Search results for: lattice architectures

Authors: Syed A. Bukhari, Ankur Goswmai, Dale Hume, Thomas Thundat

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Here we demonstrate mechanical detection of photo-induced Insulator to metal transition (MIT) in ultra-thin vanadium dioxide (VO₂) micro strings by using < 100 µW of optical power. Highly focused laser beam heated the string locally resulting in through plane and along axial heat diffusion. Localized temperature increase can cause temperature rise > 60 ºC. The heated region of VO₂ can transform from insulating (monoclinic) to conducting (rutile) phase leading to lattice compressions and stiffness increase in the resonator. The mechanical frequency of the resonator can be tuned by changing optical power and wavelength. The first mode resonance frequency was tuned in three different ways. A decrease in frequency below a critical optical power, a large increase between 50-120 µW followed by a large decrease in frequency for optical powers greater than 120 µW. The dynamic mechanical response was studied as a function of incident optical power and gas pressure. The resonance frequency and amplitude of vibration were found to be decreased with increasing laser power from 25-38 µW and increased by1-2 % when the laser power was further increased to 52 µW. The transition in films was induced and detected by a single pump and probe source and by employing external optical sources of different wavelengths. This trend in dynamic parameters of the strings can be co-related with reversible Insulator to metal transition in VO₂ films which creates change in density of the material and hence the overall stiffness of the strings leading to changes in string dynamics. The increase in frequency at a particular optical power manifests a transition to a more ordered metallic phase which tensile stress onto the string. The decrease in frequency at higher optical powers can be correlated with poor phonon thermal conductivity of VO₂ in conducting phase. Poor thermal conductivity of VO₂ can force in-plane penetration of heat causing the underneath SiN supporting VO₂ which can result as a decrease in resonance frequency. This noninvasive, non-contact laser-based excitation and detection of Insulator to metal transition using micro strings resonators at room temperature and with laser power in few µWs is important for low power electronics, and optical switching applications.

Keywords: thermal conductivity, vanadium dioxide, MEMS, frequency tuning

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Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

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Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

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Authors: Jiuyao Jiang, Jiahao Liu, Jichao Li, Kewei Yang, Minghao Li, Bingfeng Ge

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Modern warfare has transitioned from the paradigm of isolated combat forces to system-to-system confrontations due to advancements in combat technologies and application concepts. A combat system-of-systems (CSoS) is a combat network composed of independently operating entities that interact with one another to provide overall operational capabilities. Enhancing the resilience of CSoS is garnering increasing attention due to its significant practical value in optimizing network architectures, improving network security and refining operational planning. Accordingly, a unified framework called CSoS space-time resilience enhancement (CSoS-STRE) has been proposed, which enhances the resilience of CSoS by incorporating spatial features. Firstly, a multilayer spatial combat network model has been constructed, which incorporates an information layer depicting the interrelations among combat entities based on the OODA loop, along with a spatial layer that considers the spatial characteristics of equipment entities, thereby accurately reflecting the actual combat process. Secondly, building upon the combat network model, a spatiotemporal resilience optimization model is proposed, which reformulates the resilience optimization problem as a classical linear optimization model with spatial features. Furthermore, the model is extended from scenarios without obstacles to those with obstacles, thereby further emphasizing the importance of spatial characteristics. Thirdly, a resilience-oriented recovery optimization method based on improved non dominated sorting genetic algorithm II (R-INSGA) is proposed to determine the optimal recovery sequence for the damaged entities. This method not only considers spatial features but also provides the optimal travel path for multiple recovery teams. Finally, the feasibility, effectiveness, and superiority of the CSoS-STRE are demonstrated through a case study. Simultaneously, under deliberate attack conditions based on degree centrality and maximum operational loop performance, the proposed CSoS-STRE method is compared with six baseline recovery strategies, which are based on performance, time, degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. The comparison demonstrates that CSoS-STRE achieves faster convergence and superior performance.

Keywords: space-time resilience enhancement, resilience optimization model, combat system-of-systems, recovery optimization method, no-obstacles and obstacles

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Authors: Xinghui Wu, Chun Yang

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Inertial microfluidics is a competitive fluidic method with applications in separation of particles, cells and bacteria. In contrast to traditional microfluidic devices with low Reynolds number, inertial microfluidics works in the intermediate Re number range which brings about several intriguing inertial effects on particle separation/focusing to meet the throughput requirement in the real-world. Geometric modifications to make channels become irregular shapes can leverage fluid inertia to create complex secondary flow for adjusting the particle equilibrium positions and thus enhance the separation resolution and throughput. Although inertial microfluidics has been extensively studied by experiments, our current understanding of its mechanisms is poor, making it extremely difficult to build rational-design guidelines for the particle focusing locations, especially for irregularly shaped microfluidic channels. Inertial particle microfluidics in irregularly shaped channels were investigated in our group. There are several fundamental issues that require us to address. One of them is about the balance between the inertial lift forces and the secondary drag forces. Also, it is critical to quantitatively describe the dependence of the life forces on particle-particle interactions in irregularly shaped channels, such as a rectangular one. To provide physical insights into the inertial microfluidics in channels of irregular shapes, in this work the immersed boundary-lattice Boltzmann method (IB-LBM) was introduced and validated to explore the transport characteristics and the underlying mechanisms of an inertial focusing single particle in a rectangular microchannel. The transport dynamics of a finitesized particle were investigated over wide ranges of Reynolds number (20 < Re < 500) and particle size. The results show that the inner equilibrium positions are more difficult to occur in the rectangular channel, which can be explained by the secondary flow caused by the presence of a finite-sized particle. Furthermore, force decoupling analysis was utilized to study the effect of each type of lift force on the inertia migration, and a theoretical model for the lateral lift force of a finite-sized particle in the rectangular channel was established. Such theoretical model can be used to provide theoretical guidance for the design and operation of inertial microfluidics.

Keywords: inertial microfluidics, particle focuse, life force, IB-LBM

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Authors: M. Ghali, M. Elnimr, G. F. Ali, A. M. Eissa, H. Talaat

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CuIn₃Se₅ material is indexed as ordered vacancy compounds having excellent matching properties with CuInGaSe (CIGS) solar absorber layer. For example, the valence band offset of CuIn₃Se₅ with CIGS is nearly 0.3 eV, and the lattice mismatch is less than 1%, besides the absence of discontinuity in their conduction bands. Thus, CuIn₃Se₅ can work as a passivation layer for repelling holes from CIGS/CdS interface and hence to reduce the interface carriers recombination and consequently enhancing the efficiency of CIGS/CdS solar cells. Theoretically, it was reported earlier that an improvement in the efficiency of p-CIGS-based solar cell with a thin ~100 nm of n-CuIn₃Se₅ layer is expected. Recently, a reported experiment demonstrated significant improvement in the efficiency of Molecular Beam Epitaxy (MBE) grown CIGS solar cells from 13.4 to 14.5% via inserting a thin layer of MBE-grown Cu(In,Ga)₃Se₅ layer at the CdS/CIGS interface. It should be mentioned that CuIn₃Se₅ material in either bulk or thin film form, are usually fabricated by high vacuum physical vapor deposition techniques (e.g., three-source co-evaporation, RF sputtering, flash evaporation, and molecular beam epitaxy). In addition, achieving photosensitive films of n-CuIn₃Se₅ material is important for new hybrid organic/inorganic structures, where inorganic photo-absorber layer, with n-type conductivity, can form n–p junction with organic p-type material (e.g., conductive polymers). A detailed study of the physical properties of CuIn₃Se₅ is still necessary for better understanding of device operation and further improvement of solar cells performance. Here, we report on the low-cost synthesis of CuIn₃Se₅ material in nano-scale size, with an average diameter ~10nm, using simple solution-based colloidal chemistry. In contrast to traditionally grown bulk tetragonal CuIn₃Se₅ crystals using high Vacuum-based technology, our colloidal CuIn₃Se₅ nanocrystals show cubic crystal structure with a shape of nanoparticles and band gap ~1.33 eV. Ink-coated thin films prepared from these nanocrystals colloids; display n-type character, 1.26 eV band gap and strong photo-responsive behavior with incident white light. This suggests the potential use of colloidal CuIn₃Se₅ as an active layer in all-solution-processed thin film solar cells.

Keywords: nanocrystals, CuInSe, thin film, optical properties

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

Procedia PDF Downloads 118

Authors: Flavien Marteau, Pedro Affonso Nóbrega, Pascal Biwole, Nicolas Autrusson, Iona De Bievre, Christian Beauger

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Effective water management is essential for the optimal performance of fuel cells. For this reason, many vehicle systems use a membrane humidifier, a passive device that humidifies the air before the cathode inlet. Although they offer good performance, humidifiers are voluminous, costly, and fragile, hence the desire to find an alternative. Direct water injection could be an option, although this method lacks maturity. It consists of injecting liquid water as a spray in the dry heated air coming out from the compressor. This work focuses on the evaluation of direct water injection and its performance compared to the membrane humidifier selected as a reference. Two architectures were experimentally tested to humidify an industrial 2 kW short stack made up of 20 cells of 150 cm² each. For the reference architecture, the inlet air is humidified with a commercial membrane humidifier. For the direct water injection architecture, a pneumatic nozzle was selected to generate a fine spray in the air flow with a Sauter mean diameter of about 20 μm. Initial performance was compared over the entire range of current based on polarisation curves. Then, the influence of various parameters impacting water management was studied, such as the temperature, the gas stoichiometry, and the water injection flow rate. The experimental results obtained confirm the possibility of humidifying the fuel cell using direct water injection. This study, however shows the limits of this humidification method, the mean cell voltage being significantly lower in some operating conditions with direct water injection than with the membrane humidifier. The voltage drop reaches 30 mV per cell (4 %) at 1 A/cm² (1,8 bara, 80 °C) and increases in more demanding humidification conditions. It is noteworthy that the heat of compression available is not enough to evaporate all the injected liquid water in the case of DWI, resulting in a mix of liquid and vapour water entering the fuel cell, whereas only vapour is present with the humidifier. Variation of the injection flow rate shows that part of the injected water is useless for humidification and seems to cross channels without reaching the membrane. The stack was successfully humidified thanks to direct water injection. Nevertheless, our work shows that its implementation requires substantial adaptations and may reduce the fuel cell stack performance when compared to conventional membrane humidifiers, but opportunities for optimisation have been identified.

Keywords: cathode humidification, direct water injection, membrane humidifier, proton exchange membrane fuel cell

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Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

Procedia PDF Downloads 219

Authors: Natarajan Ramasamy, Gurulingamurthy Haralur, Ramesh Nivarthu, Nikhil Kumar Singha

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Elastomers are polymeric materials with varied backbone architectures ranging from linear to dendrimeric structures and wide varieties of monomeric repeat units. These elastomers show strongly viscous and weakly elastic when it is not cross-linked. But when crosslinked, based on the extent the properties of these elastomers can range from highly flexible to highly stiff nature. Lightly cross-linked systems are well studied and reported. Understanding the nature of highly cross-linked rubber based upon chemical structure and architecture is critical for varieties of applications. One of the critical parameters is cross-link density. In the current work, we have studied the highly cross-linked state of linear, lightly branched to star-shaped branched elastomers and determined the cross-linked density by using different models. Change in hardness, shift in Tg, change in modulus and swelling behavior were measured experimentally as a function of the extent of curing. These properties were analyzed using varied models to determine cross-link density. We used hardness measurements to examine cure time. Hardness to the extent of curing relationship is determined. It is well known that micromechanical transitions like Tg and storage modulus are related to the extent of crosslinking. The Tg of the elastomer in different crosslinked state was determined by DMA, and based on plateau modulus the crosslink density is estimated by using Nielsen’s model. Usually for lightly crosslinked systems, based on equilibrium swelling ratio in solvent the cross link density is estimated by using Flory–Rhener model. When it comes to highly crosslinked system, Flory-Rhener model is not valid because of smaller chain length. So models based on the assumption of polymer as a Non-Gaussian chain like 1) Helmis–Heinrich–Straube (HHS) model, 2) Gloria M.gusler and Yoram Cohen Model, 3) Barbara D. Barr-Howell and Nikolaos A. Peppas model is used for estimating crosslink density. In this work, correction factors are determined to the existing models and based upon it structure-property relationship of highly crosslinked elastomers was studied.

Keywords: dynamic mechanical analysis, glass transition temperature, parts per hundred grams of rubber, crosslink density, number of networks per unit volume of elastomer

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Kenneth Harper

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The secure sharing of Electronic Health Records (EHRs) is a critical challenge in modern healthcare, demanding solutions to enhance interoperability, privacy, and data integrity. Traditional standards like Health Information Exchange (HIE) and HL7 have made significant strides in facilitating data exchange between healthcare entities. However, these approaches rely on centralized architectures that are often vulnerable to data breaches, lack sufficient privacy measures, and have scalability issues. This paper proposes a framework for secure, decentralized sharing of EHRs using blockchain technology, cryptographic tokens, and Non-Fungible Tokens (NFTs). The blockchain's immutable ledger, decentralized control, and inherent security mechanisms are leveraged to improve transparency, accountability, and auditability in healthcare data exchanges. Furthermore, we introduce the concept of tokenizing patient data through NFTs, creating unique digital identifiers for each record, which allows for granular data access controls and proof of data ownership. These NFTs can also be employed to grant access to authorized parties, establishing a secure and transparent data sharing model that empowers both healthcare providers and patients. The proposed approach addresses common privacy concerns by employing privacy-preserving techniques such as zero-knowledge proofs (ZKPs) and homomorphic encryption to ensure that sensitive patient information can be shared without exposing the actual content of the data. This ensures compliance with regulations like HIPAA and GDPR. Additionally, the integration of Fast Healthcare Interoperability Resources (FHIR) with blockchain technology allows for enhanced interoperability, enabling healthcare organizations to exchange data seamlessly and securely across various systems while maintaining data governance and regulatory compliance. Through real-world case studies and simulations, this paper demonstrates how blockchain-based EHR sharing can reduce operational costs, improve patient outcomes, and enhance the security and privacy of healthcare data. This decentralized framework holds great potential for revolutionizing healthcare information exchange, providing a transparent, scalable, and secure method for managing patient data in a highly regulated environment.

Keywords: blockchain, electronic health records (ehrs), fast healthcare interoperability resources (fhir), health information exchange (hie), hl7, interoperability, non-fungible tokens (nfts), privacy-preserving techniques, tokens, secure data sharing,

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Authors: Nurhafizah Md. Disa, Nurhayati Binti Abdullah, Muhammad Rabie Bin Omar

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This research intends to identify the existing knowledge gap because of the lack of substantial studies to fabricate and characterize bio-graphene created from Oil Palm Shell (OPS) through the means of pre-treatment and slow pyrolysis. By fabricating bio-graphene through OPS, a novel material can be found to procure and used for graphene-based research. The characterization of produced bio-graphene is intended to possess a unique hexagonal graphene pattern and graphene properties in comparison to other previously fabricated graphene. The OPS will be fabricated by pre-treatment of zinc chloride (ZnCl₂) and iron (III) chloride (FeCl3), which then induced the bio-graphene thermally by slow pyrolysis. The pyrolizer's final temperature and resident time will be set at 550 °C, 5/min, and 1 hour respectively. Finally, the charred product will be washed with hydrochloric acid (HCL) to remove metal residue. The obtained bio-graphene will undergo different analyses to investigate the physicochemical properties of the two-dimensional layer of carbon atoms with sp2 hybridization hexagonal lattice structure. The analysis that will be taking place is Raman Spectroscopy (RAMAN), UV-visible spectroscopy (UV-VIS), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), and X-Ray Diffraction (XRD). In retrospect, RAMAN is used to analyze three key peaks found in graphene, namely D, G, and 2D peaks, which will evaluate the quality of the bio-graphene structure and the number of layers generated. To compare and strengthen graphene layer resolves, UV-VIS may be used to establish similar results of graphene layer from last layer analysis and also characterize the types of graphene procured. A clear physical image of graphene can be obtained by analyzation of TEM in order to study structural quality and layers condition and SEM in order to study the surface quality and repeating porosity pattern. Lastly, establishing the crystallinity of the produced bio-graphene, simultaneously as an oxygen contamination factor and thus pristineness of the graphene can be done by XRD. In the conclusion of this paper, this study is able to obtain bio-graphene through OPS as a novel material in pre-treatment by chloride ZnCl₂ and FeCl3 and slow pyrolization to provide a characterization analysis related to bio-graphene that will be beneficial for future graphene-related applications. The characterization should yield similar findings to previous papers as to confirm graphene quality.

Keywords: oil palm shell, bio-graphene, pre-treatment, slow pyrolysis

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Authors: I. Valdez, J. Perdomo, M. Colindres, N. Castro

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Today, digital servo systems are extensively used in industrial manufacturing processes, robotic applications, vehicles and other areas. In such control systems, control action is provided by digital controllers with different compensation algorithms, which are designed to meet specific requirements for a given application. Due to the constant search for optimization in industrial processes, it is of interest to design digital controllers that offer ease of realization, improved computational efficiency, affordable return rates, and ease of tuning that ultimately improve the performance of the controlled actuators. There is a vast range of options of compensation algorithms that could be used, although in the industry, most controllers used are based on a PID structure. This research article compares different types of digital compensators implemented in a servo system for DC motor position control. PID compensation is evaluated on its two most common architectures: PID position form (1 DOF), and PID speed form (2 DOF). State feedback algorithms are also evaluated, testing two modern control theory techniques: discrete state observer for non-measurable variables tracking, and a linear quadratic method which allows a compromise between the theoretical optimal control and the realization that most closely matches it. The compared control systems’ performance is evaluated through simulations in the Simulink platform, in which it is attempted to model accurately each of the system’s hardware components. The criteria by which the control systems are compared are reference tracking and disturbance rejection. In this investigation, it is considered that the accurate tracking of the reference signal for a position control system is particularly important because of the frequency and the suddenness in which the control signal could change in position control applications, while disturbance rejection is considered essential because the torque applied to the motor shaft due to sudden load changes can be modeled as a disturbance that must be rejected, ensuring reference tracking. Results show that 2 DOF PID controllers exhibit high performance in terms of the benchmarks mentioned, as long as they are properly tuned. As for controllers based on state feedback, due to the nature and the advantage which state space provides for modelling MIMO, it is expected that such controllers evince ease of tuning for disturbance rejection, assuming that the designer of such controllers is experienced. An in-depth multi-dimensional analysis of preliminary research results indicate that state feedback control method is more satisfactory, but PID control method exhibits easier implementation in most control applications.

Keywords: control, DC motor, discrete PID, discrete state feedback

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Authors: Jayashree Das, V. V. Srinivasu , D. K. Mishra, A. Maity

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Owing to the important potential applications over decades, transition metal (TM: Mn, Fe, Ni, Cu, Cr, V etc.) doped ZnO-based diluted magnetic semiconductors (DMS) always attract research attention for more and newer investigations. One of the interesting aspects of these materials is to study and understand the magnetic property at room temperature properly, which is very crucial to select a material for any related application. In this regard, Electron spin resonance (ESR) study has been proven to be a powerful technique to investigate the spin dynamics of electrons inside the system, which are responsible for the magnetic behaviour of any system. ESR as well as the Raman and Photoluminescence spectroscopy studies are also helpful to study the defects present or created inside the system in the form of oxygen vacancy or cluster instrumental in determining the room temperature ferromagnetic property of transition metal doped ZnO system, which can be controlled through varying dopant concentration, appropriate synthesis technique and sintering of the samples. For our investigation, we synthesised Cu-doped ZnO nanocrystalline samples with composition Zn1-xCux ( 0.005< x < 0.05) by pyrophoric method and sintered at a low temperature of 650 0C. The microwave absorption is studied by the Electron Spin Resonance (ESR) of X-band (9.46 GHz) at room temperature. Systematic analysis of the obtained ESR spectra reveals that all the compositions of Cu-doped ZnO samples exhibit resonance signals of appreciable line widths and g value ~ 2.2, typical characteristic of ferromagnetism in the sample. Raman scattering and the photoluminescence study performed on the samples clearly indicated the presence of pronounced defect related peaks in the respective spectra. Cu doping in ZnO with varying concentration also observed to affect the optical band gap and the respective absorption edges in the UV-Vis spectra. FTIR spectroscopy reveals the Cu doping effect on the stretching bonds of ZnO. To probe into the structural and morphological changes incurred by Cu doping, we have performed XRD, SEM and EDX study, which confirms adequate Cu substitution without any significant impurity phase formation or lattice disorder. With proper explanation, we attempt to correlate the results observed for the structural optical and magnetic behaviour of the Cu-doped ZnO samples. We also claim that our result can be instrumental for appropriate applications of transition metal doped ZnO based DMS in the field of optoelectronics and Spintronics.

Keywords: diluted magnetic semiconductors, electron spin resonance, raman scattering, spintronics.

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Authors: Sara A. Ben Lashihar

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The heritage building information modelling (HBIM) of the historical masonry buildings has expanded lately to meet the urgent needs for conservation and structural analysis. The masonry structures are unique features for ancient building architectures worldwide that have special cultural, spiritual, and historical significance. However, there is a research gap regarding the reliability of the HBIM modeling process of these structures. The HBIM modeling process of the masonry structures faces significant challenges due to the inherent complexity and uniqueness of their structural systems. Most of these processes are based on tracing the point clouds and rarely follow documents, archival records, or direct observation. The results of these techniques are highly abstracted models where the accuracy does not exceed LOD 200. The masonry assemblages, especially curved elements such as arches, vaults, and domes, are generally modeled with standard BIM components or in-place models, and the brick textures are graphically input. Hence, future investigation is necessary to establish a methodology to generate automatically parametric masonry components. These components are developed algorithmically according to mathematical and geometric accuracy and the validity of the survey data. The main aim of this paper is to provide a comprehensive review of the state of the art of the existing researches and papers that have been conducted on the HBIM modeling of the masonry structural elements and the latest approaches to achieve parametric models that have both the visual fidelity and high geometric accuracy. The paper reviewed more than 800 articles, proceedings papers, and book chapters focused on "HBIM and Masonry" keywords from 2017 to 2021. The studies were downloaded from well-known, trusted bibliographic databases such as Web of Science, Scopus, Dimensions, and Lens. As a starting point, a scientometric analysis was carried out using VOSViewer software. This software extracts the main keywords in these studies to retrieve the relevant works. It also calculates the strength of the relationships between these keywords. Subsequently, an in-depth qualitative review followed the studies with the highest frequency of occurrence and the strongest links with the topic, according to the VOSViewer's results. The qualitative review focused on the latest approaches and the future suggestions proposed in these researches. The findings of this paper can serve as a valuable reference for researchers, and BIM specialists, to make more accurate and reliable HBIM models for historic masonry buildings.

Keywords: HBIM, masonry, structure, modeling, automatic, approach, parametric

Procedia PDF Downloads 165

Authors: M. Maleczek, Leszek Bogdan, Kazimierz Drabczyk, Agnieszka Iwan

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Crystalline silicon (Si) solar cells are the main product in the market among the various photovoltaic technologies concerning such advantages as: material richness, high carrier mobilities, broad spectral absorption range and established technology. However, photovoltaic technology on the stiff substrates are heavier, more fragile and less cost-effective than devices on the flexible substrates to be applied in special applications. The main goal of our work was to incorporate silicon solar cells into various fabric, without any change of the electrical and mechanical parameters of devices. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management. In our work, the polyamide or polyester fabrics were used as a flexible substrate in the created devices. Applied fabrics differ in tensile and tear strength. All investigated polyamide fabrics are resistant to weathering and UV, while polyester ones is resistant to ozone, water and ageing. The examined fabrics are tight at 100 cm water per 2 hours. In our work, commercial silicon solar cells with the size 156 × 156 mm were cut into nine parts (called single solar cells) by diamond saw and laser. Gap and edge after cutting of solar cells were checked by transmission electron microscope (TEM) to study morphology and quality of the prepared single solar cells. Modules with the size of 160 × 70 cm (containing about 80 single solar cells) were created and investigated by electrical and mechanical methods. Weight of constructed module is about 1.9 kg. Three types of solar cell architectures such as: -fabric/EVA/Si solar cell/EVA/film for lamination, -backsheet PET/EVA/Si solar cell/EVA/film for lamination, -fabric/EVA/Si solar cell/EVA/tempered glass, were investigated taking into consideration type of fabric and lamination process together with the size of solar cells. In investigated devices EVA, it is ethylene-vinyl acetate, while PET - polyethylene terephthalate. Depend on the lamination process and compatibility of textile with solar cell an efficiency of investigated flexible silicon solar cells was in the range of 9.44-16.64 %. Multi folding and unfolding of flexible module has no impact on its efficiency as was detected by Instron equipment. Power (P) of constructed solar module is 30 W, while voltage about 36 V. Finally, solar panel contains five modules with the polyamide fabric and tempered glass will be produced commercially for different applications (dual use).

Keywords: flexible devices, mechanical properties, silicon solar cells, textiles

Procedia PDF Downloads 173

Authors: Devi Eka Septiyani Arifin, Jrjeng Ruan

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As an approach to manipulate the performance of polymer thin film, epitaxy crystallization within polymer blends of poly(vinylidene fluoride) (PVDF) and its copolymer poly(vinylidene fluoride-trifluoroethylene) P(VDF-TrFE) was studied in this research, which involves the competition between phase separation and crystal growth of constitutive semicrystalline polymers. The unique piezoelectric feature of poly(vinylidene fluoride) crystalline phase is derived from the packing of molecular chains in all-trans conformation, which spatially arranges all the substituted fluorene atoms on one side of the molecular chain and hydrogen atoms on the other side. Therefore, the net dipole moment is induced across the lateral packing of molecular chains. Nevertheless, due to the mutual repulsion among fluorene atoms, this all-trans molecular conformation is not stable, and ready to change above curie temperature, where thermal energy is sufficient to cause segmental rotation. This research attempts to explore whether the epitaxial interactions between piezoelectric crystals and crystal lattice of hexamethylbenzene (HMB) crystalline platelet is able to stabilize this metastable all-trans molecular conformation or not. As an aromatic crystalline compound, the melt of HMB was surprisingly found able to dissolve the poly(vinylidene fluoride), resulting in homogeneous eutectic solution. Thus, after quenching this binary eutectic mixture to room temperature, subsequent heating or annealing processes were designed to explore the involve phase separation and crystallization behavior. The phase transition behaviors were observed in-situ by X-ray diffraction and differential scanning calorimetry (DSC). The molecular packing was observed via transmission electron microscope (TEM) and the principles of electron diffraction were brought to study the internal crystal structure epitaxially developed within thin films. Obtained results clearly indicated the occurrence of heteroepitaxy of PVDF/PVDF-TrFE on HMB crystalline platelet. Both the concentration of poly(vinylidene fluoride) and the mixing ratios of these two constitutive polymers have been adopted as the influential factors for studying the competition between the epitaxial crystallization of PVDF and P(VDF-TrFE) on HMB crystalline. Furthermore, the involved epitaxial relationship is to be deciphered and studied as a potential factor capable of guiding the wide spread of piezoelectric crystalline form.

Keywords: epitaxy, crystallization, crystalline platelet, thin film and mixing ratio

Procedia PDF Downloads 222

Authors: Y. Mateyshina, A.Ulihin, N.Uvarov

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Electrolytes with different type of charge carrier can find widely application in different using, e.g. sensors, electrochemical equipments, batteries and others. One of important components ensuring stable functioning of the equipment is electrolyte. Electrolyte has to be characterized by high conductivity, thermal stability, and wide electrochemical window. In addition to many advantageous characteristic for liquid electrolytes, the solid state electrolytes have good mechanical stability, wide working range of temperature range. Thus search of new system of solid electrolytes with high conductivity is an actual task of solid state chemistry. Families of alkali perchlorates and nitrates have been investigated by us earlier. In literature data about transport properties of alkali nitrites are absent. Nevertheless, alkali nitrites MeNO2 (Me= Li+, Na+, K+, Rb+ and Cs+), except for the lithium salt, have high-temperature phases with crystal structure of the NaCl-type. High-temperature phases of nitrites are orientationally disordered, i.e. non-spherical anions are reoriented over several equivalents directions in the crystal lattice. Pure lithium nitrite LiNO2 is characterized by ionic conductivity near 10-4 S/cm at 180°C and more stable as compared with lithium nitrate and can be used as a component for synthesis of composite electrolytes. In this work composite solid electrolytes in the binary system LiNO2 - A (A= MgO, -Al2O3, Fe2O3, CeO2, SnO2, SiO2) were synthesized and their structural, thermodynamic and electrical properties investigated. Alkali nitrite was obtained by exchange reaction from water solutions of barium nitrite and alkali sulfate. The synthesized salt was characterized by X-ray powder diffraction technique using D8 Advance X-Ray Diffractometer with Cu K radiation. Using thermal analysis, the temperatures of dehydration and thermal decomposition of salt were determined.. The conductivity was measured using a two electrode scheme in a forevacuum (6.7 Pa) with an HP 4284A (Precision LCR meter) in a frequency range 20 Hz < ν < 1 MHz. Solid composite electrolytes LiNO2 - A A (A= MgO, -Al2O3, Fe2O3, CeO2, SnO2, SiO2) have been synthesized by mixing of preliminary dehydrated components followed by sintering at 250°C. In the series of nitrite of alkaline metals Li+-Cs+, the conductivity varies not monotonically with increasing radius of cation. The minimum conductivity is observed for KNO2; however, with further increase in the radius of cation in the series, the conductivity tends to increase. The work was supported by the Russian Foundation for Basic research, grant #14-03-31442.

Keywords: conductivity, alkali nitrites, composite electrolytes, transport properties

Procedia PDF Downloads 319

Authors: Lana Damaj, Vincent Laur, Azar Maalouf, Alexis Chevalier

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Matched termination is an important part of the passive waveguide components. It is typically used at the end of a waveguide transmission line to prevent reflections and improve signal quality. Waveguide terminations (loads) are commonly used in microwave and RF applications. In traditional microwave architectures, usually, waveguide termination consists of a standard rectangular waveguide made by a lossy resistive material, and ended by shorting metallic plate. These types of terminations are used, to dissipate the energy as heat. However, these terminations may increase the size and the weight of the overall system. New alternative solution consists in developing terminations based on 3D-printing of materials. Designing such terminations is very challenging since it should meet the requirements imposed by the system. These requirements include many parameters such as the absorption, the power handling capability in addition to the cost, the size and the weight that have to be minimized. 3D-printing is a shaping process that enables the production of complex geometries. It allows to find best compromise between requirements. In this paper, a comparison study has been made between different existing and new shapes of waveguide terminations. Indeed, 3D printing of absorbers makes it possible to study not only standard shapes (wedge, pyramid, tongue) but also more complex topologies such as exponential ones. These shapes have been designed and simulated using CST MWS®. The loads have been printed using the carbon-filled PolyLactic Acid, conductive PLA from ProtoPasta. Since the terminations has been characterized in the X-band (from 8GHz to 12GHz), the rectangular waveguide standard WR-90 has been selected. The classical wedge shape has been used as a reference. First, all loads have been simulated with the same length and two parameters have been compared: the absorption level (level of |S11|) and the dissipated power density. This study shows that the concave exponential pyramidal shape has the better absorption level and the convex exponential pyramidal shape has the better dissipated power density level. These two loads have been printed in order to measure their properties. A good agreement between the simulated and measured reflection coefficient has been obtained. Furthermore, a study of material structuring based on the honeycomb hexagonal structure has been investigated in order to vary the effective properties. In the final paper, the detailed methodology and the simulated and measured results will be presented in order to show how 3D-printing can allow controlling mass, weight, absorption level and power behaviour.

Keywords: additive manufacturing, electromagnetic composite materials, microwave measurements, passive components, power handling capacity (PHC), 3D-printing

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Authors: Paolo Grasso, Sai Kalyan Yelike, Federico Benzi, Mathieu Le Cam

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The cabin air quality (CAQ) in commercial aircraft is of prime interest, especially in the context of the COVID-19 pandemic. Current Environmental Control Systems (ECS) rely on a prescribed fresh airflow per passenger to dilute contaminants. An adaptive ECS strategy is proposed, leveraging air sensing and filtration technologies to ensure a better CAQ. This paper investigates the CAQ level achieved in commercial aircraft’s cabin during various flight scenarios. The modeling and simulation analysis is performed in a Modelica-based environment describing the dynamic behavior of the system. The model includes the following three main systems: cabin, recirculation loop and air-conditioning pack. The cabin model evaluates the thermo-hygrometric conditions and the air quality in the cabin depending on the number of passengers and crew members, the outdoor conditions and the conditions of the air supplied to the cabin. The recirculation loop includes models of the recirculation fan, ordinary and novel filtration technology, mixing chamber and outflow valve. The air-conditioning pack includes models of heat exchangers and turbomachinery needed to condition the hot pressurized air bled from the engine, as well as selected contaminants originated from the outside or bled from the engine. Different ventilation control strategies are modeled and simulated. Currently, a limited understanding of contaminant concentrations in the cabin and the lack of standardized and systematic methods to collect and record data constitute a challenge in establishing a causal relationship between CAQ and passengers' comfort. As a result, contaminants are neither measured nor filtered during flight, and the current sub-optimal way to avoid their accumulation is their dilution with the fresh air flow. However, the use of a prescribed amount of fresh air comes with a cost, making the ECS the most energy-demanding non-propulsive system within an aircraft. In such a context, this study shows that an ECS based on a reduced and adaptive fresh air flow, and relying on air sensing and filtration technologies, provides promising results in terms of CAQ control. The comparative simulation results demonstrate that the proposed adaptive ECS brings substantial improvements to the CAQ in terms of both controlling the asymptotic values of the concentration of the contaminant and in mitigating hazardous scenarios, such as fume events. Original architectures allowing for adaptive control of the inlet air flow rate based on monitored CAQ will change the requirements for filtration systems and redefine the ECS operation.

Keywords: cabin air quality, commercial aircraft, environmental control system, ventilation

Procedia PDF Downloads 100

Authors: Veronique Jubera, Ka-Young Kim, U-Chan Chung, Amelie Veillere, Jean-Marc Heintz

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Emitting materials and all solid state lasers are widely used in the field of optical applications and materials science as a source of excitement, instrumental measurements, medical applications, metal shaping etc. Recently promising optical efficiencies were recorded on ceramics which result from a cheaper and faster ways to obtain crystallized materials. The choice and optimization of the sintering process is the key point to fabricate transparent ceramics. It includes a high control on the preparation of the powder with the choice of an adequate synthesis, a pre-heat-treatment, the reproducibility of the sintering cycle, the polishing and post-annealing of the ceramic. The densification is the main factor needed to reach a satisfying transparency, and many technologies are now available. The symmetry of the unit cell plays a crucial role in the diffusion rate of the material. Therefore, the cubic symmetry compounds having an isotropic refractive index is preferred. The cubic Y3NbO7 matrix is an interesting host which can accept a high concentration of rare earth doping element and it has been demonstrated that SPS is an efficient way to sinter this material. The optimization of diffusion losses requires a microstructure of fine ceramics, generally less than one hundred nanometers. In this case, grain growth is not an obstacle to transparency. The ceramics properties are then isotropic thereby to free-shaping step by orienting the ceramics as this is the case for the compounds of lower symmetry. After optimization of the synthesis route, several SPS parameters as heating rate, holding, dwell time and pressure were adjusted in order to increase the densification of the Eu3+ doped Y3NbO7 pellets. The luminescence data coupled with X-Ray diffraction analysis and electronic diffraction microscopy highlight the existence of several distorted environments of the doping element in the studied defective fluorite-type host lattice. Indeed, the fast and high crystallization rate obtained to put in evidence a lack of miscibility in the phase diagram, being the final composition of the pellet driven by the ratio between niobium and yttrium elements. By following the luminescence properties, we demonstrate a direct impact on the SPS process on this material.

Keywords: emission, niobate of rare earth, Spark plasma sintering, lack of miscibility

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Authors: Daniel Manaye Kabtamu, Anteneh Wodaje Bayeh

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With the development and utilization of new energy technology, people’s demand for large-scale energy storage system has become increasingly urgent. Vanadium redox flow battery (VRFB) is one of the most promising technologies for grid-scale energy storage applications because of numerous attractive features, such as long cycle life, high safety, and flexible design. However, the relatively low energy efficiency and high production cost of the VRFB still limit its practical implementations. It is of great attention to enhance its energy efficiency and reduce its cost. One of the main components of VRFB that can impressively impact the efficiency and final cost is the electrode materials, which provide the reactions sites for redox couples (V₂₊/V³⁺ and VO²⁺/VO₂⁺). Graphite felt (GF) is a typical carbon-based material commonly employed as electrode for VRFB due to low-cost, good chemical and mechanical stability. However, pristine GF exhibits insufficient wettability, low specific surface area, and poor kinetics reversibility, leading to low energy efficiency of the battery. Therefore, it is crucial to further modify the GF electrode to improve its electrochemical performance towards VRFB by employing active electrocatalysts, such as less expensive metal oxides. This study successfully fabricates low-cost plate-like bismuth vanadate (BiVO₄) material through a simple one-step hydrothermal route, employed as an electrocatalyst to adorn the GF for use as the negative electrode in VRFB. The experimental results show that BiVO₄-3h exhibits the optimal electrocatalytic activity and reversibility for the vanadium redox couples among all samples. The energy efficiency of the VRFB cell assembled with BiVO₄-decorated GF as the negative electrode is found to be 75.42% at 100 mA cm−2, which is about 10.24% more efficient than that of the cell assembled with heat-treated graphite felt (HT-GF) electrode. The possible reasons for the activity enhancement can be ascribed to the existence of oxygen vacancies in the BiVO₄ lattice structure and the relatively high surface area of BiVO₄, which provide more active sites for facilitating the vanadium redox reactions. Furthermore, the BiVO₄-GF electrode obstructs the competitive irreversible hydrogen evolution reaction on the negative side of the cell, and it also has better wettability. Impressively, BiVO₄-GF as the negative electrode shows good stability over 100 cycles. Thus, BiVO₄-GF is a promising negative electrode candidate for practical VRFB applications.

Keywords: BiVO₄ electrocatalyst, electrochemical energy storage, graphite felt, vanadium redox flow battery

Procedia PDF Downloads 1573

Authors: Suruchi Saini, Hitender Kumar Tyagi

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With the rapid progress of the nanotechnology industry, it is becoming increasingly important to have compact semiconductor devices to function and offer the best results at various technology nodes. While performing the scaling of the device, several short-channel effects occur. To minimize these scaling limitations, some device architectures have been developed in the semiconductor industry. FinFET is one of the most promising structures. Also, the double-gate 2D Fin field effect transistor has the benefit of suppressing short channel effects (SCE) and functioning well for less than 14 nm technology nodes. In the present research, the MuGFET simulation tool is used to analyze and explain the electrical behaviour of a double-gate 2D Fin field effect transistor. The drift-diffusion and Poisson equations are solved self-consistently. Various models, such as Fermi-Dirac distribution, bandgap narrowing, carrier scattering, and concentration-dependent mobility models, are used for device simulation. The transfer and output characteristics of the double-gate 2D Fin field effect transistor are determined at 10 nm technology node. The performance parameters are extracted in terms of threshold voltage, trans-conductance, leakage current and current on-off ratio. In this paper, the device performance is analyzed at different structure parameters. The utilization of the Id-Vg curve is a robust technique that holds significant importance in the modeling of transistors, circuit design, optimization of performance, and quality control in electronic devices and integrated circuits for comprehending field-effect transistors. The FinFET structure is optimized to increase the current on-off ratio and transconductance. Through this analysis, the impact of different channel widths, source and drain lengths on the Id-Vg and transconductance is examined. Device performance was affected by the difficulty of maintaining effective gate control over the channel at decreasing feature sizes. For every set of simulations, the device's features are simulated at two different drain voltages, 50 mV and 0.7 V. In low-power and precision applications, the off-state current is a significant factor to consider. Therefore, it is crucial to minimize the off-state current to maximize circuit performance and efficiency. The findings demonstrate that the performance of the current on-off ratio is maximum with the channel width of 3 nm for a gate length of 10 nm, but there is no significant effect of source and drain length on the current on-off ratio. The transconductance value plays a pivotal role in various electronic applications and should be considered carefully. In this research, it is also concluded that the transconductance value of 340 S/m is achieved with the fin width of 3 nm at a gate length of 10 nm and 2380 S/m for the source and drain extension length of 5 nm, respectively.

Keywords: current on-off ratio, FinFET, short-channel effects, transconductance

Procedia PDF Downloads 61

Authors: M. Khorshed Alam, H. Takaba

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The catalytic properties of metal usually change by intermixturing with another metal in polymer electrolyte fuel cells. Pt-Ru alloy is one of the much-talked used alloy to enhance the CO oxidation. In this work, we have investigated the CO coverage on the Pt2Ru3 nanoparticle with different atomic conformation of Pt and Ru using a combination of material informatics with computational chemistry. Density functional theory (DFT) calculations used to describe the adsorption strength of CO and H with different conformation of Pt Ru ratio in the Pt2Ru3 slab surface. Then through the Monte Carlo (MC) simulations we examined the segregation behaviour of Pt as a function of surface atom ratio, subsurface atom ratio, particle size of the Pt2Ru3 nanoparticle. We have constructed a regression equation so as to reproduce the results of DFT only from the structural descriptors. Descriptors were selected for the regression equation; xa-b indicates the number of bonds between targeted atom a and neighboring atom b in the same layer (a,b = Pt or Ru). Terms of xa-H2 and xa-CO represent the number of atoms a binding H2 and CO molecules, respectively. xa-S is the number of atom a on the surface. xa-b- is the number of bonds between atom a and neighboring atom b located outside the layer. The surface segregation in the alloying nanoparticles is influenced by their component elements, composition, crystal lattice, shape, size, nature of the adsorbents and its pressure, temperature etc. Simulations were performed on different size (2.0 nm, 3.0 nm) of nanoparticle that were mixing of Pt and Ru atoms in different conformation considering of temperature range 333K. In addition to the Pt2Ru3 alloy we also considered pure Pt and Ru nanoparticle to make comparison of surface coverage by adsorbates (H2, CO). Hence, we assumed the pure and Pt-Ru alloy nanoparticles have an fcc crystal structures as well as a cubo-octahedron shape, which is bounded by (111) and (100) facets. Simulations were performed up to 50 million MC steps. From the results of MC, in the presence of gases (H2, CO), the surfaces are occupied by the gas molecules. In the equilibrium structure the coverage of H and CO as a function of the nature of surface atoms. In the initial structure, the Pt/Ru ratios on the surfaces for different cluster sizes were in range of 0.50 - 0.95. MC simulation was employed when the partial pressure of H2 (PH2) and CO (PCO) were 70 kPa and 100-500 ppm, respectively. The Pt/Ru ratios decrease as the increase in the CO concentration, without little exception only for small nanoparticle. The adsorption strength of CO on the Ru site is higher than the Pt site that would be one of the reason for decreasing the Pt/Ru ratio on the surface. Therefore, our study identifies that controlling the nanoparticle size, composition, conformation of alloying atoms, concentration and chemical potential of adsorbates have impact on the steadiness of nanoparticle alloys which ultimately and also overall catalytic performance during the operations.

Keywords: anode catalysts, fuel cells, material informatics, Monte Carlo

Procedia PDF Downloads 192

Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

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Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

Procedia PDF Downloads 350

Authors: Debabrata Adhikari, Mikhail Matveev, Louise Brown, Andy Long, Jan Kočí

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A good understanding of mesoscale permeability of complex architectures in fibrous porous preforms is of particular interest in order to achieve efficient and cost-effective resin impregnation of liquid composite molding (LCM). Fabrics used in structural reinforcements are typically woven or stitched. However, 3D fabric reinforcement is of particular interest because of the versatility in the weaving pattern with the binder yarn and in-plain yarn arrangements to manufacture thick composite parts, overcome the limitation in delamination, improve toughness etc. To predict the permeability based on the available pore spaces between the inter yarn spaces, unit cell-based computational fluid dynamics models have been using the Stokes Darcy model. Typically, the preform consists of an arrangement of yarns with spacing in the order of mm, wherein each yarn consists of thousands of filaments with spacing in the order of μm. The fluid flow during infusion exchanges the mass between the intra and inter yarn channels, meaning there is no dead-end of flow between the mesopore in the inter yarn space and the micropore in the yarn. Several studies have employed the Brinkman equation to take into account the flow through dual-scale porosity reinforcement to estimate their permeability. Furthermore, to reduce the computational effort of dual scale flow, scale separation criteria based on the ratio between yarn permeability to the yarn spacing was also proposed to quantify the dual scale and negligible micro-scale flow regime for the prediction of mesoscale permeability. In the present work, the key parameter to identify the influence of intra yarn permeability on the mesoscale permeability has been investigated with the systematic study of weft and warp yarn spacing on the plane weave as well as the position of binder yarn and number of in-plane yarn layers on 3D weave fabric. The permeability tensor has been estimated using an OpenFOAM-based model for the various weave pattern with idealized geometry of yarn implemented using open-source software TexGen. Additionally, scale separation criterion has been established based on the various configuration of yarn permeability for the 3D fabric with both the isotropic and anisotropic yarn from Gebart’s model. It was observed that the variation of mesoscale permeability Kxx within 30% when the isotropic porous yarn is considered for a 3D fabric with binder yarn. Furthermore, the permeability model developed in this study will be used for multi-objective optimizations of the preform mesoscale geometry in terms of yarn spacing, binder pattern, and a number of layers with an aim to obtain improved permeability and reduced void content during the LCM process.

Keywords: permeability, 3D fabric, dual-scale flow, liquid composite molding

Procedia PDF Downloads 96

Authors: Nidhi Sharotri, Dhiraj Sud

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Water pollution by pesticides constitutes a serious ecological problem due to their potential toxicity and bioaccumulation. The widespread use of pesticides in industry and agriculture along with their resistance to natural decomposition, biodegradation, chemical and photochemical degradation under typical environmental conditions has resulted in the emergence of these chemicals and their transformed products in natural water. Among AOP’s, heterogeneous photocatalysis using TiO2 as photocatalyst appears as the most emerging destructive technology for mineralization of the pollutant in aquatic streams. Among the various semiconductors (TiO2, ZnO, CdS, FeTiO3, MnTiO3, SrTiO2 and SnO2), TiO2 has proven to be the most efficient photocatalyst for environmental applications due to its biological and chemical inertness, high photo reactivity, non-toxicity, and photo stability. Semiconductor photocatalysts are characterized by an electronic band structure in which valence band and conduction band are separated by a band gap, i.e. a region of forbidden energy. Semiconductor based photocatalysts produces e-/h+ pairs which have been employed for degradation of organic pollutants. The present paper focuses on modification of TiO2 photocatalyst in order to shift its absorption edge towards longer wavelength to make it active under natural light. Semiconductor TiO2 photocatalysts was prepared by doping with anion (N), cation (Mn) and double doped (Mn, N) using greener approach. Titanium isopropoxide is used as titania precursor and ethanedithiol, hydroxyl amine hydrochloride, manganous chloride as sulphur, nitrogen and manganese precursors respectively. Synthesized doped TiO2 nanomaterials are characterized for surface morphology (SEM, TEM), crystallinity (XRD) and optical properties (absorption spectra and band gap). EPR data confirms the substitutional incorporation of Mn2+ in TiO2 lattice. The doping influences the phase transformation of rutile and anatase phase crystal and thereby the absorption spectrum changes were observed. The effect of variation of reaction parameters such as solvent, reaction time and calcination temperature on the yield, surface morphology and optical properties was also investigated. The TEM studies show the particle size of nanomaterials varies from 10-50 nm. The calculated band gap of nanomaterials varies from 2.30-2.60 eV. The photocatalytic degradation of organic pollutant organophosphate pesticide (Quinalphos) has been investigated by studying the changes in UV absorption spectrum and the promising results were obtained under visible light. The complete mineralization of quinalphos has occurred as no intermediates were recorded after 8 hrs of degradation confirmed from the HPLC studies.

Keywords: quinalphos, doped-TiO2, mineralization, EPR

Procedia PDF Downloads 328

Authors: Michalina Aniola, Andrzej Katrusiak

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4,4-Bipyridine is an important compound often used in chemical practice and more recently frequently applied for designing new metal organic framework (MoFs). Here we present a systematic high-pressure study of its hydrobromide salt. 4,4-Bipyridine hydrobromide monohydrate, 44biPyHBrH₂O, at ambient-pressure is orthorhombic, space group P212121 (phase a). Its hydrostatic compression shows that it is stable to 1.32 GPa at least. However, the recrystallization above 0.55 GPa reveals a new hidden b-phase (monoclinic, P21/c). Moreover, when the 44biPyHBrH2O is heated to high temperature the chemical reactions of this compound in methanol solution can be observed. High-pressure experiments were performed using a Merrill-Bassett diamond-anvil cell (DAC), modified by mounting the anvils directly on the steel supports, and X-ray diffraction measurements were carried out on a KUMA and Excalibur diffractometer equipped with an EOS CCD detector. At elevated pressure, the crystal of 44biPyHBrH₂O exhibits several striking and unexpected features. No signs of instability of phase a were detected to 1.32 GPa, while phase b becomes stable at above 0.55 GPa, as evidenced by its recrystallizations. Phases a and b of 44biPyHBrH2O are partly isostructural: their unit-cell dimensions and the arrangement of ions and water molecules are similar. In phase b the HOH-Br- chains double the frequency of their zigzag motifs, compared to phase a, and the 44biPyH+ cations change their conformation. Like in all monosalts of 44biPy determined so far, in phase a the pyridine rings are twisted by about 30 degrees about bond C4-C4 and in phase b they assume energy-unfavorable planar conformation. Another unusual feature of 44biPyHBrH2O is that all unit-cell parameters become longer on the transition from phase a to phase b. Thus the volume drop on the transition to high-pressure phase b totally depends on the shear strain of the lattice. Higher temperature triggers chemical reactions of 44biPyHBrH2O with methanol. When the saturated methanol solution compound precipitated at 0.1 GPa and temperature of 423 K was required to dissolve all the sample, the subsequent slow recrystallization at isochoric conditions resulted in disalt 4,4-bipyridinium dibromide. For the 44biPyHBrH2O sample sealed in the DAC at 0.35 GPa, then dissolved at isochoric conditions at 473 K and recrystallized by slow controlled cooling, a reaction of N,N-dimethylation took place. It is characteristic that in both high-pressure reactions of 44biPyHBrH₂O the unsolvated disalt products were formed and that free base 44biPy and H₂O remained in the solution. The observed reactions indicate that high pressure destabilized ambient-pressure salts and favors new products. Further studies on pressure-induced reactions are carried out in order to better understand the structural preferences induced by pressure.

Keywords: conformation, high-pressure, negative area compressibility, polymorphism

Procedia PDF Downloads 246

Authors: Dyah Purwaningsih, Roto Roto, Hari Sutrisno

Abstract:

Manganese dioxide (MnO₂) and its derivatives are among the most widely used materials for the positive electrode in both primary and rechargeable lithium batteries. The MnO₂ derivative compound of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) is one of the leading candidates for positive electrode materials in lithium batteries as it is abundant, low cost and environmentally friendly. Over the years, synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) has been carried out using various methods including sol-gel, gas condensation, spray pyrolysis, and ceramics. Problems with these various methods persist including high cost (so commercially inapplicable) and must be done at high temperature (environmentally unfriendly). This research aims to: (1) synthesize LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) by reflux technique; (2) develop microstructure analysis method from XRD Powder LiMₓMn₂₋ₓO₄ data with the two-stage method; (3) study the electrical conductivity of LiMₓMn₂₋ₓO₄. This research developed the synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) with reflux. The materials consisting of Mn(CH₃COOH)₂. 4H₂O and Na₂S₂O₈ were refluxed for 10 hours at 120°C to form β-MnO₂. The doping of Co, Ni and Cr were carried out using solid-state method with LiOH to form LiMₓMn₂₋ₓO₄. The instruments used included XRD, SEM-EDX, XPS, TEM, SAA, TG/DTA, FTIR, LCR meter and eight-channel battery analyzer. Microstructure analysis of LiMₓMn₂₋ₓO₄ was carried out on XRD powder data by two-stage method using FullProf program integrated into WinPlotR and Oscail Program as well as on binding energy data from XPS. The morphology of LiMₓMn₂₋ₓO₄ was studied with SEM-EDX, TEM, and SAA. The thermal stability test was performed with TG/DTA, the electrical conductivity was studied from the LCR meter data. The specific capacity of LiMₓMn₂₋ₓO₄ as lithium battery cathode was tested using an eight-channel battery analyzer. The results showed that the synthesis of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) was successfully carried out by reflux. The optimal temperature of calcination is 750°C. XRD characterization shows that LiMn₂O₄ has a cubic crystal structure with Fd3m space group. By using the CheckCell in the WinPlotr, the increase of Li/Mn mole ratio does not result in changes in the LiMn₂O₄ crystal structure. The doping of Co, Ni and Cr on LiMₓMn₂₋ₓO₄ (x = 0.02; 0.04; 0; 0.6; 0.08; 0.10) does not change the cubic crystal structure of Fd3m. All the formed crystals are polycrystals with the size of 100-450 nm. Characterization of LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) microstructure by two-stage method shows the shrinkage of lattice parameter and cell volume. Based on its range of capacitance, the conductivity obtained at LiMₓMn₂₋ₓO₄ (M: Co, Ni, Cr) is an ionic conductivity with varying capacitance. The specific battery capacity at a voltage of 4799.7 mV for LiMn₂O₄; Li₁.₀₈Mn₁.₉₂O₄; LiCo₀.₁Mn₁.₉O₄; LiNi₀.₁Mn₁.₉O₄ and LiCr₀.₁Mn₁.₉O₄ are 88.62 mAh/g; 2.73 mAh/g; 89.39 mAh/g; 85.15 mAh/g; and 1.48 mAh/g respectively.

Keywords: LiMₓMn₂₋ₓO₄, solid-state, reflux, two-stage method, ionic conductivity, specific capacity

Procedia PDF Downloads 193

Authors: Efrain Rodriguez, Cristhian Riano, Alberto Alvares

Abstract:

In recent years, robots manipulators with parallel architectures are used in additive manufacturing processes – 3D printing. These robots have advantages such as speed and lightness that make them suitable to help with the efficiency and productivity of these processes. Consequently, the interest for the development of parallel robots for additive manufacturing applications has increased. This article deals with the conceptual design and dimensional synthesis of the linear delta robot for additive manufacturing. Firstly, a methodology based on structured processes for the development of products through the phases of informational design, conceptual design and detailed design is adopted: a) In the informational design phase the Mudge diagram and the QFD matrix are used to aid a set of technical requirements, to define the form, functions and features of the robot. b) In the conceptual design phase, the functional modeling of the system through of an IDEF0 diagram is performed, and the solution principles for the requirements are formulated using a morphological matrix. This phase includes the description of the mechanical, electro-electronic and computational subsystems that constitute the general architecture of the robot. c) In the detailed design phase, a digital model of the robot is drawn on CAD software. A list of commercial and manufactured parts is detailed. Tolerances and adjustments are defined for some parts of the robot structure. The necessary manufacturing processes and tools are also listed, including: milling, turning and 3D printing. Secondly, a dimensional synthesis method applied on design of the linear delta robot is presented. One of the most important key factors in the design of a parallel robot is the useful workspace, which strongly depends on the joint space, the dimensions of the mechanism bodies and the possible interferences between these bodies. The objective function is based on the verification of the kinematic model for a prescribed cylindrical workspace, considering geometric constraints that possibly lead to singularities of the mechanism. The aim is to determine the minimum dimensional parameters of the mechanism bodies for the proposed workspace. A method based on genetic algorithms was used to solve this problem. The method uses a cloud of points with the cylindrical shape of the workspace and checks the kinematic model for each of the points within the cloud. The evolution of the population (point cloud) provides the optimal parameters for the design of the delta robot. The development process of the linear delta robot with optimal dimensions for additive manufacture is presented. The dimensional synthesis enabled to design the mechanism of the delta robot in function of the prescribed workspace. Finally, the implementation of the robotic platform developed based on a linear delta robot in an additive manufacturing application using the Fused Deposition Modeling (FDM) technique is presented.

Keywords: additive manufacturing, delta parallel robot, dimensional synthesis, genetic algorithms

Procedia PDF Downloads 190