G1

Finally all these hard alloys very rich in carbon, mainly present as carbides but also as graphite in some cases, displayed a rather good resistance against oxidation by air at temperatures as high as 1200°C and under. Except the three carbon-richest iron alloys exposed to the very high temperature of 1200°C, the behaviour of the alloys was rather good at least during 50 hours, as shown by the presence of external chromia (but, it is true, more or less mixed with other not so protective oxides). The low chromium contents in matrix, due to the consumption of a great part of this element when the numerous carbides formed during solidification, was obviously corrected during high temperature oxidation by an enrichment of the matrix with Cr coming from the carbides dissolving deeper and deeper (carbide-free zone development). The presence of graphite in the C-richest cobalt-based and nickel-based alloys did not provoke a catastrophic oxidation although this free carbon especially exposed to oxidation may generate great volumes of COx gases able to perturb the continuity of the growing external protective scale. To finish one can also notice that the most external parts of these alloys are replaced by carbide-free zones which are much softer than the carbides-rich bulk alloys. This can be a problem to maintain a good wear resistance on surface.

Cast cobalt-based, nickel-based and iron-based alloys are widely used for numerous applications, and notably their chromium-rich versions are often considered in different domains, among them aeronautics for which chromium allows the alloys well resisting against high temperature oxidation and corrosion. Carbon can be added in great quantities to these alloys in order to obtain high fractions of chromium carbides to achieve high levels of hardness and of good resistance against wear phenomena. In service the wear-solicited materials or coatings may reach high temperatures, because friction-induced heating. They can be then affected by oxidation by hot gases and their resistance to this deterioration needs to be better known, especially for versions of such alloys obtained by classical foundry way for which this was seemingly not extensively studied. The aim of the present work is precisely to study the behaviour in high temperature oxidation in air of chromium carbides -rich alloys based on cobalt, nickel and iron, elaborated by conventional casting. 18 alloys, 6 {Co-30wt.%Cr}+C, 6 {Fe-30wt.%Cr}+C and 6 {Ni-30wt.%Cr}+C, with %C = to 2.5 (alloys "Co25", "Fe25" and "Ni25"), 3.0 ("Co30", "Fe30", "Ni30"), 3.5 ("Co35", "Fe35", "Ni35"), 4.0 ("Co40", "Fe40", "Ni40"), 4.5 ("Co45", "Fe45", "Ni45") and 5.0wt.% ("Co50", "Fe50", "Ni50") were elaborated by foundry under argon (Ar), using a high frequency induction furnace (CELES).

Fusion and solidification were achieved in the water-cooled copper crucible of the furnace. The masses of the obtained ingots were about 40g. Compact samples of about 125 mm 3 were cut to obtain, per ingot, one sample for the examination of the as-cast microstructure, and the three others destined to the oxidation tests.

The samples were exposed to the laboratory air at 1000°C, 1100 or 1200°C for 50 hours in a resistive tubular furnace, followed by air quenching. After embedding and polishing a Scanning Electron Microscope (PHILIPS XL30) was used for metallographic observations in the Back Scattered Electrons mode.

WDS measurements (Wavelength Dispersion Spectrometry) were performed using a CAMECA SX100 microprobe (Co and Ni alloys) and a JEOL Scanning Electron Microscope equipped with a WDS device (Fe alloys), in the oxide scales and the alloys' sub-surfaces affected by oxidation to better know the oxides' natures and the minimal chromium content on extreme surface. For all the Co alloys the damage by oxidation is rather serious (deep carbide-free zones, external oxides of different types and porosity degrees, internal oxidation and voids in sub-surface) although no real catastrophic oxidation was noticed (neither exceptionally thick oxides, nor carbides disappearance from surface to center). Oxidation is more severe for a higher temperature and for a higher carbon content in the alloy. Here too the external oxides were partly lost during cooling. WDS measurements showed that chromia (inner oxide) is present in all cases, but often with other oxides (CoO and spinel CoCr2O4, outer oxides).

The Fe25 alloy displays a microstructure still hypoeutectic with presence of matrix dendrites in addition to the {matrix + carbide} eutectic. The Fe30 alloy is near eutectic and the Fe35, Fe40, Fe45 and Fe50 alloys are all hypeeutectic with presence, in addition to the same eutectic compound, of coarse and acicular pro-eutectic carbides.

Fe40, Fe45 and Fe50 were catastrophically oxidized after 50h at 1200°C. Their oxide scales were exceptionally thick and all the chromium carbides were lost consequently to the outward diffusion of all carbon and its oxidation into gaseous species. Concerning all the oxidized alloys in general, the identified oxides present on surface were Cr2O3 (chromia), (Cr,Fe)2O3 (with Cr and Fe in equal proportions or with preponderance of Cr or of Fe) and Fe2O3 (hematite). The Cr2O3 and Fe2O3 oxides were clearly differentiated on samples oxidized at 1000°C, (Cr,Fe)2O3 with preponderance of Cr and (Cr, Fe)2O3 with preponderance were often observed on alloys oxidized at 1100°C, and (Cr,Fe)2O3 with almost equal quantities of Cr and Fe existing beside Cr2O3 and/or Fe2O3 (separating the two latter) were often seen on samples oxidized at 1200°C. The nickel alloys are all hypereutectic, with a {matrix+carbide} eutectic compound and coarse proeutectic carbides, and graphite for the three carbon-richest alloys, Ni40, Ni45 and Ni50. Carbides are mainly Cr3C2 in all alloys but Cr7C3 are also present in the two lowestcarbon alloys: Cr7C3 with Cr3C2 in Ni25 at 1000 and 1100°C, and only Cr7C3 at 1200°C in Ni25 and Ni30.

Chromia was always present but other types of oxides were also seen and internal oxidation (generally Cr2O3 too) can be observed in most of the oxidized alloys. Several coarse chromium carbides emerging on surface were obviously oxidizing. Oxidation induced for all alloys the development of a carbide-free zone, deeper for a higher temperature and which increases when the carbon content increases, probably because of the faster oxidation for a higher temperature and for a higher carbon content. For 1000/1100°C and for the carbon-richest alloys the chromium content on extreme surface is the lowest (around 10wt.%Cr) and this let think that, as for the two other families of alloys, oxidation may become catastrophic soon after the 50h of these oxidation tests.

  chromium con ten t on surfa ce (wt.%) ca rb on con te nt in a lloy (w t.%) of the carb ide-free zone (µm) carbo n content in al loy (wt.%) romium co nte nt on su rfac e (wt.%) carbo n con tent in a lloy (wt.%) epth of th e carbid e-free zo ne (µ m) ca rb on co ntent i n al loy (wt.%) of the carb ide-free zone (µm) ca rb on co nte nt in allo y (wt.%) chromium con ten t on surfa ce (wt.%) carbon content in all oy (wt.%)

  , almost eutectic (Co35) or hyper-eutectic (Co40 to Co50: {matrix+carbides} eutectic + coarse acicular pro-eutectic carbides). The two carbonrichest alloys contain in addition some graphite particles. All carbides are Cr7C3.


PhD Researcher, Silvia Ientile
email: silvia.ientile@univ-eiffel.fr

PhD Mezgeen Rasol

PhD Franziska Schmidt

PhD Lucas Adelaide

PhD Boumediene Nedjar

PhD Christophe Chevalier

Sensor-based monitoring systems for resilient road infrastructures

Keywords: critical infrastructure, sensor-based monitoring, resilience assessment, performance indicators, corrosion, road surface friction

Maintenance and protection of road infrastructures (RIs) are increasingly exposed to natural hazards. This requires an effective risk assessment and mitigation methodologies considering a suitable resilience approach. Accordingly, several research projects focusing on RIs have developed resilience frameworks built on anticipatory, absorptive, restorative, and adaptive capacities. Among these, PANOPTIS conceptual resilience framework deals with scenarios linked to disastrous events based on actual data-driven from sensors (terrestrial and airborne). The main aim of PANOPTIS is minimizing service interruptions and quickly recovering with a holistic approach through an integrated platform with structural and geotechnical simulation tools. This paper presents the use of sensors-based monitoring systems: skid resistance measurements through novel mobile and passive road sensors for road surface; and in-situ measurements by a remote-real-time-automated monitoring of corrosion velocity in steel rebars of reinforced concrete bridge structures. Data collected from sensors are processed using automated algorithms to assess the monitored RI states depending on various alert thresholds of control parameters for each application (e.g., corrosion rate and velocity, ice percentage, road surface friction, etc.). These parameters are integrated in a specific platform provided to support decisions-making owners, in this case RI operators. These RI operational monitoring systems contribute in the assessment of RI resilience, in particular for resilience indicators related to the anticipatory capacity of the system. Monitoring data plays a key role in risk reduction and control strategies against negative impacts of disruptive scenario, and to build resilience improving the continuity of RI service. Besides that, broadened idea of the monitoring on-site data reliability is presented.

INTRODUCTION

Maintenance and protection of Road Infrastructure (RI) as part of country's Critical Infrastructure (CI), is essential to contribute the developments of a community assuring citizens' daily mobility and transport of goods. CIs are defined as "asset, system or part thereof in member states which is essential for the maintenance of vital societal functions, health, safety, security, economic or social well-being of people, and the disruption or destruction of which would have significant impact in a member state as a result of the failure to maintain those functions" [START_REF] Mansfield | European Directives[END_REF]. Moreover, RIs are often lifeline systems for rescuing people and for repairing and restoring other transportation systems. On this purpose, risk assessment methodologies should be integrated with a resilience approach in order to develop a methodological framework as adopted by recent EU policy trends [START_REF] Theocharidou | Resilience of Critical Infrastructure Systems : Policy[END_REF] to analyze and improve CI performance facing disruptive events. Resilience for CIs is defined as the "ability to anticipate, absorb, adapt to, and rapidly recover from a potentially disruptive event, whether naturally occurring or human caused" by National Infrastructure Advisory Council (NIAC, 2009). The concept of resilience and its assessment are defined according to its main characteristics through the evaluation of global resilience index or combining indices attributed to resilience capacities. In [START_REF] Petit | Resilience Measurement Index: An Indicator of Critical Infrastructure Resilience[END_REF], components or procedures of the infrastructure system are identified to be associated with the different resilience capacities, then the assessment methodology is based on the related rankings or weighted values attributed. Several methodological frameworks [START_REF] Francis | A metric and frameworks for resilience analysis of engineered and infrastructure systems[END_REF][START_REF] Jovanovic | Analysis of existing assessment resilience approaches, indicators and data sources: Usability and limitations of existing indicators for assessing, predicting and monitoring critical infrastructure resilience[END_REF][START_REF] Jovanovic | Analysis of existing assessment resilience approaches, indicators and data sources: Usability and limitations of existing indicators for assessing, predicting and monitoring critical infrastructure resilience[END_REF][START_REF] Nan | A quantitative method for assessing resilience of interdependent infrastructures[END_REF][START_REF] Rehak | Complex approach to assessing resilience of critical infrastructure elements[END_REF] are based on this approach, providing a general methodology for assessing resilience that was considered in this study in relation to its application to a RI system. Thus, by investigating different research projects addressing road infrastructure resilience, a list of resilience performance indicators [START_REF] Prior | RISK AND RESILIENCE REPORT 9 Measuring Critical Infrastructure Resilience : Possible Indicators[END_REF] is referred to that can be attributed to the main resilience capacities. Within the PANOPTIS project (PANOPTIS, 2018), which aims to improve RI resilience, the resilience conceptual framework is based on a holistic approach to the main capabilities of a resilient infrastructure through the use of assessment tools that integrate data from a multiplicity of novel sensors monitoring the different RI components.

This paper shows how sensor-based monitoring system, in particular sensors for the corrosion detection of steel bars in reinforced concrete structures and for the skid-resistance of road pavements, can contribute to the anticipatory capacity of a resilient infrastructure. The presence of such monitoring systems is taken into account by performance indicators that are used for a qualitative assessment of the overall resilience of the road infrastructure. In addition, a reliable data driven on-site for the RI monitoring system is crucial for the road management authorities in order to provide a safe transport infrastructure considering best reliability engineering practices.

RESILIENCE AND PERFORMANCE INDICATORS FOR CRITICAL INFRASTRUCTURES

The definition of resilient infrastructure is a system capable of dealing with scenarios linked to disastrous events with the aim of minimizing service interruptions and quickly recovering, harmonized the different definitions of resilience associated with critical infrastructures. Then, a resilient CI is characterized by the anticipatory (predicting and resisting the impact), absorptive and coping (withstanding the damage), restorative (recovering after damage) and adaptive (modifying and adapting) capacities which are based on the 4R fundamental properties (Robustness, Redundancy, Resourcefulness and Rapidity) combined with Technical, Organizational, Social and Economic (TOSE) dimensions [START_REF] Bruneau | A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities[END_REF]. Based on the abovementioned capacities, several research projects dealing with CIs resilience have developed frameworks in order to evaluate and improve the resilience of the system against extreme and climate change-related hazard events. The main distinction between the different approaches is the type of assessment, i.e. qualitative or quantitative focusing on one or more of the resilience capacities. RESOLUTE project [START_REF] Ferreira | Conceptual Framework[END_REF], focused on transportation systems, relies the methodology on qualitative estimation of the adaptive capacity according to operational pressures related to disruptive events. FORESEE project [START_REF] Adey | FORESEE -Future proofing strategies FOr RESilient transport networks against Extreme Events Guideline to measure Levels of Service and resilience in infrastructures[END_REF], on the other hand, considers a resilience quantitative assessment through specific indicators in terms of degrees of fixed service levels for passenger and freight transport. Other research projects, such as SAFE-10-T (de [START_REF] De Paor | SAFE-10-T Deliverable D1.1 Report on the Probabilistic Consideration of Resilience[END_REF], RESILENS (RESILIENS consortium, 2016), and EU-CIRCLE [START_REF] Menaha | D4.1 EU-CIRCLE RESILIENCE FRAMEWORK -INITIAL VERSION[END_REF] combine both qualitative and quantitative approach to take into account the contribution of anticipatory, absorptive and restorative capacities to the overall CI resilience.

The concept of CI resilience refers to a process contributing to system's ability to respond and recovery after a disruption; the identification and the measure of CI components' resilience degree is fundamental to manage disruption events and its consequences. Establishing a resilience measure allows to adopt suitable procedures for CI protection and risk management [START_REF] Prior | SKI Focus Report 8 -Measuring Resilience: Benefits and Limitations of Resilience Indices[END_REF]. Potential indicator for four main CI resilence capacities are setted for further assessment purposes including anticipatory, absorptive and coping, restorative and adaptive based on the research study conducted in Swiss National Strategy for Critical Infrastructure Protection (CIP) [START_REF] Prior | RISK AND RESILIENCE REPORT 9 Measuring Critical Infrastructure Resilience : Possible Indicators[END_REF]. In the resilience framework such as RESILENS and EU-CIRCLE take into account the indicators of resilience associated to each capacity, as reported in Table 1. CIP's study highlights how CI resilience is made up of the contribution of several factors that reflect the complexity of the system.

For this reason, it is important to underline that the indicators provide an estimate of one aspect/capacity of CI resilience. The overall evaluation should be a combination of these indicators, depending on the typology of infrastructure, the physical and organisational CI characteristics and the risk context.

SENSOR-BASED MONITORING FOR RI RESILIENCE ASSESSMENT

The monitoring of road infrastructures in a pre-event scenario is necessary in order to increase their resilience, as the information it provides is fundamental for vulnerability assessment of the infrastructure to the various risks to which it is subjected. Moreover, the use of monitoring systems integrated into the various CI components or structures makes it possible to follow the evolution of eventual damage processes in real time in a post-event scenario. This constitutes a fundamental element to feed the CI anticipatory capacity as it is considered in PANOPTIS resilience framework for road infrastructure.

PANOPTIS resilience framework for road infrastructures

PANOPTIS resilience framework proposes to assess and improve the main resilience capacities through a holistic risk and impact assessment approach with an integrated system based on Holistic Risk Assessment Platform (HRAP). The conceptual approach, as shown in Fig. 1, provides an integration of the different tools and components of the platform that contributes to each resilience capacity (PANOPTIS Consortium, 2019). The integrated management of components and processes provides: (i)prevention: options to minimize exposure of RI to hazards, through the more efficient and effective understanding and prioritizing of potential risk and threats ; (ii)reduction of potential impacts: enhance contingency planning and business continuity to ensure alternative supplies, reserve capacity, and/or rapid restoration of services ; (iii)adaptation to mitigating risk: investing in protection and defenses.

PANOPTIS resilience assessment combines qualitative and quantitative methods through several indicators referring to before and after events status of the RI system [START_REF] Prior | RISK AND RESILIENCE REPORT 9 Measuring Critical Infrastructure Resilience : Possible Indicators[END_REF]. Sensor-based monitoring of RI contributes mainly to the anticipatory capacity, that is the RI operational monitoring framework (corrosion sensors, passive and mobile road sensors, accelerometers, Satellites Mobile mappers/UAVs, fixed optical sensors, weather stations, Traffic control centre, ITS Systems, etc.). RI operational monitoring assess RI resilience before, and independent from, a shock or disturbance in terms of the following indicators: (i)Quality of infrastructure,(ii)Pre-event functionality of the infrastructure, (iii)Quality/extent of mitigating features, (vi)Quality of crisis communication/information sharing.

Sensor-based monitoring for road infrastructure

Corrosion sensors

Reinforced concrete structures such as bridges are strongly affected by corrosion phenomenon due to the depassivation of the passive layer of steel rebars embedded in concrete elements. The corrosion process is activated by the presence of chloride ions or CO2 as aggressive agents in the environment. The corrosive attack due to the penetration of chloride ions can take place only when the concentration of chlorides reaches a (critical) threshold value in the concrete in contact with the reinforcement [START_REF] Angst | Cement and Concrete Research Critical chloride content in reinforced concrete -A review[END_REF]. Then, the corrosion rate depends by concrete physical-chemical properties such as resistivity. Indeed, concrete electrical resistivity (ρ) is a main qualitative parameter for inspection and monitoring system as four level of corrosion risk are detected according to (ρ) or the related current density (icorr) (Rob B. [START_REF] Polder | Test methods for on site measurement of resistivity of concrete _ a RILEM TC-154 technical recommendation[END_REF]. The most widely used resistivity measurement technique for existing concrete structures is the four-points Wenner methods.

The technique is a non-destructive method using a four-points probe applied to the concrete surface to measure the electrical resistance converted in apparent resistivity. Embedded monitoring methods are being used with greater frequency as they allow for real-time monitoring of concrete resistivity with associated parameters. The advantage is therefore better control of the parameters and the continuous real-time monitoring of the corrosion process of an existing RC structure.

For the corrosion measurements in the PANOPTIS project, a monitoring system through embedded sensors is installed on the surface of the steel rebars in two real scale RC bridges cases in Spain. These sensors are monitoring the corrosion intensity on real time (Fig. 2). The INESSCOM (Integrated Network Sensors for Smart Corrosion Monitoring) system developed by Universitat Politècnica de València [START_REF] Ramón | An embedded-sensor approach for concrete resistivity measurement in on-site corrosion monitoring: Cell constants determination[END_REF]) is a continuous semi-destructive monitoring embedded system allowing the continuous measurement of several corrosion parameters, particularly the corrosion intensity and velocity. The use of accumulated charge curve allows detecting the beginning of passive layer destruction and the progression of corrosion process. Therefore, embedded monitoring systems are beneficial compared to the classical method of on-site resistivity measurements as they assure: (i)multi-parameter monitoring, (ii)accessible remotely results, (iii)totally autonomous system, (vi)low maintenance.

Passive Road-based sensors

In last decades the measurement of skid resistance and friction coefficient of the road surface was based on various manual techniques, details can be found in previous literature studies [START_REF] Acikgoz | Research to methods for skid resistance measurements[END_REF][START_REF] Fwa | The concept of pavement skid resistance state[END_REF][START_REF] Rasol | Progress and monitoring opportunities of skid resistance in road transport: A critical review and road sensors[END_REF]. In the framework of the PANOPTIS project, two main novel road-based sensors are used for the data collection on the road surface pavement of Spanish demo site highways section. These two sensors are defined as followings.

Mobile Advanced Road Weather Information Sensor (MARWIS) is a mounted sensor on vehicles on the road highway. The distance between the sensor and the road surface must be in a range 0.5-2 meters. The working principles of this sensor is based on the infrared measuring; four transmitter and two receiver diodes are capturing the reflected behaviour of the road pavement surface at a different wavelength. Various spectral properties of different substances can be measured via this sensor (e.g., ice percentage, water film thickness, snow thickness, ambient temperature, pavement temperature, dew point temperature, humidity and relative humidity, road condition and friction of the road pavement surface) (Lufft, 2021). The analysis and relation between such parameters and friction coefficient, or/and skid resistance is crucial to advance the knowledge about the functionality of the road surface in respect to the traffic management procedures. This could be significant for enhancing the RI resilience and particularly in the extreme weather condition. In addition, during the installation of MARWIS sensor, it has to be considered that vehicles will not disrupt the sensor face to avoid any inaccuracy in the data collection task. Sensor is protected from turbulences and dirt by a strong housing system 8900.G01 and 8900.G02.

Intelligent passive road-based sensor is considered one of the most efficient innovative technologies to monitor the meteorological factors that could have an impact on the traffic management procedures on the road highways. This sensor is commonly installed on the road surface in front of the vehicle acceleration direction (Fig. 3). Besides, the intelligent passive sensor is connected to 4-pin cables with a length of 50 meters or 100 meters relying on the cable type and distance interval between sensor and control device. Similar to the MARWIS sensor, several parameters could be measured by this passive road sensor such as temperature of the pavement, ambient temperature, ice percentage, road condition, water film height, friction and freezing point or freezing temperature [START_REF] Rasol | Progress and monitoring opportunities of skid resistance in road transport: A critical review and road sensors[END_REF]. The main purpose of the use of above-mentioned sensors are a real-time automatic monitoring weather condition related data, and the road surface friction of the roadways. Based on the above-mentioned information, an appropriate thresholding of the traffic management procedures could be standardized for a specific region. This can support the decision-making owners/end-users and operators to provide the most possible adequate required action for the traffic management system.

CONCEPT OF DATA RELIABILITY FOR RI MONITORING

An increase demand of a stable road networks has become a priority of road management authorities. The reliability analysis of the transportation system and monitoring techniques is crucial in order to provide a better and reliable services for transport infrastructures. Incorporation of the reliability analysis as an integration process involved in different construction process stages including planning, design, construction operation, monitoring and maintenance cycles of the critical infrastructures. In previous research studies, the importance of the reliability has been illustrated as a lifeline for transportation system [START_REF] Chen | A capacity related reliability for transportation networks[END_REF][START_REF] Iida | Basic concepts and future directions of road network reliability analysis[END_REF]. Reliability should not be limited only in the case of the extreme conditions, but also the daily operation disturbances (i.e., accidents, traffic congestion, unfavorable condition, road surface diagnostics, and advance understanding of the traffic management plan). The main aspects of the reliability are focused on the followings. Connectivity reliability is related to the probability of the network nodes remaining connected.

Commonly the terminal reliability is the existence of a known path between two main road paths, which is origin-destination pair (OD) [START_REF] Iida | Basic concepts and future directions of road network reliability analysis[END_REF]. Travel time reliability of the network is one of the main measurement indicators of the reliability analysis of the transportation system. This is considered as a success probability of the trip given between origin-destination pair (OD) within a specific internal time under normal daily flow variations [START_REF] Chen | Capacity reliability of a road network: An assessment methodology and numerical results[END_REF]. The concept of reliability is expanded due to the best reliability engineering practices to improve the reliable road infrastructures. An appropriate reliability analysis of the data driven in the real case studies could significantly improve several aspects of the functionality of road infrastructures. In this sense, several aspects are presented as follows [START_REF] Kurtz | Review of transportation hydrogen infrastructure performance and reliability[END_REF]: (i)Decrease the cost of the maintenance,(ii) Increase the lifeline time, despite the maintenance demands, (iii)Increase the operation efficiency for the road infrastructures, (vi)Accelerate an innovative system to mitigate failures and new design criteria.

Future trends of the reliable data collection and analysis is essential to increase the probability of an efficient monitoring approach for road infrastructures. On the other hand, in PANOPTIS project different non-destructive techniques and sensor-based analysis are proposed in various aspects such as corrosion monitoring in prestressed concrete bridges, influence of the weather condition on the road surface skid resistance measurements. In order to provide a useful tool for decision-making owners and operators, an advance knowledge of the reliable data is a key to understand a comprehensive knowledge of the road management systems.

CONCLUSIONS

RI maintenance and protection is a crucial issue for safeguarding the economic and social life of a country, in particular, related to the continuous and increasing exposure of critical infrastructure to extreme events linked to climate change or aging events. To this end, the resilience assessment of a road infrastructure is considered as an essential task in order to improve RI performance. The complexity of RI systems requires an appropriate assessment methodology based on the needs and actual condition of RI. PANOPTIS project, presented in this paper, relies the resilience assessment of RI system through performance indicators associated to the main resilience capacities. Among this, anticipatory capacity benefits from the presence of RI monitoring systems in order to enhance the related anticipatory performance indicators. Indeed, a sensor-based monitoring system integrated in RI component such as embedded sensors for steel rebars corrosion in RC bridges, or for skid resistance in road pavement allows real-time monitoring and provide valuable data correspond to the vulnerability of such infrastructures prior and post a disruptive event but also in operation conditions. Moreover, the use of a monitoring system increases the reliability of an infrastructure in terms of lifetime and maintenance demands. Besides, the importunacy of the developed models for a reliable operation and mitigations procedures of resilience RI system against disruptive events is discussed. Sensor-based monitoring systems allow a valid resilience assessment including a big data driven from real scale infrastructures and availability of the historical changes of different events. This could support better understanding of the future events and reinforce of the RI systems, as it is supported by data quality and availability.

Figure 1

 1 Figure 1 PANOPTIS Conceptual Resilience framework ((PANOPTIS Consortium, 2019)).

Figure 2

 2 Figure 2 RC Underpass of Spanish Highway section monitored through INESSCOM system, two sensors are applied to each underpass's walls B and C, related recorded icorr data (c).

Figure 3

 3 Figure 3 Road surface friction monitoring on Spanish highway section: a) scheme of the road pavement while sensors are installed, b) On-site installed passive sensor, c) Results of road surface friction influenced by road conditions (adapted from (Rasol et al., 2021)).

Table 1

 1 Resilience capacities and related indicators.

			Resilience capacities
		ANTICIPATORY	ABSORPTIVE&COPING	RESTORATIVE	ADAPTIVE
		Probability of failure	Systems failure (unavailability of assets)	Post-event damage assessment	Substitutability (replacement of service)
		Quality of infrastructure	Severity of failure	Recovery time post-event	Adaptability / flexibility
		Pre-event functionality of the infrastructure	Just in time delivery -Reliability	Recovery/loss ratio	Impact reducing availability
	Resilience Indicators	Quality/extent of mitigating features Quality of disturbance planning/response Quality of crisis communication/information sharing	Post-event functionality Resistance Robustness	Cost of reinstating functionality post-event Post-event damage assessment Recovery time post-event	Consequences reducing availability
		Learnability	Withstanding	Recovery/loss ratio
			Redundancy
			Resourcefulness
			Response
			Economic sustainability
			Interoperability

ACKNOWLEDGMENT:

Financial support has been provided by the Innovation and Networks Executive Agency (INEA) under the powers delegated by the European Commission through the Horizon 2020 program "PANOPTIS-Development of a decision support system for increasing the resilience of transportation infrastructure based on combined use of terrestrial and airborne sensors and advanced modelling tools", Grant Agreement number 769129.

The Project acknowledges the support of the Spanish Ministry of Transport, Mobility and Urban Agenda in the integration of PANOPTIS technologies into the A2-Highway (Section 2), part of the Spanish Network of first generation highways.


Joudi Dabboussi

Rawa Abdallah

Lionel Santinacci

Sandrine Zanna

Antoine Vacher

Vincent Dorcet

Stéphanie Fryars

Didier Floner

Gabriel Loget
email: gabriel.loget@univ-rennes1.fr

Solar-assisted urea oxidation at silicon photoanodes promoted by an amorphous and optically adaptive Ni-Mo-O catalytic layer

Enabling Si to perform solar photoelectrocatalysis is a tedious task due to its low stability and because it requires interfacial catalytic layers that can impede light absorption. Here, we report the deposition of amorphous Ni-Mo-O (NMO) coatings onto metal-insulator-semicondutor silicon junctions and we use these surfaces as photoanodes for the urea oxidation reaction (UOR). The novelty is that these photoanodes stand out for two reasons. First, they allow unprecedented performance for photoelectrochemical UOR at silicon at low overpotentials: photovoltage of 400 mV, onset potential of 0.9 V vs RHE, activity >14 h, high Faradaic and photoconversion efficiencies. Second, the deposited NMO coating exhibits an optically adaptive nature, that promotes considerable improvement of the maximum photocurrent in the presence of urea. This original behavior is promising for the future development of original photoelectrode architectures.

 or molybdenum, 28,29 have emerged as particularly stable UOR electrocatalysts, allowing for UOR operation up to several days.

Introduction

Photoelectrochemical cells (PECs) are devices comprising at least one semiconductor photoelectrode immersed in an aqueous electrolyte. [START_REF] Memming | Semiconductor Electrochemistry[END_REF] Upon light absorption and electron-hole (e --h + ) pairs generation in the photoelectrode, charge carriers are directed to the solid/liquid interfaces where they participate in electrochemical reactions. Large-scale water electrolysis at PECs is highly promising for the production of clean H 2 from solar energy. In these systems, photogenerated electrons produce H 2 at the (photo)cathode through the hydrogen evolution reaction (HER, Reaction 1) and photogenerated holes produce O 2 at the photoanode through the oxygen evolution reaction (OER, Reaction 2). [START_REF] Walter | [END_REF]3 However, a bottleneck of H 2 -producing PECs is the photoanode, which operates in severely detrimental conditions, i.e., drastic local pH and anodic conditions, promoting semiconductor decomposition. 4,5 This is particularly true for Si, which is a prime candidate for PEC [6][7][8] that suffers from dissolution, anodic passivation, and low electrocatalytic activity.

9-11

Another inconvenience in water splitting is inherent to the OER half-reaction, which requires a high overpotential and yields O 2 , already widely available in air. Therefore, there is an interest in replacing the OER in H 2 -producing PECs by a reaction that is more valuable and/or occurs with lower energy input.

Therefore, the urea oxidation reaction (UOR, Reaction 3) is an appealing anodic process that relies on the degradation of urea, the main constituent of urine. As urine is one of the most abundant wastes on Earth, 13 and UOR can be coupled to HER at high pH, [14][15][16] this reaction has important implications for the production of H 2 from contaminated waters. It has been shown that UOR can be efficiently triggered at Co-and Nibased catalysts [17][18][19][20][21][22][23] (Ni(OH) 2 being the archetypal catalyst).

Unfortunately, UOR catalysts often exhibit rapid activity decrease due to the poisoning of catalytically active sites.

24,25

Schemes showing the photoanode structure and the effect of the presence of urea in the electrolyte. a) Without urea photoelectrochemical OER is triggered and the NMO layer is opaque, producing a low maximum photocurrent. b) In the presence of urea, UOR is triggered and the NMO layer is transparent, producing a high maximum photocurrent. Red arrows represent electron flow that triggers HER at the counter electrode (not represented here).

There have been a few reports on photoelectrochemical UOR. For instance, it has been used on plasmonic Ag nanoparticles for fuel cells 34 and with TiO 2 for medical dialysis. 35 In the field of H 2 -producing PECs, UOR has been explored on Co phosphate-modified BiVO 4 36 and Ni(OH) 2 -modified: TiO 2, 37 - 38,39 CdS-sensitized TiO 2 , 40 and Si photoanodes. 41,42 If

Fe 2 O 3 ,
these works underline the strong potential of UOR to couple solar H 2 production to water depollution, long-term photoelectrochemical UOR remains to be demonstrated. Another important issue that must be considered when interfacing a catalyst layer onto a photoanode is that the optical properties of the catalyst can decrease the photon flux reaching the absorber, reducing drastically the performance of frontside-illuminated photoanodes. This is especially obvious for the above-mentioned recent UOR catalysts that are rough and relatively thick.

28-33

In this paper, we report the modification of n-type Si (n-Si)based junctions protected by a Ni thin film with an amorphous, catalytic and electrochromic Ni-Mo-O (NMO) film to produce highly active and stable n-Si/SiO x /Ni/NMO photoanodes, depicted in Figure 1a. In addition to promoting photoelectrochemical activity at low overpotentials, we report another advantage of UOR, namely that it improves optical transmission through the catalytic film, which significantly increases the maximum photocurrent density, as shown in Figure 1b.

Results and discussion

Preparation and characterization of the photoanodes

Our photoanodes are built on the n-Si/SiO x /Ni metal-insulatorsemiconductor (MIS) architecture, which has been demonstrated very efficient for promoting stable OER in high pH electrolytes. [43][44][45][46][47][48] In this junction, shown in Figure 1, SiO x and Ni protect Si from anodic passivation and alkaline etching in operation, 49 and Ni ensure a high Schottky barrier as well as hole collection through the SiO x tunnel. [41][42][43][44][45][46][47] The junction was prepared, first, by chemically oxidizing cleaned Si (100) wafers to create a 1.3-to-2 nm-thick SiO x tunnel layer, as previously reported 41,42 and measured by transmission electron microscopy (TEM, Figure S1). After that, a 17 nm-thick (as determined by atomic force microscopy (AFM) measurements, Figure S2) Ni metal layer was deposited on SiO x by direct current (DC) magnetron sputtering to yield n-Si/SiO x /Ni. This substrate was then modified by Ni and Mo precursors using a hydrothermal and Ar annealing method adapted from that reported by Yu et al. 30 In short, the MIS surfaces were immersed in a Teflon lined reactor containing a solution of nickel nitrate and sodium molybdate (57 mM each) and placed in an oven for 6 h. After that, the surfaces were cleaned, rinsed, dried, and annealed under Ar atmosphere for 2 h (experimental details are provided in SI). Compared to the reported process, 30 in our case, lower temperatures of 90 °C (growth) and 300 °C (annealing) were used because higher temperatures resulted in irreversible Si oxidation. During the hydrothermal treatment, an adherent, porous, and relatively homogeneous coating was grown on the n-Si/SiO x /Ni surface, as shown in the SEM pictures of Figure 2a,b, and Figure S3.

Annealing did not significantly affect the morphology of these films (Figure S4) but was essential for promoting optimal UOR activity and stability (Figure S5). The thickness of the deposited coating can be controlled by varying the modification time, as shown in Figures S6 (growth rate ≈13 nm h -1

, Figure S7). We decided to use a modification time of 6 h, corresponding to a thickness of 82 ±11 nm, which is a good compromise between reaction time and UOR performance (Figure S8). It is important to note the importance of the Mo precursor for growth of the coating onto the MIS surface. Indeed, as shown in Figure S9, no film was present on the surface when sodium molybdate was not added to the growth solution. Please do not adjust margins

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As shown in Figure 2c-e, surface analyses were performed to determine the nature of the coating. First, the X-ray diffraction (XRD) pattern measured on the modified junction (red curve in Figure 2d) shows broad peaks with intensity in the same order of magnitude as that of the starting n-Si/SiO x /Ni substrate (blue curve in Figure 2d). Even though the two higher characteristic peaks present at 2 = 37.1 and 43.1° can be assigned to the 111 and 200 reflections of NiO, the ill-defined shape and low intensity of these peaks reveal an amorphous nature of the deposited coating (the steep increase around 63-65° is due to the apparatus). This is in good agreement with high-resolution TEM pictures, shown in Figure 2e and Figure S10 that demonstrate the disorganized structure of the coating at the atomic scale. We attribute the formation of an amorphous phase to the low temperature we employ (mandatory to preserve Si activity) compared to previous works.

28-33

X-ray photoelectron spectroscopy (XPS) was also performed before and after deposition, as shown in the top and bottom spectra of Figure 2f-h, respectively (survey spectra are shown in Figure S12). The Ni 2p spectrum (Figure 2f) obtained for the unmodified n-Si/SiO x /Ni is in good agreement with that of a Ni metal thin film covered by a native NiO/Ni(OH) 2 layer. 50 After modification, the XPS spectrum considerably changed and the Ni 2p 3/2 region could be fitted with three components, namely, two Ni II contributions (colored curves) and a broader contribution corresponding to the Ni 2p 3/2 satellite peak (black curve). The two Ni II components are similar to that generally reported for NiO (854.5 eV) and Ni(OH) 2 (855.7 eV). [START_REF] Wagner | Hand Book of X-Ray Photoelectron Spectroscopy[END_REF] The larger relative area for the second contribution suggests that most of the surface Ni atoms are coordinated to OH groups, which is consistent with previous observation on NiO coatings. [START_REF] Barr | [END_REF] Figure 2g shows that after surface modification, the Mo 3d region presents two peaks corresponding to the 3d (530.0 eV), 55 MoO 3 (530.7 eV), 56 NiMoO 4 (530.9 eV), 57 and non-stoichiometric MoO x (530.6 eV). 58 Besides, chemical mapping using energy-dispersive X-ray spectroscopy performed in scanning transmission electron microscopy (EDS STEM) was performed on the cross-section of a modified surface (a TEM picture of the sample used for this analysis is presented in Figure S11). Figure 2c shows that O, Ni, and Mo atoms are well-dispersed within the entire coating. This figure shows a higher Ni content at the Si interface due to the deposited Ni thin film. In addition, the porosity of the coating results in a higher density at the bottom compared to the top (see also Figure S11). Finally, EDS, performed on the modified surface, revealed a Ni/Mo atomic ratio of 9.5. This value is not representative of the ratio in the deposited coating because EDS also probes the underlying (denser) Ni thin film. A more realistic Ni/Mo atomic ratio of 3 was determined from the XPS survey spectra presented in Figure S12 and is more representative of the composition in the coating. Taken together, these results show that the deposited coating is a porous and amorphous Ni-Mo-O (NMO) material containing high-oxidation-state Mo.

Next, we investigate its photoelectrocatalytic activity for UOR (Reaction 3).

Photoelectrochemical urea oxidation reaction

The anodic behaviour of several surfaces was investigated in a 1 M KOH electrolyte containing 0.33 M urea, which is the average concentration in human urine 14 and also a benchmark concentration in the UOR literature. Comparative voltammograms are shown in Figure 3a. While all anodes prepared on photoactive n-Si produced a negligible current in the dark, they exhibited high photocurrent densities (j) under simulated sunlight. Successive cyclic voltammograms (CVs) recorded with a surface prepared without the Ni thin film (n-Si/SiO x /NMO, purple CVs) revealed an onset potential (E onset , taken arbitrarily for j = 1 mA cm -2

) of 1.41 V (all potentials in this article are referred vs the reversible hydrogen electrode, RHE). In addition, a strong j decrease was noticed while cycling this photoelectrode, after 5 CV cycles, this surface lost 96% of its maximum j value due to photocorrosion. This highlights the importance of the Ni thin film, which is essential to avoid photoanode deactivation. 43 Conversely, photoanodes coated with the Ni thin film but not NMO (n-Si/SiO x /Ni, blue CV) had a low E onset of 0.91 V, attesting a decent activity for UOR. Note that the n-Si/SiO x /Ni surface was also annealed (in the same condition as the other electrodes) because it has been reported that annealing can beneficially influence n-Si/SiO x /Ni junction performance. 47 However, without NMO, j decreased strongly after 1.23 V, as a result of the deactivation of the accessible catalytic sites. After the UOR wave, j increases again as OER proceeds (vide infra). 59 An interesting aspect of this CV is the sharp peak visible during the backward scan at 1.2 V, attributed to the regeneration of the UOR catalytic sites that were passivated during the forward scan. 60 Similar CV shapes corresponding to catalyst deactivation/regeneration have been reported for UOR on Ni 60,61 and the oxidation of other molecules on various metals.

62,63

On the other hand, photoanodes comprising the Ni thin film and the NMO coating (n-Si/SiO x /Ni/NMO, red CV) exhibited optimal performance, namely a low E onset of 0.87 V, a high fill factor (as a result of high UOR kinetic) [START_REF] Walter | [END_REF] and no signs of UOR decay. A non-photoactive degenerate p ++ -Si surface was also used to manufacture a p ++ -Si/SiO x /Ni/NMO anode. This electrode was studied in the dark in the same electrolyte, as shown by the green curve in Figure 3a. The difference between the E onset measured with this anode and its photoactive counterpart (n-Si/SiO x /Ni/NMO) yields a photovoltage value of 400 mV, consistent with previous studies on photoanodes based on n-Si/SiO x /Ni Schottky junctions. Please do not adjust margins Please do not adjust margins Figure 3b compares the photoelectrochemical behaviour of an n-Si/SiO x /Ni/NMO photoanode in the presence (red CVs) and the absence of urea (black CVs). In the presence of urea, the CVs obtained at the first (thin line CVs) and the fourth (thick line CVs) cycle are almost identical, revealing good stability of the photoanode for UOR. In the absence of urea, the CVs feature a wave that starts at ≈0.9 V, attributed to the oxidation of Ni II (OH) 2 in Ni III OOH. This wave is followed by a j increase caused by OER, 70,71 that saturates in the light-limited regime (at the plateau, j = j lim ). The reduction wave observed during the backward scan corresponds to the conversion of Ni III OOH in Ni II (OH) 2 . In passing, we note that, in the absence of urea, j lim depends on the cycle number (this effect will be discussed in detail in the last section). According to this figure, it is clear that a benefit of UOR is that it allows a considerable increase of j at low overpotential. For instance, at the O 2 /H 2 O standard potential (1.23 V, depicted by a blue dotted line in Figure 3b), j recorded in the presence of urea (17.3 mA cm -2

) is more than three times higher than that recorded without urea (5.4 mA cm -2

). The effect of urea on the photoanodic response of n-Si/SiO x /Ni/NMO was also assessed by photoelectrochemical impedance spectroscopy (PEIS) measurements at an applied potential of 1 V (Nyquist and Bode plots are presented in Figure S13). Fits of the PEIS data resulted in charge transfer resistances at the solid/liquid interface of 3 and 850 in the presence and in the absence of urea, respectively (results are presented in Table S1), confirming the improved photoelectrochemical performance reached at low overpotential.

Stability during UOR

Next, stability in operation was assessed by potentiostatic measurements. These tests were performed at a low overpotential, a crucial parameter for photoelectrochemical UOR that has been overlooked. [36][37][38][39][40][41][42] Generally speaking, as previously discussed and shown in Figure 3b, UOR and OER start at distinct potentials, therefore, to ensure that UOR (and not OER) is actually occurring, it is important to perform stability tests at a low overpotential where OER does not occurs. Indeed, at high overpotential, UOR and OER can occur simultaneously, thus, in the light-limited regime, a loss of the UOR activity can be compensated by the OER, resulting in a stable CA curve even if UOR performance decreases. Indeed, drastic photocurrent decrease at low overpotential but not at high overpotential has been recently reported, 40 highlighting that operating photoelectrochemical UOR at high overpotential might lead to biased conclusions. Figure 4a presents chronoamperograms (CAs) recorded at 1 V, a potential below the OER onset, as seen in the black CV of Figure 3b. In these conditions, the NMO-free n-Si/SiO x /Ni (blue CA) showed a considerable activity decrease, as illustrated by a 70% j loss over 20 min. Conversely, the n-Si/SiO x /Ni/NMO (red CA) exhibited only a 12% j loss in the same timeframe. An experiment was also performed with n-Si/SiO x /Ni/NMO in the same condition except that the electrolyte was free of urea (black CA). Here, j drastically dropped from 5 to 0 mA cm -2 within the first seconds (i. e., after the oxidation of all active Ni(OH) 2 sites). This negative control confirms: i) the necessity of urea to generate high photocurrent densities and, ii) that OER does not occur at 1 V. Finally, long-term UOR was assessed for this photoanode, as shown in Figure 4b. The red CA shows that UOR can occur for several hours and that, after 5 hours of photoelectrolysis, j is still half of its initial value. Figure S14 shows that the photoanode was still active (j > 1 mA cm -2

) after 14 h of polarization. The green CA in Figure 4b shows that n-Si/SiO x /Ni/NMO can also be employed at a lower overpotential with similar stability. Further, a light interruption at t = 2.8 h (a more resolved CA is shown in Figure S15) caused an instantaneous j drop to 0 mA cm -2 , which indicates that the photoanode maintained its photoactivity during the test. The strong j spike that is observed when light is switched on is attributed to the rapid charge of holes in the space charge layer.

72 To verify UOR occurrence, we used a colorimetric method to measure the urea content in the electrolyte before and after a 3 h-long electrolysis at 1 V (experimental details are provided in the SI). Taking into account a stoichiometric ratio of 6 h + per molecule of urea electrolyzed (Reaction 3), the measured urea decrease corresponds to an 85% Faradaic efficiency. Conversely, a control experiment showed that illumination of the electrolyte with simulated sunlight during 3 h (without electrode) induced a negligible decrease of urea content (Figure S16). After prolonged photoelectrolysis, the n-Si/SiO x /Ni/NMO photoanodes were analyzed by SEM which revealed that the photoanode microscale morphology was not significantly affected by photoelectrolysis (Figure S17). Nevertheless, EDS analysis revealed a considerable Mo leaching during operation (Figure S18), well in line with recent reports on Mo-containing Ni-based electrocatalysts. [START_REF] Liu | [END_REF]74 Postelectrolysis XPS measurements (Figure S12b) further confirmed Mo leaching as no Mo could be detected after a 15h-long photoelectrolysis. This is also in agreement with the elemental analysis of the electrolyte that revealed the presence of Mo after photoelectrolysis. These results suggest that Mo is a structuring agent in for the NMO coating, which, by dissolving in the electrolyte, increases the surface density of the NiOOH active sites. [START_REF] Liu | [END_REF]74 Our photoanodes present, by far, the best performance and stability for Si-based photoanodes (Table S2). 41,42 Generally speaking, one can hardly compare the performance of our photoanodes with that reported on other semiconductors [36][37][38][39][40] because, as discussed before, in all cases, too high overpotentials are employed to specifically assess UOR (see Table S2).

Photoelectrochromism and behaviour at high overpotential

Stability in operation was also assessed at high overpotential and showed comparable stability (a CA recorded at an applied potential of 2.1 V is presented in Figure S19). As discussed before, at this overpotential, OER is also possible, thus, this CA does not constitute a valid criterion for UOR investigation. Nevertheless, in our specific case, studying the light-limited regime proved particularly interesting to evidence an significant role that urea plays in increasing j lim . Now, we discuss the intriguing behaviour that was reported in Figure 3b, namely, the fact that the maximum photocurrent obtained for OER decreases with the cycle number while it is not evolving when urea is present in the electrolyte. As seen in Gärtner's relation, j lim (the photocurrent plateau) is proportional to the photon flux reaching the semiconductor. 75 Thus, this behaviour suggests that the operation of n-Si/SiO x /Ni/NMO without urea leads to a decreased flux of photons reaching the Si. We show, in the following, that this is caused by the evolution of the optical properties of the NMO coating that induces a deleterious light absorption. NiO coatings are known to be electrochromic, switching from an "bleached" to a "opaque" state when biased at distinct potentials in alkaline electrolytes, as a result of the conversion of Ni(OH) 2 into NiOOH. 76,77 Figure 5a shows that, without urea, a linear correlation can be made between j lim (recorded at 2.1 V) and the charge integrated under the anodic Ni III /Ni II peak during 14 successive CV cycles. This suggests that the j lim loss is caused by the transformation of the Ni(OH) 2 into NiOOH. If XPS revealed the presence Ni(OH) 2 surface groups after preparation of the surface (Figure 2f,h), the increase of the charge associated to the Ni III /Ni II peak during cycling (Figure 3b) shows that the amount of Ni(OH) 2 /NiOOH groups increases upon CV cycling. During OER, Ni(OH) 2 is converted into NiOOH which is the active phase of Ni-based electrocatalysts and which is known to strongly absorb light in the visible region. 76,77 This is in good agreement with our ex-situ transmittance measurements performed on a Ni/NMO coating deposited on indium tin oxide (ITO) substrate (experimental details are provided in SI). Figure 5b shows that after a 10 minlong OER run, the ITO/Ni/NMO surface exhibits a considerable transmittance decrease, particularly pronounced in the visible range, attesting for the conversion of NMO to an absorbing layer. All these results evidence that the j lim decrease observed by CV during OER on n-Si/SiO x /Ni/NMO (black CVs in Figure 3b) is caused by the conversion of NMO to an opaque NiOOH-rich catalytic film. These results are in agreement with photoelectrochemical experiments performed with n-Si/SiO x /Ni/NMO made with a thinner NMO coating (42 nm) that resulted in a higher j lim value for OER (Figure S8a, thinner NMO film affords higher transmission during OER). This journal is © The Royal Society of Chemistry 20xx

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The photoelectrochemical behavior of n-Si/SiO x /Ni/NMO is different when urea is present in the electrolyte. As previously observed in the red CVs of Figure 3b, j lim is not significantly evolving upon photoanode cycling. This observation is corroborated by the potentiostatic experiment shown in Figure 5c. Here, we applied a potential of 2.1 V to an illuminated n-Si/SiO x /Ni/NMO photoanode in a urea-free electrolyte while recording j lim , and, at 10.5 min, urea was injected in the cell. In the first part of the experiment, j lim decreased due to the formation of NiOOH that decreases light transmission and, in turn, lowers the photocurrent, well in line with the CV observations of Figure 3b. When urea is injected, j lim instantaneously increases to 20 mA cm -2

, the value determined by voltammetry in the red CVs in Figure 3b. These results were further confirmed operando by photoelectrochemical spectroscopy. Incident photon-tocurrent efficiency (IPCE) spectra recorded on n-Si/SiO x /Ni/NMO at 2.1 V are presented in Figure 5d, in the presence (red spectrum) and the absence of urea (black spectrum). These results show that the photoconversion efficiency is high in the presence of urea, with a maximum IPCE of 60% in the visible range. Conversely, in the absence of urea, the photoconversion efficiency is much lower. This IPCE spectrum presents strong similarities with the transmission spectrum recorded on the ITO/Ni/NMO anode after OER, with a maximum IPCE of 40% at a wavelength (845 nm), that corresponds to the transmittance peak (Figure 5b). All these results show that urea grants high optical transmission through the NMO coating, promoting higher photocurrent density at high overpotential. Next, we propose an explanation of this effect based on the UOR reaction pathway. Pioneer studies reported that UOR (Reaction 3) at Ni-based electrocatalysts proceeds following the electrochemicalchemical (EC) mechanism as follows:

Conclusions

To conclude, we have reported the preparation and the study of Si-based photoanodes, composed of abundant materials, which can promote solar-assisted UOR for hours. The photoanodes' architecture is based on an n-Si/SiO x /Ni MIS junction onto which an amorphous NMO coating was deposited by a hydrothermal method. In this construct, n-Si is the light absorber, SiO x /Ni grants stability and NMO is the catalytic layer that promotes high UOR activity at low overpotential. Next, focus should be given to the elucidation of the role Mo, which plays an essential role for the hydrothermal growth of the coating onto the MIS structure (Figure S9). According to our measurements and recent literature [START_REF] Liu | [END_REF]74 it also probably acts as a structuring agent in the NMO coating, which, by dissolving in the electrolyte, increases the surface density of the NiOOH active sites. To the best of our knowledge, these photoanodes present the best performance reported so far for photoelectrochemical UOR on silicon (Table S2). In addition to the outstanding UOR activity, we have reported the optically adaptive nature of the NMO coating, which grants optical transmission of visible light in the presence of urea. In line with the UOR mechanism 60 and experimental considerations, we attribute this behaviour to the conversion of NiOOH into Ni(OH) 2 which counterbalance the deleterious electrochromic behaviour that occurs in the absence of urea. Next, investigation of the lifetime of the NiOOH phase during UOR by operando photoelectrochemical methods is an important aspect to gain further information on this mechanism. We think that this report presents considerable advances for the valorisation of polluted effluents for solar H 2 production and will lead to original strategies for the integration of highly active catalytic layers on semiconductor photoelectrodes.

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Escadeillas and Bertrand Lefeuvre are acknowledged for their help with elemental analyses.

Notes and references

This journal is © The Royal Society of Chemistry 20xx

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Figure 2 .

 2 Figure 2. a) Coloured and tilted SEM cross-section picture of an n-Si/SiOx/Ni/NMO surface (original uncoloured picture is shown in Figure S3c). b) SEM top picture of an n-Si/SiOx/Ni/NMO surface. c) STEM-ADF (greyscale) and EDS STEM (colour) pictures of an n-Si/SiOx/Ni/NMO cross-section showing the O (blue), Ni (purple), and the Mo (orange) content. Dashed lines indicate the boundary of the Ni/NMO layers, which thickness is 105 nm, as determined in the TEM picture of Figure S11. d) XRD patterns of n-Si/SiOx/Ni (blue curve) and n-Si/SiOx/Ni/NMO (red curve) reference Bragg peaks corresponding to Ni (ICSD 64989) and NiO (ICSD 76669) are shown by vertical blue and red lines. e) Highresolution TEM picture of the NMO coating. f-h) Ni 2p (f), Mo 3d (g), and O 1s (h) XPS spectra of n-Si/SiOx/Ni (top) and n-Si/SiOx/Ni/NMO (bottom). Disks are experimental data, coloured curves are fits, black curves are the background, and the fit envelope. In g) the reported binding energies for Mo V and Mo VI are indicated by dotted lines.

Figure 3 .

 3 Figure 3. a) Voltammograms recorded in 1 M KOH + 0.33 M urea in the dark on n-Si/SiOx/Ni/NMO (black curve) and p ++ -Si/SiOx/Ni/NMO (green curve, forward scan) and under illumination on n-Si/SiOx/NMO (purple curve, 5 successive cycles), n-Si/SiOx/Ni (blue curve, arrows indicate the scan direction), and n-Si/SiOx/Ni/NMO (red curve). b) 1 st (thin line) and 4 th (thick line) CVs recorded on illuminated n-Si/SiOx/Ni/NMO in 1 M KOH (black curves) and 1 M KOH + 0.33 M urea (red curves). The standard potential of the O2/H2O couple (1.23 V) is represented by a blue dotted line. The scan rate is 100 mV s -1 , the illumination is provided by a solar simulator (100 mW cm -2 , AM 1.5G).

Figure 4 .

 4 Figure 4. a) CAs recorded at 1 V under illumination in 1 M KOH without urea on n-Si/SiOx/Ni/NMO (black curve), with 0.33 M urea on n-Si/SiOx/Ni (blue curve) and n-

Figure 5 .

 5 Figure 5. a) Plot of the photocurrent density at 2.1 V as a function of the charge under the Ni III /Ni II peak, extracted from cyclic voltammetry. b) Transmittance spectra recorded on ITO (blue curve), ITO/Ni/NMO (red curve), and ITO/Ni/NMO after 10 min of OER (black curve). c) Chronoamperogram recorded while applying 2.1 V under illumination on n-Si/SiOx/Ni/NMO in 1 M KOH without urea, at 10.5 min (red arrow) 0.33 M urea is injected into the cell. d) IPCE spectra recorded on n-Si/SiOx/Ni/NMO at 2.1 V in 1 M KOH (black curve) and in 1 M KOH + 0.33 M urea (red curve).

  These results show that in contrast to OER, where the optical performance of the NMO coating is limited by NiOOH, in the presence of urea, the optical properties of the NMO catalytic film are dominated by the Ni(OH) 2 phase. This is in good agreement with the size of the cathodic peaks observed in the CVs of Figure3b, which reveal a lower amount of electrochemically-addressable NiOOH centers when urea is present.

		60
	6 Ni(OH) 2 (s) + 6 OH	-(aq) + 6 h +  6 NiOOH (s) + 6 H 2 O (l) (4)
	6 NiOOH (s) + (NH 2 ) 2 CO (aq) + H 2 O (l)
	 6 Ni(OH) 2 (s) + N 2 (g) + CO 2 (g)	(5)
	First, Ni(OH) 2 is electrochemically converted into NiOOH
	following Reaction 4, then the chemical reaction between
	NiOOH and urea creates the products and regenerates
	Ni(OH) 2 , following Reaction 5. In our experiments, in the
	presence of urea, the conversion of opaque NiOOH into
	transparent Ni(OH) 2 (due to Reaction 5), allows maintaining
	the high transmittance of NMO and promotes high j lim . Thus,
	the NMO coating is optically adaptive, enabling optical
	transmission when UOR occurs. This scenario is very similar to
	what is known for the electrochemical switching of
	electrochromic NiO-based films except, that, in our case, a
	reactant (urea) triggers the optical switch.

This journal is © The Royal Society of Chemistry 20xx J. Name., 2013, 00, 1-3 | 5

Acknowledgments

Loïc Joanny and Francis Gouttefangeas from ScanMAT/CMEBA are acknowledged for SEM analyses. Khalil Youssef is acknowledged for his help with colorimetric titration. Muriel

Author contributions

G.L. conceived the idea. G.L., R.A., and D.F. secured funding and cosupervised the research. J.D. developed the preparation method, manufactured the electrodes, and performed the experiments. G.L. and J.D. analyzed the electrochemical results. S.Z., L.S., A.V., V.D., and S.F. performed and analyzed surface characterizations. All authors reviewed and commented on the article.

Conflicts of interest

There are no conflicts to declare.