Nontrivial topological structures offer a rich playground in condensed matters and promise alternative device configurations for post-Moore electronics. While recently a number of polar topologies have been discovered in confined ferroelectric PbTiO₃ within artificially engineered PbTiO₃/SrTiO₃ superlattices, little attention was paid to possible topological polar structures in SrTiO₃. Here we successfully create previously unrealized polar antivortices within the SrTiO₃ of PbTiO₃/SrTiO₃ superlattices, accomplished by carefully engineering their thicknesses guided by phase-field simulation. Field- and thermal-induced Kosterlitz–Thouless-like topological phase transitions have also been demonstrated, and it was discovered that the driving force for antivortex formation is electrostatic instead of elastic. This work completes an important missing link in polar topologies, expands the reaches of topological structures, and offers insight into searching and manipulating polar textures.

Laser-induced graphene (LIG) is a simple, environmentally friendly, efficient, and less costly method, as well as can form various shapes on a flexible substrate in situ without the use of masks. More importantly, it can tune the work function of LIG easily by changing laser parameters to control the transportation of carriers. In this work, the work functions of LIG were controlled by adjusting the frequency or speed of the laser, and a series of LIG/GaO_x Schottky photodetectors were formed. When the work function of the graphene increases, the Fermi energy is shifted below the crossing point of the Π and Π^* bands, and then more electrons or holes can be activated to participate in the conduction process, resulting in low resistance. Meanwhile, a large built-in electric field can be formed when using a high work function LIG, which is more beneficial to separate photo-generated carriers. Enabled by the controllable LIG, LIG/GaO_x Schottky photodetectors can be modulated to have high photoresponsivity or self-powered characteristics. Our work provides a high-performance photodetector with excellent mechanical flexibility and long-life stability, promising applications in the flexible optoelectronic fields.

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.