Chieu Quang

Vincent Bui

Sarah Consonni

Guillaume Boubenia

Corinne Gay

Mohammed Perret

Sebastien Zeghouane

Carmen Labau

Hervé Jiménez

Xavier Roussel

Mescot

Bui

Vincent Consonni

Sarah Boubenia

Guillaume Gay

Corinne Perret

Mohammed Zeghouane

Sebastien Labau

Carmen Jiménez

Hervé Roussel

Xavier Mescot

Gustavo Ardila

Influence of the AZO Electrode on ZnO Nanowire Growth by PLI-MOCVD and Related Piezoelectric Performance: Implications for Mechanical Energy Transducers

Keywords: ZnO, AZO, Atomic Layer Deposition, Metal-Organic Chemical Vapor Deposition, Nanostructures, Transparent conductive oxide, Piezoelectricity, Nanogenerators

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

ZnO nanowire (NW) structure has many interesting properties such as wide direct bandgap (3.37 eV), high exciton binding energy (60 meV), high flexibility, high light transparency, and high electron mobility, which are suitable for a wide range of applications. [START_REF] Özgür | A Comprehensive Review of ZnO Materials and Devices[END_REF][START_REF] Kołodziejczak ; Radzimska | Zinc Oxide-From Synthesis to Application: A Review[END_REF] It has received increasing attention in recent years as a potential candidate for lead-free piezoelectric devices as an abundant, inexpensive, and biocompatible material possessing piezoelectric properties. [START_REF] Wang | Towards Self-Powered Nanosystems : From Nanogenerators to Nanopiezotronics[END_REF][START_REF] Goel | A Review on Piezo-/ Ferro-Electric Properties of Morphologically Diverse ZnO Nanostructures[END_REF][START_REF] Le | A Review on ZnO-Based Piezoelectric Nanogenerators : Synthesis, Characterization Techniques, Performance Enhancement and Applications[END_REF] Thanks to its visible light transparency, ZnO NW structure can be combined with other transparent electrodes to develop devices that require both piezoelectric and optical properties, such as touch screen sensors, [START_REF] Choi | Mechanically Powered Transparent Flexible Charge-Generating Nanodevices with Piezoelectric ZnO Nanorods[END_REF][START_REF] Kang | Fully Flexible and Transparent Piezoelectric Touch Sensors Based on ZnO Nanowires and BaTiO3-Added SiO2 Capping Layers[END_REF] or photocatalytic, photovoltaic as well as innovative piezoelectric applications using the piezophototronic effect for performance enhancement. [START_REF] Liu | Interface Engineering on P-CuI/n-ZnO Heterojunction for Enhancing Piezoelectric and Piezo-Phototronic Performance[END_REF][START_REF] Song | Flexible Li-Doped ZnO Piezotronic Transistor Array for in-Plane Strain Mapping[END_REF][START_REF] Pan | Advances in Piezo-Phototronic Effect Enhanced Photocatalysis and Photoelectrocatalysis[END_REF][START_REF] Zhang | Enhanced Photovoltaic Performances of La-Doped Bismuth Ferrite/Zinc Oxide Heterojunction by Coupling Piezo-Phototronic Effect and Ferroelectricity[END_REF][START_REF] Zheng | Dynamic Real-Time Imaging of Living Cell Traction Force by Piezo-Phototronic Light Nano-Antenna Array[END_REF] Indium tin oxide (ITO) is usually selected for the transparent electrode thanks to its high electrical conductivity (~10 -4 Ω.cm) and visible light transmittance (> 85%). [START_REF] Ellmer | Past Achievements and Future Challenges in the Development of Optically Transparent Electrodes[END_REF][START_REF] Kawajiri | Lifecycle Assessment of Critical Material Substitution: Indium Tin Oxide and Aluminum Zinc Oxide in Transparent Electrodes[END_REF] However, the scarcity and toxicity of indium-based compounds give rise to some concerns related to its supply risk and its cost. [START_REF] Kawajiri | Lifecycle Assessment of Critical Material Substitution: Indium Tin Oxide and Aluminum Zinc Oxide in Transparent Electrodes[END_REF][START_REF] Lim | Studies on the Toxicity and Distribution of Indium Compounds According to Particle Size in Sprague-Dawley Rats[END_REF][START_REF] Badding | Pulmonary Toxicity of Indium-Tin Oxide Production Facility Particles in Rats[END_REF] Other materials that can be used for transparent electrodes are for instance silver NWs, [START_REF] Madeira | Rapid Synthesis of Ultra-Long Silver Nanowires for High Performance Transparent Electrodes[END_REF] graphene, [START_REF] Rana | A Graphene-Based Transparent Electrode for Use in Fl Exible Optoelectronic Devices[END_REF] fluorine-doped zinc oxide (FZO), [START_REF] Tuan | Journal of Science : Advanced Materials and Devices High-Mobility Sputtered F-Doped ZnO Films as Good-Performance Transparent-Electrode Layers[END_REF] fluorine-doped tin oxide (FTO), [START_REF] Way | Fluorine Doped Tin Oxide as an Alternative of Indium Tin Oxide for Bottom Electrode of Semi-Transparent Organic Photovoltaic Devices[END_REF] or aluminum-doped zinc oxide (AZO). [START_REF] Sarma | Al:ZnO) Thin Films with High Figure of Merit as Stable Indium Free Transparent Conducting Oxide[END_REF] Among them, AZO is a highly suitable alternative to ITO, as it is composed of abundant elements and considered as a non-toxic material with high electrical conductivity and optical transmittance comparable to ITO. [START_REF] Kawajiri | Lifecycle Assessment of Critical Material Substitution: Indium Tin Oxide and Aluminum Zinc Oxide in Transparent Electrodes[END_REF][START_REF] Dhage | Transparent Conducting Al:ZnO Thin Films on Large Area by Efficient Cylindrical Rotating DC Magnetron Sputtering[END_REF][START_REF] Badgujar | Room Temperature Sputtered Aluminum-Doped ZnO Thin Film Transparent Electrode for Application in Solar Cells and for Low-Band-Gap Optoelectronic Devices[END_REF] Using ZnO NWs in combination with AZO electrodes would allow for the fabrication of a transparent piezoelectric device using only non-critical materials. This approach avoids using the materials that may be scarce, toxic, or have significant supply risks, thus ensuring the sustainability of the device.

When the AZO thin film is used as a bottom electrode as well as a growth platform, the deposition proceeds through a homogenous epitaxial growth, in which the surface and structure of the AZO layer can significantly affect the ZnO NW growth process. For instance, S. Pung et al. demonstrated that the growth direction of ZnO NWs is changed depending on the orientation of ZnO thin film used as a platform. [START_REF] Pung | Preferential Growth of ZnO Thin Films by the Atomic Layer Deposition Technique[END_REF] Thus, it is necessary to control not only the electrical conductivity and optical transmittance of AZO thin film, but also its structural properties in order to boost the piezoelectric performance. While many researches have showed that the AZO thin film exhibits relevant properties as a transparent electrode that can be used in many applications, there are only very few reports using it in piezoelectric applications, especially through its combination with ZnO NWs. [START_REF] Garcia | Size and Semiconducting Effects on the Piezoelectric Performances of ZnO Nanowires Grown onto Gravure-Printed Seed Layers on Flexible Substrates[END_REF] In this work, we study the possibility to use AZO thin films as an ecofriendly bottom electrode for ZnO NW-based mechanical energy transducers. These transducers can be used in energy harvesting and sensing applications. [START_REF] Lee | Ultrathin Nanogenerators as Self-Powered/Active Skin Sensors for Tracking Eye Ball Motion[END_REF][START_REF] Briscoe | Piezoelectric Nanogenerators -a Review of Nanostructured Piezoelectric Energy Harvesters[END_REF][START_REF] Tao | Performance of ZnO Based Piezo-Generators under Controlled Compression[END_REF] The AZO thin films are initially deposited on Si substrates by atomic layer deposition (ALD) process. The structural and electrical properties of AZO thin films are modified by varying the Al dopant concentration during its growth process. Then, these AZO electrodes are used as platforms for the subsequent growth of ZnO NWs using PLI-MOCVD process.

A schematic of the entire structure is described in Figure 1. A comparison of the ZnO NW growth on the AZO thin films to its growth directly on Si substrate is also performed. The morphology, structural properties and piezoelectric performance of ZnO NWs on the AZO thin film are analyzed by fieldemission scanning electron microscopy (FESEM), X-ray diffraction (XRD), Raman spectroscopy, and datacube piezoresponse force microscopy (PFM) measurements. In addition, an AZO thin film/ZnO NW structure is grown on a quartz substrate, and its optical transmittance is measured by UV-Vis-NIR spectrophotometry. The impacts of the AZO structural and electrical properties on the ZnO NW growth and piezoelectric performance are discussed in detail.

Experiment

AZO electrodes grown by ALD

Initially, AZO thin films were prepared by ALD method using the Cambridge NanoTech Fiji F200 system. Diethylzinc (DEZn) and trimethyl aluminum (TMA) were used as the Zn and Al precursors, respectively. The DEZn/TMA cycle number ratio was modified at 30, 20, and 10 to obtain the AZO thin films with different Al doping concentration, which are labeled as AZO30, AZO20, and AZO10. The water vapor (DI) was used as O precursor. The total cycle number was adjusted for every growth to have the same thickness at around 180 nm. The growths were performed simultaneously on the standard Si (100) with resistivity around 10 Ω.cm, heavily doped p-type Si (100) with the resistivity at 2 x 10 -3 Ω.cm, and quartz. The thin films on the standard Si substrates were used for the electrical measurements, while the thin films on the heavily doped p-type Si substrates were used for the PFM measurements. The thin films deposited on quartz were used for the optical transmittance measurements. The substrate temperature was maintained at 250 °C.

ZnO NWs grown by PLI-MOCVD

After the thin film deposition, the as-grown AZO thin films on heavily doped Si substrates were used as platforms for the ZnO NW growths. In addition, the ZnO NW array grown directly on a heavily doped Si substrate was also prepared as reference sample. The ZnO NWs were grown using PLI-MOCVD technique in an Annealsys MC-200 MOCVD system. The Si substrate, AZO30, AZO 20 and AZO10 thin films were put together in the PLI-MOCVD chamber, and the ZnO NW growths on those platforms were performed simultaneously. The Zn precursor was a solution of DEZn (Sigma-Aldrich) diluted in cyclohexane at 0.4 mol/l. This solution was injected to the reactor chamber at a flow rate of 0.5 g/min with 500 sccm Ar as gas carrier. The O 2 gas as an O precursor was introduced into the chamber with the flow rate set at 300 sccm. The temperature of the substrate and the chamber pressure were kept constant at 700 °C and 3 mbar during the growth, respectively. The growth duration was set at 10 minutes. On each AZO thin film, a small AZO area was covered by a piece of Si in order to protect that area from the ZnO NW deposition. Those AZO areas without ZnO NW deposition were used for electrical connection in the later PFM measurements.

Characterizations Structural, chemical, optical and electrical measurements

The morphologies and topographies of AZO thin films and ZnO NWs were studied using a Gemini300 FEI ZEISS-SEM system and a Bruker Dimension Icon atomic force microscope (AFM), respectively. The Al dopant concentrations of AZO thin films were analyzed by parallel angular X-ray photoelectron spectroscopy (XPS). The XPS system includes a customized Thermo Fisher Scientific Theta 300 system equipped with an X-ray source using a monochromatic aluminum anode (1486.6 eV) in ultrahigh vacuum conditions (< 1 × 10 -8 Pa). The XRD patterns of samples were investigated by a Bruker D8 Advance diffractometer using Cu Kα 1 radiation with the Bragg-Brentano configuration. The scanning range was from 20 to 140° on the 2θ-scale. To evaluate the structural orientation of the AZO thin films and ZnO NWs, the texture coefficients C hkl , representing the degree of preferred orientation of a given (hkl) plane within the crystalline structure, were calculated by the following equation: [START_REF] Consonni | Plasticity Induced Texture Development in Thick Polycrystalline CdTe: Experiments and Modeling[END_REF] 𝐶 %

, Ʃ , ( 1 )
where I hkl is the hkl peak intensity extracted from the XRD pattern, I 0,hkl is the reference hkl peak intensity from the 00-036-1451 file of the International Center for Diffraction Data (ICDD), and N is the number of peaks considered. In addition, the residual homogeneous strain inside the AZO thin films and ZnO NWs at the end of the fabrication process was estimated as follows:

𝜀 % 100 ( 2 )
where c o = 5.2066 Å is the theoretical c-lattice parameter of wurtzite ZnO according to the 00-036-1451 ICDD file. The actual c-lattice parameter value was deduced from the 002 diffraction peak position by using Bragg's law equation:

𝜆 2𝑑 sin 𝜃 ( 3
)
where λ is the wavelength of the Kα1(Cu) source equal to 0.15406 nm, θ is the Bragg angle of the 002 diffraction peak, d is the spacing between the (002) planes and equal to half the c-lattice parameter in the wurtzite structure of ZnO.

Raman scattering spectra were recorded at room temperature using a Jobin Yvon/Horiba Labram spectrometer and the 488 nm excitation line of an Ar + laser. The cross-polarization was used in those Raman scattering measurements to reduce the signals of the silicon substrate. The optical transmittance of the ZnO NW array and AZO thin films deposited on quartz were analyzed using a Perkin Elmer Lambda 950 spectrometer. The AZO thin film resistivity was measured by Van der Pauw measurement method using a home-made station.

Piezoelectric measurements

The piezoelectric properties of ZnO NWs grown on AZO thin films and Si substrate were analyzed by PFM measurements using a Bruker Dimension Icon AFM equipped with a conductive tip (PtSi-NCH, Nanosensors). This tip has high spring constant (~43 N/m), which was employed to reduce the interference of the electrostatic effect during the PFM measurement. [START_REF] Bui | Morphology Transition of ZnO from Thin Film to Nanowires on Silicon and Its Correlated Enhanced Zinc Polarity Uniformity and Piezoelectric Responses[END_REF] Instead of using the contact PFM mode, our measurements were performed in the DataCube PFM mode. In this mode, the tip sequentially approached, touched the sample and withdrew when moving from one position to another. This is to avoid dragging the tip during the scanning, which can bend the NW resulting in contact failure between the tip and the sample. For each position, the contact duration was set at 80 milliseconds. During this time, a 5 V amplitude and 15 kHz frequency AC voltage was applied between the top and the bottom of the sample through the tip and the chuck of the AFM system. Due to the piezoelectric property, the ZnO NW was deformed with respect to the AC voltage. This deformation was recorded, giving the piezoelectric amplitude and phase signals corresponding to the piezoelectric coefficient and the polarity of the ZnO NW, respectively. [START_REF] Bui | Morphology Transition of ZnO from Thin Film to Nanowires on Silicon and Its Correlated Enhanced Zinc Polarity Uniformity and Piezoelectric Responses[END_REF] 3. Results

Structural properties and resistivity of AZO thin films

Since the AZO30, AZO20 and AZO10 thin films were used as substrates during the ZnO NW growth, they were also affected by the growth conditions in the PLI-MOCVD process. In the reactor chamber, AZO thin films were heated from room temperature to 700 °C at the beginning of the process and were cooled down at the end of the process in Ar atmosphere. When the DEZn and O 2 gas were introduced to the chamber for the ZnO NW growth, these AZO layers were also exposed to the O 2 gas while being heated at 700 °C for 10 minutes. The pressure inside the reactor chamber was maintained at 3 mbar. This means the AZO layers were annealed throughout the NW growth process, which can affect their properties. To test the structural and electrical properties of AZO thin films after the growth, we repeated the growth process on the as-grown AZO layers using the similar conditions, but without injecting the DEZn precursor. These samples are denoted as annealed AZO thin films. The properties of those annealed AZO layers were measured and compared with the as-grown AZO thin films. Figure 2 shows the FESEM images of as-grown and annealed AZO thin films.

The top-view images present different morphologies of AZO thin films when the Al dopant concentration is changed, while the cross-sectional-view images show that all thin films have a similar thickness of around 180 nm since the number of cycle was adjusted for every ALD growth. Thus, the effect of AZO thickness on its properties is decoupled from the effect of Al dopant concentration. The incorporation of Al dopants inside the lattice of AZO thin films was confirmed and measured by parallel angular XPS (see Figure S1). The Al atomic concentrations of AZO30, AZO20 and AZO10 thin films are found to be 1.1, 2.9 and 6.7%, respectively. patterns of AZO30 and AZO 20 thin films, it can be seen that the 002 diffraction peak is the most intense one as compared to other ZnO diffraction peaks, revealing that their structures are preferably oriented along the polar c-axis. On the other hand, the XRD pattern of AZO10 thin film shows less intense and broader diffraction peaks, expressing a partially crystallized structure. This is due to the fact that a large amount of Al atoms is incorporated into the AZO10 thin film, which causes a large distortion of ZnO lattice and leads to the degradation of its crystal structure. [START_REF] Luka | The Uniformity of Al Distribution in Aluminum-Doped Zinc Oxide Films Grown by Atomic Layer Deposition[END_REF][START_REF] Wu | Optical and Electrical Properties of Al-Doped ZnO Thin Films by Atomic Layer Deposition[END_REF] To evaluate the degree of preferred orientation along the polar c-axis of the different AZO thin films, the 002 texture coefficient were calculated and reached 26.5, 68.2 and 87.8% for AZO10, AZO30 and AZO20 thin films, respectively.

Comparing to the XRD patterns of as-grown AZO thin films in Figure 3a, the XRD patterns of annealed AZO thin films in Figure 3b are similar. This comparison along with the FESEM images in Figure 2 shows that the annealing during the PLI-MOCVD process has insignificant effect on the structural properties of AZO thin films. The residual homogeneous strain of as-grown and annealed AZO thin films was also evaluated based on the position of the 002 diffraction peaks in the XRD patterns. [START_REF] Bui | Morphology Transition of ZnO from Thin Film to Nanowires on Silicon and Its Correlated Enhanced Zinc Polarity Uniformity and Piezoelectric Responses[END_REF] The residual homogeneous strain is found to slightly increase from -0.56, -0.83 and -1.77% to -0.67, -0.99 and -2.05% in AZO30, AZO20 and AZO10 thin films, respectively, following the annealing during the PLI-MOCVD process. This could be due to the adsorption of oxygen during the annealing at high temperature inside the PLI-MOCVD chamber, which have been reported to create defects or to induce a local segregation of Al atoms. [START_REF] Lin | The Properties of Heavily Al-Doped ZnO Films before and after Annealing in the Different Atmosphere[END_REF][START_REF] Wang | Effects of Doping and Annealing on Properties of ZnO Films Grown by Atomic Layer Deposition[END_REF] Different from the structural properties, the electrical measurements show that the electrical resistivity of AZO30 and AZO20 thin films is increased by 1 order of magnitude (from 0.6 -0.7 x 10 -3 to around 5 x 10 -3 Ω.cm) after the annealing. Since the AZO thin films are annealed under O 2 atmosphere, this could be due to i) the adsorption of oxygen at grain boundaries trapping free electrons, [START_REF] Wang | Effects of Doping and Annealing on Properties of ZnO Films Grown by Atomic Layer Deposition[END_REF] or to ii) the local segregation of Al atoms reducing the concentration of shallow donors formed by Al Zn defects as well as the charge carrier density. [START_REF] Lin | The Properties of Heavily Al-Doped ZnO Films before and after Annealing in the Different Atmosphere[END_REF] On the other hand, the electrical resistivity of AZO10 thin film is found to be around 5.5 x 10 -3 Ω.cm and it remains the same after annealing. This could be due to the fact that the charge carriers inside the AZO10 thin film had been trapped even before annealing due to its partially crystallized structure. Nevertheless, the electrical resistivity of AZO thin films after annealing is still decent and comparable to the electrical resistivity of the heavily doped Si substrate, which is around 2 x 10 -3 Ω.cm.

Morphology of ZnO NWs grown on AZO thin films

The FESEM images in Figure 4 show that the ZnO NWs formed on Si substrate, AZO30 and AZO20 thin films are well-aligned vertically, but not on the AZO10 thin film. In our previous result, [START_REF] Bui | Morphology Transition of ZnO from Thin Film to Nanowires on Silicon and Its Correlated Enhanced Zinc Polarity Uniformity and Piezoelectric Responses[END_REF] the ZnO NW formation on Si substrate was found to be a non-epitaxial growth. In that growth, a very thin polycrystalline ZnO layer was formed at the onset of the nucleation process, followed by the prevalence of the growth along the polar c-axis over the other growth directions at high growth temperature, leading to the vertical ZnO NW growth. In contrast, the ZnO NW formation on the AZO layer proceeds through a homogeneous epitaxial growth, where the direction of the initial layer strongly affects the direction of the structure grown on top of it. Since the AZO30 and AZO20 thin films exhibit a strong growth texture along the polar c-axis as shown by the XRD patterns in Figure 3, ZnO NWs grown by PLI-MOCVD on these thin films are also vertically developed. In contrast, the weak growth texture of the AZO10 thin film influences the growth direction of ZnO NWs grown by PLI-MOCVD that leads to its random inclination. A similar observation was reported in ref. [START_REF] Pung | Preferential Growth of ZnO Thin Films by the Atomic Layer Deposition Technique[END_REF] , where ZnO NWs were grown on AZO templates by chemical vapor deposition process. The length and diameter of ZnO NWs were measured from the cross-sectional FESEM images and are presented in Table 1. The length of ZnO NWs grown on the different AZO thin films and on Si substrate is above 1 µm and similar, but their diameter when grown on the AZO10 thin film is notably larger. As the ZnO NWs on the AZO10 thin film were grown with different inclination angles, these NWs can cross and merge into bigger NWs. These results demonstrate that the surface of AZO thin films have a strong impact on the nucleation process of ZnO, which in turn affects the formation process of NWs in the subsequent growth step. Interestingly, we also performed a comparison between the ZnO NW growth by PLI-MOCVD process on the Zn-polar ZnO single crystal (from Crystec) and on the AZO20 thin film (see

Figure S2

). The result shows that the ZnO NW arrays grown on the AZO20 thin film oriented along the polar c-axis achieves a vertical alignment that is similar to the ZnO NW arrays grown on the ZnO single crystal, which is a more expensive substrate offering less integration perspectives for piezoelectric devices. The 002 texture coefficients and residual homogeneous strains of ZnO NWs were also extracted from the XRD patterns (see Figure S3). The 002 texture coefficients of ZnO NWs on the Si substrate, AZO30 and AZO20 thin films are higher than 99 %. This value on the AZO10 thin film is also higher than 97%. This confirms that the ZnO NWs were grown by PLI-MOCVD along the polar c-axis. The residual homogeneous strains of ZnO NWs are close to 0 despite the fact that their lattice parameters are expected to slightly differ from the one of AZO thin films, indicating the efficient strain relaxation process originating from the NW geometry.

Structural and optical properties of ZnO NWs/AZO thin film structure

The comparison of the Raman spectra of the as-grown and annealed AZO thin films and of ZnO NWs was also carried out (see Figure S4). The Raman spectra of AZO thin films before and after annealing are similar, which again shows no evidence of change in their structure. In contrast, the remarkably high intensities of the E 2 low and E 2 high lines on the Raman spectra of ZnO NWs emphasize their superior crystallinity as compared to AZO thin films. Those Raman spectra also show that the strong signals of C-C bonds caused by carbon impurities [START_REF] Bui | Morphology Transition of ZnO from Thin Film to Nanowires on Silicon and Its Correlated Enhanced Zinc Polarity Uniformity and Piezoelectric Responses[END_REF] only appear on ZnO NWs grown by PLI-MOCVD process, but not in AZO thin films grown by ALD despite the fact that the DEZn chemical precursor was used as a source of Zn in both techniques. This indicates that those carbon impurities are mostly removed after the ALD process and hence they do not contribute to the high electrical conductivity of AZO thin films.

The ZnO NW growth by PLI-MOCVD was also performed on the AZO20 thin film, which was deposited on quartz substrate by ALD. The optical transmittance is presented in Figure 6. It is seen that the optical transmittance decreases after the ZnO NWs were grown on the AZO20 thin film, as compared to the as-grown AZO20 thin film. However, the ZnO NWs/AZO20 thin film structure still has a high average optical transmittance in the range of 400 -700 nm, which is around 81.2%. For comparison, ZnO nanorods grown on ITO-coated polyethersulfone (PES) substrate were reported in ref. [START_REF] Choi | Mechanically Powered Transparent Flexible Charge-Generating Nanodevices with Piezoelectric ZnO Nanorods[END_REF] , showing an optical transmittance varying from 60 to 80% in the range of 400 -700 nm. A transparent piezoelectric touch sensor based on ZnO NWs/BaTiO layer with carbon nanotubes-silver NWs as an electrode was developed in ref. [START_REF] Kang | Fully Flexible and Transparent Piezoelectric Touch Sensors Based on ZnO Nanowires and BaTiO3-Added SiO2 Capping Layers[END_REF] , for which the optical transmittance is of 81% at 550 nmwavelength. This shows that the present ZnO NWs/AZO20 thin film structure is highly suitable for visible-blind and transparent optical applications.

Piezoelectric responses of ZnO NWs on AZO thin films

The PFM measurements were performed on ZnO NWs grown on the AZO thin films and Si substrates using 2 setups. In the 1 st setup, the samples were in contact with the chuck of the AFM-PFM system (Figure 7a). The voltage was applied directly on the heavily doped Si substrate, through the AZO layer at the bottom and the conductive tip at the top. In this setup, the heavily doped Si substrates were used as the bottom electrodes. To verify that our AZO thin films are able to be used as bottom electrodes for the piezoelectric applications, a 2 nd setup was used for the PFM measurement. In this 2 nd setup, the heavily doped Si substrate was electrically isolated with the chuck by an empty plastic box placed between them (Figure 7b). The voltage was applied on the AZO layer through a copper (Cu) tape. Thus, the voltage was applied directly to the AZO layer instead of indirectly through the Si substrate. Then, datacube PFM measurement was performed. Figure 8 shows the topography, piezoelectric amplitude and phase images of ZnO grown on Si substrate and AZO thin films recorded by datacube PFM measurement with the 1 st setup. In these images, the piezoelectric amplitude is proportional to the piezoelectric coefficient, while the phase indicates the polarity of the ZnO structures. [START_REF] Bui | Morphology Transition of ZnO from Thin Film to Nanowires on Silicon and Its Correlated Enhanced Zinc Polarity Uniformity and Piezoelectric Responses[END_REF] Similar to our results shown in ref. [START_REF] Bui | Morphology Transition of ZnO from Thin Film to Nanowires on Silicon and Its Correlated Enhanced Zinc Polarity Uniformity and Piezoelectric Responses[END_REF] , the phase responses of ZnO NWs grown by PLI-MOCVD are positive indicating the Zn-polarity (Figures 8i-l). The negative phase response comes from the artifacts generated when the AFM tip scans on the void between NWs. A data treatment was carried out to remove these artifact signals. In this data treatment, the data points with phase value > 50° were kept, while other data points were removed. Figures 9a-d shows the amplitude histograms after data treatment of ZnO NWs grown on the Si substrate and AZO thin films measured in the 1 st setup, where the voltage was applied through the Si substrate and the AZO layer. The results reveal that while the amplitude is varied from 0 to 37 pm on all NW samples, their amplitude distributions are different. In the histogram of NWs grown on Si substrate (Figure 9a), the piezoelectric amplitude with the highest count, namely most frequent value of the distribution (the mode), is around 15 -19 pm. Interestingly, this mode value of NWs grown on all three AZO layers is higher than on Si substrates, which is around 23 -27 pm (Figures 9b-d). The higher amplitude of NWs grown on AZO thin films compared to NWs grown directly on Si substrate is also illustrated by brighter domains shown in their piezoelectric amplitude images (Figures 8e-h).

Since the amplitude of applied voltage is 5 V, the piezoelectric coefficient d 33 can be estimated as lying in the ranges of 3 -3.8 pm/V for ZnO NWs grown directly on Si substrate, and of 4.6 -5.4

pm/V for ZnO NWs grown on AZO thin films. These piezoelectric coefficient d 33 measured in the present ZnO NWs are still moderate as compared to other reports, where they lie in the range from 9.9 to 44.3 pm/V as shown in refs. [START_REF] Christman | Piezoelectric Measurements with Atomic Force Microscopy[END_REF][START_REF] Zhao | Piezoelectric Characterization of Individual Zinc Oxide Nanobelt Probed by Piezoresponse Force Microscope[END_REF][START_REF] Ghosh | Growth Mechanism of ZnO Nanostructures for Ultra-High Piezoelectric D33 Coefficient[END_REF] This could be due to the presence of impurities that were incorporated into ZnO NWs during the PLI-MOCVD growth, which screened the piezoelectric response.

Among AZO layers, the piezoelectric amplitude histogram on AZO10 thin film has a broad distribution, which stretches to the low piezoelectric amplitude value (Figure 9d). Correspondingly, the mode value in the histogram of NWs on AZO10 thin film consists of 30.9 % of its distribution, while it is 48.2 % on AZO20 and AZO30 thin films. This can be explained by the randomly inclined NWs on AZO10 thin film. When the AFM tip approached the NW on AZO20 and AZO30 thin films during the datacube PFM measurement, it was in contact with the NW tip and the applied electric field direction coincided with the polar c-axis of the NWs thanks to their well-aligned NW array. In contrast, since there are many inclined NWs on AZO layer, the AFM tip can touch the NWs at their sidewall. At that position, the piezoelectric measurement was carried out on the ZnO semi-polar plane instead of the polar plane, resulting in the lower piezoelectric amplitude.

Similarly, the datacube PFM measurements were performed on ZnO NWs grown on the AZO thin films with the 2 nd setup, where the bottom electrical contact only went through the Cu tape and AZO layer while the Si substrates were isolated. The data treatment was also applied to remove the artifact signals at the void between NWs. Their piezoelectric amplitude histograms were shown in 9b-c). The amplitude histogram of ZnO NWs on the AZO10 thin film measured in the 2 nd setup (Figure 9g) also has a broad distribution compared to the 1 st setup (Figure 9d) due to the inclined NWs, but it is shifted to a lower value.

Discussion

To have an overview, the average piezoelectric amplitude of all ZnO NWs measured using the 1 st and 2 nd experimental setups was calculated and shown in Figure 10. In the 1 st setup, the average piezoelectric amplitude value is of 19.4 pm for ZnO NWs grown directly on Si substrate, while it is of 23.2, 23.4 and 20.7 pm for ZnO NWs grown on the AZO30, AZO20 and AZO10 thin films, respectively. In the 2 nd setup, this value is of 23.7, 22.4 and 17.6 pm for ZnO NWs grown on the AZO30, AZO20 and AZO10 thin films, respectively. It can be seen that the piezoelectric amplitude is higher on ZnO NWs grown on the AZO thin films compared to those grown directly on Si substrate.

Since all the NWs were grown simultaneously on the Si substrate and AZO thin films in the MOCVD chamber, the difference in the piezoelectric amplitude among samples was not caused by the growth atmosphere. Besides, the XRD patterns in Figure 5 show that the ZnO NWs on Si substrate have a very high polar c-axis orientation similar to the ZnO NWs on other AZO thin films. In detail, the ZnO NWs on Si substrate exhibit the highest 002 texture coefficient (99.9%), followed by the ZnO NWs on AZO20 (99.7%), AZO30 (99.2%) and AZO10 thin films (97%), as shown in Figure S3.

Although a higher c-axis orientation typically leads to a larger piezoelectric amplitude, the higher piezoelectric amplitude of ZnO NWs grown on AZO thin films compared those grown directly on Si substrate as shown in demonstrated that the piezoelectric output was significantly increased by two ZnO layers containing different dopants. [START_REF] Pradel | Solution-Derived ZnO Homojunction Nanowire Films on Wearable Substrates for Energy Conversion and Self-Powered Gesture Recognition[END_REF] The p-Si/ZnO/n-AZO heterostructure was also demonstrated by G. Li et al.. [START_REF] Li | Characterization of Impact Ionization Coefficient of ZnO Based on a P-Si/i-ZnO/n-AZO Avalanche Photodiode[END_REF] In our work, a P-N junction formed between the p-doped Si-substrate and the ZnO NWs could lead to a higher piezoelectric amplitude compared to ZnO/AZO junction, but the present experimental results

show the opposite trend. The other factor that could also affect the results is the dimensions of NWs.

For instance, the NWs grown on AZO thin films exhibit a slightly greater length (Table 1), leading to a more effective impact of surface traps depleting the NW from its surface and thus enhancing the piezoelectric performance. [START_REF] Lopez Garcia | Dimensional Roadmap for Maximizing the Piezoelectrical Response of ZnO Nanowire-Based Transducers: Impact of Growth Method[END_REF][START_REF] Jalabert | Investigation of the Diameter-Dependent Piezoelectric Response of Semiconducting ZnO Nanowires by Piezoresponse Force Microscopy and FEM Simulations[END_REF][START_REF] Garcia | Length and Polarity Dependent Saturation of the Electromechanical Response of Piezoelectric Semiconducting Nanowires[END_REF] Conversely, the NWs on the AZO10 thin film are notably larger than others, in this case, the surface traps induced depletion is less effective resulting in a decreased piezoelectric performance. [START_REF] Jalabert | Investigation of the Diameter-Dependent Piezoelectric Response of Semiconducting ZnO Nanowires by Piezoresponse Force Microscopy and FEM Simulations[END_REF] Moreover, the piezoelectric amplitude of ZnO NWs grown on AZO thin films was also measured in the 2 nd setup where the Si substrates were electrically isolated, and compared with their amplitude measured in the 1 st setup where the applied voltage went through the Si substrate and AZO thin film (Figure 7). The piezoelectric amplitude of ZnO NWs grown on the AZO30 and AZO20 thin films is similar in both setups (Figures 9b-c, e-f and Figure 10), demonstrating that an efficient electrical contact between the copper tape and AZO layer was established. This also indicates that those AZO thin films have a good electrical conductivity to be used as an electrode in piezoelectric applications. In contrast, the piezoelectric amplitude of ZnO NWs on the AZO10 thin film measured in the nd setup is lower compared to the 1 st setup (Figures 9d, g and Figure 10). While the electrical resistivity of the AZO10 thin film is similar to the electrical resistivity of the AZO20 and AZO30 thin films after the NW growth process (around 5 x 10 -3 Ω.cm), the reason could be due to the poor electrical contact between the copper tape and partially crystallized AZO10 thin film. This could lead to a drop of the applied voltage at the bottom electrode and hence a lower measured piezoelectric amplitude of NWs on the AZO10 thin film. This result shows that a good electrical contact is important for piezoelectric devices. Furthermore, the more uniform and higher average piezoelectric amplitude values of ZnO NWs on the AZO30 and AZO20 thin films suggest that they can have better piezoelectric performance.

Conclusion

In summary, we have demonstrated the AZO thin film deposition by ALD, followed by the ZnO NW growth by PLI-MOCVD process. By modifying Zn/Al precursor cycle ratio in ALD process, the Al dopant concentrations of AZO thin films have been varied from 1.1 to 6.7%. Simultaneously, the structural orientations of these AZO thin films have also been changed, which have strongly influenced the subsequent growth direction of ZnO NWs. As a consequence, the vertically aligned ZnO NW arrays have been formed on the highly c-axis oriented AZO30 and AZO20 thin films, while the randomly inclined ZnO NWs have been grown on the partially crystallized AZO10 thin film. This has in turn affected the piezoelectric amplitude of the ZnO NW arrays. Among the NW arrays grown on AZO thin films, the NW arrays grown on the highly c-axis oriented AZO thin films have more uniform and higher piezoelectric amplitude compared to those grown on the partially crystallized AZO thin film. Interestingly, the PFM measurements have also revealed that the piezoelectric amplitude of ZnO NWs grown on the AZO thin film are higher compared to those grown directly on Si substrate.

The reason could be due to a depletion layer formation at the AZO layer/ZnO NW interface, which can reduce the free electron movement inside ZnO NWs, leading to the increase the piezoelectric performance. The highest average piezoelectric coefficient d 33 is achieved on ZnO NWs grown on the highly c-axis oriented AZO30 and AZO20 thin films, which is at around 4.5 -4.7 pm/V. These results

show that the ZnO NW piezoelectric performance is significantly affected by the properties of the AZO thin film used as a growth platform, which can finely be optimized during the ALD process.

Moreover, the average optical transmittance of 81.2% of the quartz substrate/AZO thin film/ZnO NW structure in the visible light region shows that they are relevant candidates for optoelectronic devices.

The combination of these materials and of the ALD and MOCVD techniques that can be extended to industrial scale production show a high potential for developing eco-friendly mechanical energy transducers that are suitable for energy harvesting and sensing applications.

Associated Content

Supporting Information

Average concentration of Al atoms inside the as-grown AZO30, AZO20 and AZO10 thin

Figure 1 :

 1 Figure 1: A schematic of Si substrate/AZO thin film/ZnO NW structure and their synthesis processes.

Figure 2

 2 also shows that there is no significant change in the morphology of annealed AZO thin films after the PLI-MOCVD process as compared to the as-grown AZO thin films.

Figure 2 :

 2 Figure 2: Top-view (left) and cross-sectional-view (right) FESEM images of (a) as-grown AZO30, (b) asgrown AZO20, (c) as-grown AZO10, (d) annealed AZO30, (e) annealed AZO20, and (f) annealed AZO10 thin films.

Figure 3 :

 3 Figure 3: XRD patterns of (a) as-grown and (b) annealed AZO thin films. The intensity was plotted in logarithmic scale.

Figure 4 :

 4 Figure 4: Top-view (left) and cross-sectional-view (right) FESEM images of ZnO NWs grown by PLI-MOCVD on (a) Si substrate, (b) AZO30, (c) AZO20 and (d) AZO10 thin films.

Figure 5a shows

  Figure5ashows the XRD patterns of ZnO NWs grown on the Si substrate and AZO thin films. Besides the diffraction peaks of Si substrate, other diffraction peaks are attributed to the ZnO wurtzite structure, according to the ICDD file labelled 00-036-1451. In all samples, the 002 diffraction peak exhibits a significantly higher intensity compared to other diffraction peaks, indicating that ZnO NWs are grown along the polar c-axis during the PLI-MOCVD process. It is also worth noticing in Figure5bthat most of the diffractions peaks exhibit two components: the one at higher θ value is the diffraction peak assigned to the AZO thin film grown by ALD, and the other one at lower θ value is the diffraction peak attributed to the ZnO structure formed by MOCVD. In Figure5a, the XRD pattern of ZnO NWs grown on the AZO10 thin film shows many different diffraction peaks. The 104,

Figure 5 :

 5 Figure 5: (a) XRD patterns of ZnO NWs grown by PLI-MOCVD on Si substrate and AZO thin films; (b) Zoom-in in the area of interest ranging from 30 to 40° in the XRD patterns. The intensity was plotted in logarithmic scale.

Figure 6 :

 6 Figure 6: Optical transmittance of AZO20 thin film and ZnO NWs/AZO20 thin film grown on quartz substrate. The AZO20 thin film was first grown on quartz by ALD, and the ZnO NWs were then grown on the AZO20 thin film by PLI-MOCVD.

Figure 7 :

 7 Figure 7: Schematic of the setups for PFM measurements. (a) In the 1 st setup, the voltage was applied to the ZnO NW array through the heavily doped Si substrate and AZO layer. (b) In the 2 nd setup, the voltage was applied to the ZnO NW array through a Cu tape and the AZO layer.

Figure 8 :

 8 Figure 8: Topography of ZnO NWs on (a) heavily doped Si substrate, (b) AZO30, (c) AZO20, and (d) AZO10 thin films. Piezoelectric amplitude of ZnO NWs on (e) heavily doped Si substrate, (f) AZO30, (g) AZO20, and (h) AZO10 thin films. Piezoelectric phase of ZnO NWs on (i) heavily doped Si substrate, (j) AZO30, (k) AZO20, and (l) AZO10 thin films. The PFM measurements were performed in the 1 st setup.

Figures

  Figures 9e-g. The results show that the amplitude histograms of ZnO NWs grown on the AZO30 and AZO20 thin films in the 2 nd setup (Figures9e-f) are similar to their histograms in the 1 st setup (Figures9b-c). The amplitude histogram of ZnO NWs on the AZO10 thin film measured in the 2 nd

Figure 9 :

 9 Figure 9: Piezoelectric amplitude histogram after data treatment with the 1 st setup of ZnO NWs grown on (a) heavily doped Si substrate, (b) AZO30, (c) AZO20 and (d) AZO10 thin films. Piezoelectric amplitude histogram after data treatment with the 2 nd setup of ZnO NWs grown on (e) AZO30, (f) AZO20 and (g) AZO10 thin films.

Figures 9

 9 and 10 indicates that the introduction of the AZO layer has a more significant impact on the piezoelectric amplitude of ZnO NWs, while a minor difference in the texture coefficient has little effect.Regarding the electrodes, because the electrical resistivity of Si and AZO thin films are similar and of around 2 -5 x 10 -3 Ω.cm, the applied voltage at the bottom electrical contact should be the same for all samples during the PFM measurement. Regarding the effect of heterostructures on the piezoelectric performance, Q. Wang et al. have shown that free electrons can be trapped at ZnO-CuO heterojunction, resulting in enhancing the piezoelectric output.[START_REF] Wang | Improvement in Piezoelectric Performance of a ZnO Nanogenerator by Modulating Interface Engineering of CuO-ZnO Heterojunction[END_REF] Similarly, K. Pradel et al.

Figure 10 :

 10 Figure 10: Mean piezoelectric amplitudes after data treatment of ZnO NWs grown by PLI-MOCVD on heavily doped p-type Si substrate, AZO30, AZO20 and AZO10 thin films.

  films measured by XPS (Figures S1); FESEM images of the ZnO NWs grown by PLI-MOCVD on Zn-polar ZnO substrate and AZO20 thin film (Figures S2); 002 texture coefficient and residual homogeneous strain of ZnO NWs grown by PLI-MOCVD on Si substrate and AZO thin films (Figures S3); Raman scattering spectra of as-grown AZO thin films grown by ALD, annealed AZO thin films grown by ALD, and ZnO NWs grown by PLI-MOCVD on Si substrate and AZO layers (Figure S4)

  31.8, 34.4, 36.3, 47.5, 56.6, 62.9, and 72.6°, according to the International Center for Diffraction Data (ICDD) file labelled 00-036-145. No peaks of Al-related compound are detected on these XRD patterns, indicating that Al atoms only participate as dopants inside AZO thin films. On the XRD

Table 1 :

 1 Lengths and diameters of ZnO NWs grown by PLI-MOCVD on Si substrate and AZO thin films.

	Sample	Length (nm)	Diameter (nm)
	ZnO NWs on Si	1029 ± 83	72 ± 10
	ZnO NWs on AZO30	1072 ± 92	77 ± 14
	ZnO NWs on AZO20	1174 ± 74	77 ± 13
	ZnO NWs on AZO10	1092 ± 63	95 ± 16

Acknowledgements

The authors are further grateful to Isabelle Gelard, Odette Chaix-Pluchery and Laurent Terrier, LMGP, Grenoble, France, for their assistance in FESEM, Raman spectroscopy and UV-Vis-NIR spectrophotometry, respectively.

Funding Sources

This work was financially supported by the French National Research Agency in the framework of the "Investissements d'avenir" program (ANR-15-IDEX-02) through the project CDP NEED. Q.C.B. held a doctoral fellowship from the project CDP NEED. The authors further acknowledge the financial support from the French National Research Agency through the project SCENIC (ANR-20-CE009-0005) and the CNRS Renatech Network through the "Plateforme Technologique Amont" in a cleanroom environment. This research has also benefited from some of the characterization equipments of the Grenoble INP-CMTC platform and from the facilities and expertise of the OPE)N(RA characterization platform of FMNT (FR 2542, fmnt.fr) supported by CNRS, Grenoble INP and UGA.

Author Information

Corresponding Authors

Vincent Consonni -Université Grenoble Alpes, CNRS, Grenoble INP, LMGP, F-38000 Grenoble, France;

Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

Notes

The authors declare no competing financial interest.


Claire Pascal

Sylvain Ferrant

Nemesio Rodriguez-Fernandez

Yann Kerr

Adrien Selles

Olivier Merlin

Indicator of flood-irrigated crops from SMOS and SMAP soil moisture products in southern India

Keywords: Soil moisture, SMOS, SMAP, Irrigation, Water Management, Rice Cropping, Regional Scale

Spaceborne L-band data have the potential to monitor flooded and irrigated areas. However, further studies are needed to assess in real cases the impact of flood-irrigated crops on SMOS and SMAP surface soil moisture (SSM) data. This paper demonstrates the ability of SMOS/SMAP SSM retrievals to quantify the fraction of flood-irrigated area at the seasonal scale and at a 25 km resolution in the Telangana State in southern India. Over irrigated areas, both SMOS level 3 (L3) SSM and SMAP L3 enhanced SSM products present a bimodal annual cycle, with a peak of SSM during the monsoon (wet) season corresponding to rainfall and irrigation, and a peak during the dry season due to irrigation activities solely. The second peak is absent or has a very small amplitude in areas where rice represents a small fraction (typically below 5-10%). More importantly, the amplitude of the second SSM peak is significantly correlated to the rice cover fraction within 25×25 km 2 pixels (R=0.81 for SMOS and 0.77 for SMAP), showing its potential to assess crop fraction and hence the water used for irrigation. The SMOS/SMAP L3 SSM peak during the dry period occurs several months before the harvest, constituting an indicator for rice stocks at the end of the season. However the irrigation signature is absent from the SMAP level 4 SSM product derived from the assimilation of SMAP brightness temperatures in a land surface model, which indicates that the data assimilation scheme is inefficient to restitute irrigation information.

I. INTRODUCTION

With the increase of agricultural production during the last century, irrigation has become the first consumer of freshwater, representing 70% of global freshwater withdrawals [START_REF] Foley | Solutions for a cultivated planet[END_REF]. The increase of soil moisture by irrigation practices also alters the water cycle [START_REF] Wada | Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources[END_REF]. Knowledge of irrigated land is hence crucial to manage the water resource and to ensure food security. It is also important to understand the impact of irrigation on the water cycle and climatology, and to participate to the development of hydrological models that account for irrigation in a realistic manner.

The dynamic mapping of inundated areas can be achieved with microwave radiometers thanks to the high sensitivity of the microwave brightness temperature (Tb) to open water. Such data are insensitive to clouds and hence allow continuous monitoring, in spite of having a lower spatial resolution than optical data. The Tb at various frequencies has been used to detect flooded pixels [START_REF] Rahman | Rapid Flood Progress Monitoring in Cropland with NASA SMAP[END_REF]- [START_REF] Fluet-Chouinard | Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data[END_REF] or to estimate an open water fraction within the microwave pixel by separating the contributions of land and water. Especially, Tb data from the multi-band Advanced Microwave Scanning Radiometer for EOS (AMSR-E) sensor [START_REF] Du | Implementation of satellite based fractional water cover indices in the pan-Arctic region using AMSR-E and MODIS[END_REF], [START_REF] Gouweleeuw | Space-based passive microwave soil moisture retrievals and the correction for a dynamic open water fraction[END_REF], the L-band Soil Moisture and Ocean Salinity (SMOS) mission [START_REF] Parrens | Mapping Dynamic Water Fraction under the Tropical Rain Forests of the Amazonian Basin from SMOS Brightness Temperatures[END_REF], and the L-band Soil Moisture Active Passive (SMAP) mission [START_REF] Du | Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat[END_REF] have been used at the 5 km and ≃40 km resolution for AMSR-E (89 GHz) and SMOS/SMAP, respectively. Note that higher resolutions can be achieved by downscaling the microwave data using disaggregation algorithms and ancillary data [START_REF] Du | Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat[END_REF], [START_REF] Parrens | High resolution mapping of inundation area in the Amazon basin from a combination of L-band passive microwave, optical and radar datasets[END_REF].

The particular sensitivity of the L-band (1.4 GHz) to water has been used to monitor the soil water content. Since 2010 and 2015 respectively, SMOS and SMAP satellite missions have provided surface soil moisture (SSM) estimates every 3 days at a ≃40 km resolution. L-band-derived SSM data have been proven to be sensitive to irrigation, in particular in heavily and flood irrigated areas [START_REF] Lawston | Irrigation Signals Detected From SMAP Soil Moisture Retrievals[END_REF], [START_REF] Escorihuela | Comparison of remote sensing and simulated soil moisture datasets in Mediterranean landscapes[END_REF], demonstrating their potential for irrigated area mapping and irrigation timing detection. Notably, several indicators have been identified to detect irrigation from the amplitude of SSM values in time series [START_REF] Lawston | Irrigation Signals Detected From SMAP Soil Moisture Retrievals[END_REF] and using the spatial relative difference within an area revealing the spatial distribution of irrigated sites [START_REF] Dari | Detecting and mapping irrigated areas in a Mediterranean environment by using remote sensing soil moisture and a land surface model[END_REF]. Also, irrigated areas can be detected by comparing the SSM retrievals with the SSM simulated by a land surface model that does not take irrigation into account: larger observed SSM values are attributed to irrigation [START_REF] Escorihuela | Comparison of remote sensing and simulated soil moisture datasets in Mediterranean landscapes[END_REF]- [START_REF] Kumar | Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes[END_REF]. Automatic discrimination of irrigated areas from other land types has also been achieved from SSM data with unsupervised classification algorithms [START_REF] Dari | Detecting and mapping irrigated areas in a Mediterranean environment by using remote sensing soil moisture and a land surface model[END_REF].

As a step further, L-band-derived SSM data have also been used to estimate the quantity of water used for irrigation [START_REF] Brocca | How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products[END_REF]- [START_REF] Jalilvand | Quantification of irrigation water using remote sensing of soil moisture in a semi-arid region[END_REF]. Especially, the SM2RAIN algorithm [START_REF] Brocca | Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data[END_REF] is based on the inversion of the soil water balance equation. This requires prior calibration during rainy periods, by assuming that there is no irrigation during those periods. Such an approach has been effective in quantifying irrigation water use over large irrigated areas and where irrigation and precipitation periods are distinct. However, SM2RAIN is not able to separate the contributions of rainfall and irrigation to the observed SSM dynamics [START_REF] Brocca | How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products[END_REF]. Moreover, its application to smaller and sparse irrigated areas would require disaggregated SSM data, which may not be available at the required spatio-temporal scales with a sufficient accuracy [START_REF] Peng | A review of spatial downscaling of satellite remotely sensed soil moisture[END_REF].

To this day, therefore, studies have mainly focused on the binary discrimination of irrigated and non-irrigated pixels from the SSM signals. However the microwave pixels (several tens of km) are generally much larger than the size of agricultural fields or even often the size of irrigation districts, and hence the above methods do not provide sub-pixel information about the portion of irrigated areas. In particular, further studies are needed to assess the ability of L-band-derived SSM to estimate the fraction of irrigated areas within SMOS and SMAP pixels, in the same way that the open fraction water can be estimated from Tb data. In this context, this paper aims to quantify the sensitivity of SMOS and SMAP SSM data to the percentage of irrigated rice within 25 km resolution (SMOS sampling grid) pixels. The study is undertaken over the Telangana State in southern India and for four years when field data are available (2016 to 2019 included). The reference data of rice fraction at the 25 km resolution are derived from an existing supervised classification algorithm [START_REF] Ferrant | Detection of Irrigated Crops from Sentinel-1 and Sentinel-2 Data to Estimate Seasonal Groundwater Use in South India[END_REF], [START_REF] Inglada | Operational High Resolution Land Cover Map Production at the Country Scale Using Satellite Image Time Series[END_REF] based on Sentinel-2 data and previously evaluated using ground measurements in the area.

II. STUDY AREA AND DATA A. Study area

The study focuses on the Telangana State in southern India (see Figure 1). Highly rural and irrigated (15% of the State area [START_REF] Pingle | Irrigation in Telangana: The Rise and Fall of Tanks[END_REF]), Telangana is dominated by a monsoon climate alternating with a wet and dry season. Monsoon rainfall occurs between July and October and ranges between 540 and 1300 mm a year with an average of 879 mm (Indian Meteorological Department, https://mausam.imd.gov.in/). Annual precipitation sustains generally two growing seasons of irrigated crops in a year, one during the wet season (from July to November) and one during the dry season (from January to April). Orchards, vegetables and maize are irrigated, but rice is by far the largest consumer of irrigation water in the area [START_REF] Surendran | Use of efficient water saving techniques for production of rice in india under climate change scenario: A critical review[END_REF]. Rice is flooded from early July until early September and from early January until early March in the wet and dry season respectively.

B. Data

This section presents the reference rice cover maps, SMOS/SMAP SSM data and other ancillary (vegetation index and rainfall) data used to interpret the results. All data were resampled (by simple averaging) on the same 25 km resolution SMOS grid.

1) Land cover maps: Reference land cover maps were produced from Sentinel-2 reflectances for wet and dry seasons from 2016 to 2019 separately on 8 Sentinel-2 tiles of 100×100 km 2 each at 10 m resolution. Sentinel-2 data were processed by the MAJA processing chain [START_REF] Hagolle | MAJA Algorithm Theoretical Basis Document[END_REF] which detects clouds, cloud and topographic shadows, and corrects reflectance levels for atmospheric phenomena (absorption by atmospheric gases and scattering by air molecules and aerosols). These images were downloaded from Theia data platform (https://www. theia-land.fr/). Rice cover maps are produced with the IOTA2 algorithm (Infrastructure pour l'Occupation des sols par Traitement Automatique Incorporant les Orfeo Toolbox Applications, https://framagit.org/iota2-project/iota2), that achieves a supervised multitemporal classification with a random forest algorithm on the time series of Sentinel-2 images interpolated at 10 days [START_REF] Inglada | Operational High Resolution Land Cover Map Production at the Country Scale Using Satellite Image Time Series[END_REF]. The land cover classifications in wet and dry seasons are made on images acquired between July and November and between January and April, respectively.

The samples used for learning and evaluation of the classification algorithm are field data acquired on several consecutive days during each season of each year. Field data consist in visual identification of homogenous land cover and their delimitation as polygons using a GPS to locate them [START_REF] Ferrant | Detection of Irrigated Crops from Sentinel-1 and Sentinel-2 Data to Estimate Seasonal Groundwater Use in South India[END_REF]. The performance of the rice cropping classification is evaluated with the F-score. The F-score is the harmonic mean of (i) the recall, i.e. the ability of the algorithm to identify a rice pixel, and (ii) the precision that measures the purity of the rice class. The rice class is generally deemed reliable with a F-score ranging from 75% to 92%. The interannual variability of the performances is linked to (i) the number of samples that varies between the years (262 to 1669) and (ii) the number of available Sentinel-2 images, which can significantly change during the wet season due to cloud coverage. In particular, the maps produced for the wet seasons of 2016 and 2017 are not used in this study because of their poor performance (F-score below 20%). Figure 1 shows the number of rice occurrences at the 10 m resolution during the 6 seasons when land cover maps are available.

The seasonal rice cover fraction is then estimated within each 25 km resolution SMOS grid pixel by averaging all 10 m pixels.

2) SMOS: The SMOS mission was launched in November 2009 and has a revisit time of 3 days at the Equator. The SMOS satellite carries an interferometric radiometer working at L-band. The data used for this study are the monthly level 3 (L3) SSM (L3SM RE07) in the first 5 centimeters of soil, provided by the Centre Aval de Traitement des Données SMOS (CATDS, https://www.catds.fr/) [START_REF] Al Bitar | The global SMOS Level 3 daily soil moisture and brightness temperature maps[END_REF]. The data have a ≃40 km resolution on average but are distributed on the 25 km resolution EASE2 grid [START_REF] Brodzik | EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets[END_REF] for both ascending and descending orbits. In this study we use the monthly average SSM of both orbits.

3) SMAP: The SMAP satellite, launched in January 2015, carries an L-band passive microwave radiometer. It provides SSM estimates at ≃40 km resolution with a revisit time of 3 days at the Equator. The data used for this study are the enhanced L3 dataset (L3E) provided on a 9 km resolution grid and obtained by exploiting the oversampling of the antenna overpasses. In this study we use the average SSM of both orbits. We also use the SMAP level 4 (L4) SSM data which are obtained by assimilating the SMAP Tb in the NASA Catchment Land surface Model (CLM) using an ensemble Kalman filter [START_REF] Reichle | Level 4 Surface and Root Zone Soil Moisture (L4 SM) Data Product[END_REF]. The model describes the vertical transfer of soil moisture between the surface and root zone reservoirs, and provides fields of SSM and root zone soil moisture globally at 9 km resolution every 3 hours. The model is driven with observation-based surface meteorological forcing data, including precipitation, but does not account for irrigation activities. We use both L3 and L4 SSM data aggregated at the monthly scale and averaged within the 25 km pixels of the SMOS grid.

4) MODIS NDVI: The monthly NDVI (Normalized Difference Vegetation Index) allows monitoring the state of vegetation at a temporal scale finer than that of the seasonal land cover maps. We use the monthly NDVI of MODIS (Moderate-Resolution Imaging Spectroradiometer) sensor aboard Terra and Aqua satellites (launched in 1999 and 2002, respectively), at 1 km resolution (MOD13A3v006) and averaged within the 25 km pixels of the SMOS grid.

5) GPM IMERG rainfall:

The Integrated Multi-satellitE Retrievals algorithm provides a rainfall product that combines information from the Global Precipitation Measurement mission (2014-present). We use monthly rainfall rates, provided at a resolution of 0.1°and resampled (bilinear resampling) on the 25 km resolution SMOS grid.

III. RESULTS AND DISCUSSION

A. SSM dynamics over contrasted areas

The sensitivity of L-band sensors to irrigation is illustrated by the comparison of SMOS/SMAP SSM time series on three contrasted 25×25 km 2 pixels, numbered from 1 to 3 (see Figure 1): 1) a heavily irrigated one (from 10 to 60% of rice cover) supplied with water by the irrigation systems downstream of large dams, 2) an upstream irrigated area where rice sowing is limited by the lack of water availability, and 3) a pixel with a dominant forest cover. Figure 2 shows the time series of 25 km resolution SMOS L3, SMAP L3E and SMAP L4 SSM monthly anomalies (obtained by subtracting the temporal average of SSM values between 2016 and 2019 pixelwise) averaged within each 25×25 km 2 pixel. The percentage of rice cover is shown for wet (large bands) and dry (thin hatched bands) seasons. The monthly NDVI indicates the crop/vegetation growth at higher temporal resolution.

In heavily irrigated areas (as in pixel 1), the SSM retrieved from SMOS and SMAP sensors has a bimodal annual cycle. During the wet season, the first peak of SSM is correlated with the precipitation, and the contribution of irrigation to SSM cannot be easily disentangled. During the dry season, SMOS and SMAP SSM show a systematic augmentation in the dry season, between December and March. The maximum SSM value of the second peak is reached generally in January or February, when rice crops are flooded. The absence of precipitation coinciding with this peak suggests an anthropogenic source. The peak of NDVI two months later, associated with crop growth, strengthens this interpretation.

In upstream irrigated areas (as in pixel 2), the rice cover is lower and rarely exceeds 20% because of the lack of water availability, particularly during the dry season. SSM still has a bimodal cycle, but with lower amplitude for the SSM peaks in the dry season (SSM anomaly of 0.05 m 3 /m 3 at most), while the NDVI presents a single annual peak.

By contrast, the SSM of non-irrigated areas (as in pixel 3) presents a single peak in the year during the wet season which has its origins in monsoon rainfall. The different behaviors of SSM dynamics over irrigated and not irrigated areas confirm the findings of [START_REF] Lawston | Irrigation Signals Detected From SMAP Soil Moisture Retrievals[END_REF] in the western United States.

Contrary to SMOS and SMAP L3 SSM, SMAP L4 SSM does not show a peak in the dry season in irrigated areas and seems correlated solely to rainfall. This corroborates the limitations of assimilation approaches in representing unmodeled processes [START_REF] Kumar | Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes[END_REF]. Two reasons can explain this result: first, an incorrect forcing of the model that integrates the contribution of rainfall but not irrigation to soil moisture, and second, the high dependency of assimilation results to the weights and uncertainties associated with observations and models.

B. Spatio-temporal analysis

At the scale of each 25 km resolution pixel, the amplitude of the SSM peak is generally correlated in time with the corresponding proportion of rice cultivated within the area. This is illustrated in Figure 2 on pixel 1, in which a small proportion of rice is sown during the 2016 dry season (11% of rice) due to a lack of available after a succession of dry years. This situation explains a low SSM peak amplitude (SSM anomaly of -0.05 m 3 /m 3 ). On the other hand, the heavy monsoon rainfall in September 2016 has replenished surface and groundwater that allowed a large rice cultivation in the following 2017 dry season (58% of rice for a SSM anomaly of 0.1 and 0.2 m 3 /m 3 for SMOS and SMAP respectively).

We characterize the amplitude of the SSM annual peaks by the maximum value of SSM anomaly between December and March (resp. May and November) in the dry (resp. wet) season. Table I reports the Pearson correlation coefficients between the amplitude of the 3 SSM datasets and the percentage of rice cover (obtained from land cover maps produced as explained in section II-B1) for the dry and wet seasons between 2016 and 2019. The last line presents the correlation coefficients for all years, cumulating both the spatial and temporal effects. Rice cover and SSM SMOS L3 and SMAP L3E show the same spatial pattern (as illustrated for the dry season of 2018 in figure 3a), resulting in spatial correlations close to 1 in Table I (0.81 and 0.77 on average for SMOS and SMAP L3, respectively). Correlations between rice cover and the SSM peak amplitude are weaker in the 2016 and 2019 dry seasons due to the low SSM peak amplitude caused by the low extent of rice planting in both exceptionally dry years. Correlations tend to be lower during the wet season because the SSM amplitude is due both to rainfall and irrigation. The spatial correlations with SSM SMAP L4 are much lower than with L3 SSM products.

To go further, we investigated the impact of rainfall during the wet season by removing the effect of rainfall on the SSM dynamics (using a simple correction of SSM based on a linear regression between SSM and rainfall). Interestingly, such a correction increases the correlation between the amplitude of SMOS SSM and the percentage of rice cover from 0.76 to 0.83 and from 0.65 to 0.77 for the wet season of 2018 and 2019, respectively. IV. CONCLUSION SMOS and SMAP L-band data have been used for irrigation mapping and irrigation water quantification because of their sensitivity to soil moisture and open water. Prior to retrieving SSM from Tb observations, the SMOS and SMAP algorithms remove the contribution of saturated surfaces using maps at a typical 1 km resolution (e.g. ECOCLIMAP) of permanent surface water. However, permanent surface water is scarce in Telangana: hundreds of large dams and ∼45,000 small reservoirs fill with each monsoon and empty with domestic and agricultural water use. These strong dynamics are now available in high-resolution global surface water products [START_REF] Pekel | High-resolution mapping of global surface water and its long-term changes[END_REF] but are not yet reflected in the SSM restitution algorithms. Therefore, studies are needed to evaluate in real cases the impact of irrigated crops on the SMOS and SMAP SSM data.

This study demonstrates for the first time the potential of SMOS and SMAP L3 SSM data to quantify the fraction of flood-irrigated crops within a 25 km pixel in Telangana, a State in southern India. Areas with a large fraction of cultivated rice present a clear bimodal annual cycle with two peaks of SSM. One peak occurs during the wet season and is associated with the combined effect of rainfall and irrigation, while the other peak occurs during the dry season and is due to irrigation alone. We identified a high correlation (R=0.81) between rice cover percentage and the amplitude of the SSM peak in the dry season, and a relatively lower correlation (R=0.68) in the wet season. The correlation is closer to 1 in the dry season than in the wet season because the spatial variability of rainfall disturbs the relationship between SMOS/SMAP SSM and irrigated areas in the wet season. Interestingly, if the effect of precipitation in the wet season is removed, the correlation reaches values (R=0.80) almost as high as those in the dry season. This approach could be used in combination with the knowledge of rice water needs and cultural practices to estimate the water used for irrigation.

Fig. 1 .

 1 Fig. 1. Overview of the study area within the Telangana state in India overlaid with the 25 km resolution SMOS sampling grid and the number of rice occurrences during the 6 seasons when land cover maps are available.

Fig. 2 .

 2 Fig. 2. Time series of monthly anomalies of SMOS and SMAP SSM (obtained by subtracting the temporal average of SSM values between 2016 and 2019 pixel-wise), GPM IMERG rainfall, MODIS NDVI, and seasonal land cover fraction (%) on three pixels of 25×25 km 2 . First axis: GPM IMERG rainfall (mm/month). Second axis: SMOS L3 (black line), SMAP L3E (solid dark red line) and SMAP L4 (dotted dark red line) SSM. Third axis: Land cover fraction (%) for wet (large bands) and dry (thin hatched bands) season. Fourth axis: MODIS NDVI (solid green line).

Fig. 3 .

 3 Fig. 3. (a) Maps of rice cover (%) and amplitude of the peak during the 2018 dry season for SMOS L3, SMAP L3E and SMAP L4 SSM (m 3 /m 3 ) (obtained by subtracting the temporal average of SSM values between 2016 and 2019 pixel-wise). (b) Scatterplot of rice cover and the SSM products. The linear regression fit to the data points is indicated by the red line.

TABLE I PEARSON

 I CORRELATION COEFFICIENTS BETWEEN RICE COVER (%) AND SSM FOR EVERY SEASON OF EACH YEAR OR FOR ALL YEARS ("ALL"). ALL SIGNIFICANT CORRELATIONS ARE ASSOCIATED WITH A P-VALUEBELOW 0.05.

	Season Year		SMOS L3	SMAP L3E	SMAP L4
			R	p-value	R	p-value	R	p-value
	Dry	2016	0.67 3.7e-19	0.58 1.7e-13	0.05	0.6
		2017	0.89 8.6e-47	0.77 2.4e-26	0.55 3.9e-12
		2018	0.86 1.5e-41	0.67 6.5e-18	0.36 1.5e-05
		2019	0.62 1.2e-15	0.71 3.8e-22	0.56 1.0e-12
		All	0.81 1.3e-107	0.77 1.6e-96	0.55 8.1e-18
	Wet	2018	0.76 4.8e-27	0.63 2.1e-16	0.44 6.9e-08
		2019	0.65 9.5e-18	0.56 1.1e-12	0.24 4.2e-3
		All	0.68 4.8e-38	0.55 7.1e-23	0.34 1.0e-08

ACKNOWLEDGMENTS

Field data for the production of land cover maps were surveyed with the help of the IFCGR (Indo-French Center for Groundwater Research), an Indo-French collaboration between the BRGM (Bureau des ressources géologiques et minières) and the NGRI (Indian National Geophysical Research Institute). Support from the Horizon 2020 ACCWA project (grant agreement n • 823965) in the context of Marie Sklodowska-Curie research and innovation staff exchange (RISE) program is acknowledged.