Universität Stuttgart
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Item Open Access Fatigue of Al thin films at ultra high frequencies(2005) Eberl, Christoph; Arzt, Eduard (Prof. Dr. phil.)Ultra high-cycle fatigue at frequencies in the GHz regime leads to a characteristic void and extrusion formation in patterned metal thin films. Resulting from the microstructural damage formation a significant degradation in form of a shift of the resonance frequency and failures by short circuits in Surface Acoustic Wave (SAW) test devices take place. To study fatigue at ultra high cycles, SAW test devices were used to test continuous and patterned Al thin films at ultra high frequencies. For stress amplitudes as low as 14 MPa lifetime measurements showed no fatigue limit for 400 nm Al thin films. The resulting damage sites appeared in regions of cyclic stress concentration as identified by Finite Element Analysis. In situ measurements revealed that the characteristic extrusion/void formation mechanism operates on a short time scale. The post-test analysis of microstructural changes reveals extrusion and void formation concentrated at grain boundaries. This finding and the observed grain growth indicates a high material flux at the grain boundaries induced by the cyclic load. Quantitative analysis also shows a correlation between extrusion density and electrical devices performance. This direct correlation shows a functional agreement with a common theory on the influence of crack density on intrinsic stresses in thin metal films. Advanced Finite Element (FEM) calculations simulate very well the sensitivity of the resonance frequency to damage structure in interconnects such as cracks, voids and extrusions. The experimentally observed linear correlation between damage density and frequency shift is reproduced by the FEM model. The estimation of the short circuit probability from the extrusion length distribution revealed an exponential dependency on the electrode distance. The observed damage formation is explained by the combined action of dislocation motion and stress-induced diffusion processes.Item Open Access Interaction of carbon and nitrogen in iron(Stuttgart : Max-Planck-Institut für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung), 2016) Göhring, Holger; Mittemeijer, Eric Jan (Prof. Dr. Ir.)Item Open Access Engineered bioinspired natural dynamics and their synergy with control and learning in legged robots(2022) Ruppert, Felix; Schmitt, Syn (Prof. Dr.)The performance of legged locomotion relies on the successful mitigation of unstructured, rough terrain in the presence of sparse information and neurosensory delays. Bioinspired walking systems benefit from carefully engineered passive compliant behavior that models the inherent elastic behavior of muscle-tendon structures in animals. To leverage the passive behavior that provides energy efficiency, passive stability as well as simplified control and learning tasks to the system, locomotion control and learning algorithms have to be designed and coordinated with the natural system dynamics in mind to achieve similar locomotion behavior we see in animals. The major contribution of this thesis is the synergy of a bio-inspired leg design with biarticular muscle-tendon structures, a wearable force and pressure sensor design for closed-loop control in legged locomotion, a biologically inspired closed-loop central pattern generator with reflex-like feedback and a learning approach that enables the locomotion controller to leverage the carefully engineered natural dynamics of the robot to learn convincing locomotion skills and increase energy efficiency. The first contribution is a biologically inspired leg design focusing on the biarticular lower leg muscle-tendon structure in vertebrate animals. The biarticular elasticity provides two-dimensional passive impedance to the leg and allows the storage of energy orthogonal to the leg axis direction. The leg blueprint is characterized in its capability to store and release elastic energy in the biarticular structure. The stored energy can be recuperated back into the system and increases the energy efficiency of the leg. This leg design achieves the lowest relative cost of transport documented for all dynamically hopping and running robots. The second contribution introduces the concept of training wheels, temporary mechanical modifications to the system dynamics that shape the learning reward landscape and simplify learning locomotion directly in hardware. Through deliberate changes to the system dynamics, in this case, reduced gravity, the reward landscape can be shaped to simplify the learning process. Learning with this training wheel is safer due to smoother reward landscapes with shallower gradients. Also, the initial guess for initiating the machine learning algorithm is simplified, because the salient gradient set of viable reward signals is bigger. During the learning process, the training wheel influence can be gradually reduced and the learning algorithm converges to the solution of the initial learning problem without training wheels. The third contribution presents a rugged, lightweight force and pressure sensor for feedback information and biomechanical analysis. The sensor can be mounted on a robotic foot and provides continuous force and pressure feedback during locomotion in unstructured and soft terrain. The sensor is based on a pressure sensor, encapsulated in a polyurethane dome with an air cavity around the pressure sensor. External forces deform the sensor dome and the rising pressure in the air cavity is measured by the pressure sensor. Based on the dome geometry and material, the sensor range can be adjusted for different load cases. The sensor can be used in arrays to measure pressure distributions as well as a wearable force sensor in wet or granular media where classical force plates can not be utilized. The final contribution synergizes the individual contributions into a neuroinspired learning approach that matches a bioinspired closed-loop central pattern generator with reflex-like neuroelastic feedback to the natural dynamics of a quadruped robot with biarticular legs. Through sparse contact feedback from the foot sensor, the bioinspired central pattern generator can neuroelastically mitigate short-term perturbations to adapt the robot to its environment. Because the robot dynamics and the control task dynamics initially do not match, the controller uses the neuroelastic feedback to minimize the discrepancy between commanded and measured robot behavior. The amount of feedback activity during level walking can be used as a proxy to estimate the amount of dynamics mismatching. By minimizing the amount of required neuroelastic feedback the robot learns to neuroplastically match its control task dynamics to its natural dynamics through Bayesian optimization. Through the synergy of mechanics and control the biomechatronic system benefits from both the individual functionality of its components as well as their interplay during locomotion. The designed natural dynamics provide advantageous passive behavior to the robot and the bioinspired controller learns to leverage the natural dynamics to achieve convincing locomotion.Item Open Access Engineering and evaluating naturalistic vibrotactile feedback for telerobotic assembly(2024) Gong, Yijie; Kuchenbecker, Katherine J. (Hon.-Prof. Dr.)Teleoperation allows workers on a construction site to assemble pre-fabricated building components by controlling powerful machines from a safe distance. However, teleoperation's primary reliance on visual feedback limits the operator's efficiency in situations with stiff contact or poor visibility, compromising their situational awareness and thus increasing the difficulty of the task; it also makes construction machines more difficult to learn to operate. To bridge this gap, we propose that reliable, economical, and easy-to-implement naturalistic vibrotactile feedback could improve telerobotic control interfaces in construction and other application areas such as surgery. This type of feedback enables the operator to feel the natural vibrations experienced by the robot, which contain crucial information about its motions and its physical interactions with the environment. This dissertation explores how to deliver naturalistic vibrotactile feedback from a robot's end-effector to the hand of an operator performing telerobotic assembly tasks; furthermore, it seeks to understand the effects of such haptic cues. The presented research can be divided into four parts. We first describe the engineering of AiroTouch, a naturalistic vibrotactile feedback system tailored for use on construction sites but suitable for many other applications of telerobotics. Then we evaluate AiroTouch and explore the effects of the naturalistic vibrotactile feedback it delivers in three user studies conducted either in laboratory settings or on a construction site. The primary contribution of this dissertation is the clear explanation of details that are essential for the effective implementation of naturalistic vibrotactile feedback. We demonstrate that our accessible, audio-based approach can enhance user performance and experience during telerobotic assembly in construction and other application domains. These findings lay the foundation for further exploration of the potential benefits of incorporating haptic cues to enhance user experience during teleoperation.Item Open Access Modelling of crystal plasticity effects in the fracture of a metal/ceramic interface - bridging the length scales(2006) Siddiq, Muhammad Amir; Schmauder, Siegfried (Prof. Dr. rer. nat.)Abstract: Metal/ceramic interfaces play a vital role in modern materials technology, as evident by their use in a variety of applications. High-strength materials, such as metal-matrix composites consist of internal interfaces between ceramic (e.g. SiC or Al2O3) particles or filaments within a metallic host. In microelectronics packaging, interfaces between metallic (Cu and/or Al) interconnects and SiO2, carbide/nitride (TiCN) or oxide (Al2O3) ceramics are commonplace, and impact the performance and longevity of solid state devices. Despite their widespread use, a basic understanding of these interfaces has been elusive. For example, given a particular metal/ceramic interface, it is not yet possible to accurately predict such fundamental properties as its fracture energy. In most of the cases, improvements in interface properties proceed via a costly and time consuming trial-and-error process in which numerous materials are evaluated until suitable performance is obtained. Computational methods provide a wide range of possibilities to study the fracture behaviour of such metal/ceramic interfaces. In the first part of the presented work, the deformation behaviour of niobium single crystals has been simulated using crystal plasticity theory. An automatic identification procedure has been proposed to identify the crystal plasticity parameters for each family of slip systems and simulation results of the mechanical behaviour of single crystal niobium are compared with the experiment. Good agreement between the experimental and simulation results was found. The second part presents effects of the different niobium single crystalline material orientations on crack initiation energies of the bicrystal niobium/sapphire four-point-bending-test specimens for a stationary crack tip. The trends of crack initiation energies are found to be similar to those observed during experiments. In the third part, crack propagation analyses of niobium/alumina bicrystal interface fracture have been performed using a cohesive modelling approach for three different orientations of single crystalline niobium. Parametric studies have been performed to study the effect of different cohesive law parameters, such as work of adhesion and cohesive strength, where work of adhesion is the area under the cohesive law curve while cohesive strength is the peak stress value of the cohesive law. The results show that cohesive strength has a stronger effect on the macroscopic fracture energy as compared to work of adhesion. Cohesive model parameters are identified for different combinations of cohesive strength and work of adhesion by applying a scale bridging procedure. In the last part, a correlation among the macroscopic fracture energy, cohesive strength, work of adhesion and yield stress of niobium single crystalline material will be derived.Item Open Access Light-driven microswimmers and their applications(2021) Sridhar, Varun; Sitti, Metin (Prof. Dr.)Item Open Access Development of a bioinspired multimodal mobile robot platform(2024) Kim, HyunGyu; Sitti, Metin (Prof. Dr.)Item Open Access 3D-printed stimuli-responsive soft microrobots(2023) Lee, Yunwoo; Sitti, Metin (Prof. Dr.)Untethered microrobots, i.e., mobile microrobots, with overall sizes less than 1 mm are receiving significant attention due to their great potential to conduct targeted and minimally invasive therapeutic delivery and medical treatment of diseases in the local region of the biological environment. However, there are many technical barriers in the integration of conventional on-board sensors, actuators, and batteries into micro-scale systems. To overcome these limitations, stimuli-responsive active materials with both sensing and actuation properties are integrated to mobile microrobots. Stimuli-responsive materials can morph their shape and size via swelling and deswelling mechanisms in response to external chemical, physical and other stimuli, such as heat, pH, light, magnetic field, and acoustic field, with no aid from complex wires, sensors, or batteries. While conventional fabrication methods with passive materials have led to the production of static structures, 3D printing with stimuli-responsive materials opens a new direction for 3D objects possessing volumetric transformation behavior, material property change, and shape morphing ability. In this dissertation, I integrate different stimuli-responsive materials and 3D microprinting to provide more multifunctional, versatile and complex microrobot designs based on bioinspired design principles, with a wide range of stimuli-responsive sensing and actuation properties to use them in potential biomedical applications inside the human body. In the first part, I introduce magnetically steerable 3D-printed microroller and microscrew robot designs with stimuli-responsive materials to develop volume-controllable microrobots for spatial adaptation. These wirelessly controlled microrobots possess the ability to function in response to multiple stimuli, including magnetic fields, temperature, pH, and cations, which can enhance the adaptability of the microbots to various unstructured environments. Second, octopus-inspired architectures with temperature-responsive materials to control the adhesion properties for medical purposes is proposed. Introduction of pNIPAM material leads temperature-responsive volume morphing behavior enabled controllable tissue adhesion by using externally applied magnetic fields. Furthermore, I demonstrate the capability of implementing a wide range of medical tasks repeatedly via showing the repetition of attachment and detachment processes using an external magnetic field. Finally, I present a multifunctional pollen-grain-inspired hydrogel robot by 3D direct laser printing in order to enhance the functional diversity of microrobots in biological environments. I also demonstrated multi-responsive hydrogel structures to decouple the stimulus inputs of magnetically actuated locomotion, temperature-responsive controllable attachment, and pH-responsive on-demand cargo release, respectively. The temperature-responsive outer crust shells made of pNIPAM enabled controlling the attachment of the microrobot by shrinking up to 49%, revealing the robot’s spikes. In addition, the inner pollen-grain-inspired structure with spikes made of PETA with FePt nanoparticles demonstrated an improved attachment performance and magnetically guided locomotion along biological surfaces. The inner sphere made of pNIPAM-AAc successfully released drugs by pH-induced swelling.Item Open Access Capturing and recognizing multimodal surface interactions as embedded high-dimensional distributions(2025) Khojasteh, Behnam; Kuchenbecker, Katherine J. (Hon.-Prof. Dr.)Exploring a surface with a handheld tool generates complex contact signals that uniquely encode the surface’s properties - a needle hidden in a haystack of data. Humans naturally integrate visual, auditory, and haptic sensory data during these interactions to accurately assess and recognize surfaces. However, enabling artificial systems to perceive and recognize surfaces with human-like proficiency remains a significant challenge. The complexity and dimensionality of multi-modal sensor data, particularly in the intricate and dynamic modality of touch, hinders effective sensing and processing. Successfully overcoming these challenges will open up new possibilities in applications such as quality control, material documentation, and robotics. This dissertation addresses these issues at the levels of both the sensing hardware and the processing algorithms by introducing an automated similarity framework for multimodal surface recognition, developing a haptic-auditory test bed for acquiring high-quality surface data, and exploring optimal sensing configurations to improve recognition performance and robustness.