Madzlan Aziz

A review of purification techniques for carbon nanotubes

Purification of carbon nanotubes (CNTs) is a very actively discussed topic in contemporary CNT literature. To a large extent, impurities embedded in CNTs influence the physical and chemical characteristics of the CNTs. Different purification methods yield different CNT characteristics and may be suitable for the production of different types of CNTs. Developments in the purification methods of CNTs are reviewed, and the production methods are briefly discussed and summarized. This is followed by a detailed description of the three major purification methods, viz. chemical, physical, and multi-step purification.

Pre-treatment of multi-walled carbon nanotubes for polyetherimide mixed matrix hollow fiber membranes.

Mixed matrix hollow fibers composed of multi-walled carbon nanotubes (MWCNTs) and polyetherimide (PEI) were fabricated. Pre-treatment of MWCNTs was carried out prior to the incorporation into the polymer matrix using a simple and feasible two stages approach that involved dry air oxidation and surfactant dispersion. The characterizations of the surface treated MWCNTs using TEM and Raman spectroscopy have evidenced the effectiveness of dry air oxidation in eliminating undesired amorphous carbon and metal catalyst while surfactant dispersion using Triton X100 has suppressed the agglomeration of MWCNTs. The resultant mixed matrix hollow fibers were applied for O(2)/N(2) pure gas separation. Interestingly, it was found that removal of disordered amorphous carbons and metal particles has allowed the hollow structures to be more accessible for the fast and smooth transport of gas molecules, hence resulted in noticeable improvement in the gas separation properties. The composite hollow fibers embedded with the surface modified MWCNTs showed increase in permeability as much as 60% while maintaining the selectivity of the O(2)/N(2) gas pair. This study highlights the necessity to establish an appropriate pre-treatment approach for MWCNTs in order to fully utilize the beneficial transport properties of this material in mixed matrix polymer nanocomposite for gas separation.

High‐dimensional QSAR prediction of anticancer potency of imidazo[4,5‐b]pyridine derivatives using adjusted adaptive LASSO

In high‐dimensional quantitative structure–activity relationship (QSAR) studies, identifying relevant molecular descriptors is a major goal. In this study, a proposed penalized method is used as a tool for molecular descriptors selection. The method, called adjusted adaptive least absolute shrinkage and selection operator (LASSO) (AALASSO), is employed to study the high‐dimensional QSAR prediction of the anticancer potency of a series of imidazo[4,5‐b]pyridine derivatives. This proposed penalized method can perform consistency selection and deal with grouping effects simultaneously. Compared with other commonly used penalized methods, such as LASSO and adaptive LASSO with different initial weights, the results show that AALASSO obtains the best predictive ability not only by consistency selection but also by encouraging grouping effects in selecting more correlated molecular descriptors. Hence, we conclude that AALASSO is a reliable penalized method in the field of high‐dimensional QSAR studies. Copyright

Triethanolamine as an additive to the anode to improve the rechargeability of alkaline manganese dioxide batteries

Rechargeable alkaline manganese dioxide batteries use a zinc paste anode which undergoes shape change during charging, effecting its activity. A study on triethanolamine (TEA) as an additive to the zinc anode to control its shape change and retain activity is made. Voltammetric studies showed the potential of TEA in controlling shape change. Rechargeable alkaline manganese dioxide batteries are made in the laboratory and their cycle life characteristics are compared with and without TEA in the anode. An improvement is noticed in the cycle life capacity of the rechargeable alkaline manganese dioxide batteries with TEA especially after 12th cycle.

Effect of Dispersed Multi-Walled Carbon Nanotubes on Mixed Matrix Membrane for O2/N2 Separation

Mixed matrix membranes (MMMs) consisting of multiwalled carbon nanotubes (MWCNTs) embedded within polyetherimide were prepared. Surfactants of different charges were utilized to disperse the nanotubes through a simple non-covalent approach. The characterization results suggest that proper selection of the dispersing agent contributed to better dispersion of nanotubes. The MMMs exhibited improved thermal stability and mechanical strength, which indicate the improvement of dispersion and compatibility within the polymer matrix. The resulting membrane exhibited permeance improvement of O2 and N2 as much as 87.7% and 120% respectively compared to that of neat polyetherimide. The results implied that Triton-X100 treated MWCNTs is a promising filler to enhance gas permeability.

Quantitative structure–activity relationship model for prediction study of corrosion inhibition efficiency using two-stage sparse multiple linear regression

A new quantitative structure–activity relationship (QSAR) of the inhibition of mild steel corrosion in 1 M hydrochloric acid using furan derivatives was developed by proposing two‐stage sparse multiple linear regression. The sparse multiple linear regression using ridge penalty and sparse multiple linear regression using elastic net (SMLRE) were used to develop the QSAR model. The results show that the SMLRE‐based model possesses high predictive power compared with sparse multiple linear regression using ridge penalty‐based model according to the mean‐squared errors for both training and test datasets, leave‐one‐out internal validation (Q2int = 0.98), and external validation (Q2ext = 0.95). In addition, the results of applicability domain assessment using the leverage approach reveal a reliable and robust SMLRE‐based model. In conclusion, the developed QSAR model using SMLRE can be efficiently used in the studies of corrosion inhibition efficiency. Copyright

High-dimensional QSAR modelling using penalized linear regression model with L1/2-norm

Abstract In high-dimensional quantitative structure–activity relationship (QSAR) modelling, penalization methods have been a popular choice to simultaneously address molecular descriptor selection and QSAR model estimation. In this study, a penalized linear regression model with L1/2-norm is proposed. Furthermore, the local linear approximation algorithm is utilized to avoid the non-convexity of the proposed method. The potential applicability of the proposed method is tested on several benchmark data sets. Compared with other commonly used penalized methods, the proposed method can not only obtain the best predictive ability, but also provide an easily interpretable QSAR model. In addition, it is noteworthy that the results obtained in terms of applicability domain and Y-randomization test provide an efficient and a robust QSAR model. It is evident from the results that the proposed method may possibly be a promising penalized method in the field of computational chemistry research, especially when the number of molecular descriptors exceeds the number of compounds.

High-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty

This study addresses the problem of the high‐dimensionality of quantitative structure‐activity relationship (QSAR) classification modeling. A new selection of descriptors that truly affect biological activity and a QSAR classification model estimation method are proposed by combining the sparse logistic regression model with a bridge penalty for classifying the anti‐hepatitis C virus activity of thiourea derivatives. Compared to other commonly used sparse methods, the proposed method shows superior results in terms of classification accuracy and model interpretation.

Effect of Reaction Temperature and Flow Rate of Precursor on Formation of Multi‐Walled Carbon Nanotubes

The effect of reaction temperature and flow rate of precursor on the quantity and quality of the multi‐walled carbon nanotubes (MWNTs) produced by catalytic chemical vapour deposition (CCVD) was studied. The MWNTs were grown over zeolite supported catalyst at 700 and 850° C with flow rate of acetylene at 15 and 30 sccm. The effect of an in‐situ heat treatment on the as‐grown MWNTs at 200° C was investigated. Thermogravimetric analysis (TGA) results show that CNT purity decreases with increasing reaction temperture, from 63.31 wt% at 700° C to 61.68 wt% at 850° C. However, the increase of acetylene flow rate from 15 sccm to 30 sccm has improved the yield of MWNT yield from 63.31 wt% to 69.28 wt%. The MWNTs grown at 850° C with 30 sccm of acetylene show 68.23 wt% of purity, attributed to the higher acetylene flow rate. The in‐situ heat treatment at 200° C gave the highest purity of MWNTs at 87.52 wt%. TEM and HRTEM images suggest that the impurities on the wall layers of MWNT yield were burn off at 200° C. ...

The influence of PEEK as a pore former on the microstructure of brush-painted LSCF cathodes

At lower operation temperature of intermediate temperature solid oxide fuel cells (IT-SOFC), polarization resistance was recognized as a limiting step because polarization at cathode is dependent on the rate of oxygen reduction reaction. The enhancement of cathode microstructure is one of the effective ways to improve the reaction rate. Pore former addition method is proven to be able to tailor the microstructure of cathode. The addition of polyether ether ketone (PEEK) as pore former was evaluated and compared with common pore formers (corn starch and graphite) for the microstructure cathode layer. Brush painting technique was used to deposit cathode layer on anode/electrolyte dual layer support hollow fiber. X-ray diffraction (XRD) analysis had proven that the resulting layer was free from impurities after the sintering treatment. Corn starch was able to induced cathode layer with coarse and large interconnected pores for efficient gas diffusion, as was proven by the SEM analysis. Additionally, SEM analysis also showed the formation of fine micropores throughout the layer when graphite was used as the pore former that can provide the increase in triple phase boundary region (TPB) in the layer. PEEK was able to generate both high porosity for oxygen diffusion to the reactive sites and increased number of TPB by the formation of fine microstructure pores in the cathode layer.