The magnetic skyrmion transport driven by pure voltage-induced strain gradient is proposed and studied via micromagnetic simulation.Through combining the skyrmion with multiferroic heterojunction,a voltage-induced uni...The magnetic skyrmion transport driven by pure voltage-induced strain gradient is proposed and studied via micromagnetic simulation.Through combining the skyrmion with multiferroic heterojunction,a voltage-induced uniaxial strain gradient is adjusted to move skyrmions.In the system,a pair of short-circuited trapezoidal top electrodes can generate the symmetric strain.Due to the symmetry of strain,the magnetic skyrmion can be driven with a linear motion in the middle of the nanostrip without deviation.We calculate the strain distribution generated by the trapezoidal top electrodes pair,and further investigate the influence of the strain intensity as well as the strain gradient on the skyrmion velocity.Our findings provide a stable and low-energy regulation method for skyrmion transport.展开更多
A spintronics neuron device based on voltage-induced strain is proposed.The stochastic switching behavior,which can mimic the firing behavior of neurons,is obtained by using two voltage signals to control the in-plane...A spintronics neuron device based on voltage-induced strain is proposed.The stochastic switching behavior,which can mimic the firing behavior of neurons,is obtained by using two voltage signals to control the in-plane magnetization of a free layer of magneto-tunneling junction.One voltage signal is used as the input,and the other voltage signal can be used to tune the activation function(Sigmoid-like) of spin neurons.Therefore,this voltage-driven tunable spin neuron does not necessarily use energy-inefficient Oersted fields and spin-polarized current.Moreover,a voltage-control reading operation is presented,which can achieve the transition of activation function from Sigmoid-like to Re LU-like.A three-layer artificial neural network based on the voltage-driven spin neurons is constructed to recognize the handwritten digits from the MNIST dataset.For the MNIST handwritten dataset,the design achieves 97.75% recognition accuracy.The present results indicate that the voltage-driven adaptive spintronic neuron has the potential to realize energy-efficient well-adapted neuromorphic computing.展开更多
基金Project supported in part by the National Natural Science Foundation of China(Grant No.61832007)the Natural Science Foundation of Shanxi Province,China(Grant Nos.2021JM-221 and 2018JM6075)the Natural Science Basic Research Plan in Shanxi Province of China(Grant No.2020JQ-470)。
文摘The magnetic skyrmion transport driven by pure voltage-induced strain gradient is proposed and studied via micromagnetic simulation.Through combining the skyrmion with multiferroic heterojunction,a voltage-induced uniaxial strain gradient is adjusted to move skyrmions.In the system,a pair of short-circuited trapezoidal top electrodes can generate the symmetric strain.Due to the symmetry of strain,the magnetic skyrmion can be driven with a linear motion in the middle of the nanostrip without deviation.We calculate the strain distribution generated by the trapezoidal top electrodes pair,and further investigate the influence of the strain intensity as well as the strain gradient on the skyrmion velocity.Our findings provide a stable and low-energy regulation method for skyrmion transport.
基金Supported by the National Natural Science Foundation of China under Grants Nos.61804184 and 11975311the Natural Science Basic Research Plan in Shaanxi Province of China under Grant No.2020JQ470the Foundation of Independent Scientific Research under Grant Nos.YNJC19070501,YNJC19070502,and YNJC19070504。
文摘A spintronics neuron device based on voltage-induced strain is proposed.The stochastic switching behavior,which can mimic the firing behavior of neurons,is obtained by using two voltage signals to control the in-plane magnetization of a free layer of magneto-tunneling junction.One voltage signal is used as the input,and the other voltage signal can be used to tune the activation function(Sigmoid-like) of spin neurons.Therefore,this voltage-driven tunable spin neuron does not necessarily use energy-inefficient Oersted fields and spin-polarized current.Moreover,a voltage-control reading operation is presented,which can achieve the transition of activation function from Sigmoid-like to Re LU-like.A three-layer artificial neural network based on the voltage-driven spin neurons is constructed to recognize the handwritten digits from the MNIST dataset.For the MNIST handwritten dataset,the design achieves 97.75% recognition accuracy.The present results indicate that the voltage-driven adaptive spintronic neuron has the potential to realize energy-efficient well-adapted neuromorphic computing.
