Highly Conductive In-SnO2/RGO Nano-Heterostructures with Improved Lithium-Ion Battery Performance

The increasing demand of emerging technologies for high energy density electrochemical storage has led many researchers to look for alternative anode materials to graphite. The most promising conversion and alloying materials do not yet possess acceptable cycle life or rate capability. In this work, we use tin oxide, SnO2, as a representative anode material to explore the influence of graphene incorporation and In-doping to increase the electronic conductivity and concomitantly improve capacity retention and cycle life. It was found that the incorporation of In into SnO2 reduces the charge transfer resistance during cycling, prolonging life. It is also hypothesized that the increased conductivity allows the tin oxide conversion and alloying reactions to both be reversible, leading to very high capacity near 1200 mAh/g. Finally, the electrodes show excellent rate capability with a capacity of over 200 mAh/g at 10C

Modèles et méthodes efficaces pour des problèmes stochastiques des lignes de désassemblage

L'étude du désassemblage des produits en fin de vie (EOL) sous incertitude est un sujet de recherche important en raison de ses avantages en termes de réduction de déchets, d'économie de ressources non-renouvelables et de protection de l'environnement. Les travaux existants sur les lignes de désassemblage supposent que l'information incertaine peut être estimée par des lois de probabilité ou par des fonctions et se focalisent seulement sur des problèmes stochastiques d'équilibrage de ces lignes. Cependant, il n'est pas toujours possible d'obtenir l'information incertaine complète dû à un manque de données historiques ou d'un volume excessif de données. De plus, le problème intégré des lignes de désassemblage a rarement été abordé. Dans cette thèse, quatre nouveaux problèmes stochastiques des lignes de désassemblage avec seulement à disposition l'information incertaine partielle sont investigués. L'objectif est de proposer des modèles et des méthodes efficaces pour ces problèmes. Les principaux travaux apportés par cette thèse sont les suivants :Premièrement, un nouveau problème stochastique d'équilibrage des lignes de désassemblage (SDLBP) est étudié dans le but de minimiser le coût des lignes avec les durées incertaines d'exécution des tâches, en ne tenant compte que de la moyenne, de l'écart-type et de la borne supérieure du taux de changement. Un modèle avec chance-contrainte est d'abord établi, qui est par la suite transformé approximativement en un modèle distribution-free basé sur l'analyse des propriétés. Ensuite, une heuristique est développée pour résoudre le modèle transformé. Des résultats expérimentaux montrent que le modèle distribution-free peut résoudre efficacement ce SDLBP avec de l'information incertaine partielle.Dans la plupart des travaux existants, le temps de cycle qui représente le temps d'achèvement maximal des postes de travail est prédéterminé. Cependant, le coût des lignes de désassemblage et le temps de cycle sont deux critères de performance contradictoires et s'impactent mutuellement. Un nouveau SDLBP bi-objectif est investi pour minimiser le coût des lignes et le temps de cycle, où seule l'information partielle des durées des tâches est requise. Un modèle bi-objectif distribution-free est construit et une méthode ε-contrainte améliorée est conçue. Des expériences montrent que la méthode ε-contrainte proposée peut réduire de plus de 90% le nombre d'itérations par rapport à la méthode ε-contrainte classique.Ces lignes pourraient générer des pollutions pendant le processus de désassemblage des produits EOL, néanmoins ce facteur n'a pas été considéré dans les précédents travaux. Nous nous intéressons à un nouveau SDLBP vert afin de minimiser le coût des lignes et la pollution, dans lequel des postes de travail avec des prix d'achat différents peuvent générer des quantités différentes de pollution. Un nouveau modèle bi-objectif est formulé et une méthode ε-contrainte spécifique au problème est proposée. Des résultats expérimentaux révèlent qu'un choix approprié des postes de travail peut effectivement réduire la pollution d'une ligne de désassemblage.L'optimisation intégrée d'équilibrage et de planification des lignes de désassemblage, qui n'a pas été étudiée auparavant, pourrait améliorer l'efficacité du système de désassemblage et réduire ses dépenses. Un problème stochastique intégré d'équilibrage et de planification des lignes de désassemblage (ISDLBPP) est adressé pour minimiser le coût global du système, où les ratios d'obtention des composantes et leur demande sont supposés être incertains. Une programmation stochastique à deux étapes est construite et des inégalités valides sont proposées pour réduire l'espace de recherche. Puis, des méthodes sample average approximation (SAA) et L-shaped sont proposées pour ce problème. Des expériences montrent que le temps de calcul moyen de la méthode L-shaped est seulement de 60% de celui de la méthode SAA, avec une qualité de solution comparable.Studying the disassembly of End-of-Life (EOL) products under uncertainty is becoming a hot research topic due to its benefits in reducing waste, saving non-renewable resources, and protecting the environment. Existing disassembly line works assume that stochastic information can be estimated as probability distributions or functions and most of them focus on stochastic disassembly line balancing problems. However, it is not always possible to obtain complete stochastic information due to a lack of historical data or excessive data volume, and the integrated disassembly line problem has been rarely addressed. In this thesis, four novel stochastic disassembly line problems with only partial stochastic information are investigated. The purpose is to propose effective models and solution methods for the considered problems. The main works of this thesis are:Firstly, a new stochastic disassembly line balancing problem (SDLBP) is studied to minimize the disassembly line cost under stochastic task processing times, given only the mean, standard deviation, and change-rate upper bound. For the problem, a chance-constrained model is first formulated, which is further approximately transformed into a distribution-free model by property analysis. Then, a fast heuristic is devised to solve the transformed model. Experimental results demonstrate that the distribution-free model can effectively solve the SDLBP with only partial stochastic information.In most existing literature, the cycle time that represents the maximum completion time among workstations is given. However, the disassembly line cost and cycle time are two conflicting performance criteria and impact mutually. In this thesis, a new bi-objective distribution-free SDLBP is studied to minimize the disassembly line cost and cycle time, where partial information of task processing times is required. For the problem, a bi-objective distribution-free model is constructed, and an improved ε-constraint method is designed. Numerical experiments show that the proposed method can reduce more than 90% computation rounds, compared with the basic ε-constraint method.Disassembly lines may generate pollution during separating EOL products, but this factor has not been considered in the previous SDLBP works. In this thesis, we study a new green-oriented distribution-free SDLBP to minimize the disassembly line cost and pollution emission simultaneously, in which workstations with different purchase prices can have different amounts of pollution emissions. For the problem, a new bi-objective model is formulated and a problem-specific ε-constraint method is devised. Experimental results show that selecting appropriately workstations can effectively reduce the pollution emission of a disassembly line. Besides, some managerial insights are discussed.The integrated optimization of disassembly line balancing and planning may enhance the efficiency of the disassembly system and reduce its expenses, which has not been studied before. In this thesis, an integrated stochastic disassembly line balancing and planning problem (ISDLBPP) is addressed to minimize the overall system cost, where component demands and component yield ratios are assumed to be uncertain. For the problem, a two-stage stochastic programming model is established and valid inequalities are devised to reduce the search space. Then, the sample average approximation (SAA) method and the L-shaped method are applied to solve the model. Numerical experiments show that the L-shaped method can save more than 60% computation time than the SAA method, without sacrificing solution quality

Synthesis and Characterization of Transition Metal Oxide/Hydroxide-Based Functional Materials for Environmental and Energy Applications

In this thesis, transition metal oxide/hydroxide-based functional nanomaterials with specific structures and properties are developed and characterized for targeting applications in environmental pollution abatement and energy conversion and storage. In the first part, graphene supported Co3O4 composite is synthesized in one-step using a facile microwave-assisted method. Graphene serves as the substrate, providing high surface area, good conductivity, and good mechanical and chemical durability. The wide pore size distribution, synergistic effect, and high surface area of the composite are found to contribute to the high performance of lithium-ion batteries. In the second part, we focused on the synthesis of a series of heterogeneous electrocatalysts based on graphene coupled mixed-metal (oxy)hydroxides containing specific concentrations of nickel, cobalt, and iron to investigate the influence of metal composition on the structure, properties, and activities for the oxygen evolution reaction (OER). Characterization results indicate iron incorporation induced structural disorder, ultra-small nanosheets, and high surface area of metal (oxy)hydroxides. In addition, the trend in Tafel slopes is related to the abundance of surface adsorbed hydroxyl groups. Density functional theory (DFT) calculations demonstrate electronic structure and free energy change of ternary metal oxyhydroxide enhance the energetics for OER electrocatalysis. The optimized ternary metal oxyhydroxide exhibits superior OER electrocatalytic activity than the state-of-the-art IrO2 catalyst. In the third part, we further developed unique mesoporous NiO/MnO2 in one step using modified UCT (University of Connecticut) methods. Both the OER and the oxygen reduction reaction (ORR) electrocatalytic activities and stabilities in alkaline media are promoted after further coating with polyaniline (PANI). Many factors are found to contribute to the improved catalytic activity, for example, accessible mesoporous structure, high surface area, core-shell structure, and good electrical conductivity. Beside the development of nanomaterials for renewable energy, we also created novel catalysts for environmental pollution abatement. Last but not least, a series of manganese oxide-based core-shell nanoarrays are integrated on the cordierite monolithic substrates. Different manganese-cobalt oxide core-shell nanoarrays are further evaluated due to the high activity for CO oxidation. This fast, cost-effective, and scalable method will provide a new route for synthesizing efficient core-shell nanoarray monolithic catalysts for low temperature catalysis

Infrared and infrared emission spectroscopic study of typical Chinese kaolinite and halloysite

The structure and thermal stability between typical China kaolinite and halloysite were analysed by X-ray diffraction (XRD), infrared spectroscopy, infrared emission spectroscopy (IES) and Raman spectroscopy. Infrared emission spectroscopy over the temperature range of 300 to 700 °C has been used to characterise the thermal decomposition of both kaolinite and halloysite. Halloysite is characterised by two bands in the water bending region at 1629 and 1648 cm-1, attributed to structure water and coordinated water in the interlayer. Well defined hydroxyl stretching bands at around 3695, 3679, 3652 and 3625 cm-1 are observed for both kaolinite and halloysite. In the 550 °C infrared emission spectrum of halloysite is similar to that of kaolinite in 650-1350 cm-1 region. The infrared emission spectra of halloysite were found to be considerably different to that of kaolinite at lower temperatures. This difference is attributed to the fundamental difference in the structure of the two minerals

A distribution-free model for a disassembly line design problem under uncertain environment

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Thermogravimetric analysis-mass spectrometry (TG-MS) of selected Chinese kaolinites

Thermogravimetric analysis-mass spectrometry, X-ray diffraction and scanning electron microscopy (SEM) were used to characterize eight kaolinite samples from China. The results show that the thermal decomposition occurs in three main steps (a) desorption of water below 100 °C, (b) dehydration at about 225 °C, (c) well defined dehydroxylation at around 450 °C. It is also found that decarbonization took place at 710 °C due to the decomposition of calcite impurity in kaolin. The temperature of dehydroxylation of kaolinite is found to be influenced by the degree of disorder of the kaolinite structure and the gases evolved in the decomposition process can be various because of the different amount and kinds of impurities. It is evident by the mass spectra that the interlayer carbonate from impurity of calcite and organic carbon is released as CO2 around 225, 350 and 710 °C in the kaolinite samples

A green-oriented bi-objective disassembly line balancing problem with stochastic task processing times

International audienceRemanufacturing and recycling industry has developed rapidly in recent years due to its benefits in reducing waste and protecting the environment. However, the uncertain environment and excessive emission during production become two main obstacles for its further development. In this paper, a green-oriented bi-objective disassembly line balancing problem with stochastic task processing times is studied. The objectives are to minimize the total line configuration cost respecting the given budget, and minimize the total contaminant emission, respectively. To depict stochastic processing times, their mean, standard deviation and change-rate upper bound are assumed to be known since it may be difficult to obtain the complete historical data. For the problem, a bi-objective model with chance constraints is first formulated, which is further approximated into a linear distribution-free one. To solve the second model, an efficient ε-constraint method is proposed based on problem analysis. Finally, a fuzzy-logic-based approach is applied to recommend preferred solutions for managers according to their perspectives. The solution methods are first examined by a case study, then by 247 benchmark-based instances and randomly generated instances. Experimental results indicate the efficiency and effectiveness of the proposed methods for solving the green-oriented bi-objective problem

Scheduling multiple yard cranes in two adjacent container blocks with position-dependent processing times

International audienceThis paper studies the management of three yard cranes in two adjacent container blocks in line, where cranes can move from one block to the other. Comparing with existing literature, the new multi-yard-crane scheduling problem incorporates different constraints together: (i) three yard cranes are deployed simultaneously in two adjacent blocks, (ii) non-crossing and inter-crane interference constraints of yard cranes are considered, (iii) the processing time of each container depends on its real-time location, i.e., position-dependent processing times. For the problem, a 0–1 mixed integer programming (MIP) model is constructed to minimize the total flow time to reduce the total container storage time in container yards, which helps to save container yard resources and increase production efficiency. The proposed model can be solved optimally by CPLEX for small-size instances. As the concerned problem is NP-hard, a fast heuristic and an improved genetic algorithm are devised to produce near-optimal solutions for large-size instances. Numerical experiments validate the developed MIP model and demonstrate the efficiency of the proposed algorithms