Multi-Material Additively Manufactured Magnetoelectric Architectures with a Structure-Dependent Mechanical-to-Electrical Conversion Capability

Soft Magnetoelastic Tactile Multi-Sensors with Energy-Absorbing Properties for Self-Powered Human-Machine Interfaces

Tactile sensors play a key role in human-machine interfaces (HMIs) for augmented and virtual reality, point-of-care devices, and human-robot collaboration, which show the promise of revolutionizing our ways of life. Here, we present a sensor (EMTS) that utilizes the magnetoelastic effect in a soft metamaterial to convert mechanical pressure into electrical signals. With this unique mechanism, the proposed EMTS simultaneously possesses self-powering, waterproof, and compliant features. The soft metamaterial is essentially a porous magnetoelastomer structure designed based on the Fourier series expansion, which allows for programmable mechanical response and sensing performance of the EMTS. Fabricated by simple 3D-printed molds, the EMTS also holds potential for low-cost production. Particularly, the porous magnetoelastomer structure comes with selectable buckling instabilities that can significantly enhance biomechanical-to-electrical energy conversion. Also, with the embedded magnetic microparticles, the energy-absorbing performance of the sensor is greatly improved, which is highly beneficial to HMIs. To pursue practical applications, the EMTSs are further integrated with two systems as control and perception modules. It is demonstrated that the EMTS is able to identify different hand gestures to control a lighting system even in a high-humidity environment. Also, the EMTS stands out for its superior capability of simultaneous impact perception and energy absorption in drop tests. Overall, with its compelling array of features, the presented EMTS gives impetus to multi-sensing technology and practically enables a variety of HMI applications.

AC/DC Magnetic Field Sensing Based on a Piezoelectric Polymer and a Fully Printed Planar Spiral Coil

Additive manufacturing (AM) is emerging as an eco-friendly method for minimizing waste, as the demand for responsive materials in IoT and Industry 4.0 is on the rise. Magnetoactive composites, which are manufactured through AM, facilitate nonintrusive remote sensing and actuation. Printed magnetoelectric composites are an innovative method that utilizes the synergies between magnetic and electric properties. The study of magnetoelectric effects, including the recently validated piezoinductive effect, demonstrates the generation of electric voltage through external AC and DC magnetic fields. This shift in magnetic sensors, utilizing piezoinductive effect of the piezoelectric polymer poly(vinylidene fluoride), PVDF, eliminates the need for magnetic fillers in printed devices, aligning with sustainability principles, essential for the deployment of IoT and Industry 4.0. The achieved sensitivity surpasses other studies by 100 times, showcasing linear outputs for both applied AC and DC magnetic fields. Additionally, the sensor capitalizes on the linear phase shift of the generated signal with an applied DC magnetic field, an unprecedented effect. Thus, this work introduces a remarkable magnetoactive device with a sensitivity of ST = 95.1 ± 0.9 μV Oe-1 mT-1, a significantly improved performance compared to magnetoelectric devices using polymer composites. As a functional proof of concept of the developed system, a magnetic position sensor has been demonstrated.

Additively Manufactured Flexible Liquid Metal-Coated Self-Powered Magnetoelectric Sensors with High Design Freedom

Although additive manufacturing enables controllable structural design and customized performance for magnetoelectric sensors, their design and fabrication still require careful matching of the size and modulus between the magnetic and conductive components. Achieving magnetoelectric integration remains challenging, and the rigid coils limit the flexibility of the sensors. To overcome these obstacles, this study proposes a composite process combining selective laser sintering (SLS) and 3D transfer printing for fabricating flexible liquid metal-coated magnetoelectric sensors. The liquid metal forms a conformal conductive network on the SLS-printed magnetic lattice structure. Deformation of the structure alters the magnetic flux passing through it, thereby generating voltage. A reverse model segmentation and summation method is established to calculate the theoretical magnetic flux. The impact of the volume fraction, unit size, and height of the sensors on the voltage is studied, and optimization of these factors yields a maximum voltage of 45.6 µV. The sensor has excellent sensing performance with a sensitivity of 10.9 kPa-1 and a minimum detection pressure of 0.1 kPa. The voltage can be generated through various external forces. This work presents a significant advancement in fabricating liquid metal-based magnetoelectric sensors by improving their structural flexibility, magnetoelectric integration, and design freedom.

Highly Compressible 3D-Printed Soft Magnetoelastic Sensors for Human-Machine Interfaces

Incorporating perception into robots or objects holds great potential to revolutionize daily human life. To achieve this, critical factors include the design of an integrable three-dimensional (3D) soft sensor with self-powering capability, a wide working range, and tuneable functionalities. Here, we introduce a highly compressible 3D-printed soft magnetoelastic sensor with a wide strain sensing range. Inspired by the lattice metamaterial, which offers a highly porous structure with tuneable mechanical properties, we realized a remarkably compliant 3D self-powering sensor. Using magnetoelastic composite materials and 3D printing combined with sacrificial molding, a broad design space for constituent materials and structures is investigated, allowing for tuneable mechanical properties and sensor performances. These sensors are successfully integrated with two robotic systems as the robot operation and perception units, enabling robot control and recognition of diverse physical interactions with a user. Overall, we believe that this work represents a cornerstone for compliant 3D self-powered soft sensors, giving impetus to the development of advanced human-machine interfaces.

Electric Power Generated from Magnetic Nanofluid Droplets Sliding upon Superslippery Surfaces

An enduring challenge in the field of electric power generation employing magnetic nanofluids pertains to the inherent issue of solid-liquid adhesion, which results in random residue deposition of magnetic nanofluids on solid substrates during motion. Superslippery surfaces, characterized by their exceptional repellent properties and ultralow adhesion characteristics toward an extensive spectrum of fluids, offer an effective approach to ameliorate the aforementioned adhesive problem. Herein, it is demonstrated that electric power can be generated through the sliding of magnetic nanofluid droplets on superslippery surfaces. The electric power generation can be attributed to the change in magnetic flux caused by the magnetic nanofluid droplet passing or leaving a bottom coil associated with a magnet. By tailoring system parameters, such as the volume of the magnetic nanofluid or the vibration speed, the resulting maximal current can exceed 6 μA. An integrated device, featuring enclosed superslippery inner surfaces, can be securely attached to the arm of a volunteer, allowing for the conversion of mechanical energy into electricity. When the volunteer's arm moves, the electrical energy generated by the device can be utilized to light an LED lamp bead. The proposed strategy using superslippery surfaces facilitates low-adhesion transport of magnetic nanofluids, presenting an alternative solution to the development of next-generation solid/liquid energy harvesting devices.