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Get Free AccessAbstract Cement is one of the most widely used building materials due to its strength and durability. However, conventional cement has a very high setting time, which makes it less attractive for applications requiring quick-setting behavior, such as rapid construction, emergency repairs, underwater construction, and 3D printing. The present study proposes hexagonal boron nitride (hBN) as a potential accelerant to impart quick-setting behavior to conventional cement. hBN is a two-dimensional material renowned for its exceptional thermal conductivity, chemical stability, and mechanical strength. Our study investigates the incorporation of hBN nanoparticles into class G Portland cement to enhance its mechanical, thermal, and rheological properties. Our experimental investigation demonstrates that hBN acts as an excellent accelerant in cement by reducing the dormancy period by up to 2 hours and enhancing the overall setting kinetics. This makes hBN a promising candidate for quick-setting cement applications. Further thermal analysis reveals an improved heat dissipation capability, with lower surface temperatures and enhanced structural integrity due to reduced porosity and microcrack formation. Mechanical testing demonstrates substantial improvements in compressive strength (up to 29%), compressive modulus (up to 45%), and energy absorption capacity (up to 31%) for 1% hBN-reinforced cement compared to neat cement. Moreover, hBN-reinforced 3D-printed cement structures exhibit a 72% increase in compressive strength. The hBN-reinforced cement ink also demonstrates enhanced printability, characterized by superior flow stability, better structural recovery, and reliable shape retention, making it ideal for 3D printing applications.
Vijay Vedhan Jayanthi Harikrishnan, Maruf Md. Ikram, Sudheendhra Herkel, Wei Meng, Ali Khater, Kenneth D. Johnson, Peter J. Boul, Minghe Lou, Satish Nagarajaiah, Muhammad M. Rahman, Pulickel M. Ajayan (2025). Hexagonal Boron Nitride Reinforced Quick-setting Multifunctional Cement. , DOI: https://doi.org/10.1093/oxfmat/itaf002.
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Type
Article
Year
2025
Authors
11
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1093/oxfmat/itaf002
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