Silica-modified reduced graphene oxide–based hydrogels derived from palm kernel shell for strain sensing: Characterization, computational analysis, and assistive application

Open

Munasir, Mohamad Fikri Aliansah, Nuhaa Faaizatunnisa, Muhammad Naufal Ariesta, Frizky Audis Paramundhita, Alya Arviyanti, Eva Tri Agustina, Aditya Prapanca, Markus Diantoro, Ahmad Taufiq

2026 Sensors International Vol. 7 Article Cited by 0

Abstract

Graphene-based hydrogels are promising candidates for motion-sensing applications in assistive technologies. However, conventional systems rely on expensive, non-renewable precursors, which limits scalability and sustainability. In this study, palm kernel shell waste was used as a renewable carbon source to synthesize reduced graphene oxide (RGO), which was subsequently functionalized with silica (RGS) to enhance hydrogel performance. The synthesis of RGO and RGS was optimized to achieve high yield, facile processing, and cost-effectiveness. Incorporation of silica-functionalized RGO improved dispersion, interfacial bonding, and the structural integrity of PVA hydrogels, enhancing mechanical durability and stability. Density Functional Theory (DFT) calculations were performed to elucidate the electronic properties and molecular interactions between PVA and filler supporting the experimental findings. The resulting strain sensor exhibited a high gauge factor (GF ≈ 9.5), fast response, and reliable detection of assistive motions. Furthermore, the device successfully recognized Indonesian Sign System (SIBI) gestures, demonstrating its potential as a sustainable, low-cost, and high-performance platform for assistive communication technologies. © 2026 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/

Affiliations

Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Surabaya, Kampus Ketintang, Surabaya, 60231, Indonesia; Department of Chemistry, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Jl. Arif Rahman Hakim, Kampus ITS Keputih-Sukolilo, Surabaya, 60111, Indonesia; Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Sebelas Maret (UNS), Surakarta, 57126, Indonesia; Department of Information Technology, Faculty of Engineering, Universitas Negeri Surabaya (UNESA), Kampus Unesa 1, Jl. Ketintang, Surabaya, 60231, Indonesia; Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Malang (UM), Indonesia, Jl. Semarang 5, Malang, 65145, Indonesia