The dynamics of colloidal particles driven over optical potential energy landscapes is studied. Experiments are conducted using colloids driven by solvent flow or piezo-stage, optical tweezers, magnetic fields, and video-microscopy. Firstly, the properties of optical traps and potential energy landscapes are determined using driven colloidal particles and clusters. The trap stiffness and potential depth of single Gaussian traps are measured directly. It is shown that the nature of optical potential energy landscapes may be fully engineered and predicted using a sum of single Gaussian potentials. Next, the motion of colloidal particles driven by a constant force over a periodic optical potential energy landscape is considered. The average particle velocity is found as a function of the driving velocity, and the wavelength of the optical potential energy landscape, which is found to be sinusoidal at small trap spacings. The critical driving velocity required for a particle to move across the landscape is determined as a function of the wavelength. Brownian motion is found to have a significant effect on the critical driving velocity, but a negligible effect at high driving velocity. Subsequently, the dynamic mode locking caused by adding a modulation to the driving force is studied. This synchronisation manifests as a `Devil's staircase' in the average particle velocity as a function of driving velocity. The amplitude and frequency dependence of the mode locked steps are studied. Furthermore, particle trajectories are examined, and phase portraits show locked (unlocked) states as closed (open) loops in phase space. A state diagram of mode locked steps is constructed. Finally, driven systems of magnetically interacting colloidal particles are examined in potential energy landscapes. The critical driving velocity of a chain of coupled particles driven by a constant force is found to depend strongly on the chain length and the magnetic field. Secondly, a mobile density wave (kink) in an optically pinned chain of coupled particles is exposed to a constant and modulated drive. The kink is found to behave as a quasi-particle, exhibiting analogous dynamic mode locking behaviour to the single particle case. Finally, the mode locking of a finite mobile chain is considered, and found to be affected by the chain flexibility, which is a function of the magnetic field.

The study of supercooled liquids and glasses remains one of the most divisive and divided fields in modern physics. Despite a vast amount of effort and research time invested in this topic, the answers to many central questions remain disputed and incomplete. However, the link between the behaviour of supercooled liquids and their energy landscapes is well established and widely accepted. Understanding this link would be a key step towards resolving many of the mysteries and controversies surrounding the glass transition. Therefore the study of glassy energy landscapes is an important area of research. In this thesis, I report some of the most detailed computational studies of glassy potential energy landscapes ever performed. Using geometry optimisation techniques, I have sampled the local minima and saddle points of the landscapes for several supercooled liquids to analyse their dynamics and thermodynamics. Some of my analysis follows previous work on the binary Lennard-Jones fluid (BLJ), a model atomic liquid. BLJ is a fragile glass former, meaning that its transport coefficients have super-Arrhenius temperature dependence, rather than the more usual Arrhenius behaviour exhibited by strong liquids. The difference in behaviour between these two classes of liquid has previously been attributed to differing degrees of structure in the relevant energy landscapes. I have studied models for both fragile and strong glass formers: the molecular liquid ortho-terphenyl (OTP) and viscous silica (SiO$_{2}$) respectively. My results for OTP agree closely with trends observed for BLJ, suggesting that the same diffusion mechanism is applicable to fragile molecular liquids as well as to atomic. However, the dynamics and energy landscape of OTP are made complicated by the molecular orientational degrees of freedom, making the analysis more challenging for this system. Dynamics of BLJ, OTP and silica are all dominated by cage-breaking events: structural rearrangements in which atoms change their nearest neighbours. I propose a robust and general method to identify cage breaks for small rigid molecules, and compare some properties of cage breaks between strong and fragile systems. The energy landscapes of BLJ and OTP both display hierarchical ordering of potential energy minima into metabasins. These metabasins can be detected by the cage-breaking method. It has previously been suggested that metabasins are responsible for super-Arrhenius behaviour, and are absent from the landscapes of strong liquids such as SiO2. My results indicate that metabasins are present on the silica landscape, but that they each contain fewer minima than metabasins in BLJ or OTP. Metabasins are associated with anticorrelated particle motion, mediated by reversed transitions between minima of the potential energy landscape. I show that accounting for time-correlation of particle displacement vectors is essential to describe super-Arrhenius behaviour in BLJ and OTP, but also required to reproduce strong behaviour in silica. I hypothesise that the difference between strong and fragile liquids arises from a longer correlation timescale in the latter case, and I suggest a number of ways in which this proposition could be tested. I have investigated the effect on the landscape of freezing the positions of some particles in a BLJ fluid. This “pinning” procedure induces a dynamical crossover that has been described as an equilibrium “pinning transition”, related to the hypothetical ideal glass transition. I show that the pinning transition is related to (and probably caused by) a dramatic change in the potential energy landscape. Pinning a large fraction of the particles in a supercooled liquid causes its energy landscape to acquire global structure and hence structure-seeking behaviour, very different from the landscape of a typical supercooled liquid. I provide a detailed description of this change in structure, and investigate the mechanism underlying it. I introduce a new algorithm for identifying hierarchical organisation of a landsape, which uses concepts related to the pinning transition but is applicable to unpinned liquids as well. This definition is complementary to metabasins, but the two methods often identify the same higher-order structures. The new “packings” algorithm offers a route to test thermodynamic theories of the glass transition in the context of the potential energy landscape. Over the course of this thesis, I discuss several different terms and methods to identify higher-order structures in the landscapes of model glass formers, and investigate how this organisation varies between different systems. Although little variation is immediately apparent between most glassy landscapes, deeper analysis reveals a surprising diversity, which has important implications for dynamical behaviour in the vicinity of the glass transition.

De récentes études expérimentales de la dynamique de colloïdes illuminés par une figure d'interférence optique aléatoire (tavelures ou speckle) ont montré l'existence de phénomènes de sous-diffusion, de piégeage, ou de ségrégation dans le cas de mélanges, sous l'effet de cet environnement désordonné. L'objet de ce travail de doctorat est d'approfondir la compréhension de ces phénomènes par une étude théorique. Dans ce but, une version de la théorie de couplage de modes (MCT), initialement développée pour les fluides confinés dans des solides poreux désordonnés, a été appliquée au cas d'un fluide plongé dans un potentiel aléatoire gaussien de covariance gaussienne. La résolution numérique des équations asymptotiques de cette théorie a permis la construction de diagrammes d'état, lesquels reproduisent, par exemple, le comportement réentrant non trivial de la diffusivité observé dans les expériences, dont une interprétation physique simple est proposée.Les résultats suggèrent en outre une forte dépendance de la dynamique du système par rapport à la longueur de corrélation du désordre. Une étude détaillée de la relaxation du fluide a été effectuée, dans le but d'apporter une compréhension de la dynamique à toutes les échelles de temps. En parallèle, il a été montré que de nombreuses approximations classiques utilisées dans le calcul des propriétés structurales des fluides conduisent à des résultats non physiques dans le cas présent.Finalement, un programme de simulation Monte Carlo a été développé, et les premiers résultats sont comparés à la théorie et aux expériences. / Recent experimental studies of the dynamics of colloids beamed by a random light pattern (speckle) showed the existence of subdiffusion, trapping, or mixture separation phenomena, under the action of that disordered environment.To this end, a version of the Mode Coupling Theory (MCT), initially developed for fluids in confinement in sol id porous matrices has been applied to the case of a fluid plunged in a random Gaussian potential with a Gaussian correlation function.The aim of this PhD work is to further improve the understanding of these phenomena by the addition of a theoretical study.The numerical resolution of the asymptotic equations of this theory leads to the construction o phase diagrams, which reproduce for example the non trivial reentrent behaviour of the diffusivity, observed in related experiments, for which a physical interpretation is proposed. Furthermore, results suggest a strong depend ence of the dynamics on the disorder correlation length. A detailed study of the relaxation of the fluid has been made, in order to bring an understandin( of the dynamics at ali timescales. Simultaneously, it has been showed that a number of common approximations used in the calculation of the structural properties of fluids lead in the present case to non-physical results. Finally, a Monte-Carlo simulation program has been developed, and the first results are compared to theory and experiments.

No description available.

Binding-sites which facilitate the transport of substrates across membranes are ubiquitous in membrane proteins. To understand this fundamental process in cells, we build up a synthetic membrane system consisting of microfluidic channels and colloidal particles. Holographic optical tweezers are used to modulate the potential energy landscape in those channels. We show how to extract the underlying energy potential by analysing local transition probabilities. Our method is applicable both to equilibrium systems and non-equilibrium steady states. Our method offers improved robustness when dealing with fragmented trajectories or small ensembles of data compared to other established approaches, such as probability density function and splitting probability. Meanwhile, we utilise the intensity distribution of the optical traps generated by holographic optical tweezers to estimate energy landscapes featuring high energy barriers where transitions rarely occur. We use this newly developed experimental system to mimic the functionality of membrane protein transporters that are known to alternate their substrate-binding sites between the extracellular and cytosolic side of the membrane. We study particle transport through a channel coupled with an energy well that oscillates its position between the two entrances of the channel deterministically and stochastically. Optimised particle transport across the channel is obtained by adjusting the oscillation frequency. At the optimal oscillation frequency, the translocation rate of particles through the channel is a hundred times higher with respect to free diffusion across the channel. Our findings reveal the effect of time dependent potentials on particle transport across a channel. This work adds a new tool for the investigation of highly controlled membrane transport processes at the micron scale. Our results are relevant for improving our understanding of membrane transport especially for microfluidics application.

In this dissertation, we describe a novel method that we call Diffusing Colloidal Probe Microscopy (DCPM), which integrates Total Internal Reflection Microscopy (TIRM) and Video Microscopy (VM) methods to monitor three dimensional trajectories in colloidal ensembles levitated above macroscopic surfaces. TIRM and VM are well established optical microscopy techniques for measuring normal and lateral colloidal excursions near macroscopic planar surfaces. The interactions between particle-particle and particle-substrate in colloidal interfacial systems are interpreted by statistical analyses from distributions of colloidal particles; dynamic properties of colloidal assembly are also determined from particle trajectories. Our studies show that DCPM is able to detect many particle-surface interactions simultaneously and provides an ensemble average measurement of particle-surface interactions on a homogeneous surface to allow direct comparison of distributed and average properties. A benefit of ensemble averaging of many particles is the diminished need for time averaging, which can produce orders of magnitude faster measurement times at higher interfacial particle concentrations. The statistical analyses (Ornstein- Zernike and three dimensional Monte Carlo analyses) are used to obtain particle-particle interactions from lateral distribution functions and to understand the role of nonuniformities in interfacial colloidal systems. An inconsistent finding is the observation of an anomalous long range particle-particle attraction and recovery of the expected DLVO particle-wall interactions for all concentrations examined. The possible influence of charge heterogeneity and particle size polydispersity on measured distribution functions is discussed in regard to inconsistent particle-wall and particle-particle potentials. In the final part of this research, the ability of DCPM is demonstrated to map potential energy landscapes on patterned surfaces by monitoring interactions between diffusing colloidal probes with Au pattern features. Absolute separation is obtained from theoretical fits to measured potential energy profiles and direct measurement by sticking silica colloids to Au surfaces via electrophoretic deposition. Initial results indicate that, as colloidal probe and pattern feature dimensions become comparable, measured potential energy profiles suffer some distortion due to the increased probability of probes interacting with surfaces at the edges of adjacent pattern features. Measurements of lateral diffusion via analysis of mean square displacements also indicated lateral diffusion coefficients in excellent agreement with rigorous theoretical predictions.

Comprendre l’origine microscopique du ralentissement de la dynamique au voisinage de la transition vitreuse reste l’un des problèmes fondamentaux de la physique de la matière condensée. Au cours de ce travail, nous introduisons un nouveau modèle de liquide, appelé liquide de Voronoï, et dont les interactions sont directement reliées aux propriétés géométriques des tessellations de Voronoï. Pour cette classe de liquides, les interactions sont à plusieurs corps et agissent de telle sorte que le système est toujours sous tension tout en restant stable. Le but de ce travail est d’étudier un mélange binaire du liquide de Voronoï et de voir de quelles façons ces interactions exotiques affectent le scénario habituel de la transition vitreuse. Tout au long de ce travail, nous caractérisons le liquide de Voronoï bidisperse théoriquement et par le biais des simulations numériques. Nous proposons également des comparaisons avec des liquides de Lennard-Jones surfondus bien décrit dans la littérature. / Understanding the origin of the important slowing down of the dynamics near glass transition is still one of the remaining fundamental problems of condensed matter physics. During this work we introduced a brand-new model of liquids named Voronoi liquid, whose interactions are directly related to the geometrical properties of Voronoi tessellations. For these class of liquids interactions are intrinsically manybody and act in such a way that the liquid is always under tension but remains stable. The aim of this work is to use a binary mixture of the Voronoi liquid to see to what extend these exotic interactions may affect the classical scenario of glass transition. Throughout this work we characterize theoretically and by mean of numerical simulation the bidisperse Voronoi liquid. Comparisons with well-known Lennard-Jones glass formers are systematically performed.

No description available.

Une approche donnant de meilleurs résultats pour les potentiels interatomiques en apprentissage-machine à la volée est proposée en comparant trois approches pour la recherche de processus activés par la technique d'activation-relaxation. Tout d'abord, nous discutons de l'intérêt et des enjeux de l'utilisation des potentiels en apprentissage-machine et justifions l'utilisation de l'apprentissage à la volée pour la recherche de processus activés. Cela nous mène à présenter la forme générale des potentiels en apprentissage-machine, quelques modèles via leurs descripteurs de configuration atomique, paramètres et hyperparamètres ainsi que la méthode de l'apprentissage à la volée. Ensuite, nous présentons les méthodes d'exploration utilisées et les détails d'intégration du potentiel à la volée. Enfin, nous menons une étude comparative des trois approches pour un système de Si et de SiGe avec diffusion de lacune. La méthodologie proposée de potentiel de haute précision permet d'étendre la gamme de problèmes pouvant être étudiés par la technique d'activation-relaxation. / An approach giving better results for on-the-fly machine learning interatomic potential proposed by comparing three approaches for exploration of activated processes by the activationrelaxation technique. We first discuss the interest and challenges of on-the-fly machine learning potential and justify the use of on-the-fly learning for the search for activated processes. This leads us to present the general form of machine learning potentials and some models via their atomic configuration descriptors, parameters and hyperparameters as well as the on-the-fly learning method. Then, the exploration methods used are defined and the details of the integration of the potential are presented. Finally, a study is conducted comparing the three approaches for a Si and SiGe system with vacancy diffusion. The proposed methodology of high-precision potential allows to extend the range of possible problems to be studied by the activation-relaxation technique.