Magnetically Actuated Tunable Soft Electronics

Learning to Control a Three-Dimensional Ferrofluidic Robot

In recent years, ferrofluids have found increased popularity as a material for medical applications, such as ocular surgery, gastrointestinal surgery, and cancer treatment, among others. Ferrofluidic robots are multifunctional and scalable, exhibit fluid properties, and can be controlled remotely; thus, they are particularly advantageous for such medical tasks. Previously, ferrofluidic robot control has been achieved via the manipulation of handheld permanent magnets or in current-controlled electromagnetic fields resulting in two-dimensional position and shape control and three-dimensional (3D) coupled position-shape or position-only control. Control of ferrofluidic liquid droplet robots poses a unique challenge where model-based control has been shown to be computationally limiting. Thus, in this study, a model-free control method is chosen, and it is shown that the task of learning optimal control parameters for ferrofluidic robot control can be performed using machine learning. Particularly, we explore the use of Bayesian optimization to find optimal controller parameters for 3D pose control of a ferrofluid droplet: its centroid position, stretch direction, and stretch radius. We demonstrate that the position, stretch direction, and stretch radius of a ferrofluid droplet can be independently controlled in 3D with high accuracy and precision, using a simple control approach. Finally, we use ferrofluidic robots to perform pick-and-place, a lab-on-a-chip pH test, and electrical switching, in 3D settings. The purpose of this research is to expand the potential of ferrofluidic robots by introducing full pose control in 3D and to showcase the potential of this technology in the areas of microassembly, lab-on-a-chip, and electronics. The approach presented in this research can be used as a stepping-off point to incorporate ferrofluidic robots toward future research in these areas.

Ferromagnetic Liquid Droplet on a Superhydrophobic Surface for the Transduction of Mechanical Energy to Electricity Based on Electromagnetic Induction

Ferromagnetic liquids undergo reversible magnetization changes upon varying external magnetic field levels. The movement of ferromagnetic liquid droplets across a coil under an external magnetic field holds promise as an energy transducer from mechanical force to electricity; however, it suffers from an adhesive issue between the ferromagnetic liquid and the solid pedestal. We introduce a superhydrophobic support that uses antiwetting surfaces to remarkably reduce adhesion during the movement of ferromagnetic liquid droplets. Maxwell numerical simulation was utilized to analyze the working mechanism and improve further electrical outputs. By controlling the droplet size, the strength of the magnetic bottom and the tilting speed of the test condition, we generated a ferromagnetic liquid droplet-based superhydrophobic magnetoelectric energy transducer (FLD-SMET) that can convert vibrational energy to electricity. When a 100 μL ferromagnetic liquid droplet was used for FLD-SMET under a 13 mT magnetic field, an electrical voltage response of 280 μV and electrical current response of ∼7.5 μA were generated using a shaking machine with a tilting speed of 9.5°/s. We thus show that such a device can serve as a self-powered light buoy floating on a water surface. Our study presents an applied concept for the design of droplet-based energy harvesters to convert surrounding vibrational energy to electricity.

Thermoelectric properties of CZTS thin films: effect of Cu-Zn disorder

Cu-Zn disorder is known to deeply affect kesterite (Cu2ZnSnS4, CZTS) due to the low temperature order-disorder phase transition, leading to a random occupation of the two cations in the shared crystallographic planes. This defect complex has been extensively studied in the thin film photovoltaic sector, with considerable efforts in developing methods to quantify disorder. In this study, a preliminary investigation of thermoelectric properties in temperature for thin film CZTS is presented. It is found that Cu-Zn disorder enhances both electrical conductivity and Seebeck coefficient. This can positively affect the thermoelectric performance, showing a mechanism of potential interest for a broad class of quaternary chalcogenides. The order-disorder transition is clearly visible in the electronic properties. This feature is repeatable, with samples from different preparations and groups showing consistent results, qualitatively suggesting electronic measurements as possible methods to quantify disorder. Furthermore, the reversibility of the transition allows the electronic properties to be tuned via specific thermal treatments, pointing to interesting applications in tunable electronics.

Materials, Actuators, and Sensors for Soft Bioinspired Robots

Biological systems can perform complex tasks with high compliance levels. This makes them a great source of inspiration for soft robotics. Indeed, the union of these fields has brought about bioinspired soft robotics, with hundreds of publications on novel research each year. This review aims to survey fundamental advances in bioinspired soft actuators and sensors with a focus on the progress between 2017 and 2020, providing a primer for the materials used in their design.

A Shapeshifting Ferrofluidic Robot

To create a miniature shapeshifting robot capable of controlled movement, subdivision, regeneration, passage through small channels, engulfment of particles, object manipulation, and flow manipulation, a droplet of magnetically responsive ferrofluid is used. The ferrofluidic robot can achieve the aforementioned functions when both its position and shape are controlled using a custom electromagnetic field generation system. It is demonstrated that the proposed robot can perform these functions with submillimeter and subdegree error. A robot having these capabilities can remotely perform medical and microassembly tasks requiring fine dexterity that are currently difficult or impossible.