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: firstname.lastname@example.org
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:Figure S1, S2, S3Supplementary VideosVideo S1: Process of self-folding of the SCS with 4 creases.Video S2: Process of self-folding of the SCS with 10 creases. Video S3: Demonstration of stacking SCS with 10 sheets of paper. Video S4: Three-point bending test of the SCS.
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.
Proprioception, the ability to perceive one’s own configuration and movement in space, enables organisms to safely and accurately interact with their environment and each other. The underlying sensory nerves that make this possible are highly dense and use sophisticated communication pathways to propagate signals from nerves in muscle, skin and joints to the central nervous system wherein the organism can process and react to stimuli. In a step forward to realize robots with such perceptive capability, we propose a flexible sensor framework that incorporates a novel hybrid modeling strategy, taking advantage of computational mechanics and machine learning. We implement the sensor framework on a large, thin and flexible sensor that transforms sparsely distributed strains into continuous surface shape. Finite element (FE) analysis is utilized to determine sensor design parameters, while an FE model is built to enrich the morphological data used in the supervised training to achieve continuous surface reconstruction. A mapping between the local strain data and the enriched surface data is subsequently trained using ensemble learning. This hybrid approach enables real-time, robust and high-order surface shape reconstruction. The sensing performance is evaluated in terms of accuracy, repeatability, and feasibility with numerous scenarios, which has not been demonstrated and reported on such a large-scale (A4-paper-size) sensor before.
This Supporting Information includes:Figure S1, S2, S3Supplementary Video Supplementary Video S1: Locomotion of the mobile robot. Supplementary Video S2: Vortex deforming the liquid-liquid interface. Supplementary Video S3: Locomotion of the mobile robot without electrode attached. Supplementary Video S4: Locomotion of the mobile robot with reversed polarity. Supplementary Video S5: Drawing “SIT” by controlling a floating robot with multiple electrodes. Corresponding author Email: email@example.com, firstname.lastname@example.org
This Supporting information includes:1. Component Selection and Performance of SFA2. Actuator Manufacturing and Preparation of Conductive Ink 3. Average Thickness of Conductive Coating layer on PU Foam4. Time Response of the Actuator in Different Modes 5. Characterization and Experimental Setup6. Measurement and Data Analysis7. Design Specifications of Soft Robotic Applications8. Supporting Video Corresponding author Email: email@example.com, firstname.lastname@example.org
This Supporting Information includes the extended description of the superposition state of the asymmetric double-well system in vacuum system and in solution, truth tables for the residue pairs and their corresponding quantum logic gates, and figures for the double well potential energy surfaces and transmission spectra of the residue pairs.Corresponding Authors Email: email@example.com and firstname.lastname@example.org