Capacitive effect: An original of the resistive switching memory

Journal Pre-proof Capacitive effect: an original of the resistive switching memory Guangdong Zhou, Zhijun Ren, Bai Sun, Jinggao Wu, Zhuo Zou, Shaohui Zheng, Lidan Wang, Shukai Duan, Qunliang Song PII:

S2211-2855(19)31100-0

DOI:

https://doi.org/10.1016/j.nanoen.2019.104386

Reference:

NANOEN 104386

To appear in:

Nano Energy

Received Date: 13 October 2019 Revised Date:

25 November 2019

Accepted Date: 4 December 2019

Please cite this article as: G. Zhou, Z. Ren, B. Sun, J. Wu, Z. Zou, S. Zheng, L. Wang, S. Duan, Q. Song, Capacitive effect: an original of the resistive switching memory, Nano Energy, https:// doi.org/10.1016/j.nanoen.2019.104386. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Capacitive effect: an original of the resistive switching memory a, 1

a, 1

b, 1

Guangdong Zhou , Zhijun Ren , Bai Sun , Jinggao Wu a, * a, * a, * Lidan Wang , Shukai Duan , Qunliang Song a

a, 1

a

a

, Zhuo Zou , Shaohui Zheng ,

College of Artificial Intelligence; School of Materials and Energy; College of Electronic and Information Engineering; College of Resources and Environment, Southwest University, Chongqing, 400715, P. R. China.

b

Department of Mechanics and Mechatronics Engineering, Centre for Advanced Materials Joining, Waterloo Institute for Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.

*

Email: [email protected]; [email protected]; [email protected]

1

Authors equally contribute to this work.

Abstract Interplay between ions and electrons endows memristor with promising applications from the high density storages, memory logic gates to neuromorphic chips. The interplay-induced memristor evolution stage involving an original stage (non-standard faradic capacitance, NFC), transition stage (battery-like capacitance, BLC) and resistive switching state (RS) are discovered in the Ag|TiOx nanobelt|Ti device under different moisture levels. Generation, migration and interplay between ions and electrons are effectively restricted for the NFC observed in dry ambient. The OH- suspending on the surface Vo due to the H2O-based redox reaction results in the device evolving from the NFC to BLC under moisture circumstance. Strong interplay with ions, electron transfer and migration of OH- ions push the device into the RS state. Based on theory calculations, an energy band-based physical model is proposed to comprehend the evolution process. This work gives an insight into the moisture effect on the resistive switching behaviors and the evolution track of memristor, which is meaningful for construction neuromorphic chip with an ultralow energy consumption. Graphical Abstract

Keywords: Capacitive effect; Resistive switching memory; DFT calculations; Water splitting, Energy band model. 1. Introduction Electrons can escape from a nanoscale restriction layer [1, 2]. Driven by electric field, ions with larger mass and volume than the electrons migrate and redistribute in restriction layer for long distance compared with the lattice constant and atomic interval [3]. The 1

interplay between electrons and ions endows the electronic devices with a variety of promising applications [4-9]. The resistance random access memory (ReRAM), which results from a physical reconfiguration triggered by the interplay, has shown an overwhilming advantage in the ultrahigh data storages, non-Von Neumann logic hardwares and neural morphographic chips [10-19]. The ReRAM is facing tremendous challenges ranged from the physical mechanism, preparation technology and materials, despite great progress and breakthrough have been made during the past decades [20-23]. To the physical mechanism of ReRAM, the ion migration, redistribution and interplay with electrons have been extensively accepted. However, many unique resistive switching (RS) behaviors, for instance, the cooccurrence of bipolar and nonpolar RS behavior and coexistence of differential negative resistance (NDR) and RS behavior are observed in the same material system, or even in the same memory cell [24-26]. These behaviors make the comprehension on ReRAM become more complicated. Therefore, it is rationalized that the ReRAM is not only triggered by ion migration and redox reaction of interface, but also modulated by the size of switching layer, Joule heat, field-driven ion diffusion and nucleation position [27-29]. The factors mentioned above are intrinsic, and the extrinsic factors, such as the external ambient, should be taken into account because a variety of redox reactions are triggered by the mositure of ambient [30-32]. The water reaction related electric conductivity relation can be described as following [31]: σ = qη . c . + qη . c

.

+ 2qη

..

c

..

+ η

..

c

..

(1)

where the σ denotes the electric conductivity; q, the elemental charge; c, the concentration, η, the mobility; h. , the holes; e. , the electrons;

..

, the oxygen vacancy and

..

,

the proton

bound to oxygen in the metal oxide. According to the Eq. (1), the OH- ions generated by the water reaction contribute to the conductivity of switching layer. To the holes and electrons generated by redox reaction at the interface or surface can be described as following [33, 34]:

2



= 2.99 ∙ 10 ∙

∙ !"

# $

∙ %&'("

# $

(2)

where Jp denotes the redox peak current value; z, the transfer electron number; Credox, the ions concentration; α, the charge transfer coefficient; Dredox, the ion diffusion coefficient, and ν, the bias voltage sweep rate, respectively. The conductivity of the ReRAM contributed by carriers from redox reactions can be explained by the Eq. (2). To the material system, the RS memory behaviors have been observed in the natural proteins (egg albumen, silk fibroin), synthesized organics and transition metal oxides [13, 35, 36]. Especially, the transition metal oxides have been extensively investigated in recent years because the good compatibility with the CMOS technology [37]. Titanium oxide plays an importance role in the comprehension of the ReRAM due to its rich phases, nanostructures (nanobelts, nanowires and nanorods) and electrochemical properties [24, 26, 38]. Nanobelts and nanowires are the promising function blocks due to their bottom-up growth in nanoelectronic device [39]. For instance, TiOx nanobelt has a large specific surface, uniformly distributed oxygen vacancy (Vo) and high sensitivity to the external ambient [40]. Therefore, it has presented high performance when the TiOx nanobelt arrays served as the function material in gas sensors [41], energy storages [42], photo-catalysis [43] and ReRAM [24, 26, 44]. Our previous work has demonstrated that there is an original state for the ReRAM, which is submerged by the high current density once the conduction filament formation [45]. The original state, transition state and RS state are possibly detected if the coupling between ions and electrons triggered by the ambient is controlled effectively. The TiOx nanobelt with high concentration of exposed active facets possibly makes this control become possible. To realize and comprehend the physical dynamic process of the interplay between ions and electrons in the ReRAM device, the TiOx nanobelt arrays are deliberately designed. The current voltage (I-V) hysteresis for evolution stages is systemically studied under different 3

moisture levels at room temperature. According to the first principle theory calculation on the interplay processes, an energy band-based physical model for those evolution stages is proposed. 2. Experiment Section 2.1 Memory device fabrication The TiOx nanobelts were synthesized using hydrothermal method. The Ti metal substrates were sequentially cleaned by deionized water and ethyl alcohol for 30 minutes, then, the Ti metal substrates were thermally processed in air at 200℃ for 3 hours. The 2.0 g NaOH was dissolved into 20 mL deionized water and then stirred for 30 minutes at room temperature. The 2.0 g TiO2 nanopowders (the nanosphere with an average diameter of 20 nm) were added into the NaOH solutions to form the precursor solutions. After hydrothermal reaction at 200 ℃ for 48 hours, a bluish-grey film grown on the Ti substrates. It is worth noting that the TiOx nanobelt arrays were obtained when the bluish-grey film was orderly cleaned by 10% HCl for 90 seconds and deionized water for 10 minutes. After that, the TiOx nanobelt samples were thermally processed at 80 ℃ for 24 hours in order to remove the possibly residual HCl. The Ag, Au or Pt electrodes with a diameter of 200 µm were deposited on the TiOx nanobelt surface by the radio frequency magnetron sputtering. 2.2 Device characterization All electric measurements were performed in a cavity of probe system (Lake Shore, TTPX) by the electrochemical workstation (CHI, 660D). The relative humidity of the air ambient of our laboratory was 35% ~ 45%. Dry air, O2, N2 and CO2 with RH of 0% were artificially synthesized by flowing air into three interconnected heated-glass delivery tubes filled with dry CaO nano-powders. Then the dry air could be injected into the cavity with 4

background vacuum of 5.0×10-4 Pa. Moisture air (RH=95% ~ 100%) can be obtained by flowing laboratory air into a gas-washing bottle filled with deionized water. 2.3 Computing details All calculations in this work were performed using the density functional theory (DFT) calculations as implemented in the Vienna abinitio simulation package (VASP) [46]. The projector augmented wave (PAW) method was used to describe the electron-ion interaction [47], while the Perdew-Burke-Ernzerh of (PBE) functional implementation of the generalized gradient approximation was used to describe the exchange-correlation interactions [48]. Based on the TEM analysis, the nanobelt TiO2 system was constructed from a 2 × 2 × 1 anatase TiO2 supercell (16 Ti atoms and 32 O atoms) in which the {101} surface was cleaved with a vacuum layer of at least 12 Å along the b axis and the c axis (the exposed edge) to minimize the undesired interactions between the adjacent images. The GG+U correction approach was employed to account for strong on-site Coulomb repulsion, the orbital dependent GGA+U functional as shown in Eq. (3) [49]: E GGA + U = E GGA +

U − J 2

∑σ [Tr ρ σ

− Tr( ρ σ ρ σ )]

(3)

σ Where U, J and ρ are the spherically averaged screened coulomb energy, the exchange

energy and spin(s) polarized on-site density matrix, respectively. The values of Hubbard U and J used here for Ti 3d electron were 7.8 and 1.0 eV. The k-points meshes were sampled based on the Γ centered Monkhorst-Pack method with k-point mesh resolution of 2π×0.09 Å-1, 2π × 0.04 Å-1 and 2π × 0.01 Å-1 for oxygen vacancy configuration test, the most stable geometric structure re-optimization and densities of states (DOS) calculations, respectively. The plane wave energy cutoff was set to 450 eV and electron smearing was employed Gaussian smearing method with a width of 0.1 eV. Electronic energies were computed with 5

the self-consistent field (SCF) tolerance of 10-5 eV and the force exerted on an atom was converged to less than 0.03 eV/Å. 3. Result and Discussion 3.1 Redox-based capacitance state (BLC) in air ambient

Fig. 1. (a) FE-SEM images of the TiOx nanobelt arrays and (b) its corresponding enlarge areas. (c) HR-TEM images of the TiOx nanobelts. The lattice constants of the 0.17, 0.19, 0.24, 0.35 nm originate from the lattice faces of the [116], [220], [004] and [101], respectively. (d) XRD spectrum of the TiOx nanobelt arrays. XPS spectra of the core levels of (e) Ti 2p and (f) O 1s.

Figure 1a is the field emission scanning electron microscopy (FE-SEM) image of the TiOx nanobelt. Its corresponding enlarge image shows the TiOx nanobelt with a width of ~ 150 nm (Fig. 1b). The average length of the TiOx nanobelt is ~ 850 nm. The high resolution transmission electron microscopy (HR-TEM) images of the TiOx nanobelt show the lattice constant of 0.17, 0.19, 0.24 and 0.35 nm, which are respectively contributed by the crystal planes of [116], [220], [004] and [101] (Fig. 1c). In order to further verify the local crystallization feature, the X-ray diffraction (XRD) pattern was tested using the TiOx|Ti sample as well. The TiOx nanobelt arrays are characterized by the anatase TiO2 (JCPDS: 211272), Ti2O3 (JCPDS: 43-1033) and Ti10O19 (JCPDS: 11-0474) (Fig. 1d). To be noted that the TiOx nanobelts are mainly composed by the anatase TiO2, despite the Ti2O3 and Ti10O19 are 6

involved. The polycrystal property illustrates that a large number of grain boundaries are generated for the TiOx nanobelt. X-ray photoelectron spectroscopy (XPS) was carried out to further study the chemical component of TiOx nanobelt. All XPS data were calibrated by the C-C bond binding energy of 284.5 eV. The binding energy backgrounds of 454 ~ 468 eV and 526 ~ 536 eV were employed to process the XPS peak differentiation analysis for the core level of Ti 2p and O 1s, respectively. The red and blue lines in Figures 1e-1f demonstrate the Ti4+ and Ti3+ for the TiOx nanobelts. An area of Ti 2p3/2 is nearly two times of the Ti 2p1/2. The peaks of Ti 2p3/2 located at 458.0 eV and 2p1/2 located at 463.7 eV lead to spin orbital splitting energy 5.7 eV between 2p3/2 and 2p1/2, which are originated from anatase TiO2 [26]. The peaks located at 457.2 eV for Ti 2p3/2 and 462.8 eV for Ti 2p3/2 are contributed by the Ti2O3. The energy area ratio of Ti3+ (Ti 2p3/2) /Ti2+ (Ti 2p3/2) is ~18%. The binding energy peaks of 529.2 and 531.5 eV for the core level of O 1s are contributed by the chemical bond of Ti-O in the TiO2 and Ti2O3, respectively [26]. In addition, the binding energy peak of the 531.5 eV is also partially contributed by the ions in the oxygen species deficient region (

+ $ )#* )

[50, 51]. The

+ $ )#*

chemically adsorbed on the surface and subsurface of the TiOx nanobelts can field-driven migrate, and then make contribution to the conductivity [52]. After completing the forming-like process, the cyclic voltammetry curves measured in air ambient imply that the Ag|TiOx|Ti device corresponds to the capacitor, which is characterized by the redox peaks and the uncross current-voltage curves at 0 V, (Fig. 2a). The inset of Figure 2a is the typical cyclic voltammetry curve. The relative humidity (RH) for the air ambient is 35% ~ 45%. In other words, the Ag|TiOx|Ti device has shown a battery-like capacitance (BLC) under air ambient with elevated humidity. The BLC can be described by four stages. In the first stage (0 ~ 6 V), the current continuously increases to the highest value at 6 V. Here, we define the current value at 6 V as the positive maximum (Imax+). In the second stage (6 ~ 0 V), the current gradually decreases, 7

Fig. 2. (a) Logarithm current voltage (I-V) curves of the Ag|TiOx|Ti device, and the inset is the typical I-V curve. (b) Compliance current dependency of I-V curves. Stabilities of (c) device-to-device and (d) cycle-to-cycle for the BLC. (e) Bias voltage scan rate dependent BLC (f) Bias voltage magnitude dependent BLC under a constant bias voltage scan rate of 1.0 V/s. (g) Peak currents of oxidized (positive) and reduced (negative) process versus square root of the bias voltage scan rate for the BLC. (h) Peak currents of oxidized (positive) and reduced (negative) process versus magnitude of bias voltage. All measurements were conducted under air ambient.

but large than the first stage at the same voltage point. Namely, two different resistance states are feasible for the two stages. It notes that the current value firstly decreases, then increases and finally re-decreases during the second stage (oxidized process). In the third stage (0 ~ -6 V), the current value gradually increases to the highest value at -6 V. Here, we define the current value at -6 V as the negative maximum (Imax-). In the fourth stage (-6 ~ 0 V), the current firstly decreases, and then it increases and finally re-decreases (reduced process). It is worth noticing that the redox peaks are observed in the I-V curves under air ambient. Therefore, the redox reaction and capacitance are co-occurred under the external bias voltage sweep under air ambient. In fact, the BLC has been observed in the Cu|SiOx|Pt and the Pt|SrTiO3-δ|Pt memory device under moisture ambient [31, 33, 53]. For decades, the BLC was 8

believed to be an initial state of the ReRAM [33, 45]. However, the BLC itself with low current density is easily submerged by high current density of RS state [45]. If we want to clearly understand the physical mechanism for the ReRAM, the BLC is needed to further control. Compliance current (CC) levels (1000, 100, 10, 1 µA) are operated on our device (Fig. 2b). Redox peak values show a negligible change under the CC level of 1000, 100 and 10 µA. The redox peak is limited under 1 µA. It shows that the lowest current value shifts its peak position obviously under 1000 µA. It implies that redistribution of the polarized charges occurs under the different compliance current levels [54]. Due to the non-uniformity of the function layers and electrodes, the device-to-device performance has shown some variations. Due to the stochastic I-V hysteresis under external atmosphere, the cycle-to-cycle has also shown variations [55, 56]. The Ag|TiOx|Ti cells and IV cycles for each cell were measured to investigate the device-to-device stability under air ambient (Fig. 2c). The 300 consecutive I-V cycles were tested using a single Ag|TiOx|Ti cell to investigate the cycle-to-cycle stability (Fig. 2d). The BLC has shown a good stability for both device-to-device and cycle-to-cycle under air ambient. Under different bias sweep rates, the re-distribution and migration of polarized charges at interfaces are very different. In other words, the interplay between electrons and ions at interfaces is partially depended on the bias voltage sweep rate, which is sensitive to the I-V hysteresis of a bottom-up film based electronic device. In fact, we have found that the scan rate-related interplay between electrons and ions at the interfaces of Ag|TiOx and TiOx|FTO is one of efficient methods to control the I-V hysteresis [26]. To a lateral structure device studied in this work, the interplay between electrons and ions at interfaces is weakened, but the interplay on the surface is enhanced. Therefore, the bias voltage scan rate dependent BLC is investigated under air ambient as well. Bias voltage scan rates of 1, 2, 4, 8, 16 and 32 V/s are operated during the BLC 9

measurement (Fig. 2e). It shows the increase tendency for both oxidized and reduced current peaks when increasing the voltage scan rate. The increase tendency of the redox peak current can be described by the Randles-Sevcik relationship of the Eq. (2). According to the Eq. (2), the bias voltage scan rate can be directly contributed to the redox peak current. Under high voltage bias scan rate, the interplay between electrons and ions on the surface and at the interfaces is enhanced. Taking into account the high exposed area of TiOx nanobelts, the interplay at the surfaces outweighs those at interfaces. A linear ion diffusion in solid electrolytes results in a linear feature for the peak current versus the square root of bias scan rate, which has been extensively verified in SiOx, TaOx and proteins [33, 57]. The peak current of oxidized (positive) and reduced (negative) process versus square root of the bias voltage scan rate for the BLC can be extracted from the Figure 2e (Fig. 2f). The nonlinear relationships for both oxidation and reduction processes imply that the ion diffusion on the surface of the TiOx nanobelt is nonlinear. In addition, different bias voltage magnitudes (±1, ±2, ±3, ±4, ±5 and ±6 V) were operated on the Ag|TiOx|Ti device (Fig. 2g). When the bias voltage is less than ±5 V, a linear feature can be obtained for the voltage magnitude versus the peak current (Fig. 2h). 3.2 Moisture Dependent of the BLC Transition oxides, for instance, the TiO2 [26, 33], TaOx [30], ZnO [58] and SrTiO3 [31] have shown obvious change in resistance when they are exposed from dry circumstance to moist ambient. Besides H2O, Y. Li and Y. Gao have emphasized that the I-V hysteresis is possibly influenced by other gases in air ambient, such as O2 and CO2 [59]. In order to investigate the influences on the I-V hysteresis, both dry and moist N2, O2, CO2 and air were tested using the Ag|TiOx|Ti device. In dry circumstance, the I-V hysteresis shows that i) the oxidized and reduced peaks disappear; ii) the capacitance features are kept; iii) the maximum currents sharply decrease (Fig. 3a). Disappearance of redox peaks indicates 10

Fig. 3. Moisture dependent I-V hysteresis of the Ag|TiOx|Ti device in (a) dry air, N2, O2, CO2 and (b) moist air, N2, O2, CO2. The bias voltage scan rate is 1.0 V/s.

Fig. 4. Fifteen consecutive I-V hysteresis under three relative humidity (RH) levels: (a), (d) dry circumstance; (b), (e) air ambient with RH of 35% ~ 45% and (c), (f) humidified synthetic air with RH of 95% ~ 100%. The bias voltage scan rate is 1.0 V/s.

that the redox reactions are forbidden or suppressed in dry ambient. Here, we define the I-V hysteresis in dry ambient as a non-standard faradic capacitance (NFC). The BLC behaviors are re-observed when exposing the Ag|TiOx|Ti device into the moist atmosphere (RH=35% ~ 45%) of N2, O2, CO2 and air (Fig. 3b). To be noted that the Imax+ and Imax- are -3.5 and 4.0 nA for the NFC, but they sharply increase to -4.0 and 2.5 µA when entering into the BLC. The Imax increases near three orders after exposing into the atmosphere with RH of 35% ~ 45% ambient. Therefore, the NFC as a former stage of the BLC is observed in our devices.

11

The 15 consecutive I-V loops with a constant bias voltage scan rate of 1.0 V/s were measured under three RH levels (RH=0%, 35% ~ 45%, 95% ~ 100%). The NFC is expectedly observed in the RH level of 0% (Fig. 4a). The BLC characterized oxidized and reduced peaks appears when the RH level was increased from 0% to 35% ~ 45%, and the high current feature is observed as well (Fig. 4b). Very interesting, the I-V loops present the highest current value and a cross-feature when the RH level was further increased from 35% ~ 45% to 95% ~ 100%, despite the cross point is not at 0 V (Fig. 4c). The device under the RH of 95% ~ 100% exhibits the resistive switching (RS) memory because the I-V curves are pinched. The NFC can be detected again when the RH of 95% ~ 100% downscaling to 0% (Fig. 4d). The BLC is re-observed when the RH level re-increasing from 0% to 35% ~ 45% (Fig. 4e). The RS behavior is re-observed after the RH level re-increasing from 35% ~ 45% to 95% ~ 100% (Fig. 4f). Compared with the I-V loops under the same RH levels, the NFC, BLC and RS states are reversible. The Imax+ and Imax- extracted from Figure 4 were employed to evaluate the water-redox contribution under different RH levels. The Imax+ ranges from 1.0×10-9 to 5.0×10-9 A under the dry ambient (RH=0%). When elevating the RH from 0% to 35% ~ 45%, the Imax+ is about 1.2×10-6 ~ 5.7×10-6 A. If increasing the RH level to 95% ~100%, the Imax+ reaches the 1.8×105

~ 8.5 ×10-5 A (Fig. 5a). Compared with the Imax+ in the dry atmosphere (RH=0%), the Imax+

under air ambient (RH=35% ~ 45%) and the highest moist circumstance (RH=95% ~ 100%) increases over 3 ~ 4 orders. As for Imax-, it is between 7.0×10-10 and 5.0 ×10-9 A under the dry ambient, and the value increases to 1.5×10-6 ~ 3×10-6 A after exposing into air ambient with RH= 35% ~ 45%. Finally, the Imax- reaches to 5×10-5 ~ 1.0 ×10-4A in the highest moist circumstance (Fig. 5b). By comparing, the Imax- can be increased over 4 ~ 5 orders. Therefore, the NFC in the dry ambient gradually enters into the BLC stage, and finally evolves to be the RS state. The data storage for the ReRAM is nonvolatile, but whether the NFC and BLC are nonvolatile or not have not been verified. The resistance states for same Ag|TiOx|Ti cell were 12

Fig. 5. (a) Imax+ versus the RH cycles. (b) Imax- versus the RH cycles. (c) The resistance ratios for the NFC, BLC and RS states. (d) Resistance maintained after operating moisture pulse at 0.5 V reading voltage.

investigated at -4 V, where the bias voltage sweeps from 0 to -4 V and reversely sweeps from -6 to -4 V. After that, the current versus time (100 seconds) curves are tested under a constant reading voltage of -0.5 V. By that, the resistance ratio can be obtained for each RH cycle (Fig. 5c). To further verify the results, the resistance states at +3 V under a constant reading voltage of +0.2 V can be maintained during 1000 seconds for the BLC and RS. But it is too low to be distinguished for the NFC (data not shown here). Therefore, the capacitance-based device reveals a new type of data storage device. Under zero bias voltage, the resistance states under RH cycles can be well maintained for 50 seconds at a reading voltage of +0.5 V (Fig. 5d). Thus, the moisture-based memory logic gates, moisture logic displays and the moisture sensors are feasible [26]. 3.3 Physical dynamic process for the NFC, BLC and RS state The distribution and migration of the oxygen vacancy (Vo) and

– $ )#* on

the surface

plays an important role in the electric conduction of the TiOx nanobelts. The TiOx samples are ultrasonic dispersed and the nanobelt structure can be observed, as HR-TEM image shown in Figure 6a. The XPS with Ar+ etching was operated on the TiOx dispersion sample (Fig. 6b). The Ar+ etching rate is ~ 0.1 nm/s. Without Ar+ etching, the XPS spectra of Ti 2p and O 1s agree with previous measurements (Figs. 1e-1f). However, the Ti 2p and O 1s have shown an 13

Fig. 6. (a) HR-TEM image for the TiOx nanobelt. (b) Schematic of the XPS with the Ar+ etching. XPS spectra of the (c) Ti 2p and (d) O 1s for the TiOx nanobelt after Ar+ etching for 0 ~ 30 seconds.

obvious “blue shift” after Ar+ etching for 5 s (Figs. 6c-6d), while the Ti 2p and O 1s in the TiOx nanobelts have well maintained during the etching time of 5 ~ 30s. Thus, this indicates the Vo and

– $ )#*

mainly distribute on the surface.

Based on previous XRD and XPS analysis (Figs. 1d-1f), the anatase TiO2 is the main component for the TiOx nanobelts. Therefore, the TiO2 crystal growing along anatase TiO2 [101] direction to form the nanobelt structure was employed to describe our fabricated samples (Fig. 7a). According to the Ar+ etching analysis of the TiOx nanobelts, the Vo mainly distributes on the surface. Therefore, the possible sites of the surface Vo are considered. According to the O atom sites in the Ti-O bond, four different sites of the O1, O2, O3 and O4 exist in the TiOx nanobelt (Fig. 7b). The density-functional theory (DFT) calculations illustrate that the surface Vo forming energies for the surface Vo at O1, O2, O3 and O4 sites are -303.96, -303.52, -303.19 and -305.75 eV, respectively (Fig. 7c). Therefore, O4 is the most possible reaction site for the TiOx nanobelt. Based on our previous experiment results, the NFC, BLC and RS states are mainly dominated by RH levels. Therefore, the water molecule 14

Fig. 7. (a) Schematic of the TiOx nanobelt structure. (b) Four kinds of Vo sites in the surface and subsurface of the TiOx nanobelts. (c) The Vo sites in the exposed edge along the lattice of [101] and their corresponding total energy. The Vo of O4 site has the lowest energy of -305.75 eV. (d) Water molecules adsorbed on the surface and the surface Vo of O4 site suspending OH-.

Fig. 8. Projected density of states (PDOS) of the Ti and O atoms in (a) the TiO2 bulk and (b) the TiO2 nanobelt. (c) The PDOS for the TiO2 nanobelt after adsorbing the H2O molecules. (d) The PDOS for the TiO2 nanobelt with the OH-. The inset denotes the concentration of electron for the H2O adsorption and reaction processes.

adsorption and reaction processes are should be the reason (Fig. 7d). Since the reaction active surface Vo site and H2O-based redox reaction behaviors are given by theoretical calculations, the intrinsic energy structure of the TiOx nanobelt, which is the direct reason of the electric conduction of material, is needed to study. The projected 15

density of states (PDOS) versus energy of the Ti and O atoms indicates that the band gap energy (Eg) is 3.12 eV for the anatase TiO2 bulk (Fig. 8a). This calculation result is well agreed with the result given by the group of Y. Li [59, 60]. Thus, the calculations for the TiOx nanobelt are reasonable. The PDOS versus energy presented in Figure 8b shows the Eg is 1.43 eV for the TiOx nanobelt. The Eg drops from 3.12 to 1.43 eV due to the TiOx nanobelt structure. The Eg becomes 2.61 eV after adsorbing H2O on the surface (Fig. 8c). Therefore, the H2O adsorption is an important process before the H2O-related redox reactions happen. In other words, the energy band structure of the TiOx nanobelt can be easily modulated by changing its surface state.After completing the H2O adsorption, a variety of redox reactions will take place. The large number of ions (i.e., OH-), electrons and gases are generated on the surface of the TiOxnanobelt during those redox reaction processes. The PDOS versus energy for the TiOx nanobelt with OH-, which is contributed by H2O-based redox reactions, shows that the Eg decreases from 2.61 to 2.18 eV (Fig. 8d). Namely, the electric conductivity has been enhanced due to the OH- bonded on the surface of TiOx nanobelt. After completing the redox reactions, the chemical bonds of Ti-Ow (oxygen atom from H2O) and O-Hw (hydrogen atom from H2O) are generated on the surface of TiOx nanobelt, implanting defects into the TiOx nanobelt [31]. To be noted that electrons are generated in the bandgap between the conduction band and valence band for the TiOx nanobelt due to the surface defects (i.e., Vo, VTi,

– $ )#* ).

To

evaluate the number of electrons near Fermi level, the integration of the PDOS versus energy from 0 to 1.0 eV is conducted based Figs. 8c-8d) as shown in the inset of the Fig. 8d. The electron concentration is 2.79 for the TiOx nanobelt, dropping to 1.99 when the H2O is adsorbed on the surface. It further decreases from 1.99 to 0.59 after completing redox reactions. Therefore, a conclusion can be drawn: i) the H2O firstly adsorbs on the surface, ii) a 16

Fig. 9. Physical dynamic processes for the NFC, BLC and RS states. Schematic of the Ag|TiOx|Ti device in (a) the dry ambient, (b) adsorption H2O process, (c) H2O-related redox reactions and (d) Enhanced H2O-based redox reactions and ion migration. Band structure of the Ag|TiOx|Ti device of (e) in dry atmosphere (NFC), (f) after the H2O adsorption (enhanced NFC), (g) after H2O-related redox reactions (BLC) and (h) after ion migration (RS state).

series of redox reactions are triggered by the adsorbed H2O and the active surface Vo, iii) the electrons in forbidden band have been transferred during adsorption and reaction processes. Based on above calculations, despite the results are static, the physical dynamic processes can be constructed for the NFC, BLC and RS states. The physical processes can be divided into four stages: i) the Ag|TiOx|Ti device in dry ambient (NFC); ii) H2O adsorption (enhanced NFC); iii) H2O based redox processes (BLC) and iv) ions migration (RS state), as shown Figs. 9a-9d. In the first stage i, the TiOx nanobelt with the Eg of 1.43 eV and an acceptor energy level (△Ea) of 0.34 eV above the Fermi level, which is contributed by the unique nanobelt structure, has presented the NFC under dry ambient (Fig. 9e). As previous mentioned, there are 2.79 electrons in these Ea levels. Generally, RS behavior dominated by Ag ions shows abrupt SET and RESET process for the nanoscale device with the switching layer of ~100 nm. When the switching layer more than ~500 nm, the Ag ions migration becomes more difficulty [61]. Taking into account, the thickness of ~850 nm of the TiOx nanobelt, the Ag2O generation at interface under moisture ambient and the continuous change of the BLC and NFC, we deduce that the Ag+ possibly is not the main reason. In addition, the migration and diffusion are possible for the

– $ )#* .

However, the XPS has verified its low concentration, thus, the 17

contribution from

– $ )#*

is negligible. In this case, the restriction for both ion migration and

surface-based reaction result in the TiOx nanobelt device showing NFC behaviors. In the second stage ii, the Eg of the TiOx nanobelt is enlarged to be 2.61 eV, but the △Ea increases from 0.34 to 0.89 eV due to the H2O adsorption on the surface (Fig. 9f). After hopping into the conduction band, some of the electrons at the Ea levels are possibly transferred to the electrodes. Therefore, the adsorption of H2O on the TiOx nanobelt surface enhances the NFC. Here, we predict that there is an enhanced NFC before the H2O-related redox reaction occurs. In the third stage iii, the Eg of the TiOx nanobelt is downscaled to be the 2.18 eV, but the △Ea decreases from 0.89 to 0.17 eV due to the H2O-related redox occurrence(Fig. 9g). I. Valov, Y. Li and F. Messerschmitt have stressed that the surface, subsurface and interface Vo are more sensitive to the H2O molecules [28, 31, 59], where the H2O splitting, migration and interplay between ions and electrons are happened. The H2O firstly adsorbs on the surface Vo of O4 site and then generates substantial hydroxide ions by corresponding redox reaction, these processes are described by [31]: -O

where the

× /,

∙∙ / are

+

× /

+

∙∙ /

⇌2

∙ /

(4)

the oxygen atom in lattices and the surface or subsurface Vo. According

to the Eq. (4), a large number of OH- ions are generated on the surface of TiOx nanobelt. Simultaneously, according to the half-cell theory, the H2O-based reactions are possibly occurred at the interfaces of our devices, which can be described by as following [31, 62]: 2

-O

⇌

-

↑ +4H ∓ + 4e

(5)

I. Valov and J. L. M. Rupp groups have pointed out that electric conduction of the device is possibly dominated by the Vo-based reactions [63, 64]. Taking into account that the Vo mainly distributes on the surface of TiOx nanobelts and its high concentration, the reactions described by the Eq. (4) but not Eq. (5) dominate the redox process. This leads to the 2.18 of Eg and 0.17 18

eV of △Ea for the TiOx nanobelts, respectively. While, the generation of the ions (OH-, H+) and electrons promise the high conductivity of device. Thus, the electron hopping from Ea level to the conduction band in conjunction with the ion/electron generation is responsible for the BLC observed in our device. In the final stage iv, a large number of ions (OH-, H+) and electrons have been generated despite the energy band structure shows a little change compared with that before redox reaction (Fig. 9h). Under this circumstance, the conduction filament-like paths are formed by the high concentration of ions and electrons on the surface and subsurface. Thus, a RS state characterized by the redox feature is triggered by those paths. From the theoretical calculation, an energy band-based physical model is constructed to understand the NFC, enhanced-NFC, BLC and RS states. The H2O adsorption and reaction processes are involved by this model as well. According to the Eqs. (4)-(5) and the physical model, we have deduced that electron transfer occurs during the H2O adsorption and reaction processes, which is a key point to the interpretation. This will be verified by the following theoretical calculations. The differential charge density (△ρ) is calculated to evaluate the charge transfer, during the H2O adsorption and H2O-related redox reaction processes. The △ρ is defined to be as following [65, 66]: ∆ρ = 9: Where, the 9:

:); ,

:);

− 9*=>*:"): − 9)#*

(6)

9*=>*:"): and 9)#* are the charge densities of the TiOx nanobelt with

adsorbate (H2O molecule or the suspending OH-), TiOx nanobelts and adsorbate, respectively. An isosurface is selected to be a 0.008 e/Å3 during the differential charge density calculation. The side-view of the isosurface of the differential charge density has presented the charge distribution in different region when the H2O adsorbed on the surface of the TiOx nanobelt (Fig. 10a). The yellow and grey-blue region denotes the depletion and accumulation 19

Fig. 10. Side-view of the isosurface of the differential charge density (△ρ) of (a) the H2O adsorbed on the surface and (b) the suspending OH- bond on the surface Vo at site O4 of the TiOx nanobelt. The isosurface is 0.008 e/Å3. The yellow and greyblue present the depletion and accumulation of electrons, respectively.

of electrons, respectively. One can see that many accumulated electrons mainly distribute on the surrounding of H2O molecules and a few depleted electrons distribute on the subsurface after H2O-related redox reaction. However, the grey-blue region mainly distributes on the surface/subsurface of TiOx nanobelts, while the yellow region distributes on the surrounding of OH- ions (Fig. 10b). In other words, the electrons have been transferred from the surrounding of H2O to the surface and subsurface of the TiOx nanobelts after redox reaction. Therefore, the NFC is enhanced when adsorption H2O and then the electron transfer from the H2O to the surface/subsurface of the TiOx nanobelts make the device involve to the BLC. The I-V hysteresis including the NFC in dry atmosphere, BLC in moist ambient and RS state in high moisture circumstance are now comprehended by the physical model. Ions and electrons are generated during the above stages. The interplay between ions and electrons is very weak at RH of 0% in the device, leading to the NFC (Fig. 11a). The interplay is enhanced (oxidization, reduction) when the device is exposed under the moisture ambient (RH=35% ~ 45%), driving the device into the BLC (Fig. 11b). 20

Fig. 11. The RH-dependent evolution paths from (a) the original state (NFC), (b) transition state (BLC) to (c) switching state (RS state) for the Ag|TiOx|Ti device. (d) The schematic of physical process for the NFC, BLC and RS states.

The coupling between the ions and electrons becomes very strong (migration, diffusion, electron transfer) at higher moisture levels (RH=95% ~ 100%), finalizing the device into RS state (Fig. 11c). A schematic picture for the NFC, BLC and RS states (Fig. 11d) of a scene including the H2O adsorption, splitting and interplay between ions and electrons is demonstrated. Memeristor device can be classified two types: electrochemical metallization memory device (ECM) and the valence change memory device (VCM). To verify our deduction on the NFC, the nanoscale VCM and ECM devices are carefully designed. The Ag|MoO3 (~37 nm)|Au device is designed as ECM. The NFC is observed in the Ag|α-MoO3|Au device after operating an ultralow bias sweep (-0.4~0.4 V) at RH of 0% (Fig. 12a). Under the same bias sweep but exposure to air ambience with RH of 40%±5%, the BLC is observed in the same cell. It implies that the H2O-related redox reaction has been implanted into the NFC. The redox capacitance state of Ag|MoO3|Au transfers to the memristive regime by elevating the RH level to 95%±5%. The Au|ZnO|TiO2|F-doped SnO2 device, an example of VCM device, is fabricated due to high concentration of at the interfaces of ZnO|TiO2 (~100 nm|~85 nm) and 21

Fig. 12. Verification of the NFC, BLC and RS state for the oxide-based memristor of (a) Ag|MoO3|Au, (b) Au|ZnO-TiO2|Fdoped SnO2, (c)Ag|SiO2|Pt, (d) Au|MoS2-MoOx<2|Pt [67] and the BLC for the organic memristor of (e) Ag|Banana Peel Film|Ti [69], (f) Ag|Lichen Film| F-doped SnO2 [70], (g) Ag|Sweet Potato Peel Film| Indium tin oxide[71] and (h) Ag|Garlic Film| F-doped SnO2 [72]. Reproduced with permission.

TiO2|F-doped SnO2. Therefore, the memristive regime of the device with rich-Vo is easily triggered under ultralow bias voltage (-0.2~0.2 V) when operating under high RH (95%±5%). The NFC and BLC are respectively observed when decreasing the RH to 0% and 65%±5% (Fig. 12b). The redox capacitance state has been reported in SiO2-based memristor [33]. We also fabricated a memristor with structure of Ag|SiO2 (~23 nm)|Pt (Fig. 12c). The NFC, BLC and RS are observed under low voltage (-0.4 ~ 1 V) for RH of 0%, 65%±5% and 95%±5%, respectively. Importantly, we previously have found that the NFC, BLC and RS state can be observed in the Au|MoS2-MoOx<2|Pt device under different bias voltage magnitude (Fig. 12d), despite these stages are not recognized in that time [67]. The NFC state evolves to the RS memory as the increase of bias voltage magnitude. Higher bias voltage, the larger peak current is. Under ultralow bias voltage, the RS is not be triggered [68]. Therefore, the moisture is possible as one of the conditions for the trigger of the NFC, BLC and RS. In fact, the NFC and BLC states have been extensively observed in the organic memristive devices: Ag|Banana Peel Film|Ti, Ag|Lichen Film| F-doped SnO2, Ag|Sweet Potato Peel Film| Indium tin oxide and Ag|Garlic Film| F-doped SnO2 [69-72]. As the physical 22

and chemical fundament issue of memristor, the theory and conception are needed to expand [63, 73-75]. Capacitive effect has been demonstrated by AC impedance spectra for the NFC and BLC states, but the capacitive impedance is loss for the RS state (data not shown here). Therefore, the capacitive effect is suppressed seriously when the physical reconfiguration of switching layer is established. 4. Conclusion The Ag|TiOx|Ti device exhibits a non-standard faradic capacitance (NFC) in dry circumstance. After exposing to the moisture atmosphere (RH=35% ~ 45%), the NFC evolves to a battery-like capacitance (BLC). When the moisture level is increased to the RH of 95% ~100%, the BLC finally evolves to the RS state. The Imax of BLC and RS states increase over 4 orders compared with the NFC. The H2O adsorption and redox reaction are responsible for the NFC, BLC and RS states. Importantly, the evolution processes including the NFC, BLC and RS state are detected in both VCM and ECM device. The DFT calculations illustrate that energy band structure of TiOx nanobelt is modulated by the H2O adsorption and redox reaction processes. A physical model involving the interplay between ions and electrons, band structure and electron transfer is proposed to comprehend the evolution processes. Acknowledgements The work was supported by Postdoctoral Program for Innovative Talent Support of Chongqing (CQBX201806), National Natural Science Foundation of China (Grant Nos. 11774293, 61571372, 61672436, 61601376), Fundamental Research Funds for the Central Universities (Grant Nos.XDJK2016A001, XDJK2017A002, XDJK2017A005), the Program for Innovation Team Building at Institutions of Higher Education in Chongqing (Grant No. CXTDX201601011). References [1] J. Song, Y. Zhang, C. Xu, W. Wu, Z. L. Wang, Nano Lett. 11 (2011) 2829–2834.

23

[2] Z. L. Wang, Nano Energy 54 (2018) 477-483. [3] X. B. Yan, J. Zhao, S. Liu, Z. Zhou, Q. Liu, J. Chen, X. Y. Liu, Adv. Funct. Mater. 28 (2018) 1705320. [4] Z. L. Wang, Mater. Today 20 (2017) 74-82. [5] Z. L. Wang, Nature 542 (2017) 159-160. [6] Q. Tang, M.H. Yeh, G. Liu, S. Li, J. Chen, Y. Bai, L. Feng, M. Lai, K.C. Ho, H. Guo, C.G. Hu, Nano Energy 47 (2018) 74-80. [7] X. Pu, H. Guo, J. Chen, X. Wang, Y. Xi, C. Hu, Z. L. Wang, Sci. Adv. 3 (2017) 1700694. [8] Z. Lv, M. Chen, F. Qian, V. A. L. Roy, W. Ye, D. She, Y. Wang, Z. X. Xu, Y. Zhou, S.-T. Han, Adv. Funct. Mater. 29 (2019) 1902374. [9] H. Guo, X. Pu, J. Chen, Y. Meng, M.-H. Yeh, G. Liu, Q. Tang, B. Chen, D. Liu, S. Qi, C. Wu, C. G. Hu, J. Wang, Z. L. Wang, Sci. Robot. 3 (2018) 2516. [10] Q. Xia, J. J. Yang, Nat. Mater. 18 (2019) 309-323. [11] L. Sun, Y. Zhang, G. Han, G. Hwang, J. Jiang, B. Joo, K. Watanabe, T. Taniguchi, Y. M. Kim, W. J. Yu, B. S. Kong, R. Zhao, H. Yang, Nat. Commun. 10 (2019) 3161-3167. [12] G. D. Zhou, Z. J. Ren, L. D. Wang, J. G. Wu, B. Sun, A. K. Zhou, G. H. Zhang, S. H. Zheng, S. K. Duan, Q. L. Song, Nano Energy 63 (2019) 103793. [13] G. D. Zhou, Z. J. Ren, L. D. Wang, B. Sun, S. K. Duan, Q. L. Song, Mater. Horiz. 6 (2019) 1877-1882. [14] B. Sun, Y. Chen, M. Xiao, G. D. Zhou, S. Ranjan, W. Hou, X. Zhou, Y. Zhao, S. A. T. Redfern, Y. N. Zhou, Nano Lett. 199 (2019) 6461-6465. [15] M. A. Zidan, J. P. Strachan, W. D. Lu, Nat. Electron. 1 (2018) 22-29. [16] J. Xiao, S. Zhong, Neurocomputing 363 (2019) 321-338. [17] J. Xiao, S. Zhong, Appl. Math. Comput. 323 (2018 )145-163. [18] K. Shi, S. Zhong, Y. Tang, J. Cheng, Fuzzy. Set. Syst. doi.org/10.1016/j.fss.2019.09.001. [19] K. Shi, J. Wang, Y. Tang, S. Zhong, Fuzzy. Set. Syst., doi.org/10.1016/j.fss.2018.11.017. [20] A. Wedig, M. Luebben, D. Y. Cho, M. Moors, K. Skaja, V. Rana, T. Hasegawa, K. K. Adepalli, B. Yildiz, R. Waser, I. Valov, Nat. Nanotechnol. 11 (2016) 67-74. [21] Y. Yang, H. Du, Q. Xue, X. Wei, Z. Yang, C. Xu, D. Lin, W. Jie, J. Hao, Nano Energy 57 (2019) 566573. [22] W. Xu, T. L.Nguyen, Y. T. Kim, C. Wolf, R. Pfattner, J. Lopez, B. G. Chae, S. Kim, M. Y. Lee, E.Y. Shin,Y. Y. Noh, J. H. Oh, H. Hwang, C. G. Park, H. Y. Woo,T. W. Lee, Nano Energy 48 (2018) 575581. [23] J. Borghetti, G. S. Snider, P. J. Kuekes, J. J. Yang, D. R. Stewart, R. S. Williams, Nature 464 (2010) 873-876. [24] M. D. Pickett, J. Borghetti, J. J. Yang, G. M. Ribeiro, R. S. Williams, Adv. Mater. 23 (2011) 17301733.

24

[25] M. S. Kadhim, F. Yang, B. Sun, Y. Wang, T. Guo, Y. Jia, Y. Zhao, Appl. Phys. Lett. 113 (2018) 053502. [26] G. D. Zhou, S. Duan, P. Li, B. Sun, B. Wu, Y. Yao, X. Yang, J. Han, J. Wu, G. Wang, L. Liao, C. Lin, W. Hu, C. Xu, D. Liu, T. Chen, L. Chen, A. Zhou, Q. L. Song, Adv. Electron. Mater. 4 (2018) 1700567. [27] D. Cho, M. Lübben, S. Wiefels, K. Lee, I. Valov, ACS Appl. Mater. Interfaces. 9 (2017) 19287-19295. [28] I. Valov, T. Tsuruoka, J. Phys. D: Appl. Phys. 51 (2018) 413001. [29] V. G. Karpov, Y. A. Kryukov, S. D. Savransky, I. V. Karpov, Appl. Phys. Lett. 90 (2007) 123504. [30] M. Lübben, S. Wiefels, R. Waser, I. Valov, Adv. Electron. Mater. 4 (2018) 1700458. [31] F. M. Messerschmitt, J. L. Kubicek, L. J. M. Rupp, Adv. Funct. Mater. 25 (2015) 5117-5125. [32] A. Zaffora, D.Y. Cho, K. S. Lee, F. D. Quarto, R.Waser, M. Santamaria, I. Valov, Adv. Mater. 29 (2017) 1703357. [33] S. Tappertzhofen, I. Valov, T. Tsuruoka, T. Hasegawa, R. Waser, M. Aono, ACS Nano. 7 (2012) 63966402. [34] S. Tappertzhofen, S. Menzel, I. Valov, R. Waser, Appl. Phys. Lett. 99 (2011) 203103. [35] J. Jiang, Z. L. Bai, Z. H. Chen, L. He, D. W. Zhang, Q. H. Zhang, J. A. Shi, M. H. Park, J. F. Scott, C. S. Hwang, A. Q. Jiang, Nat. Mater. 17 (2018) 49-56. [36] B. Sun, X. Zhang, G. D. Zhou, P. Li, Y. Zhang, Y. Xia, Y. Zhao, Org. Electron. 42 (2017) 181-186. [37] J. Chen, M. A. Reed, A. M. Rawlett, and J. M. Tour, Science, 286 (1999) 1550-1552. [38] M. Xiao, D. Shen, K. P. Musselman, W. W. Duley, Y. N. Zhou, Nanoscale, 10 (2018) 6069-6079. [39] G. Milano, S. Porro, I. Valov, C. Ricciardi, Adv. Electron. Mater. 5 (2019) 1970044. [40] J. Tian, Z. Zhao, A. Kumar, R. I. Boughton, H. Liu, Chem. Soc. Rev. 43 (2014) 6920-6937. [41] Y. M. Wang, G. J. Du, H. Liu, D. Liu, S. B. Qin, N. Wang, C. G. Hu, X. T. Tao, J. Jiao, J. Y. Wang , Z. L. Wang, Adv. Funct. Mater. 18 (2008) 1131-1137. [42] K. Pan, Q. Zhang, Q. Wang, Z. Liu, D. Wang, J. Li, Y. Bai, Thin Solid Films. 515 (2007) 4085-4091. [43] J. Tian, Y. Leng, Z. Zhao, Y. Xia, Y. Sang, P. Hao, J. Zhan, M. Li, H. Liu, Nano Energy 11 (2015) 419427. [44] C. J. O. Kelly, J. A. Fairfield, D. McCloskey, H. G. Manning, J. F. Donegan, J. J. Boland, Adv. Electron. Mater. 2 (2016) 1500458. [45] G. D. Zhou, X. Yang, L. Xiao, B. Sun, A. Zhou, Appl. Phys. Lett. 114 (2019) 163506. [46] G. Kresse, J. Furthmüller, Phys. Rev. B 54 (1996) 11169-11186. [47] P. E. Blochl, Phys. Rev. B 50 (1994) 17953-17979. [48] J. P. Perdew, K. Burke, M. Ernzerhof, Phys. Rev. Lett. 77 (1996) 3865. [49] S. L. Dudarev, G. A. Botton, A. P. Sutton, Phys. Rev. B 57 (1998) 1505. [50] J. Park, S. Lee, K.Yong, Nanotechnology 23 (2012) 385707. [51] A. Gurlo, Chem. Phys. Chem. 7 (2006) 2041-2052.

25

[52] R. Waser, R. Dittmann, G. Staikov, K. Szot, Adv. Mater. 21(2009) 2632. [53] F. Messerschmitt, M. Jansen, J. L. M. Rupp, Adv. Electron. Mater. 4 (2018) 1800282. [54] G. D. Zhou, W. Zhao, X. Ma, A. K. Zhou, J. Alloys. Compounds. 679 (2016) 47-53. [55] J. J. Yang, D. B. Strukov, and D. Stewart, Nat. Nanotechnol. 8 (2013) 13-24. [56] L. F. Sun, H. Yu, D. Wang, J. Jiang, D. Kim, H. Kim, and H. Yang, 2D Materials, 6 (2018) 015029. [57] K. Liu, L. Qin, X. Zhang, J. Zhu, X. Sun, K. Yang, Y. Cai, Y. Yang, R. Huang, Faraday Discuss, 213 (2019) 41-52. [58] Z. H. Rizvi, S. Panda, M. A. Khan, and F. Wuttke, Mater. Today: Proceedings. 5 (2018) 18325-18331. [59] Y. Li, Y. Gao, Phys. Rev. Lett. 112 (2014) 206101. [60] Y. Gao, Y. Zhang, X. Wang, K. Sim, J. Liu, J. Chen, X. Feng, H. Xu, C. Yu, Sci. Adv. 3 (2017) e1701222. [61] G. D. Zhou, B. Sun, Y. Yao, H. Zhang, K. Alameh, B. Ding, Q. L. Song, Appl. Phys. Lett. 109 (2016) 143904. [62] G. D. Zhou, J. Wu, L. Wang, Z. J. Ren, C. Xu, Y.Yao, L. Liao, G. Wang, S. Zheng, P. Mazumder, S. Duan, Q. L. Song, Nanoscale 11 (2019) 17222-17229. [63] I. Valov, E. Linn, S. Tappertzhofen, R. Waser, Nat. Commun. 4 (2013) 1771. [64] M. Kubicek, R. Schmitt, F. Messerschmitt, J. L. M. Rupp, ACS Nano. 9 (2015) 10737-10748. [65] X. Liu, Y. Wen, Z. Chen, B. Shan, R. Chen, Phys. Chem. Chem. Phys. 17 (2015) 16398-16404. [66] Q. Ke, C. Guan, X. Zhang, M. Zheng, Y. W. Zhang, Y. Cai, H. Zhang, J. Wang, Adv. Mater. 29 (2017) 1604164. [67] G. D. Zhou, W. Zhao, X. Ma, and A. K. Zhou, J. Alloys. Compounds. 679 (2016) 47-53. [68] G. D. Zhou, Z. J. Ren, L. Wang, C. Xu, B. Wu, P. Li, Y. Yao,S. Duan, Chem.Commun. 55 (2019) 9915-9918. [69] L. Zheng, B. Sun, S. Mao, S. Zhu, P. Zheng, Y. Zhang, M. Lei, Y. Zhao, ACS Appl. Bio Mater. 1 (2018) 496-501. [70] S. Zhu, B. Sun, Y. Chen, T. Li, G. D. Zhou, H. Zhao, W. Mao, Y. Zhao, J. Mater. Chem. C, 7 (2019) 7593-7600. [71] S. Zhu, B. Sun, S. Ranjan, X. Zhu, G. D. Zhou, H. Zhao, S. Mao, H. Wang, Y. Zhao, G. Fu, APL Mater. 7 (2019) 081117. [72] S. Mao, B. Sun, T. Yu, W. Mao, S. Zhu, Y. Ni, H. Wang, Y. Zhao, Y. Chen, New J. Chem. 43 (2019) 9634-9640. [73] L. Wang, S. Liu, Z. Zhang, X. Feng, L. Zhu, H. Guo, W. Ding, L. Chen, Y. Qin, Z. L. Wang, Nano Energy 60 (2019) 724-733. [74] L. Zhou, S. Yang, G. Ding, J.Q. Yang, Y. Ren, S.R. Zhang, Y. Yang, Y. Zhou, S.T. Han, Nano Energy 58 (2019) 393-303.

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[75] Z. L. Wang, A. C. Wan, Mater. Today 30 (2019) 34-51.

Guangdong Zhou has received his PhD in Faculty of Materials and Energy from Southwest University (P. R. China) in June 2018. He is conducting his postdoctoral research in the Southwest University during 2018.07-2020.07. His research focus on the physical mechanism of memristor, memristor-based functions including the memory logics, displays and synapses. His memristor-related researches are supported by the Postdoctoral Program for Innovative Talent Support of Chongqing (600 thousands RMB). During past 5years, more than 50 peerreviewed papers were published. Dr. Zhou sincerely thirsts for the communication and cooperation from broad researchers. E-mail: [email protected], [email protected]. Tel: 086-185-8541-3032.

Zhijun Ren has received B. E. degree of resource exploration from Guizhou Institute of Technology of China in 2017, and now she is pursuing Master Degree at College of Resources and Environment, Southwest University of China. Her research mainly focuses on the agricultural environmental protection and memristor fabrications and applications. She is warm, kind and sunshine girl and also sincerely thirsts for the communication and cooperation from each research fields.

Bai Sun has received his PhD degree in Faculty of Materials and Energy from Southwest University in 2015. Currently, he is an associate professor at Southwest Jiaotong University, 27

and doing postdoctoral research in University of Waterloo. His research interests include multifunctional application of nanomaterials, physical devices (memristor and multiferroic devices), preparation of photocatalytic materials and exploration of new energy materials.

Jinggao Wu has received his PhD degree from Faculty of Materials and Energy, Southwest University (P. R. China) in 2018. His current research is focused on design and synthesis of new generation materials for energy, environmental and information storage applications, combining experimental and DFT calculations.

Zhuo Zou is a post-doctor of Institute for Clean Energy & Advanced Materials, Southwest University, China. She received a doctorate of philosophy in science at Southwest University in Chongqing. Her research interests include rapid diagnosis of dread diseases, food chemistry and advanced nanomaterials research.

Shaohui Zheng received his B. S. degree and M. S. degree in Nankai University in 1995 and 2003. He received his PhD degree in Computational Chemistry, State University of New York Buffalo in 2009. In 2009-2010, he as research associate in University of California, Berkeley conducted his research. In 2010-2012, he as research fellow in University of Michigan conducted his research. Now, he is a professor in School of Materials and Energy, Southwest University. His research is charge (electron) transfer and exciton dissociation process and metal dynamics in classical and quantum molecular dynamics. 28

Lidan Wang has received B. E. degree in automatic control from Nanjing University of Science and Technology of China in 1999 and Ph.D. degree in computer software and theory from Chongqing University of China in 2008. She is currently a Professor in Southwest University of China. She visited Imperial College London from 2010 to 2011, University of Windsor in 2013, Nanyang Technological University from 2016 to 2017, Texas A&M University at Qatar in 2017, and the University of Tasmania in 2018. Her research interests include memristor, neuromorphic computing, nonlinear circuits and systems and artificial neural networks.

Shukai Duan received B.S. and M.S. Southwest University in 1996 and 2003. He received his PhD degree Chongqing University in 2006. 2010-2011, he as visiting professor in University of Michigan conducted his research. He was selected to be the Ministry of Education New Century Outstanding Talents Support Program, China, 2013 and the Leading Talents of the Ministry of Science and Technology, China, 2019. He is an Associate Editor, IEEE Trans. on Neural Networks and Learning Systems (IF=11.86), Chief scientist of national key research and development program. Dean, School of Artificial Intelligence, Southwest University, China. More than 100 peer-reviewed papers were published.

Qunliang Song is a physicist of Southwest University and received his doctoral degree from the Fudan University (China) in 2006. In 2008, Prof. Song was founded by the Lee Kuan Yew Postdoctoral Fund and conducted his postdoctoral research in Nanyang Technological 29

University. Now, he is a professor in School of Materials and Energy, Southwest University. His research in organic solar cell was gradually shifted to perovskite solar cells, memristors and triboelectric nanogenerators. During the last 10 years, His research funds over 5 million RMB and over 100 peer-reviewed papers were published.

30

Highlights 1．Non-standard faradic capacitance (NFC), battery-like capacitance, (BLC) and resistive switching state (RS) are discovered in memristive system. 2. Capacitive effect (NFC, BLC) is an original of RS memory. 3. By DFT calculations, physical dynamic process of the capacitive effect is constructed. 4. Moisture plays an import role in the memristor evolution from NFC, BLC to RS.

Declarations of interest：None.

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