Vittoria, Antonio (2018) Smart High-Throughput Experimentation. [Tesi di dottorato]
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Antonio_Vittoria_PhD_Thesis_fedOA.pdf Download (6MB) | Anteprima |
| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Smart High-Throughput Experimentation |
| Autori: | Autore Email Vittoria, Antonio antonio.vittoria@unina.it |
| Data: | 20 Dicembre 2018 |
| Numero di pagine: | 194 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Scienze Chimiche |
| Dottorato: | Scienze chimiche |
| Ciclo di dottorato: | 31 |
| Coordinatore del Corso di dottorato: | nome email Paduano, Luigi lpaduano@unina.it |
| Tutor: | nome email Busico, Vincenzo [non definito] |
| Data: | 20 Dicembre 2018 |
| Numero di pagine: | 194 |
| Parole chiave: | High-Throughput Experimentation; polyolefin; Ziegler-Natta; catalysis; polymerization; QSAR; polimerizzazione; catalisi; workflow; |
| Settori scientifico-disciplinari del MIUR: | Area 03 - Scienze chimiche > CHIM/03 - Chimica generale e inorganica |
| Depositato il: | 19 Gen 2019 16:25 |
| Ultima modifica: | 16 Giu 2020 10:07 |
| URI: | http://www.fedoa.unina.it/id/eprint/12714 |
Abstract
This PhD project aimed to improve the effectiveness of a trial-and-error approach to olefin polymerization catalysis, one of the most important chemical technologies, by means of High Throughput Experimentation (HTE) methodologies. The project was hosted at the Laboratory of Stereoselective Polymerizations (LSP) of the Federico II University, which is world-leading in HTE catalyst screenings with optimization purposes, and sponsored by HTExplore srl, an academic spin-off of LSP delivering HTE services to polyolefin producers. The general objective was to introduce protocols for ‘smart’ applications of the existing HTE workflow of LSP to complex chemical problems in polyolefin catalysis. In particular, methods for the rapid and accurate determination of the Quantitative Structure-Activity Relationship (QSAR) of representative molecular or heterogeneous catalyst formulations were implemented as the basis for statistical modeling with predictive ability.
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