材料科学
固化(化学)
粉煤灰
复合材料
吸水率
赤泥
冶金
作者
Yindong Shi,Weichao Guo,Yali Jia,Caihong Xue,Yongxiang Qiu,Qingxin Zhao,Dongli Wang
标识
DOI:10.1016/j.jclepro.2022.133788
摘要
The utilization of such solid wastes as red mud (RM), carbide slag (CS), and fly ash (FA) in the production of environmentally friendly and cheap construction materials is a challenging task. This study produced red mud-carbide slag-fly ash (RCF) lightweight aggregate ceramsite by disc pelletizer. The effects of the preparation and curing method on the cylinder crush strength, apparent density, bulk density, water absorption, and softening coefficient of RCF ceramsite samples were experimentally investigated. The curing method was optimized based on XRD, FTIR, TG-DTG, and SEM analyses. The mechanical properties and internal pore structure of ceramsite samples were significantly improved by increasing steam curing temperature, steam curing time, and standing curing time. The optimum curing method implied a 24 h curing at the standing time and 12 h at 80 °C steam curing temperature. RCF ceramsite samples obtained by this method featured an apparent density of 1400 kg/m3, bulk density of 770 kg/m3, and softening coefficient of 0.95. Their cylinder crush strength was increased by 114.3%, and a 1 h water absorption dropped by 17.0% compared to RT-produced samples. This was due to high temperature accelerating the activation of FA and promoting the dissolution of inner spherical beads. This, in turn, accelerated the hydration reaction and increased the amount of C-(A)-S-H gel, which filled the pores and improved the overall density. The increased length of standing curing time improved the ability of RCF ceramsite samples to withstand structural damage caused by high temperatures. This product can be used to prepare light partition walls and light non-load-bearing structural prefabricated members instead of natural gravel. The results provide a theoretical basis for engineering the application of light aggregates produced from solid wastes.
科研通智能强力驱动
Strongly Powered by AbleSci AI