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Strategic construction of hierarchical conductive networks in ultra-high performance concrete towards superior electrical conductivity and mechanical strength

  • Weichen Tian
  • , Xianglong Liu
  • , Huigang Xiao
  • , Ruipeng Qiu
  • , Xudong Zhao
  • , Yan Xia
  • , Xingang Wang*
  • *Corresponding author for this work
  • Nanchang University
  • School of Civil Engineering, Harbin Institute of Technology
  • Hong Kong Polytechnic University

Research output: Contribution to journalArticlepeer-review

Abstract

In this work, two nanomaterials (nano carbon fiber (NCF) and nano carbon black (NCB)) were respectively combined with macro-scale conductive materials (carbon fiber and steel fiber) for the strategic construction of hierarchical conductive networks in conductive ultra-high performance concrete (C-UHPC). The fluidity, electrical properties, electrochemical analysis, mechanical properties, microhardness analysis, micromorphology characterization, economic and environmental benefits were systematically evaluated to elucidate the effect of nanomaterials on C-UHPC. Results revealed that the hierarchical conductive networks dominated by different nanomaterials exhibited distinct effects on the properties of C-UHPC, along with significant differences in economic and environmental benefits. Specifically, NCF demonstrated a more superior effect on promoting the strength improvement for C-UHPC through fiber bridging with macro-scale conductive materials, but it reduced the economic and environmental benefits. In contrast, the NCB utilized its unique particulate morphology as conductive points to form a “conductive coating” within the macroscopic conductive framework, effectively improving the electrical properties of C-UHPC with high economic and environmental benefits, while significantly impairing the fluidity and 28-day compressive strength for the samples. Furthermore, machine learning algorithms were employed to predict the electrical properties of C-UHPC, with the support vector regression model demonstrating superior prediction accuracy with R2 of 0.9861. A swarm intelligence-based optimization system was also developed to support the multi-objective design of C-UHPC, considering electrical, mechanical and economic objectives. This research provides a viable pathway for developing C-UHPC with integrated multifunctionality, contributing to the intelligent regulate and sustainable management of next-generation infrastructure.

Original languageEnglish
Article number115924
JournalJournal of Building Engineering
Volume123
DOIs
StatePublished - 1 Apr 2026
Externally publishedYes

Keywords

  • AI-Driven composite design
  • Electrical properties
  • Hierarchical conductive network
  • Mechanical properties
  • Nanomaterials

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