Fine-tuning optimization of poly lactic acid impact strength with variation of plasticizer using simple supervised machine learning methods

IF 2.7 3区化学 Q2 POLYMER SCIENCE

Express Polymer Letters Pub Date : 2023-01-01 DOI:10.3144/expresspolymlett.2023.71

J. F. Fatriansyah, E. Kustiyah, S. N. Surip, Andreas Federico, Agrin Febrian Pradana, A. S. Handayani, M. Jaafar, D. Dhaneswara

引用次数: 0

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使用简单监督机器学习方法对聚乳酸冲击强度随增塑剂变化进行微调优化

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Express Polymer Letters 化学-高分子科学

CiteScore

5.60

自引率

6.10%

发文量

审稿时长

1.9 months

期刊介绍： The main scope of eXPRESS Polymer Letters (Express Polym Lett; ISSN 1788-618X) is to provide a very fast first publication possibility related to the following topics: polymers; polymer composites; blends and alloys; nanomaterials; molecular engineering; tailor-made polymers; biodegradable and biocompatible polymers; smart materials; polymer gels and membranes; reinforcements and fillers; polymer processing technologies; rubbers and rubber technologies; interfaces, interphases and adhesion; thin layer technologies; material testing and properties; recycling; modeling and simulation.