Surface characterisation of PLLA polymer in HAp/PLLA biocomposite material by means of nanoindentation and artificial neural networks
Authorized Users Only
2010
Authors
Aleksendrić, D.Balać, Igor

Tang, Chak Yin

Tsui, C. P.

Uskoković, Petar S.

Uskoković, Dragan

Article (Published version)

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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.
Keywords:
artificial neural networks / biocomposites / finite element model / nanoindentationSource:
Advances in Applied Ceramics, 2010, 109, 2, 65-70Publisher:
- Maney Publishing
Funding / projects:
- Sinteza funkcionalnih materijala sa kontrolisanom strukturom na molekularnom i nano nivou (RS-142006)
- EUREKA - 3524
DOI: 10.1179/174367509X12502621261613
ISSN: 1743-6753
WoS: 000275344200001
Scopus: 2-s2.0-77749325154
Institution/Community
Институт техничких наука САНУ / Institute of Technical Sciences of SASATY - JOUR AU - Aleksendrić, D. AU - Balać, Igor AU - Tang, Chak Yin AU - Tsui, C. P. AU - Uskoković, Petar S. AU - Uskoković, Dragan PY - 2010 UR - https://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 UR - https://hdl.handle.net/21.15107/rcub_dais_3432 ER -
@article{ author = "Aleksendrić, D. and Balać, Igor and Tang, Chak Yin and Tsui, C. P. and Uskoković, Petar S. and Uskoković, Dragan", year = "2010", 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", url = "https://hdl.handle.net/21.15107/rcub_dais_3432" }
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. in Advances in Applied Ceramics Maney Publishing., 109(2), 65-70. https://doi.org/10.1179/174367509X12502621261613 https://hdl.handle.net/21.15107/rcub_dais_3432
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. in Advances in Applied Ceramics. 2010;109(2):65-70. doi:10.1179/174367509X12502621261613 https://hdl.handle.net/21.15107/rcub_dais_3432 .
Aleksendrić, D., Balać, Igor, Tang, Chak Yin, Tsui, C. P., Uskoković, Petar S., Uskoković, Dragan, "Surface characterisation of PLLA polymer in HAp/PLLA biocomposite material by means of nanoindentation and artificial neural networks" in Advances in Applied Ceramics, 109, no. 2 (2010):65-70, https://doi.org/10.1179/174367509X12502621261613 ., https://hdl.handle.net/21.15107/rcub_dais_3432 .