Foued Abroug
email: foued.abroug@enit.fr

Axel Monnier

Lionel Arnaud

Yannick Balcaen

Olivier Dalverny

High cycle fatigue strength of additively manufactured AISI 316L Stainless Steel parts joined by laser welding

Keywords: Additive manufacturing LPBF, Laser welding, Surface defect, High cycle fatigue. Graphical

The present paper deals with the high cycle fatigue behavior of 316L stainless steel parts, obtained either by rolling or by LPBF additive manufacturing process, and their assemblies by autogenous laser welding. The aim is to study the effects of this assembly process on the fatigue strength, assessed at a 10 6 cycles, of additively produced parts, compared to that of raw rolled products. An original campaign of high cycle fatigue tests based on seven batches of specimens, manufactured additively or cold rolled, one-pieced or assembled, raw or polished, is carried out with a positive load ratio (R= 0.1). A stress relieving heat treatment is applied to all specimens to reduce residual stress levels. Particular attention is paid to identifying the damage mechanisms associated with each batch. Preliminary results allowed an original conclusion that laser welding does not degrade the fatigue strength of additively produced parts. In addition, the fatigue behavior of the studied system depends essentially on the stress concentration generated on the surface or a few micrometers in the underlayer, mainly by the roughness of the LPBF produced parts combined with the lack of fusion (LoF) defects, and in a second order by the geometry of the laser welding channel. Furthermore, additively produced parts showed higher sensitivity to the presence of defects than rolled parts.

Metal additive manufacturing processes are rapidly evolving in modern industry. Laser Fusion of Powder Bed, commonly known as LPBF, is gaining more and more prominence in the production market, due to its ability to generate, from a 3D design, parts of high geometric complexity, not achievable by conventional techniques such as machining or forging, and in an almost finished state called "near net shape". This geometric freedom makes it possible, among other things, to create more efficient, lighter parts with more compact dimensions [START_REF] Benoist | A new method of design for additive manufacturing including machining constraints[END_REF] [START_REF] Joshi | 3D printing in aerospace and its long-term sustainability[END_REF].

However, despite the progress of the LPBF process, it lacks maturity in various aspects. Among the challenges faced by this technique are the presence of manufacturing defects, such as high surface roughness of the as-built printed part [3][4], as well as internal defects created at different distances from the surface [5][6]. These defects are often at the origin of a low fatigue strength of LPBF produced parts, compared to that obtained for parts issued from other processes [START_REF] Le | Interpretation of the fatigue anisotropy of additively manufactured TA6V alloys via a fracture mechanics approach[END_REF].

For example, Vayssette et al. [START_REF] Vayssette | Numerical modelling of surface roughness effect on the fatigue behavior of Ti-6Al-4V obtained by additive manufacturing[END_REF] showed a 60% decrease in fatigue strength of the LPBF TA6V specimens in the as-built state compared to hot rolling.

In addition to these defects, residual stresses reaching hundreds of MPa in tension or compression are generated within the printed part due to the thermal history of the LPBF process [START_REF] Wu | An experimental investigation into additive manufacturing-induced residual stresses in 316L stainless steel[END_REF]. The microstructure is also different from conventional materials, with pronounced anisotropy and columnar grains reaching a few millimeters in length in the building direction [START_REF] Debroy | Additive manufacturing of metallic components-process, structure and properties[END_REF]. All these aspects can define a different fatigue behavior for each configuration [START_REF] Le | Interpretation of the fatigue anisotropy of additively manufactured TA6V alloys via a fracture mechanics approach[END_REF].

Another challenge for the LPBF process is the limitation in terms of printable volume. The volume of parts that can be printed is limited by the dimensions of the building chamber, which is commonly a bit less than 300 mm x 300 mm x 300 mm, making large printed parts, such as one meter in size, accessible only to very few factories.

One of the solutions to limited volumes is hybrid manufacturing, which consists of assembling parts obtained either by additive manufacturing or by other conventional manufacturing processes.

The assembly of parts can be performed by different techniques such as brazing, welding (arc, laser, electron beam, etc.). However, for each assembly technique, the mechanical behavior must be apprehended both in quasi-static regime and in cyclic regime before the use of the assembled part.

Several studies have reported Laser Welding (LW), mainly in the case of rolled sheets and only a few in the case of additively manufactured parts [9][10]. The results showed that LW generates defects similar to those generated by LPBF process. First, LW results in an anisotropic microstructure at the weld zone [START_REF] Wu | On the fatigue performance of laser hybrid welded high Zn 7000 alloys for next generation railway components[END_REF]. Moreover, residual stresses in the welded zone vary drastically between tension and compression along the thickness of the welded part [START_REF] Jokisch | Laser welding of SLM-manufactured tubes made of IN625 and[END_REF]. Studies also show that the welding process results in a topographic change on the surface presenting a bump in the middle of the weld zone and undercuts or valleys on the sides [START_REF] Yang | Weldability, microstructure and mechanical properties of laser-welded selective laser melted 304 stainless steel joints[END_REF], as well as a population of porosity at the weld joint [START_REF] Jokisch | Laser welding of SLM-manufactured tubes made of IN625 and[END_REF]. These porosities reach sizes of around 0.2 mm and con form clusters of around 1 mm in length in some cases [START_REF] Wu | On the fatigue performance of laser hybrid welded high Zn 7000 alloys for next generation railway components[END_REF].

As for mechanical behavior, studies show that the welded joint is at the origin of failure and defines the monotonic tensile strength of the assembly [13][14]. The elongation is reduced due to the properties of the welded material. Other studies have addressed the question of the cyclic behavior of LW parts, compared to unassembled state, but mainly in the case of rolling [11][15]. These studies show the harmfulness of the porosity population and/or the weld seam, which reduces the fatigue strength by about 50-60% [11][15]. The question of the high cycle fatigue (HCF) strength of LW parts obtained by additive manufacturing is still little addressed in the literature [START_REF] Zhang | Study on the microstructure and fatigue behavior of a laser-welded Ni-based alloy manufactured by selective laser melting method[END_REF].

A recent study by Mokhtari et al. [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF] addressed the impact of microstructure and surface roughness on the weldability, resultant microstructure and mechanical properties of butt joint SS 316L parts obtained by LPBF or rolling and provided a set of convenient parameters for welding such parts. The results showed that the welding has a low impact on the microstructure of the LPBF samples, that the fractures are located on the fusion zone and that the ductility decreased by around 30% compared to the rolled metal.

The present study is an extension of the work of [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF] and aims to assess the high cycle fatigue behavior of SS 316L parts, obtained either by LPBF process or by rolling, and assembled by LW.

The main objective is to identify the impact that LW has on LPBF produced parts in terms of high cycle fatigue strength at 10 6 cycles, for both cases. The study also focuses on the understanding of the damage mechanisms leading to the fatigue failure for each configuration.

Material and experimental procedure

The 316L stainless steel

In this paper, the base material is cold rolled, annealed 316L stainless steel and additively manufactured plates, both of 2 mm of thickness. The chemical composition of both feedstock materials has already been studied and detailed in the previous work of [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF].

The printed plates are made using an LPBF 3D Systems ProX DMP 300 machine using a powder whose size ranges mainly between 5 and 38 µm. The D The microstructure analysis of rolled sheets and LPBF process plates has been extensively detailed in the work of [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF] and is recalled in Fig. 2. Let's recall that the rolled sheet's microstructure is mainly composed of equiaxial, recrystallized and non-recrystallized grains, whereas the additively manufactured material has grains which grow along the building direction and reach a few millimeters in length, due to the thermal history during the additive process. Regarding the LW for the two materials, it is carried out on a TruLaser Cell 3000 machine as detailed in [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF]. Welding parameters are recalled in Table 2. The same set of parameters is used for rolled sheets and additively produced parts. The welded zone has an hourglass shape (see Fig. 3)

for the rolled sheet and the LPBF produced plate, with a larger upper and lower areas for the rolled sheet. This difference was attributed to the surface roughness effect on absorptivity, in addition to slight difference between chemical composition and homogeneity of feedstock material in the case of the LPBF plate [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF]. The width of the fusion zone for both materials is however the same at the center of the specimen. Fig. 3 also shows the presence of porosity at the weld joint for rolled sheets and additively produced plates.

Fig. 4 shows scans of the surface topography for the rolled sheet and printed plate after LW.

The scans are performed via a Keyence VHX-6000 numerical microscope. Fig. 4-a and Fig. 4-c show fairly homogeneous reinforcements with a convex shape for both rolled and AMed parts, It can be seen that the rolled sample still has a convex shape at the welding zone but also irregular undercuts, or valleys. These undercuts, with a depth between 100 µm and 200 µm, can be at the origin of stress concentration and possibly affect the fatigue strength. As for the LPBF sample, a concave shape is observable with a channel of 100-150 µm in depth which would also generate stress concentration and possibly affect the fatigue strength. As detailed in [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF], such difference in geometry is common in the literature [START_REF] Matilainen | Weldability of additive manufactured stainless steel[END_REF] and is due to laser-matter interactions and to the roughness and hence absorptivity difference between AMed and rolled samples.

Monotonic tensile tests were carried out by [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF] and the results are recalled in Table 3. The results showed similar behavior for the LPBF process samples before and after LW, however the elongation is reduced after welding and reaches 42%. For the rolled samples, the welding slightly enhanced the Yield stress but also reduced the elongation, which reaches 56%.

The geometry of the fatigue test specimen is designed according to the ISO1099 standard [START_REF]Metallic materials -Fatigue testing -Axial force-controlled method[END_REF] and is presented in Fig. 5, with a thickness of 2 mm. A post-processing stress relieving heat treatment is applied on all printed and/or welded specimens. It consists of a 300 • C for 6 hours followed by air cooling. According to [START_REF] Salman | Effect of Heat Treatment on Microstructure and Mechanical Properties of 316L Steel Synthesized by Selective Laser Melting[END_REF][20], it ensures no microstructural change during the Table 3: Monotonic properties of the SS 316L [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF].

LPBF ref LPBF weld Rolled ref Rolled weld

Yield stress (MPa)

423±5 423±2 261±19 284±4 Strength (MPa) 568±5 568±2 602±2 598±3 Elongation (%) 51±1 42±14 73±6 56±3
process.

For the non welded solid plates, the specimen geometry is shaped via a high-speed machining process (See Fig. 6 a and b). The welded specimens however are laser cut, after plates are laser mm mm welded, on the same machine (see Fig. 6-c). Then, for all specimens, welded or not, polished or as-built, a polishing was systematically applied along their thickness and on the edges, to avoid any surface roughness induced crack initiation. Hardness measurements were also conducted in cross section along the length and thickness of both materials, after welding and Heat Treatment (HT), and detailed in [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF]. A summary of the results is recalled in Table .4. The LPBF process Base Metal (BM) has higher hardness values than that of the rolled sheet at its BM. However, at the Heat Affected Zone (HAZ) and the Melting Zone (MZ), the hardness values are similar for both rolled and LPBF process batches, since the materials have undergone the same welding treatment. These measurements raise the question of how would the welded LPBF process parts react under fatigue, and will there be competition between crack initiation at the weld seam where the hardness is lowest, or at the BM due to the high roughness levels and the potential manufacturing defects. This question will be answered further in the text. • Frequency : f = 25 Hz.

• Ambient temperature and pressure, in ambient air.

• Load R-ratio : R = 0.1.

• Number of cycles : N = 10 6 cycles.

• Loading amplitude step S σ a = 20 MPa.

At the end of the fatigue tests, an equivalent fatigue stress is calculated for each specimen, using Basquin's law and Miner's law [START_REF] Miner | Cumulative damage in fatigue[END_REF], taking into account the damage accumulated during the different loading steps (Eq. 1-3). A mean fatigue strength per batch is then determined.

σ a = CN -1/b (1) D = m i=1 D i = m i=1 n i N i 1 (2) D = m i=1 n i ( σ a C ) b 1 (3)
With n i : number of cycles for each step, σ a the stress amplitude, D the accumulated damage which equals 1 when the specimen breaks, b and C are material parameters.

In this study, 7 batches of specimens, with 3 specimens per batch, are prepared and tested under cyclic loading. These batches split in 2 base metal types, cold rolled or LPBF produced. Half of the batches is of solid specimens and the other half is of LW specimens. Half of the batches is polished to remove LPBF process surface roughness or welding surface geometry and the other half is tested in As-Built and/or as welded surface conditions. The details for the test campaign are

shown in Table 5. any crack initiation in these areas. In addition, since the welding operation alters the specimens thickness at the weld seam (see Fig. 3), the lowest value of the thickness for each specimen is considered for the fatigue tests.

Results and analysis

Fatigue test results

This section presents the results of the fatigue tests carried out in terms of the stress amplitude σ a . As presented in Table 6, all the fracture sites considered in the following are located at the gauge length of the specimens. Almost no crack initiation occurred at the edge of the specimens.

The two specimens where crack initiation occurred at the edge or away from the gauge length are considered invalid (see Table 6). The fatigue stress amplitude of each batch is shown in Table 6 and in Fig. 7. Based on these results, several conclusions are drawn.

Firstly, the fatigue strength of the reference material in the form of a non welded rolled sheet (RP) is of 224 MPa. Second, the fatigue stress amplitude of the rolled and welded batches, in the raw state RW and after polishing RWP, are similar and are of the order of 135 MPa. This allows to conclude that LW degrades the fatigue strength of 316L rolled sheets by approximately 40%.

Then, the additively manufactured and polished specimens, whether welded AMWP or non welded AMP, have a fatigue strength of 130 MPa, and therefore also a reduction of 42% compared to the RP reference batch.

Subsequently, the batches of additively manufactured specimens and in the raw state, with and without LW, AMAB and AMW, exhibit the lowest fatigue strength with a stress amplitude of 95

MPa for the first and 88 MPa for the second, which corresponds to approximately 30% of reduction compared to the additively manufactured and polished batch AMP and 60% of total reduction compared to the reference batch RP. This decrease is clearly linked to the high surface roughness generated by the additive manufacturing process. The welded and the non welded batches have the same fatigue strength as is the case for the polished batches AMP and AMWP. An important result emerges from these last two observations ; LW does not impact the fatigue strength of additively manufactured batches, particularly in the as-built condition. In fact, crack initiation for the AMW batch occurs far from the weld joint, while remaining in the gauge length of the specimens (see Table 6). This result is interesting as it allows to conclude that it could be possible to weld two LPBF process parts without degrading the global fatigue resistance of the assembly. However, after polishing, a competition between crack initiation at the weld joint or far from it occurs. This will be further addressed in the next section.

In order to better understand these levels of fatigue strength, SEM observations are carried on the fracture surface of the different specimens. The damage mechanisms of each batch are thus identified.

Damage mechanisms identification

For the first batch RP, microscopic observations allowed to identify the presence of multiples crack initiation sites (see Fig. 8). These crack initiations are controlled by the plasticity and are always located at the surface of the specimens. No crack initiation on the sub surface or at the bulk is observed. No defects are identified at the crack initiation sites, except small tears and defects that do not exceed 10 µm in size (see Fig. 9). For the second batch which is welded RW, SEM observations allowed to identify crack ini- tiation at the bottom of the valley of the weld channel (see Fig. 10). This is due to the stress concentration generated at the undercuts at the junction between the welded zone and the BM (see Fig. 4). Also, the presence of porosity is identified at the fracture facies, however, no crack initiation occurred at the pores. This can be explained by the fact that the SS 316L is one of the ductile materials for which the HCF initiation of cracks occurs at the surface [23][24]. In addition, the geometry of the weld channel generates higher stress concentrations than those generated by the porosities. This is validated via a FE calculation in 2D domain of 10 mm x 2 mm geometry, in the elastic regime as presented in Fig. 11. The calculation is carried out using Abaqus software using triangular elements with six nodes and quadratic interpolation function. A convergence study is carried out on a model representing a hole in a plate to identify a suitable mesh size, which varies from 0.01 mm to 0.2 mm. As for the boundary conditions, the simulated domain is under uniform tension loading (Displacement Ux = 0 along the line [AB] ; Displacement Uy = 0 at the point (A) ; A uniform tensile pressure function is applied along the line [CD]). The geometry of the weld channel is reproduced based on the micrography shown in Fig. 11-a. A continuity of the mesh and therefore of the material between the different zones is considered. The material's behavior law used in the model is isotropic linear elastic whether in the BM, HAZ or MZ zone. The gradient of property between the different zones is not modelled. The variation of microstructure as well as its orientation and the anisotropy detailed in [START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF] is not taken into account. The porosity, simulated by a circular defect, is brought closer to the extreme surface to accentuate its impact.

Nonetheless, the bottom of the weld channel has a much higher stress concentration than that at the porosity. Fig. 11 also shows the stress concentration based on normal stress along the loading direction, which is also highest at the bottom of the welding seam. This result allows to explain the crack initiation at this region, as observed on the SEM analysis. For the third batch, rolled, welded and polished RWP, the polishing operation aimed to remove the geometric shape of the weld bead, in order to identify the impact of the microstructural change induced by LW on the fatigue resistance, compared to the RP reference batch as well as the RW batch. Unfortunately, the defects generated on the sides of the weld beads reached depths of between 100 and 150 µm. The polishing operation did not succeed in removing them completely without the risk of significantly reducing the specimen's thickness and altering fatigue tests results. As a result, the same crack initiation mechanism as well as the same fatigue strength as the previous batch, RW, is found (see Fig. 12 and Table 6). With this result, the question remains open on what is the sole effect of the microstructural change, if the surfaces were smooth for RWP state, on the fatigue behavior compared to the RP and the RW states. More fatigue tests with smooth specimens are required, which could not be achieved in this study. However, it would be expected for such state to exhibit a competition between crack initiation in the BM, where the hardness is lower than in the MZ (see Table .4) but more homogeneous microstructure, and in the MZ where the grain size is bigger than in the BM, with interdendritic ferrite structures and where pores are likely to appear due to the welding process. In both cases, if no or small defects are detected at the crack initiation site (around 10 µm), it would be expected a better fatigue strength than the RW batch since large defects are removed. The expected fatigue strength would be similar to or little lower than the RP batch. This assumption is based on the fact that the samples present a microstructural discontinuity and a lower elongation value at the welding zone (see Table .3). For the additively manufactured specimens, in the as-built state AMAB, the crack initiation occurs from a single site for each specimen. Crack initiation is located at the surface of the specimens which exhibit high roughness levels. In addition, at the crack initiation sites, lack of fusion (LoF) defects are identified as shown in Fig. 13. In fact, considering a case where the sample shown in Fig. 13 has been polished, along the white dotted line in Fig. 13-c, the surface roughness would be removed but the LoF defect will persist. This is the case of the following batch, additively manufactured and polished AMP (see Fig. 14). For this batch, the analysis of fracture facies shows the presence of a LoF defect at the crack initiation site, as shown in Fig. 14. For the additively manufactured, raw and welded batch AMW, the crack initiation occurs away from the weld bead. Similarly to the AMAB batch, crack initiation is located in areas of high roughness. LoF defects are also identified at the crack initiation sites as shown in Fig. 15. This allows to conclude that LW has no significant effect on the fatigue strength of the LPBF process plates in the as-built state. Thus, despite the lower hardness of the MZ compared to the rest of the gauge length of the specimen, the crack systematically initiates in the as-built BM due to the high stress concentration generated by the surface roughness and combined with the LoF defects. The stress concentration due to the defect therefore has a higher effect than the microstructural effect in this case.

As for the last additively manufactured batch, welded and polished AMWP (see Fig. 16), the analysis of fracture surfaces shows a competition between crack initiation from a LoF defect and crack initiation at the bottom of the weld channel (see Fig. 16). For the two specimens tested in this batch, crack initiation for the first sample occurred from a LoF defect, as shown in Fig. 16-a.

However, the second sample shown in Fig. 16-b, although polished, has a weld seam undercut that generates the crack responsible for its failure. However, the specimen with a LoF at the crack initiation site had a lower estimated fatigue strength than that cracked at the weld seam (see Table Some conclusions can be drawn from these observations. Firstly, for the different studied batches, fatigue crack initiation is a surface phenomenon. No internal crack initiation occurred.

This result is in agreement with results of the literature [23] [25]. Secondly, in decreasing order of severity, the stress concentration generated due to surface roughness, combined with the LoF defects plays the major role, then the sole LoF effect and finally the undercuts at the sides of the welding seams impact the fatigue resistance of the SS 316L. However, in the absence of the surface roughness, a competition between the LoF defects and the welding channel defects appears in the case of the AMWP batch.

Damage model

Fatigue test results for all batches are plotted in a bi-logarithmic Kitagawa-Takahashi (KT)

diagram [START_REF] Kitagawa | Applicability of fracture mechanics to very small cracks[END_REF], where the fatigue stress amplitude σ a is plotted against the square root of defect's projected area in a perpendicular surface to the loading direction √ area (see Fig. 17). The area of the defects is measured either directly in the case of singular defects, at the initiation sites using the SEM observations (i.e. Fig. 15 and Fig. 16), or using Murakami's approximation ( √ area = √ 10 * a)[27] in the case of long and shallow defects (i.e. Fig. 10). Fig. 17 shows a classic Kitagawa-Takahashi trend with two distinct regions. First, a plateau for which the fatigue strength is not affected by the presence of defects smaller than a threshold size. Beyond this critical size, a second zone where the fatigue strength is greatly affected by the presence of the defects. Note that the batches obtained from a rolled sheet are presented with squares and those obtained via additive manufacturing are presented with triangles.

At the first glance at Fig. 17, a high scatter in the results could be observed, at 120 MPa for example, where the defect sizes range from 55 µm to 500 µm, however, these values belong to two distinct sets of points, which correspond to two specific damage mechanisms, but more importantly to two manufacturing processes (rolling or manufacturing). In other words, the graph shows a separate area for the additively manufactured specimens and another for the rolled specimens. A trend is observed where the slope of the KT diagram is of -1/2 for the LPBF process parts, which corresponds to the Linear Elastic Fracture Mechanics (LEFM) model as expressed in Eq. 4. As for the rolled parts, the slope is of -1/6 which follows Murakami's model as expressed in Eq. 5. The diagram also allows to identify a threshold size of defects of around 10-30 µm. Furthermore, in Fig. 18, results of studies from the literature, for both rolled [START_REF] Guerchais | Influence of the microstructure and voids on the high-cycle fatigue strength of 316L stainless steel under multiaxial loading[END_REF] and LPBF process [START_REF] Andreau | A competition between the contour and hatching zones on the high cycle fatigue behaviour of a 316L stainless steel : Analyzed using X-ray computed tomography[END_REF] materials, are added to the diagram and compared with our results. Note that the results of the study of Guerchais et al. [START_REF] Guerchais | Influence of the microstructure and voids on the high-cycle fatigue strength of 316L stainless steel under multiaxial loading[END_REF], conducted using the R-1 ratio, are adapted to the R0.1 ratio using Gerber's relation. The different results show good agreement for both rolled and LPBF process part and allow to confirm, among other things, the difference between the fatigue strength levels and trends. Most of the results of Andreau's study [START_REF] Andreau | A competition between the contour and hatching zones on the high cycle fatigue behaviour of a 316L stainless steel : Analyzed using X-ray computed tomography[END_REF] are located, in the KT diagram, between 10 µm and 60 µm, which corresponds to the zone of competition between the effects of defects and microstructure on the fatigue strength. Andreau's results show that in the absence of defects, the LPBF process material exhibits a better fatigue strength than the material (fatigue strength of around 254 MPa as shown in Fig. 18). They show the of improving material health by optimizing the printing parameters [START_REF] Andreau | A competition between the contour and hatching zones on the high cycle fatigue behaviour of a 316L stainless steel : Analyzed using X-ray computed tomography[END_REF]. The present results show that beyond the competition zone between defects and microstructure (zone beyond 60 µm), the decrease in fatigue strength in the presence of defects rather follows a slope of -1/2 for LPBF process parts, against a slope of -1/6 for rolled sheets. This allows to conclude that the LPBF process parts are more sensitive to the presence of defects than the rolled parts. This could be explained by the microstructural difference between the two materials. As shown in Table .3, the LPBF process material exhibits lower elongation than the rolled material, with or without welding, which could be at the origin of this slope difference. The microstructural and elongation differences allow also to explain the scatter issue addressed above.

∆σ a = ∆K th Y √ πa (4)
In addition, Fig. 18 shows that our specimens have bigger defect sizes than the specimens used by Andreau et al., in the case of the additively manufactured parts, which results in a lower fatigue strength for our specimens. Manufacturing parameters vary for the specimens in [START_REF] Andreau | A competition between the contour and hatching zones on the high cycle fatigue behaviour of a 316L stainless steel : Analyzed using X-ray computed tomography[END_REF] and our specimens, which could be at the origin of this difference. However, the specimens used in [START_REF] Andreau | A competition between the contour and hatching zones on the high cycle fatigue behaviour of a 316L stainless steel : Analyzed using X-ray computed tomography[END_REF] have around half the section and around half the perimeter of the specimens used in the present study, which could result in a scale effect due to the lower probability of creating large defects and hence a better fatigue strength. However, for the rolled parts, the fatigue strength obtained in our study and that obtained by Guerchais et al. [START_REF] Guerchais | Influence of the microstructure and voids on the high-cycle fatigue strength of 316L stainless steel under multiaxial loading[END_REF] are close despite the fact that the specimens used in [START_REF] Guerchais | Influence of the microstructure and voids on the high-cycle fatigue strength of 316L stainless steel under multiaxial loading[END_REF] are much bigger, in terms of section and perimeter, than the specimens used in this study.

This could suggest that the LPBF process parts exhibit a higher sensitivity to the scale effect than that of the rolled parts.

Another interesting result is the case of the AMWP batch where two specimens shows different damage mechanisms and different fatigue strengths. Fig. 17 shows that the smaller √ area caused more effect in the fatigue strength. This could be explained by the stress concentration generated at the LoF defects which is often higher than that generated at the weld seam due to their shape (see Fig. 16-a). The AMWP specimen that breaks from the weld seam is located among the rolled batches in Fig. 17. This is due to the fact that the initiation occurs in the MZ, which has the same mechanical characteristics and hardness for both LPBF process and rolled batches.

On the same graph in Fig. 17 and Fig. 18 are presented the fatigue predictions via Murakami's model in red line (Eq. 5) and LEFM model in green and black (Eq.6).

σ a = 1.43(H v + 120) √ area

1/6 1 -R 2 α ( 5
)
with α = 0.3 as identified from experimental results [27].

For the LEFM model, Murakami's approximation for the stress intensity factor is applied, assuming that the cracks propagate in mode I. The fatigue stress amplitude is hence expressed, based on the LEFM, as follows :

K = 0.65σ π √ area ⇒ σ a = ∆K 1.3 π √ area (6)
Murakami's model is applied using the hardness value for the rolled welded material, of around 197 Hv (see Table

Conclusion and prospects

The main conclusions of this study can be presented as follows :

-Both LPBF process parts and rolled parts show good weldability with low rate of defects or porosity at the welded zone, However, the weld seam shows undercuts along the width of the specimens.

-LW reduces the fatigue strength of the rolled batches, which is mainly due to the stress concentration at the bottom of the welding channels.

-Compared to the rolled polished 316L (RP), the HCF strength of 316L LPBF process parts decreases by 60% in the as-built state (AMAB and AMW) and by 42% after polishing (AMP and AMWP).

-For welded LPBF process batches, there is no of the welding on the fatigue resistance, it is rather the roughness and defects at the surface that drive the fatigue behavior. It is hence possible to weld two additively manufactured parts without degrading the global fatigue strength of the assembly.

-The LPBF process parts exhibit a steeper slope on the KT diagram than that of the rolled parts and are hence more sensitive to defects. The microstructural difference between the rolled and the LPBF process materials could be at the origin of this variation.

-The obtained results are in agreement with results from the literature for both LPBF process and rolled parts. For the rolled parts, the results in presence of welding defects are in agreements with results obtained in presence of artificial defects from [START_REF] Guerchais | Influence of the microstructure and voids on the high-cycle fatigue strength of 316L stainless steel under multiaxial loading[END_REF].

-The obtained fatigue results are presented in the format of the Kitagawa-Takahashi diagram, and the size of the critical defect was identified in the order of 10-30 µm.

This study shows the possibility of assembling LPBF process parts without risking lowering the fatigue strength of the assembly. However, in the as-built state or even after polishing, the fatigue strength of the 316L LPBF process parts is lower than that of the rolled parts, mainly due to the manufacturing defects of LPBF process, such as surface roughness and LoF defects. As prospects of this study, reducing the size and population of LPBF process defects, using postprocessing or in-situ techniques will be investigated. The sole impact of the microstructure and the residual stresses will also be studied.

Nomenclature

  ∆K th threshold stress intensity factor range ∆σ a stress range ∆σ a = 2σ a σ a stress amplitude √ area square root of the defect's area projected onto a plane perpendicular to the applied stress a defect's depth AMAB Additively Manufactured As-Built AMP Additively Manufactured Polished AMW Additively Manufactured Welded AMWP Additively Manufactured Welded Polished

Figure 1 :

 1 Figure 1: Produced parts with supported specimens in the background.

Figure 2 :

 2 Figure 2: Microstructure of the SS 316L obtained by optical microscopy for a) rolled sheet part and b) additively produced material showing melt pool traces on the left and grain size and orientation on the right.

Fig. 4 -

 4 Fig.4-b and Fig.4-d show surface scans of the back of the rolled and AMed and welded samples.

Figure 3 :

 3 Figure 3: Optical microscopy observations of the welded zone for a) rolled sheet parts and b) LPBF parts [17].

Figure 4 :

 4 Figure 4: 3D surface scans of the welded zone for a) top and b) bottom of rolled sheet parts, c top and d) bottom of LPBF parts.

Figure 5 :

 5 Figure 5: Fatigue test specimen geometry, all values are in mm.

Figure 6 :

 6 Figure 6: Final specimens extracted from the a) and b) whole LPBF parts and c) welded parts. For c), two LPBF plates are welded and specimens are extracted by laser cutting.

  The first batch corresponds to the Rolled and Polished (RP) batch, used as a reference condition. The second batch corresponds to the Rolled and Welded (RW) state. The aim of this batch is to assess the impact of surface and internal defects (porosity), as well as the microstructure change on the fatigue strength. The third batch, RWP, offers a polished surface finish compared to the RW batch and aims to erase the surface geometry defects and to understand the influence of microstructure change and/or the porosity on the fatigue strength, compared to the first two batches.The fourth batch corresponds to the Additively Manufactured As-Built samples (AMAB). It represents the reference batch for the LPBF process and is compared to the RP batch in order to identify the difference in fatigue strength between rolling and additive manufacturing. The fifth batch consists of Additively Manufactured Polished samples (AMP), and allows to observe the influence of roughness compared to the AMAB batch. The sixth batch consists of Additively Manufactured Welded samples (AMW) and the seventh batch is for Additively Manufactured Welded and afterwards Polished samples (AMWP). These two batches allow, compared to the AMAB and the AMP batches, to identify the impact of the LW on the fatigue strength. The microstructural changes as well as the surface and internal defects change by the LW are assessed via these two batches. Let's recall that all samples are polished at the edges and along the side walls to avoid

Figure 7 :

 7 Figure 7: Average fatigue strength and the associated extent for each batch.

Figure 8 :

 8 Figure 8: Fractography analysis of the specimen 1 of the RP batch : a) multiple cracks identified and b) a zoomed view on the crack propagation area.

Figure 9 :

 9 Figure 9: Fractography analysis of the specimen 2 of the RP batch : a) defect at the crack initiation site and b) a zoomed view.

Figure 10 :

 10 Figure 10: Fractography analysis of the specimen 1 of the RW batch : a) crack initiation site and b) and c) zoomed views on the initiation site.

Figure 11 :

 11 Figure 11: a) Geometry of the weld seam, b) 2D geometry, representative of (a) used for FE simulation, c) Mises stress distribution, d) zoom on the maximum stressed area, e) Normal stress distribution along the loading direction and f) zoom on the maximum stressed area. The maximum stress concentration is located at the bottom of the weld seam.

Figure 12 :

 12 Figure 12: Fractography analysis of the specimen 1 of the RWP batch : a) crack initiation site and b) and c) zoomed views.

Figure 13 :

 13 Figure 13: Fractography analysis of the specimen 2 of the AMAB batch : a) crack initiation site and b) and c) zoomed views.

Figure 14 :

 14 Figure 14: Fractography analysis of the specimen 1 of the AMP batch : a) crack initiation site and b) and c) zoomed views.

  .

  6).

Figure 15 :

 15 Figure 15: Fractography analysis of the specimen 1 of the AMW batch : a) crack initiation site and b) and c) zoomed views.

Figure 16 :

 16 Figure 16: Fractography analysis of the specimens of the AMWP batch : a) crack initiation at a LoF defect and b) crack initiation at a weld seam undercut.

Figure 17 :

 17 Figure 17: KT diagram showing the stress amplitude versus the square root of the defect's area.

Figure 18 :

 18 Figure 18: KT diagram showing a comparison between our results and the literature [25] [28].

  [START_REF] Vayssette | Numerical modelling of surface roughness effect on the fatigue behavior of Ti-6Al-4V obtained by additive manufacturing[END_REF], whereas the LEFM model is applied using two different values of ∆K th of 1.9 MPa. √ m and 3.7 MPa. √ m, obtained via the least square method based on the experimental results, for the LPBF process and the rolled parts respectively. The crack closure phenomenon is neglected in this study. It can be seen on the KT diagram that Murakami's model and the LEFM model successfully describe the observed fatigue behavior for the rolled and LPBF process materials, respectively.

Table 1 :

 1 LPBF used parameters

	10 , D 50 and D 90 of the powder

Table 2 :

 2 LW parameters[START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF].

Table 4 :

 4 Hardness properties of the SS 316L at the rolled and LPBF states[START_REF] Mokhtari | Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes[END_REF].

	Hardness (HV1)	238±6	197±5	166±6	190±6

LPBF base metal LPBF welded zone Rolled base metal Rolled welded zone

2.2. Experimental fatigue procedure

All fatigue tests are carried out on a servo-hydraulic Instron 8801 machine, using the Locati method as detailed in the work of Maxwell an Nicholas

[START_REF] Maxwell | A rapid method for generation of a Haigh diagram for high cycle fatigue[END_REF]

, with 3 specimens per batch. The following conditions are applied :

Table 5 :

 5 Summary of the different surface state batches for fatigue testing.

	Batch	Process	LW	Surface state	Heat	Topography
	notation				treatment
	RP	Rolling	No	Manual polishing	No
	RW	Rolling	Yes	Raw	Yes
	RWP	Rolling	Yes	Manual polishing	Yes
	AMAB	LPBF	No	As built	Yes
	AMP	LPBF	No	Manual polishing	Yes
	AMW	LPBF	Yes	Raw	Yes
	AMWP	LPBF	Yes	Manual polishing	Yes

Table 6 :

 6 Fatigue tests results for the different batches.

	Batch	Loading at failure σ a (MPa)	Step N •	N f (x10 5 )	Estimated fatigue strength (MPa)	Topography	Mean fatigue strength/ batch (MPa)
		235	6	2.32	234
	RP	215	1	9.79	214		224
					NV
		160	4	2.33	152
	RW	140	2	3	131		135
		140	2	4.65	122
		120	2	6.41	118
	RWP	160	4	6.44	161		136
		140	3	2.42	131
		100	2	3.54	92
	AMAB	100	2	8.5	101		95
		100	2	3.16	91
		140	4	7.7	140
	AMP				NV		130
		120	2	8.21	120
		100	2	3.29	92
	AMW	100	2	2.87	90		88
		100	2	0.6	83
		120	3	9.34	121
	AMWP				NV		130
		140	3	6.31	138

NV : Non valid test because of cracking at the edge of the specimen

Declarations


Stuart J Elliott
email: stuart.elliott@liverpool.ac.uk

Quentin Stern

Olivier Cala

Sami Jannin

Protonation Tuned Dipolar Order Mediated 1 H® 13 C Cross-Polarization for Dissolution-Dynamic Nuclear Polarization Experiments

Keywords: NMR, Hyperpolarization, DNP, dDNP, CP, dCP, dipolar order, Protonation

A strategy of dipolar order mediated nuclear spin polarization transfer has recently been combined with dissolution-dynamic nuclear polarization (dDNP) and improved by employing optimized shaped radiofrequency pulses and suitable molecular modifications. In the context of dDNP experiments, this offers a promising means of transferring polarization from high-gamma 1 H spins to insensitive 13 C spins with lower peak power and lower energy compared with state-of-the-art cross-polarization schemes. The role of local molecular groups and the glassing matrix protonation level are both postulated to play a key role in the polarization transfer pathway via an intermediary reservoir of dipolar spin order. To gain appreciation of the mechanisms involved in the dipolar order mediated polarization transfer under dDNP conditions, we investigate herein the influence of the pivotal characteristics of the sample makeup: (i) revising the protonation level for the constituents of the DNP glass; and (ii) utilizing deuterated molecular derivatives. Experimental demonstrations are presented for the case of [1-13 C]sodium acetate. We find that the proton sample molarity has a large impact on both the optimal parameters and the performance of the dipolar order mediated cross-polarization sequence, with the 13 C signal build-up time drastically shortened in the case of high solvent protonation levels. In the case of a deuterated molecular derivative, we observe that the nearby 2 H substituted methyl group is deleterious to the 1 H® 13 C transfer phenomenon (particularly at low levels of sample protonation). Overall, increased solvent protonation makes the dipolar order governed polarization transfer significantly faster and more efficient. This study sheds light on the influential sample formulation traits which govern the dipolar order-controlled transfer of polarization and indicates that the polarization transfer efficiencies of deuterated molecules can be boosted and reach high performances simply by adequate solvent protonation.

Introduction

Traditional nuclear magnetic resonance (NMR) experiments generally engender weak signal outputs due to the low intrinsic sensitivity of nuclear spin ensembles. This limiting factor can be overcome by employing hyperpolarization methodologies such as dissolution-dynamic nuclear polarization (dDNP) [START_REF] Ardenkjaer-Larsen | Proc. Natl. Acad. Sci[END_REF]. This versatile technique has convincingly become a routinely and widely employed approach to boost the detectable polarization from a number of molecules, e.g., such as those of [1-13 C]pyruvate, which is relevant to various far-reaching applications in clinical studies performed on human patients [START_REF] Nelson | [END_REF][3][START_REF] Gallagher | Proc. Natl. Acad. Sci[END_REF], by up to four orders of magnitude.

dDNP yields highly polarized solutions by: (i) formulating the dDNP sample as a glassy matrix doped with suitable paramagnetic polarizing agents (PAs); (ii) freezing the dDNPcompatible sample at low-pressure liquid helium temperatures and moderate magnetic fields; (iii) irradiating the sample mixture with microwaves; (iv) dissolving the sample with a jet of superheated solvent; and (v) transferring the sample to a liquid-state NMR spectrometer for signal detection [START_REF] Elliott | [END_REF]. Stage (iii) relies on the transfer of spin polarization from highly polarized electron spins to the weakly polarized nuclear spins of interest. For dilute low-𝛾 nuclear spins at low temperatures, the dDNP process typically suffers from excessively long polarization build-up time constants tDNP sometimes exceeding an hour [6].

Employing radiofrequency (rf) pulse sequences which take advantage of the polarization of sensitive nuclear spins such as protons, which polarize rapidly under dDNP conditions (typ. 1-3 minutes build-up time constant at temperatures of ~1.0-1.6 K in superfluid helium) [7], can boost the rate of 13 C polarization build-ups (by a factor of up to 40) [8][9][10]. One such sequence is cross-polarization (CP) [11][12][13][14][15], which efficiently transfers 1 H polarization to 13 C spins in the case that the stringent Hartmann-Hahn matching condition [11], i.e., high B1-field matching (typ. > 15 kHz to cover the broad 1 H NMR linewidth of a static sample) of simultaneously applied 1 H and 13 C spin-locking rfirradiation during an optimized contact time (typ. > 1 ms), is satisfied. This not only boosts dDNP but also provides a way to generate transportable polarized metabolites [16,17].

However, the high rf-pulse powers and energies required on the low-gamma spectrometer rf-channel often lead to deleterious rf-probe arcing in the superfluid helium bath. This detrimental experimental effect limits the scaling up of dDNP sample sizes and complicates the implementation of CP for sample volumes surpassing 500 𝜇L, which is imperative for enabling clinical applications using large sample doses [18].

In previous works [19], a dipolar order mediated crosspolarization (dCP) rf-pulse sequence was demonstrated to transfer 1 H polarization to 13 C nuclear spins in static solid-state samples. The polarization transfer rf-pulse sequence operates via an intermediary reservoir of dipolar spin order [20][21][22][23][24][25][26][27][28][29][30] and relies on the sequential application of 1 H and 13 C rf-fields, which requires low rf-pulse powers and energies, and is therefore more conducive to the hyperpolarization of larger sample volumes under dDNP conditions. The efficiency of 1 H® 13 C polarization transfer was improved with respect to a state-of-the-art and optimized CP approach by the implementation of shaped rf-pulses and molecular derivatives with favourable properties. However, the exact mechanism of the polarization transfer process for standard DNP-compatible sample formulations requires further elucidation.

In the current Paper, we present the role of molecular and solvent protonation on the dCP polarization transfer mechanism. CP under dDNP conditions is usually performed on samples with a protonation extent of ~10-30% [6,8,19]. However, self-glassing dDNP-compatible samples such as pyruvic acid have much higher 1 H concentrations [31]. It is therefore of interest to investigate whether 13 C spins in highly protonated dDNP samples can also be hyperpolarized by dCP in an efficient manner. Furthermore, there has been recent interest in transferring the high levels of 1 H polarization to 13 C spins in deuterated molecules since such systems often display significantly longer 13 C relaxation time constants in solution after dissolution [32]. CP experiments performed on deuterated molecules have been shown to work equally as well as compared to their protonated counterparts [32], despite slower transfer dynamics. It is additionally worth considering if the 1 H® 13 C polarization transfer works as well in the case of dCP for deuterated molecular systems.

In the context of our dDNP experiments, we introduce the following sample formulation modifications with respect to conventional dDNP sample constituents: (i) increasing the protonation extent of the DNP solvent; and (ii) employing deuterated molecular candidates. We report experimental observations for [1-13 C]sodium acetate and its methyl deuterated derivative for a variety of solvent protonation extents. The 1 H sample molarity was shown to significantly influence the parameters and performance efficiency of the dCP rf-pulse sequence, e.g., the optimal 1 H® 13 C dCP nuclear polarization transfer time was drastically reduced at high levels of solvent protonation. It was also found that deuterated molecular moieties reduce the efficiency of the dCP transfer process, with deleterious effects observed for the build-up of the 13 C NMR signal in certain cases, i.e., low extents of sample protonation. Solutions of 3 M [1-13 C]sodium acetate (I) and [1-13 C]sodium acetate-d3 (II) doped with 50 mM TEMPOL radical (all compounds purchased from Sigma Aldrich) were prepared in the glass-forming mixtures of H2O/D2O/glycerol-h8/ glycerol-d8 (v/v/v/v) given in Table 1. All samples were sonicated for ~10 minutes. Paramagnetic TEMPOL radicals were chosen to polarize 1 H spins most efficiently under our dDNP conditions.

Methods

Sample Preparation

Sample Freezing

100 𝜇L volumes of each sample were separately pipetted into a Kel-F sample cup and rapidly immersed in the liquid helium bath of a 7.05 T prototype Bruker Biospin polarizer equipped with a specialized dDNP probe and running TopSpin 3.5 software. The sample temperature was further reduced to 1.2 K by adjusting the pressure of the variable temperature insert (VTI) towards ~0.7 mbar.

Dynamic Nuclear Polarization

The samples were polarized by applying microwave irradiation at fμw = 197.648 GHz (positive lobe of the DNP spectrum) with triangular frequency modulation of amplitude Dfμw = 120 MHz [33] and rate fmod = 0.5 kHz at a power of ca. 100 mW at the output of the microwave source and ca. 30 mW reaching the DNP cavity [START_REF] Elliott | Solid-State 1 H Spin Polarimetry by 13 CH3 Nuclear Magnetic Resonance[END_REF] which were optimized by using sample I10% prior to commencing experiments to achieve the highest possible 1 H polarization.

Microwave Gating

Microwave gating was employed shortly before and during dDNP polarization transfer experiments (see Section 2.5) to allow the electron spin ensemble to return to a highly polarized state, which happens on the timescale of the longitudinal electron relaxation time constant (typ. T1e = 100 ms with Pe = 99.93% under our experimental dDNP conditions) [35]. Microwave gating therefore affords a means to substantially reduce paramagnetic relaxation, and as a result; the 1 H and 13 C relaxation time constants in the presence of an rf-field (𝑇 !" ) are extended by orders of magnitude, allowing spin-locking rfpulses to be much longer, and ultimately significantly increasing the overall efficiency of nuclear spin polarization transfer. In previous studies [19,36,37], variants of the dipolar order mediated cross-polarization (dCP) rf-pulse sequence which included shaped rf-pulses were found to have improved 1 H® 13 C nuclear polarization transfer efficiencies versus the original non-Zeeman polarization transfer (NZPT) experiment proposed by Vieth and Yannoni [19,21] from which our work was inspired. Figure 1 shows this sequence adapted for our dDNP experiments. The dCP rf-pulse sequence operates as follows: (i) a saturation sequence of 90° rf-pulses with alternating phases separated by a short delay repeated n times (typ. n = 50) kills residual magnetization from previous experiments on both rf-channels;

dCP RF-Pulse Sequence

(ii) the microwave source becomes active for a time tDNP during which 1 H DNP builds-up;

(iii) the microwave source is deactivated, and a delay of duration tG = 0.5 s occurs before the next step, thus permitting the electron spins to relax to their highly polarized thermal equilibrium state [35];

(iv) a preparatory 1 H adiabatic half-passage (AHP) rf-pulse creates transverse 1 H magnetization;

(v) a linearly decreasing ramp H dCP rf-pulse of amplitude 𝜔 #$% & and length 𝑡 #$% & prepares proton dipolar order; (vi) an increasing hyperbolic tangent 13 C dCP rf-pulse of amplitude 𝜔 #$% $ and length ∆𝑡 #$% $ presumably converts the 1 H-1 H dipolar order into 13 C magnetization;

(vii) the induced 13 C NMR signal is detected. Further details regarding dCP rf-pulse sequence operation are given elsewhere [19].

Results

Dipolar Order Mediated Cross-Polarization

The build-up of 13 C polarizations normalized by the corresponding 1 H polarizations PdCP( 13 C)/P( 1 H) as a function the 13 C dCP rf-pulse duration ∆𝑡 '$% $ was monitored by using the dCP rf-pulse sequence depicted in Figure 1. The dCP rf-pulse sequence was repeated with incremented values of the 13 C dCP rf-pulse duration ∆𝑡 #$% $ , with all other rf-pulse parameters fixed. Experiments were performed after only 5 s of DNP to minimize the effects of radiation damping on the quantification of the 1 H polarization [38,39].

The influence of the 13 C dCP rf-pulse duration ∆𝑡 '$% $ on the build-up of the normalized 13 C polarizations for several samples is shown in Figure 2a. Experimental values lie between 0 (no transfer) and 1 (theoretical maximum). The influence of the 1 H sample molarity on the other properties of the 1 H and 13 C dCP rf-pulses, e.g., peak rf-power, was found to be minimal.

For samples with low 1 H molarities, the normalized 13 C polarization build-up curves plateau at long values of the 13 C dCP rf-pulse duration (∆𝑡 #$% $ > 40 ms). Samples with increased 1 H molarities, i.e., for sample protonation levels ≥ 40%, the normalized 13 C polarization build-up curves feature maxima at relatively short values of the 13 C dCP rf-pulse duration (∆𝑡 #$% $ < 15 ms), followed by a slowly decaying component.

The 13 C/ 1 H polarization ratio PdCP( 13 C)/P( 1 H) allows a direct comparison of the dCP transfer efficiency for samples with proton spins which polarize to different extents. The quantity 𝑃 '$% ()* ( 13 C)/P( 1 H) is plotted in Figure 2b (black data points and axis) as the normalized 13 C polarization maxima from the curves shown in Figure 2a ()* ( 13 C)/P( 1 H) increases with an increasing 1 H sample molarity, until a maximum is reached at ~53 M, after which the polarization ratio decreases with a further increase in the 1 H sample molarity. The methyl deuterated molecular derivative additionally fits this trend.

The durations of the 13 C dCP rf-pulses ∆𝑡 '$% $ at the normalized 13 C polarization maxima for the curves presented in Figure 2a are shown by the grey data points and axis in Figure 2b. The filled circles correspond to sample I for various 1 H sample molarities [H], and these data points are connected via the grey line. There is a general trend, for all samples, of decreasing 13 C dCP rf-pulse durations ∆𝑡 '$% $ with increasing 1 H sample molarities, with a rapid decrease at relatively low 1 H sample molarities. This curve begins to plateau at relatively high 1 H sample molarities (exceeding ~60 M). Even though the open symbols belong to a different molecular spin system, the data points still fit the overall trend.

The build-ups of the normalized 13 C polarizations were found to have strong stretched exponential behaviours in all cases. The experimental data in Figure 2a are well fitted with a phenomenological stretched exponential function using two rate constants denoted 𝑅 #$% $ and 𝑅 +,-./ $ responsible for the build-up and decay of the normalized 13 C polarizations, respectively. Stretched exponential function:

A(1-exp{- (𝑅 '$% $ 𝑡) 0 })exp{-𝑅 +,-./ $ 𝑡}, where A is a fitting constant, 𝑅 '$% $ = • • • • □ □ △ △ • • • • □ □ △ △ 0
( 13 C) / P( 1 H) Δt dCP C / ms • • • • • • • • • • • • •• •• •• •• •••• ••••• • ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■
▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲

◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ◇ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○○ ○○ ○ ○ ○ ○○ ○○ ○○ ○○ ○○ ○○ ○ � �� �� �� �� �� �� ���� ���� ���� ���� ���� Δ� ��� � / �� � ��� ( �� �) / �( � �) • ■ ▲ ◆ ◇ ○ I-h 10% I-h40% I-h70% I-h 100% II-h10% II-h100% a) b) 𝑅 '$% * Γ(1/𝛽)/𝛽, 𝑅 '$% *
is the average 13 C build-up rate constant, 𝛽 is the breadth of the distribution of 13 C build-up rate constants and Γ(1/𝛽) is the gamma function (see the Electronic Supporting Information (ESI) for more details). We attribute the average 13 C build-up rate constants 𝑅 #$% * to be ones associated with the generation of the normalized 13 C polarizations. It should be noted that 𝑅 +,-./ $ is an "apparent" relaxation rate constant. The connection between the 13 C spin bath and the lattice is indirect, likely via the 1 H spins. From fitting the normalized 13 C polarizations as a function of the 13 C dCP rf-pulse durations ∆𝑡 #$% $ rate constants for the build-up and decay of the normalized 13 C polarizations, namely 𝑅 '$% * and 𝑅 +,-./ $ , respectively, and the breadths of the distributions of 13 C build-up rate constants 𝛽, can be estimated. The value of the average 13 C build-up rate constant 𝑅 '$% * for the experimental curves presented in Figure 2a are shown by the black data points and axis in Figure 3. There is an overall trend of a linearly increasing value of 𝑅 '$% * with an increasing 1 H sample molarity [H]. The data points for the methyl deuterated molecular analogue also follow this trend even though the local molecular moiety lacks any considerable degree of protonation. A similar trend is observed for 𝑅 +,-./ $ (see the ESI for more details).

The breadths of the distributions of 13 C build-up rate constants 𝛽 for the experimental curves presented in Figure 2a are shown by the grey data points and axis in Figure 3. 𝛽 increases linearly with an increasing 1 H sample molarity [H]. The data points for the methyl deuterated molecular candidate also follow this trend, with the value of 𝛽 almost identical for the two most highly protonated samples.

Straight-line fits to the filled symbols presented in

Cross-Polarization

The performance efficiency of the dCP rf-pulse sequence was compared with a traditional CP experiment [8][9][10][11][12][13][14][15], which is described in the ESI along with an rf-pulse sequence diagram and all optimized parameters. To compare the 13 C polarizations achieved for each sample after a single CP contact with those obtained by implementing the dCP rf-pulse sequence with a sole 1 H® 13 C polarization transfer step, experiments employed 600 s of direct 1 H DNP at 1.2 K prior to polarization transfer to the 13 C heteronucleus. The 13 C polarization level PdCP( 13 C) obtained as a result of using the dCP rf-pulse sequence is calculated by scaling PCP( 13 C) (the analogous quantity for the CP experiment) by a factor of IdCP/ICP. For sample I-h10%, 13 C spin polarizations of PdCP( 13 C) = 19.0% and PCP( 13 C) = 37.3% were measured by using the dCP and CP rf-pulse sequences, respectively. This is reasonably similar to those of the methyl deuterated molecular derivative (sample II-h10%): PdCP( 13 C) = 15.0% and PCP( 13 C) = 44.6%. These results (see Table 2) are in approximate agreement with a previous study [32]. 13 C polarization levels higher than 60% are anticipated by using a multiple CP contact approach [8][9][10][11][12][13][14][15][16].

In the case of the heavily protonated sample formulations, sample I-h100% records significantly lower 13 C nuclear spin polarizations than sample I-h10% (see Table 2) under the same experimental dDNP conditions: PdCP( 13 C) = 14.3% and PCP( 13 C) = 23.7%. The same is also true for the methyl deuterated molecular analogue (samples II-h10% and II-h100%): PdCP( 13 C) = 12.8% and PCP( 13 C) = 19.7%. It is important to indicate that a plateau in the 1 H polarization of this sample has likely not been reached after 10 minutes of 1 H DNP, and that the 1 H spins in this sample are expected to continue polarizing. However, the plateau in 1 H polarization is lower compared with samples which have reduced proton concentrations, and therefore the performances of fully protonated samples are anticipated to remain lower than those of their partially protonated counterparts (even if a 1 H polarization plateau is achieved). The 1 H DNP build-up is also slower, in this case, since the sample of interest contains more 1 H spins to polarize per electron spin.

It is also worth noting that the contact CP rf-pulse durations are significantly reduced, by a factor of ~3.4 ± 0.05, when fully protonated DNP samples are used, compared with those of ~10% protonation extent. For example, the optimal contact rfpulse duration for sample II-h10% is 9.5 ms, whilst for sample II-h100% the duration of the contact CP rf-pulse is 2.75 ms. These results also suggest that the role of DNP solvent protonation plays an important part regarding the dynamics of CP. However, the relative reduction in the 13 C rf-pulse duration for CP is much less than in the case of dCP.

Discussion

4.1 13 C Polarization Build-Up The profiles of the 13 C build-up curves in Figure 2a have remarkably different forms depending on the protonation extent of the DNP solvent. At low 1 H sample molarities, the 13 C buildup curves increase towards an eventual plateau, whilst at high 1 H sample molarities, the 13 C build-up curves peak at a maximum before decaying towards a reduced signal intensity on a longer time scale. The stretched exponential model fit implies that the dCP polarization transfer is governed by the 1 H-13 C internuclear separation. This is ultimately responsible for the initial build-up and gradual decay of the experimental profiles presented in Figure 2a. The initial build-up components of the curves belonging to the higher 1 H sample molarities are related to decreased 1 H-13 C internuclear separations, whilst the decaying components of these curves are likely attributable to increased dipolar relaxation between 1 H and 13 C spins.

• • • • □ □ △ △ • • • • □ □ △ △ 0
The polarization ratio 𝑃 '$% ()* ( 13 C)/P( 1 H) reaches a maximum at a ~53 M proton sample molarity, where the dCP pulse sequence transfers ~54% of the original 1 H polarization P( 1 H) to the 13 C nuclear site. This result indicates that there is a delicate balance in the 1 H solvent protonation extent, which is likely a trade-off between improved polarization transfer rates and 𝑇 !" relaxation, and that a reasonable quantity of proton spins (~40%) are required to make the dCP rf-pulse sequence suitably efficient (see Figure 2b), albeit with reduced 1 H DNP efficiencies at increased 1 H molarities. Given that samples I-h70% and I-h100% achieve higher ratios of 𝑃 '$% ()* ( 13 C)/P( 1 H) compared with sample I-h10%, it is apparent that increasing the 1 H bath concentration, and consequently improving the dCP transfer process, outweighs the associated costs of increased proton induced 𝑇 !" relaxation.

dCP Transfer Efficiency vs. Protonation

Figure 2b (grey points and axis) shows a sharp decrease in the 13 C dCP rf-pulse optimal duration ∆𝑡 #$% $ as a function of the 1 H sample molarity [H]. This trend indicates that the 1 H® 13 C polarization conversion becomes increasingly more efficient once the sample has a sufficient 1 H solvent molarity (see the ESI for more details).

At a 100% sample protonation level, i.e., a 1 H sample molarity of ~120 M, the distances between neighbouring 1 H nuclear spins in the DNP solvent are reduced by a factor of ~2.15 with respect to a sample of 10% solvent protonation ([H] ≃ 20 M), which increases the 1 H-1 H dipolar couplings 𝜔 22 by a factor of ~10. Such a relationship assumes that the dipolar couplings are proportional to the 1 H sample concentration [H], since 𝜔 22 is proportional to the inverse cube of the 1 H-1 H distance, which is itself proportional to the inverse cube of the concentration. The same is true for the 1 H-13 C internuclear separations, and their respective dipolar couplings 𝜔 23 . If the transfer of 1 H® 13 C polarization is governed by such dipolar interactions, then it is permissible that the 13 C dCP rf-pulse duration ∆𝑡 #$% $ is inversely proportional to these dipolar couplings. Since a precise relationship between 𝜔 22 , 𝜔 23 and ∆𝑡 #$% $

is not yet known, this hypothesis can be tested by considering the ratio of ∆𝑡 #$% $ at 10% and 100% 1 H sample protonations, which for sample I is ~8.2. In the case of sample II, the ratio of ∆𝑡 #$% $ at 10% and 100% 1 H sample protonations is ~11.3. These results suggest that the methyl group moiety local to the 13 C labelled nuclear site plays an important role in the transfer of polarization from 1 H to 13 C spins. This could be the reason for the reduced dCP rf-pulse sequence performance for sample II-h10% (see the ESI for more details).

Dipolar Order in the Sample Bulk

The 13 C nuclear site in sample II-h10% was able to polarize to a reasonable degree without any attached protons (see Figure 2a). However, there are still a non-negligible number of proton spins within this sample due to the protonation of the DNP juice used in our experiments. These results therefore suggest that proton dipolar order is mostly generated between 1 H spins in the DNP sample solvent (or between the solvent and the molecule of interest) by the 1 H dCP rf-pulse, and subsequently transferred from the solvent 1 H spins to the 13 C spins of interest via the 13 C dCP rf-pulse. As a result, the average 13 C dCP rf-pulse build-up rate constant 𝑅 #$% * for sample II-h10% is likely to indicate the rate of 1 H® 13 C polarization transfer mediated by proton dipolar order generated within the DNP matrix itself and provides a minimum value of 𝑅 #$% * for potential future samples. The smaller average 13 C dCP rf-pulse build-up rate constant 𝑅 #$% * for sample II-h10% compared with sample I-h10% is likely due to increased internuclear separations between 1 H spins participating in the proton dipolar order within the solvent and the target 13 C nucleus of the molecule of interest due to the inclusion of the deuterated methyl group. Without such an effect, it is unlikely that the 13 C nuclear site in sample II-h10% would polarize as efficiently.

In Figure 3 it was observed that the average 13 C dCP rf-pulse build-up rate constants 𝑅 '$% $ increase linearly with the 1 H sample molarity. The reason for this trend is likely to be similar to that observed for the 13 C dCP rf-pulse duration ∆𝑡 #$% $ with 1 H sample molarity. At high 1 H sample molarities ([H] > 100 M), the 13 C dCP rf-pulse build-up rate 𝑅 '$% $ for sample I-h100% is a factor of ~1.26 greater than for sample II-h100%. At low 1 H sample molarities ([H] ≲ 20 M), the 13 C dCP rf-pulse build-up rate 𝑅 '$% * for sample I-h10% is a factor of ~9 greater than for sample II-h10%. This indicates that although the 1 H® 13 C dCP polarization transfer mechanism is mostly operating via the proton spins embedded within the DNP solvent at high 1 H molarities, given that sample II-h100% has no directly bound 1 H spins, the local methyl moiety plays a more pivotal role in the 1 H® 13 C dCP transfer of polarization to the 13 C nuclear spin at low levels of sample protonation.

The breadths of the distributions of 13 C build-up rate constants 𝛽 were shown to increase with an increasing 1 H sample molarity [H], see Figure 3 (grey data points and axis). This indicates that as [H] increases the average 13 C build-up rate constants 𝑅 #$% * converge towards a sole value. The value of 𝛽 for the 2 H substituted molecular system is almost identical to that of its protonated counterpart at high levels of sample protonation. This result suggests that there is a very similar distribution of average 13 C dCP rf-pulse build-up rates 𝑅 '$% * for both samples, which again indicates that the 1 H spins within the DNP solvent are mostly responsible for the 1 H® 13 C dCP transfer of polarization at increased levels of sample protonation.

A discussion regarding effective dCP polarization transfer rates, i.e., the dCP polarization transfer rate per unit of proton spin concentration, is given in the ESI.

Hyperpolarization of deuterated molecules

The observed 13 C polarization level (after 10 minutes of DNP) for sample II, i.e., the methyl deuterated molecular system, is lower by a factor of ~1.27 compared with that of sample I in the case of low levels of 1 H sample molarity (see Table 2). However, the results shown in Figure 3 and the ESI indicate that the dCP rf-pulse sequence relies on a pool of proton dipolar spin order which is contained between the proton spins within the DNP solvent. This claim is supported by considering that when the solvent 1 H molarity is increased from 10%®100% for sample I, 𝑅 '$% * increases by a factor of ~10.3. The same modification in solvent protonation extent for sample II leads to an increase in 𝑅 '$% * by a factor of ~74. These results highlight the beneficial role of protonating the DNP solvent in the case of deuterated molecular systems, with the performance efficiency of sample II-h10% significantly improved by increasing the protonation level of the DNP solvent (see Table 2 and the ESI). However, the overall level of 13 C polarization is reduced (even after 5 s of DNP and microwave gating) in the case of highly protonated samples, given the longer 1 H polarization build-up timescales associated with these samples.

Previous investigations regarding the overall performance of CP-based rf-methods on deuterated derivatives of 13 Clabelled small molecules has demonstrated that the level of molecular deuteration has a negligible effect on the efficiency of various CP approaches, since proton Zeeman order within the bulk of the DNP glassing matrix is employed for the polarization transfer process [32]. These results are clearly replicated for the dCP rf-pulse sequence and imply that 2 H substituted molecules can be polarized to the same extent as their protonated counterparts by using the dCP rf-pulse sequence at increased levels of sample protonation. Clearly, an increased level of overall sample protonation was found to have a positive impact on the dCP rf-pulse sequence relative to the performance of the CP rf-pulse sequence, which experienced a much more dramatic decrease in 13 C polarization with increasing sample protonation for both protonated and deuterated molecular derivatives (see Table 2), although there is less 1 H polarization available for dCP/CP transfer per unit DNP time.

The 1 H (and 13 C) NMR linewidths were found to increase with an increasing 1 H sample molarity, as shown in the ESI, which may also have consequences regarding the performances of the dCP and CP rf-pulse sequences.

Conclusions

We have shown the importance of molecular and solvent protonation on the 1 H® 13 C transfer mechanism of nuclear spin polarization in the case of a dCP rf-pulse sequence which employs an intermediary reservoir of dipolar spin order. The importance of each protonated component was demonstrated by investigating the following sample formulation strategies: (i) modifying the protonation extent of the DNP solvent; and (ii) utilizing methyl deuterated molecular targets. The overall 1 H sample molarity was found to have a significant influence on both the optimal parameters and efficiency of the dCP rf-pulse sequence, and in general made the approach substantially shorter in duration and more efficient. The absence of 1 H nuclear spins in 2 H labelled molecular moieties, e.g., methyl groups, proximal to the 13 C sites of interest were found to be detrimental to the 1 H® 13 C transfer process and decrease the dCP transfer rate of the 13 C signal build-up (particularly at low 1 H sample molarities).

This investigation has provided insights into the key sample formulation characteristics which control the dipolar order mediated transfer of 1 H polarization to 13 C nuclear spins and indicates that the dCP polarization transfer efficiencies of deuterated molecular candidates can be improved by increasing the protonation of the DNP solvent matrix. The large excess of 1 H spins within the DNP glassing matrix means that 13 C spins in a wide variety of molecular systems can be easily polarized by a low peak power and energy rf-pulse sequence which is straightforward to implement and robust with respect rf-pulse parameter optimization. Such molecular systems include deuterated molecules, dilute samples or molecules of interest with 13 C sites at natural abundance. A raft of numerical simulations could be employed to elucidate the nature of the polarization transfer mechanism in such cases. These results are encouraging for the future usage of the dCP rf-pulse sequence, which may be advantageous for certain applications that require reduced peak rf-power requirements and forge a path towards hyperpolarization experiments compatible with increased sample volumes, e.g., such as those implemented in clinical research.

Figure 1 :

 1 Figure 1: Schematic representation of the dCP rf-pulse sequence used for preparing dipolar order in samples I and II and monitoring its conversion to 13 C magnetization. The experiments used the following parameters, chosen to maximize the efficiency of the dCP rf-pulse sequence: n = 50; tDNP = 5 s; tG = 0.5 s; 𝜔 !"# " /2𝜋 = 27.8 kHz; 𝑡 !"# " = 175 𝜇s; 𝜔 $%# " /2𝜋 = 16.9 kHz; 𝑡 $%# " = 475 𝜇s; 𝜔 $%# % /2𝜋 = 14.6 kHz. AHP = adiabatic half-passage. AHP sweep width = 100 kHz. The 𝜋/2 saturation rf-pulses use a thirteen-step phase cycle to remove residual magnetization at the beginning of each experiment: {0, 𝜋/18, 5𝜋/18, 𝜋/2, 4𝜋/9, 5𝜋/18, 8𝜋/9, 𝜋, 10𝜋/9, 13𝜋/9, 𝜋/18, 5𝜋/3, 35𝜋/18}. The resonance offset was placed at the centre of the 1 H and 13 C NMR peaks.

Figure 2 :

 2 Figure 2: a) 13 C polarizations normalized by 1 H polarizations PdCP( 13 C)/P( 1 H) as a function of the 13 C dCP rf-pulse duration ∆𝑡 $%# % acquired at 7.05 T ( 1 H nuclear Larmor frequency = 300.13 MHz, 13 C nuclear Larmor frequency = 75.47 MHz) and 1.2 K. The data presented in (a) were acquired by using the dCP rf-pulse sequence shown in Figure 1. Solid and dashed lines correspond to best fits of the filled and open data points, respectively, and have the following fitting function: A(1-exp{-(𝑅 &%# % 𝑡) ' }exp{-𝑅 ()*+, % t}). b) 13 C polarizations normalized by 1 H polarizations 𝑃 $%# -./ ( 13 C)/P( 1 H) (black) and 13 C dCP rf-pulse durations ∆𝑡 $%# % (grey) as a function of the 1 H sample molarity [H] (same experimental dDNP conditions as in a)). Filled symbols: Sample I; and open symbols: Sample II. The values for the open triangles have been adjusted (see the ESI for more details) to compensate for the non-plateauing behaviour of the 13 C build-up curve for sample II-h10% (shown in a)).

  as a function of the 1 H sample molarity [H] for all the samples employed in this study. The open symbols correspond to samples: II-h10% (open triangle); and II-h100% (open square). 𝑃 '$%

Figure 3 : 1 ;

 31 Figure 3: Average 13 C dCP rf-pulse build-up rate constants 𝑅 $%# * (black) and breadths of the distributions of the 13 C build-up rate constants 𝛽 (grey) as a function of the 1 H sample molarity [H] acquired at 7.05 T ( 1 H nuclear Larmor frequency = 300.13 MHz, 13 C nuclear Larmor frequency = 75.47 MHz) and 1.2 K. The filled symbols were fitted with a straight-line function including an intercept: 𝑦 = 𝑚 1 × [H] + 𝑎 1 . Best fit values: y = 𝑅 &%# * : 𝑚 2 !"# * = 0.007 M -1 ms - 1 ; 𝑎 2 !"# * = 0 ms -1 (forced); y = 𝛽: 𝑚 ' = 0.002 M -1 ; 𝑎 ' = 0.6. Filled symbols: Sample I; and open symbols: Sample II. In some cases, the error bars are smaller than the data points.

  Figure 3 are indicated by the solid lines. The experimental data are well fitted with relationships of the kind: y([H]) = my × [H] + ay; where y([H]) is either 𝑅 #$% * or 𝛽, my is the slope of the straightline fit, [H] is the 1 H sample molarity and ay is the intercept. See the caption of Figure 3 for best fit values. The intercept 𝑎 0 was forced to zero in the case of 𝑅 #$% * . The experimental data points from the open symbols (sample II) approximately follow the trend of the filled symbols (sample I).

Table 1 :

 1 1 H solvent protonation percentages hx%, 1 H sample molarities [H] and relative proportions of H2O/D2O/glycerol-h8/glycerol-d8 used for the DNP solvent matrices of the samples employed in this study.

				Samples
			I			II
	hx%	10	40	70	100	10	100
	[H] / M	20.07	53.38	87.49	119.70	11.07	110.70
	H2O	1	4	4	4	1	4
	D2O	3	0	0	0	3	0
	glycerol-h8	0	0	3	6	0	6
	glycerol-d8	6	6	3	0	6	0

Table 2 :

 2 13 C nuclear spin polarization levels PdCP( 13 C) and PCP( 13 C) measured after 10 minutes of DNP for the 1 H depleted and enriched samples (I and II) employed in this study amassed by using the dCP and CP rf-pulse sequences, respectively, acquired at 7.05 T ( 1 H nuclear Larmor frequency = 300.13 MHz,

	13 C nuclear Larmor frequency = 75.47 MHz) and 1.2 K.
			Samples
		I-h10%	II-h10%	I-h100%	II-h100%
	PdCP( 13 C) / %	19.0	15.0	14.3	12.8
	PCP( 13 C) / %	37.3	44.6	23.7	19.7

Acknowledgements

This research was supported by ENS-Lyon, the French CNRS, Lyon 1 University, the European Research Council under the European Union's Horizon 2020 research and innovation program (ERC Grant Agreements No. 714519 / HP4all and Marie Skłodowska-Curie Grant Agreement No. 766402 / ZULF). The authors gratefully acknowledge Bruker Biospin for providing the prototype dDNP polarizer, and particularly Dmitry Eshchenko, Roberto Melzi, Marc Rossire, Marco Sacher and James Kempf for scientific and technical support. The authors additionally acknowledge Gerd Buntkowsky (Technische Universitat Darmstadt) who kindly communicated data associated with prior publications to us; Burkhard Luy (Karlsruhe Institute of Technology) for enlightening discussions; Catherine Jose and Christophe Pages for use of the ISA Prototype Service; Stéphane Martinez of the UCBL mechanical workshop for machining parts of the experimental apparatus; and Samuel Cousin and Morgan Ceillier for maintaining the experimental setup.