Shape memory Nitinol has long been used for actuation. However, utilizing Nitinol to fabricate novel devices for various applications is a challenge, but has shown incredible promise and impacts. Bistable metal strips are widely adopted for shape morphing purposes (primarily in kid’s toys, e.g., snap bracelets) due to their easy and robust transformation between two states. In this paper, we combine Nitinol shape memory alloy and bistable metal strip to fabricate a swimming actuator with both slow moving and fast snapping capability, akin to an octopus swimming slowly in water, but quickly moving upon encountering a threat. The actuator developed here can also swim in multiple directions, all controlled by a wireless module. Furthermore, we demonstrate that an on-board sensor can be incorporated for potential environmental monitoring applications. Taken together, along with the fact that the device developed here has no mechanical parts, makes this an interesting potential alternative to more expensive, and energy consuming boats.
The explosive growth of data and information has motivated technological developments in computing systems that utilize them for efficiently discovering patterns and gaining relevant insights. Inspired by the structure and functions of biological synapses and neurons in the brain, neural network algorithms that can realize highly parallel computations have been implemented on conventional silicon transistor-based hardware. However, synapses composed of multiple transistors allow only binary information to be stored, and processing such digital states through complicated silicon neuron circuits makes low-power and low-latency computing difficult. Therefore, the attractiveness of the emerging memories and switches for synaptic and neuronal elements, respectively, in implementing neuromorphic systems, which are suitable for performing energy-efficient cognitive functions and recognition, is discussed herein. Based on a literature survey, recent progress concerning memories shows that novel strategies related to materials and device engineering to mitigate challenges are presented to primarily achieve nonvolatile analog synaptic characteristics. Attempts to emulate the role of the neuron in various ways using compact switches and volatile memories are also discussed. It is hoped that this review will help direct future interdisciplinary research on device, circuit, and architecture levels of neuromorphic systems. Corresponding author(s) Email: [email protected]
Artificial muscles with large strokes are of special interest in diverse fields. However, it is difficult for large-diameter muscles to be rapidly cycled. In this study, hair artificial muscles with extremely large tensile stroke and fast recovery were prepared simply by twist insertion, coiling and steaming. The maximum tensile stroke for the hair artificial muscles upon water actuation was as large as 10000% and the large-stroke muscles could recover fast in ethanol. With a diameter of 7 mm and a twist density of 2500 turns m-1, the compacted heterochiral hair artificial muscle could elongate 100 times of its original length in water and returned to its initial length in ethanol within 10 s. In addition, these hair artificial muscles maintained their excellent performance after either 100 water-ethanol stimulation cycles or staying in open air for 5 months. Moreover, the hair artificial muscle was able to contract by 59% when lifting 10 times its own weight, pull a wheel model or climb a long distance under water and work as a smart water-sensitive switch. This work demonstrates a facile and green strategy to prepare advanced natural fiber-based artificial muscles that have promising applications in soft robotics and biomedical engineering. Corresponding author(s) Email: [email protected] (Dr. Si Sun), [email protected] (Dr. Xiao-Li Qiang), & [email protected] (Dr. Xiao-Long Shi)
Intelligence in its decisions is a trait that we have grown to expect from a cyber-physical system. In particular that it makes the right choices at runtime, i.e., those that allow it fulfill its tasks, even in case of faults or unexpected interactions with its environment. Analyzing how to continuously achieve the currently desired (and possibly continuously changing) goals and adapting its behavior to reach these goals is undoubtedly a serious challenge. This becomes even more challenging if the atomic actions a system can implement become unreliable due to faulty components or some exogenous event out of its control. In this paper, we propose a solution for the presented challenge. In particular, we show how to adopt a light-weight diagnosis concept to cope with such situations. The approach is based on rules coupled with means for rule selection that are based on previous information regarding the success or failure of rule executions. We furthermore present a Java-based framework of the light-weight diagnosis concept, and discuss the results obtained from an experimental evaluation considering several application scenarios. At the end, we present a qualitative comparison with other related approaches that should help the reader decide which approach works best for them.
The origami technique realizes unique mechanical properties of sheet materials without additional parts. In this study, a self-folded corrugated structure (SCS) is developed based on the reinforcing properties of the origami technique. The corrugated structures are employed as the core material for a high-strength, open-channel sandwich structure. Research on self-folded core materials is scarce; thus, a design concept is proposed, and the mechanical properties of the SCS are evaluated. First, the structural parameters of the SCS fabricated by changing the printing parameters (e.g., linewidth and number of lines/creases), to derive the structural model are determined. The model facilitates the design of an SCS with the desired structure. Thereafter, the mechanical properties of the SCSs are evaluated by conducting three-point bending tests to determine the essential design parameters corresponding to high stiffness. Moreover, SCSs can be stacked without occupying space, thus leading to improved strength. These SCSs fabricated using self-folding paper by ink-jet printing are low cost and eco-friendly. Moreover, they are specialized for rapid design and fabrication, depending on the application. This paper proposes the use of SCS as a novel smart core because it exhibits a high transportation efficiency and stiffness without additional components. Corresponding author(s) Email: [email protected] , [email protected]
Figure S1. Detailed explanation of microfabrication step of fully integrated NIR-LFC. a) The wafer-level microfabrication of iMLA-AFF involves a thin Cr lift-off, and plasma enhanced chemical vapor deposition (PECVD) of SiO2, and a thick Cr lift-off (6 nm Cr – 135 nm SiO2 – 130 nm Cr), photolithographic patterning of DNR photoresist (DNR L300-D1, Dong-jin Semichem, Co., Ltd, Korea), and thermal reflow. Note that a DNR photoresist exhibits both UV curable (Negative photoresist) and thermoplastic characteristic, suitable for metal lift-off as well as microlens formation. The hydrophobic coating of fluorocarbon (C4F8) effectively prevents the lateral expansion of microlenses on a metal surface during thermal reflow. iMLA-AFF are inversely bonded to an image sensor with a 60 μm gap spacer and packaged to a compact objective lens by using a UV curable adhesive. The NIR-LFC is fully assembled by combining a 8.5 mm × 4.7 mm printed circuit board with two VCSEL sources and VCSEL housing. b) A scanning electron microscope (SEM) of hexagonally arranged iMLA-AFF with 30 μm in microlens diameter and 3 μm in microlens gap. c) A photograph of fully packaged NIR-LFC. The camera module is connected to flexible extension cable and delivers raw image to Raspberry Pi 4(B). The total physical dimension of camera module is 8.5 mm × 14.0 mm × 5.6 mm.
This Supplementary Information includes: Section S1- Fabrication method Section S2- Actuation method Section S3- Analysis of sixth-DOF torque Section S4- Experiments Figures S1-S31 Supporting Table References Other supplementary materials for this manuscript include the following:Supporting SI Videos S1-S10 Corresponding author(s) Email: [email protected]
Figure S1. a) The memristive synaptic behavior with an ideally symmetric and linear weight update ability (constant ΔG for identical pulses) but limited conductance levels (N =20). b) Test accuracy for 10,000 images in the MNIST dataset obtained during the training of memristive DBN as a function of the training epoch (CDth=64).
This Supporting Information includes information regarding the magnetic field of the actuator magnet, MR-LF-S (which has the same geometry as MR-LF and a soft compartment), and a table comparing MR-LF to other small-scale, flexible magnetic crawler robots. Corresponding author email: [email protected]