Structural Feature Based Computational Approach Of Toxicity Prediction: Ionic Liquids toxicity: Effect of Anions and Cations - Brossura
Sinossi
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 (ω),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.
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L'autore
Dr 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. from Univ. Teknologi PETRONAS, Malaysia. His research area is design and development of advanced materials and chemical processes.
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Structural Feature Based Computational Approach Of Toxicity Prediction
Editore:
LAP LAMBERT Academic Publishing Mrz 2017, 2017
ISBN 10: 3330050616
ISBN 13: 9783330050617
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9783330050617
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Structural Feature Based Computational Approach Of Toxicity Prediction: Ionic Liquids toxicity: Effect of Anions and Cations
Editore:
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330050616
ISBN 13: 9783330050617
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Paperback. Condizione: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock. Codice articolo 3330050616
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Structural Feature Based Computational Approach Of Toxicity Prediction
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330050616
ISBN 13: 9783330050617
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Condizione: 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. . Codice articolo 151234679
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Structural Feature Based Computational Approach Of Toxicity Prediction
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LAP LAMBERT Academic Publishing Mär 2017, 2017
ISBN 10: 3330050616
ISBN 13: 9783330050617
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9783330050617
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Structural Feature Based Computational Approach Of Toxicity Prediction : Ionic Liquids toxicity: Effect of Anions and Cations
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330050616
ISBN 13: 9783330050617
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9783330050617
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Structural Feature Based Computational Approach Of Toxicity Prediction | Ionic Liquids toxicity: Effect of Anions and Cations
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330050616
ISBN 13: 9783330050617
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Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: 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. Codice articolo 108769707
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