Mechanical Property Prediction of Poly(Lactic Acid) Blends Using Deep Neural Network

Jaka Fajar Fatriansyah, Siti Norasmah Surip, Fernanda Hartoyo

Research output: Contribution to journalArticlepeer-review

Abstract

Physical blending is one of the method to control and improve the mechanical properties of polymer such as Poly(lactic acid) or known as PLA. However, the phenomenological theory or model to connect the structure and properties of PLA blend is not available. Thus, in order to predict the mechanical property from structure is based on many trial experiments. In this study, Deep Learning Network (DNN) was employed to predict the yield strength of PLA blend based on its structure information: blending composition, molecular weight, melting point and density of polymer. It was demonstrated that DNN can successfully predict the mechanical property from structure information of PLA blends although the accuracy could be further improved.

Original languageEnglish
Pages (from-to)141-144
Number of pages4
JournalEvergreen
Volume9
Issue number1
DOIs
Publication statusPublished - 2022

Keywords

  • Deep Neural Network
  • Machine Learning
  • Poly(lactic acid)
  • Polymer
  • Polymer blend

Fingerprint

Dive into the research topics of 'Mechanical Property Prediction of Poly(Lactic Acid) Blends Using Deep Neural Network'. Together they form a unique fingerprint.

Cite this