Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330050616 ISBN 13: 9783330050617
Librería: Revaluation Books, Exeter, Reino Unido
EUR 61,09
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330050616 ISBN 13: 9783330050617
Librería: preigu, Osnabrück, Alemania
EUR 33,20
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Structural Feature Based Computational Approach Of Toxicity Prediction | Ionic Liquids toxicity: Effect of Anions and Cations | Md Abdus Salam (u. a.) | Taschenbuch | 64 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330050617 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Mrz 2017, 2017
ISBN 10: 3330050616 ISBN 13: 9783330050617
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 35,90
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Ionic liquids(IL's) toxicity database is very important now a days due to its diversified application. An economic IL's toxicity prediction method support in enlarging the toxic IL's database and a tool of a safe and sustainable environment.There is no DFT based IL's toxicity prediction method so far. The contents of the book present a novel investigation using the density functional theory (DFT) in predicting the toxicity of ionic liquids. Seventeen DFT based reactivity descriptors were investigated and detailed out in chapter 2.Electrophilic indices ( ),the energy of highest occupied (EHOMO) and lowest unoccupied molecular orbital,(ELUMO) and energy gap ( E) were selected as the best toxicity descriptors of IL's via Pearson correlation and multiple linear regression analyses that discussed in chapter 4.The principle components analysis(PCA) demonstrated the distribution and interrelation of descriptors of the model. A multiple linear regression (MLR) analysis on selected descriptors derived the model equation for toxicity prediction of ionic liquids. The toxicity perdition method help researchers, toxicologist and for industrial application in knowing the level of their toxicity. 64 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330050616 ISBN 13: 9783330050617
Librería: moluna, Greven, Alemania
EUR 31,27
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Salam Md AbdusDr Md Abdus Salam is a scientist of BCSIR and Ex-faculty member of UTP, Malaysia. He has extensive experiences in strengthening industry-relevant research and academic excellence. He has obtained a PhD in Chemical Eng. .
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Mär 2017, 2017
ISBN 10: 3330050616 ISBN 13: 9783330050617
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 35,90
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Ionic liquids(IL's) toxicity database is very important now a days due to its diversified application. An economic IL's toxicity prediction method support in enlarging the toxic IL's database and a tool of a safe and sustainable environment.There is no DFT based IL's toxicity prediction method so far. The contents of the book present a novel investigation using the density functional theory (DFT) in predicting the toxicity of ionic liquids. Seventeen DFT based reactivity descriptors were investigated and detailed out in chapter 2.Electrophilic indices (¿),the energy of highest occupied (EHOMO) and lowest unoccupied molecular orbital,(ELUMO) and energy gap (¿E) were selected as the best toxicity descriptors of IL's via Pearson correlation and multiple linear regression analyses that discussed in chapter 4.The principle components analysis(PCA) demonstrated the distribution and interrelation of descriptors of the model. A multiple linear regression (MLR) analysis on selected descriptors derived the model equation for toxicity prediction of ionic liquids. The toxicity perdition method help researchers, toxicologist and for industrial application in knowing the level of their toxicity.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330050616 ISBN 13: 9783330050617
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 35,90
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Ionic liquids(IL's) toxicity database is very important now a days due to its diversified application. An economic IL's toxicity prediction method support in enlarging the toxic IL's database and a tool of a safe and sustainable environment.There is no DFT based IL's toxicity prediction method so far. The contents of the book present a novel investigation using the density functional theory (DFT) in predicting the toxicity of ionic liquids. Seventeen DFT based reactivity descriptors were investigated and detailed out in chapter 2.Electrophilic indices ( ),the energy of highest occupied (EHOMO) and lowest unoccupied molecular orbital,(ELUMO) and energy gap ( E) were selected as the best toxicity descriptors of IL's via Pearson correlation and multiple linear regression analyses that discussed in chapter 4.The principle components analysis(PCA) demonstrated the distribution and interrelation of descriptors of the model. A multiple linear regression (MLR) analysis on selected descriptors derived the model equation for toxicity prediction of ionic liquids. The toxicity perdition method help researchers, toxicologist and for industrial application in knowing the level of their toxicity.