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First principles study of the effect of substitution\doping on the performance of layered oxide cathode materials for secondary batteries
No full textLayered oxides have gained significant attention as promising cathode materials for both lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs). LIBs generally show better structural stability due to the smaller size of Li+ and its stronger electrostatic interactions within the host lattice. In contrast, SIBs, although more prone to larger volume changes and structural instability due to the larger Na+ radius, offer a more sustainable and cost-effective alternative because of the high natural abundance and low cost of sodium. They experience capacity fade due to structural and mechanical instability during the charging/discharging process. Identifying the origin of capacity fade and instability is essential for understanding material degradation. Therefore, in this thesis, the origin of the structural changes upon delithiation/lithiation and desodiation/sodiation has been investigated. These structural changes lead to irreversible phase transitions, resulting in significant changes to lattice parameters, particularly along the c-axis, due to anisotropic expansion and contraction. These lattice changes generate internal mechanical stresses, leading to the formation of microcracks and capacity fading during cycling.The impact of lattice doping on cathode materials for SIBs, with a specific focus on Li, Mg, Co, and Ni doping in P2-Na0.67MnO2, is also explored. We successfully investigated the theoretical design of oxygen-redox-active cathode materials for SIBs, focusing on challenges such as structural instability and Li migration (one of the possible reasons for capacity fade in Na-based cathodes) during the charging/discharging process. We also found that Li doping suppresses the phase transition from P2→O2 during charging/discharging. We also identified the reasons behind the phase stabilization (in the as-synthesized material) and phase transition (during operation) of P2-Na0.67MnO2 materials. The primary methods used in this thesis are a combination of electrostatic analysis, density functional theory calculations, and ab initio molecular dynamics simulations.Overall, in this work, I studied the mechanical and structural stability as well as the redox mechanisms of layered oxides. The main aim was to determine the parameters controlling cyclability and capacity of these materials during charge/discharge and to study the impact of substitution/doping on these quantities
A comprehensive monitoring toolkit for energy consumption measurement in cloud-based earth observation big data processing
No full textThe processing of earth observation big data (EOBD) in distributed environments has increased significantly, driven by advances in satellite technology and the growing number of earth observation missions. This massive influx of data presents unprecedented opportunities for environmental monitoring, climate change studies, and natural resource management, while simultaneously posing significant computational challenges. Cloud computing has emerged as an enabler for handling such EOBD, offering scalable computational resources, flexible storage solutions, and on-demand processing capabilities through platforms such as Google Earth Engine (GEE), AWS SageMaker, OpenEO, and Pangeo Cloud.While these cloud-based EOBD processing platforms offer varying levels of monitoring capabilities to help users understand their workflow execution, they primarily focus on traditional performance metrics. GEE provides basic performance insights focusing on task execution status, AWS SageMaker offers comprehensive resource utilization metrics through Amazon CloudWatch, and Pangeo Cloud implements the Dask profiler for real-time monitoring of cluster performance. However, a significant gap exists: none of these platforms incorporate energy consumption as a standard monitoring metric. This limitation becomes increasingly critical as the scientific community grows more concerned about the environmental impact of large-scale data processing operations.The absence of energy-related metrics from monitoring may hinder users from understanding the environmental impact associated with their EOBD processing workflows. This knowledge is particularly crucial in the earth observation domain, where the balance between computational requirements and environmental impact directly aligns with the field's core mission of environmental protection. Furthermore, recent green computing initiatives have emphasized the importance of sustainable IT infrastructure, yet the lack of standardized energy consumption metrics in EOBD processing platforms hinders researchers' ability to make informed decisions about computational resource usage.To address this gap, we propose a monitoring toolkit for understanding the energy consumption patterns in distributed EOBD processing. We develop an integrated approach that combines multi-level energy measurements: (1) hardware-level power data collected through RAPL for CPU and DRAM, IPMI for system-level metrics, and external power sensors for overall consumption; (2) software-level resource utilization metrics from the operating system including CPU usage, memory allocation, I/O operations, and network traffic; and (3) application-level profiling through integration with Dask's distributed processing framework. Our methodology employs power ratio modeling to correlate these measurements and estimate process-level energy consumption, enabling fine-grained energy profiling of EOBD workflows.The toolkit generates comprehensive monitoring reports that include energy consumption patterns, resource utilization correlations, and efficiency metrics, allowing users to make informed decisions about their processing strategies. By providing visibility into the energy consumption of computational workflows, this work contributes to the development of more sustainable EOBD processing practices. The toolkit enables users to better evaluate the true environmental cost of their computational workflows and optimize their processing strategies accordingly, supporting the broader goal of environmental protection through more energy-efficient earth observation data processing
A streamlined GIS interface for Citizen Science activities:QGIS Light
No full textCitizen science has emerged as a powerful way to involve the public in scientific research, especially in domains like environmental sciences, where participants actively collect data in the field. However, citizen scientists can contribute beyond data collection by engaging in data analytics to generate meaningful insights in collaboration with researchers. To support this broader participation, user-friendly and accessible tools for data visualization and analysis are essential. This study addresses this need in geospatial tools by introducing QGIS Light, a simplified version of the most widely used free and open-source desktop GIS software, QGIS. Developed as a plugin to QGIS, QGIS Light offers a streamlined working environment by simplifying the user interface, removing non-essential and advanced features, and introducing additional tools by default to support basic needs, such as accessing base maps and creating charts. The paper begins with an analysis of the QGIS user interface with a focus on simplicity of use. It then outlines the specific actions required to enhance the user experience for non-Technical users. The logic and technical implementation of the QGIS Light plugin are subsequently described in detail. Finally, additional user interface challenges in QGIS that affect overall usability are discussed. The findings highlight the value of critically evaluating existing interface elements and refining them into a more cohesive and standardized experience. QGIS Light is a first step in this direction to enhance usability of QGIS and may also guide similar simplification efforts in other GIS software, helping to lower their typically steep learning curves.</p
Elucidating Degradation Phenomena During Mixing of Silica-Natural Rubber Compounds:The Interplay of Viscoelastic Behavior and Silane Microstructures
Get PDFVarious commercial silica-silane coupling agent combinations are used these days for synthetic rubber-based passenger car tire treads with high silica-loadings. For truck tire treads, much lower silica-loadings are employed in combination with Natural Rubber (NR). The present study examines the impact of various commercial silane coupling agents on degradation phenomena during mixing of silica-filled NR compounds by analyzing changes in viscoelastic response, with a focus on different silane microstructures. A novel approach using delta–delta (Δδ) values to quantify branch formation caused by degradation-induced chain modifications has been adopted. Unfilled NR compounds primarily undergo polymer chain scission from thermo-mechanical and thermo-oxidative influences. During mixing, bis-(3-TriEthoxySilylPropyl) Tetrasulfide (TESPT) silane creates silica-rubber coupling and lightly crosslinked materials partly based on polysulfidic bonds. The lightly crosslinked rubber essentially sustains the reinforcement level in the compounds, counterbalancing the degradation effect. However, predominant degradation at 180°C significantly deteriorates the mechanical and dynamic properties of compounds containing both TESPT and TESPD (bis-(3-Triethoxysilylpropyl) disulfide). OTPTES (3-OctanoylThioPropylTriEthoxySilane) and MTCO (Mercapto-ThioCarboxylate Oligomer) silane-based compounds exhibit notable plasticization effects along with degradation. The choice of OTPTES in particular demonstrates excellent thermal stability, preserving mechanical properties even till 180°C. MTCO, with one reactive mercaptan group, couples efficiently with rubber at low dump temperatures, 130°C and 150°C, enhancing vulcanizate properties. At high dump temperatures of 170°C and 180°C, though, MTCO releases plasticizing moieties during mixing, leading to inferior final properties. The present study highlights the intricate balance between rubber degradation, crosslinking, branching, network formation, rubber-filler interactions, and plasticization effects specifically in silica-filled NR compounds for truck tire tread applications.</p
Moderated Mediation with Composites:The Composite Moderated Structural Equations Approach
No full textCorrigendum to “Sacroiliac joint fusion guided by intraoperatively superimposed virtual surgical planning using simulated fluoroscopic images” [Brain and Spine 4 (2024) 102905] (S2772529424001619), (10.1016/j.bas.2024.102905)
Get PDFThe authors regret that during the final upload of our manuscript, Fig. 3 was mistakenly switched with an incorrect version. Please find the correct version of Fig. 3 below.</p
Forecasting hospital drug demand for demand patterns with changepoints
Get PDFPredicting drug demand is of great importance for hospital pharmacy managers. Drug expenditures per hospital in the US averages over 7 million dollars per year, so it is important to manage these costs effectively. Due to erratic demand patterns, however, predicting demand for drugs is not an easy task. One of the patterns that occur when predicting drug demand are demand patterns with changepoints. These non-stationary patterns suddenly change with respect to their mean, which might occur due to drug authority approvals or events such as a pandemic. In this paper, we study demand patterns with changepoints, which we found to affect 25.9% of the top 500 drugs at our partnering hospital. We propose to use a Bayesian Online Changepoint Detection model. The overall performance of this method is at least as good as other methods under regular circumstances, but outperforms other commonly used forecasting tools especially right after the changepoint occurs, showing its ability to quickly adapt to changepoints. Furthermore, changepoints are more likely to occur for pricier drugs. In particular, drugs within the third and fourth quantile price range are almost three times more likely to have a changepoint compared to inexpensive drugs in the first quantile. This implies that especially for pricier drugs, specialized changepoint models may be useful in predicting drug demand.</p
An adjacency lemma on signed edge colorings with an application to planar graphs
Get PDFIn the study of edge colorings of graphs, critical graphs are of particular importance. One classical result concerning the structure of critical graphs is known as Vizing's Adjacency Lemma. This lemma provides useful structural information about the neighborhood of a vertex in a critical graph. Zhang introduced an adjacency lemma dealing with the second neighborhood of a vertex in a critical graph. Both of these adjacency lemmas are useful tools for proving classification results on edge colorings. In this paper, we present an adjacency lemma on critical signed graphs with even maximum degree. This new adjacency lemma can be interpreted as a local extension of Zhang's Adjacency Lemma. As an application of the new lemma, we show that a signed planar graph with maximum degree Δ≥6 in which every 6-cycle has at most one chord is Δ-edge-colorable.</p
Dispersion of backward-propagating waves in a surface defect on a three-dimensional photonic band-gap crystal
Get PDFWe experimentally study the dispersion relation of waves in a thin quasi-two-dimensional (2D) defect layer with periodic nanopores that sits on a 3D photonic band-gap crystal made from silicon by CMOS-compatible methods. The nanostructures are probed by momentum-resolved broadband near-infrared imaging of -polarized reflected light as a function of off-axis wave vectors. We identify surface defect modes at frequencies inside the 3D photonic band gap with a narrow relative linewidth (Δ/=0.028), which are absent in defect-free 3D photonic band-gap crystals. We calculate the dispersion of the states with relevant mode symmetries using a plane-wave-expansion supercell method, with structural parameters directly extracted from scanning electron microscope images. The calculated bands match very well with the measured data. The slope of the dispersion curves of the surface defect states is negative in one off-axis direction, corresponding to backward-propagating waves in that direction where the phase velocity and the group velocity point in opposite directions, as confirmed by finite-difference time-domain simulations. We also present a didactic and analytic model of a 2D grating sandwiched between vacuum and a negative real effective ɛ′<0 that mimics the 3D photonic band gap. The model's dispersion agrees with the experiments and with the full theory and shows that the backward propagation is caused by the surface grating. We discuss possible applications, including a device that senses the output direction of photons emitted by embedded quantum emitters in response to their emission frequency
Evaluating the performance of circular suppliers in manufacturing sector:A rough Multi-Criteria decision making approach
Get PDFThe concept of the circular economy (CE) is becoming increasingly important for a sustainable future in business. All industries should focus on adopting the principles of the circular economy and evaluating the performance of their suppliers according to these principles. However, evaluating supplier performance with a circular approach requires a complex decision-making process due to the limited scope of available criteria and the uncertainties in expert opinions. This study proposes a new hybrid approach to multi-criteria decision making (MCDM) based on a comprehensive criteria structure that includes technological, operational and strategical factors to overcome these limitations. The Rough Ordinal Priority Approach (R-OPA) method was used to determine the weighting coefficients of the criteria. A new method, the Alternative Ranking Order Method Accounting for Two-Step Normalization (R-AROMAN), was extended and used for the first time in evaluating supplier performance based on rough numbers. The integration of rough numbers in MCDM methods facilitates the handling of uncertainties associated with the problem. The proposed model is applied to a case study in a manufacturing company, the results are compared with other MCDM methods and the stability of the method is verified by a sensitivity analysis. This comprehensive approach enables decision-makers to manage uncertainty and make more effective strategic decisions in circular supplier selection.</p