Evaluating the Effect of Calcination and Grinding of Corn Stalk Ash on Pozzolanic Potential for Sustainable Cement‐Based Materials

Abstract

In developing countries, one of the usual practices is the uncontrolled, open burning of corn stalk (CS) or its utilization as a fuel. It is known that the ash obtained under uncontrolled burning conditions constitutes blackish and unburnt carbon particles as well as whitish and grayish particles (representing crystallization of silica) due to over burning. However, controlling the burning process can improve the quality of ash produced to effectively use it in cement-based materials. Hence, this research was aimed at exploring the pozzolanic properties of corn stalk ash upon calcination and grinding, for it to be used in the manufacturing of sustainable cement-based materials. In order to obtain a suitable corn stalk ash (CSA), which can be used in cement/concrete, a research investigation consisted of two phases. In the first phase, calcination was carried out at 400°C, 500°C, 600°C, 700°C, and 800°C for 2 hours. The tests applied on the resulting ashes were weight loss, XRD, pozzolanic activity index (PAI), Chapelle, Fratini, and consistency. From XRD spectra, it was found that, at lower temperatures, silica remained amorphous, while it crystallized at higher temperature. Ash combusted at a temperature of 500°C possessed largest pozzolanic activity of 96.8%, had a Fratini CaO reduction of 93.2%, and Chapelle activity of 856.3 mg/g. Thus, 500°C was chosen as an optimum calcination temperature. In the second phase, the ash produced at 500°C was grinded for durations of 30, 60, 120, and 240 minutes to ascertain the optimum grinding times. Resulting ashes were examined for hydrometer analysis, Blaine fineness, Chapelle activity, and pozzolanic activity. Experiment outcomes revealed a direct relationship between values of Blaine fineness, surface area, Chapelle activity, PAI, and grinding duration. It was concluded that CSA can be used as a pozzolan, and thus, its utilization in cement/concrete would solve ash disposal problems and aid in production of eco-friendly cement/concrete.

Machine Learning‐Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete

“…Grinding was carried out in ball mill machine with ceramic balls as grinding media. e grinding media to SCBA ratio of 5 by weight was kept constant, and the machine was operated at 100 rpm [78]. Different SCBA samples were obtained at a grinding duration of 15, 30, 45, and 60 minutes.…”

Implementation assessment of calcined and uncalcined cashew nut-shell ash with total recycled concrete aggregate in self-compacting concrete employing Bailey grading technique

“…Utilization of agro-waste materials as cementitious or pozzolanic in versatile concrete was found to be more frequent. Most utilized agro-wastes in concrete are rice husk ash, bagasse, groundnut shell ash, oyster shell ash, sawdust ash, and cork waste ash [1][2][3]. Most of these agro-wastes must undergo a calcination process, which results in property enhancement [2,4,5].…”

“…Most utilized agro-wastes in concrete are rice husk ash, bagasse, groundnut shell ash, oyster shell ash, sawdust ash, and cork waste ash [1][2][3]. Most of these agro-wastes must undergo a calcination process, which results in property enhancement [2,4,5]. Usually, these processes were executed at a higher temperature of about 400-800 °C depending on the agro-waste nature [2,4,6,7].…”

Modeling Compressive Strength of Eco-Friendly Volcanic Ash Mortar Using Artificial Neural Networking

“…Hence, efforts are being made worldwide to reduce the high carbon footprint of construction industries [7,8]. Concrete is an essential man-made material in the industry and the second-most utilized material in the world [9,10]. Cement, the binding material in concrete, causes 7% of the total CO 2 emissions and consumes around 15% of the total energy used by industries [11][12][13].…”

“…10) where ex i and Po i are the actual measured and model predicted values of compressive strengths, respectively, and ex i and Po i are the mean values of the actual measured and model predicted compressive strengths, respectively.…”