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Updated: Apr 1, 2026

Ultrahigh Density Array of Vertically Aligned Small-molecular Organic Nanowires on Arbitrary Substrates
Published on: June 18, 2013
Vertical Growth of Ultrathin Bi2WO6 Nanosheets for Visual Optoelectronic Neuromorphic Devices
Bing Wang1, Yuyu He1, Wanying Chen1
1Tianjin Key Lab for Rare Earth Materials and Applications, Center For Rare Earth and Inorganic Functional Materials, School of Materials Science and Engineering, Nankai University, Tianjin, China.
Abstract:
Planar-grown 2D Bi2WO6 is promising for ferroelectric and opto-synaptic applications, but the fabrication of the device relies on organic solvents, which introduce residues. As a result, the devices show short opto-synaptic memory and non-electrically erasable behavior, limiting their suitability for neuromorphic applications. Therefore, developing stable preparation methods for vertical 2D Bi2WO6 samples and exploring their applications in low-power neuromorphic devices are of significant importance. Here, ultrathin Bi2WO6 nanosheets with tunable vertical and planar morphologies are synthesized via controlled one-step chemical vapor deposition (CVD), where vertically aligned configurations enable residue-free transfer. Building on this, simple two-terminal Bi2WO6 optoelectronic synaptic devices that exhibit an ultralow dark current (∼0.1 pA), a high I_ph/I_dark ratio (>105), and long memory retention (∼25 000 s) are fabricated. These devices successfully emulate key synaptic functions, including excitatory postsynaptic currents (EPSC), paired-pulse facilitation (PPF), and short-to-long-term plasticity (STP-to-LTP) transitions under optical stimuli. Critically, optically programmed long-term potentiation (LTP) and electrically erased long-term depression (LTD) are achieved with ultra-low energy consumption below 1 pJ per operation. The Bi2WO6 devices, through their optically programmable plasticity and energy-efficient neuromorphic operation, demonstrate significant potential for next-generation artificial vision systems, sensing-memory-computing integrated architectures, and high-fidelity neuromorphic hardware.

