Journal Article10.1016/J.CERAMINT.2016.11.058
Optimization of bentonite clay mechano-chemical activation using artificial neural network modeling
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TL;DR: In this paper, the properties of seven montmorillonite-rich bentonites of different geological origin were investigated prior and subsequent to mechano-chemical processing in an ultra-centrifugal mill.
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About: This article is published in Ceramics International. The article was published on 01 Feb 2017.
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Citations
Tuning tetracycline removal from aqueous solution onto activated 2:1 layered clay mineral: Characterization, sorption and mechanistic studies.
TL;DR: Thermal activation was opted for the modification of natural bentonite clay and utilized to investigate the adsorptive removal of tetracycline from aqueous solution and the mechanism of TC adsorption by TB was successfully explored.
170
The effect of alternations in mineral additives (zeolite, bentonite, fly ash) on physico-chemical behavior of Portland cement based binders
Anja Terzić,Lato Pezo,Nevenka Mijatović,Jovica Stojanović,Milan Kragović,Ljiljana Miličić,Ljubiša Andrić +6 more
TL;DR: In this article, an experiment was conducted to assess physico-chemical changes induced by variations in chemical composition of cementitious composites, i.e., mortar binders, using coal combustion ash as pozzolanic mineral additive.
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•Journal Article
XRD, TEM, and thermal analysis of Arizona Ca-montmorillonites modified with didodecyldimethylammonium bromide
TL;DR: In this article, an Arizona SAz-2 Ca-montmorillonite was modified by a typical dialkyl cationic surfactant (didodecyldimethylammonium bromide, abbreviated to DDDMA) through direct ion exchange.
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Improving the quality of biopolymer (poly lactic acid) with the addition of bentonite as filler
Suryani,Harry Agusnar,Basuki Wirjosentono,Teuku Rihayat,Nurhanifa +4 more
- 01 Jul 2017
TL;DR: In this paper, the authors combined two types of natural bentonite obtained from different areas to find differences in the quality of the results of characterization, and the results were analyzed by X-Ray difraction (XRD) and Transmission Electron Microscope (TEM).
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Structural features modeling of substituted hydroxyapatite nanopowders as bone fillers via machine learning
TL;DR: In this paper, both experimental and modeling approaches were employed to explore the solid-state formation mechanisms and estimate the structural behavior of nanosized substituted hydroxyapatite (HA) powders using different machine learning (ML) techniques.
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