Active mechanical threading by a molecular motor

Molecular motors transform external energy input into directional motions and offer exquisite precision for nano-scale manipulations. In order to make full use of molecular motor capacities, their directional motions need to be transmitted and used for powering downstream molecular events – a current great challenge for molecular engineers. Here we present a macrocyclic molecular motor structure able to perform repetitive molecular threading of a flexible polyethylene glycol chain through the macrocycle. This mechanical threading event is actively powered by the motor motions and leads to a direct translation of the unidirectional motor rotation into an unidirectional translation motion (chain versus ring). The step by step mechanism of the active mechanical threading is elucidated and also the actual threading step is identified as a combined helix inversion and threading event. The here established molecular machine function resembles the crucial step of macroscopic weaving or sewing processes and therefore offers a first entry point for realizing a “molecular knitting” counterpart.

Finite Element Simulation of the Flat Crush Behavior of Corrugated Packages

Corrugated paperboards are used for packaging because of their high strength-to-weight ratio, recyclability, and biodegradability. Corrugated paperboard consists of a liner and a corrugated medium and has an orthotropic sandwich structure with unique characteristics for each direction owing to its flute shape. In this study, finite element analysis (FEA) was performed on the flat crush behavior of the corrugated paperboard based on the flute type. The stress-strain (SS) curve and shape change of the flute were analyzed during the flat compression. In addition, it was compared with the FEA results through various experiments. The restraints and boundary conditions applied during FEA were used to properly describe the conditions during the experiment. Specifically, the horizontal translation motion of the top and bottom surfaces of the modeled test specimen was constrained during FEA to correspond to the effect of sandpaper attached to the upper and lower plates of the testing machine. This was done to prevent the specimen from sliding in one direction during the flat crush test. The change in the flute shape of the corrugated paperboard by flute type analyzed through experiments and FEA was very similar; although there was a difference in the absolute value between the two methods of the SS curve, the flute type exhibited a similar trend. Therefore, a qualitative comparative study on the flat crush behavior by flute type was possible with the FEA method, as in this study. Further studies on the material properties of the corrugated paperboard components and the modeling methods of the corrugated paperboard will enable the FEA-based simulation technique to be an alternative tool that can replace the flat crush test.

Design of MEMS magnetic actuator for MEMS fourier transform infrared spectrometer

The objective of this thesis is to design MEMS magnetic actuator for MEMS FTIRS. The actuator consists of moving part and fixed part. The moving part uses rotation-to-translation motion conversion mechanism to achieve large translation, which includes four trapezoidal plates, central ring, anchoring springs and connection springs. The fixed part of the actuator consists of four solenoids. The actuator can be integrated with separately fabricated micromirror plate to achieve high surface quality translation micromirror for FTIRS. The actuator is capable of eliminating titling by controlling the four solenoids individually. The MEMS magnetic actuator has been designed and simulated to be able to output a static displacement of 370micrometers. The stress has been analyzed for the moving part of the actuator. The actuator fixed part has been designed. Dynamic analysis has been conducted for the moving part of the actuator. The moving part of the actuator has been fabricated using MetalMUMPs.

Particle Actuation by Rotating Magnetic Fields in Microchannels: A Numerical Study

Magnetic particles confined in microchannels can be actuated to perform translation motion using a rotating magnetic field, but their actuation in such a situation is not yet well understood. Here,...

Novel design of a contractible, tubular continuum manipulator

Continuum manipulators have advantages in narrow space detections and operations than the rigid-body robots. In this paper, we novel designed a continuum manipulator with contractible/extensive abilities that give the manipulator more agile and flexible motion than those without these. The robotic system is composed of the continuum deforming body, driving tendons, and a mechanism. To enhance the displacement accuracy of the tendons and compact the package, the mechanism was designed as a controlled winding roller with rotation and translation motion. A prototype of the robotic system was made to evaluate the motion ability of the proposed design.

On the Performance of Swing Arm Flapping Turbines

This study investigates the energy extraction mechanism by means of swing arm turbine. The swing arm turbines have a particular motion pattern. The pure translation motion in the conventional flapping turbine changes based on the swing arm rotation. The laminar flow around a NACA0015 is resolved using computational fluid dynamics (CFD) method. The turbine blades are equipped with an oscillating gurney flap for trying to boost the system efficiency. The connected gurney flap oscillates with a given pitching angle. A user-defined function and the sliding dynamic mesh technique available in ansys fluent version 15 are used to adjust both the blade and the flap positions during the turbine flapping cycle. The effects of the swing factor and the flap length on the system performance are provided. It is shown that the suggested strategy of control is able to alter the pressure distribution during both the up stroke and down stroke phases, which changes the blade aerodynamic forces during all the flapping cycle portions and therefore improving the turbine efficiency.

DeepPilot: A CNN for Autonomous Drone Racing

Autonomous Drone Racing (ADR) was first proposed in IROS 2016. It called for the development of an autonomous drone capable of beating a human in a drone race. After almost five years, several teams have proposed different solutions with a common pipeline: gate detection; drone localization; and stable flight control. Recently, Deep Learning (DL) has been used for gate detection and localization of the drone regarding the gate. However, recent competitions such as the Game of Drones, held at NeurIPS 2019, called for solutions where DL played a more significant role. Motivated by the latter, in this work, we propose a CNN approach called DeepPilot that takes camera images as input and predicts flight commands as output. These flight commands represent: the angular position of the drone’s body frame in the roll and pitch angles, thus producing translation motion in those angles; rotational speed in the yaw angle; and vertical speed referred as altitude h. Values for these 4 flight commands, predicted by DeepPilot, are passed to the drone’s inner controller, thus enabling the drone to navigate autonomously through the gates in the racetrack. For this, we assume that the next gate becomes visible immediately after the current gate has been crossed. We present evaluations in simulated racetrack environments where DeepPilot is run several times successfully to prove repeatability. In average, DeepPilot runs at 25 frames per second (fps). We also present a thorough evaluation of what we called a temporal approach, which consists of creating a mosaic image, with consecutive camera frames, that is passed as input to the DeepPilot. We argue that this helps to learn the drone’s motion trend regarding the gate, thus acting as a local memory that leverages the prediction of the flight commands. Our results indicate that this purely DL-based artificial pilot is feasible to be used for the ADR challenge.