Electret Molecular Configuration Induced Programmable Photonic Memory for Advanced Logic Operation and Data Encryption

Abstract

Nonvolatile organic photonic transistor (OPT) memories have attracted widespread attention due to their nondestructive readout, remote controllability, and robust tunability. Developing electrets with similar molecular structures but different memory behaviors and light‐responsive features is crucial for light‐wavelength‐modulated data encryption. However, reported OPT memories have yet to meet this challenge. Here a new electret molecule (“H‐PDI”) is developed via reconfiguring the linear perylene diimide molecule (“L‐PDI”) to a helical shape. Respectively incorporating H‐PDI and L‐PDI into the floating gate layer results to H‐PDI OPT and L‐PDI OPT. Attributing to their remarkably different electronic structures and energy bandgaps, H‐PDI OPT and L‐PDI OPT preferably respond to 405 and 532 nm light irradiation, respectively. Upon electrical programming, data can be written and stored in both memories with good retention features and a high “1”/“0” state current ratio over 105, though the data can only be erased by light with correct wavelengths, rather than the electrical field. Moreover, data stored in a memory array consisting of both H‐PDI OPT and L‐PDI OPT can only be read out by correct inputs, and wrong inputs will lead to highly deceptive outputs. This study provides a general design strategy of OPT for advanced data encryption and protection.

MXene hybrid nanocomposites enable high performance memory devices and artificial synapse applications

“…Floating-gate organic field effect transistor (FG-OFET) memory devices, which are fabricated by introducing an additional charge storage layer between the dielectric layer and the organic semiconductor layer, have emerged as one of the most promising candidates for next-generation artificial intelligence and brain-like computing, due to the non-volatile memory (NVM), nondestructive readout, high stability, and low operating current within a single device. [1][2][3][4][5] Considerable efforts have been devoted to developing FG-OFET memory devices and remarkable advances have been achieved. [6][7][8][9] Among them, the floating gate material plays an essential role in terms of storage performance, including the memory window, threshold voltage and retention time.…”

Insulating Electrets Converted from Organic Semiconductor for High‐Performance Transistors, Memories, and Artificial Synapses

“…The resulting oxygen‐degraded C 8 ‐PTCDI (D) features deep traps, with more trap density and deep trap energy levels. This property is useful not only for transistors, memories, and artificial synapses, [ 5 ] but also for other electret‐based devices such as energy harvesting, [ 6 ] logic operation and data encryption, [ 7 ] high response piezoelectric elastomers, [ 8 ] air‐permeable vibrotactile actuators, [ 9 ] liquid‐solid‐based triboelectric nanogenerators, [ 10 ] smart active sensing. [ 11 ]…”

Tailoring Wavelength-Adaptive Visual Neuroplasticity Transitions of Synaptic Transistors Comprising Rod-Coil Block Copolymers for Dual-Mode Photoswitchable Learning/Forgetting Neural Functions

“…To date, a variety of photoactive materials have been explored, including inorganic and hybrids, – conjugated molecules, , natural chromophores, , or conjugated/insulating polymers, – for light harvesting in semiconducting channels or embedded in dielectric to ensure signal transmission of artificial synapses. A wide range of proposed device architecture approaches, including (i) a photogate-embedded composite semiconducting channel; – (ii) a photoactive electret beneath the semiconducting channel; , and (iii) a photogate-embedded insulating electret beneath the semiconducting channel, , all of which exploit this phenomenon by altering the conductance level in semiconducting channels through photoexcitation-induced charge transfer. For the optical stimulation aspect thereof, the most prominent forms of synaptic functionality are realized regarding photoexcitatory potentiation of synaptic weight in two major ways: short-term plasticity (STP) and long-term plasticity (LTP) triggered by excitatory postsynaptic current (EPSC) enhancement for all types of photosynaptic transistors. , Indeed, a rehearsal learning process of the human brain was mimicked to test the dynamic visual learning/forgetting behavior of photosynaptic transistors, which is influenced by the synaptic weight along with the rate and number of pulses, pulse intensity, pulse width, and wavelength, such as brain activity during learning, depending on the frequency, time, and intensity of data rehearsal .…”