Recently, doped HfO2 thin films have attracted considerable attention because of promising applications in complementary metal–oxide–semiconductor (CMOS)‐compatible ferroelectric memories. Herein, the ferroelectric properties and polarization fatigue of La:HfO2 thin‐film capacitors are reported. By varying the substrate lattice constant and film thickness, a robust remanent polarization of ≈16 μC cm−2 is achieved in a 12 nm‐thick Pt/La:HfO2/La0.67Sr0.33MnO3 capacitor. Fatigue measurements are conducted using designed pulse sequences, in which the voltage, pulse width, and interval time are changed to observe the evolution of switchable polarization with increasing cycles. Severe fatigue is observed when the La:HfO2 capacitors are partially switched and the interval between the bipolar switching is elongated. These behaviors may be ascribed to the domain wall pinning scenario, in which domain switching is blocked by the migration and aggregation of charges on non‐electroneutral walls. Further analysis of the fatigue behaviors with a nucleation‐limited‐switching model shows that the mean time and activation field for polarization switching are increased in fatigued La:HfO2 capacitors because electrical stimuli are required to disperse the aggregated charges before the domains are set free. These results facilitate the design and fabrication of HfO2‐based ferroelectric memories with improved device reliability.
As
nanoelectronic synapses, memristive ferroelectric tunnel junctions
(FTJs) have triggered great interest due to the potential applications
in neuromorphic computing for emulating biological brains. Here, we
demonstrate multiferroic FTJ synapses based on the ferroelectric modulation
of spin-filtering BaTiO3/CoFe2O4 composite
barriers. Continuous conductance change with an ON/OFF current ratio
of ∼54 400% and long-term memory with the spike-timing-dependent
plasticity (STDP) of synaptic weight for Hebbian learning are achieved
by controlling the polarization switching of BaTiO3. Supervised
learning simulations adopting the STDP results as database for weight
training are performed on a crossbar neural network and exhibit a
high accuracy rate above 97% for recognition. The polarization switching
also alters the band alignment of CoFe2O4 barrier
relative to the electrodes, giving rise to the change of tunneling
magnetoresistance ratio by about 10 times and even the reversal of
its sign depending upon the resistance states. These results, especially
the electrically switchable spin polarization, provide a new approach
toward multiferroic neuromorphic devices with energy-efficient electrical
manipulations through potential barrier design. In addition, the availability
of spinel ferrite barriers epitaxially grown with ferroelectric oxides
also expends the playground of FTJ devices for a broad scope of applications.
Recently, tunnel junction devices
adopting semiconducting Nb:SrTiO3 electrodes have attracted
considerable attention for their
potential applications in resistive data storage and neuromorphic
computing. In this work, we report on a comparative study of Pt/insulator/Nb:SrTiO3 tunnel junctions between ferroelectric BaTiO3 and
nonferroelectric SrTiO3 and LaAlO3 barriers
to reveal the role of polarization in resistance switching properties.
Although hysteretic behaviors appear in current–voltage measurements
of all devices regardless of the barrier character, significantly
improved current ratios by more than three orders of magnitude are
observed in the Pt/BaTiO3/Nb:SrTiO3 tunnel junctions
due to the dominance of polarization in modulation of junction barrier
profiles between the low and high resistance states. The switchable
polarization also gives rise to enhanced resistance retention since
the electron diffusion that smears the barrier contrast of the bistable
resistance states is suppressed by the polar BaTiO3/Nb:SrTiO3 interface associated with the ferroelectric bound charges.
These polarization-induced effects are absent in the nonferroelectric
Pt/SrTiO3/Nb:SrTiO3 and Pt/LaAlO3/Nb:SrTiO3 devices in which serious resistance state decay,
described by Fick’s second law, is observed since there are
no switchable interface charges on SrTiO3/Nb:SrTiO3 and LaAlO3/Nb:SrTiO3 to block the electron
diffusion. In addition, the Pt/BaTiO3/Nb:SrTiO3 device also exhibits an excellent switching endurance up to ∼4.0
× 106 bipolar cycles. These enhancements indicate
the importance of ferroelectric polarization for achieving high-performance
resistance switching and suggest that metal/ferroelectric/Nb:SrTiO3 tunnel junctions are promising candidates for nonvolatile
memory applications.
Freestanding perovskite thin films display many unprecedented properties and exhibit the potential to be easily integrated on other non-oxide substrates or layers. In this work, we demonstrated a pathway to synthesis freestanding perovskite oxide thin films by using brownmillerite SrCoO2.5 as a sacrificial layer. Four representative freestanding perovskite oxide films, e.g., ferromagnetic SrRuO3, La0.7Sr0.3MnO3, dielectric SrTiO3, and ferroelectric Pb(Zr0.2Ti0.8)O3, were produced by etching SrCoO2.5 in Fe(NO3)3 weak acidic solution at room temperature. A 80 nm SrRuO3, which served as an H+ conduction channel, was deposited as a bottom layer of SrCoO2.5 to trigger a quick dissolution for the exfoliation of SrTiO3 and Pb(Zr0.2Ti0.8)O3 poor H+ conductor. Their crystal structure and physical properties were well retained in transferred films. Our work demonstrated the wide applicability of SrCoO2.5 as a sacrificial layer on the synthesis of freestanding perovskite oxide thin films.
Neuromorphic computing is a promising candidate for next-generation information technologies. In the present work, we report the realization of long-term plasticity and synapse emulations in Ag/SrTiO3/(La,Sr)MnO3 memristors with the SrTiO3 active layers down to 3 unit cells (u.c.) in thickness. In the 3 u.c.-thick SrTiO3 device, efficient control of Ag+-ion migration gives rise to enhanced memristive properties with the conductance continuously modulated within a large memory window of ∼26 000% between an Ohmic low resistance state (LRS) and an electron-tunneling high resistance state (HRS). In addition, long-term plasticity of the Ag/SrTiO3/(La,Sr)MnO3 memristors is found to be dependent upon the resistance state. In the HRS, the devices exhibit excellent spike-timing-dependent plasticity characteristics with a large modulation of synaptic weight of ∼3500% and sensitive response to electrical stimuli of as low as ∼1.0 V and as fast as ∼0.01 ms. Adopting the spike-timing-dependent plasticity results as database, supervised learning simulations are demonstrated in the Ag/SrTiO3/(La,Sr)MnO3-based neural networks and a high accuracy rate of 95.5% is achieved for recognizing handwritten digits. These results provide more insights into the ionic migration at nanoscale for continuous resistance modulation and facilitate the design of ultrathin memristors for high-density 3D stacking artificial neural networks.
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