Membranes separate uid compartments and can comprise transport structures for selective permeation. In biology, channel proteins are specialized in their atomic structure to allow transport of specific compounds (selectivity). Conformational changes in protein structure allow the control of the permeation abilities by outer stimuli (gating). In polymeric membranes, the selectivity is due to electrostatic or size-exclusion. It can thus be controlled by size variation or electric charges. Controllable permeation can be useful to determine particle-size distributions in continuous ow, e.g. in micro uidics and biomedicine to gain cell diameter profiles in blood. The present approach uses patterned polyethylene terephthalate (PET) membranes with hydrogel surface coating for permeation control by size-exclusion. The thermosensitive hydrogel poly(N-isopropylacrylamide) (PNIPAAm) is structured with a cross-shaped pore geometry. A change in the temperature of the water ow through the membrane leads to a pore shape variation. The temperature dependent behavior of PNIPAAm can be numerically modeled with a temperature expansion model, where the swelling and deswelling is depicted by temperature dependent expansion coefficients. In the present study, the free swelling behavior was implemented to the Finite Element tool ABAQUS for the complex composite structure of the permeation control membrane. Experimental values of the geometry characteristics were derived from microscopy images with the tool ImageJ and compared to simulation results. Numerical simulations using the derived thermomechanical model for different pore geometries (circular, rectangle, cross and triangle) were performed. With this study, we show that the temperature expansion model with values from the free swelling behavior can be used to adequately predict the deformation behavior of the complex membrane system. The predictions can be used to optimize the behavior of the membrane pores and the overall performance of the smart membrane.

Every day, we make many value-based decisions where we weigh the value of options with other properties, e.g. their time of delivery. In the laboratory, such value-based decision-making is usually studied on a trial by trial basis and each decision is assumed to represent an isolated choice process. Real-life decisions however are usually embedded in a rich context of previous choices at different time scales. A fundamental question is therefore how the dynamics of value-based decision processes unfold on a time scale across several decisions. Indeed, findings from perceptual decision making suggest that sequential decisions patterns might also be present for vale-based decision making. Here, we use a neural-inspired attractor model as an instance of dynamic models from perceptual decision making, as such models incorporate inherent activation dynamics across decisions. We use the model to predict sequential patterns, namely oscillatory switching, perseveration and dependence of perseveration on the delay between decisions. Furthermore, we predict RT effects for specific sequences of trials. We validate the predictions in two new studies and a reanalysis of existing data from a novel decision game in which participants have to perform delay discounting decisions. Applying the validated reasoning to a well-established choice questionnaire, we illustrate and discuss that taking sequential choice patterns into account may be necessary to accurately analyse and model value-based decision processes, especially when considering differences between individuals.

No description available.

No description available.

No description available.

No description available.

It was discovered several decades ago that eddy covariance measurements systematically underestimate sensible and latent heat fluxes, creating an imbalance in the surface energy budget. Since then, many studies have addressed this problem and proposed a variety of solutions to the problem, including improvements to instruments and correction methods applied during data postprocessing. However, none of these measures have led to the complete closure of the energy balance gap. The leading hypothesis is that not only surface-attached turbulent eddies but also sub-mesoscale atmospheric circulations contribute to the transport of energy in the atmospheric boundary layer, and the contribution from organized motions has been grossly neglected. The problem arises because the transport of energy through these secondary circulations cannot be captured by the standard eddy covariance method given the relatively short averaging periods of time (~30 minutes) used to compute statistics. There are various approaches to adjust the measured heat fluxes by attributing the missing energy to the sensible and latent heat flux in different proportions. However, few correction methods are based on the processes causing the energy balance gap. Several studies have shown that the magnitude of the energy balance gap depends on the atmospheric stability and the heterogeneity scale of the landscape around the measurement site. Based on this, the energy balance gap within the surface layer has already been modelled as a function of a nonlocal atmospheric stability parameter by performing a large-eddy simulation study with idealized homogeneous surfaces. We have further developed this approach by including thermal surface heterogeneity in addition to atmospheric stability in the parameterization. Specifically, we incorporated a thermal heterogeneity parameter that was shown to relate to the magnitude of the energy balance gap. For this purpose, we use a Large-Eddy Simulation dataset of 28 simulations with seven different atmospheric conditions and three heterogeneous surfaces with different heterogeneity scales as well as one homogeneous surface. The newly developed model captures very well the variability in the magnitude of the energy balance gap under different conditions. The model covers a wide range of both atmospheric stabilities and landscape heterogeneity scales and is well suited for application to eddy covariance measurements since all necessary information can be modelled or obtained from a few additional measurements.

Die vorliegende Arbeit befasst sich mit der Simulation und Modellierung organischer Feldeffekt-Transistoren (OFETs). Mittels numerischer Simulationen wurden detaillierte Untersuchungen zu mehreren Problemstellungen durchgeführt. So wurde der Einfluss einer exponentiellen Verteilung von Trapzuständen, entsprechend dem sogenannten a-Si- oder TFT-Modell, auf die Transistorkennlinien untersucht. Dieses Modell dient der Beschreibung von Dünnschicht-Transistoren mit amorphen Silizium als aktiver Schicht und wird teils auch für organische Transistoren als zutreffend angesehen. Dieser Sachverhalt wird jedoch erstmals in dieser Arbeit detailliert untersucht und simulierte Kennlinien mit gemessenen Kennlinien von OFETs verglichen. Insbesondere aufgrund der Dominanz von Hysterese-Effekten in experimentellen Kennlinien ist jedoch eine endgültige Aussage über die Gültigkeit des a-Si-Modells schwierig. Neben dem a-Si-Modell werden auch noch andere Modelle diskutiert, z.B. Hopping-Transport zwischen exponentiell verteilten lokalisierten Zuständen (Vissenberg, Matters). Diese Modelle liefern, abhängig von den zu wählenden Modellparametern, zum Teil ähnliche Abhängigkeiten. Möglicherweise müssen die zu wählenden Modellparameter selbst separat gemessen werden, um eindeutige Schlussfolgerungen über den zugrundeliegenden Transportmechanismus ziehen zu können. Unerwünschte Hysterese-Effekte treten dabei sowohl in Transistorkennlinien als auch in Kapazitäts-Spannungs- (CV-) Kennlinien organischer MOS-Kondensatoren auf. Diese Effekte sind bisher weder hinreichend experimentell charakterisiert noch von ihren Ursachen her verstanden. In der Literatur findet man Annahmen, dass die Umladung von Trapzuständen oder bewegliche Ionen ursächlich sein könnten. In einer umfangreichen Studie wurde daher der Einfluß von Trapzuständen auf quasistatische CV-Kennlinien organischer MOS-Kondensatoren untersucht und daraus resultierende Hysterese-Formen vorgestellt. Aus den Ergebnissen läßt sich schlussfolgern, dass allein die Umladung von Trapzuständen nicht Ursache für die experimentell beobachteten Hysteresen in organischen Bauelementen sein kann. Eine mögliche Erklärung für diese Hysterese-Effekte wird vorgeschlagen und diskutiert. In einem weiteren Teil der Arbeit wird im Detail die Arbeitsweise des source-gated Dünnschicht-Transistors (SGT) aufgezeigt, ein Transistortyp, welcher erst kürzlich in der Literatur eingeführt wurde. Dies geschieht am Beispiel eines Transistors auf der Basis von a-Si als aktiver Schicht, die Ergebnisse lassen sich jedoch analog auch auf organische Transistoren übertragen. Es wird geschlussfolgert, dass der SGT ein gewöhnlich betriebener Dünnschicht-Transistor ist, limitiert durch das Sourcegebiet mit großem Widerstand. Die detaillierte Untersuchung des SGT führt somit auf eine Beschreibung, die im Gegensatz zur ursprünglich verbal diskutierten Arbeitsweise steht. Ambipolare organische Feldeffekt-Transistoren sind ein weiterer Gegenstand der Arbeit. Bei der Beschreibung ambipolarer Transistoren vernachlässigen bisherige Modelle sowohl die Kontakteigenschaften als auch die Rekombination von Ladungsträgern. Beides wird hingegen in den vorgestellten numerischen Simulationen erstmalig berücksichtigt. Anhand eines Einschicht-Modellsystems wurde die grundlegende Arbeitsweise von ambipolaren (double-injection) OFETs untersucht. Es wird der entscheidende Einfluß der Kontakte sowie die Abhängigkeit gegenüber Variationen von Materialparametern geklärt. Sowohl der Kontakteinfluß als auch Rekombination sind entscheidend für die Arbeitsweise. Zusätzlich werden Möglichkeiten und Einschränkungen für die Datenanalyse mittels einfacher analytischer Ausdrücke aufgezeigt. Es zeigte sich, dass diese nicht immer zur Auswertung von Kennlinien herangezogen werden dürfen. Weiterhin werden erste Simulationsergebnisse eines ambipolaren organischen Heterostruktur-TFTs mit experimentellen Daten verglichen.

<p>From idea generation to conceptualization and development of products and technologies is a non-linear and iterative process. The work in this thesis follows a process that initiates with the review of existing technologies and products, examining their unique value proposition in the context of the specific applications for which they are designed. Next, the unmet needs of novel or emerging applications are identified that require new product or technologies. Once these user needs and product requirements are identified, the specific functions to be addressed by the product are specified. The subsequent process of design of products and technologies to meet these functions is enabled by engineering tools such as three-dimensional modelling, physics-based simulations, and manufacturing of a minimum viable prototype. In these steps, un-biased decisions have to be taken using weighted decision matrices to cater to the design requirements. Finally, the minimum viable prototype is tested to demonstrate the principal functionalities. The results obtained from the testing process identify the potential future improvements in the next generations of the prototype that would subsequently inform the final design of product. This thesis adopted this methodology to initiate the design two product-prototypes: i) an image-recognition-integrated service (IRIS) robotic hand for children and ii) cascaded multi-core vapor chamber (CMVC) for improving performance of next-generation computing systems. Minimum viable product-prototypes were manufactured to demonstrate the principal functionalities, followed by clear identification of future potential improvements. Tests of the prosthetic hand indicate that the image-recognition based feedback can successfully drive the actuators to perform the intended grasping motions. Experimental testing with the multi-core vapor chamber demonstrates successful performance of the prototype, which offers notable reduction in temperatures relative to the existing benchmark solid copper spreader. </p>