Abstract: The present disclosure provides a method of detecting a magnetization signal of a physically unclonable functions (PUF) device including acquiring, by a magnetization signal detection sensor, an image of a magnetic layer of the PUF device including the magnetic layer having a perpendicular magnetization component and identifying a magnetization state of the magnetic layer from the image of the magnetic layer acquired by the magnetization signal detection sensor, and according to the present disclosure, it is possible to more efficiently check the magnetization signal of the PUF device and acquire a random unique ID according to magnetization.

Abstract: The present invention relates to a three-dimensional structure electrode, a method for manufacturing same, and an electrochemical element including the electrode. The present invention is characterized by comprising: (a) an upper conductive layer and a lower conductive layer which have a structure constituting an assembly within which a conductive material and a porous nonwoven fabric including a plurality of polymeric fibers are three-dimensionally connected in an irregular and continuous manner, thereby forming a mutually connected porous structure; and (b) an active material layer forming the same assembly structure as the conductive layers and forming a three-dimensionally filled structure in which electrode active material particles are uniformly filled inside the mutually connected porous structure formed in the assembly structure, wherein the active material layer is formed between the upper conductive layer and the lower conductive layer.

Abstract: An embodiment magnetic memory device based on perpendicular exchange bias includes a non-magnetic layer, a ferromagnetic layer bonded on the non-magnetic layer, wherein a magnetization direction of the ferromagnetic layer is randomly distributed, and an anti-ferromagnetic layer bonded on the ferromagnetic layer. An embodiment method of manufacturing a magnetic memory device includes preparing the magnetic memory device based on perpendicular exchange bias, the preparing including bonding a ferromagnetic layer on a non-magnetic layer and bonding an anti-ferromagnetic layer on the ferromagnetic layer, and demagnetizing the ferromagnetic layer of the magnetic memory device, wherein a magnetization direction of the ferromagnetic layer is randomly distributed.

Abstract: An embodiment spin-orbit torque device array includes a plurality of single devices, each device including a non-magnetic layer, a magnetic layer bonded to the non-magnetic layer, and an upper layer bonded to the magnetic layer, wherein the upper layer includes oxide, and wherein a magnetization state of each of the single devices has only two states, the two states being an up state and a down state.

Abstract: A spin-orbit-torque (SOT)-based magnetic sensor is provided. The magnetic sensor includes a substrate, an electrode layer formed on the substrate, and a pair of first and second sensing elements stacked on the substrate so as to be connected to the electrode layer, wherein directions of respective currents flowing through the first and second sensing elements via the electrode layer are opposite to each other.

Abstract: A magnetic sensor using a spin-orbit torque (SOT) and a sensing method using the same, include an SOT channel layer made of a heavy metal material, a ferromagnetic layer stacked on the SOT channel layer, and a protective layer stacked on the ferromagnetic layer, wherein an SOT is generated due to a current applied to the SOT channel layer to vary magnetization of the ferromagnetic layer, and the magnetic sensor which utilizes an SOT with a fast response speed and high sensitivity using a simplified metal thin film structure in which the SOT is generated is provided.

Abstract: A weight confirmation method for analog synaptic devices of an artificial neural network includes: learning artificial neural network hardware based on artificial analog memory devices using an artificial neural network learning algorithm; after the learning of the artificial neural network hardware, reading a total weight of a pair of synaptic devices; comparing the total weight of the pair of synaptic devices with 0; applying weights to a positive synaptic device and a negative synaptic device of the pair of synaptic devices, respectively; and confirming the total weight of the pair of synaptic devices in accordance with the weight of the positive synaptic device and the weight of the negative synaptic device. A retention problem of analog synaptic devices is overcome and thus the artificial neural network may stably operate.

Abstract: A three-terminal synaptic device includes a substrate; a source electrode and a drain electrode which are provided on the substrate and spaced apart from each other. The three-terminal synaptic device further includes: a channel layer provided on the substrate, the source electrode, and the drain electrode; an ion reservoir layer which stores active ions; a gate electrode provided on the ion reservoir layer; and an ion barrier layer disposed between the ion reservoir layer. In particular, the channel layer controls movement of active ions between the ion reservoir layer and the channel layer. The three-terminal synaptic device inhibits rapid movement of ions.

Abstract: Disclosed herein is a spin-orbit torque device including a lower ferromagnetic layer, a non-magnetic layer bonded to the lower ferromagnetic layer, and an upper ferromagnetic layer bonded to the non-magnetic layer, wherein a magnetization orientation of the lower ferromagnetic layer is randomly distributed. According to the present disclosure, it is possible to provide a magnetic memory device which cannot be physically duplicated and has reconfigurability using a spin-orbit torque.

Abstract: A neuromorphic hardware apparatus based on a resistive memory array includes a resistive memory array in which a plurality of synaptic resistor elements are arranged. Each synaptic resistor element is changed in its resistance value depending on a voltage pulse applied thereto and stores the resistance value for a predetermined time. The apparatus also includes a neuron circuit configured to receive an output signal from the resistive memory array and to output a voltage signal to another resistive memory array. The neuron circuit includes a temperature compensation unit, which compensates for an output voltage of the resistive memory array on the basis of an operating temperature of the resistive memory array. Even when a resistive memory array outputs an abnormal output depending on an operating temperature, by compensating a neuron circuit for an input value, it is possible to prevent an operation error from occurring.