A method of forming the composite body can comprise forming a first extrudate and a second extrudate, wherein the first extrudate comprises an organic polymer and ceramic particles, the ceramic particles including hexagonal boron nitride (hBN) particles; combining the first extrudate and the second extrudate to form a composite body including two layers; conducting a layer multiplying procedure on the composite body, the layer multiplying procedure comprising dividing and recombining the composite body to form a multi-layer composite body.

This disclosure relates to a novel type of high molecular weight polyethylene composition, and product made from said composition, with industrially useful properties, and the process of making said composition and product.

This invention is to improve the reaction efficiency of a peroxide introduced into a cylinder compared with conventional art. In the peroxide reaction method and peroxide reaction device using an extruder according to this invention, in which a peroxide and a raw material such as a synthetic resin, a natural resin, and an elastomer are introduced into a cylinder of the extruder, wherein the raw material and the peroxide are reacted with each other in the cylinder, the raw material is introduced from a raw material supply hopper, the peroxide is introduced from a downstream side of the raw material supply hopper, and the temperature of the raw material in a peroxide introduction portion is adjusted to a temperature lower than the one-minute half-life temperature of the peroxide.

A fluoroelastomer composition, and a crosslinked fluoroelastomer obtained by crosslinking the fluoroelastomer composition. The fluoroelastomer composition contains 10 to 60 parts by mass of a carbon black (B) and 0.1 to 10 parts by mass of a peroxide cross-linking agent (C) per 100 parts by mass of a peroxide-crosslinkable fluoroelastomer (A). The carbon black (B) has a number of foreign particles of 30/mm.sup.2 or less measured as described herein.

Provided is an automatic continuous weighing/raw material supply system of a flooring tile manufacturing apparatus, and more particularly to an automatic continuous weighing/raw material supply system of a flooring tile manufacturing apparatus, which can stably supply a raw material to the flooring tile manufacturing apparatus.

A graphene reinforced polyethylene terephthalate composition is provided for forming graphene-PET containers. The graphene reinforced polyethylene terephthalate composition includes a continuous matrix comprising polyethylene terephthalate and a dispersed reinforcement phase comprising graphene nanoplatelets. The graphene nanoplatelets range in diameter between 5 m and 10 m with surface areas ranging from about 15 m.sup.2/g to about 150 m.sup.2/g. In some embodiments, the graphene reinforced polyethylene terephthalate comprises a concentration of graphene nanoplatelets being substantially 3% weight fraction of the graphene reinforced polyethylene terephthalate. The graphene reinforced polyethylene terephthalate is configured to be injection molded into a graphene-PET preform suitable for forming a container. The graphene-PET preform is configured to be reheated above its glass transition temperature and blown into a mold so as to shape the graphene-PET preform into the container.

A mixer control device having a function of a monitoring device acquires measurement data of monitoring target information that is obtained through measurement when a rubber material is kneaded by a mixer. In addition, the mixer control device compares the measurement data and reference data that is selected in past measurement data of the monitoring target information and performs abnormality determination. The mixer control device acquires measurement data that is measured from predetermined mixing operation initiation timing in a series of mixing operations of a rubber material in the mixer for every unit of the series of mixing operation.

This disclosure is to provide a method of manufacturing a rubber composition comprising kneading a rubber composition that includes 100 parts by mass (pbm) of a rubber component (A) including 50 mass % or more of natural rubber, 5-50 pbm of at least one kind of thermoplastic resin (B) selected from among C5-based resins, C5-C9-based resins, C9-based resins, terpene-based resins, terpene-aromatic compound-based resins, rosin-based resins, dicyclopentadiene resins, and alkylphenol-based resins; 20-120 pbm of a filler (C) including silica; at least one kind of vulcanization accelerator (D) selected from among guanidines, sulfenamides, thiazoles, thiourea and diethyl thiourea; a silane coupling agent (E); and a vulcanizing agent (F). The kneading comprises a kneading stage A for kneading components (A)-(C), part or all of component (D), and 2 pbm or more of component (E), and a kneading stage B for kneading component (F) with a kneaded product of the kneading stage A.

In the field of tire production, the invention relates to methods and systems for creating unvulcanized rubber batches prior to mixing them in a rubber mixer, including selecting at least one batch for mixing in the mixer, wherein each batch corresponds to a selection of rubber bales (A.sub.I, B.sub.I, C.sub.I) each corresponding to a rubber nature (A, B, C) having predefined characteristics, in order to obtain a proportion corresponding to a predetermined proportion, a target weight to attain a difference between (a) the required weight of the batch and (b) the sum of the weight of the bales (A.sub.I, B.sub.I, C.sub.I) and the weight of the pieces (A.sub.IJ, B.sub.IJ, C.sub.IJ).

The measured value of a rubber temperature parameter that is related to the temperature of a rubber material to be kneaded by a mixing machine 2 and measured values of correlation parameters that have a correlation with a change in the value of the rubber temperature parameter are acquired. The measured values are assigned to an operational control parameter-calculation model equation, which is modified from a rubber temperature parameter-calculation model equation including operational control parameters and the correlation parameters, and a constant and coefficients of the operational control parameters and the correlation parameters are calculated using a machine learning algorithm. A predetermined operational control parameter, which is required in a case in which the rubber temperature parameter is controlled to a predetermined value, is calculated using an operational control parameter-calculation equation that is specified by the coefficients and the constant calculated using the machine learning algorithm.