This PhD thesis combines chemistry and computer science, leveraging computational models to predict the behavior of real systems. The integration of dedicated software accelerates scientific research by formulating robust hypotheses that reduce the time required for experimental investigations, which are nevertheless essential to validate any theory. The thesis focuses on the photocatalytic properties of titanium dioxide (TiO₂, titania) for the conversion of carbon dioxide (CO₂) into energy carriers. This process, crucial for the energy transition, aims to reduce air pollutants and generate a net-zero carbon cycle. To overcome the high thermodynamic stability of CO₂, the catalyst must be highly selective, favoring interaction only when the molecule is adsorbed on its surface. The presented study explores adsorption geometries using Density Functional Theory (DFT), validating data simulated via vibrational spectroscopy. Simulations confirm that the material's reactivity depends on the exposed crystal plane, which is why this critical factor was considered in the synthesis of the samples. The investigated methodologies were also effectively applied to parallel projects, where the key focus was closely tied to the capture and monitoring of environmental pollutants.
Questa tesi di dottorato unisce chimica e informatica, sfruttando modelli computazionali per prevedere il comportamento di sistemi reali. L'integrazione di software dedicati accelera la ricerca scientifica, formulando ipotesi robuste che riducono i tempi delle indagini sperimentali, le quali restano comunque indispensabili per validare ogni teoria. Il focus della tesi si concentra sulle proprietà fotocatalitiche del biossido di titanio (TiO₂, titania) per la conversione dell'anidride carbonica (CO₂) in vettori energetici. Questo processo, cruciale per la transizione energetica, mira a ridurre gli inquinanti atmosferici e a generare un ciclo del carbonio a emissioni nette pari a zero. Per superare l'elevata stabilità termodinamica della CO₂, il catalizzatore deve essere altamente selettivo, favorendo l'interazione solo quando la molecola è adsorbita sulla sua superficie. Lo studio presentato approfondisce le geometrie di adsorbimento mediante la Teoria del Funzionale della Densità (DFT), convalidando i dati simulati tramite spettroscopia vibrazionale. Le simulazioni confermano che la reattività del materiale dipende dal piano cristallino esposto, motivo per cui la sintesi dei campioni ha considerato questo fattore critico. Le metodologie investigate sono state applicate efficacemente anche a progetti paralleli, in cui la tematica cardine è stata fortemente legata a cattura e monitoraggio di inquinanti ambientali.
Hybrid computational methods for environment and health: applications in catalysis, sensing, and advanced diagnostics.
Speziani, Michele
2026
Abstract
This PhD thesis combines chemistry and computer science, leveraging computational models to predict the behavior of real systems. The integration of dedicated software accelerates scientific research by formulating robust hypotheses that reduce the time required for experimental investigations, which are nevertheless essential to validate any theory. The thesis focuses on the photocatalytic properties of titanium dioxide (TiO₂, titania) for the conversion of carbon dioxide (CO₂) into energy carriers. This process, crucial for the energy transition, aims to reduce air pollutants and generate a net-zero carbon cycle. To overcome the high thermodynamic stability of CO₂, the catalyst must be highly selective, favoring interaction only when the molecule is adsorbed on its surface. The presented study explores adsorption geometries using Density Functional Theory (DFT), validating data simulated via vibrational spectroscopy. Simulations confirm that the material's reactivity depends on the exposed crystal plane, which is why this critical factor was considered in the synthesis of the samples. The investigated methodologies were also effectively applied to parallel projects, where the key focus was closely tied to the capture and monitoring of environmental pollutants.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/385250
URN:NBN:IT:UNIBS-385250