Application of Mathematical Methods in Physical and Technical Sciences

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematical Physics".

Deadline for manuscript submissions: 30 May 2024 | Viewed by 1141

Special Issue Editors


E-Mail Website
Guest Editor
Institute of Physics and Mechanics, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
Interests: mathematical and computer modeling of physical, energy, biological and regulatory processes; fractal analysis; neural networks

E-Mail Website
Guest Editor
Institute of Physics and Mechanics, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
Interests: mathematical modeling of physical processes; computer science; nuclear magnetic resonance; control of the flowing medium; optics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of Mathematics focuses on new developments in the use of mathematical methods to solve problems in the physical and technical sciences. The problems arising here are often large-scale and complex, requiring various mathematical methods and huge amounts of calculations for their analysis and finding a solution. However, the development of computer technology and numerical methods over the past few decades, as well as of machine learning and neural networks, has significantly expanded the ability of scientists to look for approaches to solving such problems. At the same time, both the accuracy of the solution and the speed of obtaining it are crucial, especially in tasks that are required to obtain them in real-time. Therefore, the relevance of applying mathematical methods is now incredibly high.

The purpose of this Special Issue is to collect new results through the application of known and new mathematical methods for solving problems in physics, chemistry, astronomy, earth sciences, etc. We invite authors whose research is related to the use of mathematical methods for computer modeling, analysis and signal processing, and solving optimization and other problems in the field of physical sciences to submit their articles for publication.

Prof. Dr. Valery Antonov
Dr. Roman Vadimovich Davydov
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • physical and technical sciences
  • mathematical modeling
  • data analysis
  • signal processing
  • machine learning
  • neural networks

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

12 pages, 2643 KiB  
Article
Using the BWA (Bertaut-Warren-Averbach) Method to Optimize Crystalline Powders Such as LiFePO4
by Aleksandr Bobyl, Oleg Konkov, Mislimat Faradzheva and Igor Kasatkin
Mathematics 2023, 11(18), 3963; https://doi.org/10.3390/math11183963 - 18 Sep 2023
Viewed by 904
Abstract
The average sizes L¯i, and their dispersion Wi along the i-th axis, of crystallites in powders are used to determine X-ray diffraction sizes, Di XRD, averaged over crystallite columns within the BWA method. [...] Read more.
The average sizes L¯i, and their dispersion Wi along the i-th axis, of crystallites in powders are used to determine X-ray diffraction sizes, Di XRD, averaged over crystallite columns within the BWA method. Numerical calculations have been carried out for an orthorhombic lattice of crystallites, such as LiFePO4, NMC, having a Lamé’s g-type superellipsoid shape. For lognormal distributions, the analytical expression for the normalized coefficient Kn has been found: Kn=Di XRD/L¯i=Kg,0+KgW2, where Kg,0 is a constant at W→0, Kg is a constant depending on the g -type shape. The dependences of Di XRD are also calculated for normal distribution. A fairly simple equation can be obtained as a result of analytical transformations in the framework of experimentally validated approximations. However, a simpler way is to carry out numerical computer calculations with subsequent approximation of the calculated curves. Using the obtained analytical expressions to control technologies from nuclear fuel to cathode materials will improve the efficiency of flexible energy network, especially storage in autonomous and standby power plants. Full article
Show Figures

Figure 1

Back to TopTop