Search results for: spacing sizes

Authors: Manon Ghislain, Timothée Bonnet, Olivier Gimenez, Olivier Dehorter, Pierre-Yves Henry

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Climatic fluctuations affect the demography of animal populations, generating changes in population size, phenology, distribution and community assemblages. However, very few studies have identified the underlying demographic processes. For short-lived species, like common passerine birds, are these changes generated by changes in adult survival or in fecundity and recruitment? This study tests for an effect of annual climatic conditions (spring and winter) on annual, local adult survival at very large spatial (a country, 252 sites), temporal (25 years) and biological (25 species) scales. The Constant Effort Site ringing has allowed the collection of capture - mark - recapture data for 100 000 adult individuals since 1989, over metropolitan France, thus documenting annual, local survival rates of the most common passerine birds. We specifically developed a set of multi-year, multi-species, multi-site Bayesian models describing variations in local survival and recapture probabilities. This method allows for a statistically powerful hierarchical assessment (global versus species-specific) of the effects of climate variables on survival. A major part of between-year variations in survival rate was common to all species (74% of between-year variance), whereas only 26% of temporal variation was species-specific. Although changing spring climate is commonly invoked as a cause of population size fluctuations, spring climatic anomalies (mean precipitation or temperature for March-August) do not impact adult survival: only 1% of between-year variation of species survival is explained by spring climatic anomalies. However, for sedentary birds, winter climatic anomalies (North Atlantic Oscillation) had a significant, quadratic effect on adult survival, birds surviving less during intermediate years than during more extreme years. For migratory birds, we do not detect an effect of winter climatic anomalies (Sahel Rainfall). We will analyze the life history traits (migration, habitat, thermal range) that could explain a different sensitivity of species to winter climate anomalies. Overall, we conclude that changes in population sizes for passerine birds are unlikely to be the consequences of climate-driven mortality (or emigration) in spring but could be induced by other demographic parameters, like fecundity.

Keywords: Bayesian approach, capture-recapture, climate anomaly, constant effort sites scheme, passerine, seasons, survival

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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

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Authors: Yau-Luen Ng, Nathan Banka, Santosh Devasia

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In this paper, a method based on soft artificial cilia is introduced to separate particles based on size and mass. In nature, cilia are used for fluid propulsion in the mammalian circulatory system, as well as for swimming and size-selective particle entrainment for feeding in microorganisms. Inspired by biological cilia, an array of artificial cilia was fabricated using Polydimethylsiloxane (PDMS) to simulate the actual motion. A row of four individually-controlled magnetic artificial cilia in a semi-circular channel are actuated by the magnetic fields from four permanent magnets. Each cilium is a slender rectangular cantilever approximately 13mm long made from a composite of PDMS and carbonyl iron particles. A time-varying magnetic force is achieved by periodically varying the out-of-plane distance from the permanent magnets to the cilia, resulting in large-amplitude deflections of the cilia that can be used to drive fluid motion. Previous results have shown that this system of individually-controlled magnetic cilia can generate effective mixing flows; the purpose of the present work is to apply the individual cilia control to a particle separation task. Based on the observed beating patterns of cilia arrays in nature, the experimental beating patterns were selected as a metachronal wave, in which a fixed phase lead or lag is imposed between adjacent cilia. Additionally, the beating frequency was varied. For each set of experimental parameters, the channel was filled with water and polyethylene microspheres introduced at the center of the cilia array. Two types of particles were used: large red microspheres with density 0.9971 g/cm³ and 850-1000 μm avg. diameter, and small blue microspheres with density 1.06 g/cm³ and diameter 30 μm. At low beating frequencies, all particles were propelled in the mean flow direction. However, the large particles were observed to reverse directions above about 4.8 Hz, whereas reversal of the small particle transport direction did not occur until 6 Hz. Between these two transition frequencies, the large and small particles can be separated as they move in opposite directions. The experimental results show that selecting an appropriate cilia beating pattern can lead to selective transport of neutrally-buoyant particles based on their size. Importantly, the separation threshold can be chosen dynamically by adjusting the actuation frequency. However, further study is required to determine the range of particle sizes that can be effectively separated for a given system geometry.

Keywords: magnetic cilia, particle separation, tunable separation, soft actutors

Procedia PDF Downloads 177

Authors: Paramita Banerjee, K. R. S. Chandrakumar, G. P. Das

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Bulk MgH2 has drawn much attention for the purpose of hydrogen storage because of its high hydrogen storage capacity (~7.7 wt %) as well as low cost and abundant availability. However, its practical usage has been hindered because of its high hydrogen desorption enthalpy (~0.8 eV/H2 molecule), which results in an undesirable desorption temperature of 3000C at 1 bar H2 pressure. To surmount the limitations of bulk MgH2 for the purpose of hydrogen storage, a detailed first-principles density functional theory (DFT) based study on the structure and stability of neutral (Mgm) and positively charged (Mgm+) Mg nanoclusters of different sizes (m = 2, 4, 8 and 12), as well as their interaction with molecular hydrogen (H2), is reported here. It has been found that due to the absence of d-electrons within the Mg atoms, hydrogen remained in molecular form even after its interaction with neutral and charged Mg nanoclusters. Interestingly, the H2 molecules do not enter into the interstitial positions of the nanoclusters. Rather, they remain on the surface by ornamenting these nanoclusters and forming new structures with a gravimetric density higher than 15 wt %. Our observation is that the inclusion of Grimme’s DFT-D3 dispersion correction in this weakly interacting system has a significant effect on binding of the H2 molecules with these nanoclusters. The dispersion corrected interaction energy (IE) values (0.1-0.14 eV/H2 molecule) fall in the right energy window, that is ideal for hydrogen storage. These IE values are further verified by using high-level coupled-cluster calculations with non-iterative triples corrections i.e. CCSD(T), (which has been considered to be a highly accurate quantum chemical method) and thereby confirming the accuracy of our ‘dispersion correction’ incorporated DFT calculations. The significance of the polarization and dispersion energy in binding of the H2 molecules are confirmed by performing energy decomposition analysis (EDA). A total of 16, 24, 32 and 36 H2 molecules can be attached to the neutral and charged nanoclusters of size m = 2, 4, 8 and 12 respectively. Ab-initio molecular dynamics (AIMD) simulation shows that the outermost H2 molecules are desorbed at a rather low temperature viz. 150 K (-1230C) which is expected. However, complete dehydrogenation of these nanoclusters occur at around 1000C. Most importantly, the host nanoclusters remain stable up to ~500 K (2270C). All these results on the adsorption and desorption of molecular hydrogen with neutral and charged Mg nanocluster systems indicate towards the possibility of reducing the dehydrogenation temperature of bulk MgH2 by designing new Mg-based nano materials which will be able to adsorb molecular hydrogen via this weak Mg-H2 interaction, rather than the strong Mg-H bonding. Notwithstanding the fact that in practical applications, these interactions will be further complicated by the effect of substrates as well as interactions with other clusters, the present study has implications on our fundamental understanding to this problem.

Keywords: density functional theory, DFT, hydrogen storage, molecular dynamics, molecular hydrogen adsorption, nanoclusters, physisorption

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Authors: Lalith Edirisinghe

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Due to the variability in global trading patterns, some ports in the world experience a shortage of shipping containers while the rest of the ports have excess container stocks. According to this study, carriers operate and manage their container inventories independently, leading to enormous container repositioning costs. In contrast, the researcher suggests that costs can be minimized if carriers exchange containers among them. In other words, rather than repositioning excess containers, a carrier could offer them to another carrier in the same port that has a shortage and vice versa. However, this is easier said than done because there is huge complexity in global container management as it involves many operational parameters such as multiple types and sizes of containers, the varying transit times of different carriers, etc., and the exchange may take place in various ports globally. Therefore, the exchange should be facilitated through a fully comprehensive automated computer system that could consider all the parameters that impact the possibility of exchange containers. Accordingly, the research used mixed research methods, combining qualitative and quantitative approaches. Data analysis is conducted using SPSS tools, and a prototype is developed as the output of the research. The proposed mathematical solution will proactively scan through the container size, type, and volume of every member carrier in each port and map how the deficit and excess quantities could be shared among them and set off the imbalance of empty container reposition at ports of their interest. The approach includes obtaining and processing container inventory information from multiple parties in real time for assessing container data associated with each party for each port at a given time. Using the container data, container inventories for each party at each port for a defined time are forecasted. A first party having surplus (offeror) and deficit (offeree) of empty containers at a first and a second port at a first time, respectively, is determined. A second party having a deficit and surplus of empty containers at the first time, respectively, is determined. Offering the first and the second party a container exchange opportunity to enable the first party to supply surplus empty containers to the second party at the first port based on the first container characteristics and the second party to supply surplus empty containers to the first party at the second port based on the second container characteristics. After the offeree obtains containers, they will be shipped to a port determined by the exporters. To ensure the sustainability of this method, the system should provide equal benefits to both the offeror and the offeree. Accordingly, the system will consider not only the number of containers exchanged but also the duration the offeree may hold them in its custody. This reduces container repositioning costs by utilizing mathematical modeling, algorithms, big data, machine learning, and artificial intelligence. This method and system may reduce the container repositioning cost by twenty percent.

Keywords: container inventory, benefit of exchange, reposition, imbalance, shipping, carriers, offeree, offeror

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Authors: Zohar Manber, Ran Elkon

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Accumulation of somatic mutations (SMs) in the genome is a major driving force of cancer development. Most SMs in the tumor's genome are functionally neutral; however, some cause damage to critical processes and provide the tumor with a selective growth advantage (termed cancer driver mutations). Current research on functional significance of SMs is mainly focused on finding alterations in protein coding sequences. However, the exome comprises only 3% of the human genome, and thus, SMs in the noncoding genome significantly outnumber those that map to protein-coding regions. Although our understanding of noncoding driver SMs is very rudimentary, it is likely that disruption of regulatory elements in the genome is an important, yet largely underexplored mechanism by which somatic mutations contribute to cancer development. The expression of most human genes is controlled by multiple enhancers, and therefore, it is conceivable that regulatory SMs are distributed across different enhancers of the same target gene. Yet, to date, most statistical searches for regulatory SMs have considered each regulatory element individually, which may reduce statistical power. The first challenge in considering the cumulative activity of all the enhancers of a gene as a single unit is to map enhancers to their target promoters. Such mapping defines for each gene its set of regulating enhancers (termed "set of regulatory elements" (SRE)). Considering multiple enhancers of each gene as one unit holds great promise for enhancing the identification of driver regulatory SMs. However, the success of this approach is greatly dependent on the availability of comprehensive and accurate enhancer-promoter (E-P) maps. To date, the discovery of driver regulatory SMs has been hindered by insufficient sample sizes and statistical analyses that often considered each regulatory element separately. In this study, we analyzed more than 2,500 whole-genome sequence (WGS) samples provided by The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) in order to identify such driver regulatory SMs. Our analyses took into account the combinatorial aspect of gene regulation by considering all the enhancers that control the same target gene as one unit, based on E-P maps from three genomics resources. The identification of candidate driver noncoding SMs is based on their recurrence. We searched for SREs of genes that are "hotspots" for SMs (that is, they accumulate SMs at a significantly elevated rate). To test the statistical significance of recurrence of SMs within a gene's SRE, we used both global and local background mutation rates. Using this approach, we detected - in seven different cancer types - numerous "hotspots" for SMs. To support the functional significance of these recurrent noncoding SMs, we further examined their association with the expression level of their target gene (using gene expression data provided by the ICGC and TCGA for samples that were also analyzed by WGS).

Keywords: cancer genomics, enhancers, noncoding genome, regulatory elements

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Authors: Malahat Rezaee, Mahiran Basri, Raja Noor Zaliha Raja Abdul Rahman, Abu Bakar Salleh

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Sodium diclofenac is one of the most commonly used drugs of nonsteroidal anti-inflammatory drugs (NSAIDs). It is especially effective in the controlling the severe conditions of inflammation and pain, musculoskeletal disorders, arthritis, and dysmenorrhea. Formulation as nanoemulsions is one of the nanoscience approaches that have been progressively considered in pharmaceutical science for transdermal delivery of drug. Nanoemulsions are a type of emulsion with particle sizes ranging from 20 nm to 200 nm. An emulsion is formed by the dispersion of one liquid, usually the oil phase in another immiscible liquid, water phase that is stabilized using surfactant. Palm kernel oil esters (PKOEs), in comparison to other oils; contain higher amounts of shorter chain esters, which suitable to be applied in micro and nanoemulsion systems as a carrier for actives, with excellent wetting behavior without the oily feeling. This research was aimed to study the effect of O/S ratio on stability and rheological behavior of sodium diclofenac loaded and unloaded palm kernel oil esters nanoemulsion systems. The effect of different O/S ratio of 0.25, 0.50, 0.75, 1.00 and 1.25 on stability of the drug-loaded and unloaded nanoemulsion formulations was evaluated by centrifugation, freeze-thaw cycle and storage stability tests. Lecithin and cremophor EL were used as surfactant. The stability of the prepared nanoemulsion formulations was assessed based on the change in zeta potential and droplet size as a function of time. Instability mechanisms including coalescence and Ostwald ripening for the nanoemulsion system were discussed. In comparison between drug-loaded and unloaded nanoemulsion formulations, drug-loaded formulations represented smaller particle size and higher stability. In addition, the O/S ratio of 0.5 was found to be the best ratio of oil and surfactant for production of a nanoemulsion with the highest stability. The effect of O/S ratio on rheological properties of drug-loaded and unloaded nanoemulsion systems was studied by plotting the flow curves of shear stress (τ) and viscosity (η) as a function of shear rate (γ). The data were fitted to the Power Law model. The results showed that all nanoemulsion formulations exhibited non-Newtonian flow behaviour by displaying shear thinning behaviour. Viscosity and yield stress were also evaluated. The nanoemulsion formulation with the O/S ratio of 0.5 represented higher viscosity and K values. In addition, the sodium diclofenac loaded formulations had more viscosity and higher yield stress than drug-unloaded formulations.

Keywords: nanoemulsions, palm kernel oil esters, sodium diclofenac, rheoligy, stability

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Authors: Johannes Günther

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Time Sensitive Networking (TSN), standardized in the IEEE 802.1 standard, has been lent increasing attention in the context of mission critical systems. Such mission critical systems, e.g., in the automotive domain, aviation, industrial, and smart factory domain, are responsible for coordinating complex functionalities in real time. In many of these contexts, a reliable data exchange fulfilling hard time constraints and quality of service (QoS) conditions is of critical importance. TSN standards are able to provide guarantees for deterministic communication behaviour, which is in contrast to common best-effort approaches. Therefore, the superior QoS guarantees of TSN may aid in the development of new technologies, which rely on low latencies and specific bandwidth demands being fulfilled. TSN extends existing Ethernet protocols with numerous standards, providing means for synchronization, management, and overall real-time focussed capabilities. These additional QoS guarantees, as well as management mechanisms, lead to an increased attack surface for potential malicious attackers. As TSN guarantees certain deadlines for priority traffic, an attacker may degrade the QoS by delaying a packet beyond its deadline or even execute a denial of service (DoS) attack if the delays lead to packets being dropped. However, thus far, security concerns have not played a major role in the design of such standards. Thus, while TSN does provide valuable additional characteristics to existing common Ethernet protocols, it leads to new attack vectors on networks and allows for a range of potential attacks. One answer to these security risks is to deploy defense mechanisms according to a moving target defense (MTD) strategy. The core idea relies on the reduction of the attackers' knowledge about the network. Typically, mission-critical systems suffer from an asymmetric disadvantage. DoS or QoS-degradation attacks may be preceded by long periods of reconnaissance, during which the attacker may learn about the network topology, its characteristics, traffic patterns, priorities, bandwidth demands, periodic characteristics on links and switches, and so on. Here, we implemented and tested several MTD-like defense strategies against different attacker models of varying capabilities and budgets, as well as collaborative attacks of multiple attackers within a network, all within the context of TSN networks. We modelled the networks and tested our defense strategies on an OMNET++ testbench, with networks of different sizes and topologies, ranging from a couple dozen hosts and switches to significantly larger set-ups.

Keywords: network security, time sensitive networking, moving target defense, cyber security

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Authors: Leonard Tiong, Sonit Singh, Kevin Ho Shon, Sarah Lewis

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Investigation into the use of artificial intelligence in radiology continues to develop at a rapid rate. During the coronavirus pandemic, the combination of an exponential increase in chest x-rays and unpredictable staff shortages resulted in a huge strain on the department's workload. There is a World Health Organisation estimate that two-thirds of the global population does not have access to diagnostic radiology. Therefore, there could be demand for a program that could detect acute changes in imaging compatible with infection to assist with screening. We generated a conventional neural network and tested its efficacy in recognizing changes compatible with coronavirus infection. Following ethics approval, a deidentified set of 77 normal and 77 abnormal chest x-rays in patients with confirmed coronavirus infection were used to generate an algorithm that could train, validate and then test itself. DICOM and PNG image formats were selected due to their lossless file format. The model was trained with 100 images (50 positive, 50 negative), validated against 28 samples (14 positive, 14 negative), and tested against 26 samples (13 positive, 13 negative). The initial training of the model involved training a conventional neural network in what constituted a normal study and changes on the x-rays compatible with coronavirus infection. The weightings were then modified, and the model was executed again. The training samples were in batch sizes of 8 and underwent 25 epochs of training. The results trended towards an 85.71% true positive/true negative detection rate and an area under the curve trending towards 0.95, indicating approximately 95% accuracy in detecting changes on chest X-rays compatible with coronavirus infection. Study limitations include access to only a small dataset and no specificity in the diagnosis. Following a discussion with our programmer, there are areas where modifications in the weighting of the algorithm can be made in order to improve the detection rates. Given the high detection rate of the program, and the potential ease of implementation, this would be effective in assisting staff that is not trained in radiology in detecting otherwise subtle changes that might not be appreciated on imaging. Limitations include the lack of a differential diagnosis and application of the appropriate clinical history, although this may be less of a problem in day-to-day clinical practice. It is nonetheless our belief that implementing this program and widening its scope to detecting multiple pathologies such as lung masses will greatly assist both the radiology department and our colleagues in increasing workflow and detection rate.

Keywords: artificial intelligence, COVID, neural network, machine learning

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Authors: David M. Gilstrap

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Designing effective instructions is a critical dimension of effective teaching systems. Due to a void in interpersonal contact, online courses present new challenges in this regard, especially with large class sizes. This presentation is a case study in how the repetition of instructions within the course design was utilized to increase instructor efficiency in managing a rapid rise in enrollment. World of Turf is a two-credit, semester-long elective course for non-turfgrass majors at Michigan State University. It is taught entirely online and solely by the instructor without any graduate teaching assistants. Discussion forums about subject matter are designated for each lecture, and those forums are moderated by a few undergraduate turfgrass majors. The instructions as to the course structure, navigation, and grading are conveyed in the syllabus and course-introduction lecture. Regardless, students email questions about such matters, and the number of emails increased as course enrollment grew steadily during the first three years of its existence, almost to a point that the course was becoming unmanageable. Many of these emails occurred because the instructor was failing to update and operate the course in a timely and proper fashion because he was too busy answering emails. Some of the emails did help the instructor ferret out poorly composed instructions, which he corrected. Beginning in the summer semester of 2015, the instructor overhauled the course by segregating content into weekly modules. The philosophy envisioned and embraced was that there can never be too much repetition of instructions in an online course. Instructions were duplicated within each of these modules as well as associated modules for syllabus and schedules, getting started, frequently asked questions, practice tests, surveys, and exams. In addition, informational forums were created and set aside for questions about the course workings and each of the three exams, thus creating even more repetition. Within these informational forums, students typically answer each other’s questions, which demonstrated to the students that that information is available in the course. When needed, the instructor interjects with corrects answers or clarifies any misinformation which students might be putting forth. Increasing the amount of repetition of instructions and strategic enhancements to the course design have resulted in a dramatic decrease in the number of email replies necessitated by the instructor. The resulting improvement in efficiency allowed the instructor to raise enrollment limits thus effecting a ten-fold increase in enrollment over a five-year period with 1050 students registered during the most recent academic year, thus becoming easily the largest online course at the university. Because of the improvement in course-delivery efficiency, sufficient time was created that allowed the instructor to development and launch an additional online course, hence further enhancing his productivity and value in terms of the number of the student-credit hours for which he is responsible.

Keywords: design, efficiency, instructions, online, repetition

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Authors: Chinedu F. Anochie

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The presence of gangue particles in recovered metal concentrates has been a serious challenge to ore dressing engineers. Middlings lower the quality of concentrates, and in most cases, drastically affect the smelter terms, owing to exorbitant amounts paid by Mineral Processing industries as treatment charge. Models which encourage optimization of liberation operations have been utilized in most ore beneficiation industries to reduce the presence of locked particles in valuable concentrates. Moreover, methods such as incorporation of regrind mills, scavenger, rougher and cleaner cells, to the milling and flotation plants has been widely employed to tackle these concerns, and to optimize the grade–recovery relationship of metal concentrates. This work compared the crushing and grinding method of liberation, to the mine to mill route, by evaluating the proportion of middlings present in selectively processed complex Pb-Zn ore samples. To establish the effect of size reduction operations on the percentage of locked particles present in recovered concentrates, two similar samples of complex Pb- Zn ores were processed. Following blasting operation, the first ore sample was ground directly in a ball mill (Mine to Mill Route of Comminution), while the other sample was manually crushed, and subsequently ground in the ball mill (Crushing and Grinding Route of Comminution). The two samples were separately sieved in a mesh to obtain the desired representative particle sizes. An equal amount of each sample that would be processed in the flotation circuit was then obtained with the aid of a weighing balance. These weighed fine particles were simultaneously processed in the flotation circuit using the selective flotation technique. Sodium cyanide, Methyl isobutyl carbinol, Sodium ethyl xanthate, Copper sulphate, Sodium hydroxide, Lime and Isopropyl xanthate, were the reagents used to effect differential flotation of the two ore samples. Analysis and calculations showed that the degree of liberation obtained for the ore sample which went through the conventional crushing and grinding route of comminution, was higher than that of the directly milled run off mine (ROM) ore. Similarly, the proportion of middlings obtained from the separated galena (PbS) and sphalerite (ZnS) concentrates, were lower for the crushed and ground ore sample. A concise data which proved that the mine to mill method of size reduction is not the most ideal technique for the recovery of quality metal concentrates has been established.

Keywords: comminution, degree of liberation, middlings, mine to mill

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Authors: B. Grygalewicz, R. Woroniecka, J. Rygier, K. Borkowska, A. Labak, B. Nowakowska, B. Pienkowska-Grela

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Introduction: Chronic lymphocytic leukemia (CLL) is the most common form of adult leukemia in the Western world. Hemizygous and or homozygous loss at 13q14 occur in more than half of cases and constitute the most frequent chromosomal abnormality in CLL. It is believed that deletions 13q14 play a role in CLL pathogenesis. Two microRNA genes miR-15a and miR- 16-1 are targets of 13q14 deletions and plays a tumor suppressor role by targeting antiapoptotic BCL2 gene. Deletion size, as a single change detected in FISH analysis, has haprognostic significance. Patients with small deletions, without RB1 gene involvement, have the best prognosis and the longest overall survival time (OS 133 months). In patients with bigger deletion region, containing RB1 gene, prognosis drops to intermediate, like in patients with normal karyotype and without changes in FISH with overall survival 111 months. Aim: Precise delineation of 13q14 deletions regions in two groups of CLL patients, with mono- and biallelic deletions and qualifications of their prognostic significance. Methods: Detection of 13q14 deletions was performed by FISH analysis with CLL probe panel (D13S319, LAMP1, TP53, ATM, CEP-12). Accurate deletion size detection was performed by CGH Haematological Cancer and SNP array (8x60K). Results: Our investigated group of CLL patients with the 13q14 deletion, detected by FISH analysis, comprised two groups: 18 patients with monoallelic deletions and 18 patients with biallelic deletions. In FISH analysis, in the monoallelic group the range of cells with deletion, was 43% to 97%, while in biallelic group deletion was detected in 11% to 94% of cells. Microarray analysis revealed precise deletion regions. In the monoallelic group, the range of size was 348,12 Kb to 34,82 Mb, with median deletion size 7,93 Mb. In biallelic group discrepancy of total deletions, size was 135,27 Kb to 33,33 Mb, with median deletion size 2,52 Mb. The median size of smaller deletion regions on one copy chromosome 13 was 1,08 Mb while the average region of bigger deletion on the second chromosome 13 was 4,04 Mb. In the monoallelic group, in 8/18 deletion region covered RB1 gene. In the biallelic group, in 4/18 cases, revealed deletion on one copy of biallelic deletion and in 2/18 showed deletion of RB1 gene on both deleted 13q14 regions. All minimal deleted regions included miR-15a and miR-16-1 genes. Genetic results will be correlated with clinical data. Conclusions: Application of CGH microarrays technique in CLL allows accurately delineate the size of 13q14 deletion regions, what have a prognostic value. All deleted regions included miR15a and miR-16-1, what confirms the essential role of these genes in CLL pathogenesis. In our investigated groups of CLL patients with mono- and biallelic 13q14 deletions, patients with biallelic deletion presented smaller deletion sizes (2,52 Mb vs 7,93 Mb), what is connected with better prognosis.

Keywords: CLL, deletion 13q14, CGH microarrays, SNP array

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Authors: Surekha Barkur, Aseefhali Bankapur, Santhosh Chidangil

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Raman Tweezers technique has become prevalent in single cell studies. This technique combines Raman spectroscopy which gives information about molecular vibrations, with optical tweezers which use a tightly focused laser beam for trapping the single cells. Thus Raman Tweezers enabled researchers analyze single cells and explore different applications. The applications of Raman Tweezers include studying blood cells, monitoring blood-related disorders, silver nanoparticle-induced stress, etc. There is increased interest in the toxic effect of nanoparticles with an increase in the various applications of nanoparticles. The interaction of these nanoparticles with the cells may vary with their size. We have studied the effect of silver nanoparticles of sizes 10nm, 40nm, and 100nm on erythrocytes using Raman Tweezers technique. Our aim was to investigate the size dependence of the nanoparticle effect on RBCs. We used 785nm laser (Starbright Diode Laser, Torsana Laser Tech, Denmark) for both trapping and Raman spectroscopic studies. 100 x oil immersion objectives with high numerical aperture (NA 1.3) is used to focus the laser beam into a sample cell. The back-scattered light is collected using the same microscope objective and focused into the spectrometer (Horiba Jobin Vyon iHR320 with 1200grooves/mm grating blazed at 750nm). Liquid nitrogen cooled CCD (Symphony CCD-1024x256-OPEN-1LS) was used for signal detection. Blood was drawn from healthy volunteers in vacutainer tubes and centrifuged to separate the blood components. 1.5 ml of silver nanoparticles was washed twice with distilled water leaving 0.1 ml silver nanoparticles in the bottom of the vial. The concentration of silver nanoparticles is 0.02mg/ml so the 0.03mg of nanoparticles will be present in the 0.1 ml nanoparticles obtained. The 25 ul of RBCs were diluted in 2 ml of PBS solution and then treated with 50 ul (0.015mg) of nanoparticles and incubated in CO2 incubator. Raman spectroscopic measurements were done after 24 hours and 48 hours of incubation. All the spectra were recorded with 10mW laser power (785nm diode laser), 60s of accumulation time and 2 accumulations. Major changes were observed in the peaks 565 cm-1, 1211 cm-1, 1224 cm-1, 1371 cm-1, 1638 cm-1. A decrease in intensity of 565 cm-1, increase in 1211 cm-1 with a reduction in 1224 cm-1, increase in intensity of 1371 cm-1 also peak disappearing at 1635 cm-1 indicates deoxygenation of hemoglobin. Nanoparticles with higher size were showing maximum spectral changes. Lesser changes observed in case of 10nm nanoparticle-treated erythrocyte spectra.

Keywords: erythrocytes, nanoparticle-induced toxicity, Raman tweezers, silver nanoparticles

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Authors: Prajakta Khare

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There is a huge number of social enterprises operating in India, across all enterprise sizes and forms addressing diverse social issues. Some cases such as such as Aravind eye care, Narayana Hridalaya, SEWA have been studied extensively in management literature and are known cases in social entrepreneurship. But there are several smaller social enterprises in India that are not called so per se due to the lack of understanding of the concept. There is a lack of academic research on social entrepreneurship in India and the term ‘social entrepreneurship’ is not yet widely known in the country, even by people working in this field as was found by this study. The present study aims to identify the most prominent form of social enterprises in India, the profile of the entrepreneurs, challenges faced, the lessons (theory and practices) emerging from their functioning and finally the factors contributing to the enterprises’ success. This is a preliminary exploratory study using primary data from 30 social enterprises in India. The study used snow ball sampling and a qualitative analysis. Data was collected from founders of social enterprises through written structured questionnaires, open-ended interviews and field visits to enterprises. The sample covered enterprises across sectors such as environment, affordable education, children’s rights, rain water harvesting, women empowerment etc. The interview questions focused on founder’s background and motivation, qualifications, funding, challenges, founder’s understanding and perspectives on social entrepreneurship, government support, linkages with other organizations etc. apart from several others. The interviews were conducted across 3 languages - Hindi, Marathi, English and were then translated and transcribed. 50% of founders were women and 65% of the total founders were highly qualified with a MBA, PhD or MBBS. The most important challenge faced by these entrepreneurs is recruiting skilled people. When asked about their understanding of the term, founders had diverse perspectives. Also, their understandings about the term social enterprise and social entrepreneur were extremely varied. Some founders identified the terms with doing something good for the society, some thought that every business can be called a social enterprise. 35% of the founders were not aware of the term social entrepreneur/ social entrepreneurship. They said that they could identify themselves as social entrepreneurs after discussions with the researcher. The general perception in India is that ‘NGOs are corrupt’- fighting against this perception to secure funds is also another problem as pointed out by some founders. There are unique challenges that social entrepreneurs in India face, as the political, social, economic environment around them is rapidly changing; and getting adequate support from the government is a problem. The research in its subsequent stages aims to clarify existing, missing and new definitions of the term to provide deeper insights in the terminology and issues relating to Social Entrepreneurship in India.

Keywords: challenges, India, social entrepreneurship, social entrepreneurs

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Authors: Anne C. Richer-De-Forges, Dominique Arrouays, Songchao Chen, Mercedes Roman Dobarco

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Most of the digital soil mapping (DSM) products rely on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs. However, many other observations (often qualitative, nominal, or ordinal) could be used as proxies of lab measurements or as input data for ML of PTF predictions. DSM and ML are briefly described with some examples taken from the literature. Then, we explore the potential of an ordinal qualitative variable, i.e., the hand-feel soil texture (HFST) estimating the mineral particle distribution (PSD): % of clay (0-2µm), silt (2-50µm) and sand (50-2000µm) in 15 classes. The PSD can also be measured by lab measurements (LAST) to determine the exact proportion of these particle-sizes. However, due to cost constraints, HFST are much more numerous and spatially dense than LAST. Soil texture (ST) is a very important soil parameter to map as it is controlling many of the soil properties and functions. Therefore, comes an essential question: is it possible to use HFST as a proxy of LAST for calibration and/or validation of DSM predictions of ST? To answer this question, the first step is to compare HFST with LAST on a representative set where both information are available. This comparison was made on ca 17,400 samples representative of a French region (34,000 km2). The accuracy of HFST was assessed, and each HFST class was characterized by a probability distribution function (PDF) of its LAST values. This enables to randomly replace HFST observations by LAST values while respecting the PDF previously calculated and results in a very large increase of observations available for the calibration or validation of PTF and ML predictions. Some preliminary results are shown. First, the comparison between HFST classes and LAST analyses showed that accuracies could be considered very good when compared to other studies. The causes of some inconsistencies were explored and most of them were well explained by other soil characteristics. Then we show some examples applying these relationships and the increase of data to several issues related to DSM. The first issue is: do the PDF functions that were established enable to use HSFT class observations to improve the LAST soil texture prediction? For this objective, we replaced all HFST for topsoil by values from the PDF 100 time replicates). Results were promising for the PTF we tested (a PTF predicting soil water holding capacity). For the question related to the ML prediction of LAST soil texture on the region, we did the same kind of replacement, but we implemented a 10-fold cross-validation using points where we had LAST values. We obtained only preliminary results but they were rather promising. Then we show another example illustrating the potential of using HFST as validation data. As in numerous countries, the HFST observations are very numerous; these promising results pave the way to an important improvement of DSM products in all the countries of the world.

Keywords: digital soil mapping, improvement of digital soil mapping predictions, potential of using hand-feel soil texture, soil texture prediction

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Authors: Nafisa Mahbub, Hajo Ribberink

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Electrification of long-haul trucks has been in discussion as a potential strategy to decarbonization. These trucks will require large batteries because of their weight and long daily driving distances. Around 245 million battery electric vehicles are predicted to be on the road by the year 2035. This huge increase in the number of electric vehicles (EVs) will require intensive mining operations for metals and other materials to manufacture millions of batteries for the EVs. These operations will add significant environmental burdens and there is a significant risk that the mining sector will not be able to meet the demand for battery materials, leading to higher prices. Since the battery is the most expensive component in the EVs, technologies that can enable electrification with smaller batteries sizes have substantial potential to reduce the material usage and associated environmental and cost burdens. One of these technologies is an ‘electrified road’ (eroad), where vehicles receive power while they are driving, for instance through an overhead catenary (OC) wire (like trolleybuses and electric trains), through wireless (inductive) chargers embedded in the road, or by connecting to an electrified rail in or on the road surface. This study assessed the total material use and associated life cycle GHG emissions of two types of eroads (overhead catenary and in-road wireless charging) for long-haul trucks in Canada and compared them to electrification using stationary plug-in fast charging. As different electrification technologies require different amounts of materials for charging infrastructure and for the truck batteries, the study included the contributions of both for the total material use. The study developed a bottom-up approach model comparing the three different charging scenarios – plug in fast chargers, overhead catenary and in-road wireless charging. The investigated materials for charging technology and batteries were copper (Cu), steel (Fe), aluminium (Al), and lithium (Li). For the plug-in fast charging technology, different charging scenarios ranging from overnight charging (350 kW) to megawatt (MW) charging (2 MW) were investigated. A 500 km of highway (1 lane of in-road charging per direction) was considered to estimate the material use for the overhead catenary and inductive charging technologies. The study considered trucks needing an 800 kWh battery under the plug-in charger scenario but only a 200 kWh battery for the OC and inductive charging scenarios. Results showed that overall the inductive charging scenario has the lowest material use followed by OC and plug-in charger scenarios respectively. The materials use for the OC and plug-in charger scenarios were 50-70% higher than for the inductive charging scenarios for the overall system including the charging infrastructure and battery. The life cycle GHG emissions from the construction and installation of the charging technology material were also investigated.

Keywords: charging technology, eroad, GHG emissions, material use, overhead catenary, plug in charger

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Authors: Šárka Hradilová, Aleš Panáček, Radek Zbořil

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Nanotechnologies are considered the most promising fields with high added value, brings new possibilities in various sectors from industry to medicine. With the growing of interest in nanomaterials and their applications, increasing nanoparticle production leads to increased exposure of people and environment with ‘human made’ nanoparticles. Nanoparticles (NPs) are clusters of atoms in the size range of 1–100 nm. Metal nanoparticles represent one of the most important and frequently used types of NPs due to their unique physical, chemical and biological properties, which significantly differ from those of bulk material. Biological properties including toxicity of metal nanoparticles are generally determined by their size, size distribution, shape, surface area, surface charge, surface chemistry, stability in the environment and ability to release metal ions. Therefore, the biological behavior of NPs and their possible adverse effect cannot be derived from the bulk form of material because nanoparticles show unique properties and interactions with biological systems just due to their nanodimensions. Silver and gold NPs are intensively studied and used. Both can be used for instance in surface enhanced Raman spectroscopy, a considerable number of applications of silver NPs is associated with antibacterial effects, while gold NPs are associated with cancer treatment and bio imaging. Antibacterial effects of silver ions are known for centuries. Silver ions and silver-based compounds are highly toxic to microorganisms. Toxic properties of silver NPs are intensively studied, but the mechanism of cytoxicity is not fully understood. While silver NPs are considered toxic, gold NPs are referred to as toxic but also innocuous for eukaryotic cells. Therefore, gold NPs are used in various biological applications without a risk of cell damaging, even when we want to suppress the growth of cancer cells. Thus, gold NPs are toxic or harmless. Because most studies comparing particles of various sizes prepared in various ways, and testing is performed on different cell lines, it is very difficult to generalize. The novelty and significance of our research is focused to the complex biological effects of silver and gold NPs prepared by the same method, have the same parameters and the same stabilizer. That is why we can compare the biological effects of pure nanometals themselves based on their chemical nature without the influence of other variable. Aim of our study therefore is to compare the cytotoxic effect of two types of noble metal NPs focusing on the mechanisms that contribute to cytotoxicity. The study was conducted on murine fibroblasts by selected common used tests. Each of these tests monitors the selected area related to toxicity and together provides a comprehensive view on the issue of interactions of nanoparticles and living cells.

Keywords: cytotoxicity, gold nanoparticles, mechanism of cytotoxicity, silver nanoparticles

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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

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Authors: Jacob Schwartz, Maxim Durach, Aniruddha Mitra, Abbas Rashidi, Glen Sage, Atin Adhikari

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NIOSH (National Institute for Occupational Safety and Health) approved N95 respirators are commonly used by workers in construction sites where there is a large amount of dust being produced from sawing, grinding, blasting, welding, etc., both electrostatically charged and not. A significant portion of airborne particles in construction sites could be nanoparticles created beside coarse particles. The penetration of the particles through the masks may differ depending on the size and charge of the individual particle. In field experiments relevant to this current study, we found that nanoparticles of medium size ranges are penetrating more frequently than nanoparticles of smaller and larger sizes. For example, penetration percentages of nanoparticles of 11.5 – 27.4 nm into a sealed N95 respirator on a manikin head ranged from 0.59 to 6.59%, whereas nanoparticles of 36.5 – 86.6 nm ranged from 7.34 to 16.04%. The possible causes behind this increased penetration of mid-size nanoparticles through mask filters are not yet explored. The objective of this study is to identify causes behind this unusual behavior of mid-size nanoparticles. We have considered such physical factors as Boltzmann distribution of the particles in thermal equilibrium with the air, kinetic energy of the particles at impact on the mask, Stoke’s drag force, and electrostatic forces in the mask stopping the particles. When the particles collide with the mask, only the particles that have enough kinetic energy to overcome the energy loss due to the electrostatic forces and the Stokes’ drag in the mask can pass through the mask. To understand this process, the following assumptions were made: (1) the effect of Stoke’s drag depends on the particles’ velocity at entry into the mask; (2) the electrostatic force is proportional to the charge on the particles, which in turn is proportional to the surface area of the particles; (3) the general dependence on electrostatic charge and thickness means that for stronger electrostatic resistance in the masks and thicker the masks’ fiber layers the penetration of particles is reduced, which is a sensible conclusion. In sampling situations where one mask was soaked in alcohol eliminating electrostatic interaction the penetration was much larger in the mid-range than the same mask with electrostatic interaction. The smaller nanoparticles showed almost zero penetration most likely because of the small kinetic energy, while the larger sized nanoparticles showed almost negligible penetration most likely due to the interaction of the particle with its own drag force. If there is no electrostatic force the fraction for larger particles grows. But if the electrostatic force is added the fraction for larger particles goes down, so diminished penetration for larger particles should be due to increased electrostatic repulsion, may be due to increased surface area and therefore larger charge on average. We have also explored the effect of ambient temperature on nanoparticle penetrations and determined that the dependence of the penetration of particles on the temperature is weak in the range of temperatures in the measurements 37-42°C, since the factor changes in the range from 3.17 10-3K-1 to 3.22 10-3K-1.

Keywords: respiratory protection, industrial hygiene, aerosol, electrostatic force

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Authors: Nkwachukwu Chukwuchekwa, Joy Ulumma Chukwuchekwa

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Magnetic characteristics of grain-oriented electrical steel (GOES) are usually measured at high flux densities suitable for its typical applications in power transformers. There are limited magnetic data at low flux densities which are relevant for the characterization of GOES for applications in metering instrument transformers and low frequency magnetic shielding in magnetic resonance imaging medical scanners. Magnetic properties such as coercivity, B-H loop, AC relative permeability and specific power loss of conventional grain oriented (CGO) and high permeability grain oriented (HGO) electrical steels were measured and compared at high and low flux densities at power magnetising frequency. 40 strips comprising 20 CGO and 20 HGO, 305 mm x 30 mm x 0.27 mm from a supplier were tested. The HGO and CGO strips had average grain sizes of 9 mm and 4 mm respectively. Each strip was singly magnetised under sinusoidal peak flux density from 8.0 mT to 1.5 T at a magnetising frequency of 50 Hz. The novel single sheet tester comprises a personal computer in which LabVIEW version 8.5 from National Instruments (NI) was installed, a NI 4461 data acquisition (DAQ) card, an impedance matching transformer, to match the 600  minimum load impedance of the DAQ card with the 5 to 20  low impedance of the magnetising circuit, and a 4.7 Ω shunt resistor. A double vertical yoke made of GOES which is 290 mm long and 32 mm wide is used. A 500-turn secondary winding, about 80 mm in length, was wound around a plastic former, 270 mm x 40 mm, housing the sample, while a 100-turn primary winding, covering the entire length of the plastic former was wound over the secondary winding. A standard Epstein strip to be tested is placed between the yokes. The magnetising voltage was generated by the LabVIEW program through a voltage output from the DAQ card. The voltage drop across the shunt resistor and the secondary voltage were acquired by the card for calculation of magnetic field strength and flux density respectively. A feedback control system implemented in LabVIEW was used to control the flux density and to make the induced secondary voltage waveforms sinusoidal to have repeatable and comparable measurements. The low noise NI4461 card with 24 bit resolution and a sampling rate of 204.8 KHz and 92 KHz bandwidth were chosen to take the measurements to minimize the influence of thermal noise. In order to reduce environmental noise, the yokes, sample and search coil carrier were placed in a noise shielding chamber. HGO was found to have better magnetic properties at both high and low magnetisation regimes. This is because of the higher grain size of HGO and higher grain-grain misorientation of CGO. HGO is better CGO in both low and high magnetic field applications.

Keywords: flux density, electrical steel, LabVIEW, magnetization

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Authors: Othman E. Othman, Amira M. Nowier, Medhat El-Denary

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Camels play an important socio-economic role within the pastoral and agricultural system in the dry and semidry zones of Asia and Africa. Camels are economically important animals in Egypt where they are dual purpose animals (meat and milk). The analysis of chemical composition of camel milk showed that the total protein contents ranged from 2.4% to 5.3% and it is divided into casein and whey proteins. The casein fraction constitutes 52% to 89% of total camel milk protein and it divided into 4 fractions namely αs1, αs2, β and κ-caseins which are encoded by four tightly genes. In spite of the important role of casein genes and the effects of their genetic polymorphisms on quantitative traits and technological properties of milk, the studies for the detection of genetic polymorphism of camel milk genes are still limited. Due to this fact, this work focused - using PCR-RFP and sequencing analysis - on the identification of genetic polymorphisms and SNPs of two casein genes in Maghrabi camel breed which is a dual purpose camel breed in Egypt. The amplified fragments at 488-bp of the camel κ-CN gene were digested with AluI endonuclease. The results showed the appearance of three different genotypes in the tested animals; CC with three digested fragments at 203-, 127- and 120-bp, TT with three digested fragments at 203-, 158- and 127-bp and CT with four digested fragments at 203-, 158-, 127- and 120-bp. The frequencies of three detected genotypes were 11.0% for CC, 48.0% for TT and 41.0% for CT genotypes. The sequencing analysis of the two different alleles declared the presence of a single nucleotide polymorphism (C→T) at position 121 in the amplified fragments which is responsible for the destruction of a restriction site (AG/CT) in allele T and resulted in the presence of two different alleles C and T in tested animals. The nucleotide sequences of κ-CN alleles C and T were submitted to GenBank with the accession numbers; KU055605 and KU055606, respectively. The primers used in this study amplified 942-bp fragments spanning from exon 4 to exon 6 of camel αS1-Casein gene. The amplified fragments were digested with two different restriction enzymes; SmlI and AluI. The results of SmlI digestion did not show any restriction site whereas the digestion with AluI endonuclease revealed the presence of two restriction sites AG^CT at positions 68^69 and 631^632 yielding the presence of three digested fragments with sizes 68-, 563- and 293-bp.The nucleotide sequences of this fragment from camel αS1-Casein gene were submitted to GenBank with the accession number KU145820. In conclusion, the genetic characterization of quantitative traits genes which are associated with the production traits like milk yield and composition is considered an important step towards the genetic improvement of livestock species through the selection of superior animals depending on the favorable alleles and genotypes; marker assisted selection (MAS).

Keywords: genetic polymorphism, SNP polymorphism, Maghrabi camels, κ-Casein gene, αS1-Casein gene

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Authors: Jing-Yang Chung, Chi-Wei Liao, Jing Li, Bor Kae Chang, Cheng-Yu Wang

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Chemical hydride ammonia borane (AB, NH3BH3) draws attentions to hydrogen energy researches for its high theoretical gravimetrical capacity (19.6 wt%). Nevertheless, the elevated AB decomposition temperatures (Td) and unwanted byproducts are main hurdles in practical application. It was reported that the byproducts and Td can be reduced with nanoconfinement technique, in which AB molecules are confined in porous materials, such as porous carbon, zeolite, metal-organic frameworks (MOFs), etc. Although nanoconfinement empirically shows effectiveness on hydrogen generation temperature reduction in AB, the theoretical mechanism is debatable. Low Td was reported in AB@IRMOF-1 (Zn4O(BDC)3, BDC = benzenedicarboxylate), where Zn atoms form closed metal clusters secondary building unit (SBU) with no exposed active sites. Other than nanosized hydride, it was also observed that catalyst addition facilitates AB decomposition in the composite of Li-catalyzed carbon CMK-3, MOF JUC-32-Y with exposed Y3+, etc. It is believed that nanosized AB is critical for lowering Td, while active sites eliminate byproducts. Nonetheless, some researchers claimed that it is the catalytic sites that are the critical factor to reduce Td, instead of the hydride size. The group physically ground AB with ZIF-8 (zeolitic imidazolate frameworks, (Zn(2-methylimidazolate)2)), and found similar reduced Td phenomenon, even though AB molecules were not ‘confined’ or forming nanoparticles by physical hand grinding. It shows the catalytic reaction, not nanoconfinement, leads to AB dehydrogenation promotion. In this research, we explored the possible criteria of hydrogen production temperature from nanoconfined AB in MOFs with different pore sizes and active sites. MOFs with metal SBU such as Zn (IRMOF), Zr (UiO), and Al (MIL-53), accompanying with various organic ligands (BDC and BPDC; BPDC = biphenyldicarboxylate) were modified with AB. Excess MOFs were used for AB size constrained in micropores estimated by revisiting Horvath-Kawazoe model. AB dissolved in methanol was added to MOFs crystalline with MOF pore volume to AB ratio 4:1, and the slurry was dried under vacuum to collect AB@MOF powders. With TPD-MS (temperature programmed desorption with mass spectroscopy), we observed Td was reduced with smaller MOF pores. For example, it was reduced from 100°C to 64°C when MOF micropore ~1 nm, while ~90°C with pore size up to 5 nm. The behavior of Td as a function of AB crystalline radius obeys thermodynamics when the Gibbs free energy of AB decomposition is zero, and no obvious correlation with metal type was observed. In conclusion, we discovered Td of AB is proportional to the reciprocal of MOF pore size, possibly stronger than the effect of active sites.

Keywords: ammonia borane, chemical hydride, metal-organic framework, nanoconfinement

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Authors: Qian Yi Ooi

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At present, airfoil parameters are still designed and optimized according to the scale of conventional aircraft, and there are still some slight deviations in terms of scale differences. However, insufficient parameters or poor surface mesh quality is likely to occur if these small deviations are embedded in a future civil aircraft with a size that is quite different from conventional aircraft, such as a blended-wing-body (BWB) aircraft with future potential, resulting in large deviations in geometric similarity in computational fluid dynamics (CFD) simulations. To avoid this situation, the study on the CFD calculation on the geometric similarity of airfoil parameters and the quality of the surface mesh is conducted to obtain the ability of different parameterization methods applied on different airfoil scales. The research objects are three airfoil scales, including the wing root and wingtip of conventional civil aircraft and the wing root of the giant hybrid wing, used by three parameterization methods to compare the calculation differences between different sizes of airfoils. In this study, the constants including NACA 0012, a Reynolds number of 10 million, an angle of attack of zero, a C-grid for meshing, and the k-epsilon (k-ε) turbulence model are used. The experimental variables include three airfoil parameterization methods: point cloud method, B-spline curve method, and class function/shape function transformation (CST) method. The airfoil dimensions are set to 3.98 meters, 17.67 meters, and 48 meters, respectively. In addition, this study also uses different numbers of edge meshing and the same bias factor in the CFD simulation. Studies have shown that with the change of airfoil scales, different parameterization methods, the number of control points, and the meshing number of divisions should be used to improve the accuracy of the aerodynamic performance of the wing. When the airfoil ratio increases, the most basic point cloud parameterization method will require more and larger data to support the accuracy of the airfoil’s aerodynamic performance, which will face the severe test of insufficient computer capacity. On the other hand, when using the B-spline curve method, average number of control points and meshing number of divisions should be set appropriately to obtain higher accuracy; however, the quantitative balance cannot be directly defined, but the decisions should be made repeatedly by adding and subtracting. Lastly, when using the CST method, it is found that limited control points are enough to accurately parameterize the larger-sized wing; a higher degree of accuracy and stability can be obtained by using a lower-performance computer.

Keywords: airfoil, computational fluid dynamics, geometric similarity, surface mesh quality

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: A. Drapeaux, S. Aviles, E. Garfoot

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Stem cell injections are a promising alternative treatment for hip osteoarthritis. Current literature has focused on short-term outcomes for both knee and hip osteoarthritis; however, there is a significant gap for longitudinal benefits for hip OA and limited firm conclusions due to small sample sizes. The purpose of this prospective study was to determine longitudinal changes in pain, function, and radiographs following bone marrow concentrate injection (BMAC) into the osteoarthritic hip joint. Methods: A prospective, cross-sectional study was conducted over the course of 12 months at an orthopedic practice. The study recruited 15 osteoarthritic pre-surgical hips with mild to moderate osteoarthritic severity who were scheduled to undergo hip arthroscopy. Data was collected at both pre-operative and post-operative time frames. Data collected included: hip radiographs, i-HOT-33 questionnaire data, BMAC autologous volume, and demographics. Questionnaire data was captured using Qualtrics XM software, and participants were sent an anonymous link at the following time frames: pre-operative, 2 weeks, 6 weeks, 12 weeks, 6 months, 12 months, and 24 months. Radiographic changes and BMAC volume were collected and reviewed by an orthopedic surgeon and sent to the primary investigator. Data was exported and analyzed in IBM-SPSS. Results: A total of 15 hips from 15 participants (mean age: 49, gender: 50% males, 50% females, BMI: 29.7) were used in the final analysis. Summative i-HOT 33 mean scores significantly changed between pre-operative status and 2-6 weeks post-operative status (p <.001) and pre-operative status and 3-6 months post-operative status (p <.001). There were no significant changes between other post-operative phases or between pre-operative status and 12 months post-operative. Significant improvements were found between summative i-HOT 33 mean (p<.001), daily pain (p<.001), daily sitting (p=.02), daily distance walked (p =.003), and daily limp (p=0.03) and post-operative status (2-6 weeks). No significant differences between demographic variables (gender, age, tobacco use, or diabetes) and i-HOT 33 summative mean scores. Discussion/Implications: The purpose of this study was to determine longitudinal changes in pain and function following a hip joint bone marrow concentrate injection. Results indicate that participants experience a significant improvement in pain and function between pre-operative and 2-6 weeks and 3-6 months post-injection. Participants also self-reported a significant change in average daily pain with sitting and walking between pre-operation and 2-6 weeks post-operative. This study includes a larger sample size of hip osteoarthritis cases; however, future research is warranted to include random controlled trials with a larger sample size.

Keywords: adult stem cell, orthopedics, osteoarthritis (hip), patient outcome assessment

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Authors: Serap Gedikli, Hakan Çakmak, M. Buğra Güldiken, Duygu Yalnızoğlu

Abstract:

Air, which is necessary for living things to survive; while it carries some useful substances in it, it can also carry foreign particles of different sizes that may be harmful to the health. All airborne organic substances of biological origin, including bacteria, fungi, fungal spores, viruses, pollen, and their components, are called "bioaerosols". Nowadays, everyone spends most of their time in closed areas such as home, workplace, school, etc. Although it is known that outdoor air pollution affects health, it is not known that indoor air pollution has harmful effects in terms of health. In this study, indoor air microbial load and SARS-CoV-2 virus cleaning efficiency of Froumann brand air cleaners were studied. This work in 300 m³, 600 m³, and 1000 m³ completely closed areas without any air circulation with Froumann N80, N90, and N100 air-cleaning devices. Analyzes were performed for both areas at 60 minutes before and after the device was operated using a particle measuring device (Particles Plus 7302) and an air sampler (Mas-100 ECO). The measurements were taken by placing the test equipment 1.5-2 m away from the air cleaner. At the same time, the efficiency of the HEPA filter was evaluated by taking samples from the air outlet point of the HEPA filter using the air sampling device (Mas-100 ECO) after the device was started. Nutrient agar and malt agar are used as total mesophilic bacteria and total fungi. The number of colony-forming units per m³ (cfu/m³) was calculated by counting colonies in Petri dishes after incubation for 48 hours at 37°C for bacteria and 72 hours at 30°C for fungi. The change in the number of colonies and the decrease in the microbial load was calculated as a percentage value. SARS-CoV-2 activity analysis studies were carried out by İnönü University Microbiology Department in accordance with the World Health Organization regulations. Finally, the HEPA filter in the devices used was taken and kept under a certain temperature and humidity, and the change in the microbial load on it was monitored over a 6-month period. At the end of the studies, a 91%-94% reduction was determined in the total mesophilic bacteria count of Frouman brand N80, N90, and N100 model air cleaners. A decrease of 94%-96% was detected in the total number of yeast/molds. HEPA filter efficiency was evaluated, and at the end of the analysis, 98% of the bacterial load and approximately 100% of yeast/mold load at the HEPA filter air outlet point were decreased. According to the SARS- CoV-2 analysis results, when the device is operating at the medium airflow level 3, it can filter virus-carrying aerosols by 99%. As a result, it was determined that the Froumann model air cleaner was effective in controlling and reducing the microbial load in the indoor air.

Keywords: HEPA filter, indoor air quality, microbial load, SARS-CoV-2

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Authors: Karolina Ordon, Sandrine Coste, Malgorzata Makowska-Janusik, Abdelhadi Kassiba

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Photocatalytic processes play key role in the production of a new source of energy (as hydrogen), design of self-cleaning surfaces or for the environment preservation. The most challenging task deals with the purification of water distinguished by high efficiency. In the mentioned process, organic pollutants in solutions are decomposed to the simple, non-toxic compounds as H2O and CO2. The most known photocatalytic materials are ZnO, CdS and TiO2 semiconductors with a particular involvement of TiO2 as an efficient photocatalysts even with a high band gap equal to 3.2 eV which exploit only UV radiation from solar emitted spectrum. However, promising material with visible light induced photoactivity was searched through the monoclinic polytype of BiVO4 which has energy gap about 2.4 eV. As required in heterogeneous photocatalysis, the high contact surface is required. Also, BiVO4 as photocatalyst can be optimized by increasing its surface area by achieving the mesoporous structure synthesize. The main goal of the present work consists in the synthesis and characterization of BiVO4 mesoporous thin film. The synthesis method based on sol-gel was carried out using a standard surfactants such as P123 and F127. The thin film was deposited by spin and dip coating method. Then, the structural analysis of the obtained material was performed thanks to X-ray diffraction (XRD) and Raman spectroscopy. The surface of resulting structure was investigated using a scanning electron microscopy (SEM). The computer simulations based on modeling the optical and electronic properties of bulk BiVO4 by using DFT (density functional theory) methodology were carried out. The semiempirical parameterized method PM6 was used to compute the physical properties of BiVO4 nanostructures. The Raman and IR absorption spectra were also measured for synthesized mesoporous material, and the results were compared with the theoretical predictions. The simulations of nanostructured BiVO4 have pointed out the occurrence of quantum confinement for nanosized clusters leading to widening of the band gap. This result overcame the relevance of nanosized objects to harvest wide part of the solar spectrum. Also, a balance was searched experimentally through the mesoporous nature of the films devoted to enhancing the contact surface as required for heterogeneous catalysis without to lower the nanocrystallite size under some critical sizes inducing an increased band gap. The present contribution will discuss the relevant features of the mesoporous films with respect to their photocatalytic responses.

Keywords: bismuth vanadate, photocatalysis, thin film, quantum-chemical calculations

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Authors: Cécile Dufloux, Klaus Böttcher, Heike Oppermann, Jürgen Wollweber

Abstract:

Hexagonal aluminum nitride (AlN) is a promising candidate for several wide band gap semiconductor compound applications such as deep UV light emitting diodes (UVC LED) and fast power transistors (HEMTs). To date, bulk AlN single crystals are still commonly grown from the physical vapor transport (PVT). Single crystalline AlN wafers obtained from this process could offer suitable substrates for a defect-free growth of ultimately active AlGaN layers, however, these wafers still lack from small sizes, limited delivery quantities and high prices so far.Although there is already an increasing interest in the commercial availability of AlN wafers, comparatively cheap Si, SiC or sapphire are still predominantly used as substrate material for the deposition of active AlGaN layers. Nevertheless, due to a lattice mismatch up to 20%, the obtained material shows high defect densities and is, therefore, less suitable for high power devices as described above. Therefore, the use of AlN with specially adapted properties for optical and sensor applications could be promising for mass market products which seem to fulfill fewer requirements. To respond to the demand of suitable AlN target material for the growth of AlGaN layers, we have designed an innovative technology based on reactive plasma spraying. The goal is to produce coarse grained AlN boules with N-terminated columnar structure and high purity. In this process, aluminum is injected into a microwave stimulated nitrogen plasma. AlN, as the product of the reaction between aluminum powder and the plasma activated N2, is deposited onto the target. We used an aluminum filament as the initial material to minimize oxygen contamination during the process. The material was guided through the nitrogen plasma so that the mass turnover was 10g/h. To avoid any impurity contamination by an erosion of the electrodes, an electrode-less discharge was used for the plasma ignition. The pressure was maintained at 600-700 mbar, so the plasma reached a temperature high enough to vaporize the aluminum which subsequently was reacting with the surrounding plasma. The obtained products consist of thick polycrystalline AlN layers with a diameter of 2-3 cm. The crystallinity was determined by X-ray crystallography. The grain structure was systematically investigated by optical and scanning electron microscopy. Furthermore, we performed a Raman spectroscopy to provide evidence of stress in the layers. This paper will discuss the effects of process parameters such as microwave power and deposition geometry (specimen holder, radiation shields, ...) on the topography, crystallinity, and stress distribution of AlN.

Keywords: aluminum nitride, polycrystal, reactive plasma spraying, semiconductor

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Authors: Pejman Salimi, Sebastiano Tieuli, Somayeh Taghavi, Michela Signoretto, Remo Proietti Zaccaria

Abstract:

Increasing the growth of industrial waste due to the large quantities of production leads to numerous environmental and economic challenges, such as climate change, soil and water contamination, human disease, etc. Energy recovery of waste can be applied to produce heat or electricity. This strategy allows for the reduction of energy produced using coal or other fuels and directly reduces greenhouse gas emissions. Among different factories, leather manufacturing plays a very important role in the whole world from the socio-economic point of view. The leather industry plays a very important role in our society from a socio-economic point of view. Even though the leather industry uses a by-product from the meat industry as raw material, it is considered as an activity demanding integrated prevention and control of pollution. Along the entire process from raw skins/hides to finished leather, a huge amount of solid and water waste is generated. Solid wastes include fleshings, raw trimmings, shavings, buffing dust, etc. One of the most abundant solid wastes generated throughout leather tanning is shaving waste. Leather shaving is a mechanical process that aims at reducing the tanned skin to a specific thickness before tanning and finishing. This product consists mainly of collagen and tanning agent. At present, most of the world's leather processing is chrome-tanned based. Consequently, large amounts of chromium-containing shaving wastes need to be treated. The major concern about the management of this kind of solid waste is ascribed to chrome content, which makes the conventional disposal methods, such as landfilling and incineration, not practicable. Therefore, many efforts have been developed in recent decades to promote eco-friendly/alternative leather production and more effective waste management. Herein, shaving waste resulting from metal-free tanning technology is proposed as low-cost precursors for the preparation of carbon material as anodes for lithium-ion batteries (LIBs). In line with the philosophy of a reduced environmental impact, for preparing fully sustainable and environmentally friendly LIBs anodes, deionized water and carboxymethyl cellulose (CMC) have been used as alternatives to toxic/teratogen N-methyl-2- pyrrolidone (NMP) and to biologically hazardous Polyvinylidene fluoride (PVdF), respectively. Furthermore, going towards the reduced cost, we employed water solvent and fluoride-free bio-derived CMC binder (as an alternative to NMP and PVdF, respectively) together with LiFePO₄ (LFP) when a full cell was considered. These actions make closer to the 2030 goal of having green LIBs at 100 $ kW h⁻¹. Besides, the preparation of the water-based electrodes does not need a controlled environment and due to the higher vapour pressure of water in comparison with NMP, the water-based electrode drying is much faster. This aspect determines an important consequence, namely a reduced energy consumption for the electrode preparation. The electrode derived from leather waste demonstrated a discharge capacity of 735 mAh g⁻¹ after 1000 charge and discharge cycles at 0.5 A g⁻¹. This promising performance is ascribed to the synergistic effect of defects, interlayer spacing, heteroatoms-doped (N, O, and S), high specific surface area, and hierarchical micro/mesopore structure of the biochar. Interestingly, these features of activated biochars derived from the leather industry open the way for possible applications in other EESDs as well.

Keywords: biowaste, lithium-ion batteries, physical activation, waste management, leather industry

Procedia PDF Downloads 143

Authors: S. V. Kuznetsov, M. N. Mayakova, V. Yu. Proydakova, V. V. Pavlov, A. S. Nizamutdinov, O. A. Morozov, V. V. Voronov, P. P. Fedorov

Abstract:

Increase in the share of electricity received by conversion of solar energy results in the reduction of the industrial impact on the environment from the use of the hydrocarbon energy sources. One way to increase said share is to improve the efficiency of solar energy conversion in silicon-based solar panels. Such efficiency increase can be achieved by transferring energy from sunlight-insensitive areas of work of silicon solar panels to the area of their photoresistivity. To achieve this goal, a transition to new luminescent materials with the high quantum yield of luminescence is necessary. Improvement in the quantum yield can be achieved by quantum cutting, which allows obtaining a quantum yield of down conversion of more than 150% due to the splitting of high-energy photons of the UV spectral range into lower-energy photons of the visible and near infrared spectral ranges. The goal of present work is to test approach of excitation through sensibilization of 4f-4f fluorescence of Yb3+ by various RE ions absorbing in UV and Vis spectral ranges. One of promising materials for quantum cutting luminophores are fluorides. In our investigation we have developed synthesis of nano- and submicron powders of calcium fluoride and strontium doped with rare-earth elements (Yb: Ce, Yb: Pr, Yb: Eu) of controlled dimensions and shape by co-precipitation from water solution technique. We have used Ca(NO3)2*4H2O, Sr(NO3)2, HF, NH4F as precursors. After initial solutions of nitrates were prepared they have been mixed with fluorine containing solution by dropwise manner. According to XRD data, the synthesis resulted in single phase samples with fluorite structure. By means of SEM measurements, we have confirmed spherical morphology and have determined sizes of particles (50-100 nm after synthesis and 150-300 nm after calcination). Temperature of calcination appeared to be 600°C. We have investigated the spectral-kinetic characteristics of above mentioned compounds. Here the diffuse reflection and laser induced fluorescence spectra of Yb3+ ions excited at around 4f-4f and 4f-5d transitions of Pr3+, Eu3+ and Ce3+ ions in the synthesized powders are reported. The investigation of down conversion luminescence capability of synthesized compounds included measurements of fluorescence decays and quantum yield of 2F5/2-2F7/2 fluorescence of Yb3+ ions as function of Yb3+ and sensitizer contents. An optimal chemical composition of CaF2-YbF3- LnF3 (Ln=Ce, Eu, Pr), SrF2-YbF3-LnF3 (Ln=Ce, Eu, Pr) micro- and nano- powders according to criteria of maximal IR fluorescence yield is proposed. We suppose that investigated materials are prospective in solar panels improvement applications. Work was supported by Russian Science Foundation grant #17-73- 20352.

Keywords: solar cell, fluorides, down-conversion luminescence, maximum quantum yield

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