Fitri Afriani, Yuant Tiandho, Aan Priyanto, William Xaveriano Waresindo, Dhewa Edikresnha, Fenny Martha Dwivany, Dian Ahmad Hapidin, Khairurrijal Khairurrijal
This study introduces an innovative method for fabricating glucomannan/PEO nanofibers using rotary force spinning (RFS) and enhances RFS efficiency through response surface methodology (RSM) and machine learning. Various machine learning models were tested, with the artificial neural network (ANN) model showing the highest predictive accuracy. The analysis identified polymer concentration, nozzle diameter, and spinneret angular speed as critical factors influencing fiber diameter. The integration of RSM and ANN provided a comprehensive understanding of glucomannan/PEO nanofiber synthesis. Process optimization achieved nanofibers with a diameter of 253.52 nm, advancing the understanding and optimization of glucomannan/PEO nanofiber synthesis. © 2024 Elsevier B.V.
Department of Physics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesa 10, Bandung, 40132, Indonesia; Department of Physics, Faculty of Science and Engineering, Universitas Bangka Belitung, Kampus Terpadu UBB, Bangka, 33172, Indonesia; Department of Biology, School of Life Sciences and Technology, Institut Teknologi Bandung, Jalan Ganesa 10, Bandung, 40132, Indonesia; Center for Green and Sustainable Materials, Institut Teknologi Sumatera, Jalan Terusan Ryacudu, Way Huwi, Lampung, 35365, Indonesia; Department of Physics, Faculty of Science, Institut Teknologi Sumatera, Jalan Terusan Ryacudu, Way Huwi, Lampung, 35365, Indonesia
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