Multiferroic CoFe2O4–Pb(Zr0.52Ti0.48)O3 core-shell nanofibers have been synthesized by coaxial electrospinning in combination with a sol-gel process. The core-shell configuration of nanofibers has been verified by scanning electron microscopy and transmission electron microscopy, and the spinel structure of CoFe2O4 and perovskite structure of Pb(Zr0.52Ti0.48)O3 have been confirmed by X-ray diffraction and selected area electron diffraction. The multiferroic properties of core-shell nanofibers have been demonstrated by magnetic hysteresis and piezoresponse force microscopy, and their magnetoelectric coupling has been confirmed by evolution of piezoresponse under an external magnetic field, showing magnetically induced ferroelectric domain switching and changes in switching characteristics. The lateral magnetoelectric coefficient is estimated to be 2.95 × 104 mV/cmOe, two orders of magnitude higher than multiferroic thin films of similar composition.
Neuromorphic computing has the potential to accelerate high performance parallel and low power in-memory computation, artificial intelligence, and adaptive learning. Despite emulating the basic functions of biological synapses well, the existing artificial electronic synaptic devices have yet to match the softness, robustness, and ultralow power consumption of the brain. Here, we demonstrate an all-inorganic flexible artificial synapse enabled by a ferroelectric field effect transistor based on mica. The device not only exhibits excellent electrical pulse modulated conductance updating for synaptic functions but also shows remarkable mechanical flexibility and high temperature reliability, making robust neuromorphic computation possible under external disturbances such as stress and heating. Based on its linear, repeatable, and stable long-term plasticity, we simulate an artificial neural network for the Modified National Institute of Standards and Technology handwritten digit recognition with an accuracy of 94.4%. This work provides a promising way to enable flexible, low-power, robust, and highly efficient neuromorphic computation that mimics the brain.
Novel nanocrystalline ultrafine fibers have been synthesized by sol-gel based electrospinning, with fiber diameter in the range of 100–300 nm and grain size of around 20 nm. Phase pure perovskite can be obtained if the fibers are fired in Ar atmosphere, eliminating impurity phases often observed when fired in air or atmosphere. Excellent piezoelectricity and clear ferroelectric domain structure of the ultrafine fibers are characterized by high voltage piezoresponse force microscopy. Enhanced weak ferromagnetism arising from the nanocrystalline structure of ultrafine fibers is also observed.
Multiferroic materials possess two or more types of orders simultaneously that couple the electric and magnetic fields, and composite multiferroics have been widely explored for their excellent magnetoelectric coupling. In this letter, we report a strategy to hybrid multiferroicity at nanoscale. Multiferroic nanofibers are synthesized by sol-gel process and electrospinning, the spinel structure of (CFO) and perovskite structure of (PZT) are verified by x-ray diffraction and high resolution transmission electron microscopy, and the multiferroicity of the nanofibers are confirmed by piezoresponse force microscopy and magnetic hysteresis. Excellent ferroelectric and ferromagnetic properties have been observed, which could enable multiferroic devices at nanoscale.
Semitransparent solar cells have attracted significant attention for their potential applications, though obtaining high average visible transmittance (AVT) while maintaining good conversion efficiency is a challenge. Here, we report a method to fabricate fully printable semitransparent perovskite solar cells with a (5-AVA)0.05(MA)0.95PbI3 infiltrated mesoporous TiO2/Al2O3/carbon architecture. Carbon grids were printed as top electrodes, and the effects of the grid spacing on device performance were systematically investigated. Under the smallest grid spacing, the highest power conversion efficiency (PCE) of 11.31% was achieved, though the AVT was low. By adjusting the grid spacing, the highest AVT of 26.4% was obtained, though the PCE dropped to 5.36%. A thin layer of multi-walled carbon nanotubes (MWCNTs) was then introduced on the top electrode, which improved both the conductivity and charge transfer characteristic of the electrode, resulting in a high PCE of 8.21% while maintaining a good AVT of 24.0%.