Vittoria, Antonio (2018) Smart High-Throughput Experimentation. [Tesi di dottorato]

[thumbnail of Antonio_Vittoria_PhD_Thesis_fedOA.pdf]
Preview
Text
Antonio_Vittoria_PhD_Thesis_fedOA.pdf

Download (6MB) | Preview
Item Type: Tesi di dottorato
Resource language: English
Title: Smart High-Throughput Experimentation
Creators:
Creators
Email
Vittoria, Antonio
antonio.vittoria@unina.it
Date: 20 December 2018
Number of Pages: 194
Institution: Università degli Studi di Napoli Federico II
Department: 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
UNSPECIFIED
Date: 20 December 2018
Number of Pages: 194
Keywords: 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
Date Deposited: 19 Jan 2019 16:25
Last Modified: 16 Jun 2020 10:07
URI: http://www.fedoa.unina.it/id/eprint/12714

Collection description

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.

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item