Since their discovery over 30 years ago, ordered mesoporous silica (OMS) has been
widely demonstrated to be an incredibly useful and valuable nanomaterial, in a variety
of applications. Its usefulness is derived from its underlying structure, consisting of
well-ordered mesopores, the size of which can be tuned by modifying the synthesis
procedure used. This structure is determined early in the synthesis by the self-assembly
of a surfactant template in the presence of a silica precursor. Therefore, understanding
the mechanisms underpinning this self-assembly behaviour allows the properties of the
final material to be more readily controlled. However, efforts to produce OMS on a
larger scale have been unsuccessful due to several factors surrounding its laboratory
synthesis route, which make it uneconomical and unsustainable at a commerical scale.
While greener, more scalable synthesis routes for producing porous silica exist, they are
unable to produce materials with the same degree of order as OMS, hampering their
effectiveness in many applications. Understanding how the degree of order of OMS is
determined and maintained during synthesis is therefore of utmost importance, in order
to develop new, greener synthesis routes for this valuable class of nanomaterials.
In this thesis, the mechanisms which determine the degree of structural ordering in
OMS are investigated in detail. Both computational and experimental approaches are
utilized. In the computational work, multi-scale modelling is used to develop a coarsegrained model for the self-assembly of OMS. In the experimental work, the design of
experiments approach is taken, allowing relationships between synthesis conditions and
material properties to be established, with a particular focus on the degree of order of
samples produced. This work also presents a rapid room-temperature synthesis route
for producing OMS, demonstrating a greener pathway for producing these materials
than the traditional synthesis method, which requires long reaction times and harsh
conditions. In both approaches, the use of bio-inspired additives to aid in the synthesis
of OMS is investigated, demonstrating that if correctly chosen, they may be used to
improve the degree of order of materials obtained through this new synthesis route.
The computational portion of the work is then expanded to study the pH-responsive
surfactant, dodecylamine, showing how its self-assembly behaviour is strongly dictated
by changes in the proportion of charged surfactant species, a behaviour that could be
exploited to produce alternative routes for producing OMS.
This work identifies that two related, but distinct, stages of OMS synthesis are
responsible for dictating the degree of order of the resultant material. The first of
these is the self-assembly process, which is shown to be most strongly influenced by
charge-matching behaviour between surfactant and silica species. This highlights the
importance of carefully controlling the relative quantities of charged silica precursor,
and charged surfactant species, which is strongly dependent on both the relative concentrations of these species in solution, and the system pH. The second stage of OMS
synthesis which strongly influences the ordering of pores is the condensation of silica
precursor species, which effectively locks in the structure formed by self-assembly. This
work shows that when these condensation reactions proceed rapidly, the ordered structure is maintained, while slower reactions lead to disordering of the silica-surfactant
mesophase before it can be locked in. Once again, system pH plays a strong role in this
stage of the synthesis, since the kinetics of silica condensation is strongly dependent
on it. In addition, if carefully selected, bio-inspired additives can aid in locking in the
ordered structure by catalysing silica condensation reactions at the silica-surfactant interface. These findings demonstrate the effectiveness of computational modelling as a
tool to better understand the complex mechanisms governing order formation in OMS
| Date of Award | 19 May 2025 |
|---|
| Original language | English |
|---|
| Awarding Institution | - University Of Strathclyde
|
|---|
| Sponsors | EPSRC (Engineering and Physical Sciences Research Council) |
|---|
| Supervisor | Miguel Jorge (Supervisor) & Javier Cardona Amengual (Supervisor) |
|---|