One-Pot Synthesis of Supertough, Sustainable Polyester Thermoplastic Elastomers Using Block-Like, Gradient Copolymer As Soft Midblock

CCS CHEMISTRY（2022）

Jilin Univ

Cited 28|Views6

Abstract

It remains challenging to synthesize supertough thermoplastic elastomers (TPEs) since the stretchability and tensile strength are mutually exclusive. Here, we report a one-pot strategy for the preparation of sustainable, triblock polyester TPEs consisting of poly(L-lactide) (PLLA) hard segments and poly(epsilon-caprolactone)-co-poly(delta-valerolactone) (PCVL) soft segments. The TPEs were synthesized successfully with high stretchability (up to 2100%) and strong tensile strength (up to 71.5 MPa) without requiring specific functionalized groups by simply adjusting the polymer microstructures, which, in turn, exhibited a world's record toughness of 445 MJ/m(3). Systematic investigation revealed that the block-like, gradient microstructure of PCVL improved the ductility by providing a flexible elastic network and enhancing the tensile strength through strain-induced crystallization. The practicability of this strategy was well demonstrated by lifting a water tank over 30,000 times heavier than itself and easy scale-up experiments. [GRAPHICS] .

Translated text

Key words

living polymerization,strain-induced crystallization,supertough,sustainable polyester,thermoplastic elastomers

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper

Data Disclaimer

The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn

Chat Paper

Summary is being generated by the instructions you defined