Optimizing the mechanical performance of adobe bricks reinforced with Vicia faba plant waste and derived biochar using ANN and RSM.

Nadia Frioui, Messaouda Boumaaza, Ahmed Belaadi, Mahmood M S Abdullah, Djamel Ghernaout, Amar Al-Khawlani, Herbert Mukalazi

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Nadia FriouiDepartment of Mechanical Engineering, Faculty of Science and Technology , University 8 Mai 1945 Guelma, 401, 24000, Guelma, BP, Algeria.

Messaouda BoumaazaLaboratory of Civil Engineering and Hydraulics (LGCH), University 8 Mai 1945 Guelma, 401, 401, 24000, Guelma, BP, Algeria.

Ahmed BelaadiDepartment of Mechanical Engineering, Faculty of Technology, University 20 Août 1955-Skikda, El‑Hadaiek, Skikda, Algeria. ahmedbelaadi1@yahoo.fr.

Mahmood M S AbdullahDepartment of Chemistry, College of Science, King Saud University, PO Box 2455, 11451, Riyadh, Saudi Arabia.

Djamel GhernaoutChemical Engineering Department, College of Engineering, University of Ha'il, PO Box 2440, 81441, Ha'il, Saudi Arabia.

Amar Al-KhawlaniJiangsu Optoelectronic Functional Materials and Engineering Research Centre, School of Chemistry and Chemical Engineering, Southeast University, Nanjing, China.

Herbert MukalaziDepartment of Mathematics and Statistics, Kyambogo University, Kampala, Uganda. hmukalazi@kyu.ac.ug.

Funding

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6 · The paper itself

Abstract

Using traditional materials, especially earthen materials and plant waste, is becoming more popular worldwide due to lower construction costs, improved thermal comfort, reduced energy use, and fewer carbon dioxide emissions. In this context, tests have been performed on a stabilized earth bricks (SEBs) made from raw earth bricks combined with Vicia faba waste (VfW) and biochar derived from this waste (BVfW), obtained by pyrolysis at 300 °C and 500 °C, using a factorial design with BVfW contents ranging from 0.5 to 6 wt%. The effects of these compounds on the controlled variables were examined using artificial neural network (ANN) techniques and response surface methodology (RSM) to assess the mechanical behavior and thermophysical properties of the bricks within a system that varies the percentage of BVfW and pyrolysis temperature. The best conditions were found to be 500 °C and 4% BVfW content, based on the RSM desirability function and the ANN genetic algorithm. This experimental approach allows for optimizing production conditions by selecting the best parameters to create bricks with balanced strength.

Indexed as

CharcoalConstruction MaterialsNeural Networks, ComputerVicia fabaPyrolysisTemperaturebiocharCharcoalEarthen bricksMechanical behaviorOptimizationthermophysical propertiesVicia faba

Identifiers

PMID42151471

DOI10.1038/s41598-026-53702-1

PMCPMC13376825

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