RESUMO
Cephalopod (e.g., squid, octopus, etc.) skin is a soft cognitive organ capable of elastic deformation, visualizing, stealth, and camouflaging through complex biological processes of sensing, recognition, neurologic processing, and actuation in a noncentralized, distributed manner. However, none of the existing artificial skin devices have shown distributed neuromorphic processing and cognition capabilities similar to those of a cephalopod skin. Thus, the creation of an elastic, biaxially stretchy device with embedded, distributed neurologic and cognitive functions mimicking a cephalopod skin can play a pivotal role in emerging robotics, wearables, skin prosthetics, bioelectronics, etc. This paper introduces artificial neuromorphic cognitive skins based on arrayed, biaxially stretchable synaptic transistors constructed entirely out of elastomeric materials. Systematic investigation of the synaptic characteristics such as the excitatory postsynaptic current, paired-pulse facilitation index of the biaxially stretchable synaptic transistor under various levels of biaxial mechanical strain sets the operational foundation for stretchy distributed synapse arrays and neuromorphic cognitive skin devices. The biaxially stretchy arrays here achieved neuromorphic cognitive functions, including image memorization, long-term memorization, fault tolerance, programming, and erasing functions under 30% biaxial mechanical strain. The stretchy neuromorphic imaging sensory skin devices showed stable neuromorphic pattern reinforcement performance under both biaxial and nonuniform local deformation.
Assuntos
Órgãos Artificiais , Robótica , Pele , Sinapses , Animais , Cefalópodes , Cognição , Pele/inervação , Transistores EletrônicosRESUMO
Conductive fibers are core materials in textile electronics for the sustainable operation of devices under mechanical stimuli. Conventional polymer-metal core-sheath fibers were employed as stretchable electrical interconnects. However, their electrical conductivity is severely degraded by the rupture of metal sheaths at low strains. Because the core-sheath fibers are not intrinsically stretchable, designing a stretchable architecture of interconnects based on the fibers is essential. Herein, we introduce nonvolatile droplet-conductive microfiber arrays as stretchable interconnects by employing interfacial capillary spooling, motivated by the reversible spooling of capture threads in a spider web. Polyurethane (PU)-Ag core-sheath (PU@Ag) fibers were prepared by wet-spinning and thermal evaporation. When the fiber was placed on a silicone droplet, a capillary force was generated at their interface. The highly soft PU@Ag fibers were fully spooled within the droplet and reversibly uncoiled when a tensile force was applied. Without mechanical failures of the Ag sheaths, an excellent conductivity of 3.9 × 104 S cm-1 was retained at a strain of 1200% for 1000 spooling-uncoiling cycles. A light-emitting diode connected to a multiarray of droplet-PU@Ag fibers exhibited stable operation during spooling-uncoiling cycles.
RESUMO
As attractive photoactive materials, metal halide perovskites demonstrate outstanding performance in a wide range of optoelectronic applications. Among the various compositions studied, mixed-halide perovskites have a finely tunable band gap that renders them desirable for targeted applications. Despite their advantages, photoinduced halide segregation often deters the photoelectric stability of the materials. Herein, we adopt a strategy of post-treating the perovskite surface with an organic spacer to generate a two-dimensional (2D) perovskite passivating layer. Trap-assisted recombination pathways can be selectively modulated by passivating the surface halide defects that cause photoinduced halide segregation. Fluorescence lifetime imaging of flat and bent surfaces of perovskites reveals that the perovskite lattice tolerates mechanical strain via the neutralizing passivation of ionic halide defects. Upon bending, the photocurrent response of the flexible photodetector is maintained over 83% for 2D passivated perovskite and drops to 23% for pristine perovskite. A flexible photodetector array built with 2D passivated perovskite, in combination with a deep learning algorithm, demonstrates excellent accuracy in determining letters of the alphabet for both flat (>96%) and bent (>93%) states. The connection of chemically modified charge carrier dynamics and mechanical properties revealed in this study offers valuable guidance for developing next-generation optoelectronic applications.