Well‐Designed Organic Semiconductors With Tunable Resistive Switching Behaviors for Multilevel Storage and Neuromorphic Computing

ABSTRACT Designing new materials with high‐performance resistive switching (RS) behaviors and/or developing alternative means to modulate the RS behaviors are of great significance for information storage and neuromorphic computing. Herein, we present a novel strategy to design and synthesize furan‐annulated naphthalenes for high‐performance digital and analog RS behaviors through controlling substituents. By introducing an electron acceptor of trifluoromethyl on the phenyl ring, 3‐phenyl‐4‐(4‐trifluoromethylphenyl)‐2 H ‐naphtho[1,8‐ bc ]furan (TPNF) is synthesized with donor–acceptor (D–A) pairs by utilizing the electron donor of furyl in the naphthalene. Owing to the constructed D–A systems where electrons can be transported under the external bias voltage, the prepared TPNF thin films demonstrate high‐performance bipolar digital RS behaviors with multilevel storage characteristics. On the other hand, if the substituent on the phenyl ring is replaced by an electron donor of methoxy, 4‐(4‐methoxyphenyl)‐3‐phenyl‐2 H ‐naphtho[1,8‐ bc ]furan (MPNF) can be constructed with only electron‐donor units of furyl and methoxy. The fabricated MPNF thin films show analog RS behaviors owing to the carrier trapping/detrapping from the nucleophilic trapping sites generated from the electron‐donor units. The analog memristors demonstrate synaptic functions with high linearity of conductance modulation, which is highly desirable for neuromorphic computing. Such synaptic memristors based on MPNF are completely capable of recognizing digit images with high accuracy (95.2%) and implementing decimal arithmetic of addition, subtraction, multiplication, and division operations. This study provides a feasible way to modulate the RS properties by the strategy of introducing different substituents, demonstrating promising applications of such well‐designed organic semiconductors for multilevel storage and neuromorphic computing.