Although efficiency of Dye Sensitized Solar Cell (DSSC) is still below the performance level of the market dominance silicon solar cells, in the last two decades DSSC has gathered sufficient ...interests because of the simplicity in device fabrication and low material cost, and therefore, DSSC is providing a possibility of solar cells production at a low entry cost. This review presents the research progress made in the implementation of natural pigments in DSSC. These pigments function as dye sensitizers and they play a major role in DSSC by absorbing light, and supplying electrons to the semiconductor matrixes in the cell. The common choices of dyes are the metal complexes, organic and/or natural dyes. A better efficiency with higher durability is observed for DSSC using metal complexes and organic dyes, however, the process of synthesizing these dyes is laborious, costly, and involves the use of toxic materials. As an alternative, natural pigments (dyes) found in plants such as anthocyanin, carotenoid, aurone, chlorophyll, tannin, betalain and many others are accepted as dyes in DSSCs. These natural pigments are easily obtained from fruits, flowers, leaves, seeds, barks and various parts of plants. Despite the limited performance of natural dyes, the prevailing advantages of natural dyes include high absorption coefficients, high light harvesting efficiency, low cost extraction and low toxicity. This review provides insight into the usage of the various natural pigments as sensitizers, the techniques to improve the pigments performance in DSSC, an outlook on the developmental work on the application of natural pigments in DSSC and their limitation. Additionally, the paper discusses the overall operation principle and the recent developments of each component of DSSC, as well as, comparing the material cost between natural dye and synthetic dye DSSC.
•Natural pigments have a promising future as sensitizers in DSSCs.•Anthocyanin, carotenoid, aurone, chlorophyll, tannin and betalain are among the natural pigments used as sensitizers.•Low-cost extraction, vast availability and eco-friendliness are major attractions of natural pigments.•The total fabrication cost for DSSC sensitized with chlorophyll is less than ~€ 2 per Watt peak.
Solid oxide fuel cell (SOFC) has been achieving attention in term of possibility in variety of fuels. Proton conductor enhanced conventional oxide conducting electrolyte has become more and more ...interesting particularly in intermediate operating temperature. Combination of doped BaCeO3 and BaZrO3 by doping Sr, Y and Sm was studied as the series of Ba1−xSrxCe0.5Zr0.35Y0.1Sm0.05O3−δ (BSCZYSm) by varying composition x = 0.5, 0.7, 0.9 and 1.0. The X-ray analysis reveals right-shifted peaks due to changing in unit cell volume. The cell parameters and density decreased with increasing Sr content. Rietveld refinement shows that all compositions crystallize in the cubic symmetry in the space group Pm-3m. Thermogravimetric analysis on dried and hydrated samples under nitrogen show significant weight change to prove the proton uptake at higher temperature. Scanning electron microscopy shows that the density is higher than 90% for all samples. BSCZYSm with x = 0.5 shows the highest conductivity in wet argon condition which is 2.391 × 10−3 S cm−1 at 700 °C. Particle size of materials were examined and reveal average diameter of 5.8 μm approximately.
Abstract Although the aspects that affect the performance and the deterioration of abrasive belt grinding are known, wear prediction of abrasive belts in the robotic arm grinding process is still ...challenging. Massive wear of coarse grains on the belt surface has a serious impact on the integrity of the tool and it reduces the surface quality of the finished products. Conventional wear status monitoring strategies that use special tools result in the cessation of the manufacturing production process which sometimes takes a long time and is highly dependent on human capabilities. The erratic wear behavior of abrasive belts demands machining processes in the manufacturing industry to be equipped with intelligent decision-making methods. In this study, to maintain a uniform tool movement, an abrasive belt grinding is installed at the end-effector of a robotic arm to grind the surface of a mild steel workpiece. Simultaneously, accelerometers and force sensors are integrated into the system to record its vibration and forces in real-time. The vibration signal responses from the workpiece and the tool reflect the wear level of the grinding belt to monitor the tool’s condition. Intelligent monitoring of abrasive belt grinding conditions using several machine learning algorithms that include K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Decision Tree (DT) are investigated. The machine learning models with the optimized hyperparameters that produce the highest average test accuracy were found using the DT, Random Forest (RF), and XGBoost. Meanwhile, the lowest latency was obtained by DT and RF. A decision-tree-based classifier could be a promising model to tackle the problem of abrasive belt grinding prediction. The application of various algorithms will be a major focus of our research team in future research activities, investigating how we apply the selected methods in real-world industrial environments.
PurposeThis paper aims to share how it was possible to change the way business was conducted in a short period in order to continue the academic semester and seek alternatives to manage the ...day-to-day university affairs in the midst of a pandemic crisis at a higher education setting. As a result, the authors’ experiences have created new norms and opportunities for the university.Design/methodology/approachThe coronavirus disease 2019 (COVID-19) pandemic in Brunei Darussalam is an evolving situation with extraordinary challenges for staff and students of the university. Although the campus remains open and essential services were continuously provided, the university had to implement and adapt to new norms instinctively to minimise the potential pathways for community spread of the coronavirus and at the same time minimise interruption in teaching and learning.FindingsFirstly, structured blended learning will be the basis of teaching and learning, alongside ensuring the highest quality of online education and successful achievement of the intended learning objectives. Secondly, blended learning will open more opportunities to offer programmes in a more flexible, personalised, student-centric and lifelong learning manner, with the option of taking a study hiatus at students' convenience. Thirdly, there will be more global classrooms and the exchange of online modules with international partner universities. Fourthly, short programmes such as the Global Discovery Programmes will be modified and improvised to become an online learning experience. And finally, there will also be the opportunity to understand and consider the physical and mental well-being and durability of the university community in overcoming a national crisis situation.Originality/valueThis paper is intended to be a conceptual paper where the authors describe novel experiences during the pandemic. The authors’ views, interventions and experiences may result into a new model for higher education that will reposition students to the new global markets and economy.
Solid oxide fuel cell (SOFC) has been considered to generate power represented by conductivity. Zinc doped Barium Cerium Zirconium Yttrium oxide (BCZYZn) has been found to offer high protonic ...conductivity and high stability as being electrolyte for proton-conducting SOFCs. In this study, we report a new series of proton conducting materials, BaCe0.7Zr0.25−xYxZn0.05O3 (x = 0.05, 0.1, 0.15, 0.2 and 0.25). The materials were synthesized by solid state reaction route and characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), thermal expansion, particle size and impedance spectroscopy (IS). Rietveld analysis of the XRD data reveal a cubic perovskite structure with Pm-3m space group up to composition x = 0.15. For x = 0.15 and 0.20, the materials have structural phase change to orthorhombic in the Pbnm space group. Scanning electron microscopy images show high density materials. Thermal expansion measurements show that the thermal expansion coefficient is in the range 10.0–11.0 × 10−6/°C. Impedance spectroscopy shows higher ionic conduction under wet condition compared to dry condition. Y content of 25% (BCZYZn25) exhibits highest conductivity of 1.84 × 10−2 S/cm in wet Argon. This study indicated that perovskite electrolyte BCZYZn is promising material for the next generation of intermediate temperature solid oxide fuel cells (IT-SOFCs).
iPlug: Decentralised dispatch of distributed generation Rongali, Subendhu; Ganuy, Tanuja; Padmanabhan, Manikandan ...
2016 8th International Conference on Communication Systems and Networks (COMSNETS),
01/2016
Conference Proceeding, Journal Article
With advances in solar photovoltaic technology and decreasing costs of panels, solar energy is considered as an economical and sustainable solution for growing energy demands, especially in countries ...such as India with high insolation levels. However, key challenges exist in large scale adoption of distributed solar generation. Firstly, there are concerns related to breach of voltage regulations and system instabilities caused by distributed generation. Secondly, there are challenges in providing robust communication infrastructure for utilities to actively control and dispatch distributed generation. We address these challenges by designing a decentralised controller iPlug, which involves voltage-sensitive back-off of the level of solar capacity injection into the grid and is inspired by the CSMA protocol from Networking literature. This is done in conjunction with other resources like local batteries and local demand ramp-up resources. iPlug functions are complementary to emerging microinverter technologies and could in principle be incorporated into either the inverter controls or battery and home energy management control systems. We present preliminary results from simulation-based evaluation of iPlug algorithms and compare it with static PV injection strategies.
World-changing technologies have rolled out in recent years to address an ever-increasing demand for safety and security. While fire accidents are increasing due to a variety of factors, the need for ...enhanced technology to detect smoke and fire at an early stage has been declared. An algorithm for detecting incipient stage smoke under any backdrop conditions has been proposed in this study using non-rigid regional bodies. The feature vector for multi-background frames was optimized in order to identify the swift and cost-effective way. Consequently, the non-rigid bodies algorithm (NRBA) was created to detect the onset of smoke or fire with a detection accuracy of 1 second for the high frame rate camera and 4 seconds for the low frame rate camera.
This thesis described the research carried out on the development of a novel hardwired tactile sensing system tailored for the application of a next generation of surgical robotic and clinical ...devices, namely a steerable endoscope with tactile feedback, and a surface plate for patient posture and balance. Two case studies are examined. The first is a one-dimensional sensor for the steerable endoscope retrieving shape and 'touch' information. The second is a two-dimensional surface which interprets the three-dimensional motion of a contacting moving load. This research can be used to retrieve information from a distributive tactile sensing surface of a different configuration, and can interpret dynamic and static disturbances. This novel approach to sensing has the potential to discriminate contact and palpation in minimal invasive surgery (MIS) tools, and posture and balance in patients. The hardwired technology uses an embedded system based on Field Programmable Gate Arrays (FPGA) as the platform to perform the sensory signal processing part in real time. High speed robust operation is an advantage from this system leading to versatile application involving dynamic real time interpretation as described in this research. In this research the sensory signal processing uses neural networks to derive information from input pattern from the contacting surface. Three neural network architectures namely single, multiple and cascaded were introduced in an attempt to find the optimum solution for discrimination of the contacting outputs. These architectures were modelled and implemented into the FPGA. With the recent introduction of modern digital design flows and synthesis tools that essentially take a high-level sensory processing behaviour specification for a design, fast prototyping of the neural network function can be achieved easily. This thesis outlines the challenge of the implementations and verifications of the performances.
This thesis described the research carried out on the development of a novel hardwired tactile sensing system tailored for the application of a next generation of surgical robotic and clinical ...devices, namely a steerable endoscope with tactile feedback, and a surface plate for patient posture and balance. Two case studies are examined. The first is a one-dimensional sensor for the steerable endoscope retrieving shape and 'touch' information. The second is a two-dimensional surface which interprets the three-dimensional motion of a contacting moving load. This research can be used to retrieve information from a distributive tactile sensing surface of a different configuration, and can interpret dynamic and static disturbances. This novel approach to sensing has the potential to discriminate contact and palpation in minimal invasive surgery (MIS) tools, and posture and balance in patients. The hardwired technology uses an embedded system based on Field Programmable Gate Arrays (FPGA) as the platform to perform the sensory signal processing part in real time. High speed robust operation is an advantage from this system leading to versatile application involving dynamic real time interpretation as described in this research. In this research the sensory signal processing uses neural networks to derive information from input pattern from the contacting surface. Three neural network architectures namely single, multiple and cascaded were introduced in an attempt to find the optimum solution for discrimination of the contacting outputs. These architectures were modelled and implemented into the FPGA. With the recent introduction of modern digital design flows and synthesis tools that essentially take a high-level sensory processing behaviour specification for a design, fast prototyping of the neural network function can be achieved easily. This thesis outlines the challenge of the implementations and verifications of the performances.
