All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

QSPR Models for Prediction of Redox Potentials Using Optimal Descriptors

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F23%3A10465638" target="_blank" >RIV/00216208:11310/23:10465638 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/978-3-031-28401-4_6" target="_blank" >https://doi.org/10.1007/978-3-031-28401-4_6</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-28401-4_6" target="_blank" >10.1007/978-3-031-28401-4_6</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    QSPR Models for Prediction of Redox Potentials Using Optimal Descriptors

  • Original language description

    The redox potential is an important physicochemical property widely used for the characterization of chemical species, and, as a characteristic constant of a given chemical species, it is also useful for predicting various other properties of the species. In the chapter, we review and discuss the pros and cons of QSPR models for the prediction of redox potentials using optimal descriptors calculated with the SMILES as well as using the so-called hybrid descriptors calculated with considering SMILES and molecular graphs of atomic orbitals.

  • Czech name

  • Czech description

Classification

  • Type

    C - Chapter in a specialist book

  • CEP classification

  • OECD FORD branch

    10406 - Analytical chemistry

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Book/collection name

    QSPR/QSAR Analysis Using SMILES and Quasi-SMILES

  • ISBN

    978-3-031-28400-7

  • Number of pages of the result

    28

  • Pages from-to

    139-166

  • Number of pages of the book

    467

  • Publisher name

    Springer Nature Switzerland AG

  • Place of publication

    Cham

  • UT code for WoS chapter