Lean burn engines are more fuel efficient than standard stoichiometric-burn engines but at the same time, the conventional three-way catalyst is not effective in reducing the NOx in oxygen-rich exhaust. One of the recent advancements in exhaust after treatment technologies for lean burn engines is the NOx storage and reduction (NSR) methodology. In this mechanism, NOx is stored on the storage component of a NSR catalyst during normal engine operation. However, before the catalyst reaches its saturation capacity, an excess of fuel is injected to the engine for a very short period resulting in reductant rich exhaust and during this period, NOx is released and subsequently reduced to N2, therefore, restoring the storage capacity of the catalyst. The operation is cyclic in nature, with the engine operating between an oxygen rich feed for long periods and a fuel rich feed for relatively shorter periods. To implement this technology in the most efficient way, a detailed understanding of the NSR chemistry under different operating conditions is required. For the past few years, several authors have studied the NSR systems using both experimental and modeling techniques. However, most of the models proposed in the literature were calibrated against the steady cyclic operation where the NOx profiles are similar for each cycle. In real life situations, the engine operation changes with different driving conditions, occurring due to sudden acceleration, roads in hilly areas, non-uniform braking, etc., which results in operation with a number of different transient cycle-to-cycle regimes depending upon the frequency with which the engine operation is altered. Due to such varying conditions, it is very important to investigate the significance of transients observed between the two different steady cycle-to-cycle operations for the optimization and control purposes. Also, the models in the literature are specific to the catalyst used in the study and therefore, their adaptation to other NSR catalysts is not straightforward. Therefore, one of the main motivations behind this research work is to develop a general approach to explain the storage dynamics. Moreover, the existing models have not studied the regeneration mechanisms, which is very important to explain the cyclic data in complete operation including both transients and steady state cycles. In this study, a pseudo one-dimensional model of a commercial NOx storage/release (NSR) catalyst is presented. The NOx storage is considered to be mass transfer limited, where as the storage proceeds, the barium carbonate particle is converted into the nitrate and for further storage, the NOx has to diffuse through this growing nitrate layer and a after certain depth, this penetration becomes nearly impossible. To explain the transient nature of the cyclic NOx profile, it is hypothesized that when incomplete regeneration occurs, only part of the nitrate is converted back to carbonate. Therefore, the nitrate layer increases in thickness with each cycle, thus making further storage increasingly more difficult. The shrinking core concept with incomplete storage in the lean phase followed by incomplete regeneration of the nitrate layer during the regeneration phase accounts for a net drop in storage capacity of the catalyst in each cycle, which continues decreasing until the amount of sites regenerated equal the amount used in NOx storage. The number of unknown parameters used for fitting were reduced by parameter sensitivity analysis and then fitted against a NOx profile at the reactor exit. The overall amount of NOx that can be stored in the lean phase of the cycle depends on the extent of regeneration that can be achieved during the previous rich phase, which in turn depends directly on the concentration of reductants in the feed. Therefore, there is a trade-off between the amount of fuel used and the NOx emissions. The proposed model can be potentially used to improve this trade-off by using model-based optimization techniques.

Lean burn engines are more fuel efficient than standard stoichiometric-burn engines but at the same time, the conventional three-way catalyst is not effective in reducing the NOx in oxygen-rich exhaust. One of the recent advancements in exhaust after treatment technologies for lean burn engines is the NOx storage and reduction (NSR) methodology. In this mechanism, NOx is stored on the storage component of a NSR catalyst during normal engine operation. However, before the catalyst reaches its saturation capacity, an excess of fuel is injected to the engine for a very short period resulting in reductant rich exhaust and during this period, NOx is released and subsequently reduced to N2, therefore, restoring the storage capacity of the catalyst. The operation is cyclic in nature, with the engine operating between an oxygen rich feed for long periods and a fuel rich feed for relatively shorter periods. To implement this technology in the most efficient way, a detailed understanding of the NSR chemistry under different operating conditions is required. For the past few years, several authors have studied the NSR systems using both experimental and modeling techniques. However, most of the models proposed in the literature were calibrated against the steady cyclic operation where the NOx profiles are similar for each cycle. In real life situations, the engine operation changes with different driving conditions, occurring due to sudden acceleration, roads in hilly areas, non-uniform braking, etc., which results in operation with a number of different transient cycle-to-cycle regimes depending upon the frequency with which the engine operation is altered. Due to such varying conditions, it is very important to investigate the significance of transients observed between the two different steady cycle-to-cycle operations for the optimization and control purposes. Also, the models in the literature are specific to the catalyst used in the study and therefore, their adaptation to other NSR catalysts is not straightforward. Therefore, one of the main motivations behind this research work is to develop a general approach to explain the storage dynamics. Moreover, the existing models have not studied the regeneration mechanisms, which is very important to explain the cyclic data in complete operation including both transients and steady state cycles. In this study, a pseudo one-dimensional model of a commercial NOx storage/release (NSR) catalyst is presented. The NOx storage is considered to be mass transfer limited, where as the storage proceeds, the barium carbonate particle is converted into the nitrate and for further storage, the NOx has to diffuse through this growing nitrate layer and a after certain depth, this penetration becomes nearly impossible. To explain the transient nature of the cyclic NOx profile, it is hypothesized that when incomplete regeneration occurs, only part of the nitrate is converted back to carbonate. Therefore, the nitrate layer increases in thickness with each cycle, thus making further storage increasingly more difficult. The shrinking core concept with incomplete storage in the lean phase followed by incomplete regeneration of the nitrate layer during the regeneration phase accounts for a net drop in storage capacity of the catalyst in each cycle, which continues decreasing until the amount of sites regenerated equal the amount used in NOx storage. The number of unknown parameters used for fitting were reduced by parameter sensitivity analysis and then fitted against a NOx profile at the reactor exit. The overall amount of NOx that can be stored in the lean phase of the cycle depends on the extent of regeneration that can be achieved during the previous rich phase, which in turn depends directly on the concentration of reductants in the feed. Therefore, there is a trade-off between the amount of fuel used and the NOx emissions. The proposed model can be potentially used to improve this trade-off by using model-based optimization techniques.

L'objectif de ce travail de thèse est de participer à l'élaboration de nanocristaux (NCs) de germanium et de mettre en évidence certaines propriétés de structures Si(n)/SiO2 contenant ces NCs non recouverts sur leur surface par l'utilisation de la technique nano-EBIC (courant induit par bombardement électronique et collecté par un nano-contact). La particularité de cette technique basée le même principe que l'EBIC classique est l'utilisation d'une pointe AFM conductrice à la place de l'électrode standard. Nous avons particulièrement ciblé le comportement d'un NC (ou d'un nombre très réduit de NCs) à piéger et émettre des porteurs de charge suite à un bombardement électronique non continu. La structure contenant les NCs peut être polarisée sous une tension nulle (alignement des niveaux de Fermi) ou sous une tension faible. Suite à cette procédure, des durées de charge ont été mesurées et les valeurs se trouvent dépendre de la taille moyenne des NCs. En effet, le processus de charge est plus long dans un NC de petite taille du fait de sa faible efficacité de stockage. D'un autre côté, le courant collecté présente une valeur de saturation plus élevée dans le cas des petits NCs. Ces deux effets (durée élevée et courant de saturation élevé dans les petits NCs) ont été expliqués par l'abaissement de la barrière d'énergie au niveau du contact pointe/NC qui résulte de l'élargissement du gap du NC et de l'augmentation du champ électrique dans la couche d'oxyde et dans la zone de désertion du substrat de silicium sous une tension de polarisation donnée. Enfin, la procédure, par son originalité, a aussi permis d'accéder à la résistivité électrique de la couche d'oxyde mince (5 nm). / The objective of this work is to contribute to the production of germanium nanocrystals (NCs) and to highlight some electronic properties of Si(n)/SiO2 structures containing those uncovered NCs on top thanks to the nano-EBIC technique (electron beam induced current collected by a nano-contact). The distinctive feature of this technique based on classic EBIC is the use of an AFM conducting probe instead of the standard electrode. Our study focuses on the capability of a single NC (or a few number of NCs) to trap and to release charge carriers as a result of a non-continuous electronic irradiation. The structure containing NCs can be connected to the ground (ensuring the Fermi levels alignment) or polarized under a low voltage. With this procedure, carriers charging times had been measured and their values depend on the mean diameter of the NCs. Indeed, the charging process takes more time in small NCs due to their weak storage efficiency. Nonetheless, the collected current reaches a higher saturation value in small NCs. Both of these effects (large charging time and high saturation current for small NCs) are explained by the lowering of the energy barrier at the AFM-tip/NCs contact, which results from the widening band-gap of NCs and the increase of the electric field across the oxide and in the Si depletion zone at a given bias voltage for small NCs. At last, this novel procedure allows measuring the electric resistivity of the 5 nanometers thin oxide.

The main goal of this dissertation is to develop a seasonal water balance model for evaporation, runoff and water storage change based on observations from a large number of watersheds, and further to obtain a comprehensive understanding on the dominant physical controls on intra-annual water balance. Meanwhile, the method for estimating evaporation and water storage based on recession analysis is improved by quantifying the seasonal pattern of the partial contributing area and contributing storage to base flow during low flow seasons. A new method for quantifying seasonality is developed in this research. The difference between precipitation and soil water storage change, defined as effective precipitation, is considered as the available water. As an analog to climate aridity index, the ratio between monthly potential evaporation and effective precipitation is defined as a monthly aridity index. Water-limited or energy-limited months are defined based on the threshold of 1. Water-limited or energy-limited seasons are defined by aggregating water-limited or energy-limited months, respectively. Seasonal evaporation is modeled by extending the Budyko hypothesis, which is originally for mean annual water balance; while seasonal surface runoff and base flow are modeled by generalizing the proportionality hypothesis originating from the SCS curve number model for surface runoff at the event scale. The developed seasonal evaporation and runoff models are evaluated based on watersheds across the United States. For the extended Budyko model, 250 out of 277 study watersheds have a Nash-Sutcliff efficiency (NSE) higher than 0.5, and for the seasonal runoff model, 179 out of 203 study watersheds have a NSE higher than 0.5. Furthermore, the connection between the seasonal parameters of the developed model and a variety of physical factors in the study watersheds is investigated. For the extended Budyko model, vegetation is identified as an important physical factor that related to the seasonal model parameters. However, the relationship is only strong in water-limited seasons, due to the seasonality of the vegetation coverage. In the seasonal runoff model, the key controlling factors for wetting capacity and initial wetting are soil hydraulic conductivity and maximum rainfall intensity respectively. As for initial evaporation, vegetation is identified as the strongest controlling factor. Besides long-term climate, this research identifies the key controlling factors on seasonal water balance: the effects of soil water storage, vegetation, soil hydraulic conductivity, and storminess. The developed model is applied to the Chipola River watershed and the Apalachicola River basin in Florida for assessing potential climate change impact on the seasonal water balance. The developed model performance is compared with a physically-based distributed hydrologic model of the Soil Water Assessment Tool, showing a good performance for seasonal runoff, evaporation and storage change.