Author

S. Abubakar

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Open access Aug 2026

Innovative development of an advanced machine learning modeling for predicting compressive strength of graphene-infused concrete: a SHAP and PDP approach

The quasi-brittle response of cementitious materials continues to limit their structural efficiency, necessitating advanced reinforcement strategies. While conventional fibers improve mechanical performance, the emergence of graphene-based nanomaterials offers new opportunities to tailor interfacial interactions and en...

A. Alzlfawi, M. H. R. Sobuz, Md. Kawsarul Islam Kabbo et al. · Scientific Reports · 0 citations

Open access Jul 2026

Mechanical assessment with data-driven hybrid machine learning-based optimization of compressive strength of sustainable biochar-concrete composite.

The rapid rise in global population and industrial activity has intensified environmental challenges, particularly carbon dioxide (CO₂) emissions from the cement and concrete industry. Biochar, a carbon-rich byproduct of biomass pyrolysis, has emerged as a promising solution for sustainable construction by enhancing ca...

M. Uddin, Md. Samsuzzaman Sobuz, Mohamed Ghalla et al. · Scientific Reports · 0 citations

Open access Jul 2026

Optimization and predictive measurement of compressive strength of iron ore slag modified concrete using data-driven supervised machine learning algorithms.

An integrated machine learning-experimental framework to predict the compressive strength (CS) of concrete incorporating ternary industrial wastes glass powder, marble powder, and iron ore slag is developed and the hybrid XGB-GBR model demonstrates the highest balanced performance.

Md. Samsuzzaman Sobuz, Md. Kawsarul Islam Kabbo, Abdullah Alzlfawi et al. · Scientific Reports · 0 citations