A research group from Tohoku University has developed spintronics devices which are promising for future energy-efficient and adoptive computing systems, as they behave like neurons and synapses in the human brain.
Today's information society is built on digital computers that have evolved drastically for half a century and are capable of executing complicated tasks reliably.
The human brain, by contrast, operates under very limited power and is capable of executing complex tasks efficiently using an architecture that is vastly different from that of digital computers.
So the development of computing schemes or hardware inspired by the processing of information in the brain is of broad interest to scientists in fields ranging from physics, chemistry, material science and mathematics, to electronics and computer science.
In computing, there are various ways to implement the processing of information by a brain. Spiking neural network is a kind of implementation method which closely mimics the brain's architecture and temporal information processing.
Successful implementation of spiking neural network requires dedicated hardware with artificial neurons and synapses that are designed to exhibit the dynamics of biological neurons and synapses.
Here, the artificial neuron and synapse would ideally be made of the same material system and operated under the same working principle. However, this has been a challenging issue due to the fundamentally different nature of the neuron and synapse in biological neural networks.
The research group - which includes Professor Hideo Ohno (currently the university president), Associate Professor Shunsuke Fukami, Dr. Aleksandr Kurenkov and Professor Yoshihiko Horio - created an artificial neuron and synapse by using spintronics technology.
Spintronics is an academic field that aims to simultaneously use an electron's electric (charge) and magnetic (spin) properties.
The research group had previously developed a functional material system consisting of antiferromagnetic and ferromagnetic materials. This time, they prepared artificial neuronal and synaptic devices microfabricated from the material system, which demonstrated fundamental behavior of biological neuron and synapse - leaky integrate-and-fire and spike-timing-dependent plasticity, respectively - based on the same concept of spintronics.
The spiking neural network is known to be advantageous over today's artificial intelligence for the processing and prediction of temporal information. Expansion of the developed technology to unit-circuit, block and system levels is expected to lead to computers that can process time-varying information such as voice and video with a small amount of power or edge devices that have the an ability to adopt users and the environment through usage.
Shunsuke Fukami | EurekAlert!
First-ever visualizations of electrical gating effects on electronic structure
18.07.2019 | University of Warwick
New safer, inexpensive way to propel small satellites
16.07.2019 | Purdue University
Adjusting the thermal conductivity of materials is one of the challenges nanoscience is currently facing. Together with colleagues from the Netherlands and Spain, researchers from the University of Basel have shown that the atomic vibrations that determine heat generation in nanowires can be controlled through the arrangement of atoms alone. The scientists will publish the results shortly in the journal Nano Letters.
In the electronics and computer industry, components are becoming ever smaller and more powerful. However, there are problems with the heat generation. It is...
Scientists have visualised the electronic structure in a microelectronic device for the first time, opening up opportunities for finely-tuned high performance electronic devices.
Physicists from the University of Warwick and the University of Washington have developed a technique to measure the energy and momentum of electrons in...
Scientists at the University Würzburg and University Hospital of Würzburg found that megakaryocytes act as “bouncers” and thus modulate bone marrow niche properties and cell migration dynamics. The study was published in July in the Journal “Haematologica”.
Hematopoiesis is the process of forming blood cells, which occurs predominantly in the bone marrow. The bone marrow produces all types of blood cells: red...
For some phenomena in quantum many-body physics several competing theories exist. But which of them describes a quantum phenomenon best? A team of researchers from the Technical University of Munich (TUM) and Harvard University in the United States has now successfully deployed artificial neural networks for image analysis of quantum systems.
Is that a dog or a cat? Such a classification is a prime example of machine learning: artificial neural networks can be trained to analyze images by looking...
An international research group led by scientists from the University of Bayreuth has produced a previously unknown material: Rhenium nitride pernitride. Thanks to combining properties that were previously considered incompatible, it looks set to become highly attractive for technological applications. Indeed, it is a super-hard metallic conductor that can withstand extremely high pressures like a diamond. A process now developed in Bayreuth opens up the possibility of producing rhenium nitride pernitride and other technologically interesting materials in sufficiently large quantity for their properties characterisation. The new findings are presented in "Nature Communications".
The possibility of finding a compound that was metallically conductive, super-hard, and ultra-incompressible was long considered unlikely in science. It was...
24.06.2019 | Event News
29.04.2019 | Event News
17.04.2019 | Event News
19.07.2019 | Physics and Astronomy
19.07.2019 | Earth Sciences
19.07.2019 | Physics and Astronomy