In the present study, 2-bromo-4-chlorophenyl-2-bromobutanoate (3) was synthesized via the reaction of 2-bromo-4-chlorophenol with 2-bromobutanoyl bromide in the presence of pyridine. A variety of 2-bromo-4-chlorophenyl-2-bromobutanoate derivatives (5a-f) were synthesized with moderate to good yields via a Pd-catalyzed Suzuki cross-coupling reaction. To find out the reactivity and electronic properties of the compounds, Frontier molecular orbital analysis, non-linear optical properties, and molecular electrostatic potential studies were performed.
State of charge (SOC) is a crucial index used in the assessment of electric vehicle (EV) battery storage systems. Thus, SOC estimation of lithium-ion batteries has been widely investigated because of their fast charging, long-life cycle, and high energy density characteristics. However, precise SOC assessment of lithium-ion batteries remains challenging because of their varying characteristics under different working environments. Machine learning techniques have been widely used to design an advanced SOC estimation method without the information of battery chemical reactions, battery models, internal properties, and additional filters. Here, the capacity of optimized machine learning techniques are presented toward enhanced SOC estimation in terms of learning capability, accuracy, generalization performance, and convergence speed. We validate the proposed method through lithium-ion battery experiments, EV drive cycles, temperature, noise, and aging effects. We show that the proposed method outperforms several state-of-the-art approaches in terms of accuracy, adaptability, and robustness under diverse operating conditions.
Alkaline-stable lipases are highly valuable biocatalysts that catalyze reactions under highly basic conditions. Herein, computational predictions of lipase from Acinetobacter haemolyticus and its mutant, Mut-LipKV1 was performed to identify functionally relevant mutations that enhance pH performance under increasing basicity. Mut-LipKV1 was constructed by in silico site directed mutagenesis of several outer loop acidic residues, aspartic acid (Asp) into basic ones, lysine (Lys) at positions 51, 122 and 247, followed by simulation under extreme pH conditions (pH 8.0-pH 12.0). The energy minimized Mut-LipKV1 model exhibited good quality as shown by PROCHECK, ERRAT and Verify3D data that corresponded to 79.2, 88.82 and 89.42% in comparison to 75.2, 86.15, and 95.19% in the wild-type. Electrostatic surface potentials and charge distributions of the Mut-LipKV1 model was more stable and better adapted to conditions of elevated pHs (pH 8.0 - 10.0). Mut-LipKV1 exhibited a mixture of neutral and positive surface charge distribution compared to the predominantly negative charge in the wild-type lipase at pH 8.0. Data of molecular dynamics simulations also supported the increased alkaline-stability of Mut-LipKV1, wherein the lipase was more stable at a higher pH 9.0 (RMSD = ∼0.3 nm, RMSF = ∼0.05-0.2 nm), over the optimal pH 8.0 of the wild-type lipase (RMSD = 0.3 nm, RMSF = 0.05-0.20 nm). Thus, the adaptive strategy of replacing surface aspartic acid to lysine in lipase was successful in yielding a more alkaline-stable Mut-LipKV1 under elevated basic conditions.Communicated by Ramaswamy H. Sarma.
Circular 10/2016 issued by UiTM Vice-Chancellor’s office comprises a clear guideline for 2017 Strategic Budget Planning. The guidelines can help the Head of PTJ’s to plan and take necessary cost effective measures to reduce on utility expenditure especially to counter the rising monthly electricity bills related to the use of air conditioners on campuses. Looking at the figures drawn from the energy management office in UiTM Negeri Sembilan Branch, UiTM Kuala Pilah campus has spent an average of RM153, 028.88 monthly in 2016. As of August 2016, the cost of electricity consumption in UiTM Kuala Pilah has reached RM1,224,231.03. This amount has surpassed the overall approved allocation of RM 800,000.00 for 2016 electricity bill. In order to reduce spending and encourage saving, as well as responding to the ‘Energy Savings Campaign’ held at the campus level, various efforts have been taken at the departmental levels. One of the innovative products that came about from the campaign is the ‘Smartfan’ project pioneered by the Physics and Materials Science Unit. The main objective of this project is the production of a “smartfan” or a mini air conditioner which is a simple, cost-effective and an energy saving device. In addition, products and ideas from the campaign can be piloted and taken to innovative, inventions and design contests at national and international levels.
The interactions within microbial, chemical and electronic elements in microbial fuel cell (MFC) system can be crucial for its bio-electrochemical activities and overall performance. Therefore, this study explored polynomial models by response surface methodology (RSM) to better understand interactions among anode pH, cathode pH and inoculum size for optimising MFC system for generation of electricity and degradation of 2,4-dichlorophenol. A statistical central composite design by RSM was used to develop the quadratic model designs. The optimised parameters were determined and evaluated by statistical results and the best MFC systematic outcomes in terms of current generation and chlorophenol degradation. Statistical results revealed that the optimum current density of 106 mA/m2 could be achieved at anode pH 7.5, cathode pH 6.3-6.6 and 21-28% for inoculum size. Anode-cathode pHs interaction was found to positively influence the current generation through extracellular electron transfer mechanism. The phenolic degradation was found to have lower response using these three parameter interactions. Only inoculum size-cathode pH interaction appeared to be significant where the optimum predicted phenolic degradation could be attained at pH 7.6 for cathode pH and 29.6% for inoculum size.
Constantly changing electricity demand has made variability and uncertainty inherent characteristics of both electric generation and cellular communication systems. This paper develops an online learning algorithm as a prescheduling mechanism to manage the variability and uncertainty to maintain cost-aware and reliable operation in cloud radio access networks (Cloud-RANs). The proposed algorithm employs a combinatorial multi-armed bandit model and minimizes the long-term energy cost at remote radio heads. The algorithm preschedules a set of cost-efficient energy packages to be purchased from an ancillary energy market for the future time slots by learning both from cooperative energy trading at previous time slots and by exploring new energy scheduling strategies at the current time slot. The simulation results confirm a significant performance gain of the proposed scheme in controlling the available power budgets and minimizing the overall energy cost compared with recently proposed approaches for real-time energy resources and energy trading in Cloud-RANs.
This paper proposes an alternative approach to extract transformer's winding parameters of resistance (R), inductance (L), capacitance (C) and conductance (G) based on Finite Element Method (FEM). The capacitance and conductance were computed based on Fast Multiple Method (FMM) and Method of Moment (MoM) through quasi-electrostatics approach. The AC resistances and inductances were computed based on MoM through quasi-magnetostatics approach. Maxwell's equations were used to compute the DC resistances and inductances. Based on the FEM computed parameters, the frequency response of the winding was obtained through the Bode plot function. The simulated frequency response by FEM model was compared with the simulated frequency response based on the Multi-conductor Transmission Line (MTL) model and the measured frequency response of a 33/11 kV, 30 MVA transformer. The statistical indices such as Root Mean Square Error (RMSE) and Absolute Sum of Logarithmic Error (ASLE) were used to analyze the performance of the proposed FEM model. It is found that the simulated frequency response by FEM model is quite close to measured frequency response at low and mid frequency regions as compared to simulated frequency response by MTL model based on RMSE and ASLE analysis.
Zinc oxide (ZnO) nanoparticles (NPs) has become as promising candidate for antibacterial agents against Escherichia coli (E.coli), commensal hospital- acquired infections (HAIs). This study investigates the antibacterial action of ZnO NPs in three difference shapes; nanorod, nanoflakes and nanospheres against E.coli ATCC 25922. The antibacterial activity of ZnO NPs was determine through two standard protocols known as Clinical Laboratory Standards Institute (CLSI) MO2-A11 under light conditions of 5.70 w/m2 and American standard test method (ASTM) E-2149. Preliminary screening shows ZnO NPs did not inhibit the growth of E.coli. Further analysis using ASTM E-2149 in dynamic conditions revealed antibacterial activity after 3 hours with 100% reduction for ZnO NPs nanoflakes and 6 hours with 94.63% reduction for ZnO nanospheres, respectively. It demonstrated the ZnO NPs in nanoflakes and nanospheres exerted higher antibacterial activity possibly through release of ios, free radicals, ROS generation and electrostatic collision which contribute to bacterial death. Further analysis is needed to investigate biocompatibility of these samples for future biomedical applications.
Microbial fuel cells (MFCs) that simultaneously remove organic contaminants and recovering metals provide a potential route for industry to adopt clean technologies. In this work, two goals were set: to study the feasibility of zinc removal from industrial effluents using MFCs and to understand the removal process by using reaction rate models. The removal of Zn2+ in MFC was over 96% for synthetic and industrial samples with initial Zn2+ concentrations less than 2.0 mM after 22 h of operation. However, only 83 and 42% of the zinc recovered from synthetic and industrial samples, respectively, was attached on the cathode surface of the MFCs. The results marked the domination of electroprecipitation rather than the electrodeposition process in the industrial samples. Energy dispersive X-ray (EDX) analysis showed that the recovered compound contained not only Zn but also O, evidence that Zn(OH)2 could be formed. The removal of Zn2+ in the MFC followed a mechanism where oxygen was reduced to hydroxide before reacting with Zn2+. Nernst equations and rate law expressions were derived to understand the mechanism and used to estimate the Zn2+ concentration and removal efficiency. The zero-, first- and second-order rate equations successfully fitted the data, predicted the final Zn2+ removal efficiency, and suggested that possible mechanistic reactions occurred in the electrolysis cell (direct reduction), MFC (O2 reduction), and control (chemisorption) modes. The half-life, t1/2, of the Zn2+ removal reaction using synthetic and industrial samples was estimated to be 7.0 and 2.7 h, respectively. The t1/2 values of the controls (without the power input from the MFC bioanode) were much slower and were recorded as 21.5 and 7.3 h for synthetic and industrial samples, respectively. The study suggests that MFCs can act as a sustainable and environmentally friendly technology for heavy metal removal without electrical energy input or the addition of chemicals.
In high-voltage (HV) insulation, electrical trees are an important degradation phenomenon strongly linked to partial discharge (PD) activity. Their initiation and development have attracted the attention of the research community and better understanding and characterization of the phenomenon are needed. They are very damaging and develop through the insulation material forming a discharge conduction path. Therefore, it is important to adequately measure and characterize tree growth before it can lead to complete failure of the system. In this paper, the Gaussian mixture model (GMM) has been applied to cluster and classify the different growth stages of electrical trees in epoxy resin insulation. First, tree growth experiments were conducted, and PD data captured from the initial to breakdown stage of the tree growth in epoxy resin insulation. Second, the GMM was applied to categorize the different electrical tree stages into clusters. The results show that PD dynamics vary with different stress voltages and tree growth stages. The electrical tree patterns with shorter breakdown times had identical clusters throughout the degradation stages. The breakdown time can be a key factor in determining the degradation levels of PD patterns emanating from trees in epoxy resin. This is important in order to determine the severity of electrical treeing degradation, and, therefore, to perform efficient asset management. The novelty of the work presented in this paper is that for the first time the GMM has been applied for electrical tree growth classification and the optimal values for the hyperparameters, i.e., the number of clusters and the appropriate covariance structure, have been determined for the different electrical tree clusters.
The present work focuses on the development of cellulose nanofibrils (CNF) film that derived from sustainable biomass resources, which potentially to work as bio-based conductive membranes that assembled into supercapacitors. The chemically purified cellulose was isolated from different parts of coconut (coconut shell and its husk) and further subjected to 2,2,6,6-tetramethylpiperidine-1-oxyl radical (TEMPO)-mediated oxidation for CNF preparation. Physicochemical properties of prepared CNFs were studied in terms of chemical characteristics & crystallinity, surface functionalities, surface morphology, and thermal properties. Both coconut shell-derived CNF and coconut husk-derived CNF fulfilled with nanocellulose's characteristics with fibres width ranged of 70-120 nm and 150-330 nm, respectively. CNF films were further prepared by solvent casting method to measure the modulus elasticity, piezoelectric and dielectric properties of the films. Mechanical study indicated that coconut shell-derived CNF film showed a higher value of elastic modulus than the coconut husk-derived CNF film, which was 8.39 GPa and 5.36 GPa, respectively. The effectiveness of electrical aspects for CNF films are well correlated with the crystallinity and thermal properties, associated with it's composition of different coconut's part.
The political upheaval and the civil war in Libya had a painful toll on the operational reliability of the electric energy supply system. With frequent power cuts and crumbling infrastructure, mainly due to the damage inflicted upon several power plants and grid assets as well as the lack of maintenance, many Libyans are left without electricity for several hours a day. As the country has a staggeringly immense potential of solar energy, it is inevitable to exploit such potential, to avert system-wide blackouts. This paper investigates the use of small-scale PV systems in local communities as non-wires alternative (NWA), offering excess energy exchange within local/neighboring microgrids (MGs) for reliable electric power supply. Different combinations of PV/storage/diesel distributed generations (DGs), with grid-interface options, were applied on a case study of a typical dwelling in the Eastern Libyan city of Benghazi. Technical and financial feasibility assessments were carried out to contrast between various supply combinations. Sensitivity analysis of the PV-grid system was also conducted using Net Present Value (NPV) and the payback time indicators to determine the impacts of Feed-in Tariff (FiT) rates, financial incentives, electricity tariff, and inflation rate on the economic viability of the PV grid system. Results show that the PV-grid system has a promising potential under reasonable set of varying system parameters. On top of its social and environmental-friendly advantages, the PV-battery system is found to be more economical when adopted as a standalone NWA solution as compared to the diesel generator option, even at the lowest diesel price. The PV-grid system does not only provide a short-term remedy to the rolling blackouts in Libya but also enhances system operational reliability by providing a NWA to rundown or shattered grid infrastructure, thus bolstering energy provision in residential neighborhoods.
Electrocardiographic abnormalities can be associated with acute pancreatitis. However, data regarding the actual causative factor still remains elusive. Many previous cases were reported on non-specific ST and T wave abnormalities concurrent with acute pancreatitis but rarely with an increasing trend of cardiac markers. We describe the case of a 70-year-old female who presented with one such conundrum. Our patient had typical presentation of acute pancreatitis but had dynamic ECG changes with markedly increased cardiac markers. Subsequently after initiation of treatment for acute pancreatitis and observation for the course of several days, the ECG returned to the baseline as pre admission. This substantiates the fact that acute pancreatitis can mimic both biochemical and electrical manifestation of an acute coronary syndrome. Thus, Emergency Physicians should consider acute pancreatitis as a possible diagnosis in patients who present with abnormal electrocardiograms.
Mechanical strength, thermal conductivity and electrical breakdown of polypropylene/lignin/kenaf core fiber (PP/L/KCF) composite were studied. PP/L, PP/KCF and PP/L/KCF composites with different fiber and lignin loading was prepared using a compounding process. Pure PP was served as control. The results revealed that tensile and flexural properties of the PP/L/KCF was retained after addition of lignin and kenaf core fibers. Thermal stability of the PP composites improved compared to pure PP polymer. As for thermal conductivity, no significant difference was observed between PP composites and pure PP. However, PP/L/KCF composite has higher thermal diffusivity. All the PP composites produced are good insulating materials that are suitable for building. All PP composites passed withstand voltage test in air and oil state as stipulated in IEC 60641-3 except PP/L in oil state. SEM micrograph showed that better interaction and adhesion between polymer matrix, lignin and kenaf core fibers was observed and reflected on the better tensile strength recorded in PP/L/KCF composite. This study has successfully filled the gap of knowledge on using lignin and kenaf fibers as PP insulator composite materials. Therefore, it can be concluded that PP/Lignin/KCF has high potential as an insulating material.
We have further developed the two-brains hypothesis as a form of complementarity (or complementary relationship) of endogenously induced weak magnetic fields in the electromagnetic brain. The locally induced magnetic field between electron magnetic dipole moments of delocalized electron clouds in neuronal domains is complementary to the exogenous electromagnetic waves created by the oscillating molecular dipoles in the electro-ionic brain. In this paper, we mathematically model the operation of the electromagnetic grid, especially in regard to the functional role of atomic orbitals of dipole-bound delocalized electrons. A quantum molecular dynamic approach under quantum equilibrium conditions is taken to illustrate phase differences between quasi-free electrons tethered to an oscillating molecular core. We use a simplified version of the many-body problem to analytically solve the macro-quantum wave equation (equivalent to the Kohn-Sham equation). The resultant solution for the mechanical angular momentum can be used to approximate the molecular orbital of the dipole-bound delocalized electrons. In addition to non-adiabatic motion of the molecular core, 'guidance waves' may contribute to the delocalized macro-quantum wave functions in generating nonlocal phase correlations. The intrinsic magnetic properties of the origins of the endogenous electromagnetic field are considered to be a nested hierarchy of electromagnetic fields that may also include electromagnetic patterns in three-dimensional space. The coupling between the two-brains may involve an 'anticipatory affect' based on the conceptualization of anticipation as potentiality, arising either from the macro-quantum potential energy or from the electrostatic effects of residual charges in the quantum and classical subsystems of the two-brains that occurs through partitioning of the potential energy of the combined quantum molecular dynamic system.
In this paper, the optimal allocation of constant and switchable capacitors is presented simultaneously in two operation modes, grid-connected and islanded, for a microgrid. Different load levels are considered by employing non-dispatchable distributed generations. The objective function includes minimising the energy losses cost, the cost of peak power losses, and the cost of the capacitor. The optimization problem is solved using the spotted hyena optimizer (SHO) algorithm to determine the optimal size and location of capacitors, considering different loading levels and the two operation modes. In this study, a three-level load and various types of loads, including constant power, constant current, and constant impedance are considered. The proposed method is implemented on a 24-bus radial distribution network. To evaluate the performance of the SHO, the results are compared with GWO and the genetic algorithm (GA). The simulation results demonstrate the superior performance of the SHO in reducing the cost of losses and improving the voltage profile during injection and non-injection of reactive power by distributed generations in two operation modes. The total cost and net saving values for DGs only with the capability of active power injection is achieved 105,780 $ and 100,560.54 $, respectively and for DGs with the capability of active and reactive power injection is obtained 89,568 $ and 76,850.46 $, respectively using the SHO. The proposed method has achieved more annual net savings due to the lower cost of losses than other optimization methods.
Agglomeration and restacking can reduce graphene oxide (GO) activity in a wide range of applications. Herein, GO was synthesized by a modified Hummer's method. To minimize restacking and agglomeration, in situ chemical oxidation polymerization was carried out to embed polyaniline (PANI) chains at the edges of GO sheets, to obtain GO-PANI nanocomposite. The GO-PANI was tested for the adsorptive removal of brilliant green (BG) from an aqueous solution through batch mode studies. Infrared (FT-IR) analysis revealed the dominance of hydroxyl and carboxylic functionalities over the GO-PANI surface. Solution pH-dependent BG uptake was observed, with maximum adsorption at pH 7, and attaining equilibrium in 30 min. The adsorption of BG onto GO-PANI was fit to the Langmuir isotherm, and pseudo-second-order kinetic models, with a maximum monolayer adsorption capacity (qm) of 142.8 mg/g. An endothermic adsorption process was observed. Mechanistically, π-π stacking interaction and electrostatic interaction played a critical role during BG adsorption on GO-PANI.
Exposure to hot and humid weather conditions will often lead to consuming a vast amount of electricity for cooling. Heating, ventilation, and air conditioning (HVAC) systems are customarily known as the largest consumers of energy in institutions and other facilities which raises the question regarding the impact of the weather conditions to the amount energy consumed. The academic building is a perfect example where a constant fixed daily operating characteristic is measured by the hour, aside from the occasional semester break. Therefore, it can be assumed that the daily HVAC services on an academic facility will operate on a fixed schedule each day, having a similar pattern all year round. This article aims to present an analysis on the relationship between typical weather data by implying the test reference year (TRY) and academic building electricity consumption in an academic building located at Durian Tunggal, Melaka. Typical weather data were generated in representing the weather data between 2010 and 2018 using the Finkelstein-Schafer statistic (F-S statistic) in addition to a data set of electricity consumption. Descriptive analysis and correlation matrix analysis were conducted using JASP software for two sets of sample data; Set A and Set B, with data points of 12 and 108, respectively. The result showed an alternate result with a positive correlation between 1)mean temperature-electricity consumption, and 2)mean rainfall-electricity consumption for data Set A, and a negative correlation between 1)mean temperature-electricity consumption and 2)mean rainfall-electricity consumption for data Set B.
This experiment was conducted to study the potential of solid electrolyte from the fish waste of Clarias gariepinus for battery application. The battery was one of the important components that supplies electrical energy to users throughout the world, and it strongly contributed to technology development in the economic sector, transportation, residential as well as agriculture. The presence of ammonia in organic fish waste could produce renewable energy and helped to reduce the use of lithium-ion batteries in modern industries. Two different parameters were being observed in this study, which was the quantity of fish and the number of the cell layer. The process of collecting the fish waste was carried out in the hatchery at Universiti Malaysia Terengganu using two methods, which were filtering and soaking. The result showed that the highest value of energy output was 0.430V from waste filtering of 50 fish and 0.207V from soaking in waste of 50 fish. Meanwhile, the lowest energy output was from the tank that contained ten fish with an energy output of 0.177V for filtering and 0.101V for soaking. Besides, for a different number of the cell layer, the highest value of energy output was 0.414V at 25 layers, and the lowest voltage was 0.175V at five layers. Thus, from the study was observed that the produced voltage was dependent on the quantity of fish and the number of the cell layer, when the quantity of fish and number of cell layer increases, the output energy was also increased.
Nowadays, the world is confronting the increasing energy demand, reduction of emissions and security of energy supply. The high energy demand leads to a severe problem, and we need to reduce the usage of non-renewable energy to avoid adverse climate change. Thus, renewable energy is an important role obtained from the natural environment and can be replenished naturally from those sources without environmental degradation. Water energy is one of the most promising renewable energy sources today, especially in the aquaculture industry. Hydropower played a vital role in producing large scale power and electricity. This study was set up to determine the electrical energy output depending on the different sizes and shapes of tanks. It is also to measure the water flow rate based on different size and shape tanks. Besides, the Pelton type of water turbine generator micro-hydroelectric DC 12V output was used in this experiment. Two types of tanks (rectangular and circular) with three different sizes (0.5 ton, 1.0 ton and 2.0 ton) were tested to measure high value of output energy (V) and flow rate (m3/s) by using clear water and wastewater. The result significantly shows that the circular tank had a higher water flow rate and output energy than the rectangular tank due to higher gravitational force, where the outlet placed in the middle and edge of the tank, respectively. The finding of this study benefits the aquaculture industry, where it introduced an alternative and cheaper method of reusing wastewater, reducing the cost maintenances and enhancing the profit of the business.