Alexandre Bouvet
email: alexandre.bouvet@cesbio.cnes.fr

Thuy Le Toan
email: thuy.letoan@cesbio.cnes.fr

Nguyen Lam-Dao

Thuy Le Toan

N Lam

Monitoring of the Rice Cropping System in the Mekong Delta Using ENVISAT/ASAR Dual Polarization Data

Keywords: Advanced) Synthetic Aperture Radar (ASAR), Mekong Delta, polarization ratio, rice mapping. I

The rice cropping system in Asia is undergoing major changes to cope with increasing demography and changing climate, making rice monitoring a critical issue. Past studies have demonstrated the use of C-band synthetic aperture radar (SAR) data to map rice areas. The methods were based on the temporal change of intensity backscattering coefficient of vertically or horizontally co-polarized data (VV or HH). In this paper, we assess the use of the HH/VV polarization ratio derived from Advanced SAR (ASAR) data from ENVISAT data for the production of rice paddy maps. The approach is based on past knowledge on the polarization behavior of rice canopy, i.e., VV backscattering is much lower than HH during a large part of the rice season, due to the attenuation of the wave by the vertical structure of the plants. The methodology is developed for the Mekong Delta, Vietnam, where a complex cropping pattern is found (one to three crops of rice per year). The approach includes a statistical analysis of the HH/VV distributions of rice and non-rice classes at different dates. The analysis results confirm that HH/VV can be used as classifier and point out the need for relevant speckle filtering prior to classification. A classification method is developed and applied to single-and multidate data sets. The methods are tested at one district of the province of An Giang and extended to the whole province. Comparisons of the mapping results to geographic-information-system land-use data and official agricultural statistics show very good agreement. The method will be further applied to the entire Mekong Delta.

significant impact on the global climate, since irrigated rice fields are among the major sources of methane (CH 4 ) emissions and because of the importance of the world rice area (1.57 million km 2 in 2007 [START_REF] Lam | FAOSTAT (Food and Agriculture Organization[END_REF]). To monitor changes in the rice production area and cultivation intensity, satellite remote sensing data constitute a unique tool which can provide timely and consistent spatial and temporal coverage needed at regional to global scales.

Among remote sensing methods, only radar imaging systems are not limited by cloud coverage in tropical and subtropical regions where most rice is grown. Using optical sensors, high temporal repeat frequency is required in order to have cloudfree observations. This could be done with medium-resolution (about 250 m-1 km) sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), VEGETATION, or Medium Resolution Imaging Spectrometer (MERIS). Investigations on the use of time series of vegetation and water indices (e.g., normalized difference vegetation index, enhanced vegetation index, and normalized difference water index) derived from VEGETATION [START_REF] Xiao | Observation of flooding and rice transplanting of paddy rice fields at the site Authorized licensed use limited to: IEEE Xplore[END_REF] and MODIS [START_REF] Xiao | Mapping paddy rice agriculture in southern China using multi-temporal MODIS images[END_REF]- [START_REF] Sakamoto | Spatio-temporal distribution of rice phenology and cropping systems in the Mekong Delta with special reference to the seasonal water flow of the Mekong and Bassac rivers[END_REF] have been carried out to map paddy rice agriculture in Asia. In [START_REF] Xiao | Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images[END_REF], the spatial distribution of paddy rice in South and Southeast Asia was reported using MODIS. Yet, ancillary information (cropping intensity) was needed to calculate the sown area. Furthermore, results in the Mekong Delta in [START_REF] Xiao | Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images[END_REF] are considered by the authors as erroneous, probably because the flood pattern disturbs the rice detection. In [START_REF] Xiao | Mapping paddy rice agriculture in southern China using multi-temporal MODIS images[END_REF], cropping systems could be identified in the Mekong Delta with MODIS data. However, prior identification of rice-e.g., by existing databases-is needed in order to remove confusion between rice and other vegetation types. Compared to optical data, radar data have the advantage to distinguish well-developed rice from water surfaces and other crops, because of the specific radar backscattering physics of inundated vegetation. The radar data have, in addition, higher spatial resolution (about 30 m), allowing observations with more details on the individual fields.

In terms of electromagnetic interaction mechanisms between radar waves and vegetation canopy, the radar backscatter can be approximated by the sum of three main components: the volume scattering, the scattering from the ground attenuated by the vegetation layer, and the multiple scattering between the volume and ground. The latter term is often negligible compared to the volume and ground scattering, with the exception of inundated fields, for which the volume-ground scattering becomes important. At C-band, theoretical studies using a coherent scattering model of rice canopy based on Monte Carlo simulations [START_REF] Le Toan | Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results[END_REF], [START_REF] Wang | Electromagnetic scattering model for rice canopy based on Monte Carlo simulation[END_REF] have demonstrated that the copolarized backscatter from rice fields covered by a water layer is dominated by the double bounce volume-ground interaction, with the dominant scatterers in the volume being the plant stems. Simulations of the temporal backscatter at HH and VV polarizations and at 23 • of incidence angle have shown a significant increase of the backscattering coefficient during the vegetative phase which lasts 40-70 days depending on the rice varieties. The backscatter then decreases slightly during the reproductive phase until harvest. This temporal behavior was effectively reported in a number of studies using ERS-1/2 and RADARSAT-1 data in Japan [START_REF] Kurosu | Monitoring of rice crop growth from space using the ERS-1 C-band SAR[END_REF], Indonesia [START_REF] Le Toan | Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results[END_REF], [START_REF] Ribbes | Rice field mapping and monitoring with RADARSAT data[END_REF], China [START_REF] Shao | Rice monitoring and production estimation using multitemporal RADARSAT[END_REF], India [START_REF] Chakraborty | Discrimination of rice crop grown under different cultural practices using temporal ERS-1 synthetic aperture radar data[END_REF], [START_REF] Chakraborty | Rice crop parameter retrieval using multi-temporal, multiincidence angle Radarsat SAR data[END_REF], the Philippines [START_REF] Chen | A neural network integrated approach for rice crop monitoring[END_REF], Thailand [START_REF] Aschbacher | Assessment of ERS-1 SAR data for rice crop mapping and monitoring[END_REF], [START_REF] Kaojarern | Assessment of multi-temporal radar imagery in mapping land system for rainfed lowland rice in Northeast Thailand[END_REF], and Vietnam [START_REF] Liew | Application of multitemporal ERS-2 synthetic aperture radar in delineating rice cropping systems in the Mekong River Delta, Vietnam[END_REF], [START_REF] Dao | The use of SAR data for rice crop monitoring, a case study of Mekong river delta-Vietnam[END_REF]. Backscatter was found increasing by more than 10 dB at HH and VV from the beginning of the growth cycle (flooded fields) to the maximum value around the end of the vegetative phase. In past studies, the use of HH or VV as classifiers was found unsuitable for rice classification in regions where adjacent fields can have shifted calendars. Instead, the unique temporal behavior has been exploited in rice mapping methods, in which the classifiers are the temporal change of HH or VV backscattering. Such methods have been proven effective at a number of sites [START_REF] Le Toan | Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results[END_REF], [START_REF] Ribbes | Rice field mapping and monitoring with RADARSAT data[END_REF], [START_REF] Chen | A neural network integrated approach for rice crop monitoring[END_REF], [START_REF] Liew | Application of multitemporal ERS-2 synthetic aperture radar in delineating rice cropping systems in the Mekong River Delta, Vietnam[END_REF], [START_REF] Dao | The use of SAR data for rice crop monitoring, a case study of Mekong river delta-Vietnam[END_REF].

The previous studies have also pointed out the conditions under which these temporal change methods can be applied. The most important conditions are 1) a sufficient number of images during the rice cycle, with a minimum number of three per cycle being indicated [START_REF] Le Toan | Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results[END_REF], and 2) that the rice fields are continuously flooded from the beginning of the cycle until two weeks before harvest. The first condition is met with traditional rice varieties (cycle of 120-150 days), which allows three or more scenes to be acquired with the current satellite repeat cycle-e.g., 35 days of the Advanced Synthetic Aperture Radar (ASAR) on board the Environmental Satellite (ENVISAT). The second condition is well suited to traditional water management, for which a persistent layer of water is maintained on the fields either by rainfed or intermittent irrigation.

Comparatively to copolarized backscatter, much less effort has been put on the use of cross-polarized backscatter in rice applications. Measurements with a multifrequency polarimetric scatterometer on an experimental paddy field in Japan [START_REF] Inoue | Season-long daily measurements of multifrequency (Ka, Ku, X, C, and L) and full-polarization backscatter signatures over paddy rice field and their relationship with biological variables[END_REF] have shown that C-band cross-polarized backscatter is correlated to some rice biophysical parameters (leaf area index and canopy height) and has a temporal behavior similar to that of copolarized backscatter. However, the HV value and its temporal change, being mostly governed by volume scattering, are not specific to rice, but also to other crops in the same scene. With the launch of ENVISAT in 2002, it has been the first time that a satellite SAR system could provide cross-polarized C-band data, as part of ASAR dual-polarization products (HH and HV or VV and VH). However, only very few studies using ASAR have been carried out to confirm the potential of HV or VH for rice monitoring. In [START_REF] Indrani | Estimation of rice growth parameter and crop phenology with conjunctive use of RADARSAT and ENVISAT[END_REF], HV/HH has been related to plant biomass at three dates during the vegetative stage in rainfed rice fields in West Bengal, India, and in [START_REF] Chen | Application of ENVISAT ASAR data in mapping rice crop growth in Southern China[END_REF], a rice map was produced in Guangdong province, China, using a ratio between HH at one date at the end of the growth cycle and HV at another date at the beginning of the cycle. Both results rely on few data sets and need to be assessed at other test sites. Theoretical modeling studies are also needed in order to provide a better understanding of the interactions between cross-polarized waves and the inundated rice canopy.

As stated previously, in recent years, changes in cultural practices have been observed in different regions of the world. The rice growth region in the Mekong Delta in Vietnam is a good example of changes from the traditional to modern rice cultivation system in the last ten years. A multiple cropping system is implemented, increasing the number of crops per year from one or two to two, three, or even more. Dike infrastructures have been built and intensified after 2000 to block the flood way into the fields during the flood season so as to allow an additional crop cycle. Short-cycle rice varieties (80-100 days) are planted in order to harvest three crops per year instead of one or two. Finally, modern water management has been partly introduced in the last three years, consisting in intermittent drainage between two irrigation operations.

For those changes in cultural practices, the intensity temporal change method for rice mapping and monitoring needs to be upgraded. In this paper, a method using polarization information is developed and assessed for this purpose.

Because of the vertical structure of rice plants, the difference between HH and VV backscattering is expected to be higher than that of other crop or land cover types, and through the relation with wave attenuation in the canopy, the ratio of the HH and VV backscattering coefficients (hereafter called HH/VV) can be related to the vegetation biomass. A joint analysis of ERS and RADARSAT-1 data [START_REF] Le Toan | Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results[END_REF], [START_REF] Ribbes | Rice field mapping and monitoring with RADARSAT data[END_REF], and the modeling of C-band HH and VV [START_REF] Le Toan | Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results[END_REF], [START_REF] Wang | Electromagnetic scattering model for rice canopy based on Monte Carlo simulation[END_REF] revealed that HH is significantly higher than VV, and the difference can reach 6-7 dB at the peak growth stage. Based on these findings, HH/VV is potentially a good classifier for rice monitoring, and methods using HH/VV need to be developed and assessed.

Specifically, in this paper, the method is developed using a time series of dual polarization (HH and VV) ASAR data and tested in the province of An Giang in the Mekong Delta. Section II describes the test site and data used in the study. The use of HH/VV as a rice classifier requires a prior statistical study of this polarization ratio on rice and non-rice pixels at different dates, which is reported in Section III. Section IV presents the implementation of the newly developed mapping algorithms, followed by mapping results and validation.

II. SITE AND DATA

A. Site Description

The study site is in the Mekong Delta, South Vietnam. This region accounts for more than half of the rice production in Vietnam, the fifth producer country in the world with about 6% of the global production in 2007 [START_REF] Lam | FAOSTAT (Food and Agriculture Organization[END_REF]. Vietnam is second to Thailand in rice export, and 80%-85% of the rice exported from Vietnam stems from the Mekong Delta.

The Mekong Delta lies in latitude from 8.5 • to 11 • N and is a wide (40 000 km 2 ) flat plain of sedimentation at the mouth of the Mekong and Bassac rivers. Seasonal changes in the precipitation are caused by the monsoon and divide the year into dry season, running from December to late May, early June, and wet season, from June to November, with 1600-2000 mm of rain annually. At the end of the rainy season, the Mekong and Bassac rivers overflow their banks in the northern part of the delta, resulting in flood that affects one third of the delta.

During the wet season, there are two rice cropping patterns, depending on the ecosystem (irrigated or rainfed). In the irrigated areas, the farmers produce both a "Summer-Autumn" and an "Autumn-Winter" rice crop, with high yield varieties. The Summer-Autumn or early rainy season rice crop (locally named "He Thu") is planted in April-early June and harvested in July-early August. The Autumn-Winter or late rainy season (locally named "Thu Dong") is transplanted in August and harvested in November-December. In the rainfed areas, the farmers produce the "main wet season" crop (locally named "Mua"). This is a rainfed crop planted with traditional varieties in July-August. They have various growing durations: early (harvested in late October-early November), medium (harvested in late November-December), and late (harvested in January-February). During the dry season, in the irrigated areas, the farmers grow "Winter-Spring" or dry season crop (locally named "Dong Xuan"). It is planted in November-December and harvested in February-April. However, locally, the crop calendar varies each year, depending on the onset of the rainy season for the start of the Summer-Autumn crop, on the duration of the flood and the date of the Spring festival which occurs in January-February.

A system of canals and dikes to bring irrigation water and control floodwater is being developed to complement the existing system that operated mainly as an irrigation source. Farmers construct minor canals and dikes to control water in their fields. During the dry season, electric pumping is used when water cannot reach the fields through canals.

Special attention is paid to the An Giang province. This province covers an area of 3406 km 2 . The land use is dominated by agricultural land (79.5%), comprising mostly rice farms (94%, thus 75% of total area) [START_REF]General Statistics Office of Vietnam, Structure of Used Land by Province[END_REF]. March 24, April 28, June 2, July 7, September 15, October 20, November 24, and December 29).

B. SAR Data

Fig. 1 shows the location of the province of An Giang and the ASAR APP frames under study. Fig. 2 shows the calendar of the main rice crops and the dates of available ASAR data.

C. Ground Data

A geographic information system (GIS) land cover database covering the Cho Moi district in An Giang province, which was completed in 2005, is provided by the University of An Giang. The land is classified and subclassified into forests, water bodies (rivers and lakes), nonvegetation cover, agricultural land (rice, mixed rice and vegetables, annual plants, and perennial trees), residential areas (urban and suburban), and others.

III. DEVELOPMENT OF RICE MAPPING METHODOLOGY BASED ON THE POLARIZATION RATIO HH/VV

A. Approach

The methodology development will be based on results of analysis carried out at the test area in the Cho Moi district. APP images of the eastern track are analyzed regarding the HH/VV ratio of rice and non-rice classes, with the help of the GIS database. The results will be used in Section IV to derive rice mapping algorithms that will be applied to the APP data from the two tracks to map the whole An Giang province.

B. Analysis 1) Data Preprocessing:

The APP level 1 images are preprocessed using the Gamma GEO software (Gamma Remote Sensing, Switzerland). This preprocessing comprises the following steps:

1) creation of a precision image for each polarization of APP image; 2) conversion into backscattering coefficients (σ 0 ) from digital numbers using a calibration factor, following the procedure specified by the European Space Agency (ESA) [START_REF] Rosich | European Space Agency[END_REF]; 3) geocoding. For this very flat terrain in the whole Mekong Delta, no Digital Elevation Model is needed to perform an accurate geocoding.

The GIS database is superimposed to the geocoded ASAR images and rasterized to create masks of rice and non-rice pixels. For this region of 31 000 ha, the rice mask contains more than 1 380 000 pixels (about 21 000 ha) and the non-rice mask contains 632 000 pixels (about 10 000 ha).

2) Statistical Analysis: A statistical study is conducted on the rice and non-rice pixels identified using the GIS. Thus, mapping rice with a threshold on HH/VV at a single date appears possible at six of the ten dates. Using GIS, fieldbased classification methods could be developed and assessed. However, for a more general use when updated GIS data are not available, pixel-based classification is considered. For this purpose, relevant speckle filtering needs to be applied, considering that the HH/VV distributions of rice and non-rice could be largely overlapping, even if their mean values are significantly different.

The statistical framework of such a mapping method is similar to that of the temporal change detection method developed in [START_REF] Rignot | Change detection techniques for ERS-1 SAR data[END_REF], using a threshold on the ratio of backscatter intensities at two dates for the latter and at two polarizations for the former.

Under the assumption of gamma distributed multilook SAR intensities, the probability density function (pdf) of the intensity ratio r = HH/VV of a homogeneous region is found to depend only on the ratio of average intensities r = HH / VV and not directly on the average intensities HH and VV

p (r| HH , V V ) = (2L -1)! (L -1)! 2 r L r L-1 (r + r) 2L (1)
where L is the number of looks. We use a threshold r t to decide on whether to classify a pixel having a given polarization ratio r into class A, characterized by a polarization ratio r A = HH A / VV A , or class B, characterized by a polarization ratio r B = HH B / VV B . With r B > r A , r ≥ r t is classified as class B and r < r t as class A. Fig. 3 shows that class B should be rice and class A non-rice.

Assuming equal a priori probabilities for both classes (p(A) = p(B)), the optimal threshold r 0 is found for p(r 0 |r A ) = p(r 0 |r B ), leading to

r 0 = √ r A r B . (2)
In the general case of unknown a priori probabilities, we find that the probability of error in the classification with a threshold

r t = d • r 0 is P E = (1 -p(B)) • h(d • X) + p(B) • h X d ( 3
)
Authorized licensed use limited to: IEEE Xplore. Downloaded on February 5, 2009 at 04:21 from IEEE Xplore. Restrictions apply. where

h(X) = (2L -1)! (L -1)! 2 L-1 j=0 (L -1)! j!(L -j -1)! (-1) j L + j 1 (1 + X) L+j (4)
and X = r B /r A .

A numerical analysis based on (3) shows that, for the general case, the optimal classification threshold depends on r 0 , L, X, and the a priori probability of rice p(B). However, for cases likely to be encountered (X ≥ 1.5, L ≥ 6, and p(B) ≤ 0.8), using r 0 instead of the true optimal threshold leads to only slightly suboptimal results (less than 5% of additional error in the worst case).

The expression of the probability of error with r 0 as a classification threshold (d = 1) reduces to P E = h(X).

(5) Fig. 4 shows the probability of error PE versus the difference between the mean ratios of the two classes Δr = r B /r A = X 2 , for different values of L, when the classification threshold is r 0 .

In order to study the statistical distributions of the HH/VV polarization ratio for the two classes and to determine the r A and r B values necessary to implement the mapping method, we compute the ratio between HH and VV ASAR backscattering images (values in linear scale, not logarithmic scale) on a pixel basis, to create an HH/VV image at each date. In this study, all pixels for each class are taken into account in the calculations of mean values or histograms.

Fig. 5(a) shows examples of HH/VV normalized histograms of rice and non-rice pixels at the three dates during the Summer-Autumn season. The values of r A and r B are derived from Fig. 3; r 0 and Δr are calculated consequently. The first date was in the early stage of the rice season, where very similar distributions of the HH/VV of rice and non-rice pixels are observed. The second and third dates correspond to well-developed stages (booting to flowering). The two distributions have significant differences in their mean values. However, they are also largely overlapped. For rice/non-rice classification, the variance of the distributions of the pixel-based HH/VV needs to be reduced. This is achieved by speckle filtering that will result in an increase in the number of looks of each pixel.

Fig. 4 can be used to estimate the number of looks required in the pixel-based classification. The ASAR APP data at incidence IS2 have a number of looks equal to 1.4. With Δr equal to 4.7 dB (at the date of June 2), the probability of error PE should be around 35%. To decrease the probability of error to 10%, the equivalent number of looks (ENL) should rise to around 12. Likewise, if Δr = 3.5 dB, ENL is around 20.

3) Multichannel Filtering: A multichannel filter described in [START_REF] Quegan | Filtering of multichannel SAR images[END_REF] was developed to reduce the speckle noise in SAR images and thus increase the original number of looks in the image to a higher ENL, without reducing the spatial resolution. The filter linearly combines M input images on a pixel-topixel basis, to create M output images with reduced speckle. For uncorrelated images with the same number of looks L, the linear combination is

J k (x, y) = I k (x, y) M M i=1 I i (x, y) I i (x, y) (6)
where J k (x, y) radar intensity of output image k at pixel (x, y); I i (x, y) radar intensity of input image i at pixel (x, y); I i (x, y) local average intensity of input image i at pixel (x, y). The local average intensity is calculated using an averaging window of N pixels.

The theoretical value of the ENL of the output filtered images is

EN L = M × N × L M + N -1 . ( 7
)
With M = 20 images (ten dates and two polarizations) of L = 1.4 look, we calculate from ( 7) that the requested ENL of 12 requires an averaging window (N ) of at least 14 pixels. A 5 × 5 square window (25 pixels) is chosen in this study for the multichannel filtering, resulting in an ENL of 15.9.

Similarly, if the requested ENL is 20, N = 46, and the window size is 7 × 7.

4) Statistical Analysis After Filtering of the ASAR Images: Fig. 5(b) shows the same histograms of rice and non-rice pixels as in Fig. 5(a), but after filtering. The separability of the two classes for the fully grown stages is improved significantly. In particular, it is to be noted that the filtering can reveal rice pixels with different calendars, as in the result of the last date, where a part of the rice fields have been harvested, resulting in a bimodal histogram. As a consequence, the values of r B have been calculated on an area with a nonnegligible proportion of non-rice pixels and must be re-estimated. To do so, we consider that, since the two modes of the bimodal histograms are relatively well separated, the theoretical pdf given in (1) and the rice mode in the histogram have their maxima at the same polarization ratio value r max . Furthermore, r max is analytically found from (1) to be directly related to r B

r max = L -1 L + 1 r B ( 8
)
where L is the ENL (15.9 here). r B and r A are thus estimated at each date by retrieving r max from the rice and non-rice histograms, respectively, and using [START_REF] Wang | Electromagnetic scattering model for rice canopy based on Monte Carlo simulation[END_REF]. The newly estimated values of r A , r B , r 0 , and Δr for the three dates of the Summer-Autumn season are shown in Fig. 5(b), and Fig. 6 shows the values of r A , r B , and Δr for the ten images available in the three rice seasons in 2007, as well as the previously estimated values from 3 for comparison. The new values exhibit a higher class separability, with Δr higher than 5 dB at two dates per season and reaching a maximum of 8 dB. The corresponding values of r 0 range from 2.0 to 3.5 dB, with a mean value around 3 dB.

IV. IMPLEMENTATION OF RICE MAPPING ALGORITHMS

A. Principles

The rice mapping methods are tested on the 2007 Summer-Autumn rice season. The test is performed on singleand multidate data sets.

The single-date mapping method relies on the use of a threshold on the polarization ratio using the optimal threshold given in [START_REF] Lam | FAOSTAT (Food and Agriculture Organization[END_REF]. For the Summer-Autumn season, with the APP image from June 2, a pixel is classified as rice when its polarization ratio is higher than r 0 = 3.07 dB and classified as non-rice if otherwise. To remove noise in the rice maps induced by remaining speckle effects or filtering artifacts, the clusters detected as rice with a size of less than 100 pixels (about 1.4 ha) are removed from the rice class. This is based on the fact that, in the Mekong Delta, rice cultivation is often organized by cooperatives of several farmers' owned fields. Rice fields, even of small size, are usually regrouped in large units.

The single-date method is expected to provide early mapping results. However, the rice fields in a same area can have a slightly shifted calendar. In the previous case (single-date mapping on June 2), later sown fields may have a higher polarization ratio on the next acquired date (July 7) and may be best detected at this date, when earlier sown fields are already harvested. This constitutes a potential source of omission error (rice classified as non-rice) in the single-date method. Comparatively, commission error (non-rice classified as rice) is expected to be much lower than omission error. The overall error can thus be reduced if the classification is applied to all available dates when Δr is higher than 4 dB (here, two dates per season). In this multidate method, a pixel is assigned to rice class if it is classified as rice (according to the single-date method) for at least one of the dates. Fig. 7 shows the June 2 image and the multidate rice map derived from the three images acquired during the Summer-Autumn season.

For the general case when no GIS data are available, the optimal thresholds r 0 and the difference between classes Δr at each date cannot be calculated, and the mapping method cannot be applied exactly as described previously. Therefore, there is a need to define a default threshold suitable for rice mapping at any date. With a constant default threshold, the multidate method consists of the union of the rice maps obtained by the single-date method at each available date within the season and is therefore strictly equivalent to applying this threshold on the maximum value of HH/VV in all the available dates for each pixel. The histograms of the maximum value of HH/VV of rice and non-rice at the three seasons for each pixel are shown in Fig. 8 and indicate a default threshold around 3 dB, which is consistent with the r 0 values found previously.

This method can be used sequentially to provide results early in the season that can be improved in near-real time at each further data acquisition during the season.

B. Validation and Discussion

The results of these methods are assessed using the rice and non-rice masks derived from the GIS data. To reduce errors due to the possible position shift between the geocoding of the ASAR data and that of the GIS, and potential inaccuracies in the GIS polygon delineation, each polygon of the GIS is eroded (3 × 3 kernel) to take into account only validation pixels that have higher reliability. The GIS gives information on the spatial distribution of rice fields, but not on the cropping systems. A field labeled as rice can be grown at one, two, or three of the rice seasons. Therefore, to allow comparison between the GIS data and ASAR results, the yearly spatial distribution of rice is derived from the rice maps obtained by the single-or multidate methods at the three seasons. This spatial distribution consists in the collection of the pixels that are detected as rice during at least one of the three seasons. The comparison between rasterized GIS pixels and the rice spatial distribution derived from ASAR in Fig. 9 shows a pixel-based agreement of 89.9% (commission rate = 2.8%, omission rate = 7.3%, with respect to rice) for the multidate method and 85.6% (commission rate = 2.2%, omission rate = 12.2%, with respect to rice) for the single-date method. Several causes can be the sources of disagreement: 1) changes in land use between 2005 (GIS) and 2007 (ASAR); 2) the position shift between ASAR and GIS; 3) initial errors in the GIS; and 4) error attributable to the ASAR method. Despite the error sources, 90% of agreement is a promising result.

These results confirm that the multidate method reduces omission error without increasing much commission error, compared to the single-date method.

The improvement induced by the multidate method (using all dates available within a season) over the single-date method (using the optimal date within a season) can also be assessed by comparing the sown areas retrieved by the two methods for each season, given in Table I, to the sown areas given in official statistics. The Agriculture and Rural Development Department of the An Giang province, which provides yearly statistics of rice sown area, has published the statistics for the first season in 2007 (Winter-Spring). The value of 17 886 ha for the Cho Moi district is in very good agreement with the multidate SAR-based results (17 825 ha), while the single-date results underestimate the sown area by 11% (15 952 ha). The figures for the two last seasons will be published during 2008.

C. Extension to the Whole Province

The method is applied on images of the two tracks to map rice crops in the An Giang province.

To map rice area for the four rice seasons (Winter-Spring, Summer-Autumn, Autumn-Winter, and main wet season), the multidate method with a constant threshold at 3 dB was applied as follows: Autumn-Winter and main wet season rice were then separated by considering that main wet season rice was grown only as a single crop (i.e., no rice at the two other seasons). The results obtained for the rice season have been compared to the statistics of the province of An Giang. The SAR method has provided the quasi-exact values published in February 2007 for the planted area of the first rice season in 2007. This promising result shows that methods using SAR data can be timely and cost effective.

The method is well-suited to regions where fields have multiple crops and shifted calendars. HH/VV is expected to remain high even for drained fields; this has to be further studied. A default threshold on the HH/VV values was defined to make the method more general. Therefore, this mapping method is expected to be operational with the advanced satellite SAR systems at C-band providing HH and VV data together, such as ASAR and RADARSAT-2.

Further works will consist of an improvement of the method by using HH/VV and the temporal change of HH and/or VV in the multidate approach. The method will be tested for rice mapping in the entire Mekong Delta, using both ENVISAT APP and Wide Swath (ScanSAR) data.

  Time series of ASAR images have been acquired during the year 2007. The ASAR instrument is a C-band SAR (5.6-cm wavelength) on board ENVISAT and operating in a number of modes: fine beam with various combinations of incidence and polarization, and ScanSAR. This study uses the fine-beam dual-polarization alternating polarization precision (APP) data (APP image) with incidence IS2 (19.2 • -26.7 • ) in HH and VV polarization. APP images have a nominal spatial resolution of 30 × 30 m and pixel size of 12.5 × 12.5 m, with a swath width of about 100 km. The exact revisit cycle of ENVISAT is 35 days. To cover the whole An Giang province, two parallel satellite tracks in ascending pass have been used. Eight images are available in 2007 over the western track (February 1, March 8, April 12, May 17, June 21, July 26, August 30, and October 4) and ten over the eastern track (January 13, February 17,

Fig. 1 .

 1 Fig. 1. Location of An Giang province in the Mekong Delta on an ENVISAT ASAR ScanSAR wide swath mode image of South Vietnam. In white is the Vietnam-Cambodia border. Frames are those of ASAR APP data used in this study.

Fig. 2 .

 2 Fig. 2. Rice calendar in the province of An Giang in the Mekong Delta and dates of the available ASAR APP data. For each rice crop, dashed lines represent the periods during which the beginning and end of the crop can take place (spatial and interannual variability).

Fig. 3 .

 3 Fig. 3. Polarization ratio of the mean intensities HH / VV for pixels defined as (gray circles) rice and (black square) non-rice in the GIS database. Black bars represent the difference of this ratio between the two classes.

Fig. 3

 3 shows the ratio of the mean HH and VV values HH / VV for these two classes at the ten dates under study (conversion to decibels is done only after averaging and ra-tioing). The non-rice class exhibits HH / VV values around -0.75 dB (±0.5 dB) at all dates, whereas the rice class shows variations as a function of growth stage during each of the three crop seasons. Maximum values of 4.3 dB are found at the peak growth stages. Fig.3also shows the difference in decibels between the HH / VV values of the two classes and indicates a high class separability (difference higher than 3 dB) at two dates per season (January 13 and February 17 for the Winter-Spring season, June 2 and July 7 for the Summer-Autumn season, and October 20 and November 24 for the Autumn-Winter season). Note that, for the Autumn-Winter season, only one part (about 75% in Cho Moi) of GIS rice pixels are grown as rice; therefore, about 25% of the pixels in the rice class are actually not rice, resulting in an underestimation of the HH / VV of the true rice class.

Fig. 4 .

 4 Fig. 4. Probability of error (in percent) of the ratio method versus the change in polarization ratio Δr (in decibels) between the two classes, for a number of looks L varying between 1 and 128.

Fig. 5 .

 5 Fig. 5. (a) Histograms of the polarization ratio HH/VV for (full line) rice and (dashed line) non-rice classes during the Summer-Autumn season. (Vertical lines) r A and r B are the HH / VV values of each class, and Δr is the distance between the two classes. Vertical dotted lines represent the optimal threshold r 0 . (b) Histograms of the polarization ratio HH/VV for (full line) rice and (dashed line) non-rice classes during the Summer-Autumn season after image filtering. (Vertical lines) r A and r B are the estimated parameters of the theoretical pdf of each class, and Δr the distance between the two classes. Vertical black dotted lines represent the optimal threshold r 0 .

Fig. 6 .

 6 Fig. 6. Estimated values of r A and r B for (gray circles) rice and (black squares) non-rice classes in 2007, and Δr is in black. Empty symbols and bars represent the previously estimated values from Fig. 3.

Fig. 7 .Fig. 8 .

 78 Fig. 7. (Left) Polarization ratio image of the filtered ASAR data on June 2 in the Cho Moi district and (right) derived Summer-Autumn rice map using the multidate method, white pixels = rice.

Fig. 9 .

 9 Fig. 9. (Left) Yearly spatial distribution of rice fields derived by ASAR, and (right) land use reported by the GIS, where rice appears in gray, non-rice in black, and pixels not included in the GIS in white.

  1) Winter-Spring using six dates: February 1, March 8, and April 12 (western track), and January 13, February 17, and March 24 (eastern track); 2) Summer-Autumn using six dates: May 17, June 21, and July 26 (western track), and April 28, June 2, and July 7 (eastern track); 3) Autumn-Winter and main wet season together using five dates: August 30 and October 4 (western track), and September 15, October 20, and November 24 (eastern track).

Fig. 10

 10 shows the results where rice crops at all seasons are distinguished. The estimated planted areas for the An Giang province are the following: 224 273 ha in the Winter-Spring season, 222 746 ha in the Summer-Autumn season, 72 070 ha in the Autumn-Winter, and 4973 ha in the main wet season, which make a total of 524 061 ha of rice planted in 2007. The Agriculture and Rural Development Department of the An Giang province publishes a Winter-Spring sown area of 229 694 ha for the An Giang province. The figures for the two last seasons will be published during 2008. The General Statistics Office of Vietnam reports the paddy rice planted areas for each province in the country [26] divided into three categories: Spring, Autumn, and Winter paddies. After an examination of these statistics, it appears that Spring paddy corresponds to the Winter-Spring season, Autumn paddy to the sum of Summer-Autumn and Autumn-Winter seasons, and Winter paddy to the main wet season. Fig. 11 shows the evolution of the planted areas of rice in the recent past years (1995-2006) together with the 2007 area as assessed by ASAR.

Fig. 10 .

 10 Fig. 10. Rice maps of the An Giang province derived from the multidate method for (a) Winter-Spring, (b) Summer-Autumn, (c) Autumn-Winter, and (d) main wet season in 2007 (white is rice, gray is non-rice, and black is outside An Giang province).

Fig. 11 .

 11 Fig. 11. Cultivated area of paddy rice in the An Giang province as reported by the General Statistics Office of Vietnam (1995-2006) and derived from the retrieved rice maps (2007).In general, there is an increase in area for the main seasons: Spring and Autumn paddy (and a decrease in Winter paddy). The total rice grown area increases of about 35% from 1995 to 2005. The increase is particularly significant for the Autumn paddy since 2002. It can be understood that, after the big floods in years 1999-2000, the dike network was intensified to protect the region from floodwater. As a consequence, Autumn-Winter rice could be grown in places where it was not possible before. The increase in Autumn rice is diminished in 2006 when less rice has been planted to avoid the propagation of a disease inoculated by brown planthoppers that occurred since the end of 2005. According to our results, the 2007 Autumn rice is back to the level of 2005. Of course, this needs to be further verified.

TABLE I SOWN

 I AREA IN THE CHO MOI DISTRICT IN 2007 FOR EACH SEASON AND TOTAL SOWN AREA RETRIEVED BY THE SINGLE-AND MULTIDATE METHODS

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ACKNOWLEDGMENT

The ENVISAT/ASAR data used in this study were provided by ESA (Cat-1 AO Project 697).

Alexandre Bouvet was born in France, in 1981. He received the B.S. degree in engineering from the Ecole Nationale Superieure d'Aeronautique et de l'Espace, Toulouse, France, in 2004. He is currently working toward the Ph.D. degree on the monitoring of rice paddies from space at the Centre d'Etudes Spatiales de la Biosphère, Toulouse.

His interests include synthetic aperture radar (SAR) image processing and the use of SAR remote sensing data in land applications.

Thuy Le Toan received the Ph.D. degree in nuclear physics from the Paul Sabatier University, Toulouse, France.

Since 1995, she has been with the Centre d'Etudes Spatiales de la Biosphère, Toulouse, where she is leading research activities in the area of microwave remote sensing applied to natural surfaces, including experimentation and modeling of microwave interaction with agricultural and forested media. Her current interest is on the use of remote sensing data to quantify the effect of land processes on the carbon cycle. She has been a Project Coordinator and Principal Investigator on several synthetic aperture radar (SAR) campaigns and projects dealing with spaceborne SARs. She is leading current projects using the Environmental Satellite/ Advanced SAR for rice monitoring in Vietnam and China (the European Space Agency (ESA)-China Ministry of Science and Technology Dragon rice project), and projects using Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) for forest observations. She is conducting studies to assess P-band SAR for forest biomass retrieval.

Dr. Le Toan is member of the ALOS Kyoto and Carbon Science team, and the Chairperson of the BIOMASS Mission Assessment Group, working toward the phase A selection by ESA for the next Earth Explorer Core mission.

Nguyen Lam-Dao received the Engineering degree in geodesy from Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam, and the M.E. degree in remote sensing and geographic information systems from Asian Institute of Technology, Thailand, in 1996. He is currently working toward the Ph.D. degree in radar remote sensing of vegetation at the University of Southern Queensland, Toowoomba, Australia, and Vietnam National University, Ho Chi Minh City.

Since 1990, he has been with the Center for Space Physics and Remote Sensing Technology, Ho Chi Minh City, Vietnam. The current name of the center is GIS and Remote Sensing Research Center, Ho Chi Minh City Institute of Resources Geography. His research interests include experimental analysis and image processing toward applications.


domain: spi chim

text:
H Lakhlifi
email: lakhlifihind21@gmail.com

Y El Jabbar

A Natik

H Lassri

M Abid

L Er-Rakho

Sophie Guillemet-Fritsch

R El

S Guillemet- Fritsch

R El Ouatib

of nanocrystalline based on zinc-cobalt molybdate

Keywords: Electronic, magnetic, optical properties, and morphological characteristics A1-Characterization, A1-XRD, A1-Solid solution, B1-Nanomaterials, B2-Semiconductor, B2-Magnetic moment

come

Introduction

Ternary oxides AB 2 O 4 (A= Co, Cu.. and B= Fe, V..) have been selected for their potential of a large use, corresponding to the present and future environmental, economic, scientific, and technological needs, and more particularly the photocatalytic applications [START_REF] Monsef | Electrochemical sensor based on a chitosan-molybdenum vanadate nanocomposite for detection of hydroxychloroquine in biological samples[END_REF][START_REF] Amiri | Caffeine: A novel green precursor for synthesis of magnetic CoFe 2 O 4 nanoparticles and pH-sensitive magnetic alginate beads for drug delivery[END_REF][START_REF] Yousefi | Synthesis, characterization and application of Co/Co 3 O 4 nanocomposites as an effective photocatalyst for discoloration of organic dye contaminants in wastewater and antibacterial properties[END_REF].

Molybdenum-based oxides are very diverse in terms of structural characteristics and physicochemical properties [START_REF] Zheng | Structure, infrared reflectivity spectra and microwave dielectric properties of a low-firing microwave dielectric ceramic Pr 2 Zr 3 (MoO 4 ) 9[END_REF]. Additionally, molybdates open the way to various potential technological applications, due to their semiconducting, optical, and optoelectronic properties.

These applications include the development of optoelectronic, photo-catalytic, and electrochemical devices [START_REF] Ahmed | Significant recycled efficiency of multifunctional nickel molybdenum oxide nanorods in photo-catalysis, electrochemical glucose sensing and asymmetric supercapacitors[END_REF][START_REF] Huerta-Flores | Synthesis of AMoO 4 (A = Ca, Sr, Ba) photocatalysts and their potential application for hydrogen evolution and the degradation of tetracycline in water[END_REF][START_REF] Yang | Enhanced electrochemical performance of CoMoO 4 nanorods/reduced graphene oxide as anode material for lithium-ion batteries[END_REF][START_REF] Ishrat | Preparation and characterization of polystyrene based Nickel molybdate composite membrane electrical-electrochemical properties[END_REF]. The electrochemical performances of AMoO 4 materials have been widely exploited for the fabrication of energy storage/conversion devices such as supercapacitors [START_REF] Liu | Rapid microwave-assisted synthesis of mesoporous NiMoO 4 nanorod/reduced graphene oxide composites for high-performance supercapacitors[END_REF][START_REF] Bhagwan | Facile synthesis of MnMoO 4 @MWCNT and their electrochemical performance in aqueous asymmetric supercapacitor[END_REF], hybrid capacitors [START_REF] Gao | Engineering pseudocapacitive MnMoO 4 @C microrods for high energy sodium ion hybrid capacitors[END_REF][START_REF] Hong | Rational construction of three dimensional hybrid Co 3 O 4 @NiMoO 4 nanosheets array for energy storage application[END_REF], and photoelectrochemical batteries [START_REF] Fei | Sodium carboxyl methyl cellulose and polyacrylic acid binder with enhanced electrochemical properties for ZnMoO 4 •0.8H 2 O anode in lithium ion batteries[END_REF][START_REF] Amanulla | Selectivity, stability and reproducibility effect of CeM -CeO 2 modified PIGE electrode for photoelectrochemical behaviour of energy application[END_REF].

These oxides are also used in optoelectronic systems [START_REF] Ren | Interfacing nickel with molybdenum oxides as monolithic catalyst to accelerate alkaline hydrogen electrocatalysis with robust stability[END_REF] and in the design of passive optical limiters [START_REF] Wang | Nonlinear absorption, refraction and optical limiting properties of cobalt molybdate microcrystals[END_REF]. Furthermore, they are incorporated into sensors as moisture biosensors [START_REF] Sasikumar | 3D walnut-like rare-earth gadolinium molybdate encapsulated with thermo-responsive hydrogel for sensitive electrochemical detection of anticancer drug Niftolide in human urine[END_REF][START_REF] Mobeen Amanulla | Antibacterial, magnetic, optical and humidity sensor studies of β-CoMoO 4 -Co 3 O 4 nanocomposites and its synthesis and characterization[END_REF].

Great interest is thus brought to the synthesis of nanocrystalline metals since it is possible to control their physicochemical properties, via the modulation of their structures, sizes, and shapes at the nanometric scale [START_REF] Davar | Synthesis and characterization of SnO 2 nanoparticles by thermal decomposition of new inorganic precursor[END_REF]. In the case of metal oxides of the chemical formula AMoO 4 , it is possible to adjust the physicochemical properties through several parameters such as pressure, temperature, synthesis time, or the concentration and chemical composition of the starting reagents. Recently, in 2017, Ghiyasiyan-Arani et al. [START_REF] Ghiyasiyan-Arani | Enhanced photodegradation of dye in waste water using iron vanadate nanocomposite; ultrasound-assisted preparation and characterization[END_REF] investigated the effect of different parameters on the sonochemical synthesis of FeVO 4 nanocomposite. The diversity of the synthesis processes (hydrothermal [START_REF] Duo | A facile salicylic acid assisted hydrothermal synthesis of different flower-like ZnO hierarchical architectures with optical and concentrationdependent photocatalytic properties[END_REF][START_REF] Panahi-Kalamuei | Synthesis and characterization of CeO 2 nanoparticles via hydrothermal route[END_REF][START_REF] Monsef | Hydrothermal architecture of Cu 5 V 2 O 10 nanostructures as new electro-sensing catalysts for voltammetric quantification of mefenamic acid in pharmaceuticals and biological samples[END_REF], microwave irradiation [START_REF] Koga | Thermal decomposition of synthetic antlerite prepared by microwave-assisted hydrothermal method[END_REF][START_REF] Phuruangrat | Synthesis of lead molybdate and lead tungstate via microwave irradiation method[END_REF], Pechini [START_REF] Wang | Pechini-type sol-gel synthesis and multicolor-tunable emission properties of GdY(MoO 4 ) 3 :RE 3+ (RE=Eu, Dy, Sm, Tb) phosphors[END_REF][START_REF] Wang | Ethanothermal reduction to MoO 2 microspheres via modified Pechini method[END_REF], sonochemical route [START_REF] Yousefi | Control sonochemical parameter to prepare pure Zn 0.35 Fe 2.65 O 4 nanostructures and study their photocatalytic activity[END_REF], solid-solid [START_REF] Sheng | Solid-state synthesis and superior electrochemical performance of MnMoO 4 nanorods for asymmetric supercapacitor[END_REF][START_REF] Zhao | A flexible all-solid-state asymmetric supercapacitors based on hierarchical carbon cloth@CoMoO 4 @NiCo layered double hydroxide core-shell heterostructures[END_REF], molybdate complexes: ligand loss [START_REF] Béres | Solid-Phase "Self-Hydrolysis" of [Zn(NH 3 ) 4 MoO 4 @2H 2 O] Involving Enclathrated Water-An Easy Route to a Layered Basic Ammonium Zinc Molybdate Coordination Polymer[END_REF][START_REF] Sajó | Unexpected Sequential NH 3 /H 2 O Solid/Gas Phase Ligand Exchange and Quasi-Intramolecular Self-Protonation Yield [NH 4 Cu(OH)MoO 4 ], a Photocatalyst Misidentified before as (NH 4 ) 2 Cu(MoO 4 ) 2[END_REF] and co-precipitation [START_REF]Synthesis of MnMoO 4 Nanorods by a Simple Co-Precipitation Method in Presence of Polyethylene Glycol for Pseudocapacitor Application[END_REF][START_REF] Shahri | Facile synthesis and characterization of nanostructured flower-like copper molybdate by the co-precipitation method[END_REF]), and preparation conditions (pH, temperature, time...) have a huge influence on the microstructure and morphology of the obtained powders.

Due to its excellent physicochemical properties, CoMoO 4 could be considered as an outstanding matrix material for energy storage devices [START_REF] Liu | Boosting energy storage and electrocatalytic performances by synergizing CoMoO 4 @MoZn22 core-shell structures[END_REF][START_REF] Prasad | Morphological transformation of rod-like to pebbles-like CoMoO 4 microstructures for energy storage devices[END_REF]. Moreover, due to the combined contributions of cobalt and molybdenum ions, high electrochemical performances could be achieved. However, ZnMoO 4 is of much less interest due to its poor electronic conduction [START_REF] Xue | Enhanced electrochemical performance of ZnMoO 4 /reduced graphene oxide composites as anode materials for lithium-ion batteries[END_REF]. Therefore, attention has been focused on methods for enhancing this material's electrochemical performance [START_REF] Lakhlifi | Synthesis of molybdates Zn 1-x Co x MoO 4 (0 ≤ x ≤ 1), by decomposition of the precursors developed by the glycine-nitrate process (GNP), and their characterization[END_REF][START_REF] Lakhlifi | Synthesis and physicochemical characterization of pigments based on molybdenum[END_REF]. Recent studies have shown that transition metal oxides could be favorable for increasing the electrical conductivity and specific capacitance of materials due to their large specific surface area, structural flexibility, high aspect ratio, and unique mechanical properties [START_REF] Budhiraju | Structurally stable hollow mesoporous graphitized carbon nanofibers embedded with NiMoO 4 nanoparticles for high performance asymmetric supercapacitors[END_REF].

The present study reports on the synthesis and characterization of nanocrystalline metal molybdate Zn 1-x Co x MoO 4 (0 ≤ x ≤ 1) using the polymeric route. The effects of the synthesis parameters on the structure, particle size, and morphology were discussed in detail. The ZnCoMo-0.2-700 and ZnCoMo-0.3-700 powders can be applied as a new blue pigment, produced by sol-gel method, in ceramic stains. The origin of the color in these two samples was investigated by UV-visible spectroscopy. Additionally, a theoretical simulations study of the electronic magnetic and optical properties of ZnCoMo-1-700 in relation to both the band structure and the associated projected density of states (PDOS) was performed.

Methods and materials

Synthesis

The synthesis of zinc-cobalt molybdate Zn O (99.0%, Acros) in stoichiometric proportions then poured into a solution containing an excess amount of complexing and chelating agents. Citric acid (CA) was then introduced with a molar ratio CA/cations metal of 3. The pH of the obtained solution was adjusted with nitric acid or ammonia. The precursors were obtained after evaporation and drying at 120 °C for 24 hours. These precursors were pre-calcined at 300 °C for 12 hours under air. The black powder obtained was heat treated for 2 hours at temperatures ranging from 600 °C to 800 °C. The composites were denoted as follows;

ZnCoMo-0-T (ZnMoO 4 , x = 0), ZnCoMo-0.2-T (Zn 0.8 Co 0.2 MoO 4 , x = 0.2), ZnCoMo-0.

Characterization

The thermal decomposition behaviours of the precursors obtained after pyrolysis were monitored with a DTA-TGA analyser (Apparatus Shimadzu). XRD patterns were obtained at room temperature using a Bruker D 8 employing CuK α radiation as the X-ray source (λ CuKα = 1.5406 Å). The infrared spectra were recorded using an FTIR spectrometer (IR Affinity-1S Shimadzu). The nanocrystalline metal molybdate solid-solutions were analyzed by Raman spectroscopy using a Horiba Jobin-Yvon HR800 LabRam spectrometer. Data were collected in the range 200-1200 cm -1 . The excitation source used was laser irradiation of 516.4 nm wavelength. The morphology and size of the grains were examined with a field emission scanning electronic microscope (JEOL JSM 6700F). A PerkinElmer Lambda 35 UV-Vis spectrophotometer was used to measure diffuse reflectance. The specific surface area of the powders was measured using Brunauer-Emmet-Teller (BET) method by Micrometrics Flowsorb II 2300 instrument. Using a CHROMA METER CR-400/ 410 colorimeter (KONICA MINOLTA), colorimetric measurements were taken in the CIE L*a*b* (Comission Internationale de l'Eclairage's L*a*b* colorimetric system). Theoretical simulations are carried out using the density function theory (DFT) and the full potential linearized augmented plane wave (FP-LAPW) to solve the Kohn-Sham equations. The exchange and correlation energy was calculated using the (GGA-PBE) approximation.

Results and discussion

Thermal decomposition

Thermograms obtained for the ZnCoMo-0.3-300 and ZnCoMo-0.6-300 compounds show similar patterns. The observed weight losses were 69% and 61%, respectively (Fig. 1). For the molybdate ZnCoMo-0.3-300 , the thermogram obtained (Fig. 1a) can be divided into several steps: an initial weight loss of ~11.5% is observed between 50 °C and 150 °C, characterized by a very weak endothermic phenomenon that can be attributed to water desorption; a second weight loss of ~57.5% in the temperature range of 300-500 °C, which was accompanied by two exothermic peaks, one located at 425 °C, which would be attributed to organic matter combustion, and the other at 450 °C, which could be due to residual carbon combustion and the beginning of molybdate crystallization; and beyond 500°C, no weight loss was observed, thus, the decomposition was complete.

The thermogram of the ZnCoMo-0.6-300 precursor shows a very slight weight loss of ~5% between 50 and 100 °C, accompanied by endothermic effects, corresponding to dehydration (Fig. 1b). A second weight loss between 300 °C and 530 °C of ~56%, which was characterized by two exothermic peaks, one located at 430 °C, which could be attributed to the combustion of the precursor, the other at 520 °C, which corresponds to the oxidation of the carbon produced during the combustion of the precursor. No phenomena were observed above 550 °C, indicating that the decomposition was complete, which confirms that temperatures higher than or equal to 600°C are the most appropriate for obtaining phases free of organic residue.

X-ray diffraction

To study the influence of the cobalt rate on powder crystallization, we prepared samples corresponding to ZnCoMo-x-600 compositions with 0 ≤ x ≤ 1 at acidic pH and temperatures of 600, 700, and 800°C. The X-ray diffractograms of these samples after heat treatment showed similar results, we have reported only the results obtained at 600°C (Fig. 2a and Fig. 2b): * For 0 ≤ x ≤ 0.3 compositions, with or without grinding, the powder was monophased and isostructural with triclinic α-ZnMoO 4 ( T ) (ICDD: 01-035-0765). * For cobalt contents 0.3 < x < 0.45, without grinding, the X-ray diffractograms show the coexistence of two phases: the triclinic phase ( T ) and the monoclinic phase ( M ) isostructural with -CoMoO 4 (ICDD: 00-021-0868) (Fig. 2a). In the case of ground powders, a two-phase mixture was observed: the triclinic phase ( T ) and the monoclinic phase ( M ) isostructural with α-CoMoO 4 (Fig. 2b). * For cobalt fractions x ≥ 0.45, only one phase is observed: either  M isostructural with - 00-021-0868) is sensitive to grinding [START_REF] Robertson | Cobalt-Zinc Molybdates as New Blue Pigments Involving Co 2+ in Distorted Trigonal Bipyramids and Octahedra[END_REF]. The representation of the coordination polyhedra is presented in Fig. 2c.

FTIR and Raman spectroscopy

The identified vibrational modes are classified into two categories, internal modes, which are formed by oscillations inside molecule ionic groups with an immobile center of mass, and external modes, which are vibrations of phonons of the lattice caused by the movement of cations [START_REF] Jayasree | Influence of Ni doping on the structural and third order nonlinear optical properties of ZnMoO 4 nanostructures[END_REF]. There are four normal modes: Symmetric stretching vibration ( 1 ); symmetric bending ( 2 ); antisymmetric stretching ( 3 ); and antisymmetric bending vibration ( 4 ). The symmetric stretching mode is a singlet, symmetric flexion mode is double, while the two antisymmetric modes triply degenerate under Td. Based on the theoretical group analysis, the total number of factor group modes due to the regular molybdate MoO 4 tetrahedron is 4 and corresponds to 9 vibrations modes possible in the molybdate compounds. We note that all four modes are Raman active, but only the antisymmetric (T d ) modes are IR active [START_REF] Zhao | A flexible all-solid-state asymmetric supercapacitors based on hierarchical carbon cloth@CoMoO 4 @NiCo layered double hydroxide core-shell heterostructures[END_REF][START_REF] Béres | Solid-Phase "Self-Hydrolysis" of [Zn(NH 3 ) 4 MoO 4 @2H 2 O] Involving Enclathrated Water-An Easy Route to a Layered Basic Ammonium Zinc Molybdate Coordination Polymer[END_REF].

FTIR and Raman spectroscopy studies were carried out on ZnCoMo-0.3-600 and ZnCoMo-0.6-600 nanocrystalline powders, obtained at 600 °C, to confirm the results attained previously (Fig. 3 and4).

As shown in Fig. 3, the bands at 981, 956, 919, and 904 cm -1 are assigned to the antisymmetric stretching of Mo-O in the MoO 4 tetrahedral units, those at 862 cm -1 would correspond to the symmetric stretching of O-Mo-O bending vibrations [START_REF] Yadav | Structural, photophysical and microwave dielectric properties of α-ZnMoO 4 phosphor[END_REF][44][START_REF] Aleksandrov | Structure study of MoO 3 -ZnO-B 2 O 3 glasses by Raman spectroscopy and formation of α-ZnMoO 4 nanocrystals[END_REF][START_REF] Keereeta | Effect of medium solvent ratios on morphologies and optical properties of α-ZnMoO 4 , β-ZnMoO 4 and[END_REF]. The bands located at 747 and 791 cm -1 can be attributed to the extension of the Zn-O-Mo bands [START_REF] Cavalcante | A combined theoretical and experimental study of electronic structure and optical properties of β-ZnMoO 4 microcrystals[END_REF].

The Zn-O-Mo mode is designated as a wideband system around 650 cm -1 [START_REF] Béres | Solid-Phase "Self-Hydrolysis" of [Zn(NH 3 ) 4 MoO 4 @2H 2 O] Involving Enclathrated Water-An Easy Route to a Layered Basic Ammonium Zinc Molybdate Coordination Polymer[END_REF]. The bands observed at 433 and 435 cm -1 are specific to the bending vibration of the Co-O-Mo bands [START_REF] Lakhlifi | Synthesis and physicochemical characterization of pigments based on molybdenum[END_REF]. The peaks in the range of 419 and 418 cm -1 originated from the stretching vibration modes of Zn-O-Zn indicating the complete transformation from zinc nitrate to zinc oxide [START_REF] Aljawfi | Impact of annealing on the structural and optical properties of ZnO nanoparticles and tracing the formation of clusters via DFT calculation[END_REF].

Fig. 4 also shows the Raman spectra of nanocrystalline powders in the wavelength range of 200-1100 cm -1 . Usually, the symmetric stretching modes and antisymmetric stretching modes of MoO 4 tetrahedral units are Raman active and observed in the region 780-960 cm -1 [START_REF] Béres | Solid-Phase "Self-Hydrolysis" of [Zn(NH 3 ) 4 MoO 4 @2H 2 O] Involving Enclathrated Water-An Easy Route to a Layered Basic Ammonium Zinc Molybdate Coordination Polymer[END_REF]. For the ZnCoMo-0.3-600 sample, the symmetric Mo-O (ν1) band could be observed at 957 cm -1 and assigned as an intensive singlet in the Raman spectra, the band at 930 cm -1 was attributed to the symmetrical stretching modes of the MoO 4 anions [START_REF] Saraiva | Lattice dynamics calculations and high-pressure Raman spectra of the ZnMoO 4[END_REF]. The internal modes ν 3 (antisymmetric stretching, Bg), ν 3 (antisymmetric stretching, Eg), ν 4 (antisymmetric bending, Bg+Eg), ν 4 (symmetric stretching, Bg), and ν 2 (symmetric bending, Ag+Bg) are localized at 871, 852, 804, 358 and 325 cm -1 respectively [START_REF] Xing | Preparation and inhibition behavior of ZnMoO 4 /reduced graphene oxide composite for Q235 steel in NaCl solution[END_REF]. The weak Raman peak observed at 278 cm -1 is attributed to external free rotation mode R (Ag) [START_REF] Jeseentharani | Co-precipitation synthesis, humidity sensing and photoluminescence properties of nanocrystalline Co 2+ substituted zinc(II)molybdate (Zn 1x Co x MoO 4 ; x = 0, 0.3, 0.5, 0.7, 1[END_REF]. For the ZnCoMo-0.6-600 sample, The most high-intensity bands observed at 915 and 878 cm -1 correspond to the Mo-O (ν 1 (Ag)) symmetric stretching vibration [START_REF] Lakhlifi | Purple nanometrics pigments based on cobalt-doped manganese molybdate: Synthesis, characterization, structural, thermal, optical, colorimetric and chemical properties[END_REF]. Those located at 831 and 787 cm -1 are assigned to O-Mo-O antisymmetric stretching vibrations modes [START_REF] Lakhlifi | Structural, morphological and optical properties of cobalt-substituted MgMoO 4 ceramics prepared by pyrolysis of citric acid precursors[END_REF]. The bands observed at 355 and 318 cm -1 were designated to the Mo-O-Co stretching vibrations [START_REF] Padmanathan | Pseudocapacitance of α-CoMoO 4 nanoflakes in non-aqueous electrolyte and its bi-functional electro catalytic activity for methanol oxidation[END_REF][START_REF] Lakhlifi | Nanocrystalline transition metal (CoMoO 4 ) prepared by sol gel method: Correlation between powder colors and α/β phase transformations[END_REF]. These results are in good agreement with those obtained from X-ray diffraction and infrared spectroscopic analysis, indicating that cobalt was inserted into the -ZnMoO 4 lattice.

Morphological properties

The ZnCoMo-0.3-T and ZnCoMo-0.6-T nanocrystalline powders were prepared in acid medium and calcined at 600, 700, and 800 °C for 2 hours and then examined by scanning electron microscopy (SEM) (Fig. 5a and Fig. 5b). The micrographs obtained show that the analysed powders are formed of particles of various morphologies that are more or less agglomerated. An advanced pre-sintering phenomenon was observed for the powders produced at 800 °C.

For the ZnCoMo-0.3-700 oxide, prepared at acidic pH and calcined at 700 °C for 2 hours, the SEM-FEG images reveal quasi-spherical particles of nanometric size (Fig. 5c. (a)). For the powder obtained at 800 °C, the micrograph shows agglomerates of particles, indicating a sintering phenomenon. This is in agreement with the SEM observations (Fig. 5c. (b)).

The particle size distribution was calculated by counting the number of particles and measuring their sizes using many SEM images for ZnCoMo-0.3-700 molybdate prepared at acidic pH (Fig. 6). This distribution shows a quasi-Gaussian type profile with a single population of grains ranging in size from 2 to 3 μm.

The particle size of the powder was calculated using transmission electron microscopy.

TEM examination was carried out only on the ZnCoMo-0.3-T composition prepared at acidic pH and calcined at 600, 700, and 800 °C. The micrograph obtained for the powder obtained at 600°C indicates that it was formed of more or less individualized quasi-spherical particles with an average size estimated between 30 and 100 nm (Fig. 7a). The TEM micrograph of the powder prepared at 700 °C shows particles more or less spherical but more agglomerated with a nanometric size in the range of 100-160 nm (Fig. 7b). The micrograph of the powder prepared at 800 °C indicates that a pre-sintering takes place with a significant magnification of the grains (crystal growth phenomenon) (Fig. 7c).

The specific surface areas of ZnCoMo-0.3-T and ZnCoMo-0.6-T samples obtained at T= 600, 700 and 800 °C were determined using the BET method. A decrease in specific surface area is shown as a function of annealing temperature (Table 1). In comparison to powders produced at 700, and 800 °C, those obtained at 600 °C have a larger specific surface area. As we observe 56.7 m 2 g -1 was the highest value recorded for the ZnCoMo-0.3-600 powder. We note that the substitution of Co 2+ in the ZnMoO 4 matrix leads to a decrease in surface area from 56.7 m 2 g -1 (ZnCoMo-0.3-600) to 42.3 m 2 g -1 (ZnCoMo-1-600). The value of the specific surface area of the ZnCoMo-1-600 powder is compatible with that obtained by Chen et al.

(43.8 m 2 g -1 ) [START_REF] Chen | CoMoO 4 /bamboo charcoal hybrid material for high-energy-density and high cycling stability supercapacitors[END_REF].

With the use of the Scherrer equation, the crystallite size was calculated from the midheight X-ray diffraction line width measurements made in the angular range of 13.6°-33.6°

for ZnCoMo-x-600 (0≤ x ≤ 1) molybdates prepared under acidic pH, calcined at 600 °C, and then ground, as shown in Fig. 8. We noticed that the crystallite size decreases abruptly upon the insertion of 30% cobalt and then gradually increases beyond this rate. This drop could be explained by the decrease in the crystallite growth kinetics during the insertion of cobalt into the -ZnMoO 4 matrix. The calculated crystallite size for ZnCoMo-0.3-600 is consistent with that observed under TEM. All microscopic analyses (SEM, FEG-SEM and TEM) show that grain size increases with temperature.

Effect of pH on morphology

The pH levels of the aqueous solutions of the metal salts and citric acid were adjusted to become acidic or basic by adding nitric acid or ammonia, respectively. The ZnCoMo-0.3-600 and ZnCoMo-0.6-600 powders were characterized by X-ray diffraction. The average crystallite size estimated by the Scherrer's formula from the broadened X-ray diffraction line profiles of ZnCoMo-0.3 and ZnCoMo-0.6 powders increases with pH (Table 2). These molybdates obtained by the calcination of the xerogels prepared at acidic and basic pH levels and calcined at 600 and 700 °C were characterized by SEM (Fig. 9). The SEM micrographs of the powders treated at 600 °C show that they consist of elementary particles of various shapes that are more or less agglomerated. At basic pH, we observed a coarsening of the grains showing pre-sintering characteristics. The SEM images obtained at 700 °C for both compositions under acidic pH show that the powders consist of larger grains than those observed at 600 °C. The micrographs show the advanced pre-sintering characteristics at basic pH. Crystal growth is observed at pH basic, we note that the size and agglomeration of particles increase with pH. These observations are perfectly similar to the results obtained for α-CuMoO 4 powder prepared by the sol-gel route [START_REF] Benchikhi | Sol-gel synthesis and sintering of submicronic copper molybdate (α-CuMoO 4 ) powders[END_REF].

Optical properties

To illustrate the optical behavior of the ZnCoMo-x-T (0 ≤ x ≤ 1) samples via UV-visible spectroscopy, we chose ZnCoMo-0.3-700 and ZnCoMo-0.6-700 as our study materials (Fig. 10). The blue/violet coloration of the synthesized ZnCoMo-0.3-700 and ZnCoMo-0.6-700 powders is shown in Fig. 10. The diffuse reflectance spectra show the presence of bands in the visible region (400-650 nm). The Co 2+ ion, located in a distorted octahedral site, is in a strong spin state (weak field) and adopts a 3d 7 configuration, who's fundamental term is an orbital triplet: 4 T 1 . It gives rise to the three permitted spin transitions (S=0) 4 T1g 4 T2g(F), 4 T1g4A2g(F) and 4 T1g 4 T1g(P). As a result, we can claim clearly from the analysis of the diffuse reflection spectra that the thermochromism occurs from the shift of the O 2- Mo 6+ charge transfer band towards high energies [START_REF] Laufer | Yttrium(iii) oxomolybdates(vi) as potential host materials for luminescence applications: an investigation of Eu 3+ -doped Y 2 [MoO 4 ] 3 and Y 2[END_REF][START_REF] Sasca | Band-gap energy of heteropoly compounds containing Keggin polyanion-[PV x Mo 12-x O 40 ] (3+x)relates to counter-cations and temperature studied by UV-VIS diffuse reflectance spectroscopy[END_REF].

The values of the band gap energy of the ZnCoMo-x-700 (0 ≤ x ≤ 1) solid solutions estimated by extrapolating the linear part of the (hʋα) 2 curve as a function of hʋ are presented in Table 3. The study by UV-visible absorption spectroscopy showed that these oxides present a direct gap transition (Fig. 11), with a band gap Eg between 4.03 eV for ZnMoO 4 and 2.153 eV for -CoMoO 4 . The value of the band gap, found at about 2.153 eV (-CoMoO 4 ), is close to those estimated by Altarawneh et al (1.8 eV) [START_REF] Altarawneh | Structures and thermodynamic stability of cobalt molybdenum oxide (CoMoO 4 -II)[END_REF] and that of the order of 4.03 eV (ZnMoO 4 ), is in good agreement with the experimental value found by Yadav and Sinha (4.1 eV) [START_REF] Yadav | Structural, photophysical and microwave dielectric properties of α-ZnMoO 4 phosphor[END_REF]. According to these values, we can consider these nanocrystalline oxides as semiconductor materials.

The evolution of the colorimetric parameters L*a*b* of the ZnCoMo-0.2-T and ZnCoMo-0.3-T compounds as a function of temperature is shown in Fig. 12. These evolutions show that the component (-b*) characterizing the blue color, has a maximum at 700°C for compositions ZnCoMo-0.2-700 and ZnCoMo-0.3-700. These powders can be applied as a new blue pigment, prepared by polymeric route, in ceramic stains.

Electronic, magnetic, and optical properties

Theoretical simulations are carried out using density functional theory (DFT) [START_REF] Jezierski | Electronic and magnetic properties of Cu 2 MgV 2 O 8 and CuMg 2 V 2 O 8 -ab initio study[END_REF][START_REF] Ullah | Study of structural, electronic and optical properties of co-doped CeO 2 using the density functional theory (DFT) method[END_REF] and solving Kohn-Sham equations using the full potential linearized augmented plane wave (FP-LAPW) [START_REF] Natik | Ab-initio investigation of the structural, electronic and optical properties of lead-free halide Cs 2 TiI 6 double perovskites[END_REF]. The exchange and correlation energy were calculated using the GGA-PBE approximation [START_REF] Bouhbou | Magnetic, half-metallicity and electronic studies of Cd 1-x Zn x Cr 2 Se 4 chromium selenospinels[END_REF]. Experimental lattice constants were used to investigate the electronic, magnetic, and optical properties of ZnCoMo-1-700 (-CoMoO 4 ; x=1) as a typical example.

The input parameters such as R kmax , G max , and k-point were chosen to be 7, 12, and 200 respectively.

The density of states (DOS) is one of the most important physical quantities for understanding the physical properties of a material. The projected total (DOS) and partial density of states (PDOS) between -8 and 16 are shown in Fig. 13a and13b, respectively. The Fermi level is taken as the origin of the energies. The analysis of the total and partial density of the state figures of ZnCoMo-1-700 indicates the presence of the band gap, E g , deducing that this material has a semiconductor nature. The electronic states are divided into two regions: the first is dominated primarily by Co-d states, with a small contribution from O-p states, and the second is dominated primarily by Co-d and Co-d states, with a small contribution from O-p states. Fig. 13c illustrates the analysis of the absorption spectrum, which shows the major peaks, called 'critical points'; E 0 is the threshold energy, and E 1 corresponds to the optical gap, which is estimated with respect to the experimental value. Each peak corresponds to an electronic transition; the first three peaks are due to transitions (inter-band) from the valence band to the conduction band.

Extrapolating the linear part of the curve (αhυ) 2 = f (E) until (αhυ) 2 → 0, the plotting (αhυ) 2 as a function of hν gives the value of Eg. This explains perfectly that ZnCoMo-1-700 has the property of a direct band gap. The optical band gap of ~ 1.989 eV was observed (Fig. 13d). The calculated value is very similar to that of the experimental results (Fig. 11/Table 3). The index of refraction of the ZnCoMo-1-700 system varies as a function of photon energy, as shown in Fig. 13e. The static refractive index of this compound is n(0) = 2.1. In addition, using the experimental lattice constants, the magnetic moments and band gap were determined, as shown in Table 4. A study shows that nanocrystalline metal ZnCoMo-1-700 undergoes a three-dimensional antiferromagnetic transition at TN = 37 K [START_REF] Viola | Induction of Colossal Magnetoresistance in the Double Perovskite Sr 2 CoMoO 6[END_REF].

Conclusion

Nanocrystalline metal molybdates ZnCoMo-x-T were synthesized using the polymeric route. The X-ray diffraction analysis of the powders treated at 600, 700 and 800 °C then ground shows two single-phase domains: the triclinic symmetry isotype of -ZnMoO 4 for 0 ≤ x ≤ 0.3 compounds and the monoclinic symmetry isotype of -CoMoO 4 for 0.45 ≤ x ≤ 1 powders. The resulting powders are formed by single-crystalline elementary particles with a quasi-spherical shape and a size range of 30-160 nm.

  3-T (Zn 0.7 Co 0.3 MoO 4 , x = 0.3), ZnCoMo-0.35-T (Zn 0.65 Co 0.35 MoO 4 , x = 0.35), ZnCoMo-0.4-T (Zn 0.6 Co 0.4 MoO 4 , x = 0.4), ZnCoMo-0.45-T (Zn 0.55 Co 0.45 MoO 4 , x = 0.45), ZnCoMo-0.6-T (Zn 0.4 Co 0.6 MoO 4 , x = 0.6), ZnCoMo-0.8-T (Zn 0.2 Co 0.8 MoO 4 , x = 0.8) and ZnCoMo-1-T (CoMoO 4 , x = 1), such as T= temperature of the heat treatment (T= 300, 600, 700, or 800 °C).

CoMoO 4 ,

 4 in the case without grinding, or isostructural with α-CoMoO 4 , in the case of ground powders. The green -CoMoO 4 (ICDD: 01-073-1331) polymorph was formed by grinding the purple -CoMoO 4 molybdate. The piezochromism phenomenon relates to the color change caused by grinding or pressure in general. The piezosensitive -CoMoO 4 molybdate (ICDD:

  Measurements of the colorimetric parameters (L*a*b*) of ZnCoMo-0.3-T and ZnCoMo-0.6-T compositions show that the component (-b*) characterizing the blue color, has a maximum at 700 °C. Based on the optical band-gap energy (Eg=2.153 eV), the monoclinic ZnCoMo-1-700 °C is a semiconductor material. The theoretical magnetic moment of this sample is approximately  theorical = 5.00049  B .

Fig. 1 .

 1 Fig. 1. TGA-DTA analysis of dried gel of (a): ZnCoMo-0.3-300 and (b): ZnCoMo-0.6-300 precursors.

Fig. 2a .

 2a Fig. 2a. X-ray diffraction patterns of ZnCoMo-x-600 (0 ≤ x ≤ 1) compounds prepared at 600 °C (without grinding).

Fig. 2b .

 2b Fig. 2b. X-ray diffraction patterns of ZnCoMo-x-600 (0 ≤ x ≤ 1) compounds prepared at 600 °C (with grinding).

Fig. 2c .

 2c Fig. 2c. Ball and stick representation of crystal structure of the ZnCoMo-0.3-600 nanocrystalline powder.

Fig. 3 .

 3 Fig. 3. FT-IR spectra of the ZnCoMo-0.3-600 and ZnCoMo-0.6-600 powders.

Fig. 4 .

 4 Fig.4. Raman Spectra of the ZnCoMo-0.3-600 and ZnCoMo-0.6-600 molybdates.

Fig. 5a .

 5a Fig. 5a. SEM micrographs of ZnCoMo-0.3-T powder obtained at: (a) 600 °C, (b) 700 °C and (c) 800 °C.

Fig. 5b .

 5b Fig.5b. SEM micrographs of ZnCoMo-0.6-T powder obtained at: (a) 600 °C, (b) 700 °C and (c) 800 °C.

Fig. 5c .

 5c Fig. 5c. SEM -FEG micrographs of ZnCoMo-0.3-T powder obtained at: (a) 700 °C and (b) 800 °C.

Fig. 6 .

 6 Fig. 6. Particle sizes distribution calculated from multiple SEM images of ZnCoMo-0.3-700 powder.

Fig. 7 .

 7 Fig. 7. TEM micrographs of ZnCoMo-0.3-T powder prepared in acid medium at: (a) 600 °C, (b) 700 °C and (c) 800 °C.

Fig. 8 .

 8 Fig. 8. Evolution and growth of crystallite size of ZnCoMo-x-600 compounds deduced from the Scherrer equation using XRD line broadening, as a function of Co 2+ (x) rates 0 ≤ x ≤ 1.

Fig. 9 .

 9 Fig. 9. SEM micrographs of (a) ZnCoMo-0.3-T and (b) ZnCoMo-0.6-T compounds synthesized in acid and basic pH at 600 and 700 °C.

Fig. 10 .

 10 Fig. 10. Shades of the blue/purple colors and diffuse reflectance spectra of ZnCoMo-0.3-700 and ZnCoMo-0.6-700 powders.

Fig. 11 .

 11 Fig. 11. Plot of (hʋα) 2 as a function of hʋ (direct transition) of molybdate ZnCoMo-1-700.

Fig. 12 .Fig. 13 .

 1213 Fig. 12. Evolution of the color parameters of ZnCoMo-0.2-T and ZnCoMo-0.3-T pigments as a function of temperature.

  1-x Co x MoO 4 (0 ≤ x ≤ 1) ultrafine powder began with mixing metal nitrates: zinc nitrate Zn(NO 3 ) 2 ⋅6H 2 O (98.0%, Sigma Aldrich), cobalt nitrate Co(NO 3 ) 2 ⋅6H 2 O (99.0%, Sigma Aldrich) and ammonium heptamolybdate (NH 4 ) 6 Mo 7 O 24 , 4H

  [START_REF] Amiri | Caffeine: A novel green precursor for synthesis of magnetic CoFe 2 O 4 nanoparticles and pH-sensitive magnetic alginate beads for drug delivery[END_REF]

Table 1

Specific surface area measurements for ZnCoMo-0.3-T and ZnCoMo-0.6-T powders at different temperature.

Table 2

Grain size of ZnCoMo-0.3-600 and ZnCoMo-0.6-600 powders prepared in acid and basic medium.

Table 3

Optical band gaps (Eg) of ZnCoMo-x-700 (x= 0, 0.3, 0.6 and 1) powders.

Samples Band gap Eg (eV)

ZnCoMo-0-700

4.03

ZnCoMo-0.3-700

3.28

ZnCoMo-0.6-700

2.47

ZnCoMo-1-700

2.15


text:
Youssef El Jabbar
email: ysf.eljabbar@gmail.com

Hind Lakhlifi

Rachida El Ouatib

Lahcen Er-Rakho

Sophie Guillemet-Fritsch

Bernard Durand

Synthesis of cobalt aluminate spinel by sol-gel process: Investigation of starting reagents and precursors obtained after pyrolysis

Keywords:

In this study, cobalt aluminate was prepared by a sol-gel method. XRD and FTIR analyses of the precursors obtained at 300 • C for 12 h revealed that the type of complexing agent used in the synthesis affects the pyrolysis step. An amorphous phase was obtained by using citric acid as the complexing agent. A beginning of crystallization was observed by using complexing agents such as polyacrylic acid and glycine. The structural investigation of the starting reagents revealed that the observed lines exhibit characteristics of Co 3 O 4 derived from cobalt nitrate. The crystallinity of the samples increased with the increase in the annealing temperature, with no effect observed by the change in the complexing agent. The appearance of the (331) reflection for the heat-treated powders was characteristic of the blue spinel compound.

Specifications table

Cobalt and aluminium nitrates were mixed with stoichiometric proportions and then poured in excess into the solution of the complexing agents. The pH of the obtained mixture was adjusted to neutral by using ammonia. Evaporation, drying, pyrolysis and calcination processes allowing to produce the CoAl 2 O 4 precursors Data accessibility Data is available with this article

Rationale

Cobalt aluminate spinel is an inorganic pigment that is typically represented by the chemical formula Co 2+ Co 3+

x Al 2x O 4 , where x = 0-2. This variation permits the possibility of obtaining different forms of the spinel structure, viz. a normal, an inverse or a mixed structure. The normal spinel structure of CoAl 2 O 4 is known for its blue colour. The inverse or mixed structure can exhibit different colours, and it changes from dark green and turquoise to blue depending on the replacement amount of Co 2+ , Al 3+ and Co 3+ in the tetrahedral and octahedral sites [START_REF] Franco | Cation distributions on CoAl 2 O 4 and Co 2 AlO 4 spinels: pressure and temperature effects[END_REF][START_REF] Serment | The versatile Co 2+ /Co 3+ oxidation states in cobalt alumina spinel: how to design strong blue nanometric pigments for color electrophoretic display[END_REF][START_REF] Jabbar | Structure, microstructure, optical and magnetic properties of cobalt aluminate nanopowders obtained by sol-gel process[END_REF][START_REF] Zhu | Engineered Co 2 AlO 4 /CoAl 2 O 4 @Al 2 O 3 monolithic catalysts for peroxymonosulfate activation: Co 3+ /Co 2+ and O Defect/OLattice ratios dependence and mechanism[END_REF]. The blue spinel of cobalt has attracted significant attention as a colouring agent in glaze and bulk tile compositions due to its superior properties, such as chemical and thermal stability as well as colour stability [START_REF] Tang | Effects of colouration mechanism and stability of CoAl 2 O 4 ceramic pigments sintered on substrates[END_REF][START_REF] Obata | Synthesis of nano CoAl 2 O 4 pigment for ink-jet printing to decorate porcelain[END_REF][START_REF] Song | Fabrication and stability of CoAl 2 O 4 ceramic pigment for 3D printing[END_REF][START_REF] Xiaojin | Environmental blue CoAl 2 O 4 pigment co-doped by Zn 2+ and Mg 2+ : synthesis, structure and optical properties[END_REF][START_REF] Abhishek | Structural and magnetic properties of Eu 3+ substituted Mg-Cd nanoferrites: a detailed study of influence of high energy γ-rays irradiation[END_REF]. Furthermore, CoAl 2 O 4 nanoparticles exhibit good photocatalytic activity for the degradation of textile dyes [START_REF] Jabbar | Photocatalytic degradation of navy blue textile dye by nanoscale cobalt aluminate prepared by polymeric precursor method[END_REF][START_REF] Boudiaf | Synthesis and characterization of semiconductor CoAl 2 O 4 for optical and dielectric studies: application to photodegradation of organic pollutants under visible light[END_REF].

Researchers have paid particular attention to the synthesis of cobalt aluminate systems via the investigation of preparation methods, processing control and firing temperatures [START_REF] Mindru | A new approach: Synthesis of cobalt aluminate nanoparticles using tamarind fruit extract[END_REF][START_REF] Liu | Synthesis of sodium polyacrylate copolymers as water-based dispersants for wet ultrafine grinding of cobalt aluminate particles[END_REF][START_REF] He | Preparation of porous cobalt aluminate and its chromogenic mechanism[END_REF][START_REF] Chueachot | Synthesis and optical properties of blue pigment CoAl 2 O 4 nanofibers by electrospinning[END_REF]. The solid-state reaction method is the most widely used synthesis for cobalt aluminate systems, which involves the reaction of cobalt-and aluminium-based precursors. For example, cobalt oxide, cobalt hydroxide or others as a source of cobalt and aluminium oxide as a source of aluminium are used. The precursors are mixed in a stoichiometric amount followed by heat treatment at a minimum temperature of >1200 • C, affording cobalt aluminate [START_REF] Yoneda | Solid-state synthesis and characterization of cobalt blue core-shell pigment particles[END_REF][START_REF] Salem | Effect of synthesis condition of cobalt-aluminate nano-sized powder on melting behaviour of transparent glaze[END_REF][START_REF] Peymannia | Production of a stable and homogeneous colloid dispersion of nano CoAl 2 O 4 pigment for ceramic ink-jet ink[END_REF]. This method can be easily implemented and does not require a considerable amount of reagents. However, it generally affords powders with a poor homogeneity and a low specific surface. Other synthesis methods, such as the sol-gel route, co-precipitation, combustion method and the hydrothermal route, have been developed to produce a powder of a good homogeneity and high purity at low temperature, with large specific surfaces [START_REF] Wang | High-performance spherical urchin-like CoAl 2 O 4 pigments prepared via microemulsionhydrothermal-precipitation method[END_REF][START_REF] Roniboss | Investigation of structural, optical and magnetic behavior of MAl 2 O 4 (M= Zn and Co) nanoparticles via microwave combustion technique[END_REF][START_REF] Han | Physical properties of MgAl 2 O 4 , CoAl 2 O 4 , NiAl 2 O 4 , CuAl 2 O 4 , and ZnAl 2 O 4 spinels synthesized by a solution combustion method[END_REF][START_REF] Jabbar | Green nanoceramic pigments based on cobalt chromite doped with Al: Synthesis, characterisation and colour performance[END_REF][START_REF] Mohammed | Preparation and investigation of the structural properties of α-Al 2 O 3 nanoparticles using the sol-gel method[END_REF].

Several factors have been considered to optimize the synthesis parameters. In previously reported studies, our group has reported the effect of the variation in pH for the synthesis and type of complexing agent on the texture of the powders obtained after heat treatment. These studies have reported that synthesis conducted in a neutral medium and using polyacrylic acid as the complexing agent leads to nanocrystalline CoAl 2 O 4 spinel powder [START_REF] Jabbar | Structure, microstructure, optical and magnetic properties of cobalt aluminate nanopowders obtained by sol-gel process[END_REF][START_REF] Jabbar | Influence of temperature and pH on the morphology and the color of the CoAl 2 O 4 prepared by sol gel method[END_REF]. In this study, particular attention was focused on the starting reagents and effect of chelating agents on the pyrolysis step during sol-gel synthesis.

Procedure

The synthesis of the cobalt aluminate powder starts by mixing metal nitrates in stoichiometric proportions and pouring them into a solution containing an excess amount of complexing and chelating agents. Three samples were prepared using polyacrylic acid, glycine and citric acid as the complexing agents. The pH of the obtained solution was adjusted to neutral by using ammonia and subsequently heating to 80 • C on a hotplate, affording a viscous gel. The gel was further dried in an oven at 120 • C for 24 h, affording a xerogel. This xerogel was subsequently ground using an agate mortar and then placed in a muffle furnace adjusted to 300 • C for 12 h. The precursors obtained after pyrolysis by using different complexing agents were analysed by X-ray diffraction (XRD) and Fourier infrared (FTIR) spectroscopy. By annealing, cobalt aluminate powder was obtained. Fig. 1 shows the schematic of the synthesis process.

Data, value and validation

Table 1 summarizes the characteristics of the reagents used in the synthesis. The metal nitrates were analysed and investigated individually by thermal analysis (TGA-DTA), XRD and FTIR analyses to study the thermal behaviour of the reagents used to prepare CoAl 2 O 4 oxide.

Study of starting reagents: Co

(NO 3 ) 2 •nH 2 O
Thermogravimetric analysis (TGA) and differential thermal analysis (DTA) of hydrated cobalt nitrate (Fig. 2) revealed a total weight loss of ~74.3% in two steps: ■ The first weight loss of ~72.5% is observed at temperatures of less than 300 • C accompanied by endothermic effects, corresponding to the dehydration and loss of nitrogen oxide. ■ The second weight loss of of ~1.8%, accompanied by an endothermic peak, is observed at ~925 • C, corresponding to the partial transformation of cobalt oxide Co 3 O 4 into cobalt monoxide CoO according to the following reaction [START_REF] Ehrhardt | Thermal decomposition of cobalt nitrato compounds: preparation of anhydrous cobalt(II)nitrate and its characterisation by Infrared and Raman spectra[END_REF]:

Co 3 O 4 ↔ 3CoO + 1 / 2O 2 (Eq. 1)
The XRD diffractograms of the hydrated cobalt nitrate samples subjected to calcination at 300 • C, 500 • C and 900 • C revealed the sole formation of the oxide Co 3 O 4 (JCPDS n • 76-1802), while the XRD spectrum of the sample subjected to calcination at 1100 • C revealed a mixture of Co 3 O 4 and CoO oxides (Fig. 3). Fig. 4 shows the FTIR spectra of the powders obtained after the calcination of The water content in hydrated cobalt nitrate sample used for synthesis is determined by its number of water molecules (n). TGA analysis (Fig. 2) revealed a weight loss of 72.5% in the temperature range of 40-200 • C. From the XRD spectra (Fig. 3), the lines observed for the sample subjected to calcination at 300 • C are characteristic of Co 3 O 4 . Therefore, the following decomposition reaction can be assumed [START_REF] Ehrhardt | Thermal decomposition of cobalt nitrato compounds: preparation of anhydrous cobalt(II)nitrate and its characterisation by Infrared and Raman spectra[END_REF]:

3(Co(NO 3 ) 2 , nH 2 O) ̅̅̅̅̅̅̅→ 30-300 ∘ c Co 3 O 4 +3nH 2 O + 6NO 2 + O 2 (Eq. 2)
From this equation, which is based on TGA and XRD analyses, the experimental number n is calculated to be 6.06.

Study of starting reagents: Al

(NO 3 ) 2 •nH 2 O
Thermal analysis (DTA-TGA) of hydrated aluminium nitrate used in the synthesis revealed a total weight loss of ~86% (Fig. 5). DTA The n values were calculated on the basic of TGA-DTA and XRD analyses. In fact, for a weight loss of 86% in the temperature range of 40-900 • C and from XRD diagrams (Fig. 6), the following decomposition reaction can occur [START_REF] Pacewska | Thermal transformations of aluminium nitrate hydrate[END_REF]:

2(Al(NO 3 ) 3 , nH 2 O) → Al 2 O 3 +2nH 2 O + 6NO 2 +3 / 2O 2 (Eq. 3)
The calculated n value from experiments is 9.15. Table 2 lists the numbers of molecules of water hydration (n) of the metal nitrates. The numbers calculated on the basis of TGA-DTA and XRD analyses are extremely similar to those provided by the suppliers.

Synthesis of CoAl 2 O 4 : Effect of the complexing agent on the precursors obtained after pyrolysis

The XRD diffractograms of the precursors obtained by using glycine and polyacrylic acid as the complexing agents revealed lines characteristic of a spinel phase (Fig. 7 (a)). FTIR spectra revealed two absorption bands at around 576 (υ 1 ) and 661(υ 2 ) cm -1 ; which originate from the stretching vibrations of the metal-oxygen bond and confirm the formation of Co 3 O 4 spinel oxide. The υ 1 band is characteristic of OB 3 (where B denotes the Co 3+ in the octahedral hole) vibration and the υ 2 band is attributable to the ABO 3 (where A denotes the Co 2+ in the tetrahedral hole) vibration in the spinel lattice [START_REF] Th | Direct fabrication of cobalt oxide nano-particles employing glycine as a combustion fuel[END_REF][START_REF] Abu-Zied | Nitrous oxide decomposition over MCO 3 -Co 3 O 4 (M = Ca, Sr, Ba) catalysts[END_REF]. In the case of citric acid, the XRD spectrum revealed an amorphous phase, and IR absorption bands are not observed in the range specific for oxides (Fig 7(b)). The IR absorption band observed at ~1610 cm -1 corresponds to the carboxylic groups resulting from citrates during pyrolysis. This result can be explained by incomplete decomposition. The bands observed between 1400 and 1500 cm -1 for the three precursors correspond to the nitrate ions (NO 3 -) [START_REF] Wahba | Flower-like morphology of blue and greenish-gray ZnCo x Al 2-x O 4 nanopigments[END_REF][START_REF] Castro | FTIR and Raman spectra and structure of Cu(NO 3 ) + in aqueous solution and acetone[END_REF].

Synthesis of CoAl 2 O 4 : heat-treatment

The powders obtained at 300 • C for 12 h (pyrolysis) were subjected to heat treatment at 500 and 900 • C. The obtained diffractograms revealed that the intensity of XRD patterns increases with the increase in temperature, indicative of the evolution of the crystallinity of the powders (Fig. 8). The pure cobalt aluminate phase is characterized by the appearance of the (331) reflection [START_REF] Peymannia | Production of a stable and homogeneous colloid dispersion of nano CoAl 2 O 4 pigment for ceramic ink-jet ink[END_REF][START_REF] Zha | Positive effects of Al 3+ partially substituted by Co 2+ cations on the catalytic performance of Co 1+x Al 2-x O 4 (x = 0-0.2) for methane combustion[END_REF][START_REF] Wang | Synthesis of cobalt-aluminate spinels via glycine chelated precursors[END_REF][START_REF] Visinescu | The environmentally benign synthesis of nanosized Co x Zn 1-x Al 2 O 4 blue pigments[END_REF]. The synthesis conditions (including type of complexing agent, calcination temperature, synthesis pH) were examined and applied in our recent study [START_REF] Jabbar | Structure, microstructure, optical and magnetic properties of cobalt aluminate nanopowders obtained by sol-gel process[END_REF][START_REF] Mohammed | Preparation and investigation of the structural properties of α-Al 2 O 3 nanoparticles using the sol-gel method[END_REF]. Results revealed that the cobalt aluminate oxide is obtained at 900 • C whatever the pH and the nature of the complexing agent used. The synthesis process of cobalt aluminate spinel can be represented as:

Co(NO 3 ) 2 (aq)+Al(NO 3 ) 3 (aq) ̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅→ complexingagent-AmmoniaDrying-Pyrolysis-Heattreatment CoAl 2 O 4 (s)+gaseousproducts (Eq. 4)

Conclusion

The characterization of the starting reagents responsible for the formation of CoAl 2 O 4 strengthens the investigation into the effect of the change of complexing agents at the pyrolysis stage. By the mixing of nitrates in the presence of citric acid as the complexing agent with the addition of ammonia for pH adjustment, followed by pyrolysis, an amorphous phase is obtained, which can be explained by the incomplete decomposition of the organic constituents. However, by using glycine and polyacrylic acid, the start of crystallization, with lines characteristic of cobalt oxide, is observed. Subsequent heat treatment affords cobalt aluminate (Eqs. ( 1)-( 4)).

Fig. 1 .

 1 Fig. 1. The schematic illustration of synthesis of cobalt aluminate powder by sol-gel synthesis.

Fig. 2 .

 2 Fig. 2. DTA and TGA curves of hydrated cobalt nitrate (Co(NO 3 ) 2 •nH 2 O).

Fig. 3 .

 3 Fig. 3. X-ray diffraction patterns of cobalt nitrate calcined at 300 • C, 500 • C, 900 • C and 1100 • C.

Fig. 4 .

 4 Fig. 4. FTIR infrared spectra of cobalt nitrate calcined at 300 • C, 500 • C, 900 • C and 1100 • C.

Fig. 5 .

 5 Fig. 5. DTA and TGA curves of hydrated aluminium nitrate.

Fig. 6 .

 6 Fig. 6. XRD diffractograms of calcined aluminium nitrate at 300 • C, 500 • C, 900 • C and 1100 • C

Fig. 7 .

 7 Fig. 7. (a) XRD patterns and (b) FTIR analysis of the precursors obtained after pyrolysis

Fig. 8 .

 8 Fig. 8. XRD patterns of the samples obtained after pyrolysis and heat-treated at 500 • C and 900 • C.

  Co(NO 3 ) 2 •6H 2 O, Al(NO 3 ) 3 •9H 2 O, C 6 H 8 O 7 •H 2 O, (C 3 H 4 O 2 ) n , H 2 NCH 2 CO 2 H.

	Subject area	Materials science, soft chemistry, sol-gel
	Compounds CoAl 2 O 4 , Data category Synthesised, spectral and experimental.
	Data acquisition	TGA-DTA, XRD, FTIR.
	format
	Data type	Experimental and analysed.
	Procedure

Table 1

 1 Characteristics of the reagents used for the synthesis.

	Chemical reagents	Molecular Weight (g/mol)	Assay (purity)	Manufacturer	Concentrations and molar ratios used in the synthesis
	Cobalt nitrate, Co(NO 3 ) 2 •6H 2 O	291.03	99.0 %		Sigma Aldrich	0.2M
	Aluminium nitrate, Al(NO 3 ) 3 •9H 2 O Glycine, H 2 NCH 2 CO 2 H (Gly)	375.13 75.07	99.0 % 99.0 %		Sigma Aldrich Aldrich	0.2M Gly/NO 3 ¡ =2/3
	Citric acid, C 6 H 8 O 7 H 2 O (CA)	210.14	99.5%		Panreac	CA/cations=3
	Polyacrylic acid, (C 3 H 4 O 2 ) n (PAA)	1800	99.0 %		Sigma Aldrich	10 wt%

Table 2

 2 Numbers of water molecules in the hydrated salts used in the synthesis.

	Hydrated salts	n experimental	n indicated on the bottle label
	Co(NO 3 ) 2 •nH 2 O	6.06	6
	Al(NO 3 ) 3 •nH 2 O	9.15	9

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.