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Item A method to enhance web service clustering by integrating label-enhanced functional semantics and service collaboration.(IEEE, 2024-05-06) Liu, Qingxue; Wang, Lifang; Du, Shengzhi; Van Wyk, Barend JacobusIn Web service clustering, the service function vector (SFV) directly determines the quality of service (QoS) clustering. To improve service clustering performance, a method is proposed in this paper by integrating label-enhanced functional semantics and service collaboration. It improves the SFV from three aspects: generation model, corpus, and structural auxiliary information. At the generation model level, a Sentence-BERT is constructed based on singular value decomposition (SVD), to alleviate the anisotropy problem of BERT in vectorizing service descriptions. For corpus, the semantic features of SFV are supplemented by extracting specific named entities from service descriptions. Meanwhile, the service collaboration graph is established according to the collaboration relationship among Web services, which is conducive to the variational graph auto-encoders (VGAE) to realize service collaboration feature aggregation and further improve the SFV. Experiments show that the improved model, corpus and structural auxiliary information effectively enhance the SFV clustering. The proposed Web service clustering method is superior to the state-of-the-art methods.Item Data-driven controller for drivers’ steering-wheel operating behaviour in haptic assistive driving system.(MDPI, 2024-03-21) Tientcheu, Simplice Igor Noubissie; Du, Shengzhi; Djouani, Karim; Liu, QingxueAn advanced driver-assistance system (ADAS) is critical to driver–vehicle-interaction systems. Driving behaviour modelling and control significantly improves the global performance of ADASs. A haptic assistive system assists the driver by providing a specific torque on the steering wheel according to the driving–vehicle–road profile to improve the steering control. However, the main problem is designing a compensator dealing with the high-level uncertainties in different driving scenarios with haptic driver assistance, where different personalities and diverse perceptions of drivers are considered. These differences can lead to poor driving performance if not properly accounted for. This paper focuses on designing a data-driven model-free compensator considering various driving behaviours with a haptic feedback system. A backpropagation neural network (BPNN) models driving behaviour based on real driving data (speed, acceleration, vehicle orientation, and current steering angle). Then, the genetic algorithm (GA) optimises the integral time absolute error (ITEA) function to produce the best multiple PID compensation parameters for various driving behaviours (such as speeding/braking, lane-keeping and turning), which are then utilised by the fuzzy logic to provide different driving commands. An experiment was conducted with five participants in a driving simulator. During the second experiment, seven participants drove in the simulator to evaluate the robustness of the proposed combined GA proportional-integral-derivative (PID) offline, and the fuzzy-PID controller applied online. The third experiment was conducted to validate the proposed data-driven controller. The experiment and simulation results evaluated the ITAE of the lateral displacement and yaw angle during various driving behaviours. The results validated the proposed method by significantly enhancing the driving performance.Item Comparison of domain selection methods for multi-source manifold feature transfer learning in electroencephalogram classification.(MDPI, 2024-03-10) Maswanganyi, Rito Clifford; Tu, Chungling; Owolawi, Pius Adewale; Du, ShengzhiTransfer learning (TL) utilizes knowledge from the source domain (SD) to enhance the classification rate in the target domain (TD). It has been widely used to address the challenge of sessional and inter-subject variations in electroencephalogram (EEG)-based brain–computer interfaces (BCIs). However, utilizing knowledge from a combination of both related and non-related sources can significantly deteriorate the classification performance across individual target domains, resulting in a negative transfer (NT). Hence, NT becomes one of the most significant challenges for transfer learning algorithms. Notably, domain selection techniques have been developed to address the challenge of NT emerging from the transfer of knowledge from non-related sources. However, existing domain selection approaches iterate through domains and remove a single low-beneficial domain at a time, which can massively affect the classification performance in each iteration since SDs respond differently to other sources. In this paper, we compare domain selection techniques for a multi-source manifold feature transfer learning (MMFT) framework to address the challenge of NT and then evaluate the effect of beneficial and non-beneficial sources on TL performance. To evaluate the effect of low-beneficial and high beneficial sources on TL performance, some commonly used domain selection methods are compared, namely, domain transferability estimation (DTE), rank of domain (ROD), label similarity analysis, and enhanced multi-class MMFT (EMC-MMFT), using the same multi-class cross-session and cross-subject classification problems. The experimental results demonstrate the superiority of the EMC-MMFT algorithm in terms of minimizing the effect of NT. The highest classification accuracy (CA) of 100% is achieved when optimal combinations of high beneficial sources are selected for two-class SSMVEP problems, while the highest CAs of 98% and 87% are achieved for three- and four-class SSMVEP problems, respectively. The highest CA of 98% is achieved for two-class MI classification problems, while the highest CAs of 90% and 71.5% are obtained for three- and four-class MI problems, respectively.Item The sense of agency in human–machine interaction systems(MDPI, 2024-08-20) Yu, Hui; Du, Shengzhi; Kurien, Anish; Van Wyk, Barend Jacobus; Liu, QingxueHuman–Machine Interaction (HMI) systems are integral to various domains and rely on human operators for effective performance. The sense of agency (SoA) is crucial in these systems, as it influences the operator’s concentration and overall efficiency. This review explores the SoA in HMI systems, analyzing its definition, key influencing factors, and methods for enhancement. We provide a comprehensive examination of SoA-related research and suggest strategies for measuring and improving the SoA. Two key research directions are highlighted: the impact of user experience on the SoA, and the role of the SoA in enabling unconscious communication between humans and machines. We propose a development route for HMI systems, outlining a progressive structure across three stages: machine-centric, human-centric, and human–machine integration. Finally, we discuss the potential of gaming platforms as tools for advancing SoA research in HMI systems. Our findings aim to enhance the design and functionality of HMI systems, ensuring improved operator engagement and system performance.Item Time-delay estimation improves active disturbance rejection control for time-delay nonlinear systems.(MDPI, 2024-08-13) Nahri, Syeda Nadiah Fatima; Du, Shengzhi; Van Wyk, Barend J.; Tong, Jigang; Nyasulu, Tawanda DenzelLately, active disturbance rejection control (ADRC), a model-independent controller, has become popular for combating various forms of uncertain disturbances incurred in industrial applications. ADRC was validated for external disturbances, internal disturbances, and nonlinearities incurred under realistic scenarios. Time delay challenges all controllers, especially when it coexists with nonlinearities. This paper investigates the impacts of time delay and backlash-like hysteresis nonlinearity in ADRC-controlled systems. These impacts are analyzed, as in the case study, in two ADRC-based methods, namely the ADRC with delayed input method and the predictive extended state observer (PESO)-based ADRC (PESO-ADRC) method. To improve the system response and to attain a decent attenuation of uncertainties, the time-delay estimation (TDE) mechanism is introduced to the concerned ADRC-based methods. Experimental studies are conducted to verify the effectiveness and stability of the proposed TDE-ADRC methods. The results demonstrate the robustness and decent recovery of the transient response after the adverse impact of the backlash-like hysteresis on both concerned ADRC-controlled systems.Item A spatio-temporal capsule neural network with self-correlation routing for eeg decoding of semantic concepts of imagination and perception tasks.(MDPI, 2024-09-15) Huang, Jianxi; Chang, Yinghui; Li, Wenyu; Tong, Jigang; Du, ShengzhiDecoding semantic concepts for imagination and perception tasks (SCIP) is important for rehabilitation medicine as well as cognitive neuroscience. Electroencephalogram (EEG) is commonly used in the relevant fields, because it is a low-cost noninvasive technique with high temporal resolution. However, as EEG signals contain a high noise level resulting in a low signal-to-noise ratio, it makes decoding EEG-based semantic concepts for imagination and perception tasks (SCIP-EEG) challenging. Currently, neural network algorithms such as CNN, RNN, and LSTM have almost reached their limits in EEG signal decoding due to their own shortcomings. The emergence of transformer methods has improved the classification performance of neural networks for EEG signals. However, the transformer model has a large parameter set and high complexity, which is not conducive to the application of BCI. EEG signals have high spatial correlation. The relationship between signals from different electrodes is more complex. Capsule neural networks can effectively model the spatial relationship between electrodes through vector representation and a dynamic routing mechanism. Therefore, it achieves more accurate feature extraction and classification. This paper proposes a spatio-temporal capsule network with a self-correlation routing mechaninsm for the classification of semantic conceptual EEG signals. By improving the feature extraction and routing mechanism, the model is able to more effectively capture the highly variable spatio-temporal features from EEG signals and establish connections between capsules, thereby enhancing classification accuracy and model efficiency. The performance of the proposed model was validated using the publicly accessible semantic concept dataset for imagined and perceived tasks from Bath University. Our model achieved average accuracies of 94.9%, 93.3%, and 78.4% in the three sensory modalities (pictorial, orthographic, and audio), respectively. The overall average accuracy across the three sensory modalities is 88.9%. Compared to existing advanced algorithms, the proposed model achieved state-of-the-art performance, significantly improving classification accuracy. Additionally, the proposed model is more stable and efficient, making it a better decoding solution for SCIP-EEG decoding.Item Investigation into the suitability of AA 6061 and Ti6Al4V as substitutes for SS 316L Use in the paraplegic swivel mechanism.(MDPI, 2024-11-13) Ajayi, Oluwaseun K.; Malomo, Babafemi O.; Du, Shengzhi; Owolabi, Hakeem A.SS 316L, a low-carbon 316 Stainless Steel, has been used to manufacture swivel mechanisms for paraplegic patients, but its weight is relatively high compared to a few materials in its range of properties. Aluminum alloy 6061 and Titanium alloy (Ti6Al4V) offer lightweight and incredible strength-to-weight ratio, hence their use for medical, aerospace, and automotive applications. This study, therefore, seeks a replacement for SS 316L. A 3D model of a swivel mechanism was developed to compare the performance of the swivel mechanism made with SS 316L, AA 6061, and Ti6Al4V. The kinematic analysis of the mechanism based on a range of weights: 1kN, 1.1 kN, 1.2 kN, 1.3 kN, 1.4 kN, and 1.5 kN was carried out to generate the inputs for the simulation. The 3D model was made with SolidWorks, and the results of the kinematic analysis were used to define the simulation parameters for the mechanism. Two scenarios generated depicted the full collapse of the mechanism and the full extension. The results showed that AA 6061 and Ti6Al4V outperformed SS 316L with higher yield strength and factor of safety. Therefore, swivel plates made with AA 6061 and Ti6Al4V have higher yield strength than those made with SS 316L, adding to the advantage that they have a higher strength-to-weight ratio. From this analysis and known knowledge of the cost of these materials, the optimal replacement considering cost with yield strength is AA 6061. However, Ti6Al4V is a better alternative for the strength-to-weight ratio for SS 316L.Item Multi-class transfer learning and domain selection for cross-subject eeg classification.(MDPI, 2023-04-21) Maswanganyi, Rito Clifford; Tu, Chungling; Owolawi, Pius Adewale; Du, ShengzhiTransfer learning (TL) has been proven to be one of the most significant techniques for cross-subject classification in electroencephalogram (EEG)-based brain-computer interfaces (BCI). Hence, it is widely used to address the challenges of cross-session and cross-subject variability with more accurate intention prediction. In this case, TL utilizes knowledge (signal features) in the source domain(s) to improve the classification in the target domain. However, current existing transfer learning approaches on EEG-based BCI are mostly limited to two-class cross-subject classification problems, while multi-class problems are only implemented with a focus on within-subject classification due to the complexity of multi-class cross-subject classification problems. In this paper, we first extended the transfer learning approaches to a multi-class cross-subject scenario, then investigated the reason for transfer learning performance being poor in multi-class cross-subject classification. Secondly, we address the challenge of significant sessional and subject-to-subject variations originating from both known and unknown factors. It is discovered that such variations have a massive influence on the classification because of the negative transfer (NT) across domains. Based on this discovery, we propose a multi-class transfer learning approach based on multi-source manifold feature transfer learning (MMFT) framework and an enhanced version to minimize the effects of NT. The proposed multi-class transfer learning approach extends the existing MMFT to multi-class cases. Then enhanced multi-class MMFT firstly searches for domains with high transferability and selects only the best combination among source domains (SD), then utilize the best-selected combination of domains for transfer learning. Experimental results illustrate that the proposed multi-class MMFT can be employed in the cross-subject classification of both three-class and four-class problems. Experimental results also demonstrated that the enhanced multi-class MMFT could effectively minimize the effect of negative transfer and significantly increase the prediction rates across individual target domains (TD). The highest classification accuracy (CA) of 98% is obtained by the enhanced multi-class MMFT.Item A low complexity greedy scheduler for multiuser MIMO downlink.(Wiley, 2014-02-01) Mureithi, George Maina; Mzyece, Mjumo; Djouani, KarimIt is widely believed that the implementation of multi-user multiple input multiple output (MU-MIMO) technology at the radio access portion of current and future wireless networks would positively impact on the performance of such networks especially in terms of system capacity. This however demands the design of efficient multi-user scheduling algorithms at the data link layer. In the case of packet data which is delay tolerant, there is more flexibility in the design of such multi-user scheduling algorithms. One such algorithm that is known to be throughput optimal is the greedy scheduler. For the downlink of a single input single output (SISO) system, the greedy scheduler serves the user whose channel maximizes the channel capacity at each transmission opportunity. By employing this algorithm to the down- link of a MU-MIMO system applying spatial multiplexing, the scheduler can allow a subset of active users whose channels are most favourable to transmit simultaneously. However, unlike in the SISO systems, the implementation of the classical greedy scheduler in MU-MIMO systems would result in very high computational complexity. This paper proposes a low complexity greedy scheduler for the MU-MIMO downlink and through simulations, demon- strates that the low complexity greedy scheduler performs close to the classical greedy scheduler but with minimum complexity.Item Energy harvesting techniques for sustainable underwater wireless communication networks: A review.(Elsevier Ltd., 2023-08-23) Alamu, Olumide; Olwal, Thomas O.; Djouani, KarimThe emergence of various underwater wireless communication systems has been on the rise due to increasing human activities in the marine environment. In underwater wireless communication networks (UWCNs), several communication devices, such as sensors and autonomous underwater vehicles (AUV) are interconnected to expand communication coverage, monitoring, information gathering, and surveillance. These devices operate on batteries, making their replacement and recharging difficult. Consequently, sustaining the operational lifetime of UWCNs is deemed a major challenge. This leads to the development of various energy harvesting (EH) techniques to perpetuate the power supply to underwater devices. In this paper, we present a review of various energy sources and EH techniques applicable to UWCNs. To achieve this, we classify the energy sources into various categories in order to establish the peculiarities of each source and the type of harvester applicable to each category. Based on this classification, we present discussions on various contributions of articles related to applications of EH techniques in UWCNs. In addition to various insights gained from the presented papers, we establish that energy harvesters based on triboelectric effect, piezoelectric effect, sediment microbial fuel cell, acoustic, and optical power transfer are suitable for low-power (milliwatt-order) consuming devices such as sensors. Also, for devices with high power consumption requirement, such as AUV, solar and inductive power transfer-based harvesters should be employed. Furthermore, we identify several technical challenges that should be taken into consideration during the planning and system design phases. Finally, we highlight open research areas that could further improve the EH and communication processes in UWCNs.Item A novel non-iterative based framework for quick dynamic assessment of wind energy dominated multi-machine power system.(Elsevier Ltd., 2023-08-05) Alayande, Akintunde Samson; Popoola, Olawale; Pam, Gyang PaulRenewable Energy Sources have considerably expanded in recent years to address the widening energy deficit in modern power systems. Integrating these sources raises significant concerns for power system management, with transient stability constraints of networks being one of the growing issues for engineers and researchers. In this paper, the impact of Doubly Fed Induction Generators integration is analyzed to examine the transient stability on two test models. A Coupling Strength Index formulated from Network Structural Characteristics Theory is explored to detect the weakest transmission line. This method identifies line 7 to 8 and 5 to 6 as the weakest line with coupling strength index of 0.02739 and 0.105158 for IEEE 9 and 39 bus system, respectively. The system’s transient stability is then investigated with and without the Doubly Fed Induction Generators, considering a three-phase short-circuit fault applied at the middle of the identified line. Several characteristics associated with the system such as generator speed, rotor angle, and electric power were investigated. The simulation was carried out using DIgSILENT Power Factory and the results indicate that the systems are negatively impacted by the integration of Doubly Fed Induction Generators.Item Energy harvesting techniques for sustainable underwater wireless communication networks: A review.(Elsevier Ltd., 2023-08-23) Alamu, Olumide; Olwal, Thomas O.; Djouani, kARIMThe emergence of various underwater wireless communication systems has been on the rise due to increasing human activities in the marine environment. In underwater wireless communication networks (UWCNs), several communication devices, such as sensors and autonomous underwater vehicles (AUV) are interconnected to expand communication coverage, monitoring, information gathering, and surveillance. These devices operate on batteries, making their replacement and recharging difficult. Consequently, sustaining the operational lifetime of UWCNs is deemed a major challenge. This leads to the development of various energy harvesting (EH) techniques to perpetuate the power supply to underwater devices. In this paper, we present a review of various energy sources and EH techniques applicable to UWCNs. To achieve this, we classify the energy sources into various categories in order to establish the peculiarities of each source and the type of harvester applicable to each category. Based on this classification, we present discussions on various contributions of articles related to applications of EH techniques in UWCNs. In addition to various insights gained from the presented papers, we establish that energy harvesters based on triboelectric effect, piezoelectric effect, sediment microbial fuel cell, acoustic, and optical power transfer are suitable for low-power (milliwatt-order) consuming devices such as sensors. Also, for devices with high power consumption requirement, such as AUV, solar and inductive power transfer-based harvesters should be employed. Furthermore, we identify several technical challenges that should be taken into consideration during the planning and system design phases. Finally, we highlight open research areas that could further improve the EH and communication processes in UWCNs.Item Development of a novel plane piezoelectric actuator using Hamilton’sprinciple based model and Hertz contact theory.(Elsevier B.V., 2014-07-06) M’boungui, G.; Semail, B.; Giraud, F.; Jimoh, A.A.A simple device based on friction coefficient control was designed as a solution to the lack of compact-ness and simplicity encountered in the number of force feedback interfaces. The structure comprises a64 × 38 × 3 mm copper-beryllium plate on which well-adjusted polarized piezoceramics are glued. The plate stands on four legs, each of which has a spherical end. By controlling the drive voltage, friction force may be varied as required by a user who moves the device on a flat surface, as he or she would do with a normal mouse. This adds the possibility of rendering simulated forces from objects manipulated on a PC screen. Friction forces obtained using Hertz contact theory compare well with the ones measured on an experimental setup, which demonstrate the validity of the approach with regard to force feedback application.Item An alternative algorithm for solving generation‐to‐load matching and loss allocation problems.(Wiley, 2017-01-21) Alayande, Akintunde S.; Jimoh, Adisa A.; Yusuff, Adedayo A.This paper presents an alternative approach of Inherent Structural Characteristics Theory (ISCT), for solving loss allocation to network participants as well as generation‐to‐load matching problems in a deregulated environment. The mathematical formulations of ISCT, based on the fundamental circuit theory laws, are revisited. A Generation‐to‐Load Allocation Coefficient (GLAC) matrix for solving generation‐to‐load allocation and network loss allocation to load problems, for efficient transmission pricing, is formulated. The allocation of real and reactive power contributions, by individual generator, required to serve the network demands is also determined on the basis of the GLAC matrix. Total network losses are determined and allocated to individual network loads based on GLAC matrix. The approach is demonstrated using the standard IEEE 30 bus network. The results obtained are compared with that obtained using graph theory approach based on the solved power flow. The comparison of the results shows that the ISCT approach is reasonable and it is a good signal, which could be useful for pricing of electricity by the market regulators.Item Design of fault-tolerant automotive gateway architecture using MC9S12XDP512 microcontroller device.(MDPI, 2023-08-10) Krishnamoorthy, Ramesh; Chokkalingam, Bharatiraja; Munda, Josiah LangeThe increasing number of electrical components and sensors in modern vehicles makes network design more challenging. The development of automotive electronics through multiple communication protocols bring out the importance of a hybrid network that is both optimal and fault tolerant. In order for a vehicle to communicate with electronic components like engine management systems, stability control units, braking systems, and door functions, a CAN (controller area network) is developed. In order to create a hierarchical vehicle network gateway for quality fortification and cost reduction of vehicles, the CAN and LIN (local interconnect network) are considered. This standardisation will reduce the variety of low-end multiplex solutions currently available for automotive electronics’ development costs, production rates, service fees, and logistics costs. The implementation of a gateway in these electronic devices is made possible with the proposed hybrid architecture. This system effectively shows the high-speed and low-speed applications relevant to crucial ECUs in the network by using two distinct CAN and LIN gateways to send sensor data between the ECUs (electronic control units).Item On the most suitable sites for wind farm development in Nigeria.(Elsevier Inc., 2018-05-08) Ayodele, T.R.; Ogunjuyigbe, A.S.O.; Odigie, O.; Jimoh, A.A.The increasing demand for energy and the need for clean and affordable energy in Nigeria have necessitated the need for renewable energy resource assessment and subsequent determination of suitable sites within the country. One of the promising renewable energy resources with good potentials of meeting the energy requirements is wind. One of the main challenges of wind power development in Nigeria is lack of scientific data for policy formulation and decision making that will aid the development of wind power utilization. The data presented in this article were obtained with proper evaluation of the wind resource while taking into consideration environmental, social, and economic factors. The information from the data could be useful for taking optimal site selection decision by the policy makers, government, engineers etc. This will ensure optimal investment and return on investment for wind farm developers.Item Selection and rating of the step-up transformer for renewable energy application.(SAIEE, 2020-06-01) Thango, Bonginkosi A.; Jordaan, Jacobus A.; Nnachi, Agha F.In the past decade, South Africa has acquired more renewable energy (RE) generation capacity than the rest of the Sub-Saharan countries. This development has led to increasing concerns about problems associated with electrical equipment connected with the RE technologies, especially in wind and solar. These RE technologies have intermittent generation profiles and are connected to non-linear loads. The fundamental electrical equipment including the step-up transformer, with respect to which, high harmonic losses, abnormal temperature rise, and gassing problems have been extensively reported within the last 10 years and remains a precedence for many Independent Power Producers (IPPs). A requirement of the step-up transformer is that IPPs are required to provide a technical schedule clarifying the harmonic and distortion content at the plant’s point of common coupling (PCC). A lack of this knowledge to the transformer manufactures thereof leads to under-designing or over-designing cases if the harmonic content has been underestimated or overestimated respectively. In hindsight, it may be beneficial for the Independent Power Producers and transformer manufactures to collaborate to assure the transformer design philosophy for the intended RE application is aligned with the technical requirements. In this paper, a method of de-rating the transformer when supplying non-sinusoidal loads is presented. In this method, the continuous power rating of the transformer is reduced to treat the additional losses as a result of harmonic penetration. Initially, a harmonic spectrum supplied by the IPP is used to calculate the transformer load and service losses. Secondly, the harmonic load spectrum is employed to compute derating factors ascribed to as “K-Factor” and “Factor-K”, indicating the amount of de-rating necessary for the transformer under study when serving the considered harmonic spectrum. Lastly, the thermal considerations under the harmonic spectrum are presented.Item Investigating the nanomechanical properties of polymer-graphene-titanium nitride nanocomposites for high strength application.(Elsevier B.V., 2023-09-01) Uyor, Uwa O.; Popoola, Abimbola Patricia I.; Popoola, Olawale M.In this work, hybrid graphene nanoplatelets (GN) and titanium nitride (TiN) were used as reinforcements to enhance nanomechanical properties of ultra-high molecular weight polyethylene (PE). The ternary nanocomposites were prepared by solvent mixing and melt-compounding processes. The nanomechanical properties of the developed nanocomposites was determined using nanoindenter. It was observed that PE-GN binaryn nanocomposites enhanced the nanomechanical properties, however, this was significantly pronounced with PEGN- TiN ternary nanocomposites. For instance, the hardness and elastic modulus increased from 171 MPa and 2.5 GPa for the pure PE to 282 MPa and 3.2 GPa for PE-2 wt %GN nanocomposite, which are about 65% and 28% increments at applied load of 100 mN respectively. While PE-2 wt%GN-20 wt% TiN ternary nanocomposite revealed hardness and elastic modulus increments of about 196% and 100% compared to the pure PE and 80% and 56% compared to PE-2 wt% GN binary nanocomposite. The enhanced nanomechanical properties is attributed to the uniform distribution and interlocking of the PE molecular chains by the presence of the hybrid GNTiN nanoparticles in the polymer matrix. The enhanced hardness, elastic modulus and other mechanical properties in this study are essential for advanced engineering applications where high mechanical features are required.Item Pseudocapacitive material for energy storage application: PEDOT and PEDOT:PSS(AIP Publishing., 2020-11-26) Adekoya, Gbolahan Joseph; Sadiku, Rotimi Emmanuel; Hamam, Yskandar; Ray, Suprakas Sinha; Mwakikunga, Bonex Wakufwa; Folorunso, Oladipo; Adekoya, Oluwasegun Chijoke; Lolu, Olajide Jimmy; Biotidara, Olusesan FrankThe total volume of solar energy reaching the earth in every second is equivalent to the total energy usage by the entire human race for three days. With this vast amount of clean energy freely available to humanity, there is still heavy dependence on fossil resources for energy. The major challenge with the use of fossil-based fuel is the generation of both land and atmospheric pollutants, which adversely affect the ecosystem. However, an essential requirement in transitioning from fossil energy to clean energy is the use of effective energy storage systems. Poly(3,4-ethylenedioxythiophene) (PEDOT) and poly (4-styrene sulfonate) (PSS) PEDOT:PSS is currently one of the highly researched semi-conducting polymers that form the vast and expanding literature on energy application. Owing to its high electrical conductivity, thermal stability, and film-forming ability, PEDOT and its derivatives are employed for pseudocapacitive storage applications. This review will present a detailed discussion on the synthesis, properties, and application of PEDOT:PSS for battery and ultracapacitors. Highlights on the recent development and outlook in the use of PEDOT and its derivatives for energy application will also be provided.Item Comparative study of graphene-polypyrrole and borophene-polypyrrole composites: molecular dynamics modeling approach(Growing Science Ltd., 2021-01-19) Folorunso, Oladipo; Hamam, Yskandar; Sadiku, Rotimi; Ray, Suprakas Sinha; Adekoya, Gbolahan JosephIn the search for the solution to energy storage problems, this study investigates the interfacial energy interaction and temperature stability of the composites made of polypyrrole-graphene-borophene (PPy-Gr-Bon) by using molecular dynamics simulations. From the calculated thermodynamics and interfacial energies of the system, comparisons between the ternary and the binary-binary systems were made. The materials in the entity show a good degree of temperature stability to a dynamic process at 300, 350, 400, and 450 K. Moreso, at 300 K, the interaction energy of PPy-Gr, PPy-Bon, and PPy-Gr-Bon are: -5.621e3 kcal/mol, -26.094e3 kcal/mol, and -28.206e3 kcal/mol respectively. The temperature stability of the systems is in the order of: PPy-Gr-Bon > PPy-Bon > PPy-Gr. The effect of temperature on the interaction energy of the systems was also investigated. The ternary system showed higher stability as the temperature increased. In addition, the radial distribution function computed for the three systems revealed that there is a strong, but non-chemical bonding interaction between PPy-Gr-Bon, Bon-PPy, and Gr-PPy. By considering the excellent mechanical properties of PPy-Gr-Bon and the already established high electrical conductivity and chemical stability of Gr, Bon and PPy, their composite is therefore suggested to be considered for the manufacturing of electrochemical electrodes.