E-viri
Recenzirano
-
Díaz-Rodríguez, Pablo; Cancilla, John; Matute, Gemma; Torrecilla, José S
Industrial & engineering chemistry research, 01/2015, Letnik: 54, Številka: 1Journal Article
A mathematical model based on artificial neural networks (ANNs) has been designed to achieve the estimation of the conductivity of three different binary mixtures containing water and one of the following imidazolium-based ionic liquids: 3-ethyl-methylimidazolium tetrafluoroborate (emimBF4), 3-butyl-methylimidazolium tetrafluoroborate (bmimBF4), and 3-hexyl-methilimidazolium tetrafluoroborate (hmimBF4). It has been accomplished employing the composition of the mixtures (in terms of mole fraction) and the number of carbon atoms that form the lateral chain of the imidazolium cation as independent variables. All the utilized data was gathered from the literature and it corresponds to measurements that were carried out at 298.15 K. The mean prediction error for the estimation of this property was 6.42% and its R 2 value 0.991. These results support that the application of nonlinear mathematical models which rely on ANNs can lead to an accurate estimation of ionic conductivity values of aqueous binary mixtures of imidazolium-based ionic liquids.
![loading ... loading ...](themes/default/img/ajax-loading.gif)
Vnos na polico
Trajna povezava
- URL:
Faktor vpliva
Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Baze podatkov, v katerih je revija indeksirana
Ime baze podatkov | Področje | Leto |
---|
Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
---|
Vir: Osebne bibliografije
in: SICRIS
To gradivo vam je dostopno v celotnem besedilu. Če kljub temu želite naročiti gradivo, kliknite gumb Nadaljuj.