C Xu

T Xiao
email: txiao@qdio.ac.cn

H M Pan

L F Wu

Wenyan Zhang

Jia Liu

Dong Yi

Xuegang Li

X U Cong

Xiao Tian

W U Long-Fei

Archaeal community structure in sediments from a seamount in the Mariana Volcanic Arc

Keywords: seamount, archaeal diversity, community structure, Nitrosopumilales

Seamounts are subsurface mountains in the ocean. Examination of the abundance and distribution of Archaea in seamount ecosystems may provide a better understanding of their ecological functions. Most studies of marine archaeal assemblages in seamount area have focused on hydrothermal vents or ferromanganese crusts. We investigated the archaeal communities from a seamount of the Mariana Volcanic Arc, in the tropical western Pacific Ocean by using high-throughput sequencing. Thaumarchaeota was dominant in the sediments of all sample stations. Community diversity and species richness were greatest at stations near the top of the seamount, and lowest at the deepest station. One sample station on the steep southeast slope that faced the Yap-Mariana trench had a unique composition of Archaea. In summary, depth has an important influence on archaeal community structure, and the geographic properties and sediment characteristics may explain the unique distribution patterns of Archaea in this seamount. This study provides a foundation for future research on Archaea in seamounts.

INTRODUCTION

Archaea is the third life domain, alongside Bacteria and Eukarya [START_REF] Woese | Phylogenetic structure of the prokaryotic domain: the primary kingdoms[END_REF][START_REF] Woese | Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya[END_REF], whose species were once thought to only occur in extreme environments.

However, recent molecular biology tools have revealed that Archaea have a wide ecological distribution, in that they occur in freshwater sediments, soils, and other habitats, and they also have important roles in global biogeochemical cycles [START_REF] Fuhrman | Novel major archaebacterial group from marine plankton[END_REF][START_REF] Auguet | Global ecological patterns in uncultured Archaea[END_REF].

In marine environments, Archaea account for nearly 30% of microbial plankton [START_REF] Delong | Archaea in coastal marine environments[END_REF][START_REF] Karner | Archaeal dominance in the mesopelagic zone of the Pacific Ocean[END_REF][START_REF] Bano | Phylogenetic composition of Arctic Ocean archaeal assemblages and comparison with Antarctic assemblages[END_REF], and are one of the most dominant groups of prokaryotes in marine sediments [START_REF] Wuchter | Archaeal nitrification in the ocean[END_REF][START_REF] Roussel | Archaeal communities associated with shallow to deep subseafloor sediments of the New Caledonia Basin[END_REF][START_REF] Durbin | Sediment-associated microdiversity within the Marine Group I Crenarchaeota[END_REF]. Archaea have key roles in marine biogeochemical cycles, particularly the carbon and nitrogen cycles, and they also contribute to sulfur cycling in marine sediments [START_REF] Auguet | Global ecological patterns in uncultured Archaea[END_REF][START_REF] Offre | Archaea in biogeochemical cycles[END_REF][START_REF] Zhang | Marine group II Archaea, potentially important players in the global ocean carbon cycle[END_REF][START_REF] Danovaro | Macroecological drivers of archaea and bacteria in benthic deep-sea ecosystems[END_REF][START_REF] He | Genomic and enzymatic evidence for acetogenesis among multiple lineages of the archaeal phylum Bathyarchaeota widespread in marine sediments[END_REF].

Archaea were first reported in the cold ocean in 1992 [START_REF] Delong | Archaea in coastal marine environments[END_REF][START_REF] Fuhrman | Novel major archaebacterial group from marine plankton[END_REF], and this led to the identification of two major groups based on 16S rRNA sequences: Marine Group I (MG-I, now classified as Nitrosopumilales in phylum Thaumarchaeota) and Marine Group II (MG-II, belonging to Phylum Euryarchaeota) [START_REF] Brochier-Armanet | Mesophilic Crenarchaeota: proposal for a third archaeal phylum, the Thaumarchaeota[END_REF][START_REF] Zhang | Marine group II Archaea, potentially important players in the global ocean carbon cycle[END_REF][START_REF] Qin | Nitrosopumilus maritimus gen. nov., sp. nov., Nitrosopumilus cobalaminigenes sp. nov., Nitrosopumilus oxyclinae sp. nov., and Nitrosopumilus ureiphilus sp. nov., four marine ammonia-oxidizing archaea of the phylum Thaumarchaeota[END_REF]. The MG-I are the most abundant and cosmopolitan chemoautotrophic archaea in the marine environment [START_REF] Bano | Phylogenetic composition of Arctic Ocean archaeal assemblages and comparison with Antarctic assemblages[END_REF][START_REF] Offre | Archaea in biogeochemical cycles[END_REF]. Studies on this group have reported that they can fix inorganic carbon and oxidize ammonia aerobically [START_REF] Stahl | Physiology and diversity of ammonia-oxidizing archaea[END_REF]. Therefore, these species may be responsible for a significant fraction of chemoautotrophic production in the dark ocean and could play a vital role in marine biogeochemical cycles, particularly the carbon and nitrogen cycles, and might be responsible for a significant amount of the primary production in dark ocean ecosystems [START_REF] Herndl | Contribution of Archaea to total prokaryotic production in the deep Atlantic Ocean[END_REF][START_REF] Tourna | Nitrososphaera viennensis, an ammonia oxidizing archaeon from soil[END_REF][START_REF] Offre | Archaea in biogeochemical cycles[END_REF]. There is evidence that marine MG-I might account for more than 10% of the total prokaryotic production in the ocean [START_REF] Herndl | Contribution of Archaea to total prokaryotic production in the deep Atlantic Ocean[END_REF][START_REF] Offre | Archaea in biogeochemical cycles[END_REF]. Previous studies have defined different phylogenetic ecotypes of MG-I [START_REF] Massana | A few cosmopolitan phylotypes dominate planktonic archaeal assemblages in widely different oceanic provinces[END_REF][START_REF] Takai | Spatial distribution of marine Crenarchaeota group I in the vicinity of deep-sea hydrothermal systems[END_REF][START_REF] Durbin | Archaea in organic-lean and organic-rich marine subsurface sediments: an environmental gradient reflected in distinct phylogenetic lineages[END_REF][START_REF] Jorgensen | Correlating microbial community profiles with geochemical data in highly stratified sediments from the Arctic Mid-Ocean Ridge[END_REF][START_REF] Lauer | Phylogenetic characterization of marine benthic Archaea in organic-poor sediments of the eastern Equatorial Pacific Ocean (ODP Site 1225)[END_REF]. The MG-I.a phylotype is common in shallow seawater and the MG-I.c phylotype is common in deep seawater [START_REF] Massana | A few cosmopolitan phylotypes dominate planktonic archaeal assemblages in widely different oceanic provinces[END_REF][START_REF] Takai | Spatial distribution of marine Crenarchaeota group I in the vicinity of deep-sea hydrothermal systems[END_REF]. MG-II are also abundant in the marine photic zone, which lives heterotrophically, and might play important roles in the long-term storage of dissolved organic carbon [START_REF] Zhang | Marine group II Archaea, potentially important players in the global ocean carbon cycle[END_REF]. Besides, members of Miscellaneous Crenarchaeota Group (MCG) affiliated in phylum Bathyarchaeota were frequently detected in the marine subsurface sediments [START_REF] Meng | Genetic and functional properties of uncultivated MCG archaea assessed by metagenome and gene expression analyses[END_REF][START_REF] He | Genomic and enzymatic evidence for acetogenesis among multiple lineages of the archaeal phylum Bathyarchaeota widespread in marine sediments[END_REF].

Seamounts, defined as subsurface topographic rises at least 1 km above the seafloor, usually form from volcanoes in the deep sea, and often have peaks that are hundreds to thousands of meters below the surface [START_REF] Menard | Marine Geology of the Pacific[END_REF]. Seamounts occur at various depths in all oceans worldwide and vary in form and size [START_REF] Schlacher | Seamount science scales undersea mountains: new research and outlook[END_REF]. Seamounts are also hosts to unique oceanic ecosystems, and they provide a variety of habitats and environmental conditions for benthic organisms [START_REF] Clark M R, Rowden | The ecology of seamounts: structure, function, and human impacts[END_REF]. Seamounts affect underwater currents and create upwellings that attract plankton, corals, and fish [START_REF] Danovaro | Prokaryote diversity and viral production in deep-sea sediments and seamounts[END_REF][START_REF] Clark M R, Rowden | The ecology of seamounts: structure, function, and human impacts[END_REF][START_REF] Rowden | A test of the seamount oasis hypothesis: seamounts support higher epibenthic megafaunal biomass than adjacent slopes[END_REF], and are believed to support high levels of biodiversity and endemic marine animals [START_REF] Schlacher | Seamount science scales undersea mountains: new research and outlook[END_REF]. The benthic communities of seamounts are distinct from those of continents and oceanic islands, in that they support greater biomass and have different community compositions [START_REF] Rowden | A test of the seamount oasis hypothesis: seamounts support higher epibenthic megafaunal biomass than adjacent slopes[END_REF][START_REF] Yesson | The global distribution of seamounts based on 30 arc seconds bathymetry data[END_REF].

Seamounts potentially provide many unique niches for microorganisms, but little is known of the composition of Archaea in seamounts area. There have been many studies of Archaea assemblages near hydrothermal vents [START_REF] Huber | Temporal changes in archaeal diversity and chemistry in a mid-ocean ridge subseafloor habitat[END_REF][START_REF] Nakagawa | Analysis of dissimilatory sulfite reductase and 16S rRNA gene fragments from deep-sea hydrothermal sites of the Suiyo Seamount, Izu-Bonin Arc, Western Pacific[END_REF][START_REF] Hara | Analysis of the archaeal sub-seafloor community at Suiyo Seamount on the Izu-Bonin Arc[END_REF][START_REF] Opatkiewicz | Individual hydrothermal vents at Axial Seamount harbor distinct subseafloor microbial communities[END_REF][START_REF] Kato | Characteristics of microbial communities in crustal fluids in a deep-sea hydrothermal field of the Suiyo Seamount[END_REF] and ferromanganese crusts [START_REF] Liao | Microbial diversity in deep-sea sediment from the cobalt-rich crust deposit region in the Pacific Ocean[END_REF][START_REF] Nitahara | Molecular characterization of the microbial community in hydrogenetic ferromanganese crusts of the Takuyo-Daigo Seamount, northwest Pacific[END_REF][START_REF] Huo | Ecological functions of uncultured microorganisms in the cobalt-rich ferromanganese crust of a seamount in the central Pacific are elucidated by fosmid sequencing[END_REF][START_REF] Nitahara | Archaeal and bacterial communities in deep-sea hydrogenetic ferromanganese crusts on old seamounts of the northwestern Pacific[END_REF]. Phylotypes in MG-I were predominant, and those of MG-II, MG-III, and Marine Benthic Group E (MBGE) were also reported in the hydrothermal fluids and waters of Suiyo Seamount and hydrothermal vents at Axial Seamount, in the Juan de Fuca Ridge [START_REF] Huber | Temporal changes in archaeal diversity and chemistry in a mid-ocean ridge subseafloor habitat[END_REF][START_REF] Nakagawa | Analysis of dissimilatory sulfite reductase and 16S rRNA gene fragments from deep-sea hydrothermal sites of the Suiyo Seamount, Izu-Bonin Arc, Western Pacific[END_REF][START_REF] Hara | Analysis of the archaeal sub-seafloor community at Suiyo Seamount on the Izu-Bonin Arc[END_REF][START_REF] Opatkiewicz | Individual hydrothermal vents at Axial Seamount harbor distinct subseafloor microbial communities[END_REF][START_REF] Kato | Characteristics of microbial communities in crustal fluids in a deep-sea hydrothermal field of the Suiyo Seamount[END_REF]. Characterization of microbial populations in sediments of the Marsili and Palinuro Seamounts in the Tyrrhenian Sea (Western Mediterranean) indicated that Crenarchaeota (now the Thaumarchaeota) dominated archaeal communities in seamount and non-seamount sediments, with an abundance generally 3 times higher than that of Euryarchaeota [START_REF] Danovaro | Prokaryote diversity and viral production in deep-sea sediments and seamounts[END_REF]. Phylogenetic analyses showed the predominance of MG-I in the sediments of cobalt-rich ferromanganese crusts of central Pacific seamounts [START_REF] Liao | Microbial diversity in deep-sea sediment from the cobalt-rich crust deposit region in the Pacific Ocean[END_REF][START_REF] Huo | Ecological functions of uncultured microorganisms in the cobalt-rich ferromanganese crust of a seamount in the central Pacific are elucidated by fosmid sequencing[END_REF], and in the sediment and crust of the Takuyo-Daigo Seamount and the Ryusei Seamount [START_REF] Nitahara | Molecular characterization of the microbial community in hydrogenetic ferromanganese crusts of the Takuyo-Daigo Seamount, northwest Pacific[END_REF][START_REF] Nitahara | Archaeal and bacterial communities in deep-sea hydrogenetic ferromanganese crusts on old seamounts of the northwestern Pacific[END_REF]. The MG-I archaea appear to have roles in sulphur and nitrogen cycling [START_REF] Huo | Ecological functions of uncultured microorganisms in the cobalt-rich ferromanganese crust of a seamount in the central Pacific are elucidated by fosmid sequencing[END_REF]. In summary, there are no systematic studies on Archaea inhabiting in seamount area, and based on these limited studies, MG-I Thaumarchaeota was always predominant, and MG-II, Euryarchaeota, and Marine Benthic Group E (MBGE) were also reported in seamount area.

As a unique ecosystem, it is important to better understand seamount biodiversity, the effect of different environmental parameters on the archaeal community and their function in the ecosystems. To fully understand the archaeal community in seamount, we performed a systematic investigation of the archaeal communities on a seamount of the Mariana Volcanic Arc, near the Challenger Deep, in the tropical western Pacific Ocean. We examined the community structure and distribution of Archaea and their relationships with different environmental variables in an effort to better understand microbial communities and their ecological functions in seamount ecosystems.

MATERIALS AND METHODS

Site description and sample collection

Sediments were collected from the Yap Seamount area in the Western Pacific (139°26′-139°43′ E, 11°26′-11°41′ N) during a cruise of the Chinese research vessel "KEXUE" from Feb. to Apr. 2016. Surface sediment samples were collected a custom-made steel alloy collector using the remotely operated vehicle (ROV) Faxian (Discovery in Chinese) at 14 stations and depths of 238-2024 m while assuring its safe operation (Fig. 1) [START_REF] Liu | Bacterial community structure and novel species of magnetotactic bacteria in sediments from a seamount in the Mariana volcanic arc[END_REF]. A sediment sample of approximately 10 g was collected from each station, transferred to a sterile sealed bag, and immediately stored at -20 °C for analyses of the archaeal community.

DNA extraction and PCR amplification

Total genomic DNA was extracted directly from 0.5 g (wet weight) of mixed sediment using the FastDNA Spin Kit for Soil (MP Biomedicals, LLC, USA) and the Fast Prep FP120 Cell Disrupter (Thermo Electron Corp, USA). The quantity and quality of genomic DNA were determined using a NanoDrop ND-1000 spectrophotometer (LabTech, Washington, DC, USA) and 1.0% (w/v) agarose electrophoresis, respectively. The hypervariable region of the archaeal 16S rRNA gene was amplified using PCR (95 °C for 3 min; 35 cycles at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 45 s; a final extension at 72 °C for 10 min; and a cooling step at 10°C) with the bar-coded universal primers Arch344F (5'barcode -ACGGGGYGCAGCAGGCGCGA-3') and Arch915R (5' -barcode -GTGCTCCCCCGCCAATTCCT-3') [START_REF] Ohene-Adjei | Postinoculation protozoan establishment and association patterns of methanogenic archaea in the ovine rumen[END_REF][START_REF] Gantner | Novel primers for 16S rRNA-based archaeal community analyses in environmental samples[END_REF]. PCR was performed in triplicate in a 20-μL mixture, which included 4 μL of 5× Fast Pfu buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of each primer (5 μM), 0.4 μL of Fast Pfu polymerase, 0.2 μL of BSA, 10 ng of template DNA, and double distilled water (ddH 2 O). The PCR product was extracted from 2% agarose gels and purified using an AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer's protocols.

Illumina MiSeq sequencing and operational taxonomic units assignment

Each purified PCR product was first quantified using a QuantiFluor™-ST fluorometer with UV/Blue Channels (Promega, USA). Pair-end libraries were constructed using the TruSeq Nano DNA Library Prep Kit (Illumina, San Diego, CA, USA), and high-throughput sequencing was performed on the MiSeq (Illumina, San Diego, CA, USA) Sequencing Platform (Majorbio Bio-Pharm Technology Co., Ltd, Shanghai, China) following the manufacturer's protocols.

Raw FASTQ files were demultiplexed, quality-filtered using QIIME (Ver. 1.7.0, http://qiime.org/) [START_REF] Caporaso | QIIME allows analysis of high-throughput community sequencing data[END_REF] and Trimmomatic software [START_REF] Bolger | Trimmomatic: a flexible trimmer for Illumina sequence data[END_REF] with the following criteria: (i) 300 bp reads were truncated at any site receiving an average quality score below 20 over a 50 bp sliding window, and truncated reads shorter than 50 bp were discarded; (ii) exact barcode matching was performed, with 2 nucleotide mismatch in primer matching, and reads containing ambiguous characters were removed; (iii) only sequences that overlapped by more than 10 bp were assembled according to their overlap sequence. Reads that could not be assembled were discarded.

Operational taxonomic units (OTUs) were clustered using UPARSE (ver. 7.1 http://drive5.com/uparse/) [START_REF] Edgar | UPARSE: highly accurate OTU sequences from microbial amplicon reads[END_REF] with a 97% similarity cutoff, and chimeric sequences were identified and removed using UCHIME (http://drive5.com/uchime/) [START_REF] Edgar | UCHIME improves sensitivity and speed of chimera detection[END_REF] The classification of each OTU was determined by alignment with the SILVA database (Version 132 http://www.arb-silva.de), and using the RDP Classifier tool (ver. 2.2 http://sourceforge.net/projects/rdp-classifier/) with a credibility threshold of 70% [START_REF] Wang | Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy[END_REF][START_REF] Quast | The SILVA ribosomal RNA gene database project: improved data processing and web-based tools[END_REF]. Taxonomic groups were derived from the number of reads assigned to each taxon at all ranks, from domain to genus, using QIIME. Bar graphs were plotted using an R software package, and a Circos graph (chord diagram) for archaeal community composition was created using Circos software (version 0.67, http://circos.ca/) [START_REF] Krzywinski | Circos: an information aesthetic for comparative genomics[END_REF].

Diversity estimations, statistical and phylogenetic analysis

To equalize the sequencing effort, reads were randomly resampled using the number of reads obtained at the station with the fewest reads using a Perl script [START_REF] Gilbert | The seasonal structure of microbial communities in the Western English Channel[END_REF]. Mothur (ver.

1.30.1, http://www.mothur.org) was applied to estimate Alpha diversity [START_REF] Schloss | Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities[END_REF].

Chao 1 and the abundance-based coverage estimator (ACE) were used to calculate community richness [START_REF] Chao | Nonparametric estimation of the number of classes in a population[END_REF][START_REF] Chao | Estimating the number of classes via sample coverage[END_REF][START_REF] Chao | Stopping rules and estimation for recapture debugging with unequal failure rates[END_REF] and the Shannon and Simpson diversity indexes were used to characterize community diversity [START_REF] Magurran | Ecological Diversity and Its Measurement[END_REF][START_REF] Simpson | Comparative microbial diversity in the gastrointestinal tracts of food animal species[END_REF] Good's coverage at the 97% similarity level was used to evaluate effect of sample depth.

Rarefaction curves were drawn from the calculated results of Mothur and plot-rarefaction using an R software package [START_REF] Amato K R, Yeoman | Habitat degradation impacts black howler monkey (Alouatta pigra) gastrointestinal microbiomes[END_REF].

Correlations between archaeal clades and environmental variables were calculated by

Pearson correlation analysis (two-tail test) using SPSS software. For beta diversity, the Bray-Curtis dissimilarity was calculated by QIIME, and a hierarchical clustering tree was plotted using an R software package, which clustered samples with similar OTU compositions and abundances [START_REF] Bray | An ordination of the upland forest communities of southern Wisconsin[END_REF][START_REF] Yoshioka | Misidentification of the Bray-Curtis similarity index[END_REF]. Principal component analysis (PCA) was performed using the R software base package [START_REF] Jolliffe | Principal Component Analysis[END_REF]. Detrended correspondence analysis (DCA) and redundancy analysis (RDA) were conducted using Canoco (ver. 4.5) to assess the relationship between microbial assemblages and environmental factors [START_REF] Hill | Detrended correspondence analysis: an improved ordination technique[END_REF][START_REF] Šmilauer | Multivariate Analysis of Ecological Data Using Canoco 5[END_REF][START_REF] Desarbo | Redundancy Analysis[END_REF].

The 16S rRNA gene sequences of the most common 50 OTUs were aligned using CLUSTAL W multiple alignment [START_REF] Thompson | CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice[END_REF]. A phylogenetic tree was constructed using MEGA 6 software [START_REF] Tamura | MEGA6: molecular evolutionary genetics analysis version 6.0[END_REF], based on the neighbor-joining (NJ) algorithm, and bootstrap values were calculated from 1000 replicates. The sequences of MG-I were defined using different clusters, as previously described [START_REF] Massana | A few cosmopolitan phylotypes dominate planktonic archaeal assemblages in widely different oceanic provinces[END_REF][START_REF] Takai | Spatial distribution of marine Crenarchaeota group I in the vicinity of deep-sea hydrothermal systems[END_REF][START_REF] Durbin | Archaea in organic-lean and organic-rich marine subsurface sediments: an environmental gradient reflected in distinct phylogenetic lineages[END_REF][START_REF] Jorgensen | Correlating microbial community profiles with geochemical data in highly stratified sediments from the Arctic Mid-Ocean Ridge[END_REF][START_REF] Lauer | Phylogenetic characterization of marine benthic Archaea in organic-poor sediments of the eastern Equatorial Pacific Ocean (ODP Site 1225)[END_REF].

RESULTS

Environmental characteristics

All sampling stations are located on the Kexue Seamount in the Mariana Volcanic Arc (Fig. 1, Table S1). The peak of the seamount is approximately 20 m below the water surface, and the depth of the sample sites ranged from 238 to 2024 m. Stations M2-22 and M2-23 were located at the southeast steep slope and differ from other sites in that they have high concentrations of trace elements. The sediments mainly consisted of different proportions of coral and foraminifera sands.

The temperature of sediments at the deeper stations (>1000 m) was below 4 °C, and the temperatures of other stations ranged from 4.9 °C to 7.3 °C. There were no significant differences in the salinity of the core water, but it was slightly lower at the deeper stations. The level of dissolved oxygen (DO) ranged from 1.5 to 4.9 mg/L, and the highest value was at station M2-8 (Table S1). Pearson correlation analysis indicated that temperature and salinity had strong negative correlations with depth (P < 0.01) (Table S2).

Archaeal diversity and richness

We examined archaeal communities in the sediments from the different seamount sample stations by analysis of the 16S rRNA gene using amplicon sequencing. After quality control, we obtained 358,160 valid reads (average length: 532 bp; range: 20,192 to 31,226 reads per station)

(Table 1). To equalize sequencing efforts, reads were randomly resampled using the number of reads obtained at the station with the fewest reads (20,192; station M2-14-1). A total of 1411 OTUs (based on 97% sequence similarity) were clustered after random resampling, and there were 248 to 697 OTUs per station (Table 1). The rarefaction curves indicated that sufficient sequencing intensities were achieved and that the populations were well-represented (Fig. S1). Good's coverage estimates for all samples exceeded 0.99 (Table 1), indicating that most species in the study area were represented by the amplicon sequencing provided by Illumina MiSeq sequencing.

In general, there were decreases in community diversity (based on Shannon and Simpson indexes)

and in species richness (based on Chao and ACE indexes) with increasing depth. In particular, the greatest diversity and richness were at station M2-8 (495 m), near the top of the seamount; the lowest diversity and richness were at station M2-5 (2024 m), the deepest station (Table 1). Pearson correlation analysis indicated a negative correlation between the Shannon index and depth (P < 0.05), and a positive correlation between the Simpson index and depth (P < 0.05) (Table S2). In sum, the archaeal community diversity and species richness had a significant relationship with depth.

Archaeal taxonomy and community composition

We performed taxonomic assignment at various levels using the Silva database. At the phylum level, the valid reads were mainly in the Thaumarchaeota (96.5%) and Nanoarchaeaeota

(1.4%), and there were a small number of Euryarchaeota (0.2%), Crenarchaeota, Diapherotrites and Altiarchaeota. Thaumarchaeota was the most abundant phylum at all sample stations, and accounted for 87.2% (M2-8; 495 m) to 99.7% (M2-5; 2024 m) of all reads, with an average of 96.5% (Fig. 2). Nanoarchaeaeota was the second most abundant phylum at all stations, and this phylum had the greatest abundance at stations M2-8 (5.3%), M2-13-1 (4.7%), M2-13 (3.0%), and M2-2-2 (2.3%), and M2-8-2 (1.0%), all of which were located near the top of the seamount (Fig. 2). The abundance of this phylum was less than 1% at all other stations. Euryarchaeota accounted for less than 1% of community abundance at all 14 stations.

At the class taxonomic level, Nitrososphaeria (belonging to Thaumarchaeota) dominated at all the 14 stations, and ranged from 83.1% (M2-8) to 99.0% (M2-2-1), with an average of 96.5%.

Marine Benthic Group A (MBGA) had the highest abundance of 6.1% at station M2-13 and had higher abundances at stations M2-2-2, M2-13-1, and M2-4 (Fig. 2; yellow bars). Woesearchaeia had an abundance of 5.3% at station M2-8, and higher abundance at M2-13-1, M2-13, M2-2-2, which were located near the top of the seamount (Fig. 2; violent bars). Additional lineages, such as Group 1.1c belonging to phylum Thaumarchaeota, Nanohaloarchaeia belonging to phylum Nanoarchaeaeota, Thermoplasmata belonging to phylum Euryarchaeota, had abundances less than 1% at all stations (Fig. 2).

At an order level, Nitrosopumilales (originally termed MG-I) dominated at all 14 stations and ranged from 82.4% (M2-8) to 99.0% (M2-2-1). Except for unclassified reads, reads in were Nitrosopumilales grouped into three genera, Candidatus Nitrosopumilus, Candidatus

Nitrosopelagicus and Cenarchaeum belonging to family Nitrosopumilaceae. Unclassified reads were dominant at all stations except M2-22 (Fig. 2; red bars); while Candidatus Nitrosopumilus accounted for 50.7% and unclassified reads accounted for 47.2% at this station. Notably, the abundance of Candidatus Nitrosopumilus tended to increase with depth and had the greatest abundance at stations M2-22, M2-23, M2-10-1, M2-5, and M2-14-1 (Fig. 2; green bars). At station M2-8-2, Cenarchaeum accounted for approximately 1.2% of community abundance, which was 2to 100-fold higher than at other stations (Fig. 2; dark red bars). Notably, there were only several MG-II reads were found in the seamount, with an average of 0.05 %. The highest abundance (0.23%) occurred at a shallower station (M2-8, 495 m). To simplify the analysis, we excluded rare organisms and analyzed the most abundant 50

OTUs (read numbers of 736 to 54,358), which accounted for more than 95% of total reads. Among these 50 OTUs, Nitrosopumilales accounted for 48 OTUs, and Marine Benthic Group A (MBGA) accounted for 2 OTUs. Phylogenetic analysis of these 50 OTUs showed that MG-I was in 7 known clusters, and mainly affiliated with ε-ζ-θ, α, and υ clusters. There were also 6 OTUs in 4 unknown clusters, indicating the possible presence of unique archaeal species in the seamount (Fig. 4).

Comparison of communities and correlations with environmental variables

Analysis of beta diversity based on OTU composition and abundance showed that all but two of the seamount stations (M2-8-2 at 238 m and M2-22 at 1676 m) grouped the archaeal communities into three clusters (Fig. 5). One cluster had stations with water depths less than 500 m (M2-2-1, M2-8, M2-13-1, and M2-2-2), a second cluster had stations at depths of 500-1000 m (M2-3, M2-13, and M2-9; M2-4 with a depth of 1420 m), and a third cluster had 4 stations at depths greater than 1000 m (M2-23, M2-10-1, M2-5, and M2-14-1). Principal component analysis (PCA) indicated a similar grouping of sample stations (Fig. 6). These results thus showed a clear transition of archaeal community composition as a function of water depth in this seamount. We also performed a detrended correspondence analysis (DCA) for all samples to examine the effect of environmental variables on community composition. The longest gradient length was 2.078, indicating that all samples were suitable for redundancy analysis (RDA) using a linear model. The different environmental parameters were selected using a Monte-Carlo test, and a P-value below 0.05 was used as the standard. The first and second RDA components explained 74.9% of the variability in archaeal community structure. Moreover, community divergence mainly correlated with depth, salinity, and concentration of Pb. Dissolved oxygen (DO) and latitude gradients had no clear effects on community structure (Fig. 7). We then conducted correlation analysis to assess the relationship of different environmental variables with Archaea families and individual OTUs. Pearson analysis indicated that the abundance of Thaumarchaeota correlated positively with water depth and Pb concentration (P < 0.05) and that the abundance of Woesearchaeota correlated negatively with water depth and Pb concentration (P < 0.05). Pearson analysis also showed that abundance of Nitrosopumilus correlated positively with Fe concentration (P < 0.01), depth (P < 0.05), and Al concentration (P < 0.05) (Table S2).

DISCUSSION

Archaea are now recognized as important as bacteria in marine biogeochemical cycling.

Archaea are not only among the most abundant microbial plankton groups in the oceans but are also highly abundant in marine sediments [START_REF] Delong | Archaea in coastal marine environments[END_REF][START_REF] Bano | Phylogenetic composition of Arctic Ocean archaeal assemblages and comparison with Antarctic assemblages[END_REF], [START_REF] Wuchter | Archaeal nitrification in the ocean[END_REF][START_REF] Roussel | Archaeal communities associated with shallow to deep subseafloor sediments of the New Caledonia Basin[END_REF][START_REF] Durbin | Sediment-associated microdiversity within the Marine Group I Crenarchaeota[END_REF].

In the present study, we investigated the archaeal diversity and communities of seamount in the Mariana Volcanic Arc, the western Pacific Ocean using high-throughput sequencing.

Interestingly, we found that community diversity and species richness decreased with depth, with the highest values at station M2-8 (495 m), near the top of the seamount, and the lowest values at station M2-5 (2024 m), the deepest sample station. A clear transition of archaeal community composition as a function of water depth could be found in this seamount, so this distinct community composition might be generally consistent with depth. The depth-dependent changes in the distribution of Archaea that we observed might be due to the temperature, which also decreased with depth. Seamounts rise abruptly from the ocean seafloor and have a substantial impact on physical oceanography. In particular, they affect the nature of circulation, local hydrographic distributions, turbulence, and vertical and horizontal transport of nutrients [START_REF] Lavelle | Motion, commotion, and biophysical connections at deep ocean seamounts[END_REF]. It seems reasonable that organic matter flux could have an influence on the distribution, as the observed decreased temperature, having an effect on the energy flux and activity. The seamount flows also have an important influence on bacterial community structure were reported [START_REF] Emerson | Microbiology of seamounts: common patterns observed in community structure[END_REF], as does depth (O 'Hara, 2007;[START_REF] Clark M R, Rowden | The ecology of seamounts: structure, function, and human impacts[END_REF]. So, the temperature and seamount circulation might jointly lead to the depth-dependent diversity and richness changes in the distribution of Archaea.

MG-I (now classified as Nitrosopumilales in phylum Thaumarchaeota) and MG-II (belonging to phylum Euryarchaeota) are the two major phyla of marine Archaea based on analysis of 16S rRNA sequences. In our study, we found that Nitrosopumilales was dominant in surface sediment, most in α, κ-υ, and ε-ζ-θ clusters. Our analysis of a subgroup of Nitrosopumilales sequences indicated the presence of 4 unknown clusters, suggesting there might be novel archaeal species in this seamount. There were still a small amount of Woesearchaeia and Marine Benthic Group A archaea reads in Kexue Seamount. However, there were only several MG-II reads were found, with an average of 0.05 percent. The highest abundance (0.23%) occurred at a shallower station (M2-8, 495 m).

Previous studies of different seamounts had reported that phylotypes affiliated within MG-I were always dominant, and most individuals are in the α, η-κ-υ, and ε-ζ-θ clusters (Nakagawa et al., 2004;[START_REF] Hara | Analysis of the archaeal sub-seafloor community at Suiyo Seamount on the Izu-Bonin Arc[END_REF][START_REF] Kato | Characteristics of microbial communities in crustal fluids in a deep-sea hydrothermal field of the Suiyo Seamount[END_REF]. Ammonia-oxidizing Archaea (AOA) in MG-I, which have the amoA gene, produce energy from the aerobic oxidation of ammonia (NH 4 + ) to nitrite (NO 2 -) [START_REF] Stahl | Physiology and diversity of ammonia-oxidizing archaea[END_REF]. CO 2 is the main carbon source of MG-I, but co-assimilation of organic carbon can also occur [START_REF] Tourna | Nitrososphaera viennensis, an ammonia oxidizing archaeon from soil[END_REF]. This means that MG-I organisms play a vital role in marine biogeochemical cycles, particularly the carbon and nitrogen cycles, and might be responsible for a significant amount of the primary production in dark ocean ecosystems [START_REF] Herndl | Contribution of Archaea to total prokaryotic production in the deep Atlantic Ocean[END_REF][START_REF] Offre | Archaea in biogeochemical cycles[END_REF]. MG-I have a global distribution and are abundant in marine water and sediments (Brochier-Armanet et al., 2008, Stahl and[START_REF] Stahl | Physiology and diversity of ammonia-oxidizing archaea[END_REF]. MG-II and other Euryarchaeota archaea were also present in seamount, with the highest abundance of 30% [START_REF] Nakagawa | Analysis of dissimilatory sulfite reductase and 16S rRNA gene fragments from deep-sea hydrothermal sites of the Suiyo Seamount, Izu-Bonin Arc, Western Pacific[END_REF][START_REF] Kato | Characteristics of microbial communities in crustal fluids in a deep-sea hydrothermal field of the Suiyo Seamount[END_REF], whilst, there were a very small amount of MG-II were found in our study. MG-II is abundant in marine aquatic environments and mainly occur in the photic zone. Their diversity is also greatest in surface seawater and decreases with depth. These organisms live heterotrophically, and are important in the long-term storage of dissolved organic carbon [START_REF] Zhang | Marine group II Archaea, potentially important players in the global ocean carbon cycle[END_REF].

Seamounts provide a variety of habitats and environmental conditions for benthic organisms [START_REF] Clark M R, Rowden | The ecology of seamounts: structure, function, and human impacts[END_REF], and affect underwater currents and create upwellings that attract plankton, corals, and fish [START_REF] Danovaro | Prokaryote diversity and viral production in deep-sea sediments and seamounts[END_REF][START_REF] Clark M R, Rowden | The ecology of seamounts: structure, function, and human impacts[END_REF][START_REF] Rowden | A test of the seamount oasis hypothesis: seamounts support higher epibenthic megafaunal biomass than adjacent slopes[END_REF]. Seamount is believed to support high levels of biodiversity and endemic marine animals [START_REF] Schlacher | Seamount science scales undersea mountains: new research and outlook[END_REF]. Biomass deposition from topwater and a large diversity of organism would promote the accumulation of organic matter in seamount ecosystem. MG-I archaea can drive the assimilation of organic carbon, but no evidence indirectly degrade organic matter. Meanwhile, MG-II archaea unlikely to participate in organic matter degradation, because of their absence in sediment. We hypothesize that MG-I archaea might play an indirect role in organic matter degradation progress, with assisting bacteria in top sediment. Which group of the microbiological organism could contribute to the degradation of organic matter needs to be further study, comprehensively considering the contribution of all the trophic levels in microbial net.

Moreover, the site of the present study is a seamount at the junction of the Yap and Mariana trenches, In particular, the seamount sediments mainly consist of coral and foraminifera sands, which have lower densities of organic carbon [START_REF] Liu | Bacterial community structure and novel species of magnetotactic bacteria in sediments from a seamount in the Mariana volcanic arc[END_REF]. Because of the different requirements of MG-I and MG-II, the unique distribution patterns of Archaea in this seamount might be a consequence of the sediment heterogeneity and the complex geochemistry. The geographic properties of the seamount might contribute to the unique community structure, and made it different from microbial communities of other seamounts.

CONCLUSIONS

Compared with other ocean ecosystems, there is only limited information of Archaea in seamount habitats, which in general are not well-studied environments. We reported the first systematic analysis of archaeal diversity and community structure in a seamount habitat by use of high-throughput sequencing. The results indicated that Nitrosopumilales was the dominant clade at all 14 sample stations, and that water depth and geographic variables seemed to be important in shaping the distinctive archaeal communities. Our study provides a foundation for the study of Archaea in seamounts, and the unique distribution patterns also shed a light on the ecological functions of Archaea in seamounts.

DATA AVAILABILITY STATEMENT

The 16S rRNA gene sequences of the most abundant 50 OTUs in the current study were deposited in the NCBI under accession numbers MG860856-MG860905.

Fig. 1

 1 Fig. 1 Location and sampling stations of Kexue Seamount in the Mariana Volcanic Arc. (a) Overview of the seamount location and Kexue Seamount was shown as a yellow triangle; (b) 14 sampling stations were shown as black circles, and the scale bar is 1 km.

Fig. 2

 2 Fig. 2 Archaeal community composition in sediments of the 14 seamount sample sites at the level of Phylum, Class, Order, and Genus, the average abundance is shown in parentheses.A Circos graph of community composition shows that unclassified Nitrosopumilales dominated the archaeal community at all stations except M2-22 where Nitrosopumilus had a high abundance (Fig.3). Community composition analysis indicated that stations at different depths and locations had different community structures. In particular, Candidatus Nitrosopumilus was dominant at greater depth stations with lower temperature, but unclassified Nitrosopumilales,

Fig. 3 .

 3 Fig. 3. Circos graph (chord diagram) of archaeal community composition, showing the relationships of the main archaeal groups at different sample stations.

Fig. 4

 4 Fig. 4 Phylogenetic relationships of the most abundant 50 archaeal OTUs (~450 bp for alignment length) in the seamount based on 16S rRNA gene sequences, using two MBGA OTUs as out-groups. The tree was constructed using the neighbor-joining (NJ) algorithm, and bootstrap values (from 1000 replicates) are shown as percentages at branch points. GenBank accession numbers of the sequences used are indicated in parentheses.

Fig. 5

 5 Fig. 5 Bray-Curtis hierarchical cluster tree of OTU composition and abundance of Archaea in the seamount. Green: water depth < 500 m; red: water depth = 500-1000 m; blue: water depth > 1000 m.

Fig. 7

 7 Fig. 7 Detrended correspondence analysis of the relationship between archaeal community structure at the OTU level according to sample site and environmental variables. Environmental variables are indicated by arrows, and sample sites as open circles.

Table 1 . Richness and diversity of Archaea in sediment samples at Kexue Seamount, based on 97% sequence similarity.

 1 Chao 1 and ACE provide estimates of richness; Shannon and Simpson provide estimates of diversity, and Good's coverage provides an estimate of coverage. The indexes were calculated after random resampling using the number of sequences obtained from the station with the fewest reads(20,192; station M2-14-1).

			Original
	Station	Depth (m)	Reads	OTUs	ACE	Chao	Coverage	Shannon	Simpson
	M2-8-2	238	25205	335	410	376	0.996	3.70	0.0570
	M2-2-2	474	28186	340	400	388	0.996	3.69	0.0639
	M2-13-1	491	20795	362	436	426	0.996	3.72	0.0658
	M2-8	495	25302	697	800	753	0.993	4.26	0.0450
	M2-2-1	575	22724	248	303	305	0.997	3.38	0.0764
	M2-3	911	26389	318	364	344	0.997	3.36	0.0896
	M2-13	939	21872	489	592	547	0.994	3.70	0.0680
	M2-9	980	29008	323	395	361	0.996	3.46	0.0817
	M2-4	1420	30252	421	531	493	0.994	3.66	0.0681
	M2-14-1	1427	20192	336	388	373	0.997	3.43	0.0837
	M2-10-1	1494	25851	293	359	349	0.996	3.43	0.0786
	M2-23	1583	27893	289	349	330	0.997	3.51	0.0655
	M2-22	1676	31226	304	393	382	0.996	3.29	0.0945
	M2-5	2024	23265	254	297	278	0.997	3.20	0.1031

ACKNOWLEDGMENT

We thank the crew of the R/V Kexue, the ROV team, and W. Zhang for collecting sediment samples.

* Supported by the National Natural Science Foundation of China (Nos. 41776130, 41776131), the Strategic Priority Research Programs (No. XDA11030202.2); the National Natural Science Foundation of China-Shandong Joint Fund (Nos. U1706208, U1606404); and a grant for LIA-MagMC, from the Centre National de la Recherche Scientifique

SUPPLEMENTARY MATERIALS


Neha Chandarana

Emmanuel Ramasso

Constantinos Soutis

Matthieu Gresil

Damage identification in composites through acoustic emission monitoring

Keywords: Composites, normalised mutual information, pattern recognition, piezoelectric sensors, unsupervised clustering

In this work, three carbon/glass hybrid composite tubes are instrumented with eight piezoelectric wafer active sensors (PWAS), used as passive receivers of acoustic emission (AE) signals. A three point bending quasi-static loading is conducted, either in a single cycle until failure or incrementally through multiple loading/unloading cycles. In the first instance, AE signal features such as maximum amplitude, peak frequency, signal duration, and energy are used to distinguish between different damage mechanisms such as matrix cracks, delamination, and fibre breakage. The group velocity of the longitudinal modes -L(0,1) and L(0,2)is obtained experimentally in a pitch-catch configuration between the PWAS network using the time of flight (ToF). The time of arrival (ToA) method is then used to calculate damage source locations from the received AE signals. To involve more signal features for data classification, an unsupervised clustering algorithm is applied to the datasets. Optimisation of the number of clusters is completed by maximising the robustness and minimising the uncertainty of the final result. It is found that the temporal evolution of clusters indicate the ability to distinguish between the initiation and growth of damage, as well as identifying non-damage related signals caused by extraneous noise or related to the test set-up.

INTRODUCTION

Composite materials have become attractive for use in structural applications over recent years, since their properties can be tailored according to needs, but assessment of damage remains a challenge. Periodic non-destructive inspections (NDI) of components can give an insight into their performance but the complexity of these techniques often results in significant down-time and increased labour costs. The cost of inspection in aerospace composites, for example, can represent up to a third of the lifecycle costs [START_REF] Diamanti | Structural health monitoring techniques for aircraft composite structures[END_REF]. Since composite materials allow for the integration of sensors, with negligible effect on their mechanical properties, permanent structural health monitoring (SHM) systems have sparked a great deal of interest [START_REF] Diamanti | Structural health monitoring techniques for aircraft composite structures[END_REF]. Piezoelectric transducers are particularly used for their low cost, small size, durability, and low power consumption [START_REF] Chandarana | Early damage detection in composites during fabrication and mechanical testing[END_REF].

In this work, quasi-static three point bending of carbon/glass hybrid composite tubes has been completed. By monitoring acoustic emission (AE) signals during loading, it is possible to estimate damage source locations and speculate about different damage modes [START_REF] Godin | Integration of the Kohonen's self-organising map and k-means algorithm for the segmentation of the AE data collected during tensile tests on crossply composites[END_REF], [START_REF] Kotsikos | Use of acoustic emission to characterize corrosion fatigue damage accumulation in glass fiber reinforced polyester laminates[END_REF] via signal analysis. The effort is in distinguishing between matrix cracking, delamination, and fibre breakage. An unsupervised pattern recognition algorithman extension of [START_REF] Ramasso | Unsupervised Consensus Clustering of Acoustic Emission Time-Series for Robust Damage Sequence Estimation in Composites[END_REF] has been applied to AE data to understand the initiation and progression of damage when the data is separated into clusters.

MATERIALS AND METHODS

Instrumentation of composite tubes

The composite tubes (60.3 mm internal diameter and 1.6 mm thick) presented in this work are a hybrid of unidirectional (UD) carbon fibres oriented in the axial (0°) direction and UD glass fibres in the hoop (90°) direction (supplied by Easy Composites Ltd.). The lay-up order of fibers is [0, 90, 0, 90, 0]. Each specimen was cut to a length of 1 meter prior to instrumentation with sensors.

Three specimens were tested, each instrumented with piezoelectric wafer active sensors (PWAS) [START_REF] Giurgiutiu | Structural Health Monitoring with Piezoelectric Wafer Active Sensors[END_REF] supplied by PI ceramic -PIC255 with 10 mm diameter and 0.5 mm thickness [START_REF] Pi Ceramic | Piezoelectric Ceramic Products[END_REF]. Eight PWAS were surface mounted on each specimen for AE monitoring during loading. On specimen 1, 32 PWAS were also bonded for pitch-catch excitation of guided waves. The arrangement of PWAS is shown in Figure 1.

Experimental set-up

The experimental set-up for flexural three point bending is shown in Figure 2. Three specimens were tested in total: specimen 1 was first subjected to a low velocity impact with approximately 5 J (resulting in an axial crack of approximately 7 cm length [START_REF] Chandarana | Characterisation of Damaged Tubular Composites by Acoustic Emission, Thermal Diffusivity Mapping and TSR-RGB Projection Technique[END_REF]), followed by three point bending over five cycles of loading/unloading; specimens 2 and 3 were subjected to bending until failure. The low frequency cycling of specimen 1 was introduced to encourage the progression of damage through repeated loading. The load vs. time curves are shown in Figure 3.

AE data acquisition and processing

During loading, AE activity was recorded via eight channels on a PCI-2 based acquisition system supplied by Mistras. Discrete AE waveforms (hits) were recorded using the 'AEwin' software package. The threshold amplitude was set to 55 dB to eliminate sources of extraneous noise, and to account for the 20 dB of pre-amplifier gain per channel. The sampling rate was set at 10 MHz (5 MHz on 2 channels due to hardware limitation) and timing parameters set to: peak definition time (PDT) = 200 µs, hit definition time (HDT) = 800 µs, hit lockout time (HLT) = 1 ms, maximum signal duration = 100 ms. Using subsets of 4 from a total of 17 features (as extracted through 'AEwin') per AE hit an unsupervised pattern recognition algorithm (based on the Gustafson-Kessel algorithm [START_REF] Gustafson | Fuzzy clustering with a fuzzy covariance matrix[END_REF]) was applied to the full dataset for each specimen. For specimen 1, the five cycles are concatenated in time to form one large dataset. The optimal number of clusters for each dataset is found by maximizing the normalized mutual information criterion (NMI) [START_REF] Fred | Combining multiple clusterings using evidence accumulation[END_REF].

RESULTS AND DISCUSSION

The time of arrival (ToA) method available within 'AEwin' is used to calculate AE source locations in order to track the growth of damage in the specimens during each loading cycle of specimen 1 (Figure 4). The presence of signals during earlier cycles of loading correlates well with the damage locations observed in the final cycle of loading, suggesting that it may be possible to estimate the failure location before reaching 70% of the breaking strength of the specimen.

CONCLUDING REMARKS

In the present work, the potential for the use of acoustic emission is demonstrated as a tool for detecting, localising, and classifying damage mechanisms arising during quasi-static loading. The use of an unsupervised clustering algorithm eliminates any operator bias and reduces the time taken to obtain a final result. Further work is required to develop a means of linking data clusters to individual damage modes in the composite, by means of destructive and non-destructive validation via, for example, x-ray computed tomography. Identifying the location, size and type of damage is of great importance in the effort to estimate residual life and long term performance of the composite tube [START_REF] Soutis | Multi-scale modelling of composite materials: the art of predictive damage modelling[END_REF].

Figure 1 .

 1 Figure 1. Schematic showing the approximate positions of PWAS used for AE (green) and guided waves (blue) on specimen 3.

Figure 2 .

 2 Figure 2. Experimental set-up for three point loading of specimen 1.

Figure 3 .

 3 Figure 3. (a) Load vs. time for all cycles on specimen 3; (b) Load vs. extension for specimens 2 and 3.

Figure 4 (

 4 Figure 4 (to be continued). Calculated damage locations during each loading of specimen 1: (a) cycle 1 (blue ˅), (b) cycle 2 (green ˄), (c) cycle 3 (purple ˃), (d) cycle 4 (lime green ˂), (e) cycle 5 (turquoise □).

Figure 4 .

 4 Figure 4. Estimated damage locations during loading of specimen 1: (a) cycle 1 (blue ˅), (b) cycle 2 (green ˄), (c) cycle 3 (purple ˃), (d) cycle 4 (lime green ˂), (e) cycle 5 (turquoise □). Dashed lines indicate locations of the through-thickness final failure cracks. Red arrows indicate the top of the specimen.

Figure 5 .

 5 Figure 5. Number of AE hits recorded by all channels, separated into clusters, for specimen 3.

Figure 6 .

 6 Figure 6. AE hits from all channels separated into clusters for (a) specimen 2 and (b) specimen 3.

ACKNOWLEDGEMENTS

The authors acknowledge the funding and technical support from BP through the BP International Centre for Advanced Materials (BP-ICAM) and financial support from EPSRC (EP/L01680X) through the Materials for Demanding Environments Centre for Doctoral Training which made this research possible. The authors also acknowledge the EIPHI Graduate School (contract "ANR-17-EURE-0002" and FEMTO-ST Institute for both funding and technical input to support the collaboration with The University of Manchester. This work has been partly done in the frame of the research project RESEM-COALESCENCE, managed by the Institut de Recherche Technologique Matériaux Métallurgie Procédés (IRT M2P) and financially supported by the French research program Plan d'Investissement d'Avenir (PIA).


Azure Hansen

Yun-Jhih Chen

Moshe Shuker

Rodolphe Boudot

Eugene Ivanov

Gregory W Hoth

Bruno Pelle

John E Kitching

Elizabeth A Donley

Performance of a point source atom interferometer gyroscope

la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche

Keywords-quantum sensors, atom interferometry, gyroscope

Matter wave interferometry facilitates precision measurements of fundamental physics, but its utility in practical devices has been limited due to the size and complexity of such instruments until recently. The development of a compact gyroscope for navigation that is sufficiently sensitive and precise remains an important goal. The technique of point source atom interferometry (PSI) [START_REF] Dickerson | Multiaxis inertial sensing with long-time point source atom interferometry[END_REF] is promising for a gyroscope device, as the setup is simplified (see Figure 1) compared to other light atom interferometer pulse gyroscope systems. It has the additional advantage that the measurement inherently measures two axes of rotation and one axis of acceleration simultaneously.

PSI makes use of the ballistic expansion of the cold atom cloud to generate a fringe pattern from which rotation and acceleration are measured. Three collinear and counterpropagating Raman pulse pairs (see Figure 1) act as optical beamsplitters and mirrors, creating a Mach-Zehnder-like interferometer for each atom, which accumulates a phase dependent on its velocity vector and the inertial forces applied to the system. When the cloud is imaged, these parallel interferometers generate a phase gradient across the atom cloud, leading to fringes in the atomic spin state population. The orientation and frequency of the fringes measures the component of the rotation vector in the plane perpendicular to the Raman beams, as shown in Figure 2. The phase of the fringes measures the acceleration parallel to the Raman beams.

The performance of our compact PSI-based device is limited by a variety of effects, including the interrogation time of the interferometer Raman pulse sequence, the phase noise of the Raman beams (90 mrad at 1 s), the vibrations of the Raman optics (62 mrad at 1 s), the dead time of the experiment, systematic errors relating to the atom cloud not being an ideal point source, and others [START_REF] Hoth | Point source atom interferometry with a cloud of finite size[END_REF]. For our current experimental setup and parameters, the measured sensitivity to the magnitude and direction of the rotation vector is 0.6 mrad/s and 5 mrad, respectively. Our estimates of the shotnoise-limited performance for an ideal point source gyroscope are 2 µrad/s and 50 µrad at 1 s. Our current work focuses on measuring, modeling, optimizing, and correcting for performance-limiting effects with the goal of creating a compact atom interferometer gyroscope in mind. Improvements being pursued include creating a smaller and more uniform initial atom cloud with an optical dipole trap, the reduction of the Raman laser phase noise with a different frequency chirping scheme, active vibration isolation, and modeling the effect of initial cloud size and shape on the scale factor.

Fig. 1 .

 1 Fig. 1. Illustration of the compact point source atom interferometer gyroscope setup. The Raman beamline is oriented along gravity (z axis) and the magnitude and direction of rotation is measured in the plane perpendicular to the beams (xy plane). Rotations can be simulated by tilting the piezo-driven retro-reflecting mirror. The atom cloud is imaged onto a camera and the fringe pattern indicates the magnitude of acceleration along z and the magnitude and orientation of the rotation vector in the xy plane.

Fig. 2 .

 2 Fig. 2. Absorption images of interference fringes generated by simulated rotation. Left: Ωy = 35 mrad/s. Center: Ωx = Ωy = 25 mrad/s. Right: Ωx = 89 mrad/s.

ACKNOWLEDGMENT A. H. was supported under an NRC Research Associateship award at NIST. R. B. was supported by the NIST Guest Researcher Program and the Délégation Générale de l'Armement (DGA). This work was funded by NIST, a U. S. government agency, and is not subject to copyright.