Publications by authors named "Langlang Xu"
Biological neural circuits demonstrate exceptional adaptability to diverse tasks by dynamically adjusting neural connections to efficiently process information. However, current two-dimension materials-based neuromorphic hardware mainly focuses on specific devices to individually mimic artificial synapse or heterosynapse or soma and encoding the inner neural states to realize corresponding mock object function. Recent advancements suggest that integrating multiple two-dimension material devices to realize brain-like functions including the inter-mutual connecting assembly engineering has become a new research trend.
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- Nonlinear optical responses in 2D materials can enable advanced free-space optical neuromorphic computing, offering a blend of high performance and tunability for diverse functions.
- Challenges arise from conventional methods that struggle to balance performance and flexibility, often leading to compromises.
- A new approach using bare molybdenum disulfide arrays enhances modulation performance and energy efficiency while improving tunability, showcasing the potential for optical artificial neural networks and digital processing in neuromorphic applications.
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- Researchers developed a new artificial visual system using 2D materials that mimics the human visual pathway, aiming to improve artificial intelligence vision functionalities.
- The innovative hardware features crossbar arrays with tungsten diselenide (WSe) units that replicate the retina and visual cortex, along with peripheral circuits to emulate their connections.
- This advanced system demonstrates capabilities like processing red-green color blindness, low-power shape recognition, and motion tracking, which could enhance machine vision, driverless technology, brain-computer interfaces, and intelligent robotics.
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- The review discusses the rising interest in 2D layered materials like graphene and h-BN, emphasizing advancements in strain engineering.
- It highlights how applying strain can modify physical properties, improving the performance of devices across various applications.
- The review also summarizes methods of strain engineering and explores its effects on multiple properties of these materials while addressing future applications and research challenges in fields like optoelectronics and spintronics.
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- Ternary computing systems can achieve higher information density with fewer devices compared to binary systems, but often require extra components to connect binary and ternary processing.
- Researchers have developed a 2D van der Waals vertical heterojunction transistor (V-HTR) that features three conductance states, allowing direct ternary processing without needing additional devices.
- This V-HTR has been used to create a ternary neural network that efficiently eliminates fuzzy data and outputs clear results, showcasing its potential as a fundamental hardware unit for future ternary computing applications.
Mesoporous silica nanoparticles (MSNs) are experiencing rapid development in the biomedical field for imaging and for use in heterogeneous catalysis. Although the synthesis of MSNs with various morphologies and particle sizes has been reported, synthesis of a pore network with monodispersion control below 200 nm is still challenging. We achieved this goal using mild conditions.
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