Optics & Laser Technology, Год журнала: 2024, Номер 183, С. 112274 - 112274
Опубликована: Дек. 12, 2024
Язык: Английский
Optics & Laser Technology, Год журнала: 2024, Номер 183, С. 112274 - 112274
Опубликована: Дек. 12, 2024
Язык: Английский
Advanced Materials, Год журнала: 2024, Номер 36(48)
Опубликована: Окт. 14, 2024
High-work function transparent electrodes (HWFTEs) are key for establishing Schottky and Ohmic contacts with n-type p-type semiconductors, respectively. However, the development of printable materials that combine high transmittance, low sheet resistance, tunable work remains an outstanding challenge. This reports a high-performance HWFTE composed Ag nanowires enveloped conformally by Ti
Язык: Английский
Процитировано
4Advanced Materials, Год журнала: 2025, Номер unknown
Опубликована: Март 26, 2025
In the brain, both recording and decaying of memory information following external stimulus spikes are fundamental learning rules that determine human behaviors. The former is essential to acquire new knowledge update database, while latter filters noise autorefresh cache data reduce energy consumption. To execute these functions, brain relies on different neuromorphic transmitters possessing various kinetics, which can be classified as nonvolatile volatile memory. Inspired by electronic devices have been employed realize artificial neural networks spiking networks, respectively, emerged tools in machine learning. Molecular switches, capable responding electrical, optical, electrochemical, magnetic stimuli, display a disruptive potential for emulating storage devices. This Review highlights recent developments responsive molecules, their interfacing with low-dimensional nanostructures nanomaterials, integration into By capitalizing concepts, unique account neurotransmitter-transfer based molecules ad hoc kinetics provided. Finally, future directions, challenges, opportunities discussed use engineer more complex logic operations computing functions at hardware level.
Язык: Английский
Процитировано
0ACS Applied Materials & Interfaces, Год журнала: 2025, Номер unknown
Опубликована: Янв. 9, 2025
In modern computing, the Von Neumann architecture faces challenges such as memory bottleneck, hindering efficient processing of large datasets and concurrent programs. Neuromorphic inspired by brain's architecture, emerges a promising alternative, offering unparalleled computational power while consuming less energy. Artificial synaptic devices play crucial role in this paradigm shift. Various material systems, from organic to inorganic, have been explored for neuromorphic devices, with materials attracting attention their excellent photoelectric properties, diverse choices, versatile preparation methods. Organic semiconductors, particular, offer advantages over transition-metal dichalcogenides, including ease flexibility, making them suitable large-area films. This review focuses on emerging artificial based discussing different branches within semiconductor system, various fabrication methods, device structure designs, applications synapse. Critical considerations achieving truly human-like dynamic perception systems semiconductors are also outlined, reflecting ongoing evolution computing.
Язык: Английский
Процитировано
0Advanced Science, Год журнала: 2025, Номер unknown
Опубликована: Март 24, 2025
Neuromorphic computing systems convert multimodal signals to electrical responses for artificial intelligence recognition. Energy is consumed during both the response enhancement and depression, making suffer from high energy consumption. This study presents a neuromorphic pathway based on supercapacitors. MXene Ti₃C₂Tx supercapacitors are fabricated current stimuli voltage responses. The depression tunable through adjusting charging discharging stimuli, thus exhibiting synaptic plasticity. Typical behaviors demonstrated, including short-term memory, long-term paired-pulse facilitation, learning experience. Next, used recognize Braille numbers represented by 3 × 4 arrays. A charging/discharging pulse train representing each array applied supercapacitor. collected converted 12-pixel greyscale images. Once images 0-9 input into neural networks deep diffraction networks, 100% accuracy can be achieved recognizing ten numbers. Because stored in supercapacitor released once declines, this research demonstrates potential applications of storage devices computing, providing an innovative way develop energy-efficient brain-like systems.
Язык: Английский
Процитировано
0Chemical Engineering Journal, Год журнала: 2025, Номер unknown, С. 164191 - 164191
Опубликована: Май 1, 2025
Язык: Английский
Процитировано
0Journal of Molecular Structure, Год журнала: 2024, Номер unknown, С. 140201 - 140201
Опубликована: Сен. 1, 2024
Язык: Английский
Процитировано
1Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0Optics & Laser Technology, Год журнала: 2024, Номер 183, С. 112274 - 112274
Опубликована: Дек. 12, 2024
Язык: Английский
Процитировано
0