Machine learning for predicting the average length of vertically aligned TiO2 nanotubes-Reference-Cited by-同舟云学术

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Machine learning for predicting the average length of vertically aligned TiO2 nanotubes

Published:2020-07-01 Issue:7 Volume:10 Page:075116
ISSN:2158-3226
Container-title:AIP Advances
language:en
Short-container-title:AIP Advances

Author:

Caro-Gutiérrez Jesús¹^ORCID,González-Navarro Félix F.¹^ORCID,Curiel-Álvarez Mario A.¹^ORCID,Peréz-Landeros Oscar M.¹^ORCID,Valdez-Salas Benjamín¹^ORCID,Radnev-Nedev Nicola¹^ORCID

Affiliation:

1. Engineering Institute, Autonomous University of Baja California, 21100 Mexicali, Mexico

Funder

Consejo Nacional de Ciencia y Tecnología

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0012410

Reference25 articles.

1. Understanding Materials Science

2. TiO2 Nanotubes: Synthesis and Applications

3. The Promotion of Antibacterial Effects of Ti6Al4V Alloy Modified with TiO2Nanotubes Using a Superoxidized Solution

4. Highly sensitive photoelectrochemical detection of glucose based on BiOBr/TiO2 nanotube array p-n heterojunction nanocomposites

5. TiO2 nanotube arrays with a volume expansion factor greater than 2.0: Evidence against the field-assisted ejection theory

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