Publications

In this work, we develop omniphobic ceramic surfaces possessing flower-like re-entrant structures that can resist surface wetting against not only water but also low surface tension liquids. This can benefit a wide range of potential applications in many ceramic fields. The synergistic strategy to fabricate omniphobic ceramic surfaces relies on the construction of re-entrant structures through pre-roughening. Using TiO 2 microflowers obtained via a hydrothermal approach and post-fluorinating via surface grafting with 1H,1H,2H,2H-perfluorodecyltriethoxysilane (C8) resulted in better metastable Cassie-Baxter state as water droplet roll-off the surface compared to non-textured ceramic surfaces where the water droplet pinned. The C8-TiO 2 -modified ceramic surface (C8/TiO 2 -CRM) can still maintain a high contact angle against palm oil (above nearly 120 o ) within 40 minutes of exposure, whereas the un-textured ceramic surface is fully wetted. In addition, the C8/TiO 2 -CRM has excellent self-cleaning, anti-fouling and “gasphilic” properties. In this work, the robustness of the composite interface from secondary re-entrant structures resulting from TiO 2 micro-flowers is further explained.

Per- and polyfluoroalkyl substances (PFAS) are a class of highly persistent carcinogenic organic pollutants owing to their strong carbon-fluorine bond (C-F) giving them high thermal and chemical stabilities. They are ubiquitous and resistant to degradation which impedes their removal from the environment, especially the water medium. The technologies deployed in conventional wastewater treatment plants (WWTPs) are inefficient and hence, a new technology is required. This chapter gives insight into a number of advanced oxidation processes (AOPs) for the removal of PFAS in water media namely the Fenton-based reaction, the ozonation and the photocatalytic process. Each AOPs theories and mechanisms are explained accordingly. In addition, the results of the past studies done on each standard AOPs and their modifications are discussed. Lastly, comparisons are made between each of the standard AOPs processes and their modified version and also comparisons of all the AOPs processes are discussed in this chapter.

Herein, we report the fabrication of polyaniline with Ag-Pt alloy nanocomposite thin films based amperometric E. coli sensor. The effects of annealing at 300oC during the synthesis of PANI-Ag-Pt nanocomposite thin films are studied. XRD, AFM, FESEM and FTIR spectroscopy analyses are conducted to characterize the films. Sensor performance is investigated by the I-V characteristic of PANI-Ag-Pt films with and without the presence of E. coli. From XRD analysis, annealed films have larger crystallite sizes than non-annealed films. AFM results indicate that annealed films have lower surface roughness but larger grain size than non-annealed films. FESEM images show Ag-Pt nanorods with sizes of 200-300 nm for non-annealed films and Ag-Pt nanocubes with sizes around 100-550 nm for annealed films. The composition of PANI-Ag0.2-Pt0.8 nanocomposite thin film has higher conductivity and performed the maximum sensitivity upon E. coli presence. The sensitivity of annealed PANI-Ag-Pt films is higher than non-annealed PANI-Ag-Pt films.

A modified poly (ether sulfone) (PES) by hydrophilic surface modifying macromolecules (LSMM) incorporated with oxygenated graphitic carbon nitride (OGCN) photocatalyst (PES/OGCN-LSMM) was successfully prepared as a hybrid photocatalytic membrane. The effect of solvent evaporation time during membrane fabrication was studied by focusing on the positioning of LSMM in order to provide the desirable properties of the PES/OGCN-LSMM hybrid membrane for phenol removal performance by photocatalytic and separation. The PES/OGCN-LSMM membranes exhibited a decreased value of contact angle as the solvent evaporation time increased. The SEM images revealed a dense top layer supported by finger-like structures underneath, which was formed for the membranes at 0–4 min solvent evaporation time, while a sponge-like microvoid structure was observed at 5 min of solvent evaporation time. It is interesting to highlight that as the evaporation time increased, the pure water flux decreased as the result of compact denser membrane. Benefitting the special feature of LSMM that tends to migrate upwards upon mixing, the LSMM effectively assisted OGCN photocatalyst to the top layer of the membrane. This was revealed by SEM top surface images that more OGCN photocatalyst particles were seen distributed on the dense top layer of the membrane upon longer solvent evaporation time supported by the membrane topography analysis. It was found that the phenol reduction by rejection and photocatalytic tests was the highest at 5 min solvent evaporation time, whilst water flux was the lowest. The obtained results showed that the LSMM has indeed assisted the positioning of OGCN towards the top layer of the membrane and consequently increased the photocatalytic activity of the membrane on phenol.

Sulfonated poly (ether ether ketone) (SPEEK)/Cloisite 15A® nanocomposite membranes were prepared via solution intercalation method. For better dispersion of nanoclay in the polymer matrix, the solution intercalation method was modified and a compatibilizer was introduced. The state of nanoclay dispersion was determined by FESEM. The effect of the solution formulation preparation method and compatibilizer on the performance properties such as proton conductivity and methanol permeability of all membranes was studied. FESEM analysis confirmed that SPEEK/Cloisite 15A® nanocomposite membrane prepared via modified solution intercalation method and in the presence of compatibilizer was the best membrane in terms of its morphological structure. Due to its well nanoclay distribution in polymer matrix, this kind of membrane exhibited the highest selectivity owing to its high proton conductivity and low methanol permeability. SPEEK/Cloisite 15A® with compatibilizer prepared via modified solution intercalation method was found to be the best membrane.

Accurate monitoring of concentration changes in saline solution is prerequisite to control and minimize the negative effect of salt in water resources. A highly sensitive refractive index (RI) sensor is fabricated via coating a novel zinc oxide/silver (ZnO/Ag) bi-layer having different ZnO nanostructure shapes as an outer layer on partially unclad silica fiber. When the ZnO layer contact to different saline concentrations, its band-gap is altered and modifies the RI of the ZnO layer. The coupling of the evanescent light with surface plasmon resonance (SPR) wave and absorption of evanescent light by the external medium are responsible for observing wavelength shift and intensity changes in the detected spectrum. For vertically oriented ZnO nanorods sample when IR light is used as a light source, by increasing the saline concentration from 0% to 20%, the wavelength is shifted from 1564.4 nm to 1573.3 nm and the intensity is dropped to 77% of its maximum value. The superior sensitivity obtained for vertically oriented ZnO sample is attributed to the larger surface area, higher average dispersion relation, better crystallinity, larger surface roughness and greater adhesion (interaction) with salt molecules compare to the other samples. The experimentally demonstrated highest intensity and wavelength sensitivity are 36 dB/RIU and 255 nm/RIU respectively.

Computational Fluid Dynamics (CFD) is a well-established tool to study fluid dynamics and particle movement, while Artificial Neural Network (ANN) models offer machine learning capabilities to accelerate indoor airflow predictions, but they still maintain a reasonable level of accuracy for prediction purposes. This study pioneers the integration of Deep Neural Network (DNN) models into indoor airflow dynamics, aiming to provide an accurate and accelerated prediction efficiency. The objective is to train two DNN models (classical and modified DNN models) to capture the complex relationships between ventilation rate, airflow patterns, and particle dispersion characteristics within buildings. Using a dataset generated from CFD simulations encompassing various air change rates, the trained modified DNN model significantly enhances prediction efficiency in term of the computational cost by 67 % reduction of CFD computational time (1 h to 20 min) while also resulting in very similar accuracy compared to the CFD outputs. The R 2 values of classical and modified DNN models (plane 1) at air flow rate equals to 4 ach are 0.6867 and 0.9567 in term of the DPM distribution, respectively. The similar pattern is observed as the accuracy of modified DNN is higher than the classical DNN for other air flow rates in terms of the DPM and velocity distributions. Accordingly, the number of prediction errors is significantly decreased as the model alters from the classical DNN to modified DNN model. The significance of this research lies in its potential to enhance the efficiency of assessing particle dispersion, allowing for the more efficient design of targeted ventilation strategies and indoor air quality control measures tailored to diverse pollutant sources emitted from humans. Integrating DNN and CFD in assessing particle dispersion characteristics is promising for improving the understanding of indoor air dynamics and facilitating data-driven decision-making for ensuring healthier and safer indoor environments.

Chemical Vapor Deposition (CVD) has been hugely favored when producing high-quality carbon nanomaterials and repeatable output. Despite being hugely favored, CVD typically requires a high temperature of above 1000 °C, which becomes the downside of this method. It requires a high cost and complicated processing environment, which explains the urgent need for low-temperature processing. Molecule properties of hydrocarbon precursors are believed to have played an essential role in CVD synthesis as it can affect the growth temperature, yield, crystallinity properties and indirectly affect the morphology of the carbon nanomaterials. In this review, various solid, liquid, and gaseous hydrocarbon precursors and how they affect the growth temperature of carbon nanomaterials syntheses via CVD are discussed.

Membrane morphology plays a great role in determining the performance of polymer electrolyte membranes (PEMs), especially for direct methanol fuel cell (DMFC) applications. Membrane morphology can be divided into two types, which are dense and porous structures. Membrane fabrication methods have different configurations, including dense, thin and thick, layered, sandwiched and pore-filling membranes. All these types of membranes possess the same densely packed structural morphology, which limits the transportation of protons, even at a low methanol crossover. This paper summarizes our work on the development of PEMs with various structures and architecture that can affect the membrane’s performance, in terms of microstructures and morphologies, for potential applications in DMFCs. An understanding of the transport behavior of protons and methanol within the pores’ limits could give some perspective in the delivery of new porous electrolyte membranes for DMFC applications.

This book chapter highlighted the preparation of mesoporous alumina membrane deposited with photocatalyst for the separation of highly concentrated oil emulsion. The catalyst (CuO-CeO) was successfully deposited onto the mesoporous alumina membrane using the sol–gel Pechini method. The obtained membranes were characterized using field emission scanning electron microscopy, X-ray diffraction (XRD), and Brunauer–Emmett–Teller. Three different methods of cleaning process were used to investigate the mesoporous alumina membrane performance in separating highly concentrated oil emulsion, namely ultraviolet (UV)-assisted cleaning, on-off UV-assisted cleaning and water spray cleaning. The results obtained showed that the catalyst dispersed uniformly onto the mesoporous alumina membrane. The membrane with a calcination temperature of 500ºC had 91% oil emulsion rejection with 30.17L/m2⸱h of solute flux under UV irradiation after a 3-hour filtration process.

The complexity of removing boron compounds from aqueous systems has received serious attention among researchers and inventors in the water treating industry. This is due to the higher level of boron in the aquatic ecosystem, which is caused by the geochemical background and anthropogenic factors. The gradual increase in the distribution of boron for years can become extremely toxic to humans, terrestrial organisms and aquatic organisms. Numerous methods of removing boron that have been executed so far can be classified under batch adsorption, membrane-based processes and hybrid techniques. Conventional water treatments such as coagulation, sedimentation and filtration do not significantly remove boron, and special methods would have to be installed in order to remove boron from water resources. The blockage of membrane pores by pollutants in the available membrane technologies not only decreases their performance but can make the membranes prone to fouling. Therefore, the surface-modifying flexibility in adsorptive membranes can serve as an advantage to remove boron from water resources efficiently. These membranes are attractive because of the dual advantage of adsorption/filtration mechanisms. Hence, this review is devoted to discussing the capabilities of an adsorptive membrane in removing boron. This study will mainly highlight the issues of commercially available adsorptive membranes and the drawbacks of adsorbents incorporated in single-layered adsorptive membranes. The idea of layering adsorbents to form a highly adsorptive dual-layered membrane for boron removal will be proposed. The future prospects of boron removal in terms of the progress and utilization of adsorptive membranes along with recommendations for improving the techniques will also be discussed further.