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Computational molecular engineering for the development of durable and high-perfornamce plasticizers

Computational molecular engineering for the development of durable and high-perfornamce plasticizers
用于开发耐用高性能增塑剂的计算分子工程
批准号:
514051-2017
负责人:
Xi, Li
金额:
$2.91万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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中文摘要
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英文摘要
Plastic materials are essentially mixtures of polymers with various additives introduced to adjust theirproperties and appearance. Plasticizers are an important class of additives used to make the polymers easier toflow during its processing and make the material more flexible in the final product. The most widely usedplasticizers belong to a family of chemicals called phthalates which, despite their strong plasticization efficacy,tend to migrate out of the host material over time. This not only causes the material performance to deterioratebut also contaminates the surrounding materials and the environment. Recent research has suggested potentialsafety risks of phthalates, leading to tightening regulation of these substances around the globe. The plasticindustry is under pressure to phase out phthalates and find alternatives. As a leading producer of plastic fabricsand films based in Ontario, CGT is increasing its effort in developing green plasticizers. The proposed projectwill use multiscale molecular modeling and computer simulation to further our understanding of the molecularmechanism of plasticization and plasticizer stability. Based this knowledge, molecular features important forplasticizer efficiency and stability will be identified. Predictions will be compared with experimental resultsfrom CGT and quantitative models will be developed for the a priori prediction of plasticizer performancebased on chemical structures. The model will help CGT screen large pools of plasticizer designs to selectpromising candidates for further testing, with which the experimental cost can be reduced and the developmentcycle shortened. Experience and know-how accumulated through the project will also put us at the forefront ofthe ongoing paradigm shift around the world in material innovation, which increasingly relies on computationalmolecular engineering and data science.
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