LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Machine learning-assisted optimization of TBBPA-bis-(2,3-dibromopropyl ether) extraction process from ABS polymer.

Photo by firmbee from unsplash

The increasing amount of e-waste plastics needs to be disposed of properly, and removing the brominated flame retardants contained in them can effectively reduce their negative impact on the environment.… Click to show full abstract

The increasing amount of e-waste plastics needs to be disposed of properly, and removing the brominated flame retardants contained in them can effectively reduce their negative impact on the environment. In the present work, TBBPA-bis-(2,3-dibromopropyl ether) (TBBPA-DBP), a novel brominated flame retardant, was extracted by ultrasonic-assisted solvothermal extraction process. Response Surface Methodology (RSM) achieved by machine learning (support vector regression, SVR) was employed to estimate the optimum extraction conditions (extraction time, extraction temperature, liquid to solid ratio) in methanol or ethanol solvent. The predicted optimum conditions of TBBPA-DBP were 96 min, 131 mL g-1, 65 °C, in MeOH, and 120 min, 152 mL g-1, 67 °C in EtOH. And the validity of predicted conditions was verified.

Keywords: extraction; extraction process; tbbpa; bis dibromopropyl; tbbpa bis; dibromopropyl ether

Journal Title: Chemosphere
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.