Assessment of Hot-Water-Alkali Treated Bagasse Fiber in Metakaolin-Based Geopolymer Using Machine Learning

Aug 5, 2026

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Study develops metakaolin-based geopolymers reinforced with sugarcane bagasse fiber and quantifies how hot-water-alkali pretreatment changes composite performance. Bagasse fiber is pretreated with hot water and sodium hydroxide, then incorporated into metakaolin matrices at 0%, 3%, 4%, and 5% fiber by weight. Mechanical properties and water absorption are measured, while SEM and FTIR verify surface modification via impurity removal and increased roughness, improving fiber–matrix bonding. Compressive strength and splitting tensile strength improve with reduced water uptake. Machine learning models (random forest, AdaBoost, XGBoost) predict splitting tensile strength, with XGBoost achieving highest accuracy (R²=0.95, MAE=0.28).

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages16

Reading Time40 min

AccessFree to download

Abstract

Introduction

Cementitious material innovation and sustainability

Geopolymer binder and metakaolin precursor

Agricultural waste valorization and bagasse fiber

Limitations of bagasse fiber and fiber treatment methods

Materials and Methods

Fiber pretreatment and mix design

Mechanical properties and water absorption tests

Characterization: SEM, FTIR, and microscopy

Machine learning for splitting tensile strength prediction

Assessment of Hot-Water-Alkali Treated Bagasse Fiber in Metakaolin Based Geopolymer Using Machine Learning Fransiskus Xaverius Maradona Manteiro 1, Tavio 1,*, Hosta Ardhyananta2 1Department of Civil Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia 2Department of Materials and Metallurgical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia Received 03 October 2025; received in revised form 08 December 2025; accepted 19 December 2025 DOI: [https://doi.org/10.46604/aiti.2026.15755](https://doi.org/10.46604/aiti.2026.15755) Abstract This study aims to develop metakaolin-based geopolymers reinforced with sugarcane bagasse fiber (BF) and to evaluate the effect of BF treatment on the composite's performance. The BF is pretreated with hot water and sodium hydroxide before being incorporated into the geopolymer matrix. Metakaolin-based geopolymer specimens containing 0%, 3%, 4%, and 5% BF by weight are prepared, and their mechanical properties and water absorption are analyzed. Scanning electron microscopy and Fourier transform infrared spectroscopy analyses reveal that the combined hot-water-alkali treatment significantly modifies the fiber surface. The treatment removes impurities and increases surface roughness, thereby enhancing fiber–matrix bonding. As a result, this treatment improves compressive and splitting tensile strength (STS) while reducing water absorption compared to untreated BF. Furthermore, machine learning algorithms, including random forest, AdaBoost, and XGBoost, are applied to predict STS. Among the three models, XGBoost demonstrates the highest predictive accuracy (R^² = 0.95, MAE = 0.28), indicating reliable predictions of mechanical strength. Keywords: geopolymer, metakaolin, bagasse fiber, hot-water-alkali treatment, machine learning. 1. Introduction Efforts have been made to introduce innovative cementitious materials to improve the performance of structural concrete. These advances leverage advancements in material technology and are primarily driven by the need to enhance mechanical properties, reduce self-weight, increase durability, and minimize the environmental impact of conventional cement-based materials. Consequently, researchers explored various approaches, including material modification, alternative constituents, and reinforcement techniques to achieve higher performance and more sustainable concrete systems [1-2] . In recent years, further innovation has focused on reducing the environmental footprint of concrete materials by replacing ordinary Portland cement with alternative binders. Geopolymer is a concrete mixture based on a non-cementitious binder containing silica (Si) and aluminum (Al) . This binder requires less energy to produce than Portland cement. For example, 1 ton of geopolymer binder generates 0.184 tons of carbon dioxide (CO2), compared to 1 ton from portland cement. Metakaolin (MK), a pozzolanic material obtained by calcining kaolin at high temperatures to particles smaller than 5 µm [1], is commonly used as a precursor. Sodium silicate (Na₂SiO₃) and sodium hydroxide (NaOH) are generally used as alkaline activators because they are less expensive and more widely available on the market compared to potassium silicate [4] . Agriculture generates substantial amounts of waste, with rice residues alone totaling 497.2 million tons globally in 2020 [5] . In recent years, increasing attention has been directed toward valorizing agricultural by-products as alternative raw * Corresponding author. E-mail address: [tavio@its.ac.id](tavio@its.ac.id) materials in construction composites. Such materials include cotton, maize stalks, peach shells, miscanthus, wood chips, bagasse, apricot shells, hemp, and rice husks [6-8] . Among these, sugarcane bagasse fiber (BF) has emerged as a promising green reinforcement material. Previous studies have found that incorporating sugarcane BF into geopolymers reduced density while increasin

FAQs

What is the purpose of hot-water-alkali treatment in this study?

To pretreat sugarcane bagasse fiber using hot water and sodium hydroxide so that impurities are removed, surface roughness increases, and fiber–matrix bonding improves in metakaolin-based geopolymer composites.

How are bagasse fiber contents selected in the geopolymer specimens?

Geopolymer specimens are prepared with bagasse fiber dosages of 0%, 3%, 4%, and 5% by weight, including untreated and hot-water-alkali-treated conditions.

Which machine learning model predicts splitting tensile strength most accurately?

XGBoost provides the highest predictive accuracy, with R² = 0.95 and MAE = 0.28, outperforming random forest and AdaBoost in this study.

Aug 5, 2026

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