Bionic Tactile-Gustatory Receptor for Object Identification Based on All-Polymer Electrochemical Transistor

Monolithically integrated solid-state vertical organic electrochemical transistors switching between neuromorphic and logic functions

Manipulating the ionic-electronic coupling in organic electrochemical transistors (OECTs) offers opportunities for interesting phenomena and advanced applications but has not been systematically exploited. Here, we develop monolithically integrated solid-state vertical OECTs to fully explore polyelectrolyte's strengths, enabling the OECTs to switch between neuromorphic and logic functions. This transition capability is achieved by mastering the complex transport of large-size polycations within the channel through well-designed drain electrodes. Frame drains positioned atop the organic channel act as ion barriers, regulating the penetration and relaxation of polycations. This regulation allows our multilevel synaptic OECTs to transform from short-term depression (STD) to STD-based long-term memory, and eventually to long-term depression (LTD). Conversely, placing frame drains beneath the channel exposes the polyelectrolyte fully, hence yielding high-density logic OECTs, which have been successfully used to construct unipolar integrated circuits such as NOT, NAND, and NOR gates. These achievements represent a substantial advancement in manipulating polyelectrolyte-based ionic-electronic interactions, introducing more possibilities beyond small ion-based OECTs.

Gel-Based Electrolytes for Organic Electrochemical Transistors: Mechanisms, Applications, and Perspectives

Organic electrochemical transistors (OECTs) have emerged as the core component of specialized bioelectronic technologies due to their high signal amplification capability, low operating voltage (<1 V), and biocompatibility. Under a gate bias, OECTs modulate device operation via ionic drift between the electrolyte and the channel. Compared to common electrolytes with a fluid nature (including salt aqueous solutions and ion liquids), gel electrolytes, with an intriguing structure consisting of a physically and/or chemically crosslinked polymer network where the interstitial spaces between polymers are filled with liquid electrolytes or mobile ion species, are promising candidates for quasi-solid electrolytes. Due to relatively high ionic conductivity, the potential for large-scale integration, and the capability to suppress channel swelling, gel electrolytes have been a research highlight in OECTs in recent years. This review summarizes recent progress on OECTs with gel electrolytes that demonstrate good mechanical as well as physical and chemical stabilities. Moreover, various components in forming gel electrolytes, including different mobile liquid phases and polymer components, are introduced. Furthermore, applications of these OECTs in the areas of sensors, neuromorphics, and organic circuits, are discussed. Last, future perspectives of OECTs based on gel electrolytes are discussed along with possible solutions for existing challenges.

Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development

The food flavor science, traditionally reliant on experimental methods, is now entering a promising era with the help of artificial intelligence (AI). By integrating existing technologies with AI, researchers can explore and develop new flavor substances in a digital environment, saving time and resources. More and more research will use AI and big data to enhance product flavor, improve product quality, meet consumer needs, and drive the industry toward a smarter and more sustainable future. In this review, we elaborate on the mechanisms of flavor recognition and their potential impact on nutritional regulation. With the increase of data accumulation and the development of internet information technology, food flavor databases and food ingredient databases have made great progress. These databases provide detailed information on the nutritional content, flavor molecules, and chemical properties of various food compounds, providing valuable data support for the rapid evaluation of flavor components and the construction of screening technology. With the popularization of AI in various fields, the field of food flavor has also ushered in new development opportunities. This review explores the mechanisms of flavor recognition and the role of AI in enhancing food flavor analysis through high-throughput omics data and screening technologies. AI algorithms offer a pathway to scientifically improve product formulations, thereby enhancing flavor and customized meals. Furthermore, it discusses the safety challenges of integrating AI into the food flavor industry.

An evaluation of recent advancements in biological sensory organ-inspired neuromorphically tuned biomimetic devices

In the field of neuroscience, significant progress has been made regarding how the brain processes information. Unlike computer processors, the brain comprises neurons and synapses instead of memory blocks and transistors. Despite advancements in artificial neural networks, a complete understanding concerning brain functions remains elusive. For example, to achieve more accurate neuron replication, we must better understand signal transmission during synaptic processes, neural network tunability, and the creation of nanodevices featuring neurons and synapses. This study discusses the latest algorithms utilized in neuromorphic systems, the production of synaptic devices, differences between single and multisensory gadgets, recent advances in multisensory devices, and the promising research opportunities available in this field. We also explored the ability of an artificial synaptic device to mimic biological neural systems across diverse applications. Despite existing challenges, neuroscience-based computing technology holds promise for attracting scientists seeking to enhance solutions and augment the capabilities of neuromorphic devices, thereby fostering future breakthroughs in algorithms and the widespread application of cutting-edge technologies.

Highly Stretchable and Oriented Wafer-Scale Semiconductor Films for Organic Phototransistor Arrays

Stretchable organic phototransistor arrays have potential applications in artificial visual systems due to their capacity to perceive ultraweak light across a broad spectrum. Ensuring uniform mechanical and electrical performance of individual devices within these arrays requires semiconductor films with large-area scale, well-defined orientation, and stretchability. However, the progress of stretchable phototransistors is primarily impeded by their limited electrical properties and photodetection capabilities. Herein, wafer-scale and well-oriented semiconductor films were successfully prepared using a solution shearing process. The electrical properties and photodetection capabilities were optimized by improving the polymer chain alignment. Furthermore, a stretchable 10 × 10 transistor array with high device uniformity was fabricated, demonstrating excellent mechanical robustness and photosensitive imaging ability. These arrays based on highly stretchable and well-oriented wafer-scale semiconductor films have great application potential in the field of electronic eye and artificial visual systems.

All-Photolithography Fabrication of Ion-Gated Flexible Organic Transistor Array for Multimode Neuromorphic Computing

Organic ion-gated transistors (OIGTs) demonstrate commendable performance for versatile neuromorphic systems. However, due to the fragility of organic materials to organic solvents, efficient and reliable all-photolithography methods for scalable manufacturing of high-density OIGT arrays with multimode neuromorphic functions are still missing, especially when all active layers are patterned in high-density. Here, a flexible high-density (9662 devices per cm2) OIGT array with high yield and minimal device-to-device variation is fabricated by a modified all-photolithography method. The unencapsulated flexible array can withstand 1000 times' bending at a radius of 1 mm, and 3 months' storage test in air, without obvious performance degradation. More interesting, the OIGTs can be configured between volatile and nonvolatile modes, suitable for constructing reservoir computing systems to achieve high accuracy in classifying handwritten digits with low training costs. This work proposes a promising design of organic and flexible electronics for affordable neuromorphic systems, encompassing both array and algorithm aspects.