Hing Wah Lee

Ternary nanohybrid of reduced graphene oxide-nafion@silver nanoparticles for boosting the sensor performance in non-enzymatic amperometric detection of hydrogen peroxide

A sensitive and novel electrochemical sensor was developed for the detection of hydrogen peroxide (H2O2) using a reduced graphene oxide-nafion@silver6 (rGO-Nf@Ag6) nanohybrid modified glassy carbon electrode (GC/rGO-Nf@Ag6). The GC/rGO-Nf@Ag6 electrode exhibited an excellent electrochemical sensing ability for determining H2O2 with high sensitivity and selectivity. The detection limit of the electrochemical sensor using the GC/rGO-Nf@Ag6 electrode for H2O2 determination was calculated to be 5.35×10-7M with sensitivity of 0.4508µAµM-1. The coupling between rGO-Nf with silver nanoparticles (AgNPs) significantly boosted the electroanalytical performance by providing more active area for analyte interaction, thereby allowing more rapid interfacial electron transfer process. The interfering effect on the current response of H2O2 was studied and the results revealed that the sensor electrode exhibited an excellent immunity from most common interferents. The proposed non-enzymatic electrochemical sensor was used for determining H2O2 in apple juice, and the sensor electrode provided satisfactory results with reliable recovery values. These studies revealed that the novel GC/rGO-Nf@Ag6 sensor electrode could be a potential candidate for the detection of H2O2.

Heteroatom Nitrogen- and Boron-Doping as a Facile Strategy to Improve Photocatalytic Activity of Standalone Reduced Graphene Oxide in Hydrogen Evolution

Owing to its superior properties and versatility, graphene has been proliferating the energy research scene in the past decade. In this contribution, nitrogen (N-) and boron (B-) doped reduced graphene oxide (rGO) variants were investigated as a sole photocatalyst for the green production of H2 and their properties with respect to photocatalysis were elucidated for the first time. N- and B-rGOs were facilely prepared via the pyrolysis of graphene oxide with urea and boron anhydride as their respective dopant source. The pyrolysis temperature was varied (600-800 °C for N-rGO and 800-1000 °C for B-rGO) in order to modify dopant loading percentage (%) which was found to be influential to photocatalytic activity. N-rGO600 (8.26 N at%) and B-rGO1000 (3.59 B at%), which holds the highest at% from each of their party, exhibited the highest H2 activity. Additionally, the effects of the nature of N and B bonding configuration in H2 photoactivity were also examined. This study demonstrates the importance of dopant atoms in graphene, rendering doping as an effective strategy to bolster photocatalytic activity for standalone graphene derivative photocatalysts.

Piezoresistive effects in controllable defective HFTCVD graphene-based flexible pressure sensor

In this work, the piezoresistive effects of defective graphene used on a flexible pressure sensor are demonstrated. The graphene used was deposited at substrate temperatures of 750, 850 and 1000 °C using the hot-filament thermal chemical vapor deposition method in which the resultant graphene had different defect densities. Incorporation of the graphene as the sensing materials in sensor device showed that a linear variation in the resistance change with the applied gas pressure was obtained in the range of 0 to 50 kPa. The deposition temperature of the graphene deposited on copper foil using this technique was shown to be capable of tuning the sensitivity of the flexible graphene-based pressure sensor. We found that the sensor performance is strongly dominated by the defect density in the graphene, where graphene with the highest defect density deposited at 750 °C exhibited an almost four-fold sensitivity as compared to that deposited at 1000 °C. This effect is believed to have been contributed by the scattering of charge carriers in the graphene networks through various forms such as from the defects in the graphene lattice itself, tunneling between graphene islands, and tunneling between defect-like structures.

Highly sensitive integrated pressure sensor with horizontally oriented carbon nanotube network

This paper presents a functionalized, horizontally oriented carbon nanotube network as a sensing element to enhance the sensitivity of a pressure sensor. The synthesis of horizontally oriented nanotubes from the AuFe catalyst and their deposition onto a mechanically flexible substrate via transfer printing are studied. Nanotube formation on thermally oxidized Si (100) substrates via plasma-enhanced chemical vapor deposition controls the nanotube coverage and orientation on the flexible substrate. These nanotubes can be simply transferred to the flexible substrate without changing their physical structure. When tested under a pressure range of 0 to 50 kPa, the performance of the fabricated pressure sensor reaches as high as approximately 1.68%/kPa, which indicates high sensitivity to a small change of pressure. Such sensitivity may be induced by the slight contact in isolated nanotubes. This nanotube formation, in turn, enhances the modification of the contact and tunneling distance of the nanotubes upon the deformation of the network. Therefore, the horizontally oriented carbon nanotube network has great potential as a sensing element for future transparent sensors.

Engineering nanoscale p–n junction via the synergetic dual-doping of p-type boron-doped graphene hybridized with n-type oxygen-doped carbon nitride for enhanced photocatalytic hydrogen evolution

In this study, an effective 2D–2D heterojunction composite was formulated by hybridizing oxygen doped graphitic carbon nitride (O-gC3N4) with boron doped reduced graphene oxide (B-rGO) using a combined sonication-assisted electrostatic self-assembly approach. Pristine gC3N4 possesses a negative surface charge, which later transforms into a positive charge upon doping with elemental oxygen. This reversal of surface charge, which occurred on top of doping, established the opportune electrostatic coupling of positively charged O-gC3N4 and negatively charged B-rGO. Moreover, the concerted dual doping of both O-gC3N4 and B-rGO, which exhibited n-type and p-type conductivity, respectively, allowed the construction of a nanoscale p–n heterojunction system at the interface, warranting a more effective and rapid charge separation and in turn bolstering the photocatalytic hydrogen performance. In particular, the optimal loading content of B-rGO was found to be 2 wt% with a corresponding H2 production rate of 1639 μmol g−1 after 6 h, which is a remarkable 4-fold photocatalytic improvement as compared to that of O-gC3N4. In brief, this study highlights that the dual doping of both gC3N4 and rGO and their hybridization present a powerful strategy to increase the photoactivity of the composite since doping could remarkably modulate their interaction at the heterointerface.

Selective formation of tungsten nanowires

We report on a process for fabricating self-aligned tungsten (W) nanowires with polycrystalline silicon core. Tungsten nanowires as thin as 10 nm were formed by utilizing polysilicon sidewall transfer technology followed by selective deposition of tungsten by chemical vapor deposition (CVD) using WF6 as the precursor. With selective CVD, the process is self-limiting whereby the tungsten formation is confined to the polysilicon regions; hence, the nanowires are formed without the need for lithography or for additional processing. The fabricated tungsten nanowires were observed to be perfectly aligned, showing 100% selectivity to polysilicon and can be made to be electrically isolated from one another. The electrical conductivity of the nanowires was characterized to determine the effect of its physical dimensions. The conductivity for the tungsten nanowires were found to be 40% higher when compared to doped polysilicon nanowires of similar dimensions.

Neuro-Genetic Optimization of Temperature Control for a Continuous Flow Polymerase Chain Reaction Microdevice

In this study, a hybridized neuro-genetic optimization methodology realized by embedding finite element analysis (FEA) trained artificial neural networks (ANN) into genetic algorithms (GA), is used to optimize temperature control in a ceramic based continuous flow polymerase chain reaction (CPCR) device. The CPCR device requires three thermally isolated reaction zones of 94 degrees C, 65 degrees C, and 72 degrees C for the denaturing, annealing, and extension processes, respectively, to complete a cycle of polymerase chain reaction. The most important aspect of temperature control in the CPCR is to maintain temperature distribution at each reaction zone with a precision of +/-1 degree C or better, irrespective of changing ambient conditions. Results obtained from the FEA simulation shows good comparison with published experimental work for the temperature control in each reaction zone of the microfluidic channels. The simulation data are then used to train the ANN to predict the temperature distribution of the microfluidic channel for various heater input power and fluid flow rate. Once trained, the ANN analysis is able to predict the temperature distribution in the microchannel in less than 20 min, whereas the FEA simulation takes approximately 7 h to do so. The final optimization of temperature control in the CPCR device is achieved by embedding the trained ANN results as a fitness function into GA. Finally, the GA optimized results are used to build a new FEA model for numerical simulation analysis. The simulation results for the neuro-genetic optimized CPCR model and the initial CPCR model are then compared. The neuro-genetic optimized model shows a significant improvement from the initial model, establishing the optimization methods superiority.

Formation of silicon nanostructures with a combination of spacer technology and deep reactive ion etching

A new method of fabricating high aspect ratio nanostructures in silicon without the use of sub-micron lithographic technique is reported. The proposed method comprises two important steps including the use of CMOS spacer technique to form silicon nitride nanostructure masking followed by deep reactive ion etching (DRIE) of the silicon substrate to form the final silicon nanostructures. Silicon dioxide is used as the sacrificial layer to form the silicon nitride nanostructures. With DRIE a high etch selectivity of 50:1 between silicon and silicon nitride was achieved. The use of the spacer technique is particularly advantageous where self-aligned nanostructures with potentially unlimited lengths are formed without the need of submicron lithographic tools and resist materials. With this method, uniform arrays of 100 nm silicon nanostructures which are at least 4 μm tall with aspect ratio higher than 40 were successfully fabricated.

Investigation of low-pressure bimetallic cobalt-iron catalyst-grown multiwalled carbon nanotubes and their electrical properties

A bimetallic cobalt-iron catalyst was utilized to demonstrate the growth of multiwalled carbon nanotubes (CNTs) at low gas pressure through thermal chemical vapor deposition. The characteristics of multiwalled CNTs were investigated based on the effects of catalyst thickness and gas pressure variation. The results revealed that the average diameter of nanotubes increased with increasing catalyst thickness, which can be correlated to the increase in particle size. The growth rate of the nanotubes also increased significantly by ∼2.5 times with further increment of gas pressure from 0.5 Torr to 1.0 Torr. Rapid growth rate of nanotubes was observed at a catalyst thickness of 6 nm, but it decreased with the increase in catalyst thickness. The higher composition of 50% cobalt in the cobalt-iron catalyst showed improvement in the growth rate of nanotubes and the quality of nanotube structures compared with that of 20% cobalt. For the electrical properties, the measured sheet resistance decreased with the increase in the height of nanotubes because of higher growth rate. This behavior is likely due to the larger contact area of nanotubes, which improved electron hopping from one localized tube to another.

Thin Film Ag Masking for Deep Glass Micromachining

We report a single thin film and low cost masking material for deep, wet isotropic etching of glass in HF, which has applications in microfluidic devices and systems. With a 100 nm thin silver (Ag) mask, microcavities with an etch depth exceeding 200 μm were achieved and, by further thickening the silver film to 300 nm, etch depths up to 340 μm were observed. The thin film was deposited by evaporation and patterned in a mixture of nitric acid and deionized water at a ratio of 1:3. Silver had good adhesion to glass.