Harnessing Deep Learning of Point Clouds for Inverse Control of 3D Shape Morphing

Shape-morphing devices, a crucial branch in soft robotics, hold significant application value in areas like human-machine interfaces, biomimetic robotics, and tools for interacting with biological systems. To achieve three-dimensional (3D) programmable shape morphing (PSM), the deployment of array-based actuators is essential. However, a critical knowledge gap impeding the development of 3D PSM is the challenge of controlling the complex systems formed by these soft actuator arrays. This study introduces a novel approach, for the first time, representing the configuration of shape morphing devices using point cloud data and employing deep learning to map these configurations to control inputs. We propose Shape Morphing Net (SMNet), a method that realizes the regression from point cloud data to high-dimensional continuous vectors. Applied to previous 2D PSM actuator arrays, SMNet significantly enhances control precision from 82.23% to 97.68%. Further, we extend its application to 3D PSM devices with three different actuator mechanisms, demonstrating the universal applicability of SMNet to the control of 3D shape morphing technologies. In our demonstrations, we confirm the efficacy of inverse control, where 3D PSM devices successfully replicate target shapes. These shapes are obtained either through 3D scanning of physical objects or via 3D modeling software. The results show that within the deformable range of 3D PSM devices, accurate reproduction of the desired shapes is achievable. The findings of this research represent a substantial advancement in soft robotics, particularly for applications demanding intricate 3D shape transformations, and establish a foundational framework for future developments in the field

Roadmap on printable electronic materials for next-generation sensors

The dissemination of sensors is key to realizing a sustainable, ‘intelligent’ world, where everyday objects and environments are equipped with sensing capabilities to advance the sustainability and quality of our lives—e.g., via smart homes, smart cities, smart healthcare, smart logistics, Industry 4.0, and precision agriculture. The realization of the full potential of these applications critically depends on the availability of easy-to-make, low-cost sensor technologies. Sensors based on printable electronic materials offer the ideal platform: they can be fabricated through simple methods (e.g., printing and coating) and are compatible with high-throughput roll-to-roll processing. Moreover, printable electronic materials often allow the fabrication of sensors on flexible/stretchable/biodegradable substrates, thereby enabling the deployment of sensors in unconventional settings. Fulfilling the promise of printable electronic materials for sensing will require materials and device innovations to enhance their ability to transduce external stimuli—light, ionizing radiation, pressure, strain, force, temperature, gas, vapours, humidity, and other chemical and biological analytes. This Roadmap brings together the viewpoints of experts in various printable sensing materials—and devices thereof—to provide insights into the status and outlook of the field. Alongside recent materials and device innovations, the roadmap discusses the key outstanding challenges pertaining to each printable sensing technology. Finally, the Roadmap points to promising directions to overcome these challenges and thus enable ubiquitous sensing for a sustainable, ‘intelligent’ world

In silico optimization of aligned fiber electrodes for dielectric elastomer actuators

Abstract Dielectric elastomer actuators (DEAs) exhibit fast actuation and high efficiencies, enabling applications in optics, wearable haptics, and insect-scale robotics. However, the non-uniformity and high sheet resistance of traditional soft electrodes based on nanomaterials limit the performance and operating frequency of the devices. In this work, we computationally investigate electrodes composed of arrays of stiff fiber electrodes. Aligning the fibers along one direction creates an electrode layer that exhibits zero stiffness in one direction and is predicted to possess high and uniform sheet resistance. A comprehensive parameter study of the fiber density and dielectric thickness reveals that the fiber density primary determines the electric field localization while the dielectric thickness primarily determines the unit cell stiffness. These trends identify an optimal condition for the actuation performance of the aligned electrode DEAs. This work demonstrates that deterministically designed electrodes composed of stiff materials could provide a new paradigm with the potential to surpass the performance of traditional soft planar electrodes

Highly Skin-Conformal Microhairy Sensor for Pulse Signal Amplification

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A bioinspired flexible organic artificial afferent nerve

The distributed network of receptors, neurons, and synapses in the somatosensory system efficiently processes complex tactile information. We used flexible organic electronics to mimic the functions of a sensory nerve. Our artificial afferent nerve collects pressure information (1 to 80 kilopascals) from clusters of pressure sensors, converts the pressure information into action potentials (0 to 100 hertz) by using ring oscillators, and integrates the action potentials from multiple ring oscillators with a synaptic transistor. Biomimetic hierarchical structures can detect movement of an object, combine simultaneous pressure inputs, and distinguish braille characters. Furthermore, we connected our artificial afferent nerve to motor nerves to construct a hybrid bioelectronic reflex arc to actuate muscles. Our system has potential applications in neurorobotics and neuroprosthetics.

A skin-inspired organic digital mechanoreceptor.

Human skin relies on cutaneous receptors that output digital signals for tactile sensing in which the intensity of stimulation is converted to a series of voltage pulses. We present a power-efficient skin-inspired mechanoreceptor with a flexible organic transistor circuit that transduces pressure into digital frequency signals directly. The output frequency ranges between 0 and 200 hertz, with a sublinear response to increasing force stimuli that mimics slow-adapting skin mechanoreceptors. The output of the sensors was further used to stimulate optogenetically engineered mouse somatosensory neurons of mouse cortex in vitro, achieving stimulated pulses in accordance with pressure levels. This work represents a step toward the design and use of large-area organic electronic skins with neural-integrated touch feedback for replacement limbs

Stretchable Self-Healing Polymeric Dielectrics Cross-Linked Through Metal–Ligand Coordination

A self-healing dielectric elastomer is achieved by the incorporation of metal–ligand coordination as cross-linking sites in nonpolar polydimethylsiloxane (PDMS) polymers. The ligand is 2,2′-bipyridine-5,5′-dicarboxylic amide, while the metal salts investigated here are Fe²⁺ and Zn²⁺ with various counteranions. The kinetically labile coordination between Zn²⁺ and bipyridine endows the polymer fast self-healing ability at ambient condition. When integrated into organic field-effect transistors (OFETs) as gate dielectrics, transistors with FeCl₂ and ZnCl₂ salts cross-linked PDMS exhibited increased dielectric constants compared to PDMS and demonstrated hysteresis-free transfer characteristics, owing to the low ion conductivity in PDMS and the strong columbic interaction between metal cations and the small Cl^– anions which can prevent mobile anions drifting under gate bias. Fully stretchable transistors with FeCl₂-PDMS dielectrics were fabricated and exhibited ideal transfer characteristics. The gate leakage current remained low even after 1000 cycles at 100% strain. The mechanical robustness and stable electrical performance proved its suitability for applications in stretchable electronics. On the other hand, transistors with gate dielectrics containing large-sized anions (BF₄^–, ClO₄^–, CF₃SO₃^–) displayed prominent hysteresis due to mobile anions drifting under gate bias voltage. This work provides insights on future design of self-healing stretchable dielectric materials based on metal–ligand cross-linked polymers

A skin-inspired organic digital mechanoreceptor.

Human skin relies on cutaneous receptors that output digital signals for tactile sensing in which the intensity of stimulation is converted to a series of voltage pulses. We present a power-efficient skin-inspired mechanoreceptor with a flexible organic transistor circuit that transduces pressure into digital frequency signals directly. The output frequency ranges between 0 and 200 hertz, with a sublinear response to increasing force stimuli that mimics slow-adapting skin mechanoreceptors. The output of the sensors was further used to stimulate optogenetically engineered mouse somatosensory neurons of mouse cortex in vitro, achieving stimulated pulses in accordance with pressure levels. This work represents a step toward the design and use of large-area organic electronic skins with neural-integrated touch feedback for replacement limbs

A Rapid and Facile Soft Contact Lamination Method: Evaluation of Polymer Semiconductors for Stretchable Transistors

Organic stretchable electronics have attracted extensive scientific and industrial interest because they can be stretched, twisted, or compressed, enabling the next-generation of organic electronics for human/machine interfaces. These electronic devices have already been described for applications such as field-effect transistors, photovoltaics, light-emitting diodes, and sensors. High-performance stretchable electronics, however, currently still involve complicated processing steps to integrate the substrates, semiconductors, and electrodes for effective performance. Herein, we describe a facile method to efficiently identify suitable semiconducting polymers for organic stretchable transistors using soft contact lamination. In our method, the various polymers investigated are first transferred on an elastomeric poly­(dimethylsiloxane) (PDMS) slab and subsequently stretched (up to 100%) along with the PDMS. The polymer/PDMS matrix is then laminated on source/drain electrode-deposited Si substrates equipped with a PDMS dielectric layer. Using this device configuration, the polymer semiconductors can be repeatedly interrogated with laminate/delaminate cycles under different amounts of tensile strain. From our obtained electrical characteristics, e.g., mobility, drain current, and on/off ratio, the strain limitation of semiconductors can be derived. With a facile soft contact lamination testing approach, we can thus rapidly identify potential candidates of semiconducting polymers for stretchable electronics