Quantitative Analysis of the UV–Vis Spectra for Gold Nanoparticles Powered by Supervised Machine Learning-Reference-Cited by-同舟云学术

Quantitative Analysis of the UV–Vis Spectra for Gold Nanoparticles Powered by Supervised Machine Learning

Published:2021-04-15 Issue:16 Volume:125 Page:8656-8666
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Pashkov D. M.¹²,Guda A. A.¹^ORCID,Kirichkov M. V.¹,Guda S. A.¹²,Martini A.¹³,Soldatov S. A.¹,Soldatov A. V.¹

Affiliation:

1. The Smart Materials Research Institute, Southern Federal University, Sladkova 178/24, Rostov-on-Don 344090, Russia

2. Institute of Mathematics, Mechanics and Computer Science, Southern Federal University, Milchakova 8a, Rostov-on-Don 344090, Russia

3. Department of Chemistry, INSTM Reference Center and NIS and CrisDi Interdepartmental Centers, University of Torino, Via P. Giuria 7, 10125 Torino, Italy

Funder

Ministry of Science and Higher Education of the Russian Federation

Publisher

American Chemical Society (ACS)

Subject

Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.0c10680

Reference63 articles.

1. Gold nanoparticles as an outstanding catalyst for the hydrogen evolution reaction

2. Thienylbenzotriazole promoted highly active gold nanoparticles supported on N-doped graphene as efficient catalysts in water and a mechanism exploration

3. Mesoporous silica supported orderly-spaced gold nanoparticles SERS-based sensor for pesticides detection in food

4. Fabrication of gold nanorods for SERS detection of thiabendazole in apple

5. Recent advances in gold nanoparticles for biomedical applications: from hybrid structures to multi-functionality

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