How does aluminium foaming agent impact the geopolymer formation mechanism?

Hajimohammadi, Ailar; Ngo, Tuan; Mendis, Priyan

doi:10.1016/j.cemconcomp.2017.03.022

Cited by 87 publications

(38 citation statements)

References 40 publications

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“…The principle of chemical foaming with aluminum powder is based on the reaction between aluminum and SH to produce H 2 gas, which initiates the expansion of the system according to the following chemical reaction formula (Hajimohammadi et al 2017):…”

Section: Chemical Foaming Methodsmentioning

confidence: 99%

Lightweight Alkali-Activated Material from Mining and Glass Waste by Chemical and Physical Foaming

Kastiukas

Zhou

Wan

et al. 2019

J. Mater. Civ. Eng.

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A foamed alkali-activated material (FAAM) based on tungsten mining waste (TMW) and municipal waste glass (WG) is fabricated by using aluminum powder and organic surfactant foaming agents. The compressive strength and density of the FAAM are investigated in terms of different parameters of production and formulation, including curing temperature as well as the dosage of Na 2 O, foaming agent, foam catalyzing agent, and stabilizing agent. FAAM made with aluminum powder consists of smaller open macropores and exhibits higher compressive strength compared with FAAMs with larger closed macropores obtained by organic surfactant counterparts. The final aluminum powder-based FAAM reaches a 7-day compressive strength in excess of 3 MPa and a density below 0.7 g=cm 3. The implementation of an appropriate amount of foam stabilizer leads to a further 15% increase in compressive strength, 6% reduction in density, and a thermal conductivity below 0.1 W=mK. The FAAM explored in this study represents an ideal material for building envelope insulation.

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Section: Chemical Foaming Methodsmentioning

confidence: 99%

Lightweight Alkali-Activated Material from Mining and Glass Waste by Chemical and Physical Foaming

Kastiukas

Zhou

Wan

et al. 2019

J. Mater. Civ. Eng.

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“…Foamed concrete is a type of lightweight concrete that offers many advantages such as reducing the dead load of structures, improving sound and thermal insulation properties, and reducing transportation and installation costs (Ngo, Hajimohammadi, Sanjayan, & Mendis, 2017;Hajimohammadi, Ngo, & Mendis, 2017a;Nguyen, Ghazlan, Kashani, Bordas, & Ngo, 2018). These advantages make foamed concrete suitable for a myriad of applications in infrastructure construction and the prefabricated industry such as prefabricated blocks or panels, insulated walls, aircraft runway arrestors, roof decks, and © 2018 Computer-Aided Civil and Infrastructure Engineering geotechnical backfills.…”

Section: Introductionmentioning

confidence: 99%

Deep neural network with high‐order neuron for the prediction of foamed concrete strength

Nguyen

Kashani

Ngo

et al. 2018

Computer aided Civil Eng

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216

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The article presents a deep neural network model for the prediction of the compressive strength of foamed concrete. A new, high‐order neuron was developed for the deep neural network model to improve the performance of the model. Moreover, the cross‐entropy cost function and rectified linear unit activation function were employed to enhance the performance of the model. The present model was then applied to predict the compressive strength of foamed concrete through a given data set, and the obtained results were compared with other machine learning methods including conventional artificial neural network (C‐ANN) and second‐order artificial neural network (SO‐ANN). To further validate the proposed model, a new data set from the laboratory and a given data set of high‐performance concrete were used to obtain a higher degree of confidence in the prediction. It is shown that the proposed model obtained a better prediction, compared to other methods. In contrast to C‐ANN and SO‐ANN, the proposed model can genuinely improve its performance when training a deep neural network model with multiple hidden layers. A sensitivity analysis was conducted to investigate the effects of the input variables on the compressive strength. The results indicated that the compressive strength of foamed concrete is greatly affected by density, followed by the water‐to‐cement and sand‐to‐cement ratios. By providing a reliable prediction tool, the proposed model can aid researchers and engineers in mixture design optimization of foamed concrete.

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“…In terms of the way of foam generation, FAFG can be divided into two categories: mechanical foamed-FAFG [22,23] and chemical foamed-FAFG [24,25], which are respectively produced by special foaming machine with some kind of foaming agent and by nely divided aluminum or hydrogen peroxide [26,27]. In this research, FAFG was made of FLA of di erent particle sizes and other raw materials in the form of chemical foaming with hydrogen peroxide.…”

Section: Introductionmentioning

confidence: 99%

Fly Ash Particle Size Effect on Pore Structure and Strength of Fly Ash Foamed Geopolymer

Xiong

Wan

Zhou

et al. 2019

Advances in Polymer Technology

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e aim of this paper is to study the particle size e ect of y ash (FLA) on pore structure and strength of Fly Ash Foamed Geopolymer (FAFG). Information on the macro-pores such as macro-pore size and distribution of FAFG is captured through binarization processing. Porosity and compressive strength of FAFG are respectively tested by Archimedes density test method and uniaxial compressive strength test method. It can be concluded that the FLA particle size has an e ect on the pore structure and strength of FAFG. More speci cally, the e ect of FLA particle size shows itself macroscopically on the quantity of middle and large macro-pores and the uniformity of macro-pores distribution, and microscopically on the quantity of micro-holes and cracks and calcium silicate (C-S-H) quantity at the early stage of FAFG mixture. All of the properties of FAFG follow some kind of changing rule except at the turning point when FLA particle is of 0.125~0.25 mm in size. To explain clearly the root cause of FLA particle size e ect on FAFG, SEM, and XRD are employed to explore the microstructure of FAFG and the component of FLA. It turns out to be the amorphous phase SiO 2 content in FLA of di erent particle sizes which could determine the reaction extent of FAFG mixture.

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How does aluminium foaming agent impact the geopolymer formation mechanism?

Cited by 87 publications

References 40 publications

Lightweight Alkali-Activated Material from Mining and Glass Waste by Chemical and Physical Foaming

Lightweight Alkali-Activated Material from Mining and Glass Waste by Chemical and Physical Foaming

Deep neural network with high‐order neuron for the prediction of foamed concrete strength

Fly Ash Particle Size Effect on Pore Structure and Strength of Fly Ash Foamed Geopolymer

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