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Tsui, C. P.

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  • Tsui, C. P. (1)
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Surface characterisation of PLLA polymer in HAp/PLLA biocomposite material by means of nanoindentation and artificial neural networks

Aleksendrić, D.; Balać, Igor; Tang, C. Y.; Tsui, C. P.; Uskoković, Petar S.; Uskoković, Dragan

(Maney Publishing, 2010)

TY  - JOUR
AU  - Aleksendrić, D.
AU  - Balać, Igor
AU  - Tang, C. Y.
AU  - Tsui, C. P.
AU  - Uskoković, Petar S.
AU  - Uskoković, Dragan
PY  - 2010
UR  - http://dais.sanu.ac.rs/123456789/3432
AB  - In this paper, the mechanical properties of polymer matrix phase (modulus of elasticity, yield stress and work hardening rate) have been determined using combined methods such as nanoindentation, finite element modelling and artificial neural networks. The approach of neural modelling has been employed for the functional approximation of the nanoindentation load-displacement curves. The data obtained from finite element analyses have been used for the artificial neural networks training and validating. The neural model of polymer matrix phase of poly-l-lactide (PLLA) polymer in hydroxyapatite (HAp)/PLLA mechanical behaviour has been developed and tested versus unknown data related to the load-displacement curves that were not used during the neural network training. Based on this neural model, the nanoindentation matrix phase properties of PLLA polymer in HAp/PLLA composite have been predicted. © 2010 Institute of Materials, Minerals and Mining.
PB  - Maney Publishing
T2  - Advances in Applied Ceramics
T1  - Surface characterisation of PLLA polymer in HAp/PLLA biocomposite material by means of nanoindentation and artificial neural networks
SP  - 65
EP  - 70
VL  - 109
IS  - 2
DO  - 10.1179/174367509X12502621261613
ER  - 
@article{
author = "Aleksendrić, D. and Balać, Igor and Tang, C. Y. and Tsui, C. P. and Uskoković, Petar S. and Uskoković, Dragan",
year = "2010",
url = "http://dais.sanu.ac.rs/123456789/3432",
abstract = "In this paper, the mechanical properties of polymer matrix phase (modulus of elasticity, yield stress and work hardening rate) have been determined using combined methods such as nanoindentation, finite element modelling and artificial neural networks. The approach of neural modelling has been employed for the functional approximation of the nanoindentation load-displacement curves. The data obtained from finite element analyses have been used for the artificial neural networks training and validating. The neural model of polymer matrix phase of poly-l-lactide (PLLA) polymer in hydroxyapatite (HAp)/PLLA mechanical behaviour has been developed and tested versus unknown data related to the load-displacement curves that were not used during the neural network training. Based on this neural model, the nanoindentation matrix phase properties of PLLA polymer in HAp/PLLA composite have been predicted. © 2010 Institute of Materials, Minerals and Mining.",
publisher = "Maney Publishing",
journal = "Advances in Applied Ceramics",
title = "Surface characterisation of PLLA polymer in HAp/PLLA biocomposite material by means of nanoindentation and artificial neural networks",
pages = "65-70",
volume = "109",
number = "2",
doi = "10.1179/174367509X12502621261613"
}
Aleksendrić, D., Balać, I., Tang, C. Y., Tsui, C. P., Uskoković, P. S.,& Uskoković, D. (2010). Surface characterisation of PLLA polymer in HAp/PLLA biocomposite material by means of nanoindentation and artificial neural networks.
Advances in Applied CeramicsManey Publishing., 109(2), 65-70. 
https://doi.org/10.1179/174367509X12502621261613
Aleksendrić D, Balać I, Tang CY, Tsui CP, Uskoković PS, Uskoković D. Surface characterisation of PLLA polymer in HAp/PLLA biocomposite material by means of nanoindentation and artificial neural networks. Advances in Applied Ceramics. 2010;109(2):65-70
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