A Cnr-Iom study, in collaboration with Cea-Leti and the University of Liège, illustrates the use of glassy materials for innovative non-volatile memories
Devices ready to be switched on, with RAM memories always active even without being powered. It is an ever closer target to which a study by the Materials Workshop Institute of the National Research Council (Cnr-Iom) has contributed, in collaboration with Cea-Leti and the University of Liège. The results were published in the journal Science Advances.
Currently in electronic devices volatile RAM memories are mostly used, which only work if powered and are canceled when the devices are turned off. On the other hand, non-volatile memories are capable of maintaining information even in the absence of power, making the ignition procedure almost immediate. In order for this to be possible it is necessary to study the chemical-atomic composition of the materials that make up the two elements: the selection element and the storage cell (based on phase change materials, PCM).
The current collaboration between Cnr-Iom and Leti concerns both aspects and the study is focused on the material to be used to produce more reliable selection elements. “The selector is a sort of switch that allows you to access the information stored in the storage element and is composed of a glassy material (Germanium-Selenium, with other elements) to which a voltage can be applied. For a phenomenon that is not yet well understood (Ovonic Threshold Switching, OTS), when the voltage is high the glass leads, while when it is low isolates. So, when we want to retrieve information, just raise the voltage and the selector, which has become a conductor, allows you to read the contents of the ‘storage element, “he explains Francesco d’Acapito of the Cnr-Iom.
The Cea-Leti team found the optimal composition of the material. To understand why this composition is the best, the researchers used the Cnr “Lisa” synchrotron beamline at the ESRF in Grenoble. “Some elements, such as antimony, were functional in some aspects and harmful to others, but the damage could be corrected through the use of nitrogen.
The X-ray analysis of the material made it possible to determine the structure and to understand the reasons for the roles played by the various elements “, concludes d’Acapito. The structural description was useful to the theorists of the University of Liège to build a model capable of to explain the OTS conduction phenomenon in these glassy materials. An important perspective for this class of PCM memories is the use in neuromorphic networks with promising applications in the field of machine learning.