using Sugars:Interference of the Maillard Reaction between Proteins and Sugars.Journal of Applied Polymer Science 2020, 137(45), 49389. https: / / doi.org / 10.1002 / app.49389. Summary of the Invention [Problem to be solved by the invention]

[0006] However, the results of a comprehensive analysis of the components contained in rubber trees and their relationship to the product, natural rubber, are unknown.

[0007] An object of the present invention is to provide a method for evaluating latex and the resulting rubber products using comprehensive analysis of the latex. [Means for solving the problem]

[0008] The present invention provides the following: [1] Step A: obtaining analytical results of one or more of the constituent molecules (1) to (154) in the latex composition as a test substance; and Step B: predicting the physical properties of a rubber composition obtained from the latex composition as the test substance based on the analysis results; A method for predicting physical properties of a rubber composition, comprising: [2] The method according to [1], wherein the prediction of the physical properties in the step B is a prediction based on the results of an analysis of the relationship between the amount or presence or absence of constituent molecules in the latex composition as the standard substance and the physical properties of a rubber composition obtained from the latex composition as the standard substance. [3] The method according to [1] or [2], wherein the prediction of the physical properties in the step B is a prediction based on the amount or presence or absence of constituent molecules that have been confirmed to be correlated as a result of an analysis of the correlation between the amount or presence or absence of constituent molecules in the latex composition as the standard substance and the physical properties of the rubber composition obtained from the latex composition as the standard substance. [Effects of the Invention]

[0009] According to the present invention, comprehensive analysis of latex compositions can be utilized to evaluate latex compositions and the resulting rubber compositions. Therefore, the present invention can be utilized to select rubber compositions suitable for the latex composition and to select latex compositions as raw materials for rubber compositions having desired performance. Furthermore, the present invention enables the improvement of the physical properties of rubber compositions by adding predetermined components, which is useful for revitalizing the rubber industry and rubber manufacturing industry. [Brief explanation of the drawings]

[0010] [Figure 1]Figure 1 shows graphs plotting (a) the vulcanization properties of nine NR samples versus the content of fatty acid (heptadecenoic acid) (17:1) (59); (b) the tensile properties of nine rubber samples versus the content of CMP-N-acetylneuraminic acid salt (47); and (c) the heat aging properties of nine NR samples versus the content of 1-methylhistidine or 3-methylhistidine (19) and cis-4-hydroxyproline (43). In each graph, the horizontal axis indicates the collection date of the latex sample, which is the raw material for the NR sample (rubber composition). The dotted lines indicate the relative values ​​of the measured values ​​of each rubber sample, the solid lines indicate the relative values ​​of the measured values ​​of each compound for (a) and (b), and the relative value of cis-4-hydroxyproline for (c), and the long-dashed line for (c) indicates the relative values ​​of 3-methylhistidine and 1-methylhistidine. DETAILED DESCRIPTION OF THE INVENTION

[0011] The evaluation method of the latex composition includes the following steps A and B.

[0012] [1. Process A] Step A is a step of obtaining analytical results of one or more molecules selected from the following constituent molecules (1) to (154) in a latex composition as a test substance.

[0013] -Latex composition- The object of analysis in step A is a latex composition. In this specification, a latex composition is an aqueous dispersion derived from the sap of a rubber plant, and refers to a composition containing polymers, which are the so-called rubber components, as well as non-rubber components. An example of a rubber plant is a rubber tree (mainly Hevea brasiliensis). The latex composition may be the sap itself of the rubber plant, or it may be a processed sap (e.g., processed by adding a solvent, concentrating, etc.), and may contain additives such as coagulation inhibitors, preservatives, and stabilizers, as necessary.

[0014] -Constituent molecules- The constituent molecules analyzed in step A are the following (1) to (154). (1) 1,2-Distearoyl-glycero-3-phosphocholine (2) 10-Hydroxyoctadecanoic acid (3) 17α-Hydroxyprogesterone (4) 19-Methylarachidic acid and Heneicosanoic acid (5) 1-Deoxysphinganine (6) 1-Methyl-4-imidazoleacetic acid (7) 1-Methyladenosine (8) 1-Stearoyl-glycero-3-phosphocholine (9) 2-Aminoisobutyric acid; 2-Aminobutyric acid (10) 2-Deoxyribonic acid (11) 2-Hydroxyglutaric acid (12)2-Hydroxyisovaleric acid;2-Hydroxyvaleric acid (13) 2-Oxoglutaric acid (14)2-Oxoisovaleric acid (15) 3-Aminopropane-1,2-diol (16) 3-Aminopropionitrile (17) 3-Hydroxy-3-methylglutaric acid (18) 3-Hydroxytetradecanoic acid (19) 3-Methylhistidine; 1-Methylhistidine (20) 3-Nitropropionic acid (21) Uridine 3'-monophosphate (3'-UMP) (22) 3β-Hydroxy-5-cholestenoic acid (23) 4-Guanidinobutyric acid (24) 5-Hydroxylysine (25) 5-Methylcytosine (26) 5α-Cholestan-3-one (27) 6-Gingerol (28) 9s-Hydroxy-10E,12Z-octadecadienoic acid (9(S)-HODE) (29) Acylcarnitine (18:1) (Oleoylcarnitine; Acylcarnitine (18:1)) (30) Adenine (31) Adenylosuccinic acid (32) Arachidonoylethanolamide (AEA(20:3)) (33) Alanine (Ala) (34) Alanylalanine (Ala-Ala) (35) Allantoic acid (36) Allo-Threonine (37) Argininosuccinic acid (38) Betaine aldehyde hydrate (Betaine aldehyde + H2O) (39) Betonicine (40) Carboxymethyllysine (41) Carnitine (42) Cholesterol sulfate (43) cis-4-Hydroxyproline (44) cis-Aconitic acid (45) Citric acid (46) Citrulline (47) Cytidine monophosphate-N-acetylneuraminic acid (CMP-N-acetylneuraminate) (48) Cytidine (49) Ectoine (50) Eleutheroside B (51) Ethanolamine (52) Ethyl arachidonate (53) Ethylacetimidate (54)Fatty acid(12:0) (55)Fatty acid(14:2) (56)Fatty acid(14:3) (57)Fatty acid(15:1) (58)Fatty acid(16:2) (59)Fatty acid(17:1) (60)Fatty acid(17:2) (61)Fatty acid(17:3) (62)Fatty acid(19:2) (63) Fumaric acid (64) γ-aminobutyric acid (GABA) (65) Gibberellic acid (66) Glucaric acid (67) Glucosaminic acid (68) Glucose 1-phosphate (69) Glucosylceramide (d18:1 / 24:1) (70) Glutamylglutamic acid (Glu-Glu) (71) Glyceric acid (72) Glycerol 2-phosphate (73) Guanidoacetic acid (74) Guanine (75) Hercynine (76) Histamine (77) Hydroxyprogesterone caproate (78) Hydroxyproline (79) Hypotaurine (80) Isoleucine (Ile) (81) Imidazole-4-methanol (82) Indole-3-carboxaldehyde (83) Inosine (84) Isethionic acid (85) Lanosterol and Cycloartenol (86) Lauric acid (87) Linoleic acid (88) Linolenic acid and γ-linolenic acid (89) Lutein (90) Methionine (Met) (91) Methoxamine (92) Mucic acid (93) Myo-Inositol 2-phosphate (94) Myristic acid (95) N1-Acetylspermidine (96) N1-Methylguanosine (97) N5-Ethylglutamine (98) N6-Acetyllysine (99) N-Acetylglucosamine, N-Acetylgalactosamine, N-Acetylmannosamine (100) N-Acetylglucosylamine (101) N-Acetylornithine (102) N-Acetylserine (103) Nicotinamide (104) Nicotinic acid (105) N-Methylglutamic acid (106) Nω-Methylarginine (107) Octadecanedioic acid (108) Ophthalmic acid (109) Ornithine (110) Oxamic acid (111) Pantothenic acid (112) Pentadecanoic acid (113) Phenylalanine (Phe) (114) Phosphorylcholine (115) Piperidine (116) Proline (Pro) (117) Propionic acid (118) Putrescine (119) Pyruvic acid (120) Quinic acid (121) Riboflavin (122) Ribulose 5-phosphate (123) Saccharopine (124) S-Carboxymethylcysteine (125) Symmetric Dimethylarginine (SDMA) (126) Serine (Ser) (127) Spermidine (128) Sphinganine (129) Sphingomyelin (d18:1 / 18:0) (130) Stachydrine (131)Tartaric acid (132) Terephthalic acid (133) Testosterone acetate (134) Tetradecanedioic acid (135) Thiaproline (136) Threonate (137) trans-Glutaconic acid (138) Trigonelline (139) Trilaurin (140)Trimethylamine (141) Trimethylamine N-oxide (142) Tryptophan (Trp) (143) α-Tocopherol (144) β-Alanine (β-Ala) (145) β-Cryptoxanthin (146) β-Cyanoalanine (147) β-Estradiol (148) γ-Butyrobetaine (149) γ-Glutamylaspartic acid (γ-Glu-Asp) (150) γ-Glutamylhistidine (γ-Glu-His) (151) γ-Glutamylleucine and γ-Glutamylisoleucine (γ-Glu-Leu; γ-Glu-Ile) (152) γ-Glutamyl-S-Allylcysteine (153) γ-Glutamylthreonine (γ-Glu-Thr) (154) γ-Glutamylvalylglycine (γ-Glu-Val-Gly)

[0015] These are non-rubber components of the latex composition other than the polymer, which is the so-called rubber component. They can be classified into any of nucleic acids, lipids, proteins, peptides, amino acids, sugars, glycoproteins, their salts, metabolic intermediates, decomposition products, fragments, and trace metals. Based on their chemical structure, they can also be classified into carboxylic acids and derivatives, organic nitrogen compounds, fatty acyls, keto acids and derivatives, organic phosphoric acids and derivatives, glycerolipids, cinnamic acids and derivatives, peptidomimetics, pyrroles, organic carboxylic acids and derivatives, isoflavonoids, pyrimidine nucleosides, ribonucleoside 3'-phosphates, piperidines, steroids and derivatives, pyridine and its derivatives, glycerophospholipids, azoles, indoles and derivatives, phenols, sphingolipids, purine nucleosides, piperidines, sulfinic acids and their derivatives, prenol lipids, pteridines and derivatives, quinolines and derivatives, imidazopyrimidines, quinolines and derivatives, steroids and derivatives, hydroxy acids and derivatives, benzene and substituted derivatives, lactones, organic oxygen compounds, etc.

[0016] The object of analysis may be one or more selected from the above-mentioned constituent molecules, or a combination of two or more, and it is preferable that the object of analysis includes one or more constituent molecules that have been confirmed in advance to be correlated with the desired physical properties of the rubber composition, or that are predicted to be correlated with the desired physical properties of the rubber composition. When the subject of analysis is a combination of two or more constituent molecules, it is preferable that the constituent molecules are a combination of constituent substances belonging to the same classification (for example, as in the above classification examples).

[0017] -analysis- The analytical method is not particularly limited as long as it can quantify each of the above substances, and can be selected depending on the type of constituent molecule. Examples include mass spectrometry such as GC-MS, LC-MS, FAB-MS, EI-MS, CI-MS, FD-MS, MALDI-MS, ESI-MS, HPLC-MS, FT-ICR-MS, CE-MS, ICP-MS, Py-MS, and TOF-MS. Furthermore, when the constituent molecules are proteins or peptides, immunoassay methods (ELISA, RIA) using specific antibodies or aptamers can also be used. Furthermore, when the constituent molecules are sugars, methods using specific lectins can also be used. The analytical results do not need to be so-called raw data such as the content or content ratio of a specific constituent molecule, but can also be relative quantitative values ​​(e.g., peak height, area ratio).

[0018] [2. Process B] Step B is a step of predicting the physical properties of a rubber composition obtained from the latex composition as the test substance based on the analysis results obtained in step A.

[0019] -Prediction method- The prediction can be made based on the results of a prior analysis of a latex composition as a standard substance. The standard substance is a so-called test sample other than the test substance. The prediction based on the analysis of the latex composition as a standard substance can be made based on the results of an analysis of the relationship between the amount or presence or absence of constituent molecules in the latex composition as a standard substance and the physical properties of a rubber composition obtained from the latex composition as a standard substance.

[0020] -Rubber composition and its properties- The rubber composition is a processed product of a latex composition, and refers to any of raw rubber (coagulated rubber), master batch (kneaded rubber), and vulcanized rubber. The physical properties of the rubber composition may be any physical properties related to rubber compositions. Examples include vulcanization characteristics (processing stability), mechanical strength, heat aging resistance, heat resistance, cold resistance, aging resistance, ozone resistance, weather resistance, heat resistance, dielectric constant, chemical resistance, oil resistance, and water resistance. Of these, vulcanization characteristics, mechanical strength, and heat aging resistance are preferred.

[0021] The vulcanization characteristics can be obtained, for example, as Mooney scorch (Mooney viscosity (M1+3) 3 minutes after the start of rotation after 1 minute of preheating, minimum Mooney viscosity (Vm), scorch time st5 (the time when the viscosity increases by 5 units from Vm), scorch time st10 (the time when the viscosity increases by 10 units from Vm), st10-st5), maximum stress (MH) in the vulcanization curve, minimum stress (ML), s0.4 (the time when the stress increases by 0.4 units from ML), induction time (T10: the time when the stress reaches ML + (MH-ML) x 0.1), 50% vulcanization time (T50: the time when the stress reaches ML + (MH-ML) x 0.5), 90% vulcanization time (T90: the time when the stress reaches ML + (MH-ML) x 0.9), cure rate (T90-T10), time to reach MH (tMH), and time to reach ML (tML). The mechanical strength can be obtained, for example, as modulus (25% modulus, 50% modulus, 100% modulus, 200% modulus, 300% modulus), tensile strength (tensile stress), or elongation at break. The heat aging resistance can be obtained, for example, as strength (modulus, tensile strength, or elongation at break) after aging treatment (e.g., 85°C, 72 hours, 240 hours, or 500 hours).

[0022] -analysis- The analysis can be performed by known methods, such as machine learning, deep learning, supervised and unsupervised data analysis, and clustering techniques (e.g., multivariate analysis). Examples of multivariate analysis include multiple regression analysis, logistic regression analysis, principal component analysis, independent component analysis, factor analysis, discriminant analysis, quantification theory, cluster analysis, conjoint analysis, multidimensional scaling (MDS), partial least squares discriminant analysis (PLS-DA), random forest, decision tree, support vector machine (SVM), k-nearest neighbor analysis, naive Bayes, linear regression, polynomial regression, SVM for regression, k-means clustering, and hidden Markov model. Multiple regression analysis is preferred. For example, a linear multiple regression model (multiple regression equation) of information about a latex composition created from the amounts of each constituent molecule in the latex composition, which is a standard material, and the physical properties of the rubber composition obtained from the standard material can be used. Prior to the multiple regression analysis, the explanatory variables (quantitative numerical data obtained by metabolome analysis) and the response variables (physical property data of the rubber composition) may be standardized using an appropriate standardization method. The machine learning analysis can utilize one or more machine learning algorithms to correlate the results of the analysis of the constituent molecules contained in the latex composition with information about the latex composition. For example, an algorithm can be trained to receive the results of the analysis of the constituent molecules contained in the latex composition and output information about the latex composition.

[0023] -Prediction method- If the analysis results obtained as described above reveal that the rubber composition obtained from the test sample has good predetermined physical properties, and if the amount of one or more constituent molecules in the test sample is high (preferably significantly high), this can be used as a reference value. If the amount of the constituent molecules in the test substance is equal to or greater than the reference value, the rubber composition obtained from the test substance can be determined to have good physical properties. Alternatively, if the amount of the one or more constituent molecules is less than the reference value, the rubber composition obtained from the test substance can be determined to have poor physical properties. As another example, if the rubber composition obtained from the test sample has good predetermined physical properties, and some (e.g., two or more) of the physical properties are linked to the amount of a certain constituent molecule in the test sample, the amount of that constituent molecule can be used as a reference value. If the amount of the constituent molecule in the test substance is equal to or greater than the reference value, the rubber composition obtained from the test substance can be determined to have good physical properties. [Example]

[0024] The present invention will be described below with reference to examples, but the present invention is not limited to these examples.

[0025] Example 1 [Sampling and sample preservation] Latex was collected from multiple Hevea trees (10-20 years old, 15-20 trees) on a plantation in Thailand over a 10-day period between May 2022 and January 2023. The latex collected from each plant on each collection day was mixed to prepare nine samples, 1-9. These were divided into two groups: one for metabolite analysis and one for physical property testing. The former was used in this example, and the latter in Example 2. Ammonia was added to each sample to prevent coagulation, and the samples were transported domestically at ambient temperature. The samples used in this example were stored at -4°C until analysis. [Metabolome analysis] Metabolomic analysis was performed on nine samples. -Metabolite extraction for LC-TOFMS- Approximately 100 mg of each sample was placed in a homogenization tube with zirconia beads (5 mm diameter and 3 mm diameter). Next, 500 μL of 1% formic acid / acetonitrile containing 10 μM internal standard (H3304-1002, Human Metabolome Technologies, Inc. (HMT)) was added to the tube, and the sample was homogenized at 3,500 rpm for 60 minutes 20 times using a bead shaker (Micro Smash, MS-100R, TOMY DIGITAL BIOLOGY CO., LTD.) at 4°C for 60 minutes. After that, 67 μL of Milli-Q water was added to the mixture, and the mixture was homogenized at 3,500 rpm for 60 minutes 5 times at 4°C. The supernatant was then centrifuged at 9,100 × g for 120 min at 4 °C through a 3-kDa cutoff filter (NANOCEP 3K OMEGA, PALL Corporation) to remove macromolecules and further filtered using a hybrid SPE phospholipid cartridge (Hybrid SPE-Phospholipid 30 mg / mL, SUPELCO) to remove phospholipids. The filtrate was evaporated, dried under nitrogen, and reconstituted in 200 μL of 50% isopropanol for use in metabolomic analysis by Human Metabolome Technologies, Inc. (HMT).

[0026] -Metabolite extraction for CF-TOFMS- Approximately 100 mg of frozen tissue was placed in a homogenization tube with zirconia beads (5 mm diameter and 3 mm diameter). Next, 500 μL of MeOH containing 50 μM internal standard (H3304-1002, Human Metabolome Technologies, Inc. (HMT)) was added to the tube, and the tissue was homogenized at 3,500 rpm for 60 minutes 20 times using a bead shaker (Micro Smash, MS-100R, TOMY DIGITAL BIOLOGY CO., LTD.) at 4°C. After that, 400 μL of Milli-Q water was added and thoroughly mixed with the homogenate, followed by further homogenization at 2,300 rpm for 5 minutes at 4°C. Subsequently, 400 μL of the supernatant was centrifuged through a 5-kDa cutoff filter (UltrafreeMC-PLHCC, HMT0) at 9,100 × g for 120 min at 4 °C to remove macromolecules. The filtrate was evaporated, vacuum-dried, and reconstituted in 50 μL of Milli-Q water for metabolomic analysis at HMT.

[0027] -Metabolome analysis- Each sample was processed using CE-TOFMS and LC-TOFMS according to a dual scan package (UltrafreeMC-PLHCC, HMT). Specifically, CE-TOFMS analysis was performed using an Agilent CE capillary electrophoresis system (Agilent Technologies, Inc.) equipped with an Agilent 6210 time-of-flight mass spectrometer. LC-TOFMS analysis was performed using an Agilent 1200 HPLC pump (Agilent Technologies, Inc.) equipped with an Agilent 6210 time-of-flight mass spectrometer. The systems were controlled by Agilent G2201AA ChemStation software version B.03.01 for CE and MassHunter for LC (both Agilent Technologies, Inc.).

[0028] -Data Processing- The spectrometer was scanned from m / z 50 to 1,000, and peaks were extracted using MasterHands (Keio University) automated integration software to obtain peak information, such as m / z, peak area, and migration time for CE-TOFMS analysis and retention time for LC-TFMS analysis. Signal peaks corresponding to isotopic isomers, adducts, and other products of known metabolites were extracted, and the remaining peaks were annotated according to the HMT metabolite database based on m / z values ​​and Mt or RT. The areas of the annotated peaks were normalized to the internal standard and sample amount to obtain the relative levels of each metabolite. As a result, various compounds were detected. Among them, the following compounds (1) to (154) were selected from the viewpoint that they are registered in PubChem (a compound database). The analysis results (peak area ratios) of each compound are shown in the table below. The analysis results of these compounds are expected to be useful for evaluating latex compositions and rubber compositions.

[0029] [Table 1]

[0030] [Table 2]

[0031] [Table 3]

[0032] [Table 4]

[0033] [Table 5]

[0034] [Table 6]

[0035]

Table 7

[0036]

Table 8

[0037]

Table 9

[0038]

Table 10

[0039]

Table 11

[0040]

Table 12

[0041]

Table 13

[0042]

Table 14

[0043]

Table 15

[0044] Table 16

[0045] [Footnotes for Tables 1 to 16] "ND" means below the detection limit. The names of the compounds corresponding to each number are as follows: (1)1,2-Distearoyl-glycero-3-phosphocholine (2)10-Hydroxyoctadecanoic acid (3) 17α-Hydroxyprogesterone (4)19-Methylarachidic acid; Heneicosanoic acid (5) 1-Deoxysphinganine (6)1-Methyl-4-imidazoleacetic acid (7)1-Methyladenosine (8)1-Stearoyl-glycero-3-phosphocholine (9)2-Aminoisobutyric acid;2-Aminobutyric acid (10) 2-Deoxyribonic acid (11)2-Hydroxyglutaric acid (12)2-Hydroxyisovaleric acid;2-Hydroxyvaleric acid (13)2-Oxoglutaric acid (14)2-Oxoisovaleric acid (15)3-Aminopropane-1,2-diol (16)3-Aminopropionitrile (17)3-Hydroxy-3-methylglutaric acid (18)3-Hydroxytetradecanoic acid (19)3-Methylhistidine;1-Methylhistidine (20)3-Nitropropionic acid (21)3'-UMP (22)3β-Hydroxy-5-cholestenoic acid (23)4-Guanidinobutyric acid (24)5-Hydroxylysine (25)5-Methylcytosine (26)5α-Cholestan-3-one (27)6-Gingerol (28)9(S)-HODE (29)Acylcarnitine(18:1) (30)Adenine (31)Adenylosuccinic acid (32)AEA(20:3) (33)Ala (34)Ala-Ala;XC0145 (35)Allantoic acid (36)allo-Threonine (37)Argininosuccinic acid (38)Betaine aldehyde +H2O (39)Betonicine (40)Carboxymethyllysine (41)Carnitine (42)Cholesterol sulfate (43)cis-4-Hydroxyproline (44)cis-Aconitic acid (45)Citric acid (46)Citrulline (47)CMP-N-acetylneuraminat (48)Cytidine (49)Ectoine (50)Eleutheroside B (51)Ethanolamine (52)Ethyl arachidonate (53)Ethylacetimidate (54)Fatty acid(12:0) (55)Fatty acid(14:2) (56)Fatty acid(14:3) (57)Fatty acid(15:1) (58)Fatty acid(16:2) (59)Fatty acid(17:1) (60)Fatty acid(17:2) (61)Fatty acid(17:3) (62)Fatty acid(19:2) (63)Fumaric acid (64)GABA (65)Gibberellic acid (66)Glucaric acid (67)Glucosaminic acid (68)Glucose 1-phosphate (69)Glucosylceramide(d18:1 / 24:1) (70)Glu-Glu (71)Glyceric acid (72)Glycerol 2-phosphate (73)Guanidoacetic acid (74)Guanine (75)Hercynine (76)Histamine (77)Hydroxyprogesterone caproate (78)Hydroxyproline (79)Hypotaurine (80)Ile (81)Imidazole-4-methanol (82)Indole-3-carboxaldehyde (83)Inosine (84)Isethionic acid (85)Lanosterol;Cycloarteno (86)Lauric acid (87)Linoleic acid (88)Linolenic acid;γ-Linolenic acid (89)Lutein (90)Met (91)Methoxamine (92)Mucic acid (93)myo-Inositol 2-phosphate (94)Myristic acid (95)N1-Acetylspermidine (96)N1-Methylguanosine (97)N5-Ethylglutamine (98)N6-Acetyllysine (99)N-Acetylglucosamine;N-Acetylgalactosamine;N-Acetylmannosamine (100)N-Acetylglucosylamine (101)N-Acetylornithine (102)N-Acetylserine (103)Nicotinamide (104)Nicotinic acid (105)N-Methylglutamic acid (106)Nω-Methylarginine (107)Octadecanedioic acid (108)Ophthalmic acid (109)Ornithine (110)Oxamic acid (111)Pantothenic acid (112)Pentadecanoic acid (113)Phe (114)Phosphorylcholine (115)Piperidine (116)Pro (117)Propionic acid (118)Putrescine (119)Pyruvic acid (120)Quinic acid (121)Riboflavin (122)Ribulose 5-phosphate (123)Saccharopine (124)S-Carboxymethylcysteine (125)SDMA (126)Ser (127)Spermidine (128)Sphinganine (129)Sphingomyelin(d18:1 / 18:0) (130)Stachydrine (131)Tartaric acid (132)Terephthalic acid (133)Testosterone acetate (134)Tetradecanedioic acid (135)Thiaproline (136)Threonic acid (137)trans-Glutaconic acid (138)Trigonelline (139)Trilaurin (140)Trimethylamine (141)Trimethylamine N-oxide (142)Trp (143)α-Tocopherol (144)β-Ala (145)β-Cryptoxanthin (146)β-Cyanoalanine (147)β-Estradiol (148)γ-Butyrobetaine (149)γ-Glu-Asp (150)γ-Glu-His (151)γ-Glu-Leu;γ-Glu-Ile (152)γ-Glutamyl-S-Allylcysteine (153)γ-Glu-Thr (154)γ-Glu-Val-Gly

[0046] Example 2 [Physical property analysis of NR samples and association with metabolites] A preservative (Bestside-500, Nippon Soda Co., Ltd.) was added to the samples for physical property testing, which were prepared as described at the beginning of Example 1 and shipped domestically. The samples were then stored at room temperature until testing. The rubber physical properties were analyzed using the following procedure.

[0047] - NR sample preparation - The sample was diluted with purified water to a specific total solids concentration, then added to sodium dodecyl sulfate (SDS) to prevent coagulation of the latex during drying, and the mixture was stirred. The mixture was dried at 180 °C to prepare an NR sample (without additives). After drying, the sample was kneaded with sulfur, sulfenamide accelerator, stearic acid, naphthenic oil, antioxidant, and carbon black to prepare two types of additive-added NR samples (additive-added NR sample and NR sample containing at least carbon black).

[0048] -Measurement of physical properties- (Vulcanization characteristics) For vulcanization properties, Mooney viscosity measurements and curing tests were carried out in accordance with JIS K6300-1 and K6300-2 as follows.

[0049] The Mooney viscosity was measured using a Mooney viscometer (AM-4, manufactured by Toyo Seiki Seisakusho, Ltd.) at 121°C with an L-shaped rotor.

[0050] The curing test was carried out using a rotorless rheometer (RLR-4 model, manufactured by Toyo Seiki Seisakusho) at a temperature of 150°C, a stress range of 200 kgf·cm, and an amplitude angle of ±3°. One piece per sample was tested.

[0051] (Tensile properties) The tensile properties were measured in accordance with JIS K6251 as follows. Using an automatic rubber tensile tester (Strograph AE Elastomer, manufactured by Toyo Seiki Seisakusho), the tensile test was carried out at a tensile speed of 500 mm / min with a dumbbell shape of No. 5. Three samples were measured, and the median value was taken.

[0052] (Heat aging resistance) The heat aging resistance was measured in accordance with JIS K6257 and K6251 as follows. The specimens were aged in air at 85°C for 72, 240, and 500 hours. After aging, tensile tests were performed using an automatic rubber tensile tester or a tensile / compression tester (Technograph TGI-1kN, manufactured by MinebeaMitsumi Inc.) depending on the specimen conditions. Three specimens per specimen were tested, and the median value was taken. The measurement items for each test are listed in Table S3.

[0053] [Relationship between metabolites and rubber properties] To account for the potential influence of metabolites selected in the sequential selection model on each property, correlation coefficients between metabolites and NR properties were calculated, and the relative quantitative values ​​of metabolites and NR properties were standardized. Because some metabolites did not follow a normal distribution, Spearman's rank correlation coefficients were calculated between all metabolites and properties. A heat map of the correlation coefficient matrix was created, revealing that vulcanization, tensile, and heat aging properties represented three different types of evaluation. Therefore, we investigated whether the correlations with metabolites differed for these three properties. The correlation coefficients for vulcanization, tensile, and heat aging properties were grouped and compared across the three groups. Metabolites, including some of the compounds (1)–(154) listed above, had mean values ​​in at least one group that were significantly different from the other properties, suggesting their possible involvement in these properties.

[0054] [Association between NR properties and metabolites] -Creating a multiple regression model- For each measurement item of characteristics, a combination of different metabolites was used as explanatory variables, and five metabolites that minimized the regression error of the model were selected using the stepwise forward floating selection (SFFS) method for each measurement as explanatory variables, and a linear multiple regression model and a stepwise selection model were created using these.Comparison of root mean square error / interquartile range (RMSE / IQR), etc., confirmed that the created model enabled analysis with sufficient regression accuracy.

[0055] -Association of NR characteristics with metabolite categories- Using the above model, we correlated metabolite categories (further classified by molecular structure) in latex samples with NR properties. Among the selected metabolite categories (Tables 17-26), "carboxylic acids and derivatives," "organic nitrogen compounds," and "fatty acyls" ranked in the top three for all properties (vulcanization, tensile, and heat aging), accounting for over 50% of the total. Furthermore, "keto acids and derivatives," "organic phosphoric acids and derivatives," and "glycerolipids" were only observed in vulcanization properties. "cinnamic acids and derivatives" and "peptidomimetics" were only observed in tensile properties. "sulfinic acids and derivatives," "pyrroles," "organic carboxylic acids and derivatives," and "isoflavonoids" were only observed in heat aging properties.

[0056] [Table 17]

[0057] [Table 18]

[0058] [Table 19]

[0059] [Table 20]

[0060] [Table 21]

[0061] [Table 22]

[0062] [Table 23]

[0063] [Table 24]

[0064] [Table 25]

[0065] [Table 26]

[0066] -Associating NR characteristics with individual metabolites- To investigate the possibility that the metabolites selected in the sequential selection model (including metabolites (1)–(154)) might affect each trait, the amounts and NR traits of up to five components for each measurement item were examined, and the metabolites with the greatest overlap between the amounts and the relative merits of each trait were identified.

[0067] Regarding cure properties, the fatty acid (heptadecenoic acid) (17:1) (59) showed the highest overlap, appearing four times among the cure properties (Figure 1(a)). The observed association with improved cure properties was completely unexpected, despite the fact that heptadecenoic acid (17:1) has a structure different from that of common accelerators and retarders for NR.

[0068] Regarding tensile properties, CMP-N-acetylneuraminic acid (47) showed the highest overlap, appearing seven times (Figure 1(b)). CMP-N-acetylneuraminic acid is a completely different compound from additives such as carbon black, which are generally added to rubber to improve its tensile properties. The observed relationship with improved tensile properties was a completely unexpected result. Because plants do not produce CMP-N-acetylneuraminic acid or N-acetylneuraminic acid, the detected CMP-N-acetylneuraminic acid is likely a contaminant. However, it has been revealed that it contributes to the tensile properties of NR rubber as a component.

[0069] Regarding heat aging properties, the overlap between 1-methylhistidine or 3-methylhistidine (19) and cis-4-hydroxyproline (43) was the highest, appearing four times (Figure 1(c)). Both are completely different compounds from the antioxidants generally added to improve the heat aging properties of rubber, and yet the observed relationship with improved heat aging properties was a completely unexpected result.

[0070] The results of the above examples show that the present invention makes it possible to predict the physical properties and performance of rubber products obtained from the analysis results of the constituent molecules of latex.

Claims

1. Step A: A step of obtaining analytical results of one or more of the following constituent molecules in a latex composition as a test substance; and Step B: predicting the physical properties of a rubber composition obtained from the latex composition as the test substance based on the analysis results; A method for predicting physical properties of a rubber composition, comprising: (1) 1,2-Distearoyl-glycero-3-phosphocholine (2) 10-Hydroxyoctadecanoic acid (3) 17α-Hydroxyprogesterone (4) 19-Methylarachidic acid and Heneicosanoic acid (5) 1-Deoxysphinganine (6) 1-Methyl-4-imidazoleacetic acid (7) 1-Methyladenosine (8) 1-Stearoyl-glycero-3-phosphocholine (9) 2-aminoisobutyric acid; 2-aminobutyric acid (10) 2-Deoxyribonic acid (11) 2-Hydroxyglutaric acid (12) 2-Hydroxyisovaleric acid; 2-Hydroxyisovaleric acid; (13) 2-Oxoglutaric acid (14) 2-Oxoisovaleric acid (15) 3-amino-1,2-propanediol (16) 3-aminopropionitrile (17) 3-Hydroxy-3-methylglutaric acid (18) 3-Hydroxytetradecanoic acid (19) 3-Methylhistidine; 1-Methylhistidine (20) 3-Nitropropionic acid (21) Uridine 3'-monophosphate (3'-UMP) (22) 3β-Hydroxy-5-cholestenoic acid (23) 4-Guanidinobutyric acid (24) 5-Hydroxylysine (25) 5-Methylcytosine (26) 5α-Cholestan-3-one (27) 6-Gingerol (28) 9s-Hydroxy-10E,12Z-octadecadienoic acid (9(S)-HODE) (29) Acylcarnitine (18:1) (oleoylcarnitine; Acylcarnitine (18:1)) (30) Adenine (31) Adenylosuccinic acid (32) Arachidonoylethanolamide (AEA (20:3)) (33) alanine (Ala) (34) Alanylalanine (Ala-Ala) (35) Allantoic acid (36) allo-Threonine (37) Argininosuccinic acid (38) Betaine aldehyde hydrate (Betaine aldehyde + H ２ O) (39) Betonicine (40) Carboxymethyllysine (41) Carnitine (42) Cholesterol sulfate (43) cis-4-Hydroxyproline (44) cis-Aconitic acid (45) Citric acid (46) Citrulline (47) Cytidine monophosphate-N-acetylneuraminic acid (CMP-N-acetylneuraminate) (48) Cytidine (49) Ectoine (50) Eleutheroside B (51) Ethanolamine (52) Ethyl arachidonate (53) Ethyl acetimidate (54) Fatty acid (12:0) (55) Fatty acid (14:2) (56) Fatty acid (14:3) (57) Fatty acid (15:1) (58) Fatty acid (16:2) (59) Fatty acid (17:1) (60) Fatty acid (17:2) (61) Fatty acid (17:3) (62) Fatty acid (19:2) (63) Fumaric acid (64) γ-aminobutyric acid (GABA) (65) Gibberellic acid (66) Glucaric acid (67) Glucosamine acid (68) Glucose 1-phosphate (69) Glucosylceramide (d18:1 / 24:1) (70) Glutamylglutamic acid (Glu-Glu) (71) Glyceric acid (72) Glycerol 2-phosphate (73) Guanidoacetic acid (74) Guanine (75) Hercynine (76) histamine (77) Hydroxyprogesterone caproate (78) Hydroxyproline (79) Hypotaurine (80) isoleucine (Ile) (81) Imidazole-4-methanol (82) Indole-3-carboxaldehyde (83) Inosine (84) Isethionic acid (85) Lanosterol and Cycloartenol (86) Lauric acid (87) Linoleic acid (88) Linolenic acid and γ-linolenic acid (89) Lutein (90) methionine (Met) (91) methoxamine (92) Mucic acid (93) myo-inositol 2-phosphate (94) Myristic acid (95) N1-Acetylspermidine (96) N1-Methylguanosine (97) N5-Ethylglutamine (98) N6-acetyllysine (99) N-acetylglucosamine, N-acetylgalactosamine, N-acetylmannosamine (N-acetylglucosamine; N-acetylgalactosamine; N-acetylmannosamine) (100) N-acetylglucosylamine (101) N-acetylornithine (102) N-Acetylserine (103) Nicotinamide (104) Nicotinic acid (105) N-Methylglutamic acid (106) Nω-Methylarginine (107) Octadecanedioic acid (108) Ophthalmic acid (109) Ornithine (110) Oxamic acid (111) Pantothenic acid (112) Pentadecanoic acid (113) Phenylalanine (Phe) (114) Phosphorylcholine (115) Piperidine (116) Proline (Pro) (117) Propionic acid (118) Putrescine (119) Pyruvic acid (120) Quinic acid (121) Riboflavin (122) Ribulose 5-phosphate (123) Saccharopine (124) S-Carboxymethylcysteine (125) Symmetric dimethylarginine (SDMA) (126) Serine (Ser) (127) Spermidine (128) Sphinganine (129) Sphingomyelin (d18:1 / 18:0) (130) Stachydrine (131) Tartaric acid (132) Terephthalic acid (133) Testosterone acetate (134) Tetradecanedioic acid (135) Thiaproline (136) Threonic acid (137) trans-Glutaconic acid (138) Trigonelline (139) Trilaurin (140) Trimethylamine (141) Trimethylamine N-oxide (142) tryptophan (Trp) (143) α-Tocopherol (144) β-alanine (β-Ala) (145) β-Cryptoxanthin (146) β-Cyanoalanine (147) β-Estradiol (148) γ-Butyrobetaine (149) γ-Glutamylaspartic acid (γ-Glu-Asp) (150) γ-Glutamylhistidine (γ-Glu-His) (151) γ-Glutamylleucine and γ-glutamylisoleucine (γ-Glu-Leu; γ-Glu-Ile) (152) γ-Glutamyl-S-allylcysteine (153) γ-Glutamylthreonine (γ-Glu-Thr) (154) γ-Glutamylvalylglycine (γ-Glu-Val-Gly)

2. 2. The method according to claim 1, wherein the prediction of the physical properties in the step B is a prediction based on a result of an analysis of a relationship between the amount or presence or absence of constituent molecules in a latex composition as a standard substance and the physical properties of a rubber composition obtained from the latex composition as a standard substance.

3. 3. The method according to claim 1 or 2, wherein the prediction of the physical properties in the step B is a prediction based on the amount or presence or absence of constituent molecules confirmed to be correlated as a result of an analysis of the correlation between the amount or presence or absence of constituent molecules in the latex composition as the standard substance and the physical properties of the rubber composition obtained from the latex composition as the standard substance.

Images