• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

The Analysis with Localization of Palladium Nanoparticles Sprayed on the Carbon Substrate

Student: Osipova Anna

Supervisor: Galina Chulkova

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Materials. Devices. Nanotechnology (Master)

Final Grade: 8

Year of Graduation: 2021

This paper presents a detailed description of the phenomenon under study, this kind of ordering of palladium nanoparticles when applied to their carbon substrate, and the creation of a deep machine learning algorithm (or a neural network) for automatic recognition of ordering from a micrograph of the analyzed sample. Neural networks have found their application in medicine, zoology, statistics, economics, neuro-physics, and other coming scientific fields of study. The creation of such software for the studied dataset has potential in the sphere of micrographs recognition, although if there are neural networks for recognizing the type of image, there is no program that analyzes the physical properties reflected in the image.

Full text (added May 19, 2021)

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses