Abstract Crossbar circuits based on two terminal (2T) memristors typically require an additional unit such as a transistor for individual node selection. A memristive device with gate‐tunable synaptic functionalities will not only integrate selection functionality at the cell level but can also lead to enriched on‐demand learning schemes. Here, a three‐terminal (3T) mixed‐halide perovskite memristive device with gate‐tunable synaptic functions operating at low potentials is demonstrated. The device operation is controlled by both the drain (VD) and gate (VG) potentials, with an extended endurance of >2000 cycles and a state retention of >5000 s. Applying a voltage (Vset) of 20 V across the 50 µm channel switches its conductance from a high‐...
Many in-memory computing frameworks demand electronic devices with specific switching characteristic...
Memristive devices have been widely employed to emulate biological synaptic behavior. In these cases...
Abstract—We present new computational building blocks based on memristive devices. These blocks, can...
Non-volatile memristors are promising for future hardware-based neurocomputation application because...
Synaptic devices with bipolar analog resistive switching behavior are the building blocks for memris...
Neuromorphic computing architectures are required to execute several operations such as forgetting a...
Emulation of brain‐like signal processing is the foundation for development of efficient learning ci...
thesisScaling limitation of current memory technology requires invention of a new class of memory th...
Organic and perovskite memristors have superior characteristics both in material and structural pers...
International audienceNeuromorphic computing has gained important attention since it is an efficient...
Memristive devices are electrical resistance switches that can retain a state of internal resistance...
Modern electronic devices are being developed for cutting-edge applications, as a result of recent d...
International audienceThe brain has the ability to learn and evaluate as it receives and registers i...
We present new computational building blocks based on memristive devices. These blocks, can be used ...
The development of energy-efficient artificial synapses capable of manifoldly tuning synaptic activi...
Many in-memory computing frameworks demand electronic devices with specific switching characteristic...
Memristive devices have been widely employed to emulate biological synaptic behavior. In these cases...
Abstract—We present new computational building blocks based on memristive devices. These blocks, can...
Non-volatile memristors are promising for future hardware-based neurocomputation application because...
Synaptic devices with bipolar analog resistive switching behavior are the building blocks for memris...
Neuromorphic computing architectures are required to execute several operations such as forgetting a...
Emulation of brain‐like signal processing is the foundation for development of efficient learning ci...
thesisScaling limitation of current memory technology requires invention of a new class of memory th...
Organic and perovskite memristors have superior characteristics both in material and structural pers...
International audienceNeuromorphic computing has gained important attention since it is an efficient...
Memristive devices are electrical resistance switches that can retain a state of internal resistance...
Modern electronic devices are being developed for cutting-edge applications, as a result of recent d...
International audienceThe brain has the ability to learn and evaluate as it receives and registers i...
We present new computational building blocks based on memristive devices. These blocks, can be used ...
The development of energy-efficient artificial synapses capable of manifoldly tuning synaptic activi...
Many in-memory computing frameworks demand electronic devices with specific switching characteristic...
Memristive devices have been widely employed to emulate biological synaptic behavior. In these cases...
Abstract—We present new computational building blocks based on memristive devices. These blocks, can...