Buscar recursos académicos

Brain-inspired neuromorphic computing systems require hardware components analogous to biological neurons and synapses. Honey based natural organic memristor has demonstrated promising nonvolatile memristive behaviors, w...

Machine learning (ML) and neuromorphic computing have been enforcing problem-solving in many applications. Such approaches found fertile ground in optical communications, a technological field that is very demanding in t...

Photonic computing and neuromorphic computing are attracting tremendous interests in breaking the memory wall of traditional von Neumann architecture. Photonic memristors equipped with light sensing, data storage, and in...

Abstract Vertical integration of two-dimensional materials holds tremendous potential for integrated sensing, memory, and computing applications, yet it still confronts challenges such as single device functionality, lim...

Memristors are considered key building blocks for developing neuromorphic or in-memory computing hardware. Here, we study the ferroelectric and memristive response of Pt/Ca:HfO2/Pt devices fabricated on silicon by spinco...

Integrated neuromorphic photonic circuits aim to power complex artificial neural networks (ANNs) in an energy and time efficient way by exploiting the large bandwidth and the low loss of photonic structures. However, sca...

ABSTRACT All‐electrical methods for nucleating, detecting, and manipulating spin textures in 2D van der Waals (vdW) magnets can serve as fundamental building blocks for multi‐state spintronic memory, logic, and neuro...

Optical neural networks (ONNs) are promising hardware platforms for next-generation neuromorphic computing due to their high parallelism, low latency, and low energy consumption. However, previous integrated photonic ten...

Recently, a three-terminal interface dipole modulation field-effect transistor (IDM FET) memory device has been proposed that leverages electric-field-induced dipole modulation at oxide/oxide interfaces. This device has ...