Modeling the Nucleation and Growth of Colloidal Nanoparticles
| dc.contributor.author | Mozaffari, Saeed | en |
| dc.contributor.committeechair | Karim, Ayman M. | en |
| dc.contributor.committeemember | Lin, Feng | en |
| dc.contributor.committeemember | Ducker, William A. | en |
| dc.contributor.committeemember | Deshmukh, Sanket A. | en |
| dc.contributor.department | Chemical Engineering | en |
| dc.date.accessioned | 2021-07-30T06:00:07Z | en |
| dc.date.available | 2021-07-30T06:00:07Z | en |
| dc.date.issued | 2020-02-05 | en |
| dc.description.abstract | Controlling the size and size distribution of colloidal nanoparticles have gained extraordinary attention as their physical and chemical properties are strongly affected by size. Ligands are widely used to control the size and size distribution of nanoparticles; however, their exact roles in controlling the nanoparticle size distribution and the way they affect the nucleation and growth kinetics are poorly understood. Therefore, understanding the nucleation and growth mechanisms and developing theoretical/modeling framework will pave the way towards controlled synthesis of colloidal nanoparticles with desired sizes and polydispersity. This dissertation focuses on identifying the possible roles of ligands and size on the kinetics of nanoparticle formation and growth using in-situ characterization tools such as small-angle X-ray scattering (SAXS) and kinetic modeling. The presented work further focuses on developing kinetic models to capture the main nucleation and growth reactions and examines how ligand-metal interactions could potentially alter the rate of nucleation and growth rates, and consequently the nanoparticle size distribution. Additionally, this work highlights the importance of using multi-observables including the concentration of nanoparticles, size and/or precursor consumption, and polydispersity to differentiate between different nucleation and growth models and extract accurate information on the rates of nanoparticle nucleation and growth. Specifically, during the formation and growth of colloidal nanoparticles, complex reactions are occurring and as such nucleation and growth can take place through various reaction pathways. Therefore, sensitivity analysis was applied to effectively compare different nucleation and growth models and identify the most important reactions and obtain a reduced model (e.g. a minimalistic model) required for efficient data analysis. In the following chapters, a more sophisticated modeling approach is presented (population balance model) capable of capturing the average-properties of nanoparticle size distribution. PBM allows us to predict the growth rate of nanoparticles of different sizes, the ligand surface coverage for each individual size, and the parameters involved in altering the size distribution. Additionally, thermodynamic calculations of nanoparticle growth and ligand-metal binding as a function of size and ligand surface coverage were conducted to further shed light on the kinetics of nanoparticle formation and growth. The combination of kinetic modeling, in-situ SAXS and thermodynamic calculations can significantly advance the understanding of nucleation and growth mechanisms and guide toward controlling size and polydispersity. | en |
| dc.description.abstractgeneral | The synthesis of colloidal metal nanoparticles with superior control over size and size distribution, and has attracted much attention given the wide applications of these nanomaterials in the fields of catalysis, photonics, and electronics. Obtaining nanoparticles with desired sizes and polydispersity is vital for enhancing the consistency and performance for specific applications (e.g., catalytic converters for automotive emission). Ligands are often employed to prevent agglomeration and also control the nanoparticle size and size distribution. Ligands can affect the precursor reactivity and therefore the reduction/nucleation by binding with the metal precursor. Nucleation refers to the assimilation of few atoms to form initial nuclei acting as templates for nanoparticle growth. Additionally, ligands can bind with the nanoparticle surface sites and change the rate of surface growth and therefore the final nanoparticle size. Despite strong effects of ligands in the colloidal nanoparticle synthesis, their exact role in the nucleation and growth kinetics is yet to be identified. Additionally, nucleation and growth models capable of unraveling the underlying mechanisms of nucleation and growth in the presence of ligands are still lacking in the literature. Therefore, obtaining nanoparticles with desired sizes and polydispersity mostly relies on trial-and-error approach making the synthesis costly and inefficient. As such, developing models capable of predicting suitable synthesis conditions is contingent upon understanding the chemistry and mechanism involved during nanoparticles formation. Therefore, in this study, novel kinetic models were developed to capture the nucleation and growth kinetics of colloidal metal nanoparticles under different synthetic conditions (different types of solvents, different concentrations of ligand and metal). In-situ SAXS was further employed to measure the average diameter, concentration of nanoparticles, and polydispersity during the synthesis and extract the nucleation and growth rates (evolution of concentration of nanoparticles and size). First, an average-property model was developed to account for ligand-metal bindings and capture the size and concentration of nanoparticles during the synthesis. Then, a more complex modeling approach; PBM, accompanied by the thermodynamic calculations of surface growth and ligand-nanoparticle binding enthalpies was implemented to capture the size distribution. As it will be shown later, the determination of the underlying mechanisms resulted in a highly predictive kinetic model capable of predicting the synthetic conditions to obtain nanoparticles with desired sizes. The proposed methodology can serve as a powerful tool to synthesize nanoparticles with specific sizes and polydispersity. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:23399 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/104448 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Colloidal nanoparticles | en |
| dc.subject | ligands | en |
| dc.subject | palladium | en |
| dc.subject | nucleation and growth kinetics | en |
| dc.subject | LaMer | en |
| dc.subject | size distribution | en |
| dc.subject | kinetic modeling | en |
| dc.subject | population balance modeling | en |
| dc.title | Modeling the Nucleation and Growth of Colloidal Nanoparticles | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Chemical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |