Field-effect bulk mobilities in polymer semiconductor films measured by sourcemeters.

Semiconducting polymers inherently exhibit polydispersity in terms of molecular structure and microscopic morphology, which often results in a broad distribution of energy levels for localized electronic states. Therefore, the bulk charge mobility strongly depends on the free charge density. In this study, we propose a method to measure the charge-density-dependent bulk mobility of conjugated polymer films with widely spread localized states using a conventional field-effect transistor configuration. The gate-induced variation of bulk charge density typically ranges within ±1018 cm-3; however, this range depends significantly on the energetic dispersion width of localized states. The field-effect bulk mobility and field-effect mobility near the semiconductor-dielectric interface along with their dependence on charge density can be simultaneously extracted from the transistor characteristics using various gate voltage ranges.

High-performance asymmetric electrode structured light-stimulated synaptic transistor for artificial neural networks.

Photonics neuromorphic computing shows great prospects due to the advantages of low latency, low power consumption and high bandwidth. Transistors with asymmetric electrode structures are receiving increasing attention due to their low power consumption, high optical response, and simple preparation technology. However, intelligent optical synapses constructed by asymmetric electrodes are still lacking systematic research and mechanism analysis. Herein, we present an asymmetric electrode structure of the light-stimulated synaptic transistor (As-LSST) with a bulk heterojunction as the semiconductor layer. The As-LSST exhibits superior electrical properties, photosensitivity and multiple biological synaptic functions, including excitatory postsynaptic currents, paired-pulse facilitation, and long-term memory. Benefitting from the asymmetric electrode configuration, the devices can operate under a very low drain voltage of 1 × 10-7 V, and achieve an ultra-low energy consumption of 2.14 × 10-18 J per light stimulus event. Subsequently, As-LSST implemented the optical logic function and associative learning. Utilizing As-LSST, an artificial neural network (ANN) with ultra-high recognition rate (over 97.5%) of handwritten numbers was constructed. This work presents an easily-accessible concept for future neuromorphic computing and intelligent electronic devices.

Enhanced Multiwavelength Response of Flexible Synaptic Transistors for Human Sunburned Skin Simulation and Neuromorphic Computation.

In biological species, optogenetics and bioimaging work together to regulate the function of neurons. Similarly, the light-controlled artificial synaptic system not only enhances computational speed but also simulates complex synaptic functions. However, reported synaptic properties are mainly limited to mimicking simple biological functions and single-wavelength responses. Therefore, the development of flexible synaptic devices with multiwavelength optical signal response and multifunctional simulation remains a challenge. Here, flexible organic light-stimulated synaptic transistors (LSSTs) enabled by alumina oxide (AlOX ), with a simple fabrication process, are reported. By embedding AlOX nanoparticles, the excitons separation efficiency is improved, allowing for multiple wavelength responses. Optimized LSSTs can respond to multiple optical and electrical signals in a highly synaptic manner. Multiwavelength optical synaptic plasticity, electrical synaptic plasticity, sunburned skin simulation, learning efficiency model controlled by photoelectric cooperative stimulation, neural network computing, "deer" picture learning and memory functions are successfully proposed, which promote the development for future artificial intelligent systems. Furthermore, as prepared flexible transistors exhibit mechanical flexibility with bending radius down to 2.5 mm and improved photosynaptic plasticity, which facilitating development of neuromorphic computing and multifunction integration systems at the device-level.

Artificial Tactile Recognition Enabled by Flexible Low-Voltage Organic Transistors and Low-Power Synaptic Electronics.

The advancement of self-powered intelligent strain systems for human-computer interaction is crucial toward wearable and energy-saving applications. Simultaneously, lowering operating voltage and thus reducing power consumption are of particular interests. A brain-like smart synaptic hardware system is considered as a promising candidate for low-power, parallel computing and learning processes. However, the combination of low-voltage organic transistors and energy efficient smart synapse hardware systems driven by a tactile signal has been hindered by the limited materials and technology. Here, by employing an elastomeric copolymer poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) with a high HFP content of 25 mol %, flexible, low-voltage transistors (|VG| ≤ 3 V) and a low energy consumption synapse ≤ 9.2 × 10-17 J are devised simultaneously, along with the lowest quality factor (R = Pw × VG, 2.76 × 10-16 J V). Furthermore, based on the low voltage and low power consumption characteristics, flexible artificial tactile recognition system and Morse code recognition are established without any computing supporting. Mechanical flexibility, cycling stability, image contrast enhancement functions, and simulated pattern recognition accuracy of the multilayer perceptron neural network are also simulated. This work recommends a route of exploiting low voltage, low power consumption synaptic systems and smart human-machine interfaces with low energy loss based on flexible organic synaptic transistors.

Ultralow-Power and Radiation-Tolerant Complementary Metal-Oxide-Semiconductor Electronics Utilizing Enhancement-Mode Carbon Nanotube Transistors on Paper Substrates.

The development of eco-friendly, ultralow-power and easy-to-process electronics is facing dominant challenges in emerging off-the-grid applications, such as the Internet of Things (IoTs) and extreme environment explorations at the south/north pole, in the deep sea, and in outer space. Eco-friendly, biodegradable, lightweight, and flexible paper-based electronics can provide many new possibilities for next-generation devices and circuits. Here, enhancement-mode (E-mode, remaining off state at zero gate voltages) carbon nanotube (CNT) complementary metal-oxide-semiconductor (CMOS) thin-film transistors (TFTs) are built on paper substrates through a printing-based process. Benefitting from the CMOS circuit style and E-mode transistors, the fabricated CMOS inverters exhibit high voltage gains (more than 11) and noise margins (up to 75% 1/2 VDD at VDD of 0.4 V), and rail-to-rail operation down to a VDD as low as 0.2 V and record low power dissipation as low as 0.0124 pW µm-1 . Furthermore, the transistors and integrated circuits (ICs) show an excellent radiation tolerance of a total ionizing dose (TID) exceeding 2 Mrad with a high dose rate of 365 rad s-1 . The record power consumption and outstanding radiation tolerance behavior achieved in paper-based and easy-to-process CNT electronics are attractive for emerging energy-saving and environmentally friendly ICs in harsh environment (such as outer-space) applications.