N Chen
email: chenn@wpi-aimr.tohoku.ac.jp

D V Louzguine-Luzgin

G Q Xie

P Sharma

J H Perepezko

M Esashi

A R Yavari

A Inoue

Structural investigation and mechanical properties of a representative of a new class of materials: nanograined metallic glasses

come

Structural investigation and mechanical properties of a representative of a new class of materials: nanograined metallic glasses.

Introduction

The properties of a material are determined by its internal structure. This relationship has guided numerous attempts to produce new structures for improving the performance of materials. In light of this, the birth of metallic glasses has triggered intensive research on their physical, chemical and mechanical properties due to their distinct structural difference from the crystalline counterparts [1][2][3][4][5][6]. The usual way to produce a metallic glass is cooling of a viscous metallic liquid, which can yield bulk metallic glasses (BMGs) [7,8]. Owing to their attractive mechanical properties such as high strength and relatively low elastic moduli, BMGs hold tremendous promise for applications in engineering fields [9][10][11][12]. However, few BMG alloys exhibit macroscopic tensile ductility, which dramatically reduces their utility for load-bearing structural applications [13,14]. This undesirable property stems from the unavoidable shear localization associated with the BMGs' macroscopically uniform microstructure. To address this issue, the most successful way is to develop metallic-glass-matrix composites by introducing ductile crystalline phases [15][16][17], but the improved ductility, unfortunately, is always accompanied by a trade off in the strength.

Nanocrystalline materials, with a grain size of typically <100 nm, show unique properties derived from a large fraction of grain boundaries compared to coarse-grained polycrystalline counterparts. Usually with decreasing the grain size nanocrystalline metals show higher strength, in accord with the Hall-Petch relationship [18,19]. In light of the grain size-strength effect in nanocrystalline materials, one can expect that a material with nanometer-sized grains having a glassy structure may show enhanced strength and ductility [20,21]. Recently, we produced such a Au 52 Ag 5 Pd 2 Cu 25 Si 10 Al 6 nanograined metallic glass (NGMG) with clear glass-glass interfaces [22]. In this paper, we report on the interrelationship between the atomic structure and the enhanced mechanical properties of this Au-based NGMG material.

Experimental procedure

The Au 46 Ag 6 Pd 2 Cu 27 Si 14 Al 5 (NGMG1) and Au 52 Ag 5 Pd 2 Cu 25 Si 10 Al 6 (NGMG2) were prepared using conventional magnetron sputtering. The detailed procedure for the formation of the NGMGs can be found in [22]. The role of the synthetic parameters on the structure of the film is discussed below.

The structure of the Au-based thin films was investigated by synchrotron radiation x-ray diffraction in transmission and high-resolution transmission electron microscopy (HRTEM) methods. The mechanical testing was carried out by using both a nanoindentation technique (Ubi 1, nanomechanical test instrument, Hysitron, Inc., USA) and a NEC MH4000 tester (a mechanical properties tester for thin films). Annealing treatment on the samples was done in a vacuum furnace at 463 K. The surface morphological evolution after the annealing was investigated by scanning electron microscope (SEM) examination. The chemical compositional analysis was conducted by an energy dispersive x-ray spectrometry (EDS) device attached to the SEM. The thermal properties of the samples were measured by a differential scanning calorimetry (DSC) method. The density measurements using the Archimedean principle were performed with a microbalance having a sensitivity of 0.01 µg. N-Tridecane was used as a liquid for measurements. The weight of every sample was measured three times in both the liquid and air and then the average values were applied to calculate the densities.

Results and discussion

As-deposited structure

The glassy nature of the as-deposited Au-based NGMGs was confirmed by (HR) TEM methods as illustrated in figure 1. Both Au 46 Ag 6 Pd 2 Cu 27 Si 14 Al 5 (NGMG1) and Au 52 Ag 5 Pd 2 Cu 25 Si 10 Al 6 (NGMG2) samples presented a nanometer-sized granular structure. The microstructure that is presented in figures 1(a) and (f) illustrates the granular morphology with both dark and light contrasts. The dark contrast area represents amorphous regions of high density (i.e. grains) while the light contrast that was between the amorphous grains highlighted in figures 1(d) and (i) represents amorphous regions of low density (i.e. interface). Using a lognormal fit of the particle size distributions (figures 1(a) and (f)), the spheroid-like nanoparticles of NGMG1 and NGMG2 samples have a mean grain size of 21 nm and 29 nm (figures 1(e) and (j)), respectively. The larger size of the NGMG2 sample may be attributed to its higher Au content, which promotes clustering of nanoparticles [23]. The selected area electron diffraction (SAED) pattern of NGMG1 shows a weak contrast overlapping on the amorphous ring as indicated by yellow arrows, possibly due to the presence of nanocrystals (figure 1(b)). The sharp diffraction spots in the nanobeam electron diffraction (NBED) pattern confirmed the existence of the nanocrystals (figure 1(c)). The corresponding layer of very fine ordered zones is evident at the interfaces among the particles (marked by yellow arrows in figure 1(d)).

In the case of the NGMG2 sample, no sharp rings, but only diffuse haloes can be found, as shown in figure 1(g), implying that the nanograins are indeed glassy (figure 1(f)). The NBED pattern from the interface structure demonstrates only a diffuse halo (figure 1(h)), that indicates that a fully glassy structure is obtained even at the interfaces of NGMG2. HRTEM images show maze-like patterns that are typical for an amorphous structure (figure 1(i)), further confirming that both the nanograins and the grain interfaces are glassy.

To further probe the structural characteristics of the fully glassy NGMG2 sample, synchrotron x-ray radiation measurements were carried out in transmission. The intensity, I(Q) versus scattering vector Q plots were processed and the resulting pair distribution functions (PDF) were derived as shown in figure 1(k), revealing a typical feature of an amorphous structure. The first peak was fitted with two Gaussian functions (figure 1(l)). The results of fitting indicate that the first maximum of the pair distribution function (PDF) consists of two subpeaks: one at 0.2341 nm, the other at 0.2807 nm, representing the mean first nearest atomic distances. The first subpeak position is between the sum of Goldschmidt atomic radii of the Si-Si pair (0.232 nm) and the Cu-Si pair (0.245 nm), and possibly attributed to these atomic pairs. The second subpeak position is larger than the interatomic distance of Au-Si (0.261 nm) and may represent the Au-Au separation (0.288 nm). For the second maximum (from 0.35 to 0.61 nm) the positions of subpeaks are at 0.4708 and 0.5408 nm, respectively. The positions of the subpeaks in the second maximum correspond very closely to those in a Pd 81 Si 19 alloy studied earlier [24], and are likely attributed to the atomic size of the main component gold (0.144 nm) that is also close to that of Pd (0.137 nm). The above results indicate the formation of a densely packed structure within the glassy particles.

Thermal stability

The DSC curve of NGMG2 demonstrates a clear glass transition temperature T g of 420 K, the initiation crystallization temperature T x of 453 K, the peak crystallization temperatures T p1 of 463 K and T p2 of 520 K, respectively (figure 2 shows the same broad peak as the original sample, indicating that no obvious crystallization takes place at this stage. With increasing annealing time to 1.5 h, the first broad diffraction peak becomes apparently narrower and the peak position shifts to a lower diffraction angle, clearly demonstrating the crystallization of the Au-based NGMG2. The crystalline phase is indexed to be a fcc Au-rich solid solution as shown in figure 2(e). The evolution of structural morphology accompanying the precipitation of nanocrystals is shown in figures 2(f) and (g). The crystalline phase nucleates at the grain interfaces and within the grain interior. Voids are formed between the glassy grains if nucleation takes place at the interfaces due to volume contraction, as illustrated by the red arrows in figure 2(g). As indicated the white arrows in figure 2(g), the nanocrystals also precipitated within the nanometer-sized glassy grains. Basically, the length scale of the precipitated crystals depends on the original glassy grain size, which offers a new option to produce very fine crystals with controllable size. It is important to stress here that the nanograined glassy particles are very stable compared to the conventional homogeneous glassy structure since no clear structural difference can be detected even after annealing at the peak crystallization temperature for 15 min (figure 2(d)).

Such a high stability of NGMG2 is also supported by the DSC curve of the corresponding Au 52 Ag 5 Pd 2 Cu 25 Si 10 Al 6 ribbons (figure 2(b)). Compared to NGMG2, the glassy ribbon samples prepared by melt-spinning display much lower T g of 405 K, T x of 430 K, T p1 of 436 K and T p2 of 494 K, respectively. A significantly narrower T of 25 K shown by the ribbons suggests their reduced thermal stability in comparison with NGMG2. Very recently, Priestley and co-workers reported a similar nanoglobular structure formed in a polymer glass which demonstrated ultrahigh kinetic stability [25]. Distinct from the usual way of cooling a liquid, the alternative route to make a glass from a gaseous phase may significantly alter the molecular packing by allowing surface deposits to reside in low energy configurations, thereby giving rise to a dramatic change in both structure and properties [26]. Simultaneously the annealing-induced nanocrystals are also quite stable against coarsening as evidenced by the SEM image shown in figure 2(g).

Nanograin synthesis

The sputtering technique used in the present study can provide a cooling rate of up to 10 12 K s -1 , which is around six orders of magnitude higher than the typical cooling rate for the melt-spinning method. At a cooling rate of this order, a computer simulation result predicted that single component Cu glassy droplets may be formed [27]. Usually high cooling rate leads to a less stable glassy structure due to the short relaxation time during the preparation process. However, unusually stable organic glasses and polymer glasses have been prepared by vapor deposition with low deposition rates [28][29][30][31]. In addition, the increase in stability of the nanostructured polymer glassy film was confirmed to originate from the property of the nanoglobules that constitute the film [25]. With many metallic glasses that require synthesis by rapid melt quenching, a slow deposition rate will yield crystalline formation. But the high glass forming ability of BMGs enables amorphous alloy formation at low deposition rates. As a result, a slow deposition rate of around 1 nm s -1 coupled with an enhanced surface mobility permits the attainment of low energy configurations of amorphous nanoparticles and thus promotes the formation of the Au-based NGMG thin films.

It is important to note that we used a cyclic deposition process instead of the usual continuous sputtering. Namely, we stopped sputtering for 10 min after every 10 min continuous sputtering. The purpose of this cyclic deposition mainly has two aspects. One is to avoid a high temperature rise of the substrate. The other is to provide sufficient time for the glassy particles to nucleate and grow due to the high atomic mobility on the surface.

With the magnetron sputtering technique, the microstructure of thin films is mainly controlled by the applied deposition rate, the rotation angle of the substrate and the substrate temperature. In our case, the substrate surface orientation is parallel to that of the target. Meanwhile, there is no cooling or heating system attached to the substrate. Therefore, the only changeable parameter is the deposition rate, which can be tuned by two key factors including the applied power for sputtering and the distance between the target and the substrate. To simplify the process, the distance between the substrate and the target is also fixed to be 110 cm. Hence, the parameter applied to change the deposition rate is only the input power of sputtering. In order to clarify the correlation between the sputtering power and the microstructure, we used different values of the applied power on deposition. As shown in figure 3(a), the deposition rate v decreases with decreasing the power P. However, the basic structural constituents for all the samples are still glassy particles, at least within the power values used in the present study (figures 3(b)-(e)). One can also note that in the samples prepared at lower input power, the particles aggregated into bigger clusters at the same deposition time.

Mechanical properties

The density of the Au-based NGMG2 is measured to be 13.33 g cm -3 . For an as-cast Au 52 Ag 5 Pd 2 Cu 25 Si 10 Al 6 rod sample with a diameter of 3 mm and an almost fully glassy structure, the density is ∼14.21 g cm -3 . The density difference between NGMG2 and the bulk sample is ∼6.2%, which is much larger than the density reduction (usually <0.5%) due to structural relaxation of metallic glasses [32]. The density variation between nanoglasses and relaxed glasses could reach up to 15% before voids are found, which may lead to a large property change of the materials [33].

Nanoindentation tests were performed to evaluate the mechanical properties. at high magnifications. The clusters are further composed of nanometer-sized particles of around 30 nm in diameter. The cluster size distributions of both samples are displayed in figures 4(c) and (d). The crystallized NGMG2 shows a mean cluster size of 143 nm with a narrower size distribution than NCMA with a mean cluster size of 175 nm (figures 4(c) and (d)). The shape of the clusters is more spherical-like than those of the NCMA specimen, possibly due to the isotropic growth associated with the glassy structure. One of typical depth-load curves of the annealed NGMG2 and the NCMA samples is shown in figure 4(e). The corresponding scanning probe microscopy (SPM) images of the indenters are shown in figures 4(g) and (h). Based on five independent measurement points, the average hardness can be derived to be 4.8 GPa and 3.9 GPa for the crystallized NGMG2 and NCMA samples, respectively. The hardness of the as-prepared NGMG2 is around 5.3 GPa [22] while the hardness of the crystallized sample is about 4.8 GPa. The lower hardness than the original nanograined glassy structured sample is likely associated with the voids formed during the nanocrystallization process, but the crystallized Au 52 Ag 5 Pd 2 Cu 25 Si 10 Al 6 NGMG2 sample still exhibited a higher hardness than Au 61 Ag 5 Pd 1 Cu 19 Si 7 Al 7 NCMA, which likely results from their Au concentration difference. It has been reported that higher Au content yields lower hardness of the Au-based metallic glasses [34]. Compared with 3.9 GPa for the bulk Au 49 Ag 5.5 Pd 2.3 Cu 26.9 Si 16.3 BMG, the nanocrystallized Au-based NGMG2 shows a higher hardness, of almost three times greater than that of conventional 18-karat crystalline gold alloys [35]. This indicates that the nanometer-sized nanograins having glassy structure indeed hardened the materials, similar to the grain size-strength effect in nanocrystalline materials. In addition, from the depth-load curves, the elastic modulus can be also derived to be 108 GPa and 115 GPa for NCMA and the crystallized NGMG2 samples, respectively. Both values are higher than ∼70 GPa for the Au-based BMGs [36,37]. Indeed there is a tendency to overestimate the Young's modulus of thin films by nanoindentation due to both the substrate and the indentation pile up effects [38]. But the elastic modulus increases with the Au content increase as the hardness changes, which is also consistent with the results reported in [34].

To obtain a reliable elastic modulus (E) of the as-deposited Au-based NGMG2, we used an alternative beam-bending method [39]. The bending deflection for a composite beam is calculated using the following equation:

d 2 Y dX 2 = -M i E i I i (1)
where M is the bending moment, and E i and I i are the Young's modulus and geometrical moment for the element i. The geometrical moments of inertia for a film/substrate composite are given by

I sub = bh 3 sub /12 (2)
I tf = bh 2 sub h tf E sub (1 + 2α)/4(E sub + 2αE tf ) + bh 3 tf /12 (3)
where the subscripts sub and tf denote the substrate and thin film terms, respectively, b is the substrate width, h is the thickness and α is the thickness ratio h tf /h sub . The loading point deflection d sub+tf at the center of the composite beam can be written as

d sub+tf = Fl 3 /48(E sub I sub + E tf I tf ) (4)
where F denotes the load. By combining equations ( 2) and (3), equation ( 4) can be rewritten as

F = 4bh 3 sub [E sub + E tf α 3 + 3E sub E tf α(1 + 2α)/(E sub + 2αE tf )]d sub+tf . (5)
As shown in figure 4(f), by linear fitting the data of 521 experimental points located within the range between the two marks, the E of the sample is derived to be ∼79 GPa. The combination of the high hardness and low E value indicated that the Au-based NGMG2 maintained the good mechanical properties of the Au-based BMGs [35][36][37].

Recently the sample size effect on the mechanical response of metallic glasses has been the focus of theoretical and experimental investigations [40][41][42][43][44][45][46][47]. Reducing the sample size is supposed to drive metallic glasses to deform homogeneously. Regarding the deformation mode via homogeneous or inhomogeneous plastic flow, however, a paradoxical debate has been aroused when the sample size is reduced to the nanoscale [43,44]. The main concern responsible for this controversy is attributed to the size limitation associated with the focused ion beam (FIB) fabrication method, which also imposes an extrinsic effect such as Ga + implantation on the experimental reliability [48,49]. An alternative way to produce nanometer-sized samples for mechanical testing is thus necessary to avoid the unwanted extrinsic effects. Now, using the deposition approach we have developed, the Au-based NGMGs were synthesized with a particle size of only ∼30 nm, which is comparable with the size scale of shear bands, normally of the order of several tens of nanometers [44]. Thus, the nanoglassy particles would be an ideal material to test the size effect on the mechanical response of metallic glasses. We used a spherical indenter tip to intentionally deform the NGMA1 sample. Because the load on the material is asymmetrical due to the surface height fluctuations, a tensile stress is induced at some sites. Along the tensile direction, the nanoglassy particles are stretched and the plasticity mainly originates from the elongation of

Nanograin structural morphology

A closer examination of nanoglass morphology as displayed in images such as that shown in figure 4(a) reveals typical fractal features of self-similarity at different scales. For example, a fractal analysis using a known formula:

D = - d ln N(ε) d ln ε ≈ ln(m) ln(r) , (6)
where N(ε) is the amount of covering of size ε, m is the number of repetitions of the reduced fractal pattern of size r, which gives fractal dimension D of 1.8 for 1 bit black and white images and 2.8 for a grayscale image [50]. Although it is a 2D representation of a 3D structure, it represents a fractal (self-similar) nature of the structural morphology. During thin film deposition, island structure genesis can evolve through various mechanisms such as diffusion controlled aggregation or by physical contact [51]. With the latter process the island (or grain) size distribution can develop a bimodal character.

In the case of the NGMG, the structures in figures 1(a), (f), 4(a) and in prior work [22] reveal a bimodal character composed of nanoglassy grains and nanograin assemblies that are consistent with the observed self-similar behavior.

In conclusion, the unusually stable Au-based NGMG having nanoglassy granular structure shows an elastic modulus of ∼79 GPa and a hardness of ∼5.3 GPa, so that they are stronger and more elastic than the crystalline counterparts and display high ductility. The attributes of an optimum combination of high strength, high hardness and large surface area are attractive for numerous applications in the areas of coatings, catalysis and electronics. When subjected to an annealing treatment, smaller nanocrystals precipitated from the nanometer-sized glassy grains, which provides an alternative way to produce new crystalline materials with tailored length scale.

Figure 1 .

 1 Figure 1. Bright-field TEM images of NGMG1 (a) and NGMG2 (f); the particle size distribution analysis of NGMG1 (e) and NGMG2 (j); selected area electron diffraction (SAED) patterns of NGMG1 (b) and NGMG (g), respectively; the typical nanobeam diffraction (NBD) patterns of NGMG1 (c) and NGMG2 (h) (probe size 3 nm); HRTEM images illustrating the interfaces between glassy particles in NGMG1 (d) and NGMG2 (i). The synchrotron x-ray radiation measurements in transmission of NGMG2. (k) Pair distribution functions (PDFs) derived from Q • I(Q) by the usual Fourier transformation and (l) a part in the first coordination shell fitted with two Gaussian functions.

  (a)). The supercooled liquid region T (=T x -T g ) is 33 K. Based on these data, NGMG2 was annealed at 463 K for 15 min and 1.5 h, respectively. The XRD patterns of the as-deposited and the annealed samples are shown in figures 2(c)-(e). After annealing for 15 min the sample still

Figure 2 .

 2 Figure 2. DSC curves of (a) the as-deposited Au-based NGMG2 and (b) the corresponding glassy ribbons. XRD patterns of (c) the as-deposited Au-based NGMG2 and the samples annealed at 463 K, (d) for 15 min and (e) for 1.5 h; (f) and (g) are the corresponding SEM images of samples (c) and (d).

  For comparison, we produced Au 61 Ag 5 Pd 1 Cu 19 Si 7 Al 7 nanocrystalline metallic alloy (NCMA) thin films. The SEM images of the crystallized Au 52 Ag 5 Pd 2 Cu 25 Si 10 Al 6 NGMG2 and the Au 61 Ag 5 Pd 1 Cu 19 Si 7 Al 7 NCMA are shown in figures 4(a) and (b). The inset of figure 4(b) presents the images obtained

Figure 3 .

 3 Figure 3. (a) Deposition rate variation with forward power for depositions and SEM images of the thin films deposited at (b) 70 W, (c) 90 W, (d) 130 W and (e) 150 W.

Figure 4 .

 4 Figure 4. SEM images of (a) the NGMG2 annealed at 463 K for 1.5 h and (b) NCMG samples; the inset of (b) is the SEM image at a high magnification. (c), (d) The cluster size distribution analysis of SEM images (a) and (b), respectively. (e), (f) are the corresponding SPM images of the indents for the crystallized NGMG2 and the NCMG samples, respectively. (g) One of the typical depth-load curves derived from nanoindentation tests for both samples. Elastic modulus determination of the NGMG2 based on the principle of a beam-bending test (h) the load-deflection curve of the Au-based NGMG deposited on the standard quartz glass substrate. The left inset is the schematic diagram for elastic modulus measurement and the right insets are the parameters of thickness (T), length (L), width (W) and the elastic modulus (E) of the standard quartz substrate.

Figure 5 .

 5 Figure 5. (a) An SEM micrograph demonstrating the elongation of the nanoglassy particles of the NGMG1 sample along the stress direction (arrow). (b) Enlarged view of the elongated nanoglassy particles indicated by brackets. (c) Schematic illustration of the deformation of nanoglassy particles.

Acknowledgments

This work was supported by the World Premier International Research Center Initiative (WPI), MEXT, Japan and partially supported by the Research and Development Project on Advanced Materials Development and Integration of Novel Structured Metallic and Inorganic Materials from the Ministry of Education, Culture, Sports, Science and Technology, Japan. JHP is grateful also for support from ONR (N00014-12-1-0569) in this area.


D Makarov

F Klimenta

S Fischer

F Liscio

S Schulze

M Hietschold

M Maret

M Albrecht

Nonepitaxially grown nanopatterned Co-Pt alloys with out-of-plane magnetic anisotropy

A study on the structural and magnetic properties of 5-nm-thick Co-Pt alloy films grown on thermally oxidized SiO 2 /Si͑100͒ substrates as well as on self-assemblies of spherical SiO 2 particles with sizes down to 10 nm is presented. An out-of-plane easy axis of magnetization was stabilized at deposition temperatures as low as 250 °C in a broad composition range between 40 and 70 at. %of Pt. Owing to the low deposition temperatures, no chemical long-range order is found. Thus, the strong outof-plane magnetic anisotropy is expected to be caused by anisotropic short-range order effects. The magnetic behavior of CoPt alloys with an equiatomic composition grown on arrays of SiO 2 particles was found to be similar to those on planar substrates. Structural investigations using high-resolution transmission electron microscopy revealed that a continuous CoPt layer has been formed, covering the particle tops and connecting them. The magnetic CoPt caps exhibit an out-of-plane easy axis for all particle sizes; however, no pronounced difference in coercive field with particle size was observed, which is associated with the specific morphology of the film structure.

I. INTRODUCTION

For further increase in the storage density in magnetic hard disk drives, materials with high uniaxial out-of-plane magnetic anisotropy such as ͑001͒ textured FePt or CoPt alloys are required to provide sufficient thermal stability for the written bits of information. However, high annealing temperatures are required to form an L1 0 chemical order in initially fcc-disordered alloys. [START_REF] Coffey | [END_REF] Therefore, many studies are directed to lower the ordering temperature, for instance, by growing the alloys on appropriate buffer layers, such as MgO, Ag, Cr, and CrRu, [2][3][4][5] or by utilizing surfactants to guide the formation of anisotropic local ordering during deposition. [6][7][8] Recently, a reduction in ordering temperature was reported for CoPt 3 ͑111͒ thin films grown on a low energy surface of WSe 2 ͑0001͒. [9][10][11] In this case, a strong out-of-plane magnetic anisotropy is induced by a short-range anisotropic chemical order driven by Se segregation even for films grown at room temperature. 8 Note that out-of-plane anisotropy direction is not expected neither in the disordered fcc structure nor in the L1 2 -ordered CoPt 3 ͑111͒ phase. A similar behavior was also observed in thin CoPt 3 ͑111͒ films grown on Pt͑111͒ and Ru͑0001͒ at elevated deposition temperatures of about 400 °C just before long-range L1 2 -type chemical ordering sets in. 12,13 In addition, the presence of out-of-plane anisotropy was found in fcc-disordered CoPt films with an equiatomic composition grown on fused SiO 2 substrates. 14 The physical origin of the short-range ordering resulting in the out-of-plane magnetic anisotropy is not yet clear. In this regard, Maranville et al. 15 performed kinetic Monte Carlo ͑MC͒ simulations on continuous CoPt 3 films relating the out-of-plane magnetic anisotropy to the short-range order induced by clustering of Co due to its step-edge segregation during the deposition process. This Co step-edge segregation does not depend on a particular growth direction. Therefore, the magnetic anisotropy orientation is expected to be independent of the growth direction, in agreement with experimental results reported by Shapiro et al. 16 In contrast, MC simulations by Heinrichs et al. 17,18 considered Pt segregation at the surface as a mechanism responsible for the short-range order effect in CoPt 3 alloy nanostructures.

In this article, a detailed study on the magnetic and structural properties of 5-nm-thick Co-Pt films grown on thermally oxidized Si͑100͒ substrates is presented, including a careful investigation of the dependence on the growth temperature and composition of Co-Pt alloys. Furthermore, the combination of a template consisting of self-assembled nanoparticles with magnetic film deposition provides an elegant way of creating ordered arrays of nanostructures with welldefined magnetic properties. [19][20][21] Therefore, it was investigated how these film properties will be altered by depositing 5-nm-thick CoPt alloys with an equiatomic composition onto self-assemblies of spherical SiO 2 particles with various particle sizes down to 10 nm.

II. EXPERIMENTAL DETAILS

The deposition of metal films was performed on planar thermally oxidized 100-nm-thick SiO 2 / Si͑100͒ substrates as well as on monolayers of self-assembled SiO 2 particles. Par-a͒ Author to whom correspondence should be addressed. Electronic mail: denys.makarov@physik.tu-chemnitz.de. ticle self-assemblies were prepared by using the convention routine proposed by Micheletto et al., 22 where a droplet of a particle/water mixture is deposited onto a thermally oxidized silicon wafer. The samples were introduced into a molecular beam epitaxy chamber operating at a base pressure of 2 ϫ 10 -10 mbar. Metal deposition was carried out utilizing two electron beam sources. The composition of the codeposited Co-Pt alloy was controlled by a mass spectrometer adjusting the ratio between the individual Co and Pt fluxes. The deposition temperature, T dep , was varied between room temperature and 415 °C. The total thickness of the Co-Pt alloys was chosen to be 5 nm. An additional 1-nm-thick Pt capping layer was deposited at room temperature to protect the samples from oxidation.

The structural characterization has been carried out by x-ray diffraction ͑XRD͒ using a four-circle Huber diffractometer equipped with a Cu K␣ rotating anode ͑ = 1.5406 Å͒ and by scanning electron microscopy ͑SEM͒ and by high-resolution transmission electron microscopy ͑HRTEM͒ employing a 200 kV Philips CM 20 FEG transmission electron microscope. The magnetic properties of the samples were investigated by a polar magneto-optical Kerr effect ͑P-MOKE͒ magnetometer using a focused laser beam with a wavelength of 670 nm and by a superconducting quantum interference device magnetometer in both in-plane and out-of-plane geometries. Magnetic force microscopy ͑MFM͒ was utilized to image the magnetic domain configurations of the samples at room temperature.

III. RESULTS AND DISCUSSION

A. CoPt alloys grown on planar SiO 2 substrates: Temperature dependence 5-nm-thick CoPt alloy films with an equiatomic composition were grown on amorphous SiO 2 / Si͑100͒ substrates at various growth temperatures between room temperature and 415 °C. The topography of the films was studied using atomic force microscopy ͑AFM͒, SEM, and transmission electron microscopy ͑TEM͒, revealing a grainy film morphology with a root mean square roughness of about 0.7 nm as well as a grain size of ͑20Ϯ 5͒ nm, which varies only slightly with deposition temperature up to 415 °C. An example is given in Fig. 1͑a͒ showing a cross-sectional bright field TEM image performed on a film grown at 415 °C.

In addition, XRD measurements reveal a ͓111͔ preferred orientation of grains along the surface normal ͑Fig. 2͒. The main structural properties deduced from the x-ray patterns are summarized in Table I. The spacing of the fcc 111 planes is found to be very close to that in the bulk CoPt alloy ͑d 111 = 2.18 Å͒. The perpendicular coherence length, L perp , deduced from the full width at half maximum ͑FWHM͒ of the 111 peaks increases with increasing deposition temperature, indicating an improvement of the ͑111͒ texture. The FWHM of the rocking curve measured at the 111 reflection for the sample grown at 415 °C is equal to 10°characterizing the poor degree of 111 grain orientation, in agreement with the HRTEM micrograph ͓Fig. 1͑b͔͒. For the other samples grown at lower temperatures, the rocking curves are nearly flat, confirming the random orientation of 111 grains.

The magnetic characterization performed on the sample grown at RT reveals an in-plane magnetic anisotropy dominated by the shape anisotropy of the magnetic film. An anisotropy field of H A = 7.1 kOe is extracted from the hard-axis loop ͑measurement in the out-of-plane geometry͒ ͓Fig. 3͑a͔͒. Taking into account the saturation magnetization of the film ͑M S = 589 emu/ cm 3 ͒, an effective anisotropy constant of K eff = H A M S / 2=-2.1ϫ 10 6 ergs/ cm 3 was estimated. The latter nearly matches the value of the shape anisotropy, K shape =2M S 2 = -2.2ϫ 10 6 ergs/ cm 3 . Note that the saturation magnetization is found to be substantially smaller than the value reported for bulk CoPt alloys, which is in the range of 800 emu/ cm 3 . [START_REF] Cullity | Introduction to Magnetic Materials ͑Addison-Wesley[END_REF][START_REF] Visokay | [END_REF][25] Although a lowering of the saturation magnetization is reported for nanostructured FePt films, 26 the reason for the reduction of M S in CoPt alloys grown on SiO 2 substrates is not clear. The formation of dead magnetic layers at the interface between CoPt and SiO 2 might be one of the possible explanations. The increase in the deposition temperature above 160 °C results in the appearance of a uniaxial magnetic anisotropy, leading to the stabilization of an out-of-plane easy axis of magnetization ͑Fig. 3͒. A maximum effective anisotropy value of about 2.6ϫ 10 6 ergs/ cm 3 was obtained for the sample deposited at 415 °C ͓Fig. 4͑a͔͒. The increase in anisotropy is accompanied with an enhancement of the outof-plane coercive field, H C ͓Fig. 4͑b͔͒. In addition, an enhancement of the normalized out-of-plane remanence magnetization, M R / M S , was observed, as summarized in Fig. 4͑c͒.

The presence of a strong out-of-plane magnetic anisotropy was also confirmed by analyzing the local magnetic domain configuration of the CoPt alloy in the demagnetized state using MFM imaging. A clear dark and bright contrast was observed, as shown in Fig. 5, where the increase in the deposition temperature from 250 to 415 °C leads to a slight decrease in the average domain size from ͑150Ϯ 30͒ to ͑120Ϯ 30͒ nm.

Owing to the structural isotropy and the absence of the L1 0 chemical order, the presence of neither out-of-plane easy axis of magnetization nor strong magnetic anisotropy is expected. The presence of an out-of-plane magnetic anisotropy in fcc CoPt 3 films has already been reported 13,14,27,28 and has been explained based on x-ray absorption fine structure measurements in terms of anisotropic chemical short-range order due to the excess of Co-Co nearest neighbors in the film plane driven by Pt segregation during codeposition. 29 This effect leads to a strong anisotropy of the 3d orbital moment of Co as well as to a weak anisotropy of the Pt orbital moment as deduced from angle-dependent x-ray magnetic circular dichroism measurements. 28 However, other mechanisms, such as growth-induced heterogeneity 16 or TABLE I. Summary of the structural properties of 5-nm-thick CoPt alloy films grown on SiO 2 / Si͑100͒ substrates at various temperatures. The XRD study was performed using Cu K␣ radiation ͑ = 1.5406 Å͒. The position of the 111 peak, 2, the FWHM of the peak, ⌬͑2͒, the perpendicular coherence length, L perp , and the spacing of the fcc 111 planes, d 111 , extracted from the peak position are listed. magnetically induced phase separation, 12 have to be considered as well. Moreover, the composition modulation in CoPt thin films grown on MgO͑111͒ single crystalline substrates might result in a formation of a chemically ordered L1 1 phase with strong out-of-plane anisotropy. 30,31 In this case, the appearance of an additional superstructure peak at 2 ϳ 21°is expected. However, the texture quality of the investigated CoPt films is too poor to draw any conclusion supporting the possibility of the L1 1 phase formation.

T dep =

B. Co-Pt alloys grown on planar SiO 2 substrates: Composition dependence

The stabilization of the out-of-plane easy axis is found to be strongly dependent on the composition of the Co-Pt alloys. 14 Therefore, the structural and magnetic properties of Co-Pt alloy films with various compositions covering the range between Co 0.25 Pt 0.75 ͑CoPt 3 ͒ and Co 0.75 Pt 0.25 ͑Co 3 Pt͒ were investigated. For all these alloy films, the deposition temperature was chosen to be 415 °C. XRD -2 diffraction patterns are shown in Fig. 6. Similar to the XRD study presented above ͑Fig. 2͒, a ͑111͒ texture is observed. The position of the 111 peak shifts to higher 2 values with decreasing Pt content, which corresponds to a reduction of the distance between 111 closest-packed planes. The extracted structural parameters from the XRD diffraction patterns are summarized in Table II.

The hysteresis loops of these samples are presented in Fig. 7. The sample with the lowest Pt content has an easy axis of magnetization in the film plane ͓Fig. 7͑a͔͒. With in-creasing Pt content above 50 at. %, a strong out-of-plane magnetic anisotropy was observed ͓Figs. 7͑b͒-7͑d͔͒. The corresponding effective magnetic anisotropy values are plotted in Fig. 8͑a͒. Note that in this composition range, the maximum value of effective anisotropy constant is found for the alloy with 53 at. % of Pt. The increase of the Pt content in the alloy results in the gradual decrease of the K eff caused by the substantial reduction of the saturation magnetization ͓Fig. 8͑b͔͒.

C. CoPt films grown on self-assembled arrays of SiO 2 nanoparticles

CoPt films with an equiatomic composition were deposited at 415 °C on self-assembled SiO 2 particle arrays with various particle diameters ranging from 10 to 900 nm. An example of a densely packed array consisting of 160 nm particles is presented in Fig. 9͑a͒. Note that owing to the particle size distribution, the pattern reveals some structural defects. The high-resolution TEM image in Fig. 9͑c͒ shows that the cap consists of individual grains of typically ͑8 Ϯ 5͒ nm in lateral size with different orientations of the dense plane packing ͓marked with white lines in Fig. 9͑c͔͒.

The selected area electron diffraction image shown as an inset in Fig. 9͑c͒ proves the polycrystalline nature of the CoPt film on the SiO 2 particles. A bright field cross-sectional TEM image taken on this sample is shown in Figs. 9͑b͒ and9͑c͒, revealing that neighboring film caps are clearly interconnected, resulting in direct magnetic exchange coupling in the magnetic cap array.

The magnetic properties of the films deposited on the particle arrays were investigated using P-MOKE magnetometry and MFM imaging. A series of P-MOKE hysteresis loops is shown in Fig. 10͑a͒. The coercive field is found to be almost independent of the particle size. In this respect, the behavior of CoPt alloys differs substantially from the one observed on Co/Pd͑Pt͒ multilayers grown on arrays of polystyrene nanoparticles, where a scaling dependence of the coercive field on the particle size was found. 20,21 This behavior is most likely due to the difference in film morphology, which gives rise to exchange coupling in the CoPt cap arrays. To get a better understanding of the magnetization reversal in the system, the angular dependence of the out-ofplane switching field was additionally investigated ͓Fig. 10͑b͔͒. This has been done by measuring remanence curves using P-MOKE and by plotting the Kerr rotation signal at zero field after applying a reverse field under an angle to the initially saturated sample. The normalized switching field, H S / H S ͑0°͒, where H S ͑0°͒ is the switching field measured at 0°͑out-of-plane͒, is plotted in Fig. 10͑b͒ versus the angle between the applied magnetic field and the direction normal to the sample plane. Surprisingly, the reversal behavior measured on particle arrays and on the planar substrate is found to be rather similar. However, the observed behavior differs from the one predicted according to the available theoretical models describing the magnetization reversal via a coherent rotation of magnetization ͑Stoner-Wohlfarth model 32 ͒ or via domain wall nucleation/propagation. 33 A pronounced dispersion in magnetic easy axis orientation might be responsible for the weak angular dependence of the switching field ͓Fig. 10͑b͔͒. In this case, the reversal is governed by many nucleation sites and limited domain wall propagation, as expected on the particle array. However, in order to make a final conclusion, a detailed micromagnetic modeling of the magnetization reversal is required.

MFM imaging is a powerful tool to locally visualize the magnetic domain configuration of the CoPt caps and to investigate the magnetic coupling in the particle arrays. A series of MFM images taken at remanence after acdemagnetizing the samples is presented in Fig. 11. Multidomain configurations are observed on SiO 2 particles with sizes larger than 160 nm ͓Figs. 11͑b͒-11͑d͔͒, which is expected from the average domain size of about 120 nm measured on a CoPt film grown on a planar SiO 2 / Si͑100͒ substrate ͓Fig. 11͑a͔͒. With decreasing particle size down to 100 nm, caps preferentially in a single-domain state are found ͓Fig. 11͑e͔͒. This situation changes again for the deposit on the smallest particles of 10 nm. In this case, the observed domain pattern appears to be rather similar to the one obtained on the planar SiO 2 / Si͑100͒ substrate ͓compare Figs. 11͑a͒ and11͑f͔͒. Therefore, it is suggested that a strong exchange coupling between neighboring caps is present and that magnetic domains can easily spread over the particle array.

In order to follow the magnetization reversal process in the magnetic cap arrays, MFM images had been taken at remanence after exposing samples to different reverse magnetic fields H R . Note that an out-of-plane reverse field was applied to the initially saturated samples. A series of selected MFM images for the 100 nm particle array is shown in Fig. 12͑a͒. In agreement with the P-MOKE hysteresis loop revealing a full remanence, the magnetization direction of the nanocaps after saturation remains unchanged at remanence. With the increase in the reverse field to Ϫ1.5 kOe, several switching events, which are randomly distributed, occur. This shows the presence of various nucleation sites; however, at larger reverse fields, it appears that domain wall propagation sets in as well. The reversal of the 330 nm particle array shows the formation of multidomain states on the particle caps. From this comparison, in addition to the angle dependence of the switching field, it is suggested that rather exchange-coupled caps are present, leading to a reversal process that is dominated by nucleation which is widely spread accompanied by domain wall propagation across the particle arrays.

Furthermore, the particle template can also provide effective pinning sides for domain walls where effective domain wall pinning occurs when the magnetic domain wall width is comparable with the size of the pinning sites. [34][35][36][37] In our films, the thickness of the Bloch domain wall is estimated to be about 18 nm, which is of similar size compared to the areas where the caps are interconnected. A similar behavior was recently reported for CoPt alloys grown on arrays of SiO 2 particles using 10-nm-thick MgO seed layers. 38 However, an alternative explanation of the presence of single-domain caps in the exchange-coupled media could be related to the formation of the bubble domains with a domain wall at the rim of a particle. Indeed, the magnetic parameters of the CoPt films used in the study fulfill the stability requirements for bubble domain formation. [39][40][41][42]

IV. CONCLUSIONS

A study on the structural and magnetic properties of nonepitaxial Co-Pt alloy films grown on amorphous SiO 2 substrates was presented. It turns out that hard magnetic Co-Pt thin films with out-of-plane anisotropy can be formed at deposition temperatures as low as 250 °C in a broad composition range between 40 and 70 at. % of Pt. The structural origin of this out-of-plane magnetic anisotropy in textured films is attributed to the anisotropic short-range order effect; however, this needs to be further investigated.

A CoPt alloy with an equiatomic composition was then deposited on arrays of SiO 2 particles of various sizes. The magnetic properties appear to be independent of particle size and similar to those found for films grown on planar substrates concerning M R / M S , coercive field H C , and angledependent switching. This behavior is related to the specific morphology of the cap structures where domain wall pinning at the rim of the cap might play an important role in the magnetization reversal process.

ACKNOWLEDGMENTS

The authors would like to thank B. Mainz ͑TU Chem-nitz͒ for assistance in TEM measurements and A. Teichgräber ͑TU Chemnitz͒ for the preparation of SiO 2 particle assemblies. The financial support by the European Commission through the project TERAMAGSTOR ͑Grant No. FP-7-FIG. 11. ͑Color online͒ Series of MFM images taken at remanence on the samples with different particle sizes after ac demagnetizing: ͑b͒ 900 nm, ͑c͒ 330 nm, ͑d͒ 160 nm, ͑e͒ 100 nm, and ͑f͒ 10 nm particles. The position of the underlying particle template is marked for clarity. The dotted circles indicate several caps in a multidomain magnetic state. The domain pattern taken on a sample grown on a planar SiO 2 / Si͑100͒ substrate is shown for comparison in ͑a͒.

FIG.

12. ͑Color online͒ Series of MFM images taken on ͑a͒ 100 nm and ͑b͒ 330 nm particles at remanence after exposing them to a reverse magnetic field, H R , perpendicular to the substrate. Note that the images were taken at different locations on the sample.

b͒

  Present address: Max-Planck-Institut für Mikrostrukturphysik, D-06120 Halle, Germany. c͒ Present address: CNR-IMM Sezione di Bologna, 40129 Bologna, Italy.

FIG. 1 .

 1 FIG. 1. ͑a͒ Cross-sectional bright field TEM study performed on a CoPt film grown at 415 °C revealing CoPt grains with a width of about 20 nm. ͑b͒ HRTEM micrograph shows randomly oriented CoPt grains.

FIG. 4 .

 4 FIG. 4. The evolution of ͑a͒ the effective anisotropy constant, ͑b͒ out-ofplane coercive field, and ͑c͒ remanence magnetization with increasing deposition temperature.

FIG. 6 .

 6 FIG. 6. ͑Color online͒ XRD -2 diffraction patterns of 5-nm-thick Co-Pt films with various compositions. The positions of the 111 peak for the CoPt 3 and Co 3 Pt alloys are marked with dashed lines. All samples were grown at 415 °C on amorphous SiO 2 / Si͑100͒ substrates.

FIG. 7 .FIG. 8 .

 78 FIG.7. Hysteresis loops measured in out-of-plane and in-plane geometries of the applied magnetic field for 5-nm-thick Co-Pt alloy films grown at 415 °C.

FIG. 9 .

 9 FIG. 9. CoPt alloy grown on an array of SiO 2 particles with a diameter of 160 nm. ͑a͒ Corresponding SEM image and ͑b͒ bright field cross-sectional TEM image. ͑c͒ The high-resolution TEM image revealing a polycrystalline structure of an individual CoPt grain. The white solid lines in ͑c͒ indicate the different orientations of the dense plane packing. The selected area electron diffraction pattern is presented as an inset in ͑c͒.


Lucie Cassarino

Katharine R Hendry

Michael P Meredith

Hugh J Venables

Christina L De

La Rocha

Silicon isotope and silicic acid uptake in surface waters of Marguerite Bay, West Antarctic Peninsula

Keywords:

The silicon isotope composition (δ 30 Si) of dissolved silicon (DSi) and biogenic silica (BSi) provides information about the silicon cycle and its role in oceanic carbon uptake in the modern ocean and in the past. However, there are still questions outstanding regarding the impact of processes such as oceanic mixing, export and dissolution on the isotopic signature of seawater, and the impacts on sedimentary BSi. This study reports the δ 30 Si of DSi from surface waters at the Rothera Time Series (RaTS) site, Ryder Bay, in a coastal region of the West Antarctic Peninsula (WAP). The samples were collected at the end of austral spring through the end of austral summer/beginning of autumn over two field seasons, 2004/5 and 2005/6. Broadly, for both field seasons, DSi diminished and δ 30 Si of DSi increased through the summer, but this was accomplished during only a few short periods of net nutrient drawdown. During these periods, the δ 30 Si of DSi was negatively correlated with DSi concentrations. The Si isotope fractionation factor determined for the net nutrient drawdown periods, ɛ uptake , was in the range of -2.26 to -1.80 ‰ when calculated using an open system model and -1.93 to -1.33 ‰ when using a closed system model. These estimates of ɛ are somewhat higher than previous studies that relied on snapshots in time rather than following changes in δ 30 Si and DSi over time, which therefore were more likely to include the effects of mixing of dissolved silicon up into the mixed layer. Results highlight also that, even at the same station and within a single growing season, the apparent fractionation factor may exhibit significant temporal variability because of changes in the extent of biological removal of DSi, nutrient source, siliceous species, and mixing events.

Paleoceanographic studies using silicon isotopes need careful consideration in the light of our new results.

Introduction

Dissolved silica (silicic acid or DSi) is a key nutrient in the surface ocean and is taken up by plankton such as diatoms, silicoflagellates and radiolarians during the production of their cell walls or skeletons. Diatoms largely dominate the cycling of silicon in the oceans [START_REF] Tréguer | The World Ocean Silica Cycle[END_REF] and have been estimated to carry out 50 to 70% of the net primary production in the oceans [START_REF] Nelson | Production and dissolution of biogenic silica in the ocean -Revised global estimates, comparison with regional data and relationship to biogenic sedimentation[END_REF]. In addition, because of the ballast provided by their silica cell wall (frustule) and their tendency to aggregate into relatively large, rapidly sinking particles, diatoms are one of the major phytoplankton likely to be exporting material from the surface layer via the biological pump. In this way, silica cycling may have a profound influence over the global carbon cycle during the present [START_REF] Demaster | The accumulation and cycling of biogenic silica in the Southern Ocean: revisiting the marine silica budget[END_REF][START_REF] Sarmiento | Three-dimensional simulations of the impact of southern ocean nutrient depletion on atmospheric CO2 and ocean chemistry[END_REF] and in the past [START_REF] Archer | What caused the glacial/interglacial atmospheric pCO2 cycles?[END_REF][START_REF] Harrison | Role of increased marine silica input on paleo pCO2�levels[END_REF] even though the contribution of diatoms to the global export has been debated and could vary significantly between species and ocean areas [START_REF] Assmy | Thick-shelled, grazer-protected diatoms decouple ocean carbon and silicon cycles in the iron-limited Antarctic Circumpolar Current[END_REF][START_REF] Baines | Causes and biogeochemical implications of regional differences in silicification of marine diatoms[END_REF][START_REF] Weston | Primary production export flux in Marguerite Bay (Antarctic Peninsula): Linking upper water-column production to sediment trap flux[END_REF]. The Southern Ocean represents the largest incompletely utilized macronutrient reservoir in the global ocean where silica and carbon cycle are strongly correlated [START_REF] Pondaven | Resolving the "opal paradox" in the Southern Ocean[END_REF][START_REF] Sigman | The polar ocean and glacial cycles in atmospheric CO2 concentration[END_REF][START_REF] Tréguer | Dynamics of nutrients and phytoplankton, and fluxes of carbon, nitrogen and silicon in the Antarctic Ocean[END_REF].

In recent years, the silica cycle has been studied using the Si isotopic composition of DSi, δ 30 Si DSi , and biogenic silica or BSi (δ 30 Si BSi ) from the water column and from sediments, which allows the investigation of Si dynamics over large spatial and temporal scales [START_REF] Cardinal | Relevance of silicon isotopes to Si-nutrient utilization and Si-source assessment in Antarctic[END_REF][START_REF] De La Rocha | The silicon isotopic composition of surface waters in the Atlantic and Indian sectors of the Southern Ocean[END_REF][START_REF] De Souza | Silicon stable isotope distribution traces Southern Ocean export of Si to the eastern South Pacific thermocline[END_REF].Variations in Si isotope ratios offer information on the extent of removal of DSi during the growing season by siliceous plankton, with the Si isotope ratio (δ 30 Si) defined as:

( ) ( )
where δ 30 Si is the sample isotopic signature, 30 Si/ 28 Si sam is the sample ratio of the isotope 30 Si and 28 Si and 30 Si/ 28 Si std of the standard.

In this way, Si isotopes have been used as an oceanographic tracer and for paleoclimatic studies of productivity and nutrient cycling (e.g. [START_REF] Beucher | Sources and biological fractionation of Silicon isotopes in the Eastern Equatorial Pacific[END_REF][START_REF] Closset | Seasonal variations, origin, and fate of settling diatoms in the Southern Ocean tracked by silicon isotope records in deep sediment traps[END_REF][START_REF] De La Rocha | Fractionation of silicon isotopes by marine diatoms during biogenic silica formation[END_REF][START_REF] De La Rocha | Purification, recovery, and laser-driven fluorination of silicon from dissolved and particulate silica for the measurement of natural stable isotope abundances[END_REF][START_REF] Fripiat | Processes controlling the Si-isotopic composition in the Southern Ocean and application for paleoceanography[END_REF]. However, the use of δ 30 Si DSi to determine Si utilization by diatoms requires more thorough investigations. The influence of environmental and biological factors on the behaviour of Si isotopes in the surface mixed layer (and thus diatoms) throughout the course of the entire year is not fully understood. For example, the contribution of non-summer bloom diatoms to DSi drawdown may have more impact than expected on the Si isotope budget.

De La [START_REF] De La Rocha | Fractionation of silicon isotopes by marine diatoms during biogenic silica formation[END_REF] first reported Si isotope fractionation during BSi formation from DSi by diatoms. Their laboratory cultures indicated that diatoms have a fractionation factor (α) of 0.9989 ± 0.0004, indicating that the δ 30 Si of biogenic silica, δ 30 Si BSi , is 1.1‰ more negative than the δ 30 Si DSi used for growth because BSi formation preferentially incorporates the lighter isotopes ( 28 Si), leaving the remaining water enriched in heavier isotopes ( 30 Si). This inverse relationship is clearly shown by an increasing DSi and a decreasing of Si isotope from surface waters to the sea bed (e.g. [START_REF] Coffineau | Exploring interacting influences on the silicon isotopic composition of the surface ocean: a case study from the Kerguelen Plateau[END_REF][START_REF] De La Rocha | The silicon isotopic composition of surface waters in the Atlantic and Indian sectors of the Southern Ocean[END_REF]Fripiat et al., 2011a;[START_REF] Reynolds | Silicon isotope fractionation during nutrient utilization in the North Pacific[END_REF]. More recent studies

(1)

indicate that the fractionation of Si is potentially species dependent, as fractionation during biomineralization ranges from -0.54‰ to -2.09‰ for two Southern Ocean diatoms grown in laboratory culture [START_REF] Sutton | Species-dependent silicon isotope fractionation by marine diatoms[END_REF]. In addition, the dynamic environment in which diatoms grow can cause complications in the interpretation of Si isotopes. For example, vertical mixing of DSi into the surface ocean layers has a stronger effect than DSi removal by diatoms during non-bloom times of the year, impacting the relationship between Si isotopes and nutrient removal [START_REF] Coffineau | Exploring interacting influences on the silicon isotopic composition of the surface ocean: a case study from the Kerguelen Plateau[END_REF]. Furthermore, Si isotopes in the surface ocean might be affected by fractionation during BSi dissolution. This process is poorly constrained but has been reported to have a value between 0 and -0.55‰ [START_REF] Demarest | Fractionation of silicon isotopes during biogenic silica dissolution[END_REF][START_REF] Wetzel | What controls silicon isotope fractionation during dissolution of diatom opal? Geochim[END_REF].

Here, we investigate the time-varying concentration and Si isotopic composition of DSi in surface waters over the course of spring and summer in Ryder Bay on the West Antarctic Peninsula (WAP).

These are the first data to follow the seasonal progression of Si isotopes in the surface ocean at a given site both during times of net nutrient drawdown and during times of stronger mixing relative to diatom growth. This study illustrates the challenges that arise when calculating the fractionation of Si isotopes by diatoms in natural settings, as biological and physical factors, such as water mass inputs, strongly influence the DSi concentration and δ 30 Si DSi .

Material and methods

Study area and sample collection

Seawater samples were collected during the austral summers of 2004/2005 and 2005/2006, once or twice a week, from the Rothera Time Series (RaTS) site within Ryder Bay, a small embayment within the larger Marguerite Bay on the WAP Shelf (Fig. 1). The RaTS site is located 4 km offshore and has an approximate water depth of 520 m. Samples were obtained from 15 m depth (the average depth of the fluorescence maximum in Ryder Bay [START_REF] Clarke | Seasonal and interannual variability in temperature, chlorophyll and macronutrients in northern Marguerite Bay, Antarctica[END_REF] Above UCDW, a deep homogenous mixed layer exists in winter, created due to late autumn and winter cooling, sea ice formation and sinking of dense, cold waters [START_REF] Meredith | Impact of the 1997/98 ENSO on upper ocean characteristics in Marguerite Bay, western Antarctic Peninsula[END_REF]. In summer, the melt of sea ice and discharge of glacial ice acts to freshen the surface, which is also warmed by insolation; this creates a shallow summer mixed layer that overlies the remnant of the winter mixed layer, the latter surviving as a subsurface temperature minimum termed the Winter Water Mass (WW).

At the RaTS site, large and colonial forms of diatoms dominate summer blooms [START_REF] Clarke | Seasonal and interannual variability in temperature, chlorophyll and macronutrients in northern Marguerite Bay, Antarctica[END_REF] leading to a significant reduction of DSi (i.e. 20μM), however nutrient (PO 4 , NO 3 , Si(OH) 4 ) concentrations remain high [START_REF] Ducklow | The Marine System of the Western Antarctic Peninsula[END_REF][START_REF] Weston | Primary production export flux in Marguerite Bay (Antarctic Peninsula): Linking upper water-column production to sediment trap flux[END_REF] due to UCDW intrusion. The dominance of diatoms in this region should imply a considerable export to deep waters with fast sinking through diatoms aggregation and fecal pellets [START_REF] Mcdonnell | Variability in the average sinking velocity of marine particles[END_REF], however some studies have characterised the West Antarctic Peninsula as "high recycling, low export" area with a measured export of 1-10% of the primary production in upper water column assessed using sediment trap fluxes [START_REF] Ducklow | Particle export from the upper ocean over the continental shelf of the west Antarctic Peninsula: A long-term record, 1992-2007[END_REF][START_REF] Weston | Primary production export flux in Marguerite Bay (Antarctic Peninsula): Linking upper water-column production to sediment trap flux[END_REF]. More recent studies as Buesseler et al. (2010) and [START_REF] Stukel | The imbalance of new and export production in the western Antarctic Peninsula, a potentially "leaky" ecosystem[END_REF] re-estimated the export using the flux proxy, thorium-234. Both studies show that moored conical shaped sediment traps significantly underestimate export by an order of magnitude.

Treatment and analysis of samples

DSi concentration of samples were determined using the acid-molybdate spectrophotometric method [START_REF] Strickland | A practical handbook of seawater analysis[END_REF]. For isotopic analysis, DSi was precipitated from the seawater with triethylamine molybdate, collected, rinsed, and then combusted (12 hours at 1050 °C) to form a mixture of relatively pure cristobalite and tridymite (SiO 2 ) as described in De La [START_REF] De La Rocha | Purification, recovery, and laser-driven fluorination of silicon from dissolved and particulate silica for the measurement of natural stable isotope abundances[END_REF]. ) was diluted up to 7.7 ml with deionized, distilled water

At
(18.2 MΩ-cm) (Milli-Q).
Separation of the silicon from any remaining contaminants from seawater (in particular magnesium, sulphate, and boron) was carried out using anion-exchange chromatography. The columns used contained 4 ml of AG 1-x8 resin of 100-200 mesh (BioRad). All samples, standards (NBS28) and blanks were purified following steps summarised in Table 1. A final dilution was required before Si isotope analysis on the Neptune multi-collector inductively coupled plasma mass spectrometer (MC-ICP-MS, IFREMER, Plouzané, France). Si-containing elutions were diluted with 2% HNO 3 to 1 ppm Si to produce an approximate 20V signal on mass 28 at medium resolution. The samples were doped with 0.1 ppm Mg using a standard solution to allow estimation of the amount of isotope fractionation occurring within the machine during the measurement through the monitoring of the 26 Mg/ 25 Mg ratio [START_REF] Cardinal | Isotopic composition of silicon measured by multicollector plasma source mass spectrometry in dry plasma mode[END_REF][START_REF] Engstrom | Chromatographic purification for the determination of dissolved silicon isotopic compositions in natural waters by high-resolution multicollector inductively coupled plasma mass spectrometry[END_REF]. All samples and standards were matched to give the same signal strength and to contain 1mM of HF. Five minutes of rinse with a solution of the same nitric and HF concentration as the samples (and standards) followed each sample and each standard solution (NBS28).

Si isotope ratios ( 30 Si/ 29 Si and 29 Si/ 28 Si) were corrected for mass bias during the measurements by Mg-correction [START_REF] Cardinal | Isotopic composition of silicon measured by multicollector plasma source mass spectrometry in dry plasma mode[END_REF], as per the following example:

( ) ( ) ( )
where ( 30 Si/ 28 Si) meas is the measured ratio, and are the atomic masses of 30 Si and 28 Si.

, the magnesium fractionation factor, is calculated assuming exponential fractionation law, from the beam intensities on masses 25 and 26:

[ ( ) ] [ ]
where 25 Mg A / 26 Mg A is the expected ratio of the natural abundance of the isotopes, ( 25 Mg/ 26 Mg) meas is the measured ratio and 25 Mg AM and 26 Mg AM are the atomic masses of 25 Mg and 26 Mg.

Each measurement of a sample was conducted between two measurements of the standard and each sample was measured two times (Table 2 shows the average of the two measurement and 1SD is the internal error from the two measurement). Together, the two sample measurements and the three standard measurements were used to calculate δ 30 Si and δ 29 Si values (Equation 1). Furthermore, δ 30 Si/δ 29 Si was monitored and found to correspond to the expected mass fractionation, δ 30 Si = 1.93 x δ 29 Si.

Additional data

(2)

(3)

Our DSi and δ 30 Si DSi data are compared with additional samples collected at the RaTS site.

Chlorophyll a (Chl a) is measured routinely by the British Antarctic Survey using chloroform/methanol extraction and fluorometry assays [START_REF] Clarke | Seasonal and interannual variability in temperature, chlorophyll and macronutrients in northern Marguerite Bay, Antarctica[END_REF]. Mixed Layer Depth (MLD) is calculated from Conductivity Temperature Depth profiles, following [START_REF] Barth | Mesoscale physical and bio-optical structure of the Antarctic Polar Front near 170 degrees W during austral spring[END_REF].

Dissolved aluminium (Al) concentrations were measured on trace metal clean samples using an automated Flow Injection Analytical System (FIA, [START_REF] Resing | Fluorometric Determination of Al in Seawater by Flow Injection Analysis with In-Line Preconcentration[END_REF] and have been reported previously [START_REF] Hendry | Deep ocean nutrients during the Last Glacial Maximum deduced from sponge silicon isotopic compositions[END_REF]. Samples for diatom species abundance were collected at the same site and the same depth as our samples. The species identification was carried scanning electron microscopy (SEM) [START_REF] Annett | Seasonal progression of diatom assemblages in surface waters[END_REF].

Results

Dynamics of DSi and δ 30 Si in Ryder Bay

Although the DSi concentrations in near-surface waters at the RaTS site decrease overall through each field season (84.3 to 70μM for 2004/2005 and 88.1 to 62.2μM for 2005/2006), the declines in concentration did not occur continuously, and were punctuated by pulses of increasing DSi concentration (Fig. 2 and Table 2). Both field seasons contained at least one clear episode of uninterrupted net DSi drawdown correlated with a net δ 30 Si DSi increase (grey box in Fig. 2) showing DSi removal due to uptake. This general pattern of phytoplankton growth matches well the RaTS chlorophyll profiles (Fig. 2; see also [START_REF] Clarke | Seasonal and interannual variability in temperature, chlorophyll and macronutrients in northern Marguerite Bay, Antarctica[END_REF]. δ 30 Si DSi behaviour during both seasons is largely opposite to the DSi concentration (Fig. 2 and [START_REF] Brzezinski | Silicon dynamics within an intense open-ocean diatom bloom in the Pacific sector of the Southern Ocean[END_REF][START_REF] Cardinal | Relevance of silicon isotopes to Si-nutrient utilization and Si-source assessment in Antarctic[END_REF][START_REF] De La Rocha | The silicon isotopic composition of surface waters in the Atlantic and Indian sectors of the Southern Ocean[END_REF]Fripiat et al., 2011b;[START_REF] Varela | Biological fractionation of silicon isotopes in Southern Ocean surface waters[END_REF].

Dynamics of Chlorophyll, MLD and Al

Chlorophyll concentrations of both seasons show the same pattern (Figure 2

Discussion

Results presented in this study elucidate the behaviour of Si isotopes in coastal Antarctic surface waters over the course of several months, during periods both of net nutrient drawdown and strong mixing and/or upwelling. Here, we focus on the seasonal difference in the isotopic composition of dissolved silica relative to shifts in the balance between inputs of silicic acid to the euphotic zone and rates of DSi removal for BSi production by diatoms.

The balance between oceanic mixing and nutrient uptake

The prevailing view of silicon isotopes in the upper ocean is that changes in DSi concentrations are roughly opposite to changes in its δ 30 Si DSi (i.e. the progressive decreasing of silicic acid concentrations is accompanied by an increase of its δ 30 Si DSi ). This is due to the discrimination against the heavier isotopes of silicon during the biological uptake of DSi that enriches the pool of DSi remaining in surface waters in the heavier isotopes [START_REF] De La Rocha | Fractionation of silicon isotopes by marine diatoms during biogenic silica formation[END_REF] as supported by previous field studies [START_REF] Cardinal | Relevance of silicon isotopes to Si-nutrient utilization and Si-source assessment in Antarctic[END_REF][START_REF] De La Rocha | The silicon isotopic composition of surface waters in the Atlantic and Indian sectors of the Southern Ocean[END_REF]Fripiat et al., 2011a;[START_REF] Varela | Biological fractionation of silicon isotopes in Southern Ocean surface waters[END_REF]. Modelling studies, however, have suggested that the situation may be more complicated in certain oceanographic settings. If there are times when notable removal of DSi is masked by a considerable input of DSi through mixing, there will be a characteristic shift in δ 30 Si BSi towards values that are roughly 1.1 ‰ lower than the δ 30 Si DSi mixing into the euphotic zone, rather than an increase in δ 30 Si DSi [START_REF] Coffineau | Exploring interacting influences on the silicon isotopic composition of the surface ocean: a case study from the Kerguelen Plateau[END_REF]. This would lead to times of the year, likely late in the growing season, where surface DSi concentrations remain low but δ 30 Si DSi is not elevated. This situation starts to establish itself in our data from early January 2005, a period when DSi concentrations are roughly constant but the δ 30 Si DSi decreased. The same pattern is more clearly defined in January 2006 (between the two DSi drawdown period) when DSi concentrations are steady, reflecting a balance between DSi inputs via mixing and DSi removal via biological uptake. In both cases, the isotopic composition is evolving towards the value of the underlying water, δ 30 Si DSi = 1.03‰ (see section 4.2). Furthermore, surface water δ 30 Si DSi values are influenced by subsurface inputs/mixing events, with lower values from isotopically light underlying waters coinciding with high dissolved Al concentrations during January 2006, which resulted from input via upwelling and/or mixing [START_REF] Hendry | Deep ocean nutrients during the Last Glacial Maximum deduced from sponge silicon isotopic compositions[END_REF], and/or deeper MLD. [START_REF] Venables | Wintertime controls on summer stratification and productivity at the western Antarctic Peninsula[END_REF] shows significant interannual variability in the levels of primary production, nutrient dynamics and physical properties of the RaTS site, associated with shifts in sea-ice dynamics and winter mixing influence upper ocean stratification, a key influence on phytoplankton growth. In contrast to the years sampled here, which were characterised by clear periods of nutrient depletion during the summer growth season, it would be expected that there would be minimal significant variability in surface δ 30 Si DSi values during years where there is low diatom production (Annett et al., this issue, submitted).

Quantifying silicon isotope fractionation in surface waters

The increase in δ 30 Si DSi that occurs when DSi concentrations are decreasing can be used to estimate the fractionation (ɛ) of silicon isotopes associated with DSi uptake (De la [START_REF] De La Rocha | A first look at the distribution of the stable isotopes of silicon in natural waters[END_REF][START_REF] Reynolds | Silicon isotope fractionation during nutrient utilization in the North Pacific[END_REF][START_REF] Varela | Biological fractionation of silicon isotopes in Southern Ocean surface waters[END_REF]. This can be achieved using simple models that assume

either closed or open system behaviour.

The closed system model (the Rayleigh distillation model) predicts the behaviour of Si isotopes in reactant (DSi) and product (i.e. BSi) in a system where one input of DSi occurs just prior to the bloom episode. δ 30 Si DSi evolves from the initial value (δ 30 Si DSi initial ) and may be calculated from ε multiplied by the natural log of f, the fraction of initial DSi remaining in solution:

( ) (4)
This model best describes the changes in δ 30 Si that occur over relatively short time scales, for example during a single phytoplankton bloom. In this model, fractionation, in terms of the per mil difference between product and reactant, is estimated from the slope of δ 30 Si DSi versus the natural log of DSi (Fig. 3; Equation 4; [START_REF] Cardinal | Relevance of silicon isotopes to Si-nutrient utilization and Si-source assessment in Antarctic[END_REF][START_REF] De La Rocha | A first look at the distribution of the stable isotopes of silicon in natural waters[END_REF][START_REF] Reynolds | Silicon isotope fractionation during nutrient utilization in the North Pacific[END_REF][START_REF] Varela | Biological fractionation of silicon isotopes in Southern Ocean surface waters[END_REF].

On the other hand, the open system model (continuous input model) considers a small but continuous input of DSi to the surface water that occurs at the same time as DSi is being removed for the production of BSi through the growing season. In this case, the δ 30 Si DSi evolves from the δ 30 Si DSi initial value and is calculated from ε multiplied by (1-f):

( f) (5)
This model is also only applicable to periods when DSi concentrations are decreasing over time (i.e., it is not a steady state model). This model is most appropriate in turbulent regimes or in areas where there is relatively uninhibited mixing from below [START_REF] Coffineau | Exploring interacting influences on the silicon isotopic composition of the surface ocean: a case study from the Kerguelen Plateau[END_REF]. In this case, fractionation is estimated by the slope of δ 30 Si DSi versus the ratio of the observed concentration of DSi to the initial concentration i.e. that at the beginning of the growing season (Fig. 3, Equation 5) [START_REF] De La Rocha | The silicon isotopic composition of surface waters in the Atlantic and Indian sectors of the Southern Ocean[END_REF][START_REF] Varela | Biological fractionation of silicon isotopes in Southern Ocean surface waters[END_REF]. As UCDW supplies the deeper levels of Marguerite Bay [START_REF] Martinson | Western Antarctic Peninsula physical oceanography and spatio-temporal variability[END_REF], the δ 30 Si DSi initial value used is from a sample of UCDW taken at 61°28 S, 56°42 W at a depth of 400 m with a dissolved silica concentration (DSi initial ) of 96 μM and δ 30 Si DSi initial of 1.03 ‰ [START_REF] Hendry | Deep ocean nutrients during the Last Glacial Maximum deduced from sponge silicon isotopic compositions[END_REF].

Both models have been used to estimate the fractionation required to explain the increase in δ 30 Si DSi during the summers of 2004/2005 and 2005/2006. During periods of strong mixing, the contribution of the underlying water masses to DSi or δ 30 Si DSi cannot be constrained. ɛ reflecting only the fractionation due to biological uptake (denoted by ɛ uptake ) can only be calculated during periods of net nutrient drawdown (i.e. when there is net DSi consumption and relatively low mixing); otherwise the resulting ɛ represents the biological, upwelling and mixing effect, and it is termed ɛ apparent here.

Figure 3 shows ɛ apparent , the results of modelling for the entire summers (2004/2005 and 2005/2006) and ɛ uptake for the periods of nutrient drawdown, and the calculated ɛ apparent , ɛ uptake are given in Table 3.

The calculated ɛ apparent values are lower relative to ɛ uptake particularly in 2004/2005 where ɛ apparent is equal to -1.20‰ (Standard Error, SE = 0.56) and -0.97‰ (SE = 0.45) for open and closed system, respectively, relative to -2.26‰ (SE = 0.54) and -1.93‰ (SE = 0.42) (Fig. 3). This is likely due to mixing supplying the euphotic zone with deep water enriched in DSi and lower in δ 30 Si DSi compared with the surface pool [START_REF] Coffineau | Exploring interacting influences on the silicon isotopic composition of the surface ocean: a case study from the Kerguelen Plateau[END_REF][START_REF] Reynolds | Silicon isotope fractionation during nutrient utilization in the North Pacific[END_REF]. Furthermore, the diatom assemblage is another parameter to take into consideration. Data from [START_REF] Annett | Seasonal progression of diatom assemblages in surface waters[END_REF] show that the diatom community during both years (Fig. 4 from Table 1 in [START_REF] Annett | Seasonal progression of diatom assemblages in surface waters[END_REF]). The ɛ uptake during 2004/2005 predominantly represents the fractionation of three different groups, Chaetoceros hyalochaeta, Fragilariopsis curta and Minidiscus chilensis while the ɛ apparent reflects a combination of water masses and a variety of species in the system.

In 2005/2006 the period of net DSi drawdown covers most of the sampling period, with a significant regression curve between DSi and δ 30 Si DSi (p < 0.05) but the standard errors are bigger than for the net DSi drawdown period. The offset between ɛ apparent and ɛ uptake in 2005/2006 is less than for the previous summer; ɛ apparent equals to -1.50‰ (SE = 0.34) and -1.10‰ (SE = 0.25) for open and closed system, compare to ɛ uptake that is -1.88‰ (SE = 0.19) and -1.33‰ (SE = 0.14), open and closed system respectively. This is also likely the result of a change in diatom community dominated this time by F. curta, C. hyalochaeta and Proboscia inermis.

Comparison with previous studies

As expected, fractionation values calculated from the two time-series in this study for only periods of net nutrient drawdown, are higher than previous published studies (see Table 3), due to the negligible influence of episodic inputs of DSi into the upper layers via mixing from below compare to the biological uptake. These input processes lead to incorrect estimation of the fractionation resulting from biological uptake in temporally limited "snapshot" studies contrasting with time-series where inputs can be more clearly identified. A study from the polar frontal zone of the Southern Ocean also revealed higher values of ɛ, implying that diatoms from Southern Ocean fractionate Si to a greater degree than diatoms from lower latitudes (Fripiat et al., 2011b). Other coastal areas, characterised as upwelling systems, show also higher ɛ values due to the dynamics of these systems making the identification of the initial water more difficult, which can influence the ɛ estimation [START_REF] Cao | Silicon isotope constraints on sources and utilization of silicic acid in the northern South China Sea[END_REF][START_REF] Ehlert | Factors controlling the silicon isotope distribution in waters and surface sediments of the Peruvian coastal upwelling[END_REF]. This is not the case of Ryder Bay, which is a dynamic system with UCDW as a well define DSi source. Furthermore, our results highlight that even at the same station and within a single growing season, the apparent fractionation factor may exhibit significant temporal variability because of changes in the extent of biological removal of DSi, nutrient source, siliceous species, and mixing events. Recent work in the Australian sector of the Southern Ocean suggest that the ratio of Si supply to uptake differs between Antarctic zones and can impact the fractionation of Si isotopes during BSi formation. For example, the fractionation factor calculated for the Subantarctic Zone (SAZ) was lower than for the Antarctic Zone due to a higher BSi dissolution:production ratio and higher Si supply:Si uptake ratio [START_REF] Closset | Seasonal variations, origin, and fate of settling diatoms in the Southern Ocean tracked by silicon isotope records in deep sediment traps[END_REF].

Finally, the results presented here show higher ɛ uptake than culture studies (Table 3). Cultures are isolated systems, whereas our study site is influenced by complex water mass mixing, even during periods of net nutrient drawdown, and cannot be described fully by a closed-system model.

Paleoceanographic studies using Si isotopes of BSi generally assume that the BSi exported from the surface ocean and accumulating in the sediments was produced during times of net nutrient drawdown and that the open or closed system models can be used to reconstruct the degree of nutrient removal from the δ 30 Si of the BSi. However, the time of net nutrient drawdown represents only a short period of the whole year, and as shown here may not even encompass the entire growing season. Shifts in the fraction of total annual export produced during bloom growth could strongly influence the δ 30 Si of BSi in marine sediments along with winter export, neither of which are considered. Thus, while high values of δ 30 Si BSi can indicate high levels of net nutrient removal, low values of δ 30 Si BSi could either reflect silicon limited growth (i.e. all DSi input being immediately converted to BSi and then exported) or low levels of net nutrient drawdown. Our work highlights the need for further investigation into δ 30 Si BSi systematics to enable its robust use as a proxy of nutrient use by diatoms in the past.

CONCLUSIONS

Silicon isotopes have been identified as a proxy for nutrient utilization by diatoms in the past and present surface layer of the ocean. Here, we demonstrate the importance of understanding the balance between the inputs and outputs of DSi into surface waters, and their impacts on Si isotope systematics. The uptake fractionation factor, associated with the formation of BSi by diatoms, can only be calculated during periods of net nutrient drawdown, characterised by a decline in DSi and an increase in δ 30 Si DSi . During other periods throughout the summer, where mixing and/or upwelling increase Si supply relative to nutrient uptake by diatoms, the δ 30 Si DSi will reflect a combination of biological fractionation and contributions from isotopically light underlying waters. Hence, the fractionation factor calculated only for the net drawdown period was greater than that calculated for the whole summer, and is likely to reflect more closely the true Si isotopic fractionation associated with BSi formation. However, results highlight that, even at the same station and within a single growing season, the apparent fractionation factor may exhibit significant temporal variability because of changes in the extent of biological removal of DSi, nutrient source, siliceous species, and mixing events.

This highlights the need for further investigation into δ 30 Si BSi systematics to enable its robust use as a

  ). Early in each season chlorophyll peaked at around 25 mg m -3 and then the concentration slowly decreased over the following weeks before rising to 35.6 and 27.9 mg m -3 for 2004/2005 and 2005/2006 respectively. MLD differed much more between the two seasons. 2004/2005 started with a deep mixed layer (to 50 m), and then the water column stratified (MLD approximately 2 m) until February, when mixing begin homogenising the upper layers. MLD reached 42 m by the end of March. In contrast, season 2005/2006 had a deeper MLD in the middle of the season (mid-February), but this only reached 28 m water depth. The rest of the season was comparatively more stratified, with MLD no greater than 10 m except close to the start of the autumn. Al concentrations, only available for 2005/2006, show a temporal progression mirrored to chlorophyll, with a small peak in early season (end of December 2005) and an increase to 27.13 nM in mid-summer (end of January).

  proxy of nutrient use by diatoms in the past. There are questions outstanding that require further investigation, including the extent of isotope fractionation during BSi formation, the δ 30 Si of DSi upwelling into the surface layer, the characterisation of the system (closed, open or non-bloom), and the fractionation that occurs during dissolution and diagenesis of the diatom silica.

Figure 1 :

 1 Figure 1: Location of the Rothera Research Station on Adelaide Island, West Antarctic Peninsula

Figure 2 :

 2 Figure 2: DSi concentration, δ 30 Si DSi (‰), chlorophyll a (Chl a), dissolved Aluminium (Al) and

Figure 3 :

 3 Figure 3: Calculated fractionation factors for both summers. A and C show ɛ uptake during 2004/2005

Figure 4 :

 4 Figure 4: Relative abundances of Diatoms species (%), data from Table1in[START_REF] Annett | Seasonal progression of diatom assemblages in surface waters[END_REF].

  and were immediately filtered through 0.6 μm polycarbonate (PCTE) filters and stored at room temperature in acid-cleaned (2N reagent grade hydrochloric acid) polyethylene (PE) or polypropylene (PP) bottles until analysis.The marine environment of the WAP is strongly influenced by the adjacent Antarctic Circumpolar

	Current (ACC), which delivers warm, nutrient-rich water onto the shelf in the form of Upper
	Circumpolar Deep Water (UCDW). Glacially-scoured canyons that dissect the shelf are especially
	efficacious conduits for the transport of this water, with Marguerite Trough being an important route
	enabling modified UCDW to penetrate near the coast in Marguerite Bay. UCDW fills the deep layers
	of Ryder Bay, having crossed a ~300 m deep sill from the northern part of Marguerite Bay.

Table 2

 2

	) with δ 30 Si DSi increasing as DSi

season 2004/2005 and 2005/2006, respectively. These temporally-resolved results from a single location agree broadly with results based on shorter-duration data that are collected at different latitudes, and thus at different levels of DSi removal

Table 1 :

 1 Silicon separation scheme for strong base ion exchange chromatography using AG© 1x8 100-200 mesh.

	Separation step	Matrix	Volume (mL)
	Rinse	Milli-Q	Full reservoir
	Preconditioning	NaOH	10.4
	Rinse	Milli-Q	15
	Sample Load	SiF 6	2-	(Variable volume)
	Matrix elution	Milli-Q	30
	Matrix elution	HCl + HF	20
	Matrix elution	HF (23mM)	5
	Matrix elution	HNO 3 + HF	10
	Silicon elution	HNO 3 + HF	10
	Rinse	Milli-Q	Full reservoir

Table 2 :

 2 Seawater DSi concentration and δ 30 Si of silicic acid in the Ryder Bay, in the Bellingshausen Sea, Pacific sector of the Southern Ocean. 1SD is the internal error from double analysis.

	Date	Samples	DSi (μM)	δ 30 Si (‰)	1s (SD)
	05 Dec 2004	RaTS 7	84.3	1.54	0.01
	08 Dec 2004	RaTS 1	84.8	1.55	0.03
	10 Dec 2004	RaTS 2	91.8	1.47	0.01
	13 Dec 2004	RaTS 4	79.4	1.75	0.04
	15 Dec 2004	RaTS 3	76.5	1.69	0.09
	20 Dec 2004	RaTS 5	76.5	1.73	0.2
	29 Dec 2004	RaTS 11	69.6	2.05	0.05
	31 Dec 2004	RaTS 12	74.6	1.71	0.06
	05 Jan 2005	RaTS 13	72.8	1.64	0.02
	07 Jan 2005	RaTS 14	74.1	1.56	0.01
	13 Jan 2005	RaTS 15	79.8	1.86	0.07
	28 Jan 2005	RaTS 27	74.1
	01 Feb 2005	RaTS 24	63.7	1.89	0.05
	12 Feb 2005	RaTS 16	72.5	1.43	0.12
	18 Feb 2005	RaTS 18	70.9	1.66	0.02
	28 Dec 2005	RaTS 31	88.1	1.54	0.03
	04 Jan 2006	RaTS 32	82.3	1.41	0.09
	06 Jan 2006	RaTS 33	74.1	1.59	0.03
	10 Jan 2006	RaTS 34	74.4	1.83	0.06
	13 Jan 2006	RaTS 35	71.6	1.71	0.05
	19 Jan 2006	RaTS 36	71.6	1.66	0.02

Table 3 :

 3 Comparison of fractionation factor values with previous studies.

  Table 1 in Annett et al (2010).

Acknowledgments

Sample collection was funded by Antarctic Funding Initiative AFI4/02 and analysis were supported by the Laboratory of Environmental Marin sciences (LEMAR, UMR 6539). The authors are grateful to E. Ponzevera and Y. Germain for their assistance during isotopic measurement and Samia Mantoura, Damien Carson, Andrew Miller, Paul Mann, the Base Commander and all staff at Rothera Research Station (BAS). We also thank P. Tréguer, S. Lalonde and N. Coffineau for their interesting comments and suggestions.