Lg Chem, Ltd

Dae Sik Hong

Ki Soo Lee

Heon Yong Kwon

Eun Kyoung Song

Eun Young Shin

Yong Ho Lee

Hyun Jee Kwon

Sung Min Lee

Yi Young Choi

Se Young Kim

Yu Taek Sung

Young Suk You

Dong Hoon Jeong

Sung Ho Park

Sung Hyun Park

Kyung Jin Cho

Joong Soo Kim

Hyuck Ju Kwon

Oh Joo Kwon

Jin Young Lee

Myung Han Lee

Min Seok Cho

Sol Cho

Seung Mi Lee

Hyunsup Lee

Sang Jin Jeon

Soon Ho Sun

Yoon Ki Hong

Hyun Sup Lee

Seok Hwan Kim

Seong Min Chae

Hee Kwang Park

Ye Jin Lee

Taejin Kim

Hyeon-Gook Kim

Ki Heon Song

Ye Hoon Im

Jin Young Park

Dae Hwan Kim

Sun Mi Kim

Kyoung-Chan Lim

Man-Seong Jeon

Jong Sang Park

Chae Gyu Lee

Yu-Taek Sung

Seung Ki Park

Nak-Kyu Song

Woo Ri Kim

Chang-Hwan Jang

Si Yong Kim

Provided are a novel metallocene-supported catalyst and a method of preparing a polyolefin using the same. The metallocene-supported catalyst according to the present disclosure may be used in the preparation of polyolefins, it may have excellent activity and excellent reactivity with comonomers, and it may prepare olefinic polymers having a high molecular weight and a low molecular weight.

Metallocene-supported catalyst and method of preparing polyolefin using the same

The present disclosure provides an olefin polymer having excellent film processability and physical properties, and a preparation method of the same.

Olefin polymer and preparation method thereof

The present disclosure relates to a polypropylene for injection having a high content of ultra-high molecular weight and excellent rigidity, and a method for preparing the same.

Polypropylene and method for preparing the same

A method for evaluating long-term durability of a resin for piping is provided. Unlike the conventional FNCT evaluation method requiring a long period of time, the method disclosed herein is capable of predicting long-term durability of a resin for piping in a short time, by a simple calculation using a content of tie molecules, an entanglement molecular weight (M) and a content of ultrahigh molecular weight components. In addition, the olefinic polymer is configured to have a predetermined relationship in relation to the content of tie molecules, the entanglement molecular weight (M) and the content of ultrahigh molecular weight components, whereby the polymer of the present application can be used in the manufacture of a heating pipe requiring excellent long-term durability.

Method for predicting long-term durability of resin composition for piping and olefinic polymer used for resin for piping

The present application relates to a method for quantitative analysis of a polymer structure. Specifically, the method may be carried out through steps of measuring rheological properties and/or molecular weight distribution of the arbitrarily selected polymer, setting a random value for the selected polymer and then predicting the rheological property and/or the molecular weight distribution of the polymer from the random value, and comparing the measured value with the predicted value to determine the value of the structural parameter of the polymer.

Method for quantitative analysis of polymer structure and analyzer

The present invention provides a hybrid supported catalyst capable of easily preparing an olefin polymer capable of having improved melt strength even while having appropriate molecular weight distribution, and thus having improved bubble stability and exhibiting excellent blown film processability, and a method for preparing an olefin polymer using the same.

Hybrid supported catalyst

The present invention relates to a method for predicting the physical properties of polymers. More specifically, the present invention relates to a method for predicting the processability of polymers using a molecular weight distribution curve.

Method for predicting physical properties of polymers

The present disclosure provides a supported hybrid catalyst which facilitates the preparation of polyolefins having improved bubble stability and exhibiting excellent processability for a blown film while maintaining high transparent haze and improved melt strength, and a method for preparing the same.

Supported hybrid catalyst

The present disclosure relates to an assessment method for a polyethylene resin, and more specifically to a new assessment method for a polyethylene resin which can accurately determine long-term durability of a molded article by using physical properties that are easily measurable in a short time.

Assessment method for polyethylene resin

The present invention relates to an olefin polymer and a preparation method thereof. The olefin polymer exhibits excellent mechanical strength and high processability, and thus is expected to be utilized as a material for various products. Particularly, the olefin polymer can be stably produced into films by a melt-blowing process and thus is expected to be usefully used as a material for products prepared by a melt-blowing process.

The present invention relates to a supported hybrid catalyst and a method for preparing olefin polymer using the same. Using the supported hybrid catalyst, olefin polymer that maintains excellent mechanical strength of olefin polymer polymerized with the existing metallocene catalyst, but exhibits remarkably improved processibility compared to the existing olefin polymer, can be provided.

Supported hybrid catalyst and method for preparing olefin polymer using the same

The present invention relates to a method for predicting the physical properties of polymers. More specifically, the present invention relates to a method for predicting long-term stability of polymers using a molecular weight distribution curve.

The present invention provides a metallocene supported catalyst that can prepare a polyolefin having excellent transparency even when processed into a film, as well as excellent processibility and mechanical properties, with high catalytic activity, and a method for preparing a polyolefin using the same.

Metallocene supported catalyst and method for preparing polyolefin using the same

Growing community of inventors

Daejeon, South Korea

Dae Sik Hong