domain: chim phys

text:
Lucile Magnier

Garance Cossard

Vincent Martin

Céline Pascal

Virginie Roche

Eric Sibert

Irina Shchedrina

Richard Bousquet

Valérie Parry

Marian Chatenet

Fe-Ni-based alloys as highly active and low-cost oxygen evolution reaction catalyst in alkaline media

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Global warming calls for renewable electricity, which hydrogen, ideally produced via water electrolysis, can efficiently store [START_REF] Lewis | Powering the planet: Chemical challenges in solar energy utilization[END_REF][START_REF] Cook | Solar energy supply and storage for the legacy and nonlegacy worlds[END_REF]. The slow-kinetics oxygen evolution reaction (OER) that occurs in water electrolysers induces efficiency-loss in operation and high cell voltage [START_REF] Jiao | Design of electrocatalysts for oxygen-and hydrogen-involving energy conversion reactions[END_REF][START_REF] Ayers | Perspectives on low-temperature electrolysis and potential for renewable hydrogen at scale[END_REF]. Although IrO2 is often employed as the reference OER electrocatalyst [START_REF] Mccrory | Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction[END_REF][START_REF] Walter | Solar Water splitting cells[END_REF][START_REF] Matsumoto | Electrocatalytic properties of transition metal oxides for oxygen evolution reaction[END_REF], more sustainable, active, stable and Earth-abundant catalysts must be developed: NiFe-based oxo-hydroxides (Ni1-xFexOOH) [START_REF] Gong | An advanced Ni-Fe layered double hydroxide electrocatalyst for water oxidation[END_REF][START_REF] Louie | An investigation of thin-film Ni-Fe oxide catalysts for the electrochemical evolution of oxygen[END_REF][START_REF] Trotochaud | Solution-cast metal oxide thin film electrocatalysts for oxygen evolution[END_REF][START_REF] Trotochaud | Nickel-iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation[END_REF][START_REF] Corrigan | The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes[END_REF][START_REF] Dionigi | NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes[END_REF][START_REF] Görlin | Oxygen evolution reaction dynamics, faradaic charge efficiency, and the active metal redox states of Ni-Fe oxide water splitting electrocatalysts[END_REF][START_REF] Song | Transition metal oxides as electrocatalysts for the oxygen evolution reaction in alkaline solutions: an application-inspired renaissance[END_REF] are usable in alkaline water electrolysers [START_REF] Colli | Non-precious electrodes for practical alkaline water electrolysis[END_REF][START_REF] Brauns | Alkaline water electrolysis powered by renewable energy: a review[END_REF][START_REF] Marini | Advanced alkaline water electrolysis[END_REF], their Fe/Ni ratio determining activity, the optimum being 10-50 at.% Fe (0.11 < Fe/Ni ratio < 1) [START_REF] Louie | An investigation of thin-film Ni-Fe oxide catalysts for the electrochemical evolution of oxygen[END_REF][START_REF] Dionigi | NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes[END_REF][START_REF] Friebel | Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting[END_REF][START_REF] Klaus | Effects of Fe electrolyte impurities on Ni(OH)2/NiOOH structure and oxygen evolution activity[END_REF]. The active-sites' nature in Ni1-xFexOOH remains debated [START_REF] Dionigi | NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes[END_REF][START_REF] Song | Transition metal oxides as electrocatalysts for the oxygen evolution reaction in alkaline solutions: an application-inspired renaissance[END_REF]: Fe atoms [START_REF] Friebel | Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting[END_REF][START_REF] Klaus | Effects of Fe electrolyte impurities on Ni(OH)2/NiOOH structure and oxygen evolution activity[END_REF][START_REF] Enman | Effects of intentionally incorporated metal cations on the oxygen evolution electrocatalytic activity of nickel (oxy)hydroxide in alkaline media[END_REF][START_REF] Mirabella | Ni-modified Fe3O4(001) surface as a simple model system for understanding the oxygen evolution reaction[END_REF], Ni atoms [START_REF] Louie | An investigation of thin-film Ni-Fe oxide catalysts for the electrochemical evolution of oxygen[END_REF][START_REF] Wang | Deciphering the exceptional performance of NiFe hydroxide for the oxygen evolution reaction in an anion exchange membrane electrolyzer[END_REF][START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF][START_REF] Diaz-Morales | The importance of nickel oxyhydroxide deprotonation on its activity towards electrochemical water oxidation[END_REF] or a synergy between Ni and Fe sites were proposed to explain the impressive OER performances of Ni1-xFexOOH [START_REF] Görlin | Oxygen evolution reaction dynamics, faradaic charge efficiency, and the active metal redox states of Ni-Fe oxide water splitting electrocatalysts[END_REF][START_REF] Qiu | Direct observation of active catalyst surface phases and the effect of dynamic self-optimization in NiFe-layered double hydroxides for alkaline water splitting[END_REF]; for Burke et al., Fe atoms in a Ni oxo-hydroxide matrix are the active-sites, the matrix providing electrical conductivity, Fe chemical stability and large active surface area support [START_REF] Burke | Oxygen evolution reaction electrocatalysis on transition metal oxides and (oxy)hydroxides: activity trends and design principles[END_REF]. Co-precipitation, homogeneous precipitation or electrodeposition on a substrate enable to synthesize Ni1-xFexOOH electrocatalysts of tailored crystal-size and morphology [START_REF] Dionigi | NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes[END_REF]. The electrocatalyst stability and lifetime depending on its adherence on the support [START_REF] Spöri | The stability challenges of oxygen evolving catalysts: towards a common fundamental understanding and mitigation of catalyst degradation[END_REF][START_REF] Maljusch | Advanced evaluation of the long-term stability of oxygen evolution electrocatalysts[END_REF][START_REF] Zeradjanin | Rational design of the electrode morphology for oxygen evolution -enhancing the performance for catalytic water oxidation[END_REF], carbon substrate [START_REF] Gong | An advanced Ni-Fe layered double hydroxide electrocatalyst for water oxidation[END_REF][START_REF] Andronescu | Powder catalyst fixation for post-electrolysis structural characterization of NiFe layered double hydroxide based oxygen evolution reaction electrocatalysts[END_REF] was considered, but is not industrially viable, owing to its inherent OER instability [START_REF] Lafforgue | Degradation of carbonsupported platinum-group-metal electrocatalysts in alkaline media studied by in situ fourier transform infrared spectroscopy and identical-location transmission electron microscopy[END_REF][START_REF] Möller | Online monitoring of electrochemical carbon corrosion in alkaline electrolytes by differential electrochemical mass spectrometry[END_REF]. Commercial stainless steels containing Fe and Ni can be activated by high-current (1770 mA.cm -2 ) application in aggressive electrolyte (7.2 M NaOH at 50°C) [START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF], high/low potential steps in 5 M LiOH or KOH at 25°C [START_REF] Moureaux | Development of an oxygenevolution electrode from 316L stainless steel: application to the oxygen evolution reaction in aqueous lithium-air batteries[END_REF][START_REF] Moureaux | Timely-activated 316L stainless steel: A low cost, durable and active electrode for oxygen evolution reaction in concentrated alkaline environments[END_REF] or in situ activation at 75°C under constant current (30 mA.cm -2 ) in 1 M KOH [36], to form a surface layer capable of self-healing, hence enabling long-term stability [START_REF] Moureaux | Development of an oxygenevolution electrode from 316L stainless steel: application to the oxygen evolution reaction in aqueous lithium-air batteries[END_REF][START_REF] Moureaux | Timely-activated 316L stainless steel: A low cost, durable and active electrode for oxygen evolution reaction in concentrated alkaline environments[END_REF] and high OER activity, as reported for stainless steels AISI 316L [START_REF] Moureaux | Development of an oxygenevolution electrode from 316L stainless steel: application to the oxygen evolution reaction in aqueous lithium-air batteries[END_REF][START_REF] Moureaux | Timely-activated 316L stainless steel: A low cost, durable and active electrode for oxygen evolution reaction in concentrated alkaline environments[END_REF], AISI 304 [START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF], AISI 316, AISI 303 and AISI 310S [36,[START_REF] Todoroki | Nanostructures and oxygen evolution overpotentials of surface catalyst layers synthesized on various austenitic stainless steel electrodes[END_REF]. The alloys composition (AISI 310S, AISI 316 and AISI 303, with a Fe/Ni ratio of 2.82, 6.90 and 8.26, respectively) critically influences the materials' OER activity [START_REF] Todoroki | Nanostructures and oxygen evolution overpotentials of surface catalyst layers synthesized on various austenitic stainless steel electrodes[END_REF], steel electrodes showing better OER activity than pure Ni and pure Fe; activated AISI 304 shows optimal performance with an ultra-thin film composed of Ni0.67Fe0.33 (Fe/Ni ratio = 0.49) [START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF].

Herein, the activation method developed by Moureaux et al. [START_REF] Moureaux | Development of an oxygenevolution electrode from 316L stainless steel: application to the oxygen evolution reaction in aqueous lithium-air batteries[END_REF][START_REF] Moureaux | Timely-activated 316L stainless steel: A low cost, durable and active electrode for oxygen evolution reaction in concentrated alkaline environments[END_REF] was applied to five Fe-and Ni-based alloys with a Fe/Ni ratio ranging from 0.004 to 7.4 on wire and plate samples, to determine how alloy composition and manufacturing affect OER activity, measured at initial state, after aging and after activations. The active-layer was characterized using transmission electron microscopy coupled with X-Ray energy dispersive spectrometry (TEM-EDS), orientation and phase mapping transmission electron microscopy (TEM-ASTAR), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). The surface Fe/Ni ratio is a key parameter; its evolution during aging and activation drives the OER performance, together with an increase in Ni III /Ni II capacity (active-layer growth), which enables to unveil the active-sites' nature and the synergy between Fe and Ni atoms. Durability studies further demonstrate that such activated surfaces are robust for long-term OER.

RESULTS

Comparison of different grades at initial state

Five alloys, either austenitic stainless steels or Ni-based alloys were evaluated for OER. XRD evidenced different preferential grain orientations between wires (W) and plates (P) (Fig. S1). The alloy compositions in major elements (Fe, Ni, Cr, Mo, Nb) cover a range of Fe/Ni ratio between 0 and 7.4 (Table S1). S1). OER potentials for wires and plates (c) after polishing, (d) after aging, (e) after activations. Potentials are measured at a current density of 5 mA.cm -2 from Supplementary Figs. S2a to S8a. The differences between the highest and lowest potentials are plotted on the right of each graph after polishing (pink), after aging (green) and after activations (orange). (f) Evolution of the Ni III /Ni II reaction capacity for each grade after polishing, after aging and after activations. The value is calculated from the integration of the Ni III /Ni II reduction peak of the CV scans in Supplementary Figs. Electrochemical measurements: effects of Fe-content, manufacturing process and surface preparation Fig. 1a reports the CV scans performed on polished wires (for plates, see Figs. S2a andS3a). Oxidation (1.35-1.5 V vs RHE) and reduction (1.3-1.45 V vs RHE) peaks attributed to the Ni II /Ni III transitions (Ni(OH)2/NiOOH [START_REF] Louie | An investigation of thin-film Ni-Fe oxide catalysts for the electrochemical evolution of oxygen[END_REF][START_REF] Moureaux | Development of an oxygenevolution electrode from 316L stainless steel: application to the oxygen evolution reaction in aqueous lithium-air batteries[END_REF]36,[START_REF] Kostecki | Electrochemical and in situ raman spectroscopic characterization of nickel hydroxide electrodes: I. Pure nickel hydroxide[END_REF][START_REF] Lyons | The oxygen evolution reaction on passive oxide covered transition metal electrodes in aqueous alkaline solution. Part 1-Nickel[END_REF]) confirm the presence of surface Ni oxohydroxide. Their positions depend on the alloys' Fe-content (Fig. 1b): increasing Fe-contents up to 35.3 at.% positively-shifts the Ni III /Ni II reduction peak [START_REF] Louie | An investigation of thin-film Ni-Fe oxide catalysts for the electrochemical evolution of oxygen[END_REF][START_REF] Trotochaud | Nickel-iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation[END_REF][START_REF] Corrigan | The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes[END_REF][START_REF] Görlin | Oxygen evolution reaction dynamics, faradaic charge efficiency, and the active metal redox states of Ni-Fe oxide water splitting electrocatalysts[END_REF][START_REF] Wang | Deciphering the exceptional performance of NiFe hydroxide for the oxygen evolution reaction in an anion exchange membrane electrolyzer[END_REF][START_REF] Todoroki | Nanostructures and oxygen evolution overpotentials of surface catalyst layers synthesized on various austenitic stainless steel electrodes[END_REF]. For higher Fecontent, up to 70.5 at.%, the reduction peak potential is stable [START_REF] Görlin | Oxygen evolution reaction dynamics, faradaic charge efficiency, and the active metal redox states of Ni-Fe oxide water splitting electrocatalysts[END_REF].

The OER slope (above 1.5 V vs RHE, Fig. 1a) reflects a variation in OER overpotential (Fig. 1c). The materials' OER performance (potential at J = 5 mA.cm -2 , from Figs. S2.a to S8.a) depends on the bulk Fe-content (Figs. 1c-e). For polished surfaces, Fig. 1c, the grade greatly influences performance: W-625 (1.66±0.03 V vs RHE) and W-825 (1.56±0.01 V vs RHE) exhibit the highest and lowest potential, respectively. As reported by Dionigi and Strasser's [START_REF] Dionigi | NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes[END_REF] for NiFe-based oxo-hydroxides [START_REF] Louie | An investigation of thin-film Ni-Fe oxide catalysts for the electrochemical evolution of oxygen[END_REF][START_REF] Corrigan | The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes[END_REF][START_REF] Dionigi | NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes[END_REF][START_REF] Friebel | Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting[END_REF][START_REF] Mirabella | Ni-modified Fe3O4(001) surface as a simple model system for understanding the oxygen evolution reaction[END_REF][START_REF] Li | Nickel based electrocatalysts for oxygen evolution in high current density, alkaline water electrolysers[END_REF], grades with 21.76 < Fe-content < 35.3 at.% yield the highest OER activity (Fig. 1c). 2.5 hour-aging at open circuit voltage (OCV) in the electrolyte (Fig. 1d) drastically decreases the OER potential of Fe-poor grades (W-625 and P-625), by 0.08 and 0.06 V respectively, and (slightly) improves the performance of other grades, hence homogenizing performance among all. Activations (alternated high/low potentials) further reduce the OER potential (Fig. 1e), the lowest potential being recorded for P-825 (1.53±0.01 V vs RHE). All grades tend towards similar OER potential after activations, insignificant variation being observed between wires and plates.

The Ni III /Ni II peaks coulometry (capacity, Fig. 1f) scales with the grade's initial Ni-content: W-316L, of smallest Ni-content (9.53 at.% Ni, Table S1), has the lowest initial capacity (0.06±0.01 mC.cm -2 ); W-625 (65.6 at.% Ni) has the highest (1.5±0.4 mC.cm -2 ). The capacity increases with aging and activations. The Ni III /Ni II capacity-normalized current-density (Figs. S2.b to S8.b) reflects changes in Ni active-site performance, assuming Ni III is the OER active-site [START_REF] Moureaux | Development of an oxygenevolution electrode from 316L stainless steel: application to the oxygen evolution reaction in aqueous lithium-air batteries[END_REF]. The measured potential at given OER current-density (E(Jnormed)) decreases when the sites efficiency increases at constant active-sites number, as for W-625 and P-625 (Fig. 1g). For other grades, E(Jnormed) increases or is constant, suggesting decreased or stable active-site efficiency.

After aging and activations, the alloys' catalytic performance improved; activated Fe-Ni-alloys outperform commercial IrO2 (Figs. 1h andS9). The overpotential related to the electrochemical surface area (ECSA), which denotes the number of active sites (η-ECSA in Table 1), demonstrates the real interest of our surfaces; they outperform many materials from the literature in terms in "intrinsic OER activity". When the ECSA (Table 1) is large (high roughness), the complete surface cannot be efficiently used for OER, resulting in smaller apparent turnover frequency. The Fe-Ni alloys were submitted to long-term polarization (Fig. S10.a) and highly intensive potential cycling (accelerated stress test (AST), Fig. S10.b-g): 20 000 cycles at 1 V.s -1 between 0.5 and 1.8 V vs RHE). Overall, the durability tests of Fig. S10 The faradaic efficiency towards OER was evaluated for the Fe-Ni alloys. Two complementary techniques were used, the rotating ring-disk electrode (RRDE) to directly measure the evolved O2 and inductively-coupled plasma mass-spectrometry (ICP-MS) analyses, to dose potential metal dissolution in the electrolyte. From the results presented in Figs. S12-S13 (RRDE) and Table S2 (ICP-MS), consequent metal dissolution from the alloys can be ruled out. This means that, whatever the Fe-Ni alloy considered, the oxidation current measured upon OER CVs nearfully originates from oxygen evolution, once the active layer is formed on the alloy surface.

(Micro)structural characterisation of the active-surface-layer

The active-surface-layer developed at the alloy/electrolyte interface after polishing, aging and activations is presented in Figs. 2a-d. W-316L, of lowest Ni-content, has the thinnest activesurface-layer: 9.4±2.0 nm (Fig. 2a). This agrees with the weak Ni III /Ni II capacity increase after aging and activations (Fig. 1f, 1.0±0.4 mCcm -2 after activations), reflecting the low amount of Ni active-sites. W-825 (Fig. 2b) and W-718 (Fig. 2c) have active-surface-layers of 20.3±5.4 and 34.3±6.3 nm, respectively, in line with their larger Ni III /Ni II capacity (2.6±0.4 and 3.6±0.1 mC.cm -2 ). W-825 and W-718, have variable active-surface-layer thickness, with maximal deviation from the average of 15.1 nm and 17.7 nm, respectively. W-625 has thicker activesurface-layer (38.8±2.7 nm, Fig. 2d), which coincides with its large capacity 11±3 mC.cm -2 . Both P-625 and P-825 have a fcc bulk structure (grazing incidence X-ray diffraction (GI-XRD) after polishing, Fig. 2e). Additional small/wide peaks appear with the active-surface-layer formation, (GI-XRD after activations, Fig. 2e) the bulk fcc peaks remaining (thin oxide-layer).

Comparison with theoretical α-Ni(OH)2, β-Ni(OH)2, NiFe LDH and NiO peaks, identifies the active-surface-layer to α-Ni(OH)2 or NiFe LDH. The relatively broad peaks' width related to nanocrystallized structure does not allow an exact identification of the layer structure.

According to the TEM analyses, the active-surface-layer is porous and nanocrystallized: multitude of spots distributed on circles in the diffraction patten in Fig 2 .g, and grains below 5 nm in Fig 2 .i (with no preferential orientation).The active-surface-layer TEM diffraction pattern in Fig. 2f highlights a cubic structure that matches cubic NiO, as plotted in Fig. S14. Phase mapping (Fig. 2h) highlights a bulk austenitic phase (red) and a NiO cubic active-surface-layer (green). The conversion of α-Ni(OH)2 or NiFe LDH (detected using GI-XRD) into NiO (detected using TEM) may come from the TEM samples focused ion beam (FIB) preparation.

Active-surface-layer composition

According to TEM-EDS elemental profiles (Fig. 3), though Fe remains the main component in the active-surface-layer of W-316L (Fe/Ni ratio > 1 after activations), the Fe-content decreases, the Ni-content is rather stable and Cr-content approaches zero. W-825 and W-718, initially containing more bulk Ni than Fe, show decreased Fe-content, Cr disappearance from the layer (as for W-316L), their Fe/Ni ratio remaining below 1 after activations. W-625, whose major element is Ni, shows a markedly-increased Fe-content in the active-surface-layer. Except for W-316L, the grades reach active-surface-layer compositions of 5-10 at.% Fe and 15-20 at.% Ni, evidencing that the active-surface-layer composition homogenizes for all samples after activations. The fitting parameters used are reported in Tables S3 to S5. Three samples per grade were analysed by XPS after polishing, aging and activations.

W-625 and P-625 behave differently: the Fe 3p line is considered in XPS (Fig. 4e), because the Fe 2p peaks overlap with a Ni LMM Auger one. The correspondence of the Fe 2p and Fe 3p fits was validated by analysing these peaks for other grades, with lower Ni-content. The Fe 3p peak contains two contributions at 55.4 and 56.8 eV, corresponding to Fe2O3 and FeOOH [START_REF] Mcintyre | X-ray photoelectron spectroscopic studies of iron oxides[END_REF][START_REF] Asami | The X-ray photo-electron spectra of several oxides of iron and chromium[END_REF]. The Ni 2p and Cr 2p peaks exhibit a similar trend as the other grades with aging and activations: a Ni-rich oxo-hydroxide-layer grows (the metallic peaks disappear and the Cr peak decreases). The Fe 3p peak analysis, Fig. 4e, highlights the initial absence of Fe in this grade. After aging and activations, Fe-oxide is detected, confirming the TEM-EDS measurement: Fe incorporates during aging (without current or potential application) and increases upon activations. For each point, the geometric current density (mA.cm -2 -geo) is taken for a potential of 1.56 V vs RHE, corresponding to the OER region. This value is then normalized by the ECSA value to be expressed in mA.cm -2 -ECSA. The ECSA value for W-316L in the initial state being very low, the error on the measurement is large; the corresponding Fe/Ni ratio of 16.0 is therefore not reported on the graph. [START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF] reports AISI 304 activated steels with different Fe/Ni ratios: 0.49 (Elox300), 0.58 (Elox480) and 3.5 (EloxCycl) [START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF]. These data support the trend of an increase in Ni active-site activity with higher Fe/Ni ratio. [START_REF] Xiang | In situ vertical growth of Fe-Ni layered double-hydroxide arrays on Fe-Ni alloy foil: interfacial layer enhanced electrocatalyst with small overpotential for oxygen evolution reaction[END_REF] corresponds to a vertically grown FeNi LDH nanosheet arrays on FeNi foil, i.e. very large developed surface [START_REF] Xiang | In situ vertical growth of Fe-Ni layered double-hydroxide arrays on Fe-Ni alloy foil: interfacial layer enhanced electrocatalyst with small overpotential for oxygen evolution reaction[END_REF]. The reported Fe/Ni ratio is the one of the interfacial hydroxide (Fe/Ni = 3). [START_REF] Dionigi | In-situ structure and catalytic mechanism of NiFe and CoFe double hydroxides during oxygen evolution[END_REF] refers to a NiFe LDH on GC with a Fe/Ni ratio of 0.33 [START_REF] Dionigi | In-situ structure and catalytic mechanism of NiFe and CoFe double hydroxides during oxygen evolution[END_REF]. The Dionigi reference presents a similar behaviour as our NiFe alloys. The low J (mA.cm -

DISCUSSION

The Ni III /Ni II reduction peak potential strongly depends on the bulk materials Fe-content (Fig. 1b). Furthermore, the Ni III /Ni II peak positively-shifts for increased Fe-content (Fig. 5a), which originates from atomic-scale structure/organization. Assuming that GI-XRD (Fig. 2e) identified the α-Ni(OH)2 phase (or a NiFe LDH phase) in the active-surface-layer after activations, as on Fe-doped Ni(OH)2 [START_REF] Wang | Deciphering the exceptional performance of NiFe hydroxide for the oxygen evolution reaction in an anion exchange membrane electrolyzer[END_REF], mixed Ni-Fe oxo-hydroxides [START_REF] Görlin | Oxygen evolution reaction dynamics, faradaic charge efficiency, and the active metal redox states of Ni-Fe oxide water splitting electrocatalysts[END_REF] and activated steels [START_REF] Moureaux | Development of an oxygenevolution electrode from 316L stainless steel: application to the oxygen evolution reaction in aqueous lithium-air batteries[END_REF], Fe is likely substituted to Ni in this α-Ni(OH)2 matrix [START_REF] Friebel | Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting[END_REF][START_REF] Balasubramanian | X-ray absorption spectroscopy studies of the local atomic and electronic structure of iron incorporated into electrodeposited hydrous nickel oxide films[END_REF]; this possibly induces a different electronic environment of Ni in the α-Ni(OH)2 phase [START_REF] Enman | Effects of intentionally incorporated metal cations on the oxygen evolution electrocatalytic activity of nickel (oxy)hydroxide in alkaline media[END_REF] and a symmetry-distortion around Ni with increasing Fe-content [START_REF] Smith | Geometric distortions in nickel (oxy)hydroxide electrocatalysts by redox inactive iron ions[END_REF]. Beyond 40 at.% Fe, the Ni III /Ni II potential stabilizes around 1.4 V vs RHE: the limited solubility of Fe 3+ in α-Ni(OH)2 may yield a Fe-rich phase (FeOxHy) for higher Fe-content, that coexists with the previous Fe-containing α-Ni(OH)2 phase [START_REF] Friebel | Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting[END_REF][START_REF] Klaus | Effects of Fe electrolyte impurities on Ni(OH)2/NiOOH structure and oxygen evolution activity[END_REF]. Figure 5a is therefore a master-curve to determine, from the CV scans, the Fe-content in NiFe oxohydroxides.

Crystallographic orientations of the OER active phase is believed to influence the OER activity [START_REF] Bajdich | Theoretical investigation of the activity of cobalt oxides for the electrochemical oxidation of water[END_REF][START_REF] Poulain | Electrocatalytic properties of (100)-, (110)-, and (111)oriented NiO thin films toward the oxygen evolution reaction[END_REF][START_REF] Wang | Deciphering the exceptional performance of NiFe hydroxide for the oxygen evolution reaction in an anion exchange membrane electrolyzer[END_REF]. Herein, wires and plates have different preferential crystallographic orientations (XRD, Fig. S1); OER performances (Figs. 1c-e) slightly vary between wire and plates for the 625 and 825 grades, denoting a poor bulk crystallographic orientation effect on OER performance. Indeed, no epitaxial growth of the active-surface-layer was induced since this layer is nanocrystallized with no preferential crystallographic orientations (see Fig. 2i). The metals surface preparation also has no impact on OER (Fig. S11), demonstrating that the activesurface-layer formation mostly determines the OER activity; these grades can be highly-active for OER without any surface preparation step. Hence, chemical composition is the main parameter influencing OER performance (Fig. 1c) with an optimum for 10 < at.% Fe < 50 in Ni(OH)2/NiOOH [START_REF] Dionigi | NiFe-based (oxy)hydroxide catalysts for oxygen evolution reaction in non-acidic electrolytes[END_REF]. Grades with lower Fe-content exhibit high OER potential, owing to the poor catalytic activity of pure Ni(OH)2 [START_REF] Corrigan | The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes[END_REF][START_REF] Klaus | Effects of Fe electrolyte impurities on Ni(OH)2/NiOOH structure and oxygen evolution activity[END_REF]. Fe-rich grades (above 50 at.%) exhibit intermediate performance, because an inactive FeOxHy phase forms, overall decreasing the apparent OER activity [START_REF] Friebel | Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting[END_REF][START_REF] Klaus | Effects of Fe electrolyte impurities on Ni(OH)2/NiOOH structure and oxygen evolution activity[END_REF]. Despite the addition-elements present in the grades (mainly Cr and Mo), the samples follow the trend described for NiFe-based oxohydroxide catalysts: the Fe-and Ni-content (Fe/Ni ratio) remains the main criterion determining OER performances.

W-625 and P-625 have a very low initial Fe-content (Fig. 4e); however, Fe was detected in the active-surface-layer after aging and activations (Figs. 3 and4e). The positive-potential-shift of the Ni III /Ni II reduction peak (Figs. S2 andS4) confirms this Fe-enrichment (Figs. 1b and5a). This Fe-content increase correlates with the strongly-improved OER performance (Figs. 1c-e): for W-625 and P-625, the OER potential is drastically reduced after aging and activations. Feincorporation into Ni-based electrocatalysts is known to significantly accelerate OER [START_REF] Trotochaud | Nickel-iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation[END_REF][START_REF] Corrigan | The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes[END_REF][START_REF] Klaus | Effects of Fe electrolyte impurities on Ni(OH)2/NiOOH structure and oxygen evolution activity[END_REF][START_REF] Mirabella | Ni-modified Fe3O4(001) surface as a simple model system for understanding the oxygen evolution reaction[END_REF][START_REF] Wang | Deciphering the exceptional performance of NiFe hydroxide for the oxygen evolution reaction in an anion exchange membrane electrolyzer[END_REF][START_REF] Burke | Oxygen evolution reaction electrocatalysis on transition metal oxides and (oxy)hydroxides: activity trends and design principles[END_REF][START_REF] Li | Nickel based electrocatalysts for oxygen evolution in high current density, alkaline water electrolysers[END_REF]. Fe-incorporation into NiOOH enhances conductivity, while partial charge-transfer between Fe and Ni 3+/4+ promotes OER kinetics [START_REF] Trotochaud | Nickel-iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation[END_REF], in line with the improved of Ni active-sites with aging and activations of W-625 and P-625 (Fig. 1g). Feincorporation increases the Fe/Ni ratio and leads to a more favourable range of Fe-content of the surface composition. Table S8 and Figures S16-S17, relative to a 99.999% pure Ni (W-Ni), for which surfaceenrichment by migration of Fe contained in the bulk is impossible, show that Fe impurities in the electrolyte (prepared from KOH pellets, 85%) are mostly responsible for Fe-incorporation in the oxide-layer [START_REF] Trotochaud | Nickel-iron oxyhydroxide oxygen-evolution electrocatalysts: the role of intentional and incidental iron incorporation[END_REF][START_REF] Corrigan | The catalysis of the oxygen evolution reaction by iron impurities in thin film nickel oxide electrodes[END_REF][START_REF] Klaus | Effects of Fe electrolyte impurities on Ni(OH)2/NiOOH structure and oxygen evolution activity[END_REF]. TEM-EDS (Fig. 3) and XPS analyses (Figs. 4 andS15) demonstrate that the OER active-surfacelayer predominantly contains Ni and Fe. The initially relatively-high Cr content (Table S1) drastically reduces from the surface layer after aging and activations. Based on different grades of narrower compositions (67-72 at% Fe, 7-21 at% Ni, 1-8 at% Cr), Todoroki et al. explained such trend [36,37] by solubility differences in alkaline media: Ni-oxides are stabilized, unlike Fe-and Cr-oxides [START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF][START_REF] Pourbaix | Atlas of Electrochemical Equilibria in Aqueous Solutions[END_REF]. The Ni III /Ni II capacity plot (Fig. 1f) demonstrates the growth of a Nirich oxo-hydroxide-layer upon aging and activations, yielding more Ni surface-sites. Correlation with the layer thickness (TEM analysis, Fig. 2) indicates that Ni-rich bulk alloys exhibit larger Ni III /Ni II capacity increase with aging and activations, and thicker oxide-layer. W-Invar (65.4 at.% Fe, 34.1 at.% Ni, Tables S9, S10, Figs. S18 andS19),whose Fe/Ni ratio (1.92) is comparable to W-825 (0.97) and W-286 (2.44), exhibits stable OER potential (at 5 mA.cm -2 ) with aging and activations (Fig. S19.a), higher than for W-825 and W-286. Neither grade show Ni active-site performances improvement (Figs. S19.d and 1g). The Ni III /Ni II capacity of W-Invar remains very low even after activations (0.5±0.1 mC.cm -2 , Fig. S19.b), well below the smallest value of the tested steels (W-316L: 1.0±0.4 mC.cm -2 ). Thus, minor alloying elements (mainly Cr and Mo) have an important role in the Ni-rich active-layer creation for Fe-rich grades. Studying pure Ni (99.999%) revealed that the OER performance could be improved solely by Feincorporation (without the presence of additional elements), suggesting that the active-layer formation may depend on the bulk Fe-content: for Fe-poor grades, Fe-incorporation increases the OER performance with the development of a thick Ni-oxide layer; for Fe-rich grades, a Nirich layer grows with a decrease in addition-element content in the surface layer (Cr, Mo, Nb, Figs. 4 andS15), which are therefore essential in the layer's formation and growth.

After activations, each active-surface-layer mainly contains Fe and Ni (TEM-EDS and XPS).

Plotting the activity of the Ni active-sites versus the Fe/Ni ratio in the layer (Fig. 5b) shows that higher Fe/Ni ratio yield better active-sites' performance: better OER performance per number of Ni sites are obtained for as-high-as-possible Fe-content in the active-layer. In comparison with NiFe-LDH or other activated steels, our NiFe alloys have a similar or better Ni active-sites activity for the same Fe/Ni ratio.

The number of Ni active-sites is also crucial in the catalyst's OER performance. Although W-316L has the highest initial Fe-content, its OER activity after activations is poor (Figs. 1e,h), owing to a very small increase in Ni III /Ni II capacity (Fig. 1f) and a very small oxide-layer thickness (Fig. 2a). Its composition (70.5 at.% Fe, 9.53 at.% Ni) cannot develop a Ni-rich activelayer with the present activation method, in agreement with Todoroki et al. [START_REF] Todoroki | Nanostructures and oxygen evolution overpotentials of surface catalyst layers synthesized on various austenitic stainless steel electrodes[END_REF]: the Fe/Ni ratio and the capacity to generate a catalyst layer (with a large surface area) are the dominant criteria to obtain the best OER performances.

Fig. 5c correlates the OER potential with the layer's chemical composition. The very high initial Fe/Ni ratio (around 16.0) of W-316L significantly decreased to 1.8 and 1.3 after aging and activations, lowering the OER potential: 1.577, 1.568 and 1.541 V vs RHE, initially, after aging and after activations. W-825, P-825 and W-718, with an initial Fe/Ni ratio of 1.1, 1.3 and 1.1 respectively, exhibit lower OER potentials: 1.555, 1.559 and 1.564 V vs RHE. Aging reduces both the Fe/Ni ratio (0.6, 0.6 and 0.4) and OER potential (1.550, 1.545 and 1.560 V vs RHE), activations decreasing them even more: Fe/Ni ratio of 0.4, 0.4 and 0.3, and OER potential of 1.534, 1.539 and 1.537 V vs RHE, This evolution of Fe/Ni ratio follows the layer's Ni-enrichment (XPS, Fig. 4) following Ni-oxides' stabilization, unlike Fe-or Cr-oxides [START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF][START_REF] Pourbaix | Atlas of Electrochemical Equilibria in Aqueous Solutions[END_REF]. For these grades, the OER performance increase is therefore correlated to the decreased Fe/Ni ratio, which converges to 0.3-0.4. The Fe/Ni ratio of W-625 and P-625 initially tends to zero. Aging induces Fe-incorporation into the oxide-layer (from electrolyte impurities), leading to a ratio of 0.09 for both samples, and OER potentials decreased to 1.577 and 1.562 V vs RHE, respectively. Activations further increase the Fe/Ni ratio (0.2 and 0.1) and decrease the OER potential (1.522 and 1.552 V vs RHE). For grades with very low initial Fe-content, increased Fe/Ni ratio improves OER. The wide range of chemical composition of the alloys tested (bulk Fe/Ni ratio between 7.40 and 0.004 (Table S1) and between 16 and 0 in the native oxide-layer (XPS)) enables to correlate the OER activity increase to an optimized Fe/Ni ratio, which tends towards 0.2-0.4. Schäfer et al. also reported optimized performance for steels composed of 67% Ni and 33.0% Fe (Fe/Ni ratio of 0.49) [START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF], the optimum being 25% Fe (Fe/Ni ratio of 0.33) for mixed Ni-Fe catalysts [START_REF] Friebel | Identification of highly active Fe sites in (Ni,Fe)OOH for electrocatalytic water splitting[END_REF].

CONCLUSION

Fe-and Ni-based alloys of different chemical compositions and different crystallographic orientations between wires and plates were studied as alkaline OER electrocatalysts. Their bulk chemical compositions strongly influence their initial electrochemical performances, unlike the manufacturing and surface preparation processes. Grades containing 21.8-35.3 at.% Fe are initially optimal for fast OER, as reported for NiFe oxohydroxides catalysts. Aging (2.5 hours in 0.1 M KOH) and activations (alternated high/low potentials) further reduce the OER overpotential by thickening the Fe-doped Ni oxo-hydroxides layer. This layer's Ni III /Ni II capacity and Fe/Ni ratio determine the apparent OER kinetics: the Fe-Nialloys must develop a thick Ni-rich active-surface-layer (large number of Ni active-sites) and efficient Ni active-sites (large Fe/Ni ratio). Efficient active-sites and high Ni III /Ni II capacity is optimal for 0.2 < Fe/Ni < 0.4. Reaching this ratio is possible for a very wide range of initial alloy composition (0.004 < initial < 7.4): Fe-poor grades optimized by Fe-incorporation (impurity contained in the electrolyte), while Fe-rich grades show Ni-enriched oxide-layer (selective dissolution of Fe, Cr, etc.), these alloying elements favouring the development of the Ni-rich active-layer. Both processes are emphasized by potential cycling. As a result, whatever the Fe and Ni contents of the initial alloy, one can easily obtain remarkable OER activity (outperforming commercial IrO2) and reasonable durability upon alternated potential application (which proceeds upon water electrolyser coupling to renewable sources of electricity), though alloys with low initial Fe content (e.g. 625) seem less robust to harsh potential alternation than Fe-richer ones.

Table 2: Details of the main characteristics of the different grades supplied by Aperam company. The column "Fe-Ni alloy" is the commercial name of the alloy and the column "Label" is the name that is used in this article to refer simply to the samples. The "Process" column gives the indication of the processing of the sample. The "Geometric surface" column is the active area tested electrochemically (used to calculate the current density). Surface preparation. The analyzed surfaces underwent several grinding steps starting with SiC abrasive discs (P320, P600, P1200, P2400) followed by polishing with diamond suspension (3 µm and 1 µm). A final mechanical-chemical polishing step was performed with a colloidal silica solution (OPU NonDry, 0.04 µm, Struers). Cleaning and rinsing were performed with ethanol and ultra-pure water (18.2 MΩ.cm, < 3 ppb total organic carbon, Milli-Q system, Millipore, Merck). The polished samples were placed in PTFE tubes (wires) or Origalys sample holder (plates) to be fixed on a rotating electrode during electrochemical tests (see Fig. S20b).

Fe-Ni alloy

Preparation of IrO2 samples. IrO2 inks were prepared from IrO2 powder (Iridium (IV) oxide, Premion, 99.99% (metal basis), Ir 84.5% min, Alfa Aesar), 5 wt.% Nafion ® dispersion (1100EW, Sigma Aldrich), isopropyl alcohol (IPA, HPLC grade Fisher Chemical)) and ultra-pure water. Two inks were prepared with different loadings: 20 µgcm -2 (ink A) and 100 µgcm -2 (ink B). A mass of 2.0 mg (10 mg) of IrO2 powder was weighed into a pillbox, for ink A (respectively for ink B). Volumes of 3.40 mL (3.39 mL) of ultrapure water, then 1.70mL (1.70mL) of IPA and finally 2.3 µL (11.32 µL) of Nafion ® dispersion were added to the pillbox. A content of 5 wt.% Nafion ® / 95 wt.% IrO2 weighed, and a ratio of 1/3 IPA -2/3 H2O was kept. The synthesized ink was placed in an ultrasonic (US) bath for homogenization. A carbon electrode was polished to 1 µm, cleaned successively 5 min with US in acetone, ethanol and ultrapure water and then placed in an oven at 90°C for 20 min. A volume of 10 µL of synthesized ink was deposited on the surface of the carbon electrode (0.196 cm 2 ) and dried until evaporation of the solvents.

Electrochemical set up. Electrochemical measurements were performed in a three-electrode glass cell under Argon flow at room temperature (25°C). The electrolyte, KOH at 0.1 M, was prepared with KOH pellets (85%, Alfa Aesar) and ultra-pure water. The sample is fixed to a rotating electrode (1600 rpm imposed during the measurement) and used as working electrode. Pt was used as counter electrode and [Hg/HgO -0.1 M KOH] was used as reference electrode (+ 0.926 V vs RHE). In this work, all potentials are expressed versus the RHE. A numerical potentiostat-galvanostat (VMP3, Bio-Logic ® ) was used to perform the electrochemical measurements.

OER performance determination. Cyclic Voltammetries (CV) were performed between 1.061 and 1.761 V vs. RHE at a scan rate of 50 mV.s -1 (minimal impact of the scan rate on the measured potential is demonstrated onFig. S21). For each result presented in this article, ohmic drop was corrected, based on impedance spectroscopy measurement. The current densities are referred to the surface" value, reported in Table 2. For each result presented, three repetitions were performed to estimate the measurement error. Eleven CV scans were successively performed for the characterization of one state, and the 11 th CV is used to characterize the stable state of the material. The potential required to reach a given current density is the parameter indicating the reaction kinetics. The OER performances of the different samples are thus given by comparing the potentials at a current density of 5 mA.cm -2 or 10 mA.cm -2 . For commercial IrO2 samples, two loading were investigated, 20 µg.cm -2 and 100 µg.cm -2 , leading to OER potentials at 10 mA.cm -2 1.63±0.01 V and 1.584±0.03 V, respectively.

Characterization of the initial state. The initial state performance characterization was performed by recording a first CV scan just after the sample was immersed in the electrolyte.

For the comparison with IrO2, the deposits on the carbon electrode were characterized by a CV scan performed after immersion of the electrode in the electrolyte.

Impact of aging in 0.1 M KOH. After the initial state, the samples were placed at open circuit voltage (OCV) for 2.5 hours. A new succession of eleven CV scans was then performed to determine the impact of aging in the electrolyte (the 11 th CV is also used to characterized the stable state).

Impact of activations. After the aging period, the samples underwent the activation protocol proposed by Moureaux et al. [START_REF] Moureaux | Timely-activated 316L stainless steel: A low cost, durable and active electrode for oxygen evolution reaction in concentrated alkaline environments[END_REF]. The first part of this protocol (step 1) is a polarization at E = 1.581 V vs. RHE during 10 min, then at E = 0.981 V vs. RHE during 5 min. The second stage (step 2) consists of two CV scans performed between 1.061 and 1.581 V vs. RHE, at a scan rate of 5 mV.s -1 . Steps 1 and 2 are repeated 12 times. To maximize the performances, this activation protocol was repeated four times on each sample, and is subsequently referred to as the "impact of activations".

Durability assessment using an accelerated stress test (AST). The robustness of the Fe-Ni alloys against harsh potential variations (that can occur upon start/stops of real alkaline water electrolyser cells) was tested by applying the AST protocol suggested by Todoroki et al. [START_REF] Todoroki | Dissolution of constituent elements from various austeniticstainless steel oxygen evolution electrodes under potential cycle loadings[END_REF]and Fujita et al. [START_REF] Fujita | The effect of LixNi2-xO2/Ni with modification method on activity and durability of alkaline water electrolysis anode[END_REF]. The AST consists of repeated triangle-wave potential cycles between 0.5 and 1.8 V vs RHE at 1 V.s -1 for 20 000 cycles. In the present case, the OER performance was measured after polishing (or after activations), and then after 100, 500, 1000, 5000, 10000 and 20000 cycles of AST, through a CV recorded at 20 mV.s -1 in 0.1 M KOH at 25°C between 0.5 and 1.65 V vs RHE.

Faradaic efficiency assessment by rotating ring-disk electrode measurements. A changedisk rotating ring-disk electrode tip with a platinum ring from PINE instruments (model E6R1Pt) was mounted on a PINE MSR rotator. The disk consisted of either a cylinder of polycrystalline Pt electrode (from PINE) or of home-made Fe-Ni alloy from the studied series, machined at the proper dimensions and carefully mirror-polished before use.

The important steps of this procedure are as follows.

1 -All the measurements were performed at 1500 rpm. In these conditions, for the electrolyte employed (0.1 M KOH at 25°C), assuming the values of O2 diffusion coefficient (1.6 10 -5 cm² s -1 ), solution kinematic viscosity (0.01 cm² s -1 ) and the of the RRDE tip (disk radius = 0.25 cm, ring inner radius = 0.325 cm), the theoretical transit time (see [START_REF] Chatenet | Electrochemical measurement of the oxygen diffusivity and solubility in concentrated alkaline media on rotating ring-disk and disk electrodes-application to industrial chlorine-soda electrolyte[END_REF][START_REF] Chatenet | Direct rotating ring-disk measurement of the sodium borohydride diffusion coefficient in sodium hydroxide solutions[END_REF] for details) for O2 is ca. 0.55 s. The experimental times at which the disk and ring maximum currents were measured upon the OER voltammetries was superior to this value (ca. 1 s), and this can originate from the hindrance of O2 bubbles in the KOH electrolyte that are transported from the outer radius to the ring inner radius. For this reason, the current time was corrected by ca. 1 s for all the experiments presented hereafter.

2 -The collection efficiency (N) of the rotating ring-disk electrode, in theory 25% for this RRDE tip, was measured for the hydrogen evolution reaction in conditions of H2 gas bubbles evolution on the RRDE, this reaction being chosen because it shall not lead to any competing reaction in the operating conditions employed (O2-free electrolyte). This calibration was made firstly for the polycrystalline Pt disk and also for each of the Fe-Ni alloys, the Pt ring (previously cleaned by applying a few cycles of cyclic voltammetry in supporting electrolyte) being maintained at Ering = 0.4 V vs RHE. The collection efficiency was close to 10% for the Pt disk, but closer to 15±2% for the different Fe-Ni alloys tested. All values are slightly below the theoretical one (owing to the harsh bubbles evolution) but correspond (for the Pt disk) or are slightly above (for the Fe-Ni disks) that found in similar conditions in [START_REF] Chung | Dynamic stability of active sites in hydr (oxy) oxides for the oxygen evolution reaction[END_REF]. It was verified that the collection efficiency remains "constant" for repeated incursion into the HER domain on the disk, which was the case if the absolute value of the disk current density remained below 10 mA cm - 2 (i.e. not for very intense bubbles formation at the disk); such maximum current was targeted for any subsequent measurements, as for larger values, non-negligible noise in the measurement and depreciated collection efficiency was witnessed. Also, the potential sweep rate at the disk was set to 20 mV.s -1 , a value which is the best compromise between "stationary" measurements (that require slow sweep rate) and limited hindrance by bubbles evolution (which require as fast as possible measurement to limit bubbles accumulation). This potential sweep rate was also chosen for the OER characterizations.

3 -Then, cyclic voltamperograms of OER were plotted at each of the Fe-Ni alloy disk, while the ring was maintained at Ering = 0.4 V vs RHE for O2 detection or Ering = 1.1 V vs RHE for H2O2 detection.

4 -The ring current was firstly baseline-corrected, then time-corrected to account for the transit-time for species to escape the disk and reach the ring, and then divided by the collection efficiency measured in HER on the given disk electrode (see point 2-above, being admitted that each electrode had its own collection efficiency).

Faradaic efficiency assessment by ICP-MS measurements. The metal ions were detected with a PerkinElmer NexION 2000c spectrometer. 27 Al, 60 Ni, 65 Cu, 93 Nb, 94 Mo, 98 Mo were analysed in standard mode. 48 Ti, 52 Cr, 53 Cr, 56 Fe, were analysed in kinetic energy discrimination (KED) mode with He, to avoid interferences with polyatomic ions. Calibration curves were determined with daily-prepared calibration solutions of Al, Ti, Cr, Fe, Ni, Cu, Nb and Mo at 0, 5, 10, 20 and 50 μg L -1 . ICP-MS standard solutions (Carl Roth GmbH & Co.) were diluted with 2% HNO3 (Suprapur® 68 %, Analpure) in ultrapure water (MilliQ, 18.2 MΩ cm, TOC < 3 ppb) and 0.01 M KOH was added to have the same concentration of K in all sample solutions, to keep the same ionization of metals. The samples were diluted by 10 with 2% HNO3. 2.5 ppb of Rh was added in all solutions to correct the instrumental drift. The percentage of recovery of internal standard was about 3% at 100%. Data were traced with the Syngistic Software. The obtained results are summarized in Table S2, and discussed in the related section in supporting information.

Surface characterizations. The chemical composition of the different grades, after the final polishing step, was measured by scanning electron microscopy (FESEM, Field Emission Scanning Electron Microscope, ZEISS Ultra 55) coupled with elemental X-Ray energy dispersive spectrometry (EDS, BRUKER Quantax system equipped with a Silicon Drift Detector (SDD, active surface 30 2 ), controlled with Esprit software), performed at 20 kV. In order to determine the measurement error, four 0.45 mm 2 zones per sample were analyzed. X-ray diffraction measurements (XRD, PANalytical X'Pert Pro MPD, Cu Kα (1.5418 Å), with a Pixcel 1D detector) were realized in Bragg-Brentano configuration for the initial state characterization of all wires and plates. Grazing incidence measurements (sensitive to extreme surface), requiring larger surfaces, were performed on plates after polishing and after activations. The surface layers created by aging and activations were characterized by transmission electron microscopy (MET JEOL 2100F -FEG -200kV), coupled with EDS measurements (mapping mode with a 1 nm probe) and advanced imaging and diffraction tools for transmission electron microscopy (ASTAR). The TEM samples were prepared by FIB-SEM which required a protective coating (Pt was used for W-316L and carbon was used for W-825, W-718 and W-625). The active-surface-layer developed at the alloy/electrolyte interface after polishing, aging and four activations was characterized using TEM for all the samples (W-316L, W-825, W-718 and W-625 in Fig. 2a, 2b, 2c and 2d respectively). The layer thicknesses are extracted from the analysis of images with a pixel size of 0.1 nm and the statistic was performed on a length of 1.4 µm. The active-surface-layer crystallinity of the samples was further analyzed by TEM. X-ray photoelectron spectroscopy measurements (XPS, K-Alpha apparatus from Thermo Fisher Scientific, UHV chamber (10 -9 mbar), Al Kα radiation (1486.6eV), hemispherical analyser at 30 eV constant pass energy, constant angle of 90° between the sample surface and the analyser) were performed on the samples at initial state (after the final polishing step), after aging in the electrolyte and after activations. The position of the peaks was recalibrated with respect to the carbon peak (C 1s at 285.0 eV), the fits were performed with the background determined by the Shirley method and the fit parameters used are reported in Tables S3 to S7. More specifically, to fit the XPS data, our approach was to refer to the literature values for peak positions, their FWHM and degrees of freedom around the values (see references in Tables S3 to S7). Many iterations were performed on the 18 spectra of the Fe-Ni samples. By iteration, the position of the peaks, the FWHM and the degrees of freedom around the values were refined. No modification of peak symmetry was carried out to best match literature data. To have robust and comparable results between samples, it was chosen to optimize the fits using the same fit parameters (with few degrees of freedom) for all 18 spectra, and not to modify each fit to best match the experimental data of each sample. This constraint leads to fits that may not perfectly match the experimental values, but are the result of a global iterative optimization on a large number of spectra. This is the most relevant approach to compare "similar" materials, as is the case here. This choice was made because the absolute value of the composition of each surface was not the main target, but instead the evolution of the Fe/Ni ratio between the different samples. Allowing too much freedom to individual fits would have induced better visual match, but an error on the comparability of the results between the different spectra and samples.

Figure 1 :

 1 Figure 1: Electrochemical characterization of the OER performances in 0.1 M KOH at 25°C. (a) CV scans of the different alloys (wires) after polishing, performed at 50 mV.s -1 (the start of the CVs is indicated by the dot and the scan direction by the arrows). (b) Potential of Ni III /Ni II reduction peak, extracted from Fig. 1a, as a function of the initial Fe-content determined by SEM-EDS (TableS1). OER potentials for wires and plates (c) after polishing, (d) after aging, (e) after activations. Potentials are measured at a current density of 5 mA.cm -2 from Supplementary Figs. S2a to S8a. The differences between the highest and lowest potentials are plotted on the right of each graph after polishing (pink), after aging (green) and after activations (orange). (f) Evolution of the Ni III /Ni II reaction capacity for each grade after polishing, after aging and after activations. The value is calculated from the integration of the Ni III /Ni II reduction peak of the CV scans in Supplementary Figs. S2a to S8a. (g) Evolution of the Ni active-site performance: a decrease in potential corresponds to an increase in active-site performance. These values are extracted from Supplementary Figs. S2b to S8b representing the current density normalized by the Ni III /Ni II reaction capacity as a function of the potential. (h) OER potential at a current density of 10 mA.cm -2 . Comparison of the different grades (wires, after activations) with IrO2 deposits on glassy-carbon electrode. The potentials for IrO2 are extracted from the CV scans reported in Supplementary Fig. S9.

  Figure 1: Electrochemical characterization of the OER performances in 0.1 M KOH at 25°C. (a) CV scans of the different alloys (wires) after polishing, performed at 50 mV.s -1 (the start of the CVs is indicated by the dot and the scan direction by the arrows). (b) Potential of Ni III /Ni II reduction peak, extracted from Fig. 1a, as a function of the initial Fe-content determined by SEM-EDS (TableS1). OER potentials for wires and plates (c) after polishing, (d) after aging, (e) after activations. Potentials are measured at a current density of 5 mA.cm -2 from Supplementary Figs. S2a to S8a. The differences between the highest and lowest potentials are plotted on the right of each graph after polishing (pink), after aging (green) and after activations (orange). (f) Evolution of the Ni III /Ni II reaction capacity for each grade after polishing, after aging and after activations. The value is calculated from the integration of the Ni III /Ni II reduction peak of the CV scans in Supplementary Figs. S2a to S8a. (g) Evolution of the Ni active-site performance: a decrease in potential corresponds to an increase in active-site performance. These values are extracted from Supplementary Figs. S2b to S8b representing the current density normalized by the Ni III /Ni II reaction capacity as a function of the potential. (h) OER potential at a current density of 10 mA.cm -2 . Comparison of the different grades (wires, after activations) with IrO2 deposits on glassy-carbon electrode. The potentials for IrO2 are extracted from the CV scans reported in Supplementary Fig. S9.

Figure 2 :

 2 Figure 2: TEM images of the samples after four activations (a) W-316L, (b) W-825, (c) W-718 and (d) W-625. The activesurface-layer is outlined by the blue area on the right side of each image.For the TEM sample preparation using FIB-SEM, a protective layer was deposited over the oxide-layer: platinum for W-316L and carbon for W-825, W-718 and W-625. (e) Grazing incidence X-ray diffraction (GI-XRD) analysis of P-625 and P-825 after polishing and after activations. The reference patterns for α-Ni(OH)2 (red, rhombohedral, ICDD no. 00-038-0715), β-Ni(OH)2 (green, hexagonal, ICDD no. 00-057-0907), NiFe LDH (orange, rhombohedral, ICDD no. 00-35-0965*) and NiO (blue, cubic, ICDD no 00-004-0835) are displayed. Diffraction pattern of pixel in the active-surface-layer highlighting: (f) a well-crystallized structure and (g) a nanocrystallized structure. (h) ASTAR phase mapping generated by comparing the diffraction patterns to the austenitic phase (in red, identified using GI-XRD) and to the NiO cubic structure (in green, matching the active-surface-layer structure, see Figs.2f and S14). (i) ASTAR crystallographic orientation mapping[START_REF] Rauch | Automated crystal orientation and phase mapping in TEM[END_REF], using the same phases as Fig.2h, highlighting the nanocrystallized structure of the active-surface-layer with no preferential orientation. Both Figs. 2h and 2i include the uncertainty related to the indexation quality (black pixels are those that do not match well with the proposed phases). *ICDD no. 00-35-0965 corresponds to FeNi LDH structure according to Dionigi et al.[START_REF] Dionigi | Intrinsic electrocatalytic activity for oxygen evolution of crystalline 3Dtransition metal layered double hydroxides[END_REF]

Figure 3 :

 3 Figure 3: TEM-EDS analysis: chemical composition profiles performed on samples after activations. The negative depths correspond to the bulk and the positive depths to the active-surface-layer. Only the major elements are plotted on these graphs.

Figure 4 displays

 4 Figure 4 displays Ni 2p, Fe 2p and Cr 2p photoelectron lines of W-718 and W-625; Mo 3d and Nb 3d peaks are reported in Fig. S15. As satellites structures are present and since Ni(OH)2 and

Figure 4 :

 4 Figure 4: XPS analysis of W-718: (a) Ni 2p, (b) Fe 2p and (c) Cr 2p. XPS analysis of W-625: (d) Ni 2p, (e) Fe 3p and (f) Cr 2p. The fitting parameters used are reported in TablesS3 to S5. Three samples per grade were analysed by XPS after polishing, aging and activations.

Figure 5 :

 5 Figure 5: (a) Potential of Ni III /Ni II reduction peaks as a function of the Fe content (at.%) determined from the Fe/Ni ratio measured by XPS. To calculate the Fe atomic percentage, an alloy containing only Fe and Ni is considered. (b) Ni active-site activity as a function of the Fe/Ni ratio in the surface layer.For each point, the geometric current density (mA.cm -2 -geo) is taken for a potential of 1.56 V vs RHE, corresponding to the OER region. This value is then normalized by the ECSA value to be expressed in mA.cm -2 -ECSA. The ECSA value for W-316L in the initial state being very low, the error on the measurement is large; the corresponding Fe/Ni ratio of 16.0 is therefore not reported on the graph.[START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF] reports AISI 304 activated steels with different Fe/Ni ratios: 0.49 (Elox300), 0.58 (Elox480) and 3.5 (EloxCycl)[START_REF] Schäfer | Stainless steel made to rust: a robust water-splitting catalyst with benchmark characteristics[END_REF]. These data support the trend of an increase in Ni active-site activity with higher Fe/Ni ratio.[START_REF] Xiang | In situ vertical growth of Fe-Ni layered double-hydroxide arrays on Fe-Ni alloy foil: interfacial layer enhanced electrocatalyst with small overpotential for oxygen evolution reaction[END_REF] corresponds to a vertically grown FeNi LDH nanosheet arrays on FeNi foil, i.e. very large developed surface[START_REF] Xiang | In situ vertical growth of Fe-Ni layered double-hydroxide arrays on Fe-Ni alloy foil: interfacial layer enhanced electrocatalyst with small overpotential for oxygen evolution reaction[END_REF]. The reported Fe/Ni ratio is the one of the interfacial hydroxide (Fe/Ni = 3).[START_REF] Dionigi | In-situ structure and catalytic mechanism of NiFe and CoFe double hydroxides during oxygen evolution[END_REF] refers to a NiFe LDH on GC with a Fe/Ni ratio of 0.33[START_REF] Dionigi | In-situ structure and catalytic mechanism of NiFe and CoFe double hydroxides during oxygen evolution[END_REF]. The Dionigi reference presents a similar behaviour as our NiFe alloys. The low J (mA.cm -

2 -

 2 ECSA) values for Schäfer's and Xiang's references can be explained by the large ECSA of the samples, i.e. a low current density per Ni site. (c) Correlation of OER performance with the oxidelayer chemical composition: OER potential (at 5 mA.cm -2 ) as a function of the Fe/Ni ratio measured by XPS. The initial state is represented by the solid dots (•); after aging corresponds to the lighter dots (•) and after activations is reported with the open circles (○).

Table 1 : Comparison of OER overpotential (η-geo) measured in our study with reference of the literature (related to a fixed geometric current density). The electrochemical active surface area (ECSA) is also measured from the papers of the literature where appropriate CVs are given to make this estimation. The OER overpotential measured at a fixed ECSA current density (η-ECSA) is also reported in this table.

 1

	a OER overpotential measured after activations. b Vertically grown FeNi LDH nanosheet arrays, i.e. very large developed
	surface. LDH = layered double hydroxide; GC = glassy carbon
	Electrocatalyst	η-geo (mV, at J = 10 mA cm -2 -geo)	ECSA (cm 2 )	η-ECSA (mV, at J = 0.4 mA cm -2 -ECSA)	Electrolyte Reference
	W-625 a	327 ± 7	8 ± 2	341 ± 10	0.1 M KOH This work
	W-718 a	320 ± 10	3.4 ± 0.1	310 ± 2	0.1 M KOH This work
	W-825 a	322 ± 3	2.0 ± 0.3	308 ± 12	0.1 M KOH This work
	W-286 a	339 ± 4	1.11 ± 0.07	304 ± 2	0.1 M KOH This work
	W-316L a	340 ± 20	0.9 ± 0.4	304 ± 5	0.1 M KOH This work
	IrO2 -20 µg.cm -2	400 ± 10	-	-	0.1 M KOH This work
	IrO2 -100 µg.cm -2	354 ± 3	-	-	0.1 M KOH This work
	FeNi LDH on FeNi foil b	130	1120	-	0.1 M KOH	[43]
	Electrodeposited Fe-Ni film (Fe/Ni = 0.67)	280	381	265	0.1 M KOH	[9]

Acknowledgments

This work was funded by Carnot EF (NICKEL project); VP, VR, MC and ES, thank Pierre Joncourt and William Ait Idir, who participated to a preliminary study that ended up on this project. The research has benefited from the characterization equipment of the Grenoble INP -CMTC platform supported by the Centre of Excellence of Multifunctional Architectured Materials ''CEMAM'' (grant ANR-10-LABX-44-01) funded by the ''Investments for the Future'' Program. All authors thank Grégory Berthomé for the XPS measurements, Gilles Renou for the TEM analysis, Stéphane Coindeau and Thierry Encinas for XRD measurements. The internship of GC was funded by the DAEMONHYC project, supported by the "France 2030" government investment plan managed by the French National Research Agency, under the reference "ANR-22-PEHY-0010".

Author contributions

C.P., V.R., E.S., M.C. and V.P. designed the project study. I.S. and R.B. provided the samples. L.M. carried out the experiments and analysed the data, except for the following; G.C. and M.C. performed the rotating ring-disk experiments and evaluated the corresponding OER faradaic efficiency; G.C. made the accelerated stress tests; V.M. made the ICP-MS measurements to evaluate the extent of metal dissolution upon OER. C.P., V.R., E.S., M.C., V.P., I.S and R.B. helped discussing the results. All authors contributed to the preparation of the manuscript.

Competing interests

The authors declare no competing interests.

Additional information

Supplementary information METHODS Materials. Five Fe-and Ni-based alloys were studied: APERAM 316L, IMPHY 286, IMPHY 825, IMPHY 718 and IMPHY 625. These grades, manufactured by Aperam company as wires with diameters between 5.00 and 5.94 mm, were then cut into cylinders of 5 mm height (see Fig. S20a). For IMPHY 825 and IMPHY 625, 2 and 2.2 mm thick (respectively) plates were also analyzed by cutting 15 mm diameter discs. The set of grades studied, the label used in this article and the processing method are reported in Table 2.


Basile Rousse

Sylvain Lobry

Laurent Wendling

Géraldine Duthé

Valérie Golaz

LINKING POPULATION DATA TO HIGH RESOLUTION MAPS: A CASE STUDY IN BURKINA FASO

Recent research in demography focuses on linking population data to environmental indicators. Satellite imagery can support such projects by providing data at a large scale and a high frequency. Moreover, population surveys often provide geolocations of households, yet sometimes with an offset, to guarantee data confidentiality. In such cases, the proper management of this incertitude is required, to accurately link environmental indicators such as land cover/land use maps or spectral indices to population data. In this paper, we introduce a method based on the random sampling of possible households geolocations around the coordinates provided. Then, we link a land cover map generated using semi-supervised deep learning and a Malaria Indicator Survey in Burkina Faso. After linking households to their close environment, we distinguish several types of environment conducive to high malaria rates, beyond the urban/rural dichotomy.

INTRODUCTION

Besides demographic data, population surveys often provide geolocations of interviewed households. For the Demographic and Health Survey (DHS) program 1 and other surveys built with a similar design, these geolocations are slightly displaced to preserve households confidentiality. However, they allow linking households data to their close environment using derived spatial data such as NDVI or more complete land classification schemes. The Local Climate Zones (LCZs) [START_REF] Stewart | Local climate zones for urban temperature studies[END_REF]) is a land cover/land use classification system based on the surface physical properties and human activities. LCZ classes describe different types of environment, as "Compact low-rise" cities, "Sparsely built", "Scattered trees" and "Bush/scrub" areas. This scheme can be applied globally as it is not specific to any part of the World. Recent works on LCZ mapping use machine learning techniques to train models that could be applied globally. [START_REF] Demuzere | A global map of local climate zones to support earth system modelling and urban-scale environmental science[END_REF] proposes a global LCZ map using random forests algorithms on 46 spatial features. The So2Sat dataset proposed by Zhu et al. ( 2020) is a large-scale labeled dataset for training neural networks to classify LCZs. It is made of 32x32 Sentinel-1/2 patches over 42 cities in various part of the world. This dataset has been used to generate maps for 1642 cities, supporting environmental urban studies [START_REF] Xiang Zhu | The urban morphology on our planet -global perspectives from space[END_REF]. Although on a large scale, this strategy does not produce optimal results on sub-Saharan countries as few African cities were available in the training dataset. Recent works focus on semi-supervised domain adaptation strategy based on sub-Saharan seasonal changes to produce more accurate maps. This technique uses the So2Sat dataset and additional Sentinel-2 images to adapt training to the mapping of these countries. It allows the creation of LCZ maps with a resolution of 320m, well below DHS buffer on households' geolocations. Accurately linking such maps and DHS-like population data would benefit from lowering the error made on the selection of the close environment, due to geo-relocations. This work introduces a new method to model the environment of households in DHS studies, and applies it to the Burkina Faso Malaria Indicator Survey (MIS) of 2017[START_REF] Insd | Enquête sur les indicateurs du paludisme au burkina faso[END_REF][START_REF] Insd | Enquête sur les indicateurs du paludisme au burkina faso[END_REF]. To this end, we first map the whole of Burkina Faso using the LCZ classification scheme and the semi-supervised method. Then, we characterize the households' local environment using randomly sampled areas, that are actual possibilities for their true location. Finally, we show that environmental structures can be a determining factor of malaria prevalence in Burkina Faso.

DEMOGRAPHIC DATA

DHS buffer on geolocations. To produce representative indicators at a defined study-area level, DHS surveys follow a two-stage sampling procedure: First, enumeration zones (EZs, areas canvassed by one census representative) are randomly sampled. Then, in each of the sampled EZs, households are randomly selected for interviews [START_REF] Burgert | Geographic displacement procedure and georeferenced data release policy for the demographic and health surveys[END_REF]. Each household geolocation is recorded and is grouped in its corresponding enumeration zone. Only coordinates of the centroid of each enumeration zone are provided. To preserve the respondents' confidentiality, they are randomly displaced within a circle of 2-10 kilometers radius (2km in urban areas, 5 for most of the rural enumeration areas with 1% only being displaced of up to 10 km) . The type (urban or rural) of environment is specified. To link EZs to spatial data, DHS recommends to average environmental values on this offset area [START_REF] Perez-Heydrich | Influence of demographic and health survey point displacements on raster-based analyses[END_REF]. [START_REF] Grace | Integrating environmental context into dhs analysis while protecting participant confidentiality: A new remote sensing method[END_REF] demonstrates that selecting environmental values of settlements near the DHS' EZs geolocations is a better estimation than averaging over the entire offset area. Other than manually, this selection can be done using gridded population data such as the Global Human Settlement Layer [START_REF] Pesaresi | Ghs built-up grid, derived from landsat, multitemporal[END_REF]. However, this method requires having reference data at the time of the study, which is not always the case are.

Malaria Indicator Survey 2017-2018, Burkina Faso. Malaria Indicator Surveys (MISs) are surveys following the general DHS population studies sampling procedure. They focus on monitoring malaria within the context of the global effort to fight this disease. MISs aim to estimate basic demographic and health indicators about malaria as well as the population knowledge about this disease. To this end, malaria rapid tests (giving results in 15 minutes) are done on all 6-59 months old children of the sampled households, with the consent of their legal representatives. The positive tests are confirmed by more reliable laboratory tests. In this paper, we use the MIS 2017-2018 in Burkina Faso. In the survey, malaria prevalence results are representative for each of the 17 study areas (administrative divisions). Among the 252 sampled EZs, 245 were visited. however, 21 of the visited EZs have corrupted geolocations and cannot be used and only 224 EZs can be finally used for analysis. We define the malaria rate R i of the EZ i as the ratio of the number of positive 6-59 months old children by the total number of 6-59 months old children in the EZ i.

LOCAL CLIMATE ZONES MAPPING FOR SUB-SAHARAN AFRICA

Our objective is to extract environmental indicators from remote sensing images that can be linked to malaria rate. We use the Local Climate Zones (LCZs) taxonomy which proposes 17 classes, ranging from dense high-rise built-up areas to water areas. As mentioned in Section 1, training neural networks in a supervised way is not sufficient for accurately predicting LCZs in sub-Saharan countries. However, So2Sat can be used as a reference dataset for building semi-supervised learning to reduce the divergence between a reference domain (i.e. a labeled dataset) and a target domain (i.e. an unlabeled dataset). This type of strategy enables adding useful information to the training without requiring additional labeled data. Sub-Saharan countries experience successive dry and rainy seasons in a year which significantly change vegetation and the overall appearance of the environment, observed by optical remote sensing images. We define D S = (x i , y i ) i∈ 1,n S as the labeled dataset where x i is a Sentinel-2 image from So2Sat, y i its associated LCZ label and n S the number of samples in D S . Our strategy aims to make a model F (.) robust to seasonal change, and learn seasonal features from countries' seasonal changes. Therefore, we define D T = (z s1 i , z s2 i ) i∈ 1,n T made of n T pairs of unlabeled images z s1 , z s2 from the same area at different seasons s 1 and s 2 . As Burkina Faso has one dry and one rainy season, each pair in D T uses images of both seasons. These two datasets are combined with a consistency regularization approach and contrastive learning. We employed a two tracks training, described in Algorithm 1, resulting in two losses that are combined in a second stage. The first track is a regular supervised track using D S where Cross-Entropy L S is computed. The second track uses contrastive learning based on D T where z s2 i is considered as a seasonal augmentation of z s2 i similarly as in [START_REF] Mañas | Seasonal contrast: Unsupervised pre-training from uncurated remote sensing data[END_REF]. The contrastive loss L T is computed and combined with a weighted sum as follow:

L T (z s1 i , z s2 i ) = -log exp(sim(F (z s1 i ), F (z s2 i ))/τ ) 2N k=1,k̸ =i exp(sim(F (z s1 i ), F (z s2 k ))/τ ) (1)
where N is the size of the batch, sim(•, •) is a cosine similarity measure, τ is the temperature, (i, j) ∈ 1, N 2 , (z s1/2 l

) l∈ 1,2N samples from the batch, and (z s1 i , z s2 i ) a positive pair. The total loss used for back-propagation is a weighted sum of the supervised and unsupervised losses, with a regularization coefficient α ∈ [0, 1]:

L = α × L S + (1 -α) × L T .
Algorithm 1 Semi-supervised training step 1: for i = 1, 2, . . . , N S |j = 1, 2, . . . , N T do 2: Predict x i , z s1 j , z s2 j LCZ classes with F (.)

3:

Compute the Cross-Entropy L S and Contrastive Loss L T 4:

L ← α × L S + (1 -α) × L T 5:
Back-propagate L through F (.) 6: end for Algorithm 2 EZs characterization 1: X ← Random areas of all EZs 2: Separate X in clusters X 1 , X 2 , X 3 , X 4 3: for i = 1, 2, . . . , N EZ do 4:

Compute the mean LCZ distribution of EZ i M i 5:

Predict the cluster of EZ i M i with the fuzzy-c-means 6: end for To map Burkina Faso, we selected Sentinel-2 tiles taken during the time of the study, in early January 2018. The tiles are split into 32×32 patches for classification, and the model predictions are reconstructed into the final LCZ map. Thus, the resolution of the LCZ map is 320m×320m. More information about the mapping process is available in [START_REF] Basile Rousse | Seasonal semi-supervised domain adaptation for linking population studies and Local Climate Zones[END_REF].

LINKING MAPS TO HOUSEHOLD GEOLOCATIONS

Our objective is to characterize the type of environment of each EZ using the LCZs computed with the method presented in Section 3. We first model the EZs' offset areas by circles centered on their displaced centroids. As already mentioned, these circles have a radius of 2 km in urban areas or 10 km in rural areas. These circles will be referred to as C k , k being the identifier of the EZ. For each EZ k, we semi-randomly sample n random squared areas of size A (in the 320m × 320m resolution LCZ map) inside C k to model the potential true geolocations of interviewed households. These n random random areas should have at least δ% of LCZs belonging to their urban or rural type to ensure the sampling consistency. This sampling procedure results in a total of n sampled random areas sampled from all EZs. These n sampled samples give a global view on the local environment in which the household were interviewed. We propose to summarize local environments into n E typical environments. To achieve this categorization, the n sampled samples are clustered into n E clusters. Finally, we want to characterize the environment of each EZ. The mean LCZ distribution of an EZ k is computed by taking the mean proportion of each LCZ class within all the random areas selected inside C k . Then, we separate EZs into the n E types of environment defined by the clustering step described above, using their mean LCZ distributions. We applied this method to the Burkina Faso MIS 2017-2018 and a LCZ map generated using the method presented in 3. In this paper, we use n random = 10 and A = 100m, which results in a total of 2240 random areas sampled. These areas are clustered using the fuzzy-c-means algorithm [START_REF] Bezdek | Fcm: The fuzzy c-means clustering algorithm[END_REF] into n E = 4 typical environments. The distributions of the clustering centers are shown in Figure 1. As expected, the 4 clusters are highly dominated by one single LCZ class. Cluster 3 and 4 are rural clusters dominated by bush/scrub and scattered trees areas, cluster 1 is highly urban with compact low-rise (cities) and cluster 2 is in between rural and urban with sparely built areas. A 2D representation computed using the t-SNE algorithm (van der [START_REF] Van Der Maaten | Viualizing data using t-sne[END_REF] of the EZs LCZ distribution is shown in Figure 1.

APPLICATION: LINKING MALARIA TO HOUSEHOLD ENVIRONMENTS

To explore a possible link between environmental indicators and malaria prevalence, we considered malaria rates computed using MIS data. We plot in Figure 2 the distributions of these malaria rates grouped in the n E = 4 types of environment defined in Section 4 and described in Figure 1. We used δ = 0.9. Malaria rates distributions differ according to the type of environment. The definition of such clusters using the LCZ classification goes beyond the urban/rural dichotomy and enables identifying different structures where the propagation of malaria is higher. The urban clusters 1 and 2, respectively focused on "compact-low-rise" and "sparsely-built", have lower malaria rates than the rural ones. Malaria rates of EZs in cluster 4 bush/scrub are not concentrated in a particular range but are distributed over the entire range of values. This class is widely represented on the Burkina Faso LCZ map, which implies that it is very represented in our randomly selected areas. This results in about half of the available EZs being associated to this cluster. Nevertheless, as depicted in Figure 2 , the proportion of EZs belonging to cluster 3 is increasing when the malaria rates are increasing. We performed an independence t-test to look at the statistical difference between clusters, based on their malaria rate distributions. Values are shown in Table 1. All are statistically different according to this method except for the rural clusters 3 and 4. The LCZ classification enables distinguishing the types of environment where malaria propagation is lower, or higher. Further developments are required for distinguishing, if possible, scattered trees and bush-scrub areas.

CONCLUSION

In this paper, we introduce a new method to model households geo-relocations on DHS surveys. We based our method on a semi-random sampling of small areas within DHS offset areas, which are possible real close environment of interviewed households. Then, we applied this method to link the LCZ environment classification scheme to the MIS survey in Burkina Faso. This method, when linked with a LCZ map, was able to distinguish different environmental structures where malaria propagation is either higher or lower. Further development on the mapping and incertitude management must be done to clarify these distinctions.

Figure 1 :

 1 Figure 1: LCZ distributions of clustering centers (left) and visualisation of EZs, grouped by environment types as defined by the clustering step. The visualization has been done using t-SNE.

Figure 2 :

 2 Figure 2: Distribution of EZs malaria rates grouped by cluster (left) and proportion of malaria rates, grouped by cluster and by intervals.

Table 1 :

 1 Independence t-test results p-values Cst1 Cst2

				Cst3	Cst4	t-values Cst1	Cst2	Cst3	Cst4
	Cst1	1	0	0	0	Cst1	0 7.706 9.223 11.899
	Cst2	x	1 0.004 0.033	Cst2	x	0 3.004	2.151
	Cst3	x	x	1 0.160	Cst3	x	x	0 -1.433
	Cst4	x	x	x	1	Cst4	x	x	x	0

https://dhsprogram.com

ACKNOWLEDGMENTS

Work supported by the Data Intelligence Institute of Paris (DiiP), and IdEx Université Paris Cité (ANR-18-IDEX-0001). This work was performed using HPC resources from GENCI-IDRIS (Grant 2021-AD011013527).