Dependence of Morphology, Structure, Composition and Biocompatibility of Ca- and P-Doped TiO2 Coatings on PEO Process Parameters

Correction for ‘Intrinsically ferromagnetic Fe-doped TiO2 coatings on titanium for accelerating osteoblast response in vitro’ by Kai Li et al., J. Mater. Chem. B, 2018, DOI: 10.1039/c8tb01414k.

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Photocatalytic activity of doped TiO2 coatings prepared by sputtering deposition

Journal of Materials Processing Technology ◽

10.1016/j.jmatprotec.2007.04.031 ◽

2007 ◽

Vol 192-193 ◽

pp. 60-67 ◽

Cited By ~ 36

Author(s):

Sung-Mao Chiu ◽

Zhi-Sheng Chen ◽

Kuo-Yuan Yang ◽

Yu-Lung Hsu ◽

Dershin Gan

Keyword(s):

Photocatalytic Activity ◽

Sputtering Deposition ◽

Doped Tio2 ◽

Tio2 Coatings

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Corrosion Behavior of Ag-doped TiO2 Coatings on Commercially Pure Titanium in Simulated Body Fluid Solution

Journal of Bionic Engineering ◽

10.1016/s1672-6529(16)60311-6 ◽

2016 ◽

Vol 13 (3) ◽

pp. 397-405 ◽

Cited By ~ 16

Author(s):

Tuba Yetim

Keyword(s):

Simulated Body Fluid ◽

Corrosion Behavior ◽

Body Fluid ◽

Simulated Body Fluid Solution ◽

Pure Titanium ◽

Fluid Solution ◽

Commercially Pure Titanium ◽

Doped Tio2 ◽

Commercially Pure ◽

Tio2 Coatings

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Intrinsically ferromagnetic Fe-doped TiO2 coatings on titanium for accelerating osteoblast response in vitro

Journal of Materials Chemistry B ◽

10.1039/c8tb01414k ◽

2018 ◽

Vol 6 (36) ◽

pp. 5756-5767 ◽

Cited By ~ 12

Author(s):

Kai Li ◽

Ting Yan ◽

Yang Xue ◽

Lijun Guo ◽

Lan Zhang ◽

...

Keyword(s):

Magnetic Field ◽

Osteogenic Differentiation ◽

Doped Tio2 ◽

Tio2 Coatings

An intrinsically magnetic field induced by ferromagnetic TiO2 doped with 4.65 wt% Fe clearly enhances proliferation, osteogenic differentiation of osteoblasts.

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Red shift of absorption spectra of metal-doped TiO2 coatings

Journal of Physics Conference Series ◽

10.1088/1742-6596/1115/3/032055 ◽

2018 ◽

Vol 1115 ◽

pp. 032055

Author(s):

M V Shandrikov ◽

A S Bugaev ◽

A V Vizir ◽

K P Savkin ◽

E M Oks

Keyword(s):

Absorption Spectra ◽

Red Shift ◽

Doped Tio2 ◽

Tio2 Coatings ◽

Metal Doped

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Photocatalytic activities of N doped TiO2 coatings on 316L stainless steel by plasma surface alloying technique

Transactions of Nonferrous Metals Society of China ◽

10.1016/s1003-6326(12)61695-1 ◽

2012 ◽

Vol 22 ◽

pp. s120-s126 ◽

Cited By ~ 7

Author(s):

He-feng WANG ◽

Xue-feng SHU ◽

Xiu-yan LI ◽

Bin TANG

Keyword(s):

Stainless Steel ◽

316L Stainless Steel ◽

Surface Alloying ◽

Plasma Surface ◽

Doped Tio2 ◽

Photocatalytic Activities ◽

Tio2 Coatings ◽

Plasma Surface Alloying Technique ◽

Plasma Surface Alloying

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Neural Modelling of APS Thermal Spray Process Parameters for Optimizing the Hardness, Porosity and Cavitation Erosion Resistance of Al2O3-13 wt% TiO2 Coatings

Processes ◽

10.3390/pr8121544 ◽

2020 ◽

Vol 8 (12) ◽

pp. 1544

Author(s):

Mirosław Szala ◽

Leszek Łatka ◽

Michał Awtoniuk ◽

Marcin Winnicki ◽

Monika Michalak

Keyword(s):

Thermal Spray ◽

Process Parameters ◽

Cavitation Erosion ◽

Erosion Resistance ◽

Ceramic Coatings ◽

Thermal Spray Process ◽

Spray Process ◽

Tio2 Coatings ◽

Cavitation Erosion Resistance ◽

Selection Of

The study aims to elaborate a neural model and algorithm for optimizing hardness and porosity of coatings and thus ensure that they have superior cavitation erosion resistance. Al2O3-13 wt% TiO2 ceramic coatings were deposited onto 316L stainless steel by atmospheric plasma spray (ASP). The coatings were prepared with different values of two spray process parameters: the stand-off distance and torch velocity. Microstructure, porosity and microhardness of the coatings were examined. Cavitation erosion tests were conducted in compliance with the ASTM G32 standard. Artificial neural networks (ANN) were employed to elaborate the model, and the multi-objectives genetic algorithm (MOGA) was used to optimize both properties and cavitation erosion resistance of the coatings. Results were analyzed with MATLAB software by Neural Network Toolbox and Global Optimization Toolbox. The fusion of artificial intelligence methods (ANN + MOGA) is essential for future selection of thermal spray process parameters, especially for the design of ceramic coatings with specified functional properties. Selection of these parameters is a multicriteria decision problem. The proposed method made it possible to find a Pareto front, i.e., trade-offs between several conflicting objectives—maximizing the hardness and cavitation erosion resistance of Al2O3-13 wt% TiO2 coatings and, at the same time, minimizing their porosity.

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