TY - JOUR
T1 - Applying grid nanoindentation and maximum likelihood estimation for N-A-S-H gel in geopolymer paste
T2 - Investigation and discussion
AU - Luo, Zhiyu
AU - Li, Wengui
AU - Gan, Yixiang
AU - Mendu, Kavya
AU - Shah, Surendra P.
N1 - Funding Information:
The authors appreciate the financial supports from the Australian Research Council (ARC) (DE150101751), University of Technology Sydney Research Academic Program at Tech Lab (UTS RAPT), University of Technology Sydney Tech Lab Blue Sky Research Scheme and the Systematic Projects of Guangxi Key Laboratory of Disaster Prevention and Structural Safety (Guangxi University), China (2019ZDX004) and State Key Laboratory of Subtropical Building Science (South China University of Technology), China (2019ZA06). The first author would like to thank the support by the Australian Government Research Training Program Scholarship.
Funding Information:
The authors appreciate the financial supports from the Australian Research Council (ARC) ( DE150101751 ), University of Technology Sydney Research Academic Program at Tech Lab (UTS RAPT), University of Technology Sydney Tech Lab Blue Sky Research Scheme and the Systematic Projects of Guangxi Key Laboratory of Disaster Prevention and Structural Safety ( Guangxi University ), China ( 2019ZDX004 ) and State Key Laboratory of Subtropical Building Science ( South China University of Technology ), China ( 2019ZA06 ). The first author would like to thank the support by the Australian Government Research Training Program Scholarship.
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/9
Y1 - 2020/9
N2 - Static nanoindentation and Maximum Likelihood Estimation (MLE) were applied for the nano/micromechanical properties investigation of alkali-activated fly ash (AAFA) in this study. Some critical issues of statistical nanoindentation were fully discussed, including properties of pure gel phase, influence of bin size when using least-square estimation (LSE), and suitable number of components for deconvolution. Results indicate that the model estimated by MLE method can effectively reflect the micromechanical distribution of AAFA. The number of components needed to separate sodium aluminosilicate hydrate (N-A-S-H) gels is sometimes more than the normally used 3 or 4, depending on the sample and testing factors. The gel phase does not always display as a prominent peak in the histogram and is easy to be mixed with other adjacent peaks even if the bin size is small, indicating the challenges of employing the LSE method to investigate the gel phase in highly heterogeneous materials, such as geopolymer.
AB - Static nanoindentation and Maximum Likelihood Estimation (MLE) were applied for the nano/micromechanical properties investigation of alkali-activated fly ash (AAFA) in this study. Some critical issues of statistical nanoindentation were fully discussed, including properties of pure gel phase, influence of bin size when using least-square estimation (LSE), and suitable number of components for deconvolution. Results indicate that the model estimated by MLE method can effectively reflect the micromechanical distribution of AAFA. The number of components needed to separate sodium aluminosilicate hydrate (N-A-S-H) gels is sometimes more than the normally used 3 or 4, depending on the sample and testing factors. The gel phase does not always display as a prominent peak in the histogram and is easy to be mixed with other adjacent peaks even if the bin size is small, indicating the challenges of employing the LSE method to investigate the gel phase in highly heterogeneous materials, such as geopolymer.
KW - Alkali activated fly ash geopolymer
KW - Maximum likelihood estimation (MLE)
KW - Nano/micromechanical properties
KW - Sodium aluminosilicate hydrate (N-A-S-H)
KW - Statistical nanoindentation
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U2 - 10.1016/j.cemconres.2020.106112
DO - 10.1016/j.cemconres.2020.106112
M3 - Article
AN - SCOPUS:85085257674
VL - 135
JO - Cement and Concrete Research
JF - Cement and Concrete Research
SN - 0008-8846
M1 - 106112
ER -