A multilayered spin valve film with a structure of Ta(5 nm)/Co_(75)Fe_(25)(5 nm)/Cu(2.5 nm)/Co_(75)Fe_(25)(5 nm)/Ir_(20)Mn_(80)(12 nm)/Ta(8 nm)is prepared by the high-vacuum direct current(DC)magnetron sputtering.The ...A multilayered spin valve film with a structure of Ta(5 nm)/Co_(75)Fe_(25)(5 nm)/Cu(2.5 nm)/Co_(75)Fe_(25)(5 nm)/Ir_(20)Mn_(80)(12 nm)/Ta(8 nm)is prepared by the high-vacuum direct current(DC)magnetron sputtering.The effect of temperature on the spin valve structure and the magnetic properties are studied by x-ray diffraction(XRD),atomic force microscopy(AFM),and vibrating sample magnetometry.The effect of temperature on the exchange bias field thermomagnetic properties of multilayered spin valve is studied by the residence time of samples in a reverse saturation field.The results show that as the temperature increases,the IrMn(111)texture weakens,surface/interface roughness increases,and the exchange bias field decreases.Below 200℃,the exchange bias field decreases with the residence time increasing,and at the beginning of the negative saturation field,the exchange bias field Hex decreases first quickly and then slowly gradually.When the temperature is greater than 200℃,the exchange bias field is unchanged with the residence time increasing.展开更多
The local field potential（LFP） is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are or...The local field potential（LFP） is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood（SL） is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas. One drawback of non-linear algorithms is the heavy computational burden. In the present study, we proposed a graphic processing unit（GPU）-accelerated implementation of an SL algorithm with optional 2-dimensional time-shifting. We tested the algorithm with both artificial data and raw LFP data. The results showed that this method revealed detailed information from original data with the synchronization values of two temporal axes,delay time and onset time, and thus can be used to reconstruct the temporal structure of a neural network. Our results suggest that this GPU-accelerated method can be extended to other algorithms for processing time-series signals（like EEG and f MRI） using similar recording techniques.展开更多
基金supported by the Yunnan Provincial Ten Thousand Talents Plan Young Talents Training Fund,China(Grant No.KKRD201952029)the Applied Basic Research Program of Yunnan Province,China(Grant No.2011FB037)the School Talent Cultivation Foundation,China(Grant No.KKSY201252017)。
文摘A multilayered spin valve film with a structure of Ta(5 nm)/Co_(75)Fe_(25)(5 nm)/Cu(2.5 nm)/Co_(75)Fe_(25)(5 nm)/Ir_(20)Mn_(80)(12 nm)/Ta(8 nm)is prepared by the high-vacuum direct current(DC)magnetron sputtering.The effect of temperature on the spin valve structure and the magnetic properties are studied by x-ray diffraction(XRD),atomic force microscopy(AFM),and vibrating sample magnetometry.The effect of temperature on the exchange bias field thermomagnetic properties of multilayered spin valve is studied by the residence time of samples in a reverse saturation field.The results show that as the temperature increases,the IrMn(111)texture weakens,surface/interface roughness increases,and the exchange bias field decreases.Below 200℃,the exchange bias field decreases with the residence time increasing,and at the beginning of the negative saturation field,the exchange bias field Hex decreases first quickly and then slowly gradually.When the temperature is greater than 200℃,the exchange bias field is unchanged with the residence time increasing.
基金supported by Grants from the National Natural Science Foundation of China(81230023,81571067,and 81521063)National Basic Research Development Program(973 Program)of China(2013CB531905)the‘‘111’’Project of China
文摘The local field potential（LFP） is a signal reflecting the electrical activity of neurons surrounding the electrode tip. Synchronization between LFP signals provides important details about how neural networks are organized. Synchronization between two distant brain regions is hard to detect using linear synchronization algorithms like correlation and coherence. Synchronization likelihood（SL） is a non-linear synchronization-detecting algorithm widely used in studies of neural signals from two distant brain areas. One drawback of non-linear algorithms is the heavy computational burden. In the present study, we proposed a graphic processing unit（GPU）-accelerated implementation of an SL algorithm with optional 2-dimensional time-shifting. We tested the algorithm with both artificial data and raw LFP data. The results showed that this method revealed detailed information from original data with the synchronization values of two temporal axes,delay time and onset time, and thus can be used to reconstruct the temporal structure of a neural network. Our results suggest that this GPU-accelerated method can be extended to other algorithms for processing time-series signals（like EEG and f MRI） using similar recording techniques.
