Scholarlink

<p>The development of high-performance cementitious composites with superior strength and durability is hindered by the complex, non-linear interactions between modern chemical admixtures. This study presents a hybrid experimental and computational framework to systematically understand and optimize a quaternary system composed of cement, nanosilica (NS), xanthan gum (XG), and a polycarboxylate ether (PCE) superplasticizer. A comprehensive experimental investigation was conducted to characterize the material’s performance, spanning from fresh-state rheology to hardened-state mechanical properties, durability, and detailed microstructural analysis. The results revealed that the synergistic combination of a low water-to-cement ratio and a high dosage of nanosilica was the most critical factor for enhancing performance. This synergy was shown to significantly refine the material’s microstructure, reducing total porosity and median pore diameter, which in turn dramatically improved resistance to water absorption and chloride ion penetration. Advanced spectroscopic analyses (XRD, FTIR, and ²⁹Si MAS NMR) was complemented by a hybrid PSO–ANN framework to model nonlinear interactions and identify optimized mix compositions, emphasizing predictive capability rather than methodological enumeration.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrated hybrid machine learning and metaheuristic approach: optimizing green-surfactant stabilized nano-silica cement composites for structural applications

  • 期刊论文

  • 发表日期：

    2026年1月20日

查看全文
  • Vignesh Jagajeevan,
  • Vidhya Lakshmi Sivakumar,
  • Nanthini M

摘要

The development of high-performance cementitious composites with superior strength and durability is hindered by the complex, non-linear interactions between modern chemical admixtures. This study presents a hybrid experimental and computational framework to systematically understand and optimize a quaternary system composed of cement, nanosilica (NS), xanthan gum (XG), and a polycarboxylate ether (PCE) superplasticizer. A comprehensive experimental investigation was conducted to characterize the material’s performance, spanning from fresh-state rheology to hardened-state mechanical properties, durability, and detailed microstructural analysis. The results revealed that the synergistic combination of a low water-to-cement ratio and a high dosage of nanosilica was the most critical factor for enhancing performance. This synergy was shown to significantly refine the material’s microstructure, reducing total porosity and median pore diameter, which in turn dramatically improved resistance to water absorption and chloride ion penetration. Advanced spectroscopic analyses (XRD, FTIR, and ²⁹Si MAS NMR) was complemented by a hybrid PSO–ANN framework to model nonlinear interactions and identify optimized mix compositions, emphasizing predictive capability rather than methodological enumeration.