JOURNAL ARTICLE
Properties of tartaric acid modified steel slag as supplementing cementitious materials.
Published In: International Journal of Applied Ceramic Technology, 2025, v. 22, n. 1. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Tang, Panpan; Xiong, Yangkai; Huang, Lei; Fang, Zhiqiang; Jiang, Hao; Wang, Guoqing 3 of 3
Abstract
By using tartaric acid (TA) as a wet‐method modifier to modify steel slag powder (SS), it is helpful to reduce the content of free calcium oxide (f‐CaO) in SS and further improve the mechanical properties and soundness of SS as supplementing cementitious materials (SCM) in the mortar. The results indicate that with the addition of 2 wt% of TA, the number of large particles bigger than 45 µm in the SS decreased, resulting in predominantly smaller particles smaller than 45 µm. While the specific surface area increased from 417 to 704 m2/kg, the water consumption at standard consistency was significantly reduced. The soundness of the paste SS as SCM had improved including the f‐CaO content decreased from 4.81% to 0.95%, and the Le Chatelier expansion reduced from 4.5 to 1.5 mm. The mechanical properties were significantly enhanced, with the flexural strength increasing from 5.6 to 7.8 MPa, and the compressive strength rising from 38.8 to 52.7 MPa. After 28 days of curing in water, the hydration products of the mortar are hydrated calcium silicate (C‐S‐H), calcium hydroxide (CH), and calcium carbonate (CaCO3). [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Applied Ceramic Technology. 2025/01, Vol. 22, Issue 1, p1
- Document Type:Article
- Subject Area:Chemistry
- Publication Date:2025
- ISSN:1546-542X
- DOI:10.1111/ijac.14872
- Accession Number:181226385
- Copyright Statement:Copyright of International Journal of Applied Ceramic Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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