Effect of doped multi-walled carbon nanotubes and nano-magnetite on the mechanical and self-sensing properties of cemented soil composites DOI
Siyi Huang, Liyuan Tong, Xiao Yu

et al.

Mechanics of Advanced Materials and Structures, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 19

Published: April 26, 2025

Language: Английский

Understanding the role of carbon nanotubes in low carbon sulfoaluminate cement-based composite DOI

Kai Cui,

Dong Lu, Ting Jiang

et al.

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 416, P. 137843 - 137843

Published: June 18, 2023

Language: Английский

Citations

44

Enhancing sustainability in pavement Engineering: A-state-of-the-art review of cement asphalt emulsion mixtures DOI Creative Commons
Dong Lu, Xi Jiang, Zhifei Tan

et al.

Cleaner Materials, Journal Year: 2023, Volume and Issue: 9, P. 100204 - 100204

Published: Aug. 16, 2023

Cement asphalt emulsion mixture (CAEM) is an environmentally sustainable substitute for hot mix and can trigger a substantial economic benefit. This paper systematically reviews the interactions between organic-inorganic composites their influence on performance of CAEM. First, (AE) cement are introduced. Next, demulsification AE hydration in CAEM system analyzed. Finally, fresh properties CA paste, static dynamic mechanical mortar its applications ballastless slab tracks, road pavement construction discussed. review allows better understanding interaction composite thus has strategy to regulate promote practical application.

Language: Английский

Citations

42

Investigation on the preparation of low carbon cement materials from industrial solid waste phosphogypsum: Clinker preparation, cement properties, and hydration mechanism DOI
Jixin Zhang,

Kai Cui,

Yi Yang

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 452, P. 142203 - 142203

Published: April 10, 2024

Language: Английский

Citations

22

Effect of carbon dots with different sizes on chloride binding of cement DOI

Hua-feng Shan,

E Shuang,

Roulan Zhao

et al.

Construction and Building Materials, Journal Year: 2024, Volume and Issue: 425, P. 136103 - 136103

Published: April 1, 2024

Language: Английский

Citations

20

Phosphogypsum-based building materials: Resource utilization, development, and limitation DOI
Jixin Zhang,

Kai Cui,

Jun Chang

et al.

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: 91, P. 109734 - 109734

Published: May 24, 2024

Language: Английский

Citations

17

Mechanical properties and mechanisms of soda residue and fly ash stabilized soil DOI Creative Commons

Tianfeng Yang,

Bo Huang, Chenghong Zhan

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 7, 2025

To improve the utilization rates of soda residue (SR) and fly ash (FA), reduce environmental pollution, enhance mechanical properties marine clay (MC), this study proposes mixing SR, FA, MC with cement /or lime to prepare residue-fly stabilized soil (SRFSS). Using an orthogonal design for proportions, analyzes compaction performance, unconfined compressive strength (UCS), shear SRFSS. The influence various factors on SRFSS was investigated through range variance analyses. mechanism revealed from perspectives grading cementation. results indicate that SR FA significantly impact analysis are consistent: content 30% 70% has most significant performance UCS, respectively, while 20% greatest effect strength. recommended base proportion is + 10% MC. gradation cementitious jointly microstructure SRFSS, G8 lowest planar porosity, at only 0.89%. calcium (Ca) in specimens different proportions shows variation, 5.0 53.6 wt%, silicon (Si)/Al ratio (0.76–2.73) relatively small fluctuations. primary hydration products include hydroxide (Ca(OH)2), silicate hydrate (C-S-H), ettringite (AFt).

Language: Английский

Citations

2

Electrically conductive asphalt concrete for smart and sustainable pavement construction: A review DOI
Dong Lu, Xi Jiang, Zhen Leng

et al.

Construction and Building Materials, Journal Year: 2023, Volume and Issue: 406, P. 133433 - 133433

Published: Sept. 22, 2023

Language: Английский

Citations

35

Development of effective porous geopolymer adsorbent with high strength for copper(II) ion removal DOI
Kaikang Liang,

Guangzhao Yang,

Xing Quan Wang

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 449, P. 141752 - 141752

Published: March 12, 2024

Language: Английский

Citations

14

Recent advancements in carbon-based composite materials as electrodes for high-performance supercapacitors DOI
Mohaiminul Islam, Md. Sajib Hossain, Bapan Adak

et al.

Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 107, P. 114838 - 114838

Published: Dec. 10, 2024

Language: Английский

Citations

9

Investigating the effectiveness of carbon nanotubes for the compressive strength of concrete using AI-aided tools DOI Creative Commons

Han Sun,

Muhammad Nasir Amin,

Muhammad Tahir Qadir

et al.

Case Studies in Construction Materials, Journal Year: 2024, Volume and Issue: 20, P. e03083 - e03083

Published: March 28, 2024

Sustainable development in the building industry can be achieved through use of versatile cementitious composites. Thus, incorporating nanoparticles into cement composites create materials with enhanced performance and numerous applications. The utilization carbon nanotubes (CNTs) construction has great promise for developing efficient solutions to establish a sustainable ecosystem diverse characteristics. However, forecasting characteristics these is significant challenge due their intricate composite structure nonlinear behavior. Designing conducting laboratory experiments on samples across multiple age groups challenging, time-consuming, costly. Moreover, there presently lack model that predict concrete's compressive strength (fc') nanoparticles. Three machine learning (ML) techniques, K-nearest neighbor (KNN), linear regression (LR), artificial neural network (ANN), were used fc' nanocomposites containing CNTs this research. A thorough database consisting 282 data entities CNTs-based concrete model's reliability was assessed using R2 test statistical error analysis. ANN had most outstanding value 0.885, while KNN LR models values 0.838 0.744, respectively. RReliefF analysis utilized evaluate primary components predicting outcomes. This research shows properties CNT-based are greatly affected by water-to-binder ratio, followed proportions coarse aggregates. ML algorithms exhibited superior generalization capabilities, suggesting potential accurate predictions properties.

Language: Английский

Citations

8