Analysis of Thin Film Parylene-Metal-Parylene Device Based on Mechanical Tensile Strength Measurement

International audienceThis paper presents an FEM analysis and experiment of parylene-metal-parylene flexible substrate for implantable medical devices. Tensile strength measurement of the parylene-metal-parylene has been carried out and corresponding FEM modeling and simulation has been done to understand its mechanical behaviour. Besides, frequently encountered metal delamination on parylene substrate has been studied based on cohesive zone model of interface between the two materials

Learning Terrain-Aware Kinodynamic Model for Autonomous Off-Road Rally Driving With Model Predictive Path Integral Control

High-speed autonomous driving in off-road environments has immense potential for various applications, but it also presents challenges due to the complexity of vehicle-terrain interactions. In such environments, it is crucial for the vehicle to predict its motion and adjust its controls proactively in response to environmental changes, such as variations in terrain elevation. To this end, we propose a method for learning terrain-aware kinodynamic model which is conditioned on both proprioceptive and exteroceptive information. The proposed model generates reliable predictions of 6-degree-of-freedom motion and can even estimate contact interactions without requiring ground truth force data during training. This enables the design of a safe and robust model predictive controller through appropriate cost function design which penalizes sampled trajectories with unstable motion, unsafe interactions, and high levels of uncertainty derived from the model. We demonstrate the effectiveness of our approach through experiments on a simulated off-road track, showing that our proposed model-controller pair outperforms the baseline and ensures robust high-speed driving performance without control failure.Comment: Accepted to IEEE Robotics and Automation Letters (and ICRA 2024). Our video can be found at https://youtu.be/VXf_prNQnJo Project page : https://sites.google.com/view/terrainawarekinody

Flow-Induced Voltage Generation Over Monolayer Graphene in the Presence of Herringbone Grooves

While flow-induced voltage over a graphene layer has been reported, its origin remains unclear. In our previous study, we suggested different mechanisms for different experimental configurations: phonon dragging effect for the parallel alignment and an enhanced out-of-plane phonon mode for the perpendicular alignment (Appl. Phys. Lett. 102:063116, 2011). In order to further examine the origin of flow-induced voltage, we introduced a transverse flow component by integrating staggered herringbone grooves in the microchannel. We found that the flow-induced voltage decreased significantly in the presence of herringbone grooves in both parallel and perpendicular alignments. These results support our previous interpretation

Smooth Model Predictive Path Integral Control without Smoothing

We present a sampling-based control approach that can generate smooth actions for general nonlinear systems without external smoothing algorithms. Model Predictive Path Integral (MPPI) control has been utilized in numerous robotic applications due to its appealing characteristics to solve non-convex optimization problems. However, the stochastic nature of sampling-based methods can cause significant chattering in the resulting commands. Chattering becomes more prominent in cases where the environment changes rapidly, possibly even causing the MPPI to diverge. To address this issue, we propose a method that seamlessly combines MPPI with an input-lifting strategy. In addition, we introduce a new action cost to smooth control sequence during trajectory rollouts while preserving the information theoretic interpretation of MPPI, which was derived from non-affine dynamics. We validate our method in two nonlinear control tasks with neural network dynamics: a pendulum swing-up task and a challenging autonomous driving task. The experimental results demonstrate that our method outperforms the MPPI baselines with additionally applied smoothing algorithms.Comment: Accepted to IEEE Robotics and Automation Letters (and IROS 2022). Our video can be found at https://youtu.be/ibIks6ExGw

Optofluidic ring resonator laser with an edible liquid laser gain medium

We demonstrate a biocompatible optofluidic laser with an edible liquid laser gain medium, made of riboflavin dissolved in water. The proposed laser platform is based on a pulled-glass-capillary optofluidic ring resonator (OFRR) with a high Q-factor, resulting in a lasing threshold comparable to that of conventional organic dye lasers that are mostly harmful, despite the relatively low quantum yield of the riboflavin. The proposed biocompatible laser can be realized by not only a capillary OFRR, but also by an optical-fiber-based OFRR that offers improved mechanical stability, and is promising technology for application to in vivo bio-sensing

Gas-induced segregation in Pt-Rh alloy nanoparticles observed by in-situ Bragg coherent diffraction imaging

Bimetallic catalysts can undergo segregation or redistribution of the metals driven by oxidizing and reducing environments. Bragg coherent diffraction imaging (BCDI) was used to relate displacement fields to compositional distributions in crystalline Pt-Rh alloy nanoparticles. 3D images of internal composition showed that the radial distribution of compositions reverses partially between the surface shell and the core when gas flow changes between O2 and H2. Our observation suggests that the elemental segregation of nanoparticle catalysts should be highly active during heterogeneous catalysis and can be a controlling factor in synthesis of electrocatalysts. In addition, our study exemplifies applications of BCDI for in situ 3D imaging of internal equilibrium compositions in other bimetallic alloy nanoparticles

Effect of Long-Term Exposure to Lower Low-Density Lipoprotein Cholesterol Beginning Early in Life on the Risk of Coronary Heart Disease A Mendelian Randomization Analysis

ObjectivesThe purpose of this study was to estimate the effect of long-term exposure to lower plasma low-density lipoprotein cholesterol (LDL-C) on the risk of coronary heart disease (CHD).BackgroundLDL-C is causally related to the risk of CHD. However, the association between long-term exposure to lower LDL-C beginning early in life and the risk of CHD has not been reliably quantified.MethodsWe conducted a series of meta-analyses to estimate the effect of long-term exposure to lower LDL-C on the risk of CHD mediated by 9 polymorphisms in 6 different genes. We then combined these Mendelian randomization studies in a meta-analysis to obtain a more precise estimate of the effect of long-term exposure to lower LDL-C and compared it with the clinical benefit associated with the same magnitude of LDL-C reduction during treatment with a statin.ResultsAll 9 polymorphisms were associated with a highly consistent reduction in the risk of CHD per unit lower LDL-C, with no evidence of heterogeneity of effect (I2 = 0.0%). In a meta-analysis combining nonoverlapping data from 312,321 participants, naturally random allocation to long-term exposure to lower LDL-C was associated with a 54.5% (95% confidence interval: 48.8% to 59.5%) reduction in the risk of CHD for each mmol/l (38.7 mg/dl) lower LDL-C. This represents a 3-fold greater reduction in the risk of CHD per unit lower LDL-C than that observed during treatment with a statin started later in life (p = 8.43 × 10−19).ConclusionsProlonged exposure to lower LDL-C beginning early in life is associated with a substantially greater reduction in the risk of CHD than the current practice of lowering LDL-C beginning later in life