<p>Researchers at Universitat Autonoma de Barcelona have developed a magnetic material that has the capability of storing information like the brain. This research was led by researchers from the UAB Department of Physics Jordi Sort and Enric Menéndez, along with the ALBA Synchrotron, the Catalan Institute of Nanoscience and Nanotechnology (ICN2), and the ICMAB.&nbsp;</p><h3 class=""><b><u>Keywords</u></b>: magnetic materials, Neuromorphic computing, neuronal plasticity, neuron synapses, cobalt mononitride (CoN), voltage, stimulus&nbsp;</h3><p><br></p><p>Neuromorphic computing is considered as a new computing paradigm. In this, the behavior of the brain is emulated by mimicking the main synaptic functions of neurons. Among the functions, neuronal plasticity is considered. Neuronal plasticity is referred to as the ability to store or forget information based on the duration and repetition of the electrical impulses that stimulate the brain.</p><p>Various materials mimic neuron synapses. They are: memresistive materials, ferroelectrics, phase change memory materials, topological insulators, and recently magneto-ionic materials stand out.&nbsp;</p><p>Changes in magnetic properties are generally induced by the displacement of ions within the material. This is caused by the application of an electric field. While applying the electric field, it is well known to modulate the magnetism in these materials. But when the voltage is stopped, the evolution of magnetic properties is difficult to control. This increases the complications of emulating some brain-inspired functions such as maintaining learning efficiency even while the brain is in a state of deep sleep.</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<img src="/media/django-summernote/2022-11-11/1102a9c2-25e7-4cfc-b411-b116c5b2a88c.jpg" style="width: 451.707px; height: 146.823px;"><br></p><p>But now, the researchers have developed a material based on a thin layer of cobalt mononitride (CoN). In this, by applying an electric field, the accumulation of N ions at the interface between the layer and a liquid electrolyte in which the layer has been placed is possible to be controlled.&nbsp;</p><p>ICREA research professor Jordi Sort and&nbsp;<span style="border-radius: 0px !important;">Serra Húnter</span>&nbsp;Tenure-track Professor Enric Menéndez said, "The new material works with the movement of ions controlled by electrical voltage, in a manner analogous to our brain, and at speeds similar to those produced in neurons, of the order of milliseconds. We have developed an artificial synapse that in the future may be the basis of a new computing paradigm, alternative to the one used by current computers".</p><p>By applying voltage pulses, it is possible to emulate various processes such as memory, information processing, information retrieval, the updating information without applied voltage. The emulation is possible in a controlled way. It is achieved by modifying the thickness of the cobalt mononitride layers which determines the speed of the motion of ions, and the frequency of the pulses.&nbsp;</p><p>The arrangement of material is in such a way that it allows the magnetic properties to be controlled when the voltage is applied and even when the voltage is removed. As the external voltage stimulus disappears, the magnetization of the system can be reduced or increased. This can be done by depending on the thickness of the material and considering the protocol of how was the voltage applied previously.</p><p>Jordi Sort and Enric Menendez said, "When the thickness of the cobalt mononitride layer is below 50 nanometers and with a voltage applied at a frequency greater than 100 cycles per second, we have managed to emulate an additional logic function: once the voltage is applied, the device can be programmed to learn or to forget, without the need for any additional input of energy, mimicking the synaptic functions that take place in the brain during deep sleep, when information processing can continue without applying any external signal".</p><p>The development of this material has opened a new range of opportunities for new neuromorphic computing functions.&nbsp;</p>