Self‐Limiting Galvanic Growth of MnO2 Monolayers on a Liquid Metal—Applied to Photocatalysis

Liquid metals offer unprecedented chemistry. Here it is shown that they can facilitate self‐limiting oxidation processes on their surfaces, which enables the growth of metal oxides that are atomically thin. This claim is exemplified by creating atomically thin hydrated MnO₂ using a Galvanic replacement reaction between permanganate ions and a liquid gallium–indium alloy (EGaIn). The “liquid solution”–“liquid metal” process leads to the reduction of the permanganate ions, resulting in the formation of the oxide monolayer at the interface. It is presented that under mechanical agitation liquid metal droplets are established, and simultaneously, hydrated gallium oxides and manganese oxide sheets delaminate themselves from the interfacial boundaries. The produced nanosheets encapsulate a metallic core, which is found to consist of solid indium only, with the full migration of gallium out of the droplets. This process produces core/shell structures, where the shells are made of stacked atomically thin nanosheets. The obtained core/shell structures are found to be an efficient photocatalyst for the degradation of an organic dye under simulated solar irradiation. This study presents a new research direction toward the modification and functionalization of liquid metals through spontaneous interfacial redox reactions, which has implications for many applications beyond photocatalysis.     

Effect of copper foil annealing process on large graphene domain growth by solid source-based chemical vapor deposition

Controlling the metal catalyst surface structure is a critical factor to achieve growth of large graphene domains. In this prospect, we explored the annealing process to create an oxide layer and subsequent recrystallization of Cu foil for growth of large graphene domain by the atmospheric pressure chemical vapor deposition (AP-CVD) technique. We revealed the transformation of Cu surface crystallographic structures in every step of annealing process by electron back-scattered diffraction analysis. Initially, electroless polished Cu foils are annealed in Ar and then in H₂ atmosphere to obtain a smoother surface with reduced graphene nucleation sites. The transformation of Cu grain structures at various annealing steps was confirmed, where the gas atmosphere and annealing duration have significant influence. Graphene domains with the size more than 560 µm are obtained on the processed Cu surface using polystyrene as solid precursor. It is obtained that the oxidation and recrystallization process of Cu foil surface significantly influence the nucleation density, which enable growth of larger graphene domain in the developed CVD process.     

Removal of leachate pollutants using flocculation method at simultaneous factors of optimum pH and Tacca leontopetaloides biopolymer flocculant (TBPF) dosage via face-centred central composite design

The effect of the interaction factor between pH and dosage is important in leachate wastewater treatment. This study aims to remove leachate pollutants such as turbidity, total suspended solid (TSS), chemical oxygen demand (COD) and colour using simultaneous factors of plant-based Tacca leontopetaloides biopolymer flocculant (TBPF) dosage and leachate pH. The flocculation process was carried out through jar test by applying the perikinetic theory and statical analysis (face-centred central composite design). The results found that the optimum leachate pH and TBPF dosage were pH 3 and 150 mg/L, respectively. The highest removal of leachate pollutants reached up to 69% with a second-order perikinetic model; R² = 0.9545 and k = 9 × 10⁻⁶ L/mg/min were obtained. Simultaneous interaction factors between leachate pH and TBPF dosage on turbidity and TSS removal were found significant and hence can be applied in the actual leachate wastewater treatment industry, particularly at the primary stage using the proposed model.     

Potential use of nanofiltration like-forward osmosis membranes for copper ion removal

The discharge of industrial effluent containing heavy metal ions would cause water pollution if such effluent is not properly treated. In this work, the performance of emerging nanofiltration(NF) like-forward osmosis(FO)membrane was evaluated for its efficiency to remove copper ion from water. Conventionally, copper ion is removed from aqueous solution via adsorption and/or ion-exchange method. The engineered osmosis method as proposed in this work considered four commercial NF membranes(i.e., NF90, DK, NDX and PFO) where their separation performances were accessed using synthetic water sample containing 100 mg·L~(-1) copper ion under FO and pressure retarded osmosis(PRO) orientation. The findings indicated that all membranes could achieve almost complete removal of copper regardless of membrane orientation without applying external driving force.The high removal rates were in good agreement with the outcomes of the membranes tested under pressuredriven mode at 1 MPa. The use of appropriate salts as draw solutes enabled the NF membranes to be employed in engineered osmosis process, achieving a relatively low reverse solute flux. The findings showed that the best performing membrane is PFO membrane in which it achieved N 99.4% copper rejection with very minimum reverse solute flux of 1 g·m~(-2)·h~(-1).     

Numbering with spiral pattern to prove authenticity and integrity in medical images

With the rapid development of technology in digital multimedia, manipulation and misconduct of digital data are soaring. The watermarking procedure is seen as helpful to protect the security of digital images which are highly confidential such as medical images. In this study, an efficient watermarking method for greyscale images is proposed. The scheme is designed to achieve good numbering pattern, exact detection and image recovery. The proposed scheme uses a unique spiral pattern numbering before implementing the block-based mechanism for embedding. The experiment tests the difference between using normal pattern and unique spiral pattern in numbering, and the results show that the proposed method produces a great quality value of embedded image with great tamper localization and recovery ability. This function can help in proving authenticity and integrity of medical images in the system.     

Catalytic Metal Foam by Chemical Melting and Sintering of Liquid Metal Nanoparticles

Metal foams are highly sought‐after porous structures for heterogeneous catalysis, which are fabricated by templating, injecting gas, or admixing blowing agents into a metallic melt at high temperatures. They also require additional catalytic material coating. Here, a low‐melting‐point liquid metal is devised for the single‐step formation of catalytic foams in mild aqueous environments. A hybrid catalytic foam fabrication process is presented via simultaneous chemical foaming, melting, and sintering reaction of liquid metal nanoparticles. As a model, nanoparticles of tertiary low‐melting‐point eutectic alloy of indium, bismuth, and tin (Field's metal) are processed with sodium hydrogen carbonate, an environmentally benign blowing agent. The competing endothermic foaming and exothermic sintering reactions are triggered by an aqueous acidic bath. The overall foaming process occurs at a localized temperature above 200 °C, producing submicron‐ to micron‐sized open‐cell pore foams with conductive cores and semiconducting surface decorations. The catalytic properties of the metal foams are explored for a range of applications including photo‐electrocatalysis, bacteria electrofiltration, and CO₂ electroconversion. In particular, the Field's metal‐based foams show exceptional CO₂ electrochemical conversion performance at low applied voltages. The facile process presented here can be extended to other low‐temperature post transition and transition metal alloys.     

Efficient Android Software Development Using MIT App Inventor 2 for Bluetooth-Based Smart Home

Wireless Personal Communications - In this paper, a specific Android application for Bluetooth-based smart home system is presented. The aim of this research is to design, develop, and evaluate a...     

Effect of nickel oxide - Modified BaCe0.54Zr0.36Y0.1O2.95 as composite anode on the performance of proton-conducting solid oxide fuel cell

The effect of NiO-m-BCZY64 (BCZY64 = BaCe_0.54Zr_0.36Y_0.1O_2.95) as a composite anode with a single anode functional layer (AFL) and gradient AFL on the performance of a button cell was systematically evaluated. The m-BCZY64 is referred to the pristine BCZY64 that was modified by a functionalized activated carbon derived from palm-oil empty fruit bunch (EFB). The electrochemical performance of the cell was investigated by impedance spectroscopy in a controlled atmosphere. The NiO-m-BCZY64 exhibited smaller grain size and homogenous elemental distribution compared to pristine NiO-BCZY64 as observed by SEM/EDX. At T = 800 °C, a button cell consists of NiO:m-BCZY64 with gradient AFL showed the best performance with total resistance (R_T) of 21.12 Ωcm² compared to the cell with single AFL (R_T = 86.04 Ωcm²) and pristine NiO-BCZY64 (R_T = 145.64 Ωcm²). The significant reduction of R_T indicates that the NiO:m-BCZY64 with gradient AFL showed high potential to be used as a composite anode for proton-conducting solid oxide fuel cells.     

A Review on Nanocellulose and Its Application in Supercapacitors

Commercially available supercapacitors offer very limited advantages over other energy storage devices. Balancing their electrochemical performance such as capacitance, energy density, and cyclability is challenging. Studies have shown that this challenge can be overcome by using light and cheap substrates that are highly stable with solvents, and have high loading capacities and compatibility with nanomaterials. Nanocellulose, derived from wastes or biomass, is a good candidate for integrating with other nanosize conductive materials, such as carbon, conducting polymers, and metal oxides, as active materials or nanocomposites for supercapacitors. This review focuses on the properties and preparation of nanocellulose sourced from wastes (biomass) and bacteria, and extends to emerging materials, such as metal–organic frameworks and MXene, for nanocellulose-based supercapacitors. Even though supercapacitors are mainly composed of electrodes, electrolytes, and separators, this paper focuses on the overall electrochemical performance of nanocellulose-based supercapacitors to evaluate the influence of nanocellulose. In addition, the potentials and possible limitations of nanocellulose in supercapacitors are discussed. Overall, the incorporation of waste-derived nanocellulose into energy storage applications is an initiative that improves the circular economy and supports environmental sustainability.     

Electrical Tree Image Segmentation Using Hybrid Multi Scale Line TrackingAlgorithm

Electrical trees are an aging mechanism most associated with partial discharge (PD) activities in crosslinked polyethylene (XLPE) insulation of high-voltage (HV) cables. Characterization of electrical tree structures gained considerable attention from researchers since a deep understanding of the tree morphology is required to develop new insulation material. Two-dimensional (2D) optical microscopy is primarily used to examine tree structures and propagation shapes with image segmentation methods. However, since electrical trees can emerge in different shapes such as bush-type or branch-type, treeing images are complicated to segment due to manifestation of convoluted tree branches, leading to a high misclassification rate during segmentation. Therefore, this study proposed a new method for segmenting 2D electrical tree images based on the multi-scale line tracking algorithm (MSLTA) by integrating batch processing method. The proposed method, h-MSLTA aims to provide accurate segmentation of electrical tree images obtained over a period of tree propagation observation under optical microscopy. The initial phase involves XLPE sample preparation and treeing image acquisition under real-time microscopy observation. The treeing images are then sampled and binarized in pre-processing. In the next phase, segmentation of tree structures is performed using the h-MSLTA by utilizing batch processing in multiple instances of treeing duration. Finally, the comparative investigation has been conducted using standard performance assessment metrics, including accuracy, sensitivity, specificity, Dice coefficient and Matthew’s correlation coefficient (MCC). Based on segmentation performance evaluation against several established segmentation methods, h-MSLTA achieved better results of 95.43% accuracy, 97.28% specificity, 69.43% sensitivity rate with 23.38% and 24.16% average improvement in Dice coefficient and MCC score respectively over the original algorithm. In addition, h-MSLTA produced accurate measurement results of global tree parameters of length and width in comparison with the ground truth image. These results indicated that the proposed method had a solid performance in terms of segmenting electrical tree branches in 2D treeing images compared to other established techniques.