Nano-TiO₂-treated recycled aggregate-based photocatalytic mortar: Efficient NOx removal and mathematical modeling across diverse operational scenarios

Xue-Fei Chen; Xiu-Cheng Zhang; Xiangping Xian; S Thomas Ng

doi:10.1016/j.dibe.2025.100604

Nano-TiO₂-treated recycled aggregate-based photocatalytic mortar: Efficient NOx removal and mathematical modeling across diverse operational scenarios

Xue-Fei Chen, Xiu-Cheng Zhang, Xiangping Xian^*, S Thomas Ng

^*Corresponding author for this work

Department of Architecture and Civil Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

4 Citations (Scopus)

8 Downloads (CityUHK Scholars)

Abstract

Nano-TiO₂-treated (NT) recycled concrete aggregates (RA) were successfully integrated into the built environment by producing green photocatalytic mortar. Employing various microstructural characterization techniques, it was revealed that the old mortar layer of the RA possessed a porous surface structure, providing a significant specific surface area conducive to effective NT loading. A stable Ti-O-Si chemical bond was established between the surface of the RA and the NT through a hydroxylation treatment process, ensuring the durability of the green photocatalytic mortar during its manufacture and deployment within the built environment. This innovative mortar demonstrated an exceptional NOx removal efficiency of c.a. 90.75%. A predictive model was developed using the Back Propagation Neural Network, integrating experimental and theoretical data to optimize mortar performance across various scenarios. The findings mark a significant advancement in using RA in construction, contributing to sustainable development in the built environment. © 2025 The Authors. Published by Elsevier Ltd.

Original language	English
Article number	100604
Journal	Developments in the Built Environment
Volume	21
Online published	10 Jan 2025
DOIs	https://doi.org/10.1016/j.dibe.2025.100604
Publication status	Published - Mar 2025

Funding

This project was also financially supported by the [Faculty Start-up Grant of City University of Hong Kong] with Award Number [No. 9610660], Green Tech Fund of the Environment and Ecology Bureau, HKSAR Government (Grant No.: GTF202110158)and [Natural Science Foundation of Fujian] with grant number [No. 2023J01999], [Putian University Zixiao Scholars-Young Top Talent Program-2024] with grand number [2024174]. Special thanks to the ‘Testing Technology Center for Materials and Devices of Tsinghua Shenzhen International Graduate School’ for providing us with testing-related service.

Research Keywords

Construction wastes
Green photocatalytic mortar
Recycled concrete aggregates

Publisher's Copyright Statement

This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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title = "Nano-TiO₂-treated recycled aggregate-based photocatalytic mortar: Efficient NOx removal and mathematical modeling across diverse operational scenarios",

abstract = "Nano-TiO2-treated (NT) recycled concrete aggregates (RA) were successfully integrated into the built environment by producing green photocatalytic mortar. Employing various microstructural characterization techniques, it was revealed that the old mortar layer of the RA possessed a porous surface structure, providing a significant specific surface area conducive to effective NT loading. A stable Ti-O-Si chemical bond was established between the surface of the RA and the NT through a hydroxylation treatment process, ensuring the durability of the green photocatalytic mortar during its manufacture and deployment within the built environment. This innovative mortar demonstrated an exceptional NOx removal efficiency of c.a. 90.75%. A predictive model was developed using the Back Propagation Neural Network, integrating experimental and theoretical data to optimize mortar performance across various scenarios. The findings mark a significant advancement in using RA in construction, contributing to sustainable development in the built environment. {\textcopyright} 2025 The Authors. Published by Elsevier Ltd. ",

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author = "Xue-Fei Chen and Xiu-Cheng Zhang and Xiangping Xian and Ng, {S Thomas}",

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doi = "10.1016/j.dibe.2025.100604",

language = "English",

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Nano-TiO₂-treated recycled aggregate-based photocatalytic mortar: Efficient NOx removal and mathematical modeling across diverse operational scenarios. / Chen, Xue-Fei; Zhang, Xiu-Cheng; Xian, Xiangping et al.
In: Developments in the Built Environment, Vol. 21, 100604, 03.2025.

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

TY - JOUR

T1 - Nano-TiO₂-treated recycled aggregate-based photocatalytic mortar

T2 - Efficient NOx removal and mathematical modeling across diverse operational scenarios

AU - Chen, Xue-Fei

AU - Zhang, Xiu-Cheng

AU - Xian, Xiangping

AU - Ng, S Thomas

PY - 2025/3

Y1 - 2025/3

N2 - Nano-TiO2-treated (NT) recycled concrete aggregates (RA) were successfully integrated into the built environment by producing green photocatalytic mortar. Employing various microstructural characterization techniques, it was revealed that the old mortar layer of the RA possessed a porous surface structure, providing a significant specific surface area conducive to effective NT loading. A stable Ti-O-Si chemical bond was established between the surface of the RA and the NT through a hydroxylation treatment process, ensuring the durability of the green photocatalytic mortar during its manufacture and deployment within the built environment. This innovative mortar demonstrated an exceptional NOx removal efficiency of c.a. 90.75%. A predictive model was developed using the Back Propagation Neural Network, integrating experimental and theoretical data to optimize mortar performance across various scenarios. The findings mark a significant advancement in using RA in construction, contributing to sustainable development in the built environment. © 2025 The Authors. Published by Elsevier Ltd.

AB - Nano-TiO2-treated (NT) recycled concrete aggregates (RA) were successfully integrated into the built environment by producing green photocatalytic mortar. Employing various microstructural characterization techniques, it was revealed that the old mortar layer of the RA possessed a porous surface structure, providing a significant specific surface area conducive to effective NT loading. A stable Ti-O-Si chemical bond was established between the surface of the RA and the NT through a hydroxylation treatment process, ensuring the durability of the green photocatalytic mortar during its manufacture and deployment within the built environment. This innovative mortar demonstrated an exceptional NOx removal efficiency of c.a. 90.75%. A predictive model was developed using the Back Propagation Neural Network, integrating experimental and theoretical data to optimize mortar performance across various scenarios. The findings mark a significant advancement in using RA in construction, contributing to sustainable development in the built environment. © 2025 The Authors. Published by Elsevier Ltd.

KW - Construction wastes

KW - Green photocatalytic mortar

KW - Recycled concrete aggregates

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U2 - 10.1016/j.dibe.2025.100604

DO - 10.1016/j.dibe.2025.100604

M3 - RGC 21 - Publication in refereed journal

SN - 2666-1659

VL - 21

JO - Developments in the Built Environment

JF - Developments in the Built Environment

M1 - 100604

ER -

Nano-TiO₂-treated recycled aggregate-based photocatalytic mortar: Efficient NOx removal and mathematical modeling across diverse operational scenarios

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UN SDGs

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GTF_EPD: Low Carbon Road Pavement by Maximising Material Circularity and Adopting Sustainable Materials

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Nano-TiO₂-treated recycled aggregate-based photocatalytic mortar: Efficient NOx removal and mathematical modeling across diverse operational scenarios

Abstract

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Research Keywords

Publisher's Copyright Statement

UN SDGs

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GTF_EPD: Low Carbon Road Pavement by Maximising Material Circularity and Adopting Sustainable Materials

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