Optimization of Mechanical Properties of Eco-Friendly Mortar Containing Wood Ash and Nano Silica Using Response Surface Methodology and Artificial Neural Networks.

Abiodun Akinwale, Walied A Elsaigh, Akeem Ayinde Raheem

Abstract read

In one paragraph

Article in Nanomaterials (Basel, Switzerland), 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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0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Abiodun AkinwaleDepartment of Civil Engineering & Environmental Engineering and Building Science, Florida Campus, University of South Africa, Johannesburg 1709, South Africa.ORCID 0000-0003-4983-6960

Walied A ElsaighDepartment of Civil Engineering & Environmental Engineering and Building Science, Florida Campus, University of South Africa, Johannesburg 1709, South Africa.ORCID 0000-0002-1668-3104

Akeem Ayinde RaheemDepartment of Building, Ladoke Akintola University of Technology, Ogbomosho 4000, Oyo State, Nigeria.ORCID 0000-0003-0360-3977

Funding

University of South Africa MDSP2024-07-02

6 · The paper itself

Abstract

As the demand for sustainable construction materials grows, wood ash and nanosilica have emerged as promising components for eco-friendly mortars, whose optimization requires advanced analytical techniques capable of capturing their complex linear and nonlinear interactions, making frameworks such as response surface methodology and artificial neural networks essential for effective mix design. This study examines the mechanical performance of eco-friendly mortar incorporating wood ash (WA) as a partial cement replacement and nanosilica solution (NSS) as a strength-enhancing additive, with the aim of optimizing compressive and flexural behaviour. Wood ash was substituted at levels of 5-25%, while NS (0.265 moL

Indexed as

artificial neural network (ANN)compressive strengthflexural strengthnanosilicaresponse surface methodology (RSM)wood ash

Identifiers

PMID42347282

DOI10.3390/nano16120717

PMCPMC13305701

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.