Abstract
Atmospheric concentrations of carbon dioxide (CO2) are significantly increasing
since the industrial revolution at an accelerating rate causing environmental
impact such as global warming and climate change. Projections indicate that CO2
concentrations will continue to rise to unsustainable levels. This highlights the
scale of the challenge our scientists are facing in order to reduce CO2 emissions
and underpins the importance of promoting green process engineering for the
utilisation of CO2 as a valuable commodity in the process industry. The
transformation of CO2 to value-added chemicals such as organic carbonates
provides a promising technological advancement aimed at reducing CO2
atmospheric concentrations to sustainable levels.
Dimethyl carbonate (DMC) is a promising green compound that exhibits versatile
and excellent chemical properties and therefore finds applications as an
intermediate in the chemical and pharmaceutical industries. DMC has a high
oxygen content and can be used as an oxygenate additive to gasoline to improve
its performance and reduce exhaust emission. The conventional method for DMC
synthesis involves the utilisation of phosgene as a toxic feedstock. Thus, greener
and more sustainable synthetic processes for the synthesis of DMC are required.
Recently, non-toxic synthetic routes have been explored; these include, oxidative
carbonylation of carbon monoxide (CO), oxygen (O2) and MeOH, direct synthesis
from MeOH and CO2 and the transesterification of cyclic carbonates and
methanol (MeOH). The oxidative carbonylation route suffers from the use of
expensive raw materials and corrosive reagents as well as being hazardous due
to the explosive potential of CO. The direct production of DMC from MeOH and
CO2 offers an attractive and green synthetic route for DMC synthesis. Also, the
synthesis of DMC via the transesterification of cyclic carbonates and MeOH,
where cyclic carbonates can be synthesised from their corresponding epoxides
and CO2, makes the synthesis of DMC via transesterification route more
environmentally friendly and desirable in terms of green chemistry and
sustainable development. Therefore, in this research new greener catalytic
processes for DMC synthesis via addition of MeOH to CO2 route and
transesterification route have been explored.
In this work, several commercially available heterogeneous catalysts such as
ceria and lanthana doped zirconia (Ce–La–Zr–O), ceria doped zirconia (Ce–Zr–
O), lanthana doped zirconia (La–Zr–O), lanthanum oxide (La–O) and zirconium
oxide (Zr–O) have been extensively assessed for the synthesis of DMC. Strongly
coupled graphene based inorganic nanocomposites represent an exciting and
new class of functional materials and therefore the utilisation of graphene oxide
(GO) as a suitable support for metal oxide catalysts has been explored. Ceria
doped zirconia graphene nanocomposites (Ce–Zr/GO) have been synthesised
using conventional wet impregnation methods. Samples of Ce–Zr/GO have been
subjected to heat treatment at various temperatures (773 K, 873 K, 973 K and
1073 K) in an attempt to enhance their catalytic performance. As-prepared Ce–
Zr/GO sample and the corresponding heat treated samples have been assessed
for the direct synthesis for DMC from MeOH and CO2. Furthermore, a new
innovative approach has been employed for synthesising advanced, highly
efficient and active heterogeneous catalysts via utilisation of a continuous
hydrothermal flow synthesis (CHFS) reactor. Tin doped zirconium oxide (Zr–Sn–
O) and tin doped zirconia/graphene nanocomposite (Zr–Sn/GO) have been
assessed as suitable heterogeneous catalysts for the synthesis of DMC via the
transesterification route. The catalysts were characterised using various
analytical techniques such as scanning electron microscopy (SEM), transmission
electron microscopy (TEM), powder X-ray diffraction (XRD), X-ray photoelectron
spectroscopy (XPS), Raman spectroscopy and Brunauer-Emmett-Teller (BET)
surface area measurement.
A heterogeneous catalytic process for the synthesis of DMC has been
investigated using a high pressure reactor. The effect of various reaction
parameters such as the reactant molar ratio, catalyst loading, reaction
temperature, CO2 pressure, reaction time and the use of a dehydrating agent was
studied for the optimisation of DMC synthesis. Reusability studies were
conducted to evaluate the long term stability of the heterogeneous catalysts by
recycling and reusing the catalyst several times for the synthesis of DMC. Tin
doped zirconia graphene oxide (Sn–Zr/GO) nanocomposite catalyst has been
found to be the best performed catalyst for the synthesis of DMC as compared to
other catalysts evaluated in this research work. This can be attributed to the
phase composition and crystallinity of the catalyst along with the defects on the
graphene sheet such as, holes, acid/basic groups and presence of residual which
can provide additional active catalytic sites. Catalyst reusability studies evidently
showed that Sn–Zr/GO nanocomposite can be easily recovered and reused
without any significant reduction in the catalytic performance.
Response Surface Methodology (RSM) has track record in helping researchers in
modeling and optimisation of the experimental design for various applications in
food industry, catalysis and chemical reaction engineering. Therefore, it has been
employed to evaluate the relationship between multiple process variables in order
to optimise a specified response (i.e. yield of DMC). RSM using Box-Behneken
design (BBD) was carried out for process modeling and optimisation, with an aim
to better understand the relationship between five operating variables (i.e.
MeOH:PC molar ratio, catalyst loading (w/w), reaction temperature, reaction time
and stirring speed) and their impact on the yield of DMC. A model for the
synthesis of DMC by transesterification of PC and MeOH has been developed
using BBD to compare the experimental data and the predicted results by the
BBD model. Furthermore, regression analysis was applied to establish the
optimum reaction conditions for a maximising DMC synthesis. The BBD model
predicted values are in good agreement with the experimental results.
Original language | English |
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DOIs | |
Publication status | Published - 1 Sept 2015 |
Externally published | Yes |