Search
2026-02-26
Characterization and pyrolysis kinetic modelling of lignocellulosic waste from rambutan seeds: A machine learning approach

September 30, 2025 | Biomass and Bioenergy |

A study by Universiti Putra Malaysia, Chulalongkorn University, and Prince Mohammad Bin Fahd University investigated the thermal kinetic characteristics of rambutan (Nephelium lappaceum) seed-derived lignocellulosic waste, a readily available seasonal by-product in Southeast Asia. Rambutan seed biomass has potential for bioenergy applications, but its thermal degradation characteristics remain insufficiently understood.

Ultrafine rambutan seed powder was prepared and characterized using functional group analysis, Raman spectroscopy, nitrogen physisorption, X-ray diffraction, elemental analysis, and morphological observations. Thermogravimetric analysis was then performed at multiple heating rates to examine thermal degradation behavior. Kinetic parameters were estimated using both model-free methods (Friedman and modified Vyazovkin) and model-fitting approaches, revealing a complex multistep decomposition mechanism. The average activation energy across conversion degrees of 0.2–0.7 was approximately 282 kJ/mol.

In addition, several machine learning models, including multilayer perceptron, boosted regression trees, classification and regression trees, and multivariate adaptive regression splines (MARS), were applied to predict activation energy values. Among these, the MARS model showed the highest predictive accuracy, with strong agreement with experimentally derived data. The findings demonstrate that combining kinetic analysis with machine learning provides a reliable approach for modeling biomass pyrolysis and supports the utilization of rambutan seed waste as a bioenergy resource.

Read more

Viewed Articles
Characterization and pyrolysis kinetic modelling of lignocellulosic waste from rambutan seeds: A machine learning approach
September 30, 2025 | Biomass and Bioenergy | A study by Universiti Putra Malaysia, Chulalongkorn University, and Prince Mohammad Bin Fahd University investigated the thermal kinetic characteristics of
Feb 26, 2026
Read More
Structural determinants of gelation kinetics in rambutan seed starches: Implications for enhanced precision in 3D food printing
February 09, 2026 | Carbohydrate Polymers | This study conducted by Southwest University, China investigated the potential use of rambutan seed starch as a novel material for 3D food printing applicat
2026.05.26
Potential of methanol extracts of <span style="font-style:italic;">Nephelium lappaceum </span>(Sapindaceae) and <span style="font-style:italic;">Hyphaene thebaica </span>(Arecaceae) as adjuvants to enhance the efficacy of antibiotics against critical class priority bacteria
September 09, 2025 | Plos one |The study conducted by the University of Buea, Cameroon, investigated the potential of plant-derived extracts to address the growing problem of antibiotic resistance in
2025.12.23
Key determinants of volatile profile and bioactive potential in durian (<span style="font-style:italic;">Durio zibethinus</span>)
November 17, 2025 | Critical Reviews in Food Science and Nutrition |The study conducted by The University of Melbourne, Australia, reviews current knowledge on the factors that influence the volatile
2025.12.23
Eco-friendly adsorbent from rambutan (<span style="font-style:italic;">Nephelium lappaceum </span>) seeds: Characterization and turbidity removal performance in wastewater treatment
September 11, 2025 | Progress in Engineering Science |The potential of using rambutan (Nephelium lappaceum) seed waste as a sustainable raw material for producing activated carbon in wastewater treatm
2025.11.11
Green synthesis and characterization of copper oxide nanoparticles from durian (<span style="font-style:italic;">Durio zibethinus</span>) husk for environmental applications
March 15, 2025 | Catalysts |The study conducted by Jalan Universiti, Malaysia, and the Bangladesh Council of Scientific and Industrial Research (BCSIR), Bangladesh, investigated a sustainable approach
2025.12.23
TOP