This thesis investigates materialization and representation in contemporary architectural design practice. Due to cultural and technological shifts, the act of design is no longer squarely located in the abstract realms of drawings or digital geometries. Computer aided manufacturing, simulation and scanning offer new design opportunities that are located in the transfer between representation and material. This has given rise to a post-digital model of practice and thought, in which ‘real’ and discrete chunks of matter are incorporated at the earliest stages of design. The thesis is practice-based, and spans in scope from design to technology to theory. The design work included explores materialization and representation from a particular point of view. In addition, it suggests a methodological approach to design, and explores the theoretical implications in this approach. These implications are addressed in two connected research questions: How can material processes, whether real or simulated, turn transfers between geometry and materialized objects into productive design opportunities? And how might material simulation alter the ways in which representations are conceptualized and used by architects? In parallel with practice-based work, the thesis suggests a theoretical framework for current issues of representation and materialization in architecture. This framework draws from the recent history of the digital turn in architecture as well as from recent design research work and theory in a post-digital turn. This thesis makes contributions in three main areas. Through the design work Erratic, it makes a visceral case for how the use of material simulation might open up new ways of harnessing material agency. It positions simulation in the field of architecture in-between established polarities such as geometry vs. matter, virtual vs. real and drawing vs. mock-up. It discusses the conceptual difference between design based on geometry and design based on discrete pieces of material. Finally, it proposes that form in architecture increasingly can be conceptualized as ‘chunks,’ as opposed to reduced descriptions of geometry. / <p>QC 20161102</p>

Doctor of Philosophy / Department of Physics / Talat S. Rahman / This dissertation is an extensive study of several issues related to post deposition morphological evolution of fcc metal surfaces. These studies were carried out by probing the energetics and the dynamics of underlying atomistic mechanisms responsible for surface diffusion. An important aspect is the determination of relative probability of competing atomistic mechanisms and their contribution to controlling shapes and step edge patterns of nano structures on surfaces. In this scenario, the descent of adatoms from Ag islands on Ag(111) surface is examined. It shows an exchange mechanism to dominate over hopping and the process to favor the formation of (100)-microfacetted steps (A-type) over the (111)-microfacetted ones (B-type). Molecular dynamics simulations support these results at low temperature while at high temperature B-type step formation dominates. This change in the trend could happen if these processes leading to the formation of the A and B type steps have different values of their diffusion prefactors. This difference is confirmed on the basis of our calculations of the diffusion coefficients. Further, to understand the macroscopic properties of a system on the basis of its atomic scale information, spatial and temporal fluctuations of step edges on vicinal Cu(1 1 13) and Cu(1 1 19) surfaces is studied using kinetic Monte Carlo (KMC) simulations. These results show excellent agreement with experimental data, highlighting the role of mass transport along step edges, and also showing the validity of tools like KMC which aims at bridging the gap in length and time scales at which a range of interesting phenomena take place. To facilitate unbiased modeling of material properties, a novel way of performing KMC simulations is presented. In this approach the lists of diffusion processes are automatically collected during the simulation using a saddle-point search method in the potential energy landscape. The speed of the simulations is thus enhanced along with a substantial gain in reliability. Using this method the diffusion and coalescence of two-dimensional Cu and Ag adatom-island on Cu(111) and Ag(111) is studied. Together with input from molecular dynamics simulations, new processes involving the concerted motion of smaller islands are revealed. A significant difference in the scaling of the effective diffusion barriers with island size is observed for the sets of smaller (less than 10 atoms) and larger islands. In particular, the presence of concerted island motion leads to an almost linear increase in the effective diffusion barrier with size, while its absence accounts for strong size-dependent oscillations and anomalous behavior for trimers and heptamers. A crossover from diffusion due to the collective motion of the smaller island to a regime in which the island diffuses through the periphery dominated mass transport (large islands, 19 to 100 atoms) is predicted. For islands containing 19 to 100 atoms the scaling exponent is found to be in good agreement with that found in previous studies.

This thesis deals with the robotic machining of composite materials. It is divided into two main parts - theoretical and practical part. The theoretical part is focused on detailed introduction of the term “an industrial robot” and a description of its controls, types of the robots, types of their propulsion and programming methods. Furthermore, there is a list of CAM softwares with its specification designed for both conventional machining and machining by using a robot. It also includes the introduction of composite materials and specification of their machining. The practical part deals with selection of appropriate type of bracket spindle by using a simulation software, suction design and economic evaluation of two types of machining in manufacture.

Graphene-based conductor materials (GCMs) consist of stacked and decoupled layers of graphene flakes and could potentially transfer graphene’s outstanding material properties like its exceptional electrical conductivity to the macro scale, where alternatives to the heavy and expensive metallic conductors are desperately needed. To reach super-metallic conductivity however, a systematic electrical conductivity optimization regarding the structural and physical input parameters is required. Here, a new trend in the field of process and material optimization are data-based models which utilize data science methods to quickly identify and abstract information and relationships from the available data. In this work such data-based models for the conductivity of a real GCM thin-film sample are build on data generated with an especially improved and extended version of the network simulation approach by Rizzi et al. [1, 2, 3]. Appropriate methods to create data-based models for GCMs are thereby introduced and typical challenges during the modelling process are addressed, so that data-based models for other properties of GCMs can be easily created as soon as sufficient data is accessible. Combined with experimental measurements by Slawig et al. [4] the created data-based models allow for a coherent and comprehensive description of the thin-films’ electrical parameters across several length scales.:List of Figures List of Tables Symbol Directory List of Abbreviations 1 Introduction 2 Simulation approaches for graphene-based conductor materials 2.1 Traditional simulation approaches for GCMs 2.1.1 Analytical model for GCMs 2.1.2 Finite element method simulations for GCMs 2.2 A network simulation approach for GCMs 2.2.1 Geometry generation 2.2.2 Electrical network creation 2.2.3 Contact and probe setting 2.2.4 Conductivity computation 2.2.5 Results obtained with the network simulation approach 2.3 An improved implementation for the network simulation 2.3.1 Rizzi’s implementation of the network simulation approach 2.3.2 An network simulation tool for parameter studies 2.3.3 Extending the network simulation approach for anisotropy investigations and multilayer flakes 3 Data-based material modelling 3.1 Introduction to data-based modelling 3.2 Data-based modelling in material science 3.3 Interpretability of data-based models 3.4 The data-based modelling process 3.4.1 Preliminary considerations 3.4.2 Data acquisition 3.4.3 Preprocessing the data 3.4.4 Partitioning the dataset 3.4.5 Training the model 3.4.6 Model evaluation 3.4.7 Real-world applications 3.5 Regression estimators 3.5.1 Mathematical introduction to regression 3.5.2 Regularization and ridge regression 3.5.3 Support Vector Regression 3.5.4 Introducing non-linearity through kernels 4 Data-based models for a real GCM thin-film 4.1 Experimental measurements 4.2 Simulation procedure 4.3 Data generation 4.4 Creating data-based models 4.4.1 Quadlinear interpolation as benchmark model 4.4.2 KR, KRR and SVR 4.4.3 Enlarging the dataset 4.4.4 KR, KRR and SVR on the enlarged training dataset 4.5 Application to the GCM sample 5 Conclusion and Outlook 5.1 Conclusion 5.2 Outlook Acknowledgements Statement of Authorship

La 3D s'impose comme un nouveau média dont l'adoption généralisée passe par la conception d'outils, accessibles au grand public, de création et de manipulation de formes tridimensionnelles quelconques. Les outils actuels reposent fortement sur la modélisation sous-jacente des formes, généralement surfacique, et sont alors peu intuitifs ou limitatifs dans l'expressivité offerte à l'utilisateur.Nous souhaitons, dans ces travaux, définir une approche ne présentant pas ces défauts et permettant à l'utilisateur de se concentrer sur le processus créatif. En nous inspirant de l'utilisation séculaire de l'argile, nous proposons une approche modélisant la matière sous forme lagrangienne.Une forme est ainsi décrite par un système de particules, où chaque particule représente un petit volume du volume global.Dans ce cadre lagrangien, la méthode Smoothed Particle Hydrodynamics (SPH) permet l'approximation de grandeurs physiques en tout point de l'espace. Nous proposons alors une modélisation de matériaux à deux couches, l'une décrivant la topologie et l'autre décrivant la géométrie du système global.La méthode SPH permet, entre autres, d'évaluer la densité de matière. Ceci nous permet de définir une surface implicite basée sur les propriétés physiques du système de particules pour redonner un aspect continu à la matière.Ces matériaux peuvent alors être manipulés au moyen d'interactions locales reproduisant le maniement de la pâte à modeler, et de déformations globales. L'intérêt de notre approche est démontrée par plusieurs prototypes fonctionnant sur des stations de travail standard ou dans des environnements immersifs. / 3D is emerging as a new media. Its widespread adoption requires the implementation of userfriendly tools to create and manipulate three-dimensional shapes. Current softwares heavily rely on underlying shape modeling, usually a surfacic one, and are then often counter-intuitive orlimiting. Our objective is the design of an approach alleviating those limitations and allowing the user to only focus on the process of creating forms. Drawing inspiration from the ancient use of clay,we propose to model a material in a lagrangian description. A shape is described by a particles system, where each particle represents a small fraction of the total volume of the shape. In this framework, the Smoothed Particle Hydrodynamics method enables to approximate physical values anywhere in space. Relying on this method, we propose a modeling of material with two levels, one level representing the topology and the other one describing local geometry of the shape.The SPH method especially enables to evaluate a density of matter. We use this property todefine an implicit surface based on the physical properties of the particles system to reproduce the continuous aspect of matter. Those virtual materials can then be manipulated locally through interactions reproducing the handling of dough in the real world or through global shape deformation. Our approach is demonstrated by several prototypes running either on typical desktop workstation or in immersive environment system.

A new method, probability distribution of diffusivities (time scaled square displacements between succeeding video frames), was developed to analyze single molecule tracking (SMT) experiments. This method was then applied to SMT experiments on ultrathin liquid tetrakis(2-ethylhexoxy)silane (TEHOS) films on Si wafer with 100 nm thermally grown oxide, and on thin semectic liquid crystal films. Spatial maps of diffusivities from SMT experiments on 220 nm thick semectic liquid crystal films reveal structure related dynamics. The SMT experiments on ultrathin TEHOS films were complemented by fluorescence correlation spectroscopy (FCS). The observed strongly heterogeneous single molecule dynamics within those films can be explained by a three-layer model consisting of (i) dye molecules adsorbed to the substrate, (ii) slowly diffusing molecules in the laterally heterogeneous near-surface region of 1 - 2 molecular diameters, and (iii) freely diffusing dye molecules in the upper region of the film. FCS and SMT experiments reveal a strong influence of substrate heterogeneity on SM dynamics. Thereby chemisorption to substrate surface silanols plays an important role. Vertical mean first passage times (mfpt) in those films are below 1 µs. This appears as fast component in FCS autocorrelation curves, which further contain a contribution from lateral diffusion and from adsorption events. Therefore, the FCS curves are approximated by a tri-component function, which contains an exponential term related to the mfpt, the correlation function for translational diffusion and a stretched exponential term for the broad distribution of adsorption events. Lateral diffusion coefficients obtained by FCS on 10 nm thick TEHOS films, thereby, are effective diffusion coefficients from dye transients in the focal area. They strongly depend on the substrate heterogeneity. Variation of the frame times for the acquisition of SMT experiments in steps of 20 ms from 20 ms to 200 ms revealed a strong dependence of the corresponding probability distributions of diffusivities on time, in particular in the range between 20 ms and 100 ms. This points to average dwell times of the dye molecules in at least one type of the heterogeneous regions (e.g. on and above silanol clusters) in the range of few tens of milliseconds. Furthermore, time series of SM spectra from Nile Red in 25 nm thick poly-n-alkyl-methacrylate (PnAMA) films were studied. In analogy to translational diffusion, spectral diffusion (shifts in energetic positions of SM spectra) can be studied by probability distributions of spectral diffusivities, i.e. time scaled square energetic displacements. Simulations were run and analyzed to study contributions from noise and fitting uncertainty to spectral diffusion. Furthermore the effect of spectral jumps during acquisition of a SM spectrum was investigated. Probability distributions of spectral diffusivites of Nile Red probing vitreous PnAMA films reveal a two-level system. In contrast, such probability distributions obtained from Nile Red within a 25 nm thick poly-n-butylmethacrylate film around glass transition and in the melt state, display larger spectral jumps. Moreover, for longer alkyl side chains a solvent shift to higher energies is observed, which supports the idea of nanophase separation within those polymers.