This dissertation computationally and analytically investigates ways to model solar cells when the lateral motion of charge carriers and light are relevant. We focus on back-contact perovskite solar cells, and assessing the experimental technique of scanning photocurrent microscopy as a means to investigate them. Solar cells are three-dimensional objects frequently modelled as being one-dimensional. However, for more complex designs of solar cell or if the cell is only point-illuminated, one-dimensional modelling is insufficient. In the first study, some conditions for reducing the complexity of two-dimensional drift-diffusion simulations are investigated for a back-contact perovskite cell. Analytic expressions for the relationship in both the low extraction velocity and high extraction velocity regimes are demonstrated, and the conditions where these approximations break down are investigated. These findings are then applied a point-excited film with an extended electrode, a problem encountered during scanning photocurrent microscopy. We show the current recorded in this case should decay exponentially with the distance between excitation and electrode, with a decay constant that can be related to device parameters. The characteristic equilibration time for the system to reach this current is demonstrated to increase linearly with distance. Between this gradient and the exponent, information about the diffusion and recombination mechanics can be extracted from a variety of systems. Photon recycling is the process in whereby photogenerated carriers recombine to generate light that is absorbed again within the solar cell. In the second section, we apply the findings of the first section to show that experimental results published elsewhere are best explained by photon recycling in methylammonium lead iodide perovskite back-contact solar cells. However we do not have an established theoretical model for long-ranged lateral optical transport in these solar cells. Three models are developed: a bimolecular model for unscattered, coherent transport; a photon diffusion model for frequently scattered, noncoherent light; and a monomolecular, assisted-diffusion model. The modal nature of coherent optical transport is considered and modifications to previous one-dimensional theories are made. The nature of the photon diffusion model is discussed, as are theoretical shortcomings. All three models are then solved numerically and compared to experimental results. The low-scattering photon diffusion models correspond well to the experiment. The third investigation involves the performance of different architectures of back-contact perovskite cells. These cells potentially offer increased current due to less shadowing by front electrodes. We compare them to each other and to traditional vertical structures. It is found that, in terms of internal transport, the back-contact solar cells give less efficient performance than the vertical design. The best of the back-contact cells investigated is a flat interdigitated design. The increase in efficiency from optical factors would have to exceed 10% for the overall efficiency of back-contact cells to be higher than vertical devices. We also develop a model of photon recycling appropriate for short-ranged, bulk 2D transport and demonstrate that in perovskites, it produces little change in power conversion efficiency (and small changes in short-circuit voltage) when compared with the standard drift-diffusion equations with the second-order recombination constant is adjusted.

In tasks with more than one path to succeed, it is possible that participants’ strategies vary and therefore, participants should not be analyzed as a homogeneous group. This thesis investigates individual differences in a two-dimensional categorization task with redundancy (i.e., a task where any of the two dimensions by itself suffices for perfect performance). Individual differences in learned knowledge and used knowledge are considered and studied. Participants first performed a categorization task with redundancy (training phase), and afterward were asked to do categorizations in which the previously redundant knowledge becomes decisive (testing phase). Using the data from the testing phase, dimension(s) learned by each participant were determined and the response patterns of each participant in the training phase was used to determine which dimension(s) were used. The used knowledge was assessed using two separate analyses, both of which look at accuracy and response time patterns, but in different ways. Analysis 1 uses iterative decision bound modeling and RT-distance hypothesis and Analysis 2 uses the stochastic version of general recognition theory. In Analysis 1, more errors and slower response times close to a decision bound perpendicular to a dimension indicate that a participant is using that dimension. Analysis 2 goes a step further and in addition to determining which dimension(s) are used, specifies in what way they were used (i.e., identifying the strategy of each participant). Possible strategies are described heuristically (unidimensional, time efficient and conservative) and then each heuristic is translated into a drift diffusion model by the unique way that strategy is assumed to affect trial-by-trial difficulty of the task. Finally, a model selection criterion is used to pick the strategy that is used by each participant.

L’homme est un animal social. La majorité des décisions que nous prenons se font dans un contexte social et dépendent d’autrui, ce qui implique des calculs cérébraux complexes qui incluent tous les facteurs contextuels et environnementaux. La majorité des études ultérieures de la prise en compte d’autrui dans la décision ont utilisé des tâches de partage de récompenses entre soi et autrui. Les choix possibles amènent le décideur à considérer autrui, mais dans le but de gagner soi-même une récompense ; donc dans un contexte où les récompenses liées à soi et les récompenses liées à autrui sont confondues. Le travail présenté dans cette thèse avait pour but une meilleure compréhension des mécanismes cérébraux soutenant l’intégration d’autrui dans la prise de décision, sans que la récompense pour autrui n’interfère directement avec soi. Nous nous sommes appuyés sur le cadre théorique de la décision perceptuelle et des modèles de diffusion pour l'étude i) des modifications du processus décisionnel induites par une récompense monétaire allant à autrui et ii) de l’impact de l’effet d’audience (le fait de se sentir observé) sur la décision. Nos résultats computationnels montrent qu'une récompense pour autrui, par rapport à une récompense pour soi, et une audience, par rapport au secret, modifient le taux de dérive de la variable de décision. En magnétoencéphalographie, nos résultats indiquent que les décisions pour soi et pour autrui diffèrent pendant, mais aussi après, la prise de décision dans des zones cérébrales associées avec la transformation sensori-motrice, l'ajustement du compromis entre rapidité et justesse et avec la cognition sociale. Ainsi, le cortex temporal montre des différences de -1170 millisecondes (ms) à -1023 ms, de -993 ms à -915 ms et de -343 ms à -188 ms en amont de la réponse. Ce qui suppose une influence sur l’intégration des preuves sensorielles. Après la décision, les régions frontales ont également montré des différences entre soi et autrui, de 153 ms à 303 ms post-réponse, suggérant une différence entre soi et autrui dans l’ajustement du compris entre justesse et rapidité. Le bénéficiaire de la récompense associée à la décision modifie les paramètres décisionnels et les corrélats cérébraux de la décision perceptuelle, démontrant l’importance du contexte social dans l’implémentation de la prise de décision chez l’Homme. Ce travail appuie également l’utilité des modèles mathématiques tels que les modèles de diffusion dans la compréhension des processus décisionnels, même de ceux découlant de la cognition sociale / Humans are inherently social: most of human’s decisions are within a social context and depend on others. For more than a century, researchers explore aspects of social cognition. Aiming to understand human behavior in social contexts, neuro-economic researches showed that taking others into account involve complex brain computations that include all environmental and contextual factors. However, most of the work was made using money allocation tasks; mixing self-affecting and other-affecting rewards into the decision making process. The present work intended the understanding of the brain mechanisms underpinning the integration of others into the decision making process for decisions that include others and do not interfere with self-rewards.Taking advantage of mathematical models from the drift diffusion models framework, we conducted experiments investigating how others influence the mechanistic of perceptual decisions and their correlates in the human brain. We showed that taking rewards for others into account and being observed by others influence the drift rate of the decision variable. The drift rate is higher in audience than in secret and higher for self-rewards than for other-rewards. These results indicate that others are integrated into the accumulation process together with the evidence available for making a decision. At the brain level, we found difference between self and other decisions over the anterior temporal and centro-frontal cortices during decision making. This suggests that the beneficiary of a decision modifies sensory-motor transformation processes. In addition, self- and other-affecting difference showed difference over the medial frontal sensors after the decision making process, indicating a variation in the speed-accuracy tradeoff adjustment process