Genoveva Vargas-Solar
email: genoveva.vargas@imag.fr

Gavin Kemp
email: gavin.kemp@liris.cnrs.fr

Irving Hernández-Gallegos

Javier A Espinosa-Oviedo

Catarina Ferreira
email: catarina.ferreira-da-silva@liris.cnrs.fr

Da Silva

Parisa Ghodous
email: parisa.ghodous@liris.cnrs.fr

Exploring and Curating Data Collections with CURARE

This paper demonstrates CURARE, an environment for curating raw data collections and assisting data scientists to explore them. CURARE implements a data curation model used to store structural and quantitative metadata such as the number of columns, de name of columns and the statistics of the values of every column. It provides associated functions for exploring these metadata. The demonstration proposed in this paper is devoted to evaluate and compare the effort invested by a data scientist when exploring data collections with and without CURARE assistance.

INTRODUCTION

The emergence of new platforms that produce data at different rates, is adding to the increase in the amount of data collections available online. Open data initiatives frequently release data collections as sets of records with more or less information about their structure and content. For example, different governmental, academic and private initiatives release open data collections like Grand Lyon in France 1 , Wikipedia 2 , Stack Overflow 3 and those accessible through Google Dataset Search [START_REF] Halevy | Goods: Organizing google's datasets[END_REF] . Releases often specify minimum "structural" metadata as the size of the release, the access and exploitation license, the date, and eventually the structure of the records (e.g., names and types of columns). This brings an unprecedented volume and diversity of data to be explored.

Data scientists invest a big percentage of their effort processing data collections to understand records structure and content and to generate descriptions. Useful descriptions should specify the values' types, their distribution, the percentage of null, absent or default values, and dependencies across attributes. Having this knowledge is crucial to decide whether it is possible to run analytics tasks on data collections directly or whether they should be preprocessed (e.g., cleaned). Therefore, several questions should be considered by a data scientist. For example, whether one or more data collections can be used for target analytics tasks; whether they are complementary or not, or whether they can be easily integrated into one data set to be analyzed; whether certain attributes have been cleaned, computed (e.g., normalized) or estimated. Keeping track of cleansing changes is important because such operations can bias certain statistics analysis and results.

Therefore, the data scientist must go through the records and the values exploring data collections content like the records structure, values distribution, presence of outliers, etc. This is a time consuming process that should be done for every data collection. The process and operations performed by the data scientist are often not described and preserved, neither considered as metadata. Thus, the data scientist effort cannot be capitalized for other cases and by other data scientists.

Curation tasks include extracting explicit, quantitative and semantic metadata, organizing and classifying metadata and providing tools for facilitating their exploration and maintenance (adding and adjusting metadata and computing metadata for new releases) [3, 4, 6]. The problem addressed by curation initiatives is to address the exploration of data collections by increasing their usefulness and reducing the burden of exploring records manually or by implementing ad-hoc processes. Curation environments should aid the user in understanding the data collections' content and provide guidance to explore them [1, 2, 5, 8].

Our work focuses on (semi)-automatic metadata extraction and data collections exploration which are key activities of the curation process. Therefore, we propose CURARE, an environment for curating and exploring data collections.

CURARE provides tools in an integrated environment for extracting metadata using descriptive statistics measures and data mining methods. Metadata are stored by CURARE according to its data model proposed for representing curation metadata (see Figure 1). The data model organizes metadata into four main concepts: • Data Collection: models structural metadata concerning several releases like the number of releases it groups, their aggregated size, the provider, etc. • Release: models structural metadata about the records of a release (file) including for example the columns' name in the case of tabular data, the size of the release, the date of production, access license, etc. • Release view: models quantitative metadata of the release records of a data collection. For example, the number of columns and the number of records in a release. A release view can store, for every column in all the records of a release, its associated descriptive statistics measures (mean, median, standard deviation, distribution, outlier values). • View: models quantitative aggregated metadata about the releases of a data collection.

CURARE also provides functions for exploring metadata and help data analysts determining which are the collections that can be used for achieving an analytics objective (comparing several collections, projecting and filtering their content). Rather than performing series of self-contained queries (like keyword search or relational ones when possible), a scientist can stepwise explore into data collections (i.e., computing statistical descriptions, discovering patterns, cleaning values) and stop when the content reaches a satisfaction point.

The demonstration proposed in this paper is devoted to evaluate and compare the effort put by a data scientist when exploring data collections with and without CURARE assistance. Through a treasure seeking metaphor we ask users to find clues within non curated Stack Overflow releases. Then, we compare the effort for finding cues by exploring metadata extracted by CURARE. The tasks are intended to show the added value of using metadata to explore data collections for determining whether they can be used for answering target questions.

The remainder of the paper is organized as follows. Section 2 describes the general architecture of CURARE and the extraction of structural and quantitative metadata. Section 3 describes the demonstration scenario for CURARE and the tasks used for measuring user experience during the demo. Section 4 concludes the paper and discusses lessons learned from the demonstration.

CURARE

The curation tasks implemented by CURARE are coordinated through a general iterative workflow consisting in three steps: (i) data collections' harvesting (manually or automatically) and preservation; (ii) structural and statistical meta-data extraction; (iii) exploration.

Figure 2: CURARE data curation workflow

The workflow is iterative because data collections can be updated with new releases and therefore releases are harvested recurrently. Similarly, as a result of curated data collections exploration, new metadata can be defined and the processing step can be repeated to include new metadata and store them.

General architecture

Figure 3 shows the architecture of CURARE consisting of services that can be deployed on the cloud. The current version of CURARE are Azure services running on top of a data science virtual machine. The services of CURARE are organized into three layers that correspond to the phases of the curation workflow. They are accessible through their Application Programming Interfaces (API's). Services can be accessed vertically as a whole environment or horizontally from every layer.

• The first layer is devoted to harvesting data collections and extracting structural metadata like the size, the provenance, time and location time-stamps. • The second layer addresses distributed storage and access of curated data and metadata. • The third layer provides tools for extracting quantitative metadata by processing raw collections. The structural and quantitative metadata of CURARE are organized into four types of persistent data structures implementing the CURARE data model (i.e., data collection, release, view and release view). According to the CURARE approach, a data collection consists of several sets of data released at a given moment. For example, Stack Overflow is a data collection consisting of packages These data structures are then explored using ad-hoc operators within semi-declarative expressions or programs instead of directly exploring raw data collections. For example, is a release included in another? To which extent a release has new records with respect to others? Which is the percentage of missing values of the releases of a data collection?

Extracting structural metadata

The data collection model shown in the left hand side of Figure 1 provides concepts for representing data collections as sets of releases of raw data. Each release consists of a set of items (e.g. records). The data collections model is used by the data harvesting and cleansing services for organizing structural and context metadata related to collections (provider, objective, URL, item structure).

The demonstrated version of CURARE provides a data collection upload facility for CSV files, which is an explicit data harvesting process. During this process, the structure, the size and release date of the file are extracted automatically. Then, other metadata for example the URI of the provider and the type of license can be provided by the data scientist by filling a form.

As said before, metadata are stored by CURARE. Thus, in the exploration phase a data scientist can search for releases of a given size, with a "open source" licence, or produced by a specific provider, expressing queries or executing explicit exported methods.

Extracting quantitative metadata

The view model of CURARE shown in the right hand side of Figure 1 provides concepts for representing quantitative and analytic aspects of the releases of a data collection. For instance, statistics of the content including the distribution of the values of each attribute across the items of a release, missing values, null values.

Depending on the attribute type (only atomic types are considered for statistics) the strategies for computing measures can change. CURARE first defines for every attribute in a tabular file, for example, its type and it approximately discovers possible null, absent and default values. Then, it computes description statistics measures (mean, mode, median, standard deviation, distribution) of the values of every attribute of the structure of the data collection in tabular format. It interacts with the data scientist to decide what to do with those attributes with a domain containing "dirty" values. Should these values be excluded from the computation? Or how can they be adjusted if they should be considered? If values are modified, should CURARE create a new release? Should it be preserved completely tagging the modified values as modified and indicating the applied formula or procedure. This is specified by the data scientist and managed by CURARE. For computing statistics of string values, CURARE processes the strings and creates frequency matrices and inverted indexes for the terms.

CURARE processes collections with many attributes and records that can be somehow costly depending on the tasks the data is used for, and the data volume. Thus, CURARE uses a Spark environment for computing statistics measures that sits on the data science virtual machine [START_REF] Martin L Kersten | The researcher as guide to the data deluge: Querying a scientific database in just a few seconds[END_REF] . This strategy can be related to existing approaches like the one proposed in [7].

DEMONSTRATION OVERVIEW

The demonstration of CURARE uses a Jupyter notebook prepared for performing the tasks intended to test the use of metadata (i.e., entities of the CURARE data model) for exploring data collections. We use the Azure Notebooks environment [START_REF] Stonebraker | Data Curation at Scale: The Data Tamer System[END_REF] to run the demonstration. The back-end of the demonstrated version uses the Python data science libraries, nltk [START_REF] Wasay | Data canopy: Accelerating exploratory statistical analysis[END_REF] for dealing with the processing of string typed attributes. We use ATLAS [START_REF] Sam Likun Xi | Beyond the wall: Near-data processing for databases[END_REF] , the clustered public service of MongoDB for storing metadata associated to raw data collections.

The demonstration provides 3 releases of Stack Overflow9 made available between the 1st. and 4th. January 2018 each consisting in five files "badges", "comments", "posts", "users" and "votes". These files range between ca. 300 KB to 20 MB.

CURARE extracts structural metadata and stores them as Data Collection documents according to its data model. It extracts quantitative metadata and stores them as Views documents. For the demonstration purposes we use a notebook that shows the process and the results. The releases used in the demonstration are processed and the results are stored in Atlas. The result weights 126,5 MB in Mongo and the data collection of structural metadata 9,5 KB.

Demonstration scenario. The demonstration of CURARE shows in which situations it can be useful to have an integrated curation and exploration environment. This can be evaluated through a set of tasks proposed by the demonstration scenario with a game called The cure challenge. The objective is to compare the effort when performing tasks to explore Stack Overflow releases manually and with CURARE.

When the game is activated it gives access to raw data collections and to CURARE metadata. The game consists of two curation matches where a data scientist has to perform the following tasks.

(1) Data collections exploration tasks:

• Discover the release of the Stack Overflow data collection with the best quality. That is, the one with less missing, null and default values in the posts. • Compare the releases size in terms of number of records.

• Compare releases in terms of values distribution for a given attribute. • Compare releases with respect to the topic by comparing terms of a given attribute. (2) Discover the attribute(s) of the Stack Overflow posts that can be used to compute the popularity of the answers and the reputation of the author (stared answers and authors). (3) Discover the attribute(s) that can be used to identify the most trendy topics addressed in the release. Will missing, null, default values bias the observation of the trends? (4) Choose the attributes that can be used as sharding keys to fragment the release using a hash based and an interval based strategy.

In the first match the tasks are done by exploring directly the raw data collections. The second using CURARE's exploration facilities. For both matches a dashboard shown in Figure 4 automatically measures the degree of effort given by comparing with the accuracy/precision and correctness of the answers against time used for providing an answer. These measures are completed with an explicit score for every task given by the data scientist (one star low effort, three stars high effort).

Measuring data exploration effort. The experiment is assessed by comparing the evaluation results of the tasks performed in the two matches. We evaluate:

• Whether the metadata in views provide representative information of the raw content of a release (Q 1 and Q 2 ) • How easy it is to see data collection quality in terms of consistency of the structure, the degree of missing, null and absent values of the attributes (Q 2 ) • Usefulness of views for exploring the data collections to determine which kind of analytics questions they can answer. (Q 3 , Q 4 )

CONCLUSION AND RESULTS

We demonstrate CURARE that implements a data curation approach integrating metadata describing the structure, content and statistics of raw data collections. Thereby raw data collections can be comfortably explored and understood for designing data centric experiments through exploration operations. The demonstration shows the usefulness of CURARE by measuring the effort of a data scientist for performing exploration tasks in predefined Stack Overflow releases, used as demonstration examples.

  Figure 1: CURARE Model

Figure 3 :

 3 Figure 3: General functional architecture of CURARE

https://azure.microsoft.com/en-us/services/virtual-machines/data-science-virtualmachines/

[START_REF] Stonebraker | Data Curation at Scale: The Data Tamer System[END_REF] https://notebooks.azure.com

https://www.nltk.org

https://www.mongodb.com/cloud/atlas

https://data.stackexchange.com/stackoverflow/query/new

ACKNOWLEDGEMENT

This work was partially funded by the Rhône-Alpes region through the project AMBED of the ARC 7 program 10 and the LDE Centre for BOLD Cities 11 . The implementation of CURARE was partially funded by the CONACYT "beca mixta" fellowship program of the Mexican government awarded to Irving Hernández Gallegos.

DATA CLEANING SERVICE


domain: sde sdv

text:
Blandine Gaillard
email: blandine.gaillard5@gmail.com

Claire E Lazareth

Hugo Lestrelin

Elise Dufour

Roberto V Santos

Carlos E C Freitas

Marc Pouilly

Seasonal oxygen isotope variations in freshwater bivalve shells as recorders of Amazonian rivers hydrogeochemistry

Keywords: Amazon basin, freshwater, bivalve shells, hydroclimate, isotope ecology, isotope hydrology, oxygen isotopes

Freshwater bivalve shell oxygen isotope values (δ 18 OS) may act as a recorder of river δ 18 O variations that can then be interpreted in terms of hydrology (e.g. precipitationevaporation balance, precipitation and river discharge patterns). We investigated the potential of this proxy measured across the hinge of South American unionid shells: Anodontites elongatus collected in Peru and A. trapesialis in Brazil. The isotopic signatures were reproducible between individuals of the same species. A. trapesialis clearly showed a strong δ 18 OS cyclicity in accordance with its growth patterns while A. elongatus presented less clear δ 18 OS with lower amplitude. We confirm that the deposition of successive growth lines and increments is annual, with growth line corresponding to the wet season. Also, we suggest that low amplitude of δ 18 OS in the A. elongatus shells indicates a habitat close to the river while large amplitude of δ 18 O cycles observed in A. trapesialis shells would reflect a floodplain lake habitat, seasonally disconnected from the river and thus subjected to higher seasonal fluctuations in water δ 18 O. Considering these promising first results, future studies could be directed towards the use of fossil shells to reconstruct the past and present hydrological and geochemical conditions of the Amazon.

Introduction

The Amazon basin holds several world records: the Amazon River is the world's largest one included in the largest basin in the world, supporting the largest tropical forest and diversity of freshwater fish species. This continental hydrosystem participates significantly to the global hydrological, climatic, and carbon cycles, and its contribution to the ocean in terms of sediment is also considerable [START_REF] Filizola | Suspended sediment yields in the Amazon basin: an assessment using the Brazilian national data set[END_REF][START_REF] Moreira-Turcq | Exportation of organic carbon from the Amazon River and its main tributaries[END_REF]. Moreover, it is the supplier of multiple ecosystemic services to the human populations such as food, incomes via fishing, and transport [START_REF] Castello | The vulnerability of Amazon freshwater ecosystems[END_REF]. Climate change has, however, already impacted the hydrology of this hydrosystem, e.g. in increasing extreme hydrological event occurrences [START_REF] Ronchail | The flood recession period in Western Amazonia and its variability during the 1985-2015 period[END_REF][START_REF] Villar | Climate variability and extreme drought in the upper Solimoes River (western Amazon Basin): understanding the exceptional 2010 drought[END_REF][START_REF] Marengo | Extreme seasonal droughts and floods in Amazonia: causes, trends and impacts[END_REF]. It is thus crucial to better understand the functioning of this system, its temporal variability, and the modifications induced by the global and regional changes, to define optimal strategies of sustainable development. To this end, a geochemical and hydrological monitoring programme was launched in the Amazonian basin in 2003 (HYBAM observatory; www.ore-hybam.org). Indeed, geochemical tools have been used to define hydrogeochemical zones within the basin to trace the water sources of the rivers and their evolutions and to understand erosion processes and global geochemical cycles [START_REF] Gaillardet | Chemical and physical denudation in the Amazon River Basin[END_REF][START_REF] Poitrasson | Iron isotope composition of the bulk waters and sediments from the Amazon River Basin[END_REF][START_REF] Seyler | Distribution and partition of trace metals in the Amazon basin[END_REF][START_REF] Dellinger | Lithium isotopes in large rivers reveal the cannibalistic nature of modern continental weathering and erosion[END_REF]. These geochemical tools are also of paramount importance in ecology and in the following-up of fish migration or river pollution, for example [START_REF] Duponchelle | Trans-Amazonian natal homing in giant catfish[END_REF][START_REF] Cao | Hydrochemical zoning: natural and anthropogenic origins of the major elements in the surface water of Taizi River Basin, Northeast China[END_REF][START_REF] Pouilly | Geographical origin of Amazonian freshwater fishes fingerprinted by 87 Sr/ 86 Sr ratios on fish otoliths and scales[END_REF][START_REF] Sousa | Movement patterns of adult peacock bass Cichla temensis between tributaries of the middle Negro River basin (Amazonas -Brazil): an otolith geochemical analysis[END_REF]. However, due to the huge extension of this basinbetween 5°N and 20°S and from the Andes to the Atlantic Ocean, covering approximately 7,500,000 km2 [START_REF] Goulding | Smithsonian Atlas of the Amazon[END_REF] the instrumental monitoring is expensive and demands a complex logistic, particularly in remote areas [START_REF] Gaillardet | Chemical and physical denudation in the Amazon River Basin[END_REF][START_REF] Santos | Source area and seasonal 87 Sr/ 86 Sr variations in rivers of the Amazon basin[END_REF]. The dynamic geological evolution of the basin, together with the pronounced seasonal variation of rainfall and hydrological regime, lead to the formation of three landscapes characterised by distinct hydrology and hydrological variations: (1) the 'Terra Firme', corresponding to land that is never flooded, (2) the 'Varzea' floodplains including secondary channels, lakes, and lands which are permanently or temporarily inundated according to the hydrological regime, and (3) the main channel of the river that corresponds to permanent flowing water body. Because of the huge spatial coverage and the complexity of the Amazon basin, its hydrology and geochemistry is not fully known [START_REF] Duponchelle | Trans-Amazonian natal homing in giant catfish[END_REF]. Because of the dynamic evolution of the Andes, the Amazon basin and its drainage system are under permanent changes. To better understand and track these changes, including river channel migration and floodplain development, it is necessary to develop high-resolution environmental proxies such as those based on aquatic mollusc shells. Indeed, these organisms may record endogenous and environmental information, from seasonal to inter-annual scales, both for present day or past periods [START_REF] Butler | New research in the methods and applications of sclerochronology[END_REF][START_REF] Schöne | Unraveling environmental histories from skeletal diariesadvances in sclerochronology[END_REF][START_REF] Goodwin | Resolution and fidelity of oxygen isotopes as paleotemperature proxies in bivalve mollusk shells: models and observations[END_REF][START_REF] Schöne | Looking back over skeletal diarieshigh-resolution environmental reconstructions from accretionary hard parts of aquatic organisms[END_REF]. The potential of freshwater bivalve shells as an archive of geochemical and environmental conditions of their habitats (e.g. precipitation and river discharge patterns, (paleo)temperature, pollution) has been recognised in many studies [START_REF] Dettman | The use of oxygen isotope variation in shells of estuarine mollusks as a quantitative record of seasonal and annual Colorado River discharge[END_REF][START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF][START_REF] O'neil | Do freshwater mussel shells record road-salt pollution?[END_REF][START_REF] Versteegh | Seasonally resolved growth of freshwater bivalves determined by oxygen and carbon isotope shell chemistry[END_REF][START_REF] Vonhof | Environmental and climatic control on seasonal stable isotope variation of freshwater molluscan bivalves in the Turkana Basin (Kenya)[END_REF]. One powerful proxy is the oxygen isotope composition (δ 18 OS1), which records rainfall or river discharge patterns in such mollusc shells [START_REF] Versteegh | Seasonally resolved growth of freshwater bivalves determined by oxygen and carbon isotope shell chemistry[END_REF][START_REF] Abell | The shells of Etheria elliptica as recorders of seasonality at Lake Victoria[END_REF][START_REF] Dettman | Controls on the stable isotope composition of seasonal growth bands in aragonitic fresh-water bivalves (unionidae)[END_REF]. In contrast to studies that use shells as paleoclimatic proxies in the Amazon [START_REF] Kaandorp | Seasonal Amazonian rainfall variation in the Miocene Climate Optimum[END_REF][START_REF] Kaandorp | Ecological implications from geochemical records of Miocene Western Amazonian bivalves[END_REF][START_REF] Vonhof | Reconstruction of the Miocene western Amazonian aquatic system using molluscan isotopic signatures[END_REF][START_REF] Vonhof | Paleogeography of Miocene Western Amazonia: isotopic composition of molluscan shells constrains the influence of marine incursions[END_REF], only one study has addressed the potential of modern amazonian freshwater bivalve shells as bio-archives of environmental conditions [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF]. In an attempt to push forward the use of shells as environmental proxy in the Amazon, we studied oxygen isotopes of modern Anodontites sp. shells that have grown under distinct environmental conditions in the Amazon basin. Besides addressing intraspecies reproducibility, we have also evaluated how the observed oxygen isotope variations and patterns can be used to determine the hydrological condition of the environment in which they have grown.

Material and method

Study sitesenvironmental characteristics

The Unionidae shells were collected empty in 2015 by local people in two South American sites. We observed that, in such environments, shells degrade rapidly after death of the animal. Even during the animal's lifetime, the periostracum on the hinge can be locally damaged (pers. comm., C.E. Lazareth). Here, since the shells were all in the same well-preserved state, presumably they have died recently. Two A. trapesialis shells were collected in a lake bordering the Rio Solimões close to the Ilha Paciencia that is located between Manacapuru and Manaus in Brazil (Table 1, Figure 1). This lake, located in the annual active band of the river, at around 1 km from the mainstream at low water level, is disconnected from the Rio Solimões several months per year (4-6 months). Note that the so-called Solimões River (Brazil) is the downstream part name of the Amazonas River (Peru). Two A. elongatus shells were collected in a marginal lake along the Rio Amazonas close to Iquitos in Peru (Table 1, Figure 1). Unfortunately, the exact distance of the lake from the mainstream is unknown. On each site, shells with similar size were chosen to avoid any age-related isotope fractionation effect. The amount of precipitation as well as the oxygen isotope values of rivers and precipitation (δ 18 O R and δ 18 O P respectively) were taken from the International Atomic Energy Agency's (IAEA) Global Networks of Isotopes in Precipitation and Rivers (GNIP, GNIR; http://www.iaea.org/water) (Table 2). For the Rio Solimões (Brazil), river water oxygen isotope values come from the Manacapuru station (distant from around 80 km from the shells sampling location) and precipitation amount and δ 18 O P values from Manaus (about 35 km from the shells sampling location) (Figure 1, Table 2). At this place, during the dry season, which lasts for about 3 months around August, precipitation is <100 mm month -1 and the δ 18 O P value is higher than -2 ‰ (vs. Vienna Standard Mean Ocean Water, V-SMOW). During the wet season (5 months around March), precipitation is >250 mm month -1 and δ 18 O P values are the lowest of the year (<-4 ‰ V-SMOW) (Figure 2(a)). Accordingly, the oxygen isotope values of the river water (δ 18 O R ) of the Rio Solimões vary seasonally with most positive values (-4.91 and -5.65 ‰ V-SMOW) during September and October and most negative ones (-5.77 and -6.69 ‰ V-SMOW) during May and June (Figure 2(a)). For the Rio Amazonas site (Peru), the precipitation data (amount and δ 18 O P ) were taken from the Iquitos station (about 20 km from Iquitos city; Figure 1, Table 2). The precipitation amount ranges from 156 mm month -1 during the dry season (August) to more than 500 mm month -1 during the wet one (April, Figure 2(b)). The lowest δ 18 O P values (δ 18 O P = -8.89 ± 4.07 ‰ March and -7.06 ± 3.23 ‰ October, V-SMOW) occur during the wet seasons and the highest (δ 18 O P = -1.87 ± 0.96 ‰ August and -4.44 ± 1.62 ‰ February, V-SMOW) during the wet one (Figure 2(b)).

Table 2 Environmental data used in this study. Monthly precipitation and δ 18 OP are from the GNIP (Global Network of Isotopes in Precipitation) database, and δ 18 OR from GNIR (Global Network of Isotopes in Rivers). The mean seasonal range is expressed as the mean (SD) difference between the highest (max) and the lowest (min) monthly mean. SD: standard deviation. See figure 1

Shell preparation

Shell lengths and heights are reported in Table 1. We prepared the shell hinges for analysis since the growth pattern (succession of increment and growth lines) is clearer than in other parts of the shell. In addition, hinge represents the whole life, while also limiting the number of samples to collect and analyse to obtain several years of seasonal isotope profile. All shells were cleaned and air-dried before further preparation. One valve of each specimen was cut along the axis of maximum growth (Figure 3(b)) using a water diamond saw (Isomet 5000®, Buehler), and afterwards a slice about 5 mm thick was cut from these half-valves (Figure 3(c)). Since the small and thin A. elongatus shells could have broken during preparation, one valve of each specimen was embedded in epoxy resin (Epoxicure®, Buehler) before cutting. The A. trapesialis cross-sections were manually broken and hinges were embedded in epoxy resin. Finally, embedded hinge cross-sections were polished using grinding disks with decreasing grain size and diamond suspensions (down to 1 µm) on polishing cloths.

Microdrilling and oxygen isotope analysis

Samples for oxygen isotope measurements were drilled in the hinge using a computermonitored microdrilling equipment (New Wave® Micromill) at the 'Muséum National d'Histoire Naturelle' (MNHN) in Paris. Growth increments separated by growth lines were observed in all hinges viewed using an optical microscope under diffused light. The hinges were sampled continuously from the internal to the external part of the shell taking care to maintain each sampling groove parallel to growth lines. The distance between successive grooves was determined to provide enough carbonate powder for a valid oxygen isotope analysis and an infra-seasonal resolution assuming that growth lines, corresponding to a growth cessation or important slow down [START_REF] Rhoads | Skeletal growth of aquatic organisms: biological records of environmental change[END_REF], were annual due to the clear seasonal Amazonian environmental variability (characterised by alternation of dry and wet seasons). Grooves were about 60 µm-large for approximately 3 mm long. Carbonate powder weighted 41 ± 26 µg (n = 129). On average, 9 and 6 sampling grooves were done per growth increment for A. trapesialis and A. elongatus, respectively. Carbonate powder samples were reacted with orthophosphoric acid at 70 °C, and δ 18 OS values were measured using a VG SIRA 9 mass spectrometer coupled to a ThermoKiel IV carbonate device at the Institut des Sciences de la Terre de Paris (ISTeP, University Paris VI). δ 18 OS is expressed in per mille (‰ standardised against the Vienna PeeDee Belemnite -VPDB standard). Since Anodontites sp. shells are aragonitic, we used the Kim et al. [START_REF] Kim | Phosphoric acid fractionation factors for calcite and aragonite between 25 and 75°C: Revisited[END_REF] equation to calculate the acid fractionation factor for aragonite at 70 °C and corrected our δ 18 OS isotope values accordingly. The analytical precision was 0.03 ‰ for δ 18 OS (1σ of NBS19 standard measurements done every 10 shell samples, n = 129 in total; NBS19 V-PDB values are δ 18 O = -2.20 ‰). All isotope data, including non-presented δ 13 C S , have been deposited in the information system Zenodo (DOI: 10.5281/zenodo.1217596).

Data analysis

Before undertaking parametric statistical tests, normality of the distribution and equality of variances of data were verified using the Shapiro-Wilk and F-tests, respectively. Nested two-way ANOVA were then done to test the significance of the differences in isotope values between the two specimens of each Anodontites species and between the two species/sites. All analyses were done using the statistical package R version 3.3.0 (R Core Team, 2017). A significance threshold of α = 0.05 was adopted for all statistical tests.

Results

Hinge growth patterns

In A. trapesialis, 4 and 5 growth lines and growth increments were counted for At-1 and At-2 hinges, respectively (Figure 4(a,b)). In the hinge of A. elongatus Ae-1, 8 growth lines and 7 growth increments were observed (Figure 4(c)) and 3 growth lines and 4 growth increments for specimen Ae-2 (Figure 4(d)).

δ 18 OS intraspecific and temporal variability

On average, there was no significant isotope composition difference between shells of the same species that had grown presumably at the same site (p-value > 0.05; Table 3). However, average oxygen isotope values significantly differed between the two species collected in two different sites. Mean δ 18 OS (± SD) and range were significantly higher in A. trapesialis shells from Brazil (δ 18 OS = -4.42 ± 1.74 ‰; 6.70 ‰) than in A. elongatus from Peru (δ 18 OS = -6.23 ± 0.73 ‰; 3.28 ‰) (p-value < 0.001) (see Table 3 for specimen's data). All shells presented isotope cyclicity with one cycle defined as the isotope variations comprised between two successive lowest δ 18 OS values. Cyclic amplitude was calculated as the difference between the highest and the lowest values of each δ 18 OS cycle within a shell. Cyclic variations were higher in A. trapesialis than in A. elongatus with mean amplitudes of 4.46 ± 1.37 vs. 1.59 ± 0.77 ‰ (Figure 5, Table 3). At-1 and At-2 presented 3 and 4 cycles, respectively. The more negative δ 18 OS values corresponded to growth lines and the more positive to growth increments. A positive trend on δ 18 OS was observed in At-1 (Figure 5). For A. elongatus, 4 cycles per shell were counted (Figure 5). Low δ 18 OS in Ae-1 corresponded to growth lines, except for growth line n°2; while δ 18 OS variations did not match the growth pattern in Ae-2 (Figure 5). Table 3. Oxygen isotopes data (δ 18 OS) obtained in the hinge of the 4 Anodontites spp. specimens. The cyclic amplitude in δ 18 OS is expressed as the mean (SD) of the range between the highest (Max) and the lowest (Min) values of each δ 18

Discussion

δ 18 OS variations and growth pattern

It has been shown in many bivalve species that shell growth patterns can be used to give an age to the shell as well as to reconstruct environmental parameter (e.g. water temperature) changes [START_REF] Kelemen | Calibration of hydroclimate proxies in freshwater bivalve shells from Central and West Africa[END_REF]. In freshwater unionid bivalve shells that lived in lake or floodplain lake, growth decreases or cessations were linked to high water turbidity related to high discharge events [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF][START_REF] Kelemen | Calibration of hydroclimate proxies in freshwater bivalve shells from Central and West Africa[END_REF]. In the two Brazilian A. trapesialis specimens presented here, the lowest δ 18 OS values, supposedly characteristics of the wet season (see below), occurred at the time of growth line deposition. This season is marked by turbulent waters and high amount of suspended material (HYBAM database, data not shown, http://www.ore-hybam.org/index.php/eng/Data). The shape of the A. trapesialis δ 18 O profiles appears similar to that obtained in shells that present a seasonal-related growth decrease. The 'constant-winter/summer-shutdown' model established by Goodwin et al. [START_REF] Goodwin | Resolution and fidelity of oxygen isotopes as paleotemperature proxies in bivalve mollusk shells: models and observations[END_REF], defined for shells in temperate climate, could thus be transposed here in a 'wet-shutdown' model for environments characterised by the alternating of wet and dry seasons. Consequently, the growth lines in our A. trapesialis shells are most probably the mark of the wet season growth slowdown.

In A. elongatus from Peru, interpretation of the occurrences of growth lines in relation with the environmental seasonality is more complex than in Brazilian A. trapesialis. There was no clear correspondence between δ 18 OS profiles and growth pattern. One to two cycles were seen per presumed annual increment, and the lowest/highest values in δ 18 OS did not necessarily match observed growth lines. Therefore, no definitive conclusion can be drawn for this species yet.

δ 18 OS reproducibility

Shells of A. trapesialis were collected in the same lake in Brazil and thus lived in the same environmental conditions. Similarly, A. elongatus were collected in the same lake in Peru.

Reproducibility assessed by statistical analyses (Table 3) and by similar variability of the δ 18 OS profiles (Figure 5) leads us to conclude that the δ 18 OS variations observed in Anodontites spp. shells are mostly governed by environmental forcing (see Section 4.3), as observed by Kaandorp et al. [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF].

Considering the two A. trapesialis shells, we observe that At-1 presents a trend of increasing δ 18 OS values compared to At-2. Such tendency may represent an evolution of the δ 18 OS fractionation related to the animal, either an ontogenic trend or other unknown individual effects (i.e. disease, specific behaviour). Since shells have a very similar size, an age-component effect can be excluded. This trend could not result from a change in water chemistry linked for example to hydrological variations such as an inter-annual increase/decrease in discharge over several years. Firstly, shells lived in the same lake and should thus have recorded the same environmental variations. Secondly, although Marengo and Espinoza Villar [START_REF] Marengo | Extreme seasonal droughts and floods in Amazonia: causes, trends and impacts[END_REF] concluded to an increasing frequency of extreme hydrological events in the last two decades for the Amazon region, no clear tendency on average flow in the Solimões river for the 1996-2017 period could be detected (J. Ronchail, pers. comm. based on HYBAM database). The other 3 shells did not present such a trend, indicating that an individual effect is the most probable. Therefore, studies using bivalve shells to reconstruct geochemical baseline of complex freshwater environments like those encountered in the Amazon basin would probably have to consider a specific number of individuals or species, which remains to be defined, to avoid or correct for individual physiologic effect.

δ 18 O S and environmental variations

The δ 18 O variations observed in the two Anodontites sp. reported here exhibit quite distinct patterns. We argue that the observed differences reflect the environmental conditions under which they have grown, thus indicating the potential use of these shells as proxy of past hydrological variability. The A. trapesialis shells were collected in a lake located in the Ilha da Paciencia (Brazil) that is strongly affected by the Solimões river seasonal dynamics. In this regard, these samples had grown in an environment similar to the floodplain described by Kaandorp et al. [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF]. During the rainy season, the Ilha da Paciencia floodplain lake water level is high because, in addition to the precipitation, it is fed by the Solimões river waters. During this period of the year, the river and precipitation waters have the lowest values of the year (Figure 2, Table 2). In contrast, during the dry season, the river level drops and the floodplain lake becomes disconnected from the mainstream, thus becoming strongly affected by the combined effect of highly δ 18 O-enriched precipitation (δ 18 O P = -1.80 ± 1.46 ‰ at the height of the dry season, August) and 18 O water enrichment related to evaporation [START_REF] Hoefs | Stable isotope geochemistry[END_REF]. Consequently, water δ 18 O variations in such lakes are high and seasonal, reflecting the disconnection from the mainstream during several months a year. Yet, the A. trapesialis shells have an average δ 18 OS of -4.42 ‰ and a δ 18 OS amplitude of 4.49 ‰ (Table 3) similar to the local precipitation, which has an average δ 18 O P of -4. 18 ‰ and a δ 18 O P amplitude of 5.38 ‰ different from the river oxygen isotope signature (average δ 18 OS = -5.59 ‰; δ 18 O R amplitude = 1.78 ‰; Table 2, Figure 2). We thus conclude that the large δ 18 OS range observed in A. trapesialis of this study, as in Kaandorp et al. [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF], reflect elevated isotopic variations of floodplain lake, confirming the potential of this species δ 18 OS as a proxy of water δ 18 O variations in such complex environments. Conversely, A. elongatus shells collected along the Rio Amazonas near Iquitos (Peru) present far less variable δ 18 OS values (Figure 6) with a mean seasonal amplitude of 1.58 ‰ (Table 3), which is almost three times smaller than that observed in A. trapesialis shells from the Ilha da Paciencia floodplain lake (4.49 ‰; Table 3) and very different from the local precipitation one (7.03 ‰; Table 2, Figure 2). Even not ruling out the possibility of a species-specific effect, we argue that the narrow range of δ 18 OS observed in A. elongatus, when compared with A. trapesialis from Ilha Paciencia and from Kaandorp et al. [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF], indicates that the habitat of these shells was largely influenced by the main river course water.

To further support the above conclusions, we calculated theoretical shell δ 18 O values (δ 18 OAR) for two environmental end-members, i.e. floodplain lake and river, for the two seasonal extremes, i.e. wet and dry, using the Grossman and Ku [START_REF] Grossman | Oxygen and carbon isotope fractionation in biogenic aragonite: temperature effects[END_REF] thermometry equation established for molluscs (T(°C) = 21.8-4.69(δ 18 OS -δ 18 OW)). Environmental data for the floodplain lake end-member were taken from Kaandorp et al. [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF] with δ 18 OW and water temperature data corresponding to the maximum(minimum) lake water depth for wet(dry) season theoretical δ 18 OAR value calculations. For the river endmember, we took environmental data from the Manaus station. Wet (March) and dry (August) season months were set up to March and August based on maximal and minimal average precipitation amount per month on the whole dataset (Table 2). Figure 6. Wet and dry seasons shell theoretical (δ 18 O AR ) and observed δ 18 OS signatures for two Amazonian end-members, river (A) and floodplain lake (B). δ 18 O AR were calculated using the Grossman and Ku [START_REF] Grossman | Oxygen and carbon isotope fractionation in biogenic aragonite: temperature effects[END_REF] equation for molluscs. Floodplain lake environmental data were taken from Kaandorp et al. [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF] and river ones from the Manaus station (see text for details).

To compare with our shell data, we averaged the lowest and highest δ 18 OS values for each species (Table 3; Figure 6). The difference in theoretical δ 18 OAR values between wet and dry season for the river end-member is low and compare with data obtained in our A. elongatus shells from Iquitos. This is the opposite for our A. trapesialis shells from Manaus that mimic δ 18 OAR values calculated from the floodplain lake end-member environmental data (Figure 6). Note that modifying the temperature amplitude does not change the δ 18 OAR above results, confirming the limited influence of water temperature on δ 18 OS signature in such hydrologically contrasted environments. Thus, the calculation of theoretical δ 18 OAR for floodplain lake and river endmembers confirms our above deductions done considering environmental data, hydrological functioning, and Kaandorp et al. [START_REF] Kaandorp | Seasonal stable isotope variations of the modern Amazonian freshwater bivalve Anodontites trapesialis[END_REF] work.

Conclusion

The Amazon basin hydrology is a complex system that depends on multiple processes like precipitation amount, evapotranspiration, and mix of different water sources depending on the location (e.g. floodplain lake vs. main stream). Those processes are reflected in the δ 18 O signature that can be retrieved at the seasonal scale using Anodontites spp. bivalve shells, which have low seasonal δ 18 O variability when living in or close to the river's mainstream and high seasonal δ 18 O variability when living in the floodplain, or in a floodplain lake (varzea), seasonally disconnected from the river. These results are promising for the use of such archives to retrieve hydrological data in various and numerous sites. Indeed, depending on the δ 18 OS of the specimens, one will be able to decipher the hydrologic functioning at the collection site (floodplain, floodplain lake, mainstream) for actual or past conditions, that is very interesting in the Amazon basin in which some rivers present an intense geomorphological dynamic (e.g. frequent mainstream moving, oxbow lakes creation and recovery). One might also be able to retrieve water δ 18 O P or δ 18 O R values, at least at a seasonal resolution over several years, for highly contrasted sites (floodplain lake vs. mainstream) that might replace costly and complex monitoring procedures. Our results also encourage the expansion of such studies to other chemical elements (e.g. barium, strontium, magnesium) to use Anodontites spp. shells for reconstruction of biogeochemical conditions and variations of the Amazon. In addition, the understanding of infra-seasonal variations in shell composition in the present climate will help decrypt seasonal variations in the past, based on dated fossil shells.

Figure 1 .

 1 Figure 1. Shells sampling locations (red stars): Anodontites elongatus (Ae) at Iquitos, Peru, and A. trapesialis (At) at Ilha da Paciencia, Brazil. Environmental data were taken from GNIP (blue square) and GNIR (orange square) stations. See text for details.

Figure 2 .

 2 Figure 2. Seasonal precipitation variability and δ 18 O values of precipitations and river water (in ‰ VSMOW) for the two sites: (A) in Brazil, mean monthly precipitation (grey bars) and isotopic monthly variability in precipitation (δ 18 O P , black squares) at Manaus and δ 18 O values for the Rio Solimões (δ 18 O R , open circles) at Manacapuru and (B) in Peru, mean monthly precipitation (grey bars) and isotopic monthly variability in precipitation (δ 18 O P , black squares) at Iquitos. See Figure 1 for station locations and data sources.

Figure 3 .

 3 Figure 3. Shells of the two studied bivalve species: (A) Anodontites elongatus (Ae-2). (B) Anodontites trapesialis (At-1). The box shows the position of the shell cross-section removed along the axis of maximum growth. (C) Shell cross-section. Arrows in B and C indicate the growth direction. Scale bars are 1 cm.

Figure 4 .

 4 Figure 4. Growth patterns in the hinge of the A. trapesialis and A. elongatus specimens. Hinge cross sections of the two A. trapesialis At-1 (A) and At-2 (B) and the two A. elongatus Ae-1 (C) and Ae-2 (D) viewed under an optical microscope under diffused light. Numbers and letters indicate successive growth lines and increments from the inner to the outer part of the hinge. Arrows indicate the growth direction. Each picture is independent, i.e. the same number/letter does not correspond to the same year of growth line/increment formation. Scale bars are 1 mm. Increments were noted by a letter and growth lines were numbered. The code 'A1' represents thus the oldest part of the shell.

Figure 5 .

 5 Figure 5. δ 18 OS (in ‰ V-PDB) pro les in the hinge of the two A. trapesialis (At-1 and At-2) and the two A. elongatus (Ae-1 and Ae-2). Numbers and letters indicate successive growth lines and increments as inFigure 4.

Table 1 .

 1 Anodontites spp. shell sampling location and size (L: length and H: height).

				Sampling location			Shell size
	Species	Country	Site	Latitude	Longitude	Specimen L (mm) H (mm)
	Anodontites trapesialis Brazil	Ilha da Paciencia 3°19 ′ 21.0 ′′ S 60°16 ′ 36.0 ′′ W	At-1	17.0	9.1
						At-2	16.8	9.5
	Anodontites elongatus Peru	Iquitos	3°44 ′ 32.2 ′′ S 73°13 ′ 31.2 ′′ W	Ae-1	05.0	3.5
						Ae-2	05.8	3.6

  for stations location.

			Precipitation	δ 18 OP	δ 18 OR
			(mm)	(‰)	(‰)
		Station	Manaus		Rio Solimões, Manacapuru
		Resolution	monthly		1-3 per month
	Brazil	Period	1965-1990 (n = 303)	1965-1990 (n = 187)	2000-2004 (n = 56)
		Mean (SD)	191.3 (122.9)	-4.18 (2.71)	-5.59 (0.65)
		Mean seasonal Range	277.3	5.38	1.78
		Station	Iquitos
		Resolution	monthly
	Peru	Period	2007-2012 (n = 50)	2006-2012 (n = 54)	No data
		Mean (SD)	382.3 (218.2)	-5.94 (3.37)
		Mean Seasonal Range	360.6	7.03

  OS cycle. SD: standard deviation. N: number of analysed carbonate powder samples. n: number of cycles per species.

			δ 18 OS (‰ V-PDB)		Mean δ 18 OS cyclic variability (‰ V-PDB)
	Specimen N	Mean (SD)	Min	Max	Range	Min (SD)	Max (SD)	Amplitude (SD)
	At-1	29	-4.39 (1.83) -8.01	-1.31	6.70	-6.49 (1.09) -2.00 (0.93)	4.49 (1.37)
	At-2	37	-4.45 (1.70) -7.85	-1.73	6.12		n = 7
	Ae-1	33	-6.24 (0.75) -7.52	-4.38	3.14	-6.67 (0.32) -5.09 (0.60)	1.58 (0.77)
	Ae-2	30	-6.23 (0.71) -7.66	-4.77	2.90		n = 8

The letters indexing O in the text mean: S-shell, R-river, P-precipitation, AR-aragonite, W-water.

Acknowledgments

We are grateful to Lorenzo Barocco and Ivanildo L.A. Santos from UFAM (Manaus) and Carmen R.G. Davila (Instituto de Investigaciones de la Amazonía Peruana -IIAP, Iquitos) from Peru who helped for shells sampling. We also thank Nathalie Labourdette for isotope analyses at ISTeP, Paris VI. The Version of Record of this manuscript has been published and is available in " Isotopes in Environmental and Health Studies" 18 Sep 2019, https://www.tandfonline.com/doi/full/10.1080/10256016.2019.1666120.

Funding

We thank national institutions that supported our work through PEPS (CNRS -BiBhy project) and EC2CO (INSU -BiEauAmaz project) funding programmes.


E J Petit

B Gay

Challenges to make general vapor phase galvanizing a viable industrial process

Keywords: Revêtement métallique, galvanisation, anticorrosion, Activation de surface, Germination, IMMAT'2019 Metal coating, Galvanizing, Anticorrosion, Surface activation, Nucleation, IMMAT'2019

Nous présentons une tentative de développement d'une technologie de galvanisation à façon en phase vapeur qui entrerait potentiellement en concurrence avec la galvanisation à façon au trempé à chaud. Cette technologie produit des dépôts intermétalliques Fe-Zn sur l'acier en présence de vapeurs de zinc par une réaction de diffusion. Ces dépôts forment d'excellentes couches sacrificielles pour les revêtements de type duplex destinés à des pièces aux formes complexes. Le papier se concentre sur la présentation des écueils rencontrés lors du passage à l'échelle industrielle. Nous nous intéressons ici principalement au grenaillage utilisé pour activer les surfaces avant d'exposer les pièces aux vapeurs de zinc sous vide. Il s'agit de comprendre comment le grenaillage influence la croissance des couches. Nous indiquerons quelques pistes qui à notre avis valent la peine d'être explorées dans le futur. Pour faire court, nous proposons de désigner par le terme générique « Epanisation », les conditions particulières que nous utilisons pour la galvanisation à façon en phase vapeur.

Introduction

Anticorrosion zinc-rich coatings are fabricated by hot-dip galvanizing (HDG), electro-deposition, metal-spraying, and cementation (Sherardizing). Continuous galvanizing of steel sheets by Physical Vapor Deposition (PVD) is presently commercially emerging. A challenge to coat complex-shape articles by General Vapor Phase Galvanizing (GVPG) is to get a layer of uniform thickness because vapor goes in vacuum from the source to the substrate in straight line, and deposition rate is highly dependent on the angle of incidence [START_REF] Mattox | Physical vapor deposition (PVD) processes[END_REF]. Flat and long products can be coated by balancing the flux of deposition or by using complex handling devices moving pieces during deposition [START_REF] Mattox | Physical vapor deposition (PVD) processes[END_REF][START_REF] Patent | Method and system for galvanizing by plasma evaporation[END_REF]. Complex-shape articles and hollow parts cannot be coated by standard (evaporation -condensation) PVD. Pioneers have reported that exposing hot iron to zinc vapor in vacuum produces a coating [START_REF] Short | The nature and kinetics of the interaction layers formed during the reaction between solid iron and zinc vapor at 500°C[END_REF][START_REF] Mackowiak | Effect of chemical potential of zinc on composition and nature of interaction layers formed during reaction between solid iron and zinc vapor at 793[END_REF][START_REF] Bretez | Phase relations and diffusion paths in the system Zn vapor-iron silicon alloys at 773 and 973[END_REF][START_REF] Yu | Diffusion driven grain boundary migration in Fe during zincification[END_REF][7][8]. However, Reumont et al got negligible rates of growth at 450°C, and different thickness of coatings on both sides of samples at 500°C [7]. They also reported unreacted areas after 6 hours at 500°C. Short and Mackowiak have reported foreign materials included in the coating, variable thickness depending on surface orientation, as well as extensive fissuring of the coating produced at 500°C [START_REF] Short | The nature and kinetics of the interaction layers formed during the reaction between solid iron and zinc vapor at 500°C[END_REF].

The growth rates reported by Mackowiak (max ~3.4 µm/h at 500°C [START_REF] Short | The nature and kinetics of the interaction layers formed during the reaction between solid iron and zinc vapor at 500°C[END_REF][START_REF] Mackowiak | Effect of chemical potential of zinc on composition and nature of interaction layers formed during reaction between solid iron and zinc vapor at 793[END_REF]) and Schmitz (60 µm after 19h at 390°C [8]) was about 200 time lower than the one in general HDG. Schmitz et al reported even lower rates at lower temperature [8]. Yu and Shewmon did not aim at producing coating [START_REF] Yu | Diffusion driven grain boundary migration in Fe during zincification[END_REF]. Improving this concept, we have proposed a fabrication protocol and specific PVD conditions making GVPG possible [START_REF]Process for coating discrete articles with a zinc-based alloyed layer[END_REF]. Corrosion tests have demonstrated that vapor-phase galvanized samples, and duplex coatings based on them, offer outstanding resistance against corrosion [START_REF] Petit | General Vapor-Phase Galvanizing and duplex coatings[END_REF]. The next challenges are to succeed the upscaling and to reach sufficient throughput. The present paper reports success and stumbling blocks met while upscaling the technology. We address here the effect of shot blasting on the activation of steel surfaces before coating. Shot blasting is an advantageous alternative to pickling because a dry surface preparation avoids chemical effluents, reduces the risk of re-oxidizing during drying, and discards the inconvenient of steaming water vapor into the vacuum vessel. Finally, visual inspection for cleanliness is easier if the work is grit-blasted instead of pickled.

Methods

The experimental set up (figure 1) includes an oven (1) that can be heated to 550°C [START_REF] Patent | Method and system for galvanizing by plasma evaporation[END_REF]. Articles [START_REF] Short | The nature and kinetics of the interaction layers formed during the reaction between solid iron and zinc vapor at 500°C[END_REF] enter the oven (5), and can be removed [START_REF] Bretez | Phase relations and diffusion paths in the system Zn vapor-iron silicon alloys at 773 and 973[END_REF], through a sealable port (4). The oven is equipped with vacuum pumps [START_REF] Yu | Diffusion driven grain boundary migration in Fe during zincification[END_REF]. Vacuum valves are used for feeding reactive gases, and to enter air into the vacuum vessel at the end of the process (7). The zinc vapour is produced by thermal evaporation (8). Coatings presented in the present paper have been grown on low carbon hypo-Sandelin steels. Steel surfaces have been shot blasted in an automatic industrial shelter equipped with wind turbines. Shots were: small rounded steel shots (A), large rounded steel shots (B), small angular steel shots (C), large angular cast iron shots (D), corundum shots (E). Blasting conditions were reproducible but poorly characterized. So we refer our results to the surface states after shot blasting as observed by optical and electron microscopy. As expected, examination by optical microscopy and SEM showed that the removal of the oxide scale, surface roughening and mechanical stirring of the steel surface depend on the shots. Chemical analyses by XPS and EDX also revealed surface contamination by the shots (traces of C, S, Si, Al2O3). Shot blasting has been completed in-situ by annealing in a mixture of 5% H2 in N2 at atmospheric pressure 10 minutes at 450°C. The oxide scale that is not removed by pickling or shot blasting, cannot be reduced by annealing in hydrogen, and prevents the diffusive reaction when it covers more than µm-size areas. On the contrary, the iron native oxides grown after pickling or shot basting are fully reduced by hydrogen even if steel has been exposed 20 days to the atmosphere after etching or milling. The specificity of our concept consists of keeping simultaneously the temperature of the vacuum vessel close to the one of the articles to be coated; and the zinc vapor pressure below the dew point of zinc at the temperature of growth. Then, the rate of formation of the intermetallic coating is controlled by: the vapor pressure of zinc, the temperature of pieces, and the duration of reaction [START_REF] Mackowiak | Effect of chemical potential of zinc on composition and nature of interaction layers formed during reaction between solid iron and zinc vapor at 793[END_REF]. The reaction temperature is in the range between 300°C and 600°C. The zinc vapor is fed into the vessel after pumping below 100 Pa, when the temperature is uniform into the oven. A cold finger can reduce the zinc vapor pressure. The reaction is stopped by cooling and admitting the air into the vessel. Similar conditions in continuous PVD would condense zinc on entry and exit slits. In r-PVD where zinc vapour condenses first on the surface before alloying, interdiffusion produces first a brittle ς phase that transforms progressively to the δ phase. The same occurs in general HDG [START_REF] Horstmann | Die Reaktionen zwishen Eisen und Zink[END_REF][START_REF] Mackowiak | Metallurgy of galvanized coatings[END_REF][START_REF] Taniyama | In-situ observation of growth behavior of Fe-Zn intermetallic compounds at initial stage of galvannealing process[END_REF], and in Zn/Fe interdiffusion-couples [START_REF] Onishi | Formation and growth kinetics of intermediate phases in Fe-Zn diffusion couples[END_REF][START_REF] Syahbuddin | The development of Fe-Zn intermetallic compounds in solid Fe/Zn and Fe/Zn-Al diffusion couples during annealing at 400°C[END_REF]. On the contrary, our process favours the growth of the δ phase [START_REF] Petit | General Vapor-Phase Galvanizing and duplex coatings[END_REF]. Thermodynamics imposes the presence of the Γ (and Γ1) phase at the interface, and traces of the ς phase at the surface. The growth temperature determines the branching ratio between phases. In order to distinguish our specific operating protocol from standard PVD and r-PVD, we refer to it as "Epanizing". Articles treated by GVPG using Epanizing conditions are said to be "epanized".

Results

Upscaling to the industrial level

Technological challenges include: the production of zinc vapor, the stability of tools in the reactive atmosphere, the sealing of the metallic vapors at high temperatures, a uniform distribution of temperature on pieces, and a sufficient control of the heating cycle. Figure 2 shows a test of up-scaling. The diameter of the chamber was about 0.8 m. The zinc source was separated from the reaction chamber by a hot valve. The reaction chamber and heating elements were into the vacuum chamber. A heat trap avoided overheating of the pump by hot gases [START_REF] Petit | Heat trapping for fast pumping of very hot gases[END_REF]. This device operated properly. Figure 3 displays a production unit. Heating elements were outside the vacuum chamber: the reaction was performed in the vacuum chamber. The length of the chamber was about 4 m, and the source was inside the reaction chamber. A standard heat exchanger cooled the gas before the pumps. In operation the zinc source settled a detrimental thermal gradient in the chamber despite radiation shields between the source and the articles. Up-scaling was successful with background pressures from 10 to 10 3 Pa, as far as surfaces are not re-oxidized.

Reproducibility is highly dependent on the ability of controlling the thermal route (duration / temperature) and preventing thermal gradients within the reaction chamber. The best compromise between surface quality and throughput have been obtained with coating thickness between 25 and 50 µm.

Figure 4 shows articles coated in a set-up similar to the one on figure 3, ~1 m in diameter. Pieces were shot blasted using large and angular steel shots. Surfaces look dull grey. Eye exam cannot distinguish any shadow, surface roughness, nor defects. This demonstrates that complex-shape parts can be coated without a complex handling device.

Influence of shot blasting

Shot blasting modifies the roughness of steel (figure 5). Rounded steel shots (A and B) limit the roughening of the steel, but poorly remove the oxide scales. Angular steel shots (C) and angular cast-iron shots (D) efficiently etched the oxide but roughen and stir the surface. Lower density corundum shots (E) are moderately efficient in cleaning, and some alumina grains remain impinged into the surface. The (Elcometer) permascope measurements of coating thickness after Epanizing suggest that reactivity is related to roughness after shot blasting (figure 5). The observation of cross sections at flat matted areas using the SEM (CS-SEM) refutes this feeling because thickness of coatings apart from strongly roughened places remain constant. The artefact on the magnetic measurements is due to the fact that the contact method is sensitive to the variation of heights of the highest tips on the surface. At a glance, this explanation seems unsatisfactory on a quantitative basis since the apparent thickness varies over ~25 µm when (Ra) varies over ~5 µm (Figure 5). In fact, (Ra) is the variance of the surface roughness around the average plane; but, point-to-point variations of heights are 2 to 3 times larger than (Ra). Moreover, figure 6 shows that Epanizing amplifies the thickness of the coating on top of surface tips by about 5 µm. The grains in the steel are ~6.6 µm in diameter.

Then, the colony of aggregates on the left hand side, which is about 80 µm in diameter, is not correlated to the grain size of the steel substrate. However, the mean distance between aggregates in this colony corresponds to the one between grains or grain boundaries in the substrate. On the right hand side, a strip of densely nucleated Fe-Zn grains has formed at a scratch on the steel sheet before Epanizing. Surface attrition has stimulated the growth of several nuclei on each single iron grain.

On the contrary, in the space between the colony and the strip, the nucleation Fe-Zn aggregates has been delayed at some places. There, the growth is preceded by an "incubation" period [START_REF] Petit | General Vapor-Phase Galvanizing and duplex coatings[END_REF]. The crystal orientation of α-Fe grains, or the nature of grain boundaries, could explain this situation.

Aggregates are larger in the colony, and between the colony and the strip, than in the densely nucleated strip. This is due to the fact that a dendritic growth selects the shape of the aggregates. The diameters of aggregates are then limited by the available space between neighbor grains. Overlapping triggers the columnar growth.

Figure 7 shows that surface activation expresses the ability to nucleate Fe-Zn aggregates. Sensitivity to surface attrition explains that shot blasting accelerates the nucleation of grains at T < 390°C. XPS and EDX analyses of pickled steel surfaces have revealed that they were contaminated by calcium, sulfur, carbon and copper traces. Contaminants originated from tap water and from the inhibitor that stops the attack after the removal of the oxide scale. Surface contamination could degrade reactivity while surface defects could provide sites suitable for a stable adsorption of zinc.

The hypothesis of a reactivity hindered by contaminants is corroborated by figure 8 that shows a fragment of a submicron thick calcite foil lift out of the surface due to the directional dendritic growth during Epanizing at 350°C. The foil has been engrossed by the growing compound, and finally wrapped up by the coating. The same was observed with µm-size fragments of the oxide scale, and Corundum grains impinged in the steel. Mackowiack reported the same for silica and carbon particles [START_REF] Short | The nature and kinetics of the interaction layers formed during the reaction between solid iron and zinc vapor at 500°C[END_REF].

Discussion

Our results demonstrate that surface reactivity must be properly mastered. This explains why previous attempts reported in the literature had failed to evolve to a practicable industrial process [START_REF] Short | The nature and kinetics of the interaction layers formed during the reaction between solid iron and zinc vapor at 500°C[END_REF][START_REF] Mackowiak | Effect of chemical potential of zinc on composition and nature of interaction layers formed during reaction between solid iron and zinc vapor at 793[END_REF][START_REF] Bretez | Phase relations and diffusion paths in the system Zn vapor-iron silicon alloys at 773 and 973[END_REF][START_REF] Yu | Diffusion driven grain boundary migration in Fe during zincification[END_REF][7][8]. To control an even diffusive-reaction requires a reproducible chemical activity. Below 390°C, nucleation produces an incubation period that delays significantly the start of the diffusive-reaction, and reduce the effective duration of reaction during a batch. Sophisticated cleaning procedures, common in the thin film technology, should be adapted to the metallurgical industry.

Above 400°C, we have not been able to observe the nucleation step because it proceeded fast on every samples. The reaction is easily controlled. Criticality of surface cleaning and preferential nucleation on grain boundaries suggest that the availability of labile iron atoms trigger nucleation [START_REF] Yu | Diffusion driven grain boundary migration in Fe during zincification[END_REF]. Dense nucleation on defects generated by surface attrition highlights the importance of surface sites able to stick and pin the adsorbed zinc atoms moving on the surface. The subsequent columnar growth manifests that atomic mobility is not sufficient to densify the coating below 390°C.

Roughness is an additional processing parameter after shot blasting at all reaction temperatures. It is able to change the apparent thickness of the coating by a factor of 2 to 3. It is known that the roughness of steel affects the growth of the intermetallic phases during hot-dip galvanizing (HDG) because it disturbs the parallelism of the ς filaments that usually grow perpendicular to the steel during HDG and degrades the passivating capability of the ς layer in the liquid zinc [START_REF] Horstmann | Die Reaktionen zwishen Eisen und Zink[END_REF][START_REF] Mackowiak | Metallurgy of galvanized coatings[END_REF][START_REF] Ferrier | Etude de la formation des composés Fe-Zn par galvanisation à chaud[END_REF]. The reactivity of steel is similarly increased by mechanical grinding after galvannealing [START_REF] Hong | The effects of mechanical polishing of the steel substrate surfaces on galvannealing properties[END_REF]. The directional growth of the reaction product in the 3 technologies is the only similarity that enables to compare the similar influence of surface geometry. Below 390°C, space occupancy by the δ aggregates is determined by the density of nuclei, the shape of aggregates imposed by crystallography, and the local curvature of the steel surface. Above 400°C, the directional growth on surface tips suggests that densification proceeds after a dendritic growth (figure 6).

Conclusions

GVPG supplements the panel of technologies for fabricating anticorrosion zinc-rich coatings on steel [START_REF]Process for coating discrete articles with a zinc-based alloyed layer[END_REF]. Gas-phase reactions are controlled by surface activation, the temperature of the steel substrate, and the duration of the reaction because the growth is driven by a surface mediated mechanism, which is not directly related to the deposition rate. 25 and 50 µm -thick coating can be obtained in about one hour. This is an acceptable throughput. Technological challenges for a successful operation include: the production and handling of hot metallic vapor in the vacuum vessel, and the control of the thermal route on every pieces. Temperature uniformity across the batch load could be of particular concern during thermal transients when articles includes parts of various thickness. Up-scaling has been demonstrated successfully in a set-up up to 4 meter-long with a background pressure between 10 and 1000 Pa. Our experience suggests to prefer an external source of metallic vapor in order to keep flexibility, and to avoid uncontrolled thermal gradient in the oven around the batch load. Surface activation involves any operation favoring the reaction.

To remove the oxide scale is mandatory. Surface cleaning to the atomic scale is also important to stimulate the sticking coefficient of zinc. The production of defects by surface attrition could be a powerful mean to control the nucleation step between 300°C and 390°C. However, the surface roughness produced by shot blasting becomes a concern when it exceeds ~1 µm in amplitude. Epanizing extends galvanizing with a reasonable throughput below 425°C, and potentially down to 350°C.

This opportunity could save heating expenses, reduce the thermal stresses induced distortions in complex-shape pieces, and limit the residual stress within the coating after cooling. It is also favorable to keep the mechanical properties of high strength steels. The new process solves important concerns of HDG, and could be a potential competitor to general HDG.

Figure 1 .

 1 Figure 1. A schematic representation of the experimental set-up for GVPG.

Figure 2 .

 2 The equipment built to develop the process at a larger scale (Umicore). a) The vacuum vessel. b) An overall view of a development set-up.

Figure 3 .

 3 Figure 3. First industrial set-up (Umicore -Drever International).

Figure 4 .

 4 Figure 4. Complex-shape articles epanized at 400°C during 90 min (coating thickness = 25 µm).

Figure 5 .

 5 Figure 5. Thickness of coatings epanized at 450°C during 90 min on the shot blasted steel sheets (A to E) versus the roughness after shot blasting (before Epanizing). Measures produced by an (Elcometer) permascope are compared to SEM observations on cross sections on flat matted areas (CS-SEM).Unreacted bare spots are visible on the surface A, B and E after Epanizing because remaining oxide scales (~ 5 µm thick) prevent the diffusive reaction. Some alumina grains are found into the coating after the diffusive reaction on surface E. Surfaces

Figure 6 .

 6 Figure 6. Cross section of a coating epanized at 450°C during 90 min on a steel plate shot blasted with small angular steel shots (C). Observation by SEM at a rough place. (Scale bar = 10 µm).

Figure 7

 7 Figure 7 is a SEM micrograph of a sample epanized at 350°C during 30 minutes. The sample had been prepared by acid pickling and dry reduction of the native oxides in situ.

Figure 7 .

 7 Figure 7. SEM observation of a steel sheet pickled and epanized at 350°C 30 min. Evidence of uneven reactivity associated to uncompleted nucleation step and surface attrition.

Figure 8 .

 8 Figure 8. Observation of a submicron calcite foil lift out of the steel surface by the coating after Epanizing at 350°C during 30 min.

Acknowledgments

The Evaplex project corresponding to the industrial development phase (Umicore, Drever International, Galva45 (GalvaUnion), CRM (Liège)) has been supported by the Walloon Region (Belgium) (Eureka program). The CORI (Corrosion Research Institute -Limelette -Belgium) and the CRM (Centre de Recherche Métallurgique, Liège, Belgium) performed the analyses related to roughness.