Investigation of opal nanostructures using scanning probe microscopy

Syritskii, A. B.; Panfilova, E. V.

doi:10.1088/1757-899x/443/1/012035

Cited by 4 publications

(1 citation statement)

References 5 publications

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“…Students can, depending on their background and interests, choose the research fields such as processing techniques, specialized equipment and key materials of electronics, nanoelectronics and nanoengineering. In their research, they are engaged in the development of technologies, machines and mechanisms, for example, vacuum technics [4,5], vacuum [6,7] and colloidal [8,9] thin films deposition processes, various lithographic and etching processes, etc. The range of tasks that students solve is very wide.…”

Section: Introductionmentioning

confidence: 99%

Skill Oriented Online Master’s Course “Neural Network Modeling of Complex Technical Systems”

Panfilova

2020

ITM Web Conf.

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In this paper we consider the application of online course “Neural Network modeling of Complex Technical Systems” in the Master’s degree programs in the field of nanotechnology and nanoengineering in Bauman Moscow State Technical University. The course has rather practical than theoretical nature. The aim of this course is skill oriented learning. Nowadays neural network models have become a powerful tool of scientific research for engineers and students. The methods studied during the study of the discipline can be applied to estimation, modeling, classification, clustering, forecasting and more. The neural networks modeling plays a significant role in Master’s education and student’s research work. Neural Networks models are successfully presented in graduation theses. Thanks to online educations students can practice at their own pace and study modern neural networks software products, methods of data preparing, designing and training neural network and then apply these algorithms in practice. According to the steps of neural network modeling algorithm the course consists of three main parts and conclusive one. In this paper course structure and study results are presented.

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Section: Introductionmentioning

confidence: 99%

Skill Oriented Online Master’s Course “Neural Network Modeling of Complex Technical Systems”

Panfilova

2020

ITM Web Conf.

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Automation of the Opal Colloidal Films Obtaining Processes

Panfilova

Dyubanov²

2020

Lecture Notes in Electrical Engineering

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Uncertainty of tunnelling microscopy measurements of the field emission from multilayer nanostructures

Panfilova

Syritskii

Ibragimov

2019

IOP Conf. Ser.: Mater. Sci. Eng.

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The paper presents the results of scanning tunnelling microscopy investigation of electron field emission from multilayer nanostructures based on silica opal film Cr-SiO2-Au-C. Opal film was deposited in colloidal solvent, while other films – by vacuum deposition methods. We discuss the problem of uncertainty of measurements of the field enhancement factor and carbon nano-edge sizes using the current versus applied voltage characteristics of the emission. Field enhancement factor is defined as the ratio of the electric field at the nano-edge to the field applied to the gap. We found that at well-controlled experimental conditions the combined uncertainty of field enhancement factor measurements is ∼15% based on a 95% confidence interval and the combined uncertainty of nano-edge sizes measurements is ∼18% based on a 95% confidence interval.

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Investigation of opal nanostructures using scanning probe microscopy

Cited by 4 publications

References 5 publications

Skill Oriented Online Master’s Course “Neural Network Modeling of Complex Technical Systems”

Skill Oriented Online Master’s Course “Neural Network Modeling of Complex Technical Systems”

Automation of the Opal Colloidal Films Obtaining Processes

Uncertainty of tunnelling microscopy measurements of the field emission from multilayer nanostructures

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