Research on electronic devices and materials is currently driven by both the slowing down
of transistor scaling and the exponential growth of computing needs, which make present …

With the upcoming trend of Big Data era, some new types of memory technologies have
emerged as substitutes for the traditional Si-based semiconductor memory devices, which …

A memristor is a two-terminal device with nonvolatile resistive switching (RS) behaviors.
Recently, memristors have been highly desirable for both fundamental research and …

Profuse dendritic-synaptic interconnections among neurons in the neocortex embed intricate
logic structures enabling sophisticated decision-making that vastly outperforms any artificial …

Brain‐inspired neuromorphic computing is a new paradigm that holds great potential to
overcome the intrinsic energy and speed issues of traditional von Neumann based …

Neuromorphic materials are promising for fabricating artificial synapses for flexible
electronics, but they are usually expensive and lack a good combination of electronic and …

Emerging brain-inspired neuromorphic computing systems have become a potential
candidate for overcoming the von Neuman bottleneck that limits the performance of most …

Inexpensive and flexible organic resistive memory can be easily fabricated, scaled and
stacked. Owing to these advantages, organic resistive memory is considered as a very …

Artificial Intelligence (AI) is the domain of large resource-intensive data centres that limit
access to a small community of developers,. Neuromorphic hardware promises greatly …

This study reports intrinsic multimodal memristivity of a nonconjugated radical polymer with
ambient stability. Organic memristive devices represent powerful candidates for biorealistic …