Computer Modeling and Reaction Mechanisms in Chemistry

A special issue of Compounds (ISSN 2673-6918).

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4368

Special Issue Editor


E-Mail Website
Guest Editor
Institute of Chemistry, Saint Petersburg State University, Universitetskii pr., 26, Petergof, 198504 St. Petersburg, Russia
Interests: quantum and computational chemistry; inorganic and coordination chemistry; organometallic chemistry; organic chemistry; catalysis; non-covalent interactions; machine learning and artificial intelligence in chemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computer modeling, machine learning, and artificial intelligence are cutting-edge topics in chemistry today. The application of information technologies in natural sciences can help us to collect big data and understand patterns that are not obvious to humans. In this Special Issue, we plan to collect interdisciplinary works in the fields of computational and quantum chemistry, computational statistics, artificial intelligence, machine learning, neural networks, predictive analytics, data mining, and data science. Manuscripts dealing with chemical compounds; the relationship between the structure, the properties, or the functions of all kinds of compounds (including mechanical, thermal, structural, electric, magnetic, and optical properties); as well as chemical theory (including thermodynamics, kinetics, mechanisms, and reactivity) and applications are welcome. Both conceptual and applied works in any format (from short communications to comprehensive reviews) are welcome. We look forward to your contributions.

Dr. Alexander S. Novikov
Guest Editor

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. Compounds is an international peer-reviewed open access quarterly 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 1000 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

  • computer modeling
  • machine learning
  • artificial intelligence
  • chemistry
  • noncovalent interactions
  • reaction mechanisms
  • compounds
  • molecules
  • chemical substances
  • reactivity

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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

Review

Jump to: Other

10 pages, 1628 KiB  
Review
Recent Progress in the Theoretical Studies of the Noncovalent Interactions of Supramolecular Complexes with Polyhalides and Halometalates
by Alexander S. Novikov
Compounds 2023, 3(1), 27-36; https://doi.org/10.3390/compounds3010003 - 30 Dec 2022
Viewed by 1746
Abstract
Despite the fact that first polyhalides and halometalates have been discovered decades ago, this subject of chemical science has been progressing, and many supramolecular associates with these compounds exhibiting promising properties were reported. In this mini-review, I would like to highlight recent progress [...] Read more.
Despite the fact that first polyhalides and halometalates have been discovered decades ago, this subject of chemical science has been progressing, and many supramolecular associates with these compounds exhibiting promising properties were reported. In this mini-review, I would like to highlight recent progress in theoretical studies of noncovalent interactions in supramolecular complexes with polyhalides and halometalates from our research group. Full article
(This article belongs to the Special Issue Computer Modeling and Reaction Mechanisms in Chemistry)
Show Figures

Figure 1

Other

Jump to: Review

5 pages, 496 KiB  
Perspective
Computer Modeling and Machine Learning in Chemistry and Materials Science: From Properties and Reactions of Small Organic and Inorganic Molecules to the Smart Design of Polymers and Composites
by Alexander S. Novikov
Compounds 2023, 3(3), 459-463; https://doi.org/10.3390/compounds3030034 - 24 Aug 2023
Viewed by 1760
Abstract
Computer modeling, machine learning, and artificial intelligence are currently considered cutting-edge topics in chemistry and materials science. The application of information technologies in natural sciences can help researchers collect big data and understand patterns that are not obvious to humans. In this perspective, [...] Read more.
Computer modeling, machine learning, and artificial intelligence are currently considered cutting-edge topics in chemistry and materials science. The application of information technologies in natural sciences can help researchers collect big data and understand patterns that are not obvious to humans. In this perspective, I would like to highlight the recent achievements of our research group and other researchers in relation to computer modeling and machine learning in chemistry and materials science. Full article
(This article belongs to the Special Issue Computer Modeling and Reaction Mechanisms in Chemistry)
Show Figures

Figure 1

Back to TopTop