Search results for: single step anodization

Authors: G. Ravindranath, S. Savitha

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This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

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Authors: Tamer Shehata

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Recently, nanotechnology acquired a great interest in the field of pharmaceutical production. Several pharmaceutical equipment were introduced into the research field for production of nanoparticles, among them, BÜCHI’ fourth generation nano-spray dryer B-90. B-90 is specialized with single step of production and drying of nano and microparticles. Currently, our research group is investigating several pharmaceutical formulations utilizing BÜCHI Nano-Spray Dryer B-90 technology. One of our projects is the formulation and evaluation of metformin hydrochloride mucoadhesive microparticles for treatment of type 2-diabetis. Several polymers were investigated, among them, gelatin and sodium alginate. The previous polymers are natural polymers with mucoadhesive properties. Preformulation studies such as atomization head mesh size, flow rate, head temperature, polymer solution viscosity and surface tension were performed. Postformulation characters such as particle size, flowability, surface scan and dissolution profile were evaluated. Finally, the pharmacological activity of certain selected formula was evaluated in streptozotocin-induced diabetic rats. B-90’spray head was 7 µm hole heated to 120 with air flow rate 3.5 mL/min. The viscosity of the solution was less than 11.5 cP with surface tension less than 70.1 dyne/cm. Successfully, discrete, non-aggregated particles and free flowing powders with particle size was less than 2000 nm were obtained. Gelatin and Sodium alginate combination in ratio 1:3 were successfully sustained the in vitro release profile of the drug. Hypoglycemic evaluation of the previous formula showed a significant reduction of blood glucose level over 24 h. In conclusion, mucoadhesive metformin hydrochloride microparticles obtained from B-90 could offer a convenient dosage form with enhanced hypoglycemic activity.

Keywords: mucoadhesive, microparticles, metformin hydrochloride, nano-spray dryer

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Authors: Mateus Silva Mendonça, Wender Pereira de Oliveira, Gabriel Heleno de Paula Araújo, Hiago Tenório Teixeira Santana Rocha, Augusto César Teixeira Malaquias, José Guilherme Coelho Baeta

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The stricter legislation and the greater demand of the population regard to gas emissions and their effects on the environment as well as on human health make the automotive industry reinforce research focused on reducing levels of contamination. This reduction can be achieved through the implementation of improvements in internal combustion engines in such a way that they promote the reduction of both specific fuel consumption and air pollutant emissions. These improvements can be obtained through numerical simulation, which is a technique that works together with experimental tests. The aim of this paper is to build, with support of the GT-Suite software, a one-dimensional model of a single-cylinder research engine to analyze the impact of the variation of swirl and tumble coefficients on the performance and on the air pollutant emissions of an engine. Initially, the discharge coefficient is calculated through the software Converge CFD 3D, given that it is an input parameter in GT-Power. Mesh sensitivity tests are made in 3D geometry built for this purpose, using the mass flow rate in the valve as a reference. In the one-dimensional simulation is adopted the non-predictive combustion model called Three Pressure Analysis (TPA) is, and then data such as mass trapped in cylinder, heat release rate, and accumulated released energy are calculated, aiming that the validation can be performed by comparing these data with those obtained experimentally. Finally, the swirl and tumble coefficients are introduced in their corresponding objects so that their influences can be observed when compared to the results obtained previously.

Keywords: 1D simulation, single-cylinder research engine, swirl coefficient, three pressure analysis, tumble coefficient

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Authors: Nahum Yustus Godi

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A three-dimensional numerical optimisation of combined microchannels with constructal solid, half hollow, and hollow circular fins is documented in this paper. The technique seeks to minimize peak temperature in the entire volume of the microchannel heat sink. The volume and axial length were all fixed, while the width of the microchannel could morph. High-density heat flux was applied at the bottom wall of the microchannel. The coolant employed to remove the heat deposited at the bottom surface of the microchannel was a single-phase fluid (water) in a forced convection laminar condition, and heat transfer was a conjugate problem. The unit cell symmetrical computation domain was discretised, and governing equations were solved using computational fluid dynamic (CFD) code. The results reveal that the combined microchannel with hollow circular fins and solid fins performed better at different Reynolds numbers. The numerical study was validated for the single microchannel without fins and found to be in good agreement with previous studies.

Keywords: constructal fins, complex heat exchangers, cooling technique, numerical optimisation

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Authors: B. Makhlouf, O. Bouchhida, M. Nibouche, K. Laidi

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A variety of methods for selective harmonics elimination pulse width modulation have been developed, the most frequently used for real-time implementation based on look-up tables method. To address real-time requirements based in modified carrier signal is proposed in the presented work, with a general formulation to real-time harmonics control/elimination in switched inverters. Firstly, the proposed method has been demonstrated for a single value of the modulation index. However, in reality, this parameter is variable as a consequence of the voltage (amplitude) variability. In this context, a simple interpolation method for calculating the modified sine carrier signal is proposed. The method allows a continuous adjustment in both amplitude and frequency of the fundamental. To assess the performance of the proposed method, software simulations and hardware experiments have been carried out in the case of a single-phase inverter. Obtained results are very satisfactory.

Keywords: harmonic elimination, Particle Swarm Optimisation (PSO), polynomial interpolation, pulse width modulation, real-time harmonics control, voltage inverter

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Authors: Maryam Beiranvand

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Multi-drug resistance in various microorganisms has increased globally in many healthcare facilities. Less effective antimicrobial activity of drug therapies for infection control becomes trouble. Since 1980, no new type of antimicrobial drug has been identified, even though combinations of antibiotic drugs have been discovered almost every decade. Between 1981 and 2006, over 70% of novel pharmaceuticals and chemical agents came from natural sources. Microorganisms have yielded almost 22,000 natural compounds. The identification of antimicrobial components from endophytes bacteria could help overcome the threat posed by multi-drug resistant strains. The project aims to analyze and identify antimicrobial peptides isolated from entophytic bacteria and their activity against multidrug-resistant Gram-negative bacteria in South Korea. Endophytic Paenibacillus polymyxa. 4G3 isolated from the plant, Gynura procumbery exhibited considerable antimicrobial activity against Methicillin-resistant Staphylococcus aureus, and Escherichia coli. The Rapid Annotations using Subsystems Technology showed that the total size of the draft genome was 5,739,603bp, containing 5178 genes with 45.8% G+C content. Genome annotation using antiSMASH version 6.0.0 was performed, which predicted the most common types of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS). In this study, diethyl aminoethyl cellulose (DEAEC) resin was used as the first step in purifying for unknown peptides, and then the target protein was identified using hydrophilic and hydrophobic solutions, optimal pH, and step-by-step tests for antimicrobial activity. This crude was subjected to C18 chromatography and elution with 0, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% methanol, respectively. Only the fraction eluted with 20% -60% methanol demonstrated good antimicrobial activity against MDR E. coli. The concentration of the active fragment was measured by the Brad-ford test, and Protein A280 - Thermo Fisher Scientific at the end by examining the SDS PAGE Resolving Gel, 10% Acrylamide and purity were confirmed. Our study showed that, based on the combined results of the analysis and purification. P polymyxa. 4G3 has a high potential exists for producing novel functions of polymyxin E and bacitracin against bacterial pathogens.

Keywords: endophytic bacteria, antimicrobial activity, antimicrobial peptide, whole genome sequencing analysis, multi -drug resistance gram negative bacteria

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Authors: Anjana R. Menon, Anjana Bhasi

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Development of highways and railways play crucial role in a nation’s economic growth. While rigid concrete pavements are durable with high load bearing characteristics, growing economies mostly rely on flexible pavements which are easier in construction and more economical. The strength of flexible pavement is based on the strength of subgrade and load distribution characteristics of intermediate granular layers. In this scenario, to simultaneously meet economy and strength criteria, it is imperative to strengthen and stabilize the load transferring layers, namely subbase and base. Geosynthetic reinforcement in planar and cellular forms have been proven effective in improving soil stiffness and providing a stable load transfer platform. Studies have proven the relative superiority of cellular form-geocells over planar geosynthetic forms like geogrid, owing to the additional confinement of infill material and pocket effect arising from vertical deformation. Hence, the present study investigates the efficiency of geocells over single/multiple layer geogrid reinforcements by a series of three-dimensional model analyses of a flexible pavement section under a standard repetitive wheel load. The stress transfer mechanism and deformation profiles under various reinforcement configurations are also studied. Geocell reinforcement is observed to take up a higher proportion of stress caused by the traffic loads compared to single and double-layer geogrid reinforcements. The efficiency of single geogrid reinforcement reduces with an increase in embedment depth. The contribution of lower geogrid is insignificant in the case of the double-geogrid reinforced system.

Keywords: Geocell, Geogrid, Flexible Pavement, Repetitive Wheel Load, Numerical Analysis

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Authors: Nader Khalafian, Mohsen Ghaderi

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Field observations have revealed many examples of structures which were damaged due to ground surface deformation caused by the faulting phenomena. In this paper some efforts were made in order to estimate the length and location of the ground surface where large displacements were created due to the reverse faulting. This research has conducted in two steps; (1) in the first step, a 2D explicit finite element model were developed using ABAQUS software. A subroutine for Mohr-Coulomb failure criterion with strain softening model was developed by the authors in order to properly model the stress strain behavior of the soil in the fault rapture zone. The results of the numerical analysis were verified with the results of available centrifuge experiments. Reasonable coincidence was found between the numerical and experimental data. (2) In the second step, the effects of the fault dip angle (δ), depth of soil layer (H), dilation and friction angle of sand (ψ and φ) and the amount of fault offset (d) on the soil surface displacement and fault rupture path were investigated. An artificial neural network-based model (ANN), as a powerful prediction tool, was developed to generate a general model for predicting faulting characteristics. A properly sized database was created to train and test network. It was found that the length and location of the zone of displaced ground surface can be accurately estimated using the proposed model.

Keywords: reverse faulting, surface deformation, numerical, neural network

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Authors: Lukasz Szydlowski, Jiri Ehlich, Igor Goryanin

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We demonstrate a single chamber, 96-well-plated based Microbial Fuel Cell (MFC) with printed, electronic components. This invention is aimed at robust selection of electrogenic microbial community under specific conditions, e.g., electrode potential, pH, nutrient concentration, salt concentration that can be altered within the 96 well plate array. This invention enables robust selection of electrogenic microbial community under the homogeneous reactor, with multiple conditions that can be altered to allow comparative analysis. It can be used as a standalone technique or in conjunction with other selective processes, e.g., flow cytometry, microfluidic-based dielectrophoretic trapping. Mobile conductive elements, like carbon paper, carbon sponge, activated charcoal granules, metal mesh, can be inserted inside to increase the anode surface area in order to collect electrogenic microorganisms and to transfer them into new reactors or for other analytical works. An array of 96-well plate allows this device to be operated by automated pipetting stations.

Keywords: bioengineering, electrochemistry, electromicrobiology, microbial fuel cell

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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Authors: Vitaly Haslavsky, Helena Vitoshkin

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The total energy saving effect of different types of greenhouse thermal/shade screens was determined by measuring and calculating the overall heat transfer coefficients (U-values) for single and several layers of screens. The measurements were carried out using the hot box method, and the calculations were performed according to the ISO Standard 15099. The goal was to examine different types of materials with a wide range of thermal radiation properties used for thermal screens in combination with a dehumidification system in order to improve greenhouse insulation. The experimental results were in good agreement with the calculated heat transfer coefficients. It was shown that a high amount of infra-red (IR) radiation can be blocked by the greenhouse covering material in combination with moveable thermal screens. The aluminum foil screen could be replaced by transparent screens, depending on shading requirements. The results indicated that using a single layer, the U-value was reduced by approximately 70% compared to covering material alone, while the contributions of additional screen layers containing aluminum foil strips could reduce the U-value by approximately 90%. It was shown that three screen layers are sufficient for effective insulation.

Keywords: greenhouse insulation, heat loss, thermal screens, U-value

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Authors: Paula Quiterio, Arlete Apolinario, Celia T. Sousa, Joao Azevedo, Paula Dias, Adelio Mendes, Joao P. Araujo

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Nowadays one of the mankind's greatest challenges has been the supply of low-cost and environmentally friendly energy sources as an alternative to non-renewable fossil fuels. Hydrogen has been considered a promising solution, representing a clean and low-cost fuel. It can be produced directly from clean and abundant resources, such as sunlight and water, using photoelectrochemical cells (PECs), in a process that mimics the nature´s photosynthesis. Hematite (alpha-Fe2O3) has attracted considerable attention as a promising photoanode for solar water splitting, due to its high chemical stability, nontoxicity, availability and low band gap (2.2 eV), which allows reaching a high thermodynamic solar-to-hydrogen efficiency of 16.8 %. However, the main drawbacks of hematite such as the short hole diffusion length and the poor conductivity that lead to high electron-hole recombination result in significant PEC efficiency losses. One strategy to overcome these limitations and to increase the PEC efficiency is to use 1D nanostructures, such as nanotubes (NTs) and nanowires (NWs), which present high aspect ratios and large surface areas providing direct pathways for electron transport up to the charge collector and minimizing the recombination losses. In particular, due to the ultrathin walls of the NTs, the holes can reach the surface faster than in other nanostructures, representing a key factor for the NTs photoresponse. In this work, we prepared hematite NWs and NTs, respectively by hydrothermal process and electrochemical anodization. For hematite NWs growing, we studied the effect of variable hydrothermal conditions, different annealing temperatures and time, and the use of Ti and Sn dopants on the morphology and PEC performance. The crystalline phase characterization by X-ray diffraction was crucial to distinguish the formation of hematite and other iron oxide phases, alongside its effect on the photoanodes conductivity and consequent PEC efficiency. The conductivity of the as-prepared NWs is very low, in the order of 10-5 S cm-1, but after doping and annealing optimization it increased by a factor of 105. A high photocurrent density of 1.02 mA cm-2 at 1.45 VRHE was obtained under simulated sunlight, which is a very promising value for this kind of hematite nanostructures. The stability of the photoelectrodes was also tested, presenting good stability after several J-V measurements over time. The NTs, synthesized by fast anodizations with potentials ranging from 20-100 V, presented a linear growth of the NTs pore walls, with very low thicknesses from 10 - 18 nm. These preliminary results are also very promising for the use of hematite photoelectrodes on PEC hydrogen applications.

Keywords: hematite, nanotubes, nanowires, photoelectrochemical cells

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Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli

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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.

Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: Nivedita Sharma

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The global demand for fossil fuels is very high, but their use is not sustainable since its reserves are declining. Additionally, fossil fuels are responsible for the accumulation of greenhouse gases. The emission of greenhouse gases from the transport sector can be reduced by substituting fossil fuels by biofuels. Thus, renewable fuels capable of sequestering carbon dioxide are in high demand. Second‐generation biofuels, which require lignocellulosic biomass as a substrate and ultimately producing ethanol, fall largely in this category. Bioethanol is a favorable and near carbon-neutral renewable biofuel leading to reduction in tailpipe pollutant emission and improving the ambient air quality. Lignocellulose consists of three main components: cellulose, hemicellulose and lignin which can be converted to ethanol with the help of microbial enzymes. Enzymatic hydrolysis of lignocellulosic biomass in 1st step is considered as the most efficient and least polluting methods for generating fermentable hexose and pentose sugars which subsequently are fermented to power alcohol by yeasts in 2nd step of the process. In the present technology, a complete bioconversion process i.e. potential hydrolytic enzymes i.e. cellulase and xylanase producing microorganisms have been isolated from different niches, screened for enzyme production, identified using phenotyping and genotyping, enzyme production, purification and application of enzymes for saccharification of different lignocellulosic biomass followed by fermentation of hydrolysate to ethanol with high yield is to be presented in detail.

Keywords: cellulase, xylanase, lignocellulose, bioethanol, microbial enzymes

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Authors: I. Filikhin, B. Vlahovic

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We focus on a novel type of detection based on electron tunneling properties of double nanoscale structures in semiconductor materials. Semiconductor heterostructures as quantum wells (QWs), quantum dots (QDs), and quantum rings (QRs) may have energy level structure of several hundred of electron confinement states. The single electron spectra of the double quantum objects (DQW, DQD, and DQR) were studied in our previous works with relation to the electron localization and tunneling between the objects. The wave function of electron may be localized in one of the QDs or be delocalized when it is spread over the whole system. The localizing-delocalizing tunneling occurs when an electron transition between both states is possible. The tunneling properties of spectra differ strongly for “regular” and “chaotic” systems. We have shown that a small violation of the geometry drastically affects localization of electron. In particular, such violations lead to the elimination of the delocalized states of the system. The same symmetry violation effect happens if electrical or magnetic fields are applied. These phenomena could be used to propose a new type of detection based on the high sensitivity of charge transport between double nanostructures and small violations of the shapes. It may have significant technological implications.

Keywords: double quantum dots, single electron levels, tunneling, electron localizations

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Authors: Arfan Ali, Muhammad Shahzad Iqbal, Idrees Ahmad Nasir

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Potato (Solanum tuberosum L.) is ranked among the top leading staple foods in the world. Salinity adversely affects potato crop yield and quality. Therefore, increased level of salt tolerance is a key factor to ensure high yield. The present study focused on the Agrobacterium-mediated transformation of Atriplex canescens betaine aldehyde dehydrogenase (BADH) gene, using single, double and triple CAMV35s promoter to improve salt tolerance in potato. Detection of seven potato lines harboring BADH gene, followed by identification of T-DNA insertions, determination of transgenes copies no through Southern Hybridization and quantification of BADH protein through Enzyme Linked Immunosorbent Assay were considered in this study. The results clearly depict that the salt tolerance of potato was found to be promoter-dependent, as the potato transgenic lines with triple promoter showed 4.4 times more glycine betaine production which consequently leads towards high resistance to salt stress as compared to transgenic potato lines with single and double promoters having least production of glycine betaine. Moreover, triple promoter transgenic potato lines have also shown lower levels of H2O2, malondialdehyde (MDA), relative electrical conductivity, high proline and chlorophyll content as compared other two lines having a single and double promoter. Insilco analysis also confirmed that Atriplex canescens BADH has the tendency to interact with sodium ions and water molecules. Taken together these facts it can be concluded that over-expression of BADH under triple CAMV35s promoter with more glycine betaine, chlorophyll & MDA contents, high relative quantities of other metabolites results in an enhanced level of salt tolerance in potato.

Keywords: Atriplex canescens, BADH, CAMV35s promotor, potato, Solanum tubersum

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Authors: B. Khorram, M. Taslikh, R. Sattarzadeh, M. Ghazanfari

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Bitterness is one of the most important problems in cheese processing industry all over the world. There are several reasons that bitterness may develop in cheese. With a few exceptions bitterness is generally associated with proteolysis. In this investigation, anti-stick as a neutral substance in proteolysis were considered and studied for reducing the problem. This vast survey was conducted in a big cheese production factory (in Neyshabur) and in the same procedure anti-stick as interested factor in cheeses packaging compared to standard cheeses production, one line productions (65200 packs with anti-stick were tested by 2953 persons for bitterness and another line was included the same procedure with standard cheese. In this investigate: 83% of standard packaging cheeses, compared with only28% of consumers cheese with anti-stick which confirmed bitterness. Although bitterness is generally associated with proteolysis and Microbial factors, Somatic cell, Starters play important role in generating bitterness in ultra filtrated cheeses, but based on the results the other factors such as anti-stick in packaging can be effective methods for reducing and removing unfavorable bitterness in cheese production.

Keywords: bitterness, uf cheese, anti-stick, single packaged

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Authors: Modreck Gomo

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The evolution of groundwater chemistry and its quality is largely controlled by hydrogeochemical processes and their understanding is therefore important for groundwater quality assessments and protection of the water resources. A study was conducted in Bloemfontein town of South Africa to assess and compare the groundwater chemistry and quality characteristics in an alluvial aquifer and single-plane fractured-rock aquifers. 9 groundwater samples were collected from monitoring boreholes drilled into the two aquifer systems during a once-off sampling exercise. Samples were collected through low-flow purging technique and analysed for major ions and trace elements. In order to describe the hydrochemical facies and identify dominant hydrogeochemical processes, the groundwater chemistry data are interpreted using stiff diagrams and principal component analysis (PCA), as complimentary tools. The fitness of the groundwater quality for domestic and irrigation uses is also assessed. Results show that the alluvial aquifer is characterised by a Na-HCO₃ hydrochemical facie while fractured-rock aquifer has a Ca-HCO₃ facie. The groundwater in both aquifers originally evolved from the dissolution of calcite rocks that are common on land surface environments. However the groundwater in the alluvial aquifer further goes through another evolution as driven by cation exchange process in which Na in the sediments exchanges with Ca²⁺ in the Ca-HCO₃ hydrochemical type to result in the Na-HCO₃ hydrochemical type. Despite the difference in the hydrogeochemical processes between the alluvial aquifer and single-plane fractured-rock aquifer, this did not influence the groundwater quality. The groundwater in the two aquifers is very hard as influenced by the elevated magnesium and calcium ions that evolve from dissolution of carbonate minerals which typically occurs in surface environments. Based on total dissolved levels (600-900 mg/L), groundwater quality of the two aquifer systems is classified to be of fair quality. The negative potential impacts of the groundwater quality for domestic uses are highlighted.

Keywords: alluvial aquifer, fractured-rock aquifer, groundwater quality, hydrogeochemical processes

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Authors: Manasa Kalla, Narasimha Raju Chebrolu, Ashok Chatterjee

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We have studied the quantum transport properties of a single molecular transistor in the presence of an external magnetic field using the Keldysh Green function technique. We also used the Anderson-Holstein-Caldeira-Leggett Model to describe the single molecular transistor that consists of a molecular quantum dot (QD) coupled to two metallic leads and placed on a substrate that acts as a heat bath. The phonons are eliminated by the Lang-Firsov transformation and the effective Hamiltonian is used to study the effect of an external magnetic field on the spectral density function, Tunneling Current, Differential Conductance and Spin polarization. A peak in the spectral function corresponds to a possible excitation. In the presence of a magnetic field, the spin-up and spin-down states are degenerate and this degeneracy is lifted by the magnetic field leading to the splitting of the central peak of the spectral function. The tunneling current decreases with increasing magnetic field. We have observed that even the differential conductance peak in the zero magnetic field curve is split in the presence electron-phonon interaction. As the magnetic field is increased, each peak splits into two peaks. And each peak indicates the existence of an energy level. Thus the number of energy levels for transport in the bias window increases with the magnetic field. In the presence of the electron-phonon interaction, Differential Conductance in general gets reduced and decreases faster with the magnetic field. As magnetic field strength increases, the spin polarization of the current is increasing. Our results show that a strongly interacting QD coupled to metallic leads in the presence of external magnetic field parallel to the plane of QD acts as a spin filter at zero temperature.

Keywords: Anderson-Holstein model, Caldeira-Leggett model, spin-polarization, quantum dots

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Authors: Alex Fedoseyev

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This study investigates a generalized hydrodynamic equation (GHE) simplified model for the simulation of turbulent flow over a two-dimensional backward-facing step (BFS) at Reynolds number Re=132000. The GHE were derived from the generalized Boltzmann equation (GBE). GBE was obtained by first principles from the chain of Bogolubov kinetic equations and considers particles of finite dimensions. The GHE has additional terms, temporal and spatial fluctuations, compared to the Navier-Stokes equations (NSE). These terms have a timescale multiplier τ, and the GHE becomes the NSE when $\tau$ is zero. The nondimensional τ is a product of the Reynolds number and the squared length scale ratio, τ=Re*(l/L)², where l is the apparent Kolmogorov length scale, and L is a hydrodynamic length scale. The BFS flow modeling results obtained by 2D calculations cannot match the experimental data for Re>450. One or two additional equations are required for the turbulence model to be added to the NSE, which typically has two to five parameters to be tuned for specific problems. It is shown that the GHE does not require an additional turbulence model, whereas the turbulent velocity results are in good agreement with the experimental results. A review of several studies on the simulation of flow over the BFS from 1980 to 2023 is provided. Most of these studies used different turbulence models when Re>1000. In this study, the 2D turbulent flow over a BFS with height H=L/3 (where L is the channel height) at Reynolds number Re=132000 was investigated using numerical solutions of the GHE (by a finite-element method) and compared to the solutions from the Navier-Stokes equations, k–ε turbulence model, and experimental results. The comparison included the velocity profiles at X/L=5.33 (near the end of the recirculation zone, available from the experiment), recirculation zone length, and velocity flow field. The mean velocity of NSE was obtained by averaging the solution over the number of time steps. The solution with a standard k −ε model shows a velocity profile at X/L=5.33, which has no backward flow. A standard k−ε model underpredicts the experimental recirculation zone length X/L=7.0∓0.5 by a substantial amount of 20-25%, and a more sophisticated turbulence model is needed for this problem. The obtained data confirm that the GHE results are in good agreement with the experimental results for turbulent flow over two-dimensional BFS. A turbulence model was not required in this case. The computations were stable. The solution time for the GHE is the same or less than that for the NSE and significantly less than that for the NSE with the turbulence model. The proposed approach was limited to 2D and only one Reynolds number. Further work will extend this approach to 3D flow and a higher Re.

Keywords: backward-facing step, comparison with experimental data, generalized hydrodynamic equations, separation, reattachment, turbulent flow

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Authors: Lanlan Xiao, Yang Liu, Shuo Chen, Bingmei Fu

Abstract:

Most cancer-related deaths are due to metastasis. Metastasis is a complex, multistep processes including the detachment of cancer cells from the primary tumor and the migration to distant targeted organs through blood and/or lymphatic circulations. During hematogenous metastasis, the emigration of tumor cells from the blood stream through the vascular wall into the tissue involves arrest in the microvasculature, adhesion to the endothelial cells forming the microvessel wall and transmigration to the tissue through the endothelial barrier termed as extravasation. The narrow slit between endothelial cells that line the microvessel wall is the principal pathway for tumor cell extravasation to the surrounding tissue. To understand this crucial step for tumor hematogenous metastasis, we used Dissipative Particle Dynamics method to investigate an individual cell passing through a narrow slit numerically. The cell membrane was simulated by a spring-based network model which can separate the internal cytoplasm and surrounding fluid. The effects of the cell elasticity, cell shape and cell surface area increase, and slit size on the cell transmigration through the slit were investigated. Under a fixed driven force, the cell with higher elasticity can be elongated more and pass faster through the slit. When the slit width decreases to 2/3 of the cell diameter, the spherical cell becomes jammed despite reducing its elasticity modulus by 10 times. However, transforming the cell from a spherical to ellipsoidal shape and increasing the cell surface area only by 3% can enable the cell to pass the narrow slit. Therefore the cell shape and surface area increase play a more important role than the cell elasticity in cell passing through the narrow slit. In addition, the simulation results indicate that the cell migration velocity decreases during entry but increases during exit of the slit, which is qualitatively in agreement with the experimental observation.

Keywords: dissipative particle dynamics, deformability, surface area increase, cell migration

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Authors: Ping-Ping Zhang, Hui-Zhang, Xu-Hui Sun

Abstract:

Highly-uniform In2O3/CuO bilayer and multilayer porous thin films were successfully fabricated using self-assembled soft template and simple sputtering deposition technique. The sensor based on the In2O3/CuO bilayer porous thin film shows obviously improved sensing performance to ethanol at the lower working temperature, compared to single layer counterpart sensors. The response of In2O3/CuO bilayer sensors exhibits nearly 3 and 5 times higher than those of the single layer In2O3 and CuO porous film sensors over the same ethanol concentration, respectively. The sensing mechanism based on p-n hetero-junction, which contributed to the enhanced sensing performance was also experimentally confirmed by a control experiment which the SiO2 insulation layer was inserted between the In2O3 and CuO layers to break the p-n junction. In addition, the sensing performance can be further enhanced by increasing the number of In2O3/CuO junction layers. The facile process can be easily extended to the fabrication of other semiconductor oxide gas sensors for practical sensing applications.

Keywords: gas sensor, multilayer porous thin films, In2O3/CuO, p-n junction

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Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

Abstract:

DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

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Authors: Kayode A. Olaniyi, Olabanji F. Omotoye, Adeola A. Ogunleye

Abstract:

Computer system components such as the CPU, the Controllers, and the operating system, work together as a team, and storage or memory is the essential parts of this team apart from the processor. The memory and storage system including processor caches, main memory, and storage, form basic storage component of a computer system. The characteristics of the different types of storage are inherent in the design and the technology employed in the manufacturing. These memory characteristics define the speed, compatibility, cost, volatility, and density of the various storage types. Most computers rely on a hierarchy of storage devices for performance. The effective and efficient use of the memory hierarchy of the computer system therefore is the single most important aspect of computer system design and use. The memory hierarchy is becoming a fundamental performance and energy bottleneck, due to the widening gap between the increasing demands of modern computer applications and the limited performance and energy efficiency provided by traditional memory technologies. With the dramatic development in the computers systems, computer storage has had a difficult time keeping up with the processor speed. Computer architects are therefore facing constant challenges in developing high-speed computer storage with high-performance which is energy-efficient, cost-effective and reliable, to intercept processor requests. It is very clear that substantial advancements in redesigning the existing memory physical and logical structures to meet up with the latest processor potential is crucial. This research work investigates the importance of computer memory (storage) hierarchy in the design of computer systems. The constituent storage types of the hierarchy today were investigated looking at the design technologies and how the technologies affect memory characteristics: speed, density, stability and cost. The investigation considered how these characteristics could best be harnessed for overall efficiency of the computer system. The research revealed that the best single type of storage, which we refer to as ideal memory is that logical single physical memory which would combine the best attributes of each memory type that make up the memory hierarchy. It is a single memory with access speed as high as one found in CPU registers, combined with the highest storage capacity, offering excellent stability in the presence or absence of power as found in the magnetic and optical disks as against volatile DRAM, and yet offers a cost-effective attribute that is far away from the expensive SRAM. The research work suggests that to overcome these barriers it may then mean that memory manufacturing will take a total deviation from the present technologies and adopt one that overcomes the associated challenges with the traditional memory technologies.

Keywords: cache, memory-hierarchy, memory, registers, storage

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Authors: Marco Naegele, Klaus Stoppel, Thomas Dekorsy

Abstract:

Passively Q-switched microchip lasers enable the great potential for sophisticated LiDAR systems due to their compact overall system design, excellent beam quality, and scalable pulse energies. However, many near-infrared solid-state lasers show emitting wavelengths > 1000 nm, which are not compatible with state-of-the-art silicon detectors. Here we demonstrate a passively Q-switched microchip laser operating at 914 nm. The microchip laser consists of a 3 mm long Nd:YVO₄ crystal as a gain medium, while Cr⁴⁺:YAG with an initial transmission of 98% is used as a saturable absorber. Quasi-continuous pumping enables single pulse operation, and low duty cycles ensure low overall heat generation and power consumption. Thus, thermally induced instabilities are minimized, and operation without active cooling is possible while ambient temperature changes are compensated by adjustment of the pump laser current only. Single-emitter diode pumping at 808 nm leads to a compact overall system design and robust setup. Utilization of a microchip cavity approach ensures single-longitudinal mode operation with spectral bandwidths in the picometer regime and results in short laser pulses with pulse durations below 10 ns. Beam quality measurements reveal an almost diffraction-limited beam and enable conclusions concerning the thermal lens, which is essential to stabilize the plane-plane resonator. A 7% output coupler transmissivity is used to generate pulses with energies in the microjoule regime and peak powers of more than 600 W. Long-term pulse duration, pulse energy, central wavelength, and spectral bandwidth measurements emphasize the excellent system stability and facilitate the utilization of this laser in the context of a LiDAR system.

Keywords: diode-pumping, LiDAR system, microchip laser, Nd:YVO4 laser, passively Q-switched

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Authors: Nurul Izzah Ibrahim, Isa Naina Mohamed, Norazlina Mohamed, Ahmad Nazrun Shuid

Abstract:

Osteoporosis disease delays fracture healing. Statins have shown potential for osteoporosis and to promote fracture healing. The effects of statin can be further potentiated by combining it with a carrier known as poly-(DL-lactide), which would provide persistent release of statin to the fracture site. This study was designed to investigate the effects of direct injection of poly-(DL-lactide)-incorporated lovastatin on fracture healing of postmenopausal osteoporosis rat model. Twenty-four Sprague-Dawley female rats were divided into 3 groups: sham-operated (SO), ovariectomized-control rats (OVxC) and poly-(DL-lactide)-incorporated lovastatin (OVx+Lov) groups. The OVx+Lov group was given a single injection of 750 µg/kg lovastatin particles incorporated with poly-(DL-lactide). After 4 weeks, the fractured tibiae were dissected out for biomechanical assessments of the callus. The OVx+Lov group showed significantly better callus strength than the OVxC group (p<0.05). In conclusion, a single injection of lovastatin-incorporated poly-(DL-lactide) was able to promote better fracture healing of osteoporotic bone.

Keywords: statins, fracture healing, osteoporosis, poly-(DL-lactide)

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Authors: Ameur Ameur Abdelkader, Boukherrouba Hadjira

Abstract:

The aim of the present study was to evaluate different doses of PMSG on reproductive performance in Ouled Djellal ewes synchronized during the breeding season period. A total of 200 ewes were used in this experiment, were divided in two groups, 100 uniparous (A) and 100 multiparous (B). All animals in both groups were divided equally into four groups homogeneous lots of then a single intramuscular (IM) injection of PMSG, Lot T1, A1 (400 IU), A2 (500 IU), A3 (600 IU) and (lot T2, B1 (400 IU), B2 (500UI), B3 (600UI), T1, and T2 are batch control groups received a single injection of progestin treatment without PMSG. The results showed that the fertility rate ranges from 79.16% to 92% with no significant difference (P > 0.05) between uniparous and multiparous ewes. The prolificity rate varies from 100% to 140% in uniparous ewes with the respective doses of 0 IU for the control group and 600 IU for lot A3. A significant difference between multiparous ewes prolificacy and uniparous receiving 500UI PMSG (respectively 142% vs 109%). The productivity rate has increased significantly among uniparous ewes with 82% for lot A1 to 112.5% for lot A3, as in multiparous ewes 66.66% for lot B1 to 133.33% for lot B3. At the same we recorded a positive correlation between the number of born products and increasing the dose of PMSG injected into the two categories of ewes (112.5% to 133.33% for multiparous uniparous VS 83% for and 66.66 uniparous % for multiparous).

Keywords: Ouled djellal ewe, PMSG, reproductive performance, Fertility

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Authors: N. Cihan KayaçEtin, Stijn Verdoodt, Alexis Versele

Abstract:

The construction industry is accounted for one-third of all waste generated in the European Union (EU) countries. The Circular Economy Action Plan of the EU aims to tackle this issue and aspires to enhance the sustainability of the construction industry by adopting more circular principles and bio-based material use. The Interreg Circular Bio-Based Construction Industry (CBCI) project was conceived to research how this adoption can be facilitated. For this purpose, an approach is developed that integrates technical, legal and social aspects and provides business models for circular designing and building with bio-based materials. In the scope of the project, the research outputs are to be displayed in a real-life setting by constructing a demo terraced single-family house, the living lab (LL) located in Ghent (Belgium). The realization of the LL is conducted in a step-wise approach that includes iterative processes for design, description, criteria definition and multi-criteria assessment of building components. The essence of the research lies within the exploratory approach to the state-of-art building envelope and technical systems options for achieving an optimum combination for a circular and bio-based construction. For this purpose, nine preliminary designs (PD) for building envelope are generated, which consist of three basic construction methods: masonry, lightweight steel construction and wood framing construction supplemented with bio-based construction methods like cross-laminated timber (CLT) and massive wood framing. A comparative analysis on the PDs was conducted by utilizing several complementary tools to assess the circularity. This paper focuses on the life cycle assessment (LCA) approach for evaluating the environmental impact of the LL Ghent. The adoption of an LCA methodology was considered critical for providing a comprehensive set of environmental indicators. The PDs were developed at the component level, in particular for the (i) inclined roof, (ii-iii) front and side façade, (iv) internal walls and (v-vi) floors. The assessment was conducted on two levels; component and building level. The options for each component were compared at the first iteration and then, the PDs as an assembly of components were further analyzed. The LCA was based on a functional unit of one square meter of each component and CEN indicators were utilized for impact assessment for a reference study period of 60 years. A total of 54 building components that are composed of 31 distinct materials were evaluated in the study. The results indicate that wood framing construction supplemented with bio-based construction methods performs environmentally better than the masonry or steel-construction options. An analysis on the correlation between the total weight of components and environmental impact was also conducted. It was seen that masonry structures display a high environmental impact and weight, steel structures display low weight but relatively high environmental impact and wooden framing construction display low weight and environmental impact. The study provided valuable outputs in two levels: (i) several improvement options at component level with substitution of materials with critical weight and/or impact per unit, (ii) feedback on environmental performance for the decision-making process during the design phase of a circular single family house.

Keywords: circular and bio-based materials, comparative analysis, life cycle assessment (LCA), living lab

Procedia PDF Downloads 181

Authors: Yongyi Chen, Li Qin, Peng Jia, Yongqiang Ning, Yun Liu, Lijun Wang

Abstract:

The distributed feedback (DFB) lasers are indispensable in optical phase array (OPA) used for light detection and ranging (LIDAR) techniques, laser communication systems and integrated optics, thanks to their stable single longitudinal mode and narrow linewidth properties. Traditional index-coupled (IC) DFB lasers with uniform gratings have an inherent problem of lasing two degenerated modes. Phase shifts are usually required to eliminate the mode degeneration, making the grating structure complex and expensive. High-quality antireflection (AR) coatings on both lasing facets are also essential owing to the random facet phases introduced by the chip cleavage process, which means half of the lasing energy is wasted. Gain-coupled DFB (GC-DFB) lasers based on the periodic gain (or loss) are announced to have single longitudinal mode as well as capable of the unsymmetrical coating to increase lasing power and efficiency thanks to facet immunity. However, expensive and time-consuming technologies such as epitaxial regrowth and nanoscale grating processing are still required just as IC-DFB lasers, preventing them from practical applications and commercial markets. In this research, we propose a low-cost, single-mode regrowth-free GC-DFB laser based on periodic surface p-contacts. The gain coupling effect is achieved simply by periodic current distribution in the quantum well caused by periodic surface p-contacts, introducing very little index-coupling effect that can be omitted. It is prepared by i-line lithography, without nanoscale grating fabrication or secondary epitaxy. Due to easy fabrication techniques, it provides a method to fabricate practical low cost GC-DFB lasers for widespread practical applications.

Keywords: DFB laser, gain-coupled, low cost, periodic p-contacts

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