Matheus Coelho Cosenza

Marcos Val Ério Ribeiro

Anna Carla Araujo

Stability on turning of Inconel 718 using vibration-assisted machining

Keywords: metal cutting, chatter, hard-to-cut materials, VAM

Inconel is a hard-to-cut material that uses very low cutting speed. In turning operation added to the low cutting velocity, there is also a second limitation to productivity: chatter. In order to reduce chatter, the depth of cut is reduced and the material removal rate is lower. One option to avoid reducing the depth of cut is using vibration assistance machining. This paper presents a numerical investigation using 1D vibrations in the feed direction in order to reduce chatter in turning Inconel 718.

INTRODUCTION

As the aerospace, oil and gas and chemical industries advance, the need to improve and develop new manufacturing processes is a constant challenge. Researches and studies have been held to discover materials and methods to not only achieve high precision, but also to reduce the production time. Inconel and titanium alloys have excellent mechanical properties, nevertheless, as per its low thermal conductivity and high hardening, cutting speed ranges and tool life are below other metallic materials [START_REF] Sharman | The effect of tool nose radius on surface integrity and residual stresses when turning inconel 718[END_REF]. Furthermore, chatter is also a limitation on high production, caused by the friction between the tool and the workpiece [START_REF] Urbicain | Stability prediction maps in turning of difficult-to-cut materials[END_REF]. So, there are two main barriers in metal cutting against this progress: difficult-to-cut materials and chatter.

The vibration-assisted machining (VAM) is one method used for chatter mitigation, it adds small-amplitude and highfrequency displacement to the tool. [START_REF] Brehl | Review of vibration-assisted machining[END_REF] presents the VAM benefits from the periodic separation between the tool rake face and the uncut material generated by the vibration to produce thinner chips, increase form accuracy and extend tool life. For 1D VAM, it is used a ultrasonic generator and a sonotrode (booster and horn) to create and amplify reciprocating harmonic motin of high frequency keeping a low amplitude. The tool is attached to the end of the horn and positioned so that the rake face is normal to the direction of vibration motion. This paper propose a numerical simulation of chatter suppression using small amplitude tool displacement in the feed direction during turning Inconel 718. The goal is to analyze and compare the results with experiments previously published. Furthermore, the regions of instability are taken from a published paper and it is proposed to compare two situations in non-stable region, with and without small amplitudes, to confirm the benefits of VAM.

MECHANICAL MODEL FOR DYNAMIC CUTTING FORCE

Chatter is a self-excited vibration that can occur during machining operations that can be classified in two different categories, primary and secondary chatter [START_REF] Quintana | Chatter in machining processes: A review[END_REF]. The first one is caused by the friction between the workpiece and the cutting tool, by mode coupling and thermo-mechanical effects on the chip formation. The second and most relevant one, secondary chatter, can occur because most metal cutting operations contain overlapping cuts, which can generate a vibration amplification. As a result of the cutting tool vibration, the workpiece surface acquires a wavy surface and, consequently, the cutting force and the chip thickness change in relation to the difference between the uncut material left by the previous revolution and the current one. Basically, chatter can be avoid by estimating the stablility lobe diagram and adjusting the cutting parameters to maintain the system in the stable area. However, in the past years, a different approach have been used to manage the system vibration, this strategy uses elements, devices and actuators to modify the system behavior and control chatter.

Chatter in turning operations

Turning is a machining process in which the workpiece rotates around the x axis, as shown in Figure 1a, with a Ω spindle speed, while the tool holder moves in the feed direction parallel to x. The feed velocity is a function of the feed per revolution f r and the spindle speed Ω, which is calculated considering the cutting speed V c and the workpiece diameter D. As presented in Figure 1b, the depth of cut a p is the difference between the workpiece and the machined radius, if there is no vibration in the radial direction.

As shown in Figure 1a, if considering both tool and workpiece rigid, the chip would have a constant uncut chip thickness h 0 , calculated as a function of the feed f (mm/rev) and the lead angle κ r . In this article it is considered that the cutting edge is orthogonal to the feed direction, so κ r = π/2 and h 0 = f r sin κ r = f r .

In real conditions, components, like boring bars and tool holders, affect the flexibility of the system causing vibration and generating a non-uniform surface, as presented in Figure 1b. In this case, the tool tip position is moving as a result of the tool deflection x(t). The uncut chip thickness is not constant h(t) = h 0 due to x(t) and the workpiece surface machined in the previous revolution x(tτ):

h(t) = h 0 + x(t -τ) -x(t) (1)
For a system that vibrates only in the feed direction, as shown in Figure 1b, the feed force F x (t) is a function as the specific cutting energy in feed direction K x , depth of cut and the instantaneous uncut chip thickness h(t) (Eq. 2). The cutting-force expoent q has to be consider to evaluate the force in the vibration direction [START_REF] Hajdu | Sensitivity of stability charts with respect to modal parameter uncertainties for turning operations[END_REF].

F x = K x .a p .h(t) q (2)
Assuming the cutting tool is always in contact with the workpiece, in other words, the chip thickness is never less than zero, the system can be analyzed as a one-dimensional oscillator with excitation in the feed direction x. Since instantaneous chip thickness x(t) depends on the workpiece surface machined in the past revolution x(t-τ) and considering the dynamical parameters: modal mass m t , damping c, stiffness k and the cutting parameter: feed velocity v f , the governing equation can be written as:

m t ẍ(t) + c ẋ(t) + kx(t) = F x (K x , a p , h(t), q) = K x a p (v f τ(t) + x(t -τ(t)) -x(t)) q
(3)

The stability of the system can be analysed for each spindle speed Ω. Figure 2 shows the diagram of stability lobes, which presents the depth of cut a lim that bounds the values of depth cut that maintain the system stable and the values that result in instability and chatter.

Vibration-assisted machining (VAM)

Althought vibration is usually avoided, it can also be used to reduce cutting forces and produce thinner chips. The Vibration-assisted machining (VAM) adds a small amplitude with high frequency displacement to the cutting motion of the tool, generates an improvement in surface finish, form accuracy and burr reduction when compared with conventional machining. The critical feed velocity is the one the rake face lose contact with the uncut material. For 1D VAM, the tool vibrates harmonically in a linear path in the feed direction, so x(t) is known and controlled. In Fig. 3a, t = t 1 , the tool has just started to cut the material and the velocity relative to the work ẋ(t) is in the direction of V f . In Fig. 3b, t = t 2 , the tool already is though the vibration linear path, ẋ(t) is equal to zero. After that, the tool goes slightly to reverse direction, in t = t 3 (Fig. 3c), and the tool lose contact with the workpiece. In Fig. 3d, t = t 1 , the tool reestablish contact with the material to start a new cutting cycle with ẋ(t) > 0 again.

Eq. 4 describes the feed controled position, where ω f is the angular frequency, V f is the feed velocity and A f is amplitude of the tool vibration [START_REF] Brehl | Review of vibration-assisted machining[END_REF]. The critical feed velocity V lim f that would cause the separation between the tool rake face and the workpiece surface is described in Eq. 6:

x(t) = A f sin(ω f t) +V f .t (4) ẋ(t) = ω f A f cos(ω f .t) +V f (5) V lim f = ω f A f (6)
When the velocity is greater or equal to the critical value, the tool is always in contact with the work surface. On the other hand, when the opposite happens, V < V lim f , the cutting is interrupted and the benefits of VAM can be noticed (better surface finish, form accuracy, etc.).

If one considers that VAM uncut chip thickness h (t) will also change due to the vibration applied to the system (Eq. 7), the governing equation (Eq. 8) can be written as:

h (t) = h(t) + A f sin(ω f t) = h 0 + x(t -τ) -x(t) + A f sin(ω f t) = v f τ(t) + A f sin(ω f t) + x(t -τ(t)) -x(t) (7) m t ẍ(t) + c ẋ(t) + kx(t) = F x K x , a p , h(t), q) = K x a p (v f τ(t) + A f sin(ω f t) + x(t -τ(t)) -x(t)) q (8)

NUMERICAL SIMULATION

The numerical simulation analyze the effects and benefits of VAM comparing the algorithm considering constant h 0 and VAM uncut chip thickness h (t). Beyond that, the results will be compared with some experiments previously published to validate the routine. As proposed by [START_REF] Altinas | Manufacturing Automation: metal cutting mechanics, machine tool vibrations, and CNC design[END_REF], first, a frequency greater than the natural frequency f n is chosen as the chatter frequency f c so ω c > ω n .

φ = X(s) F f (s) = ω 2 n k x (s 2 + 2ξ ω n s + ω 2 n ) (9)
Applying the Laplace Transformation, the transfer function is found (Eq. 9) and the phase angle ψ can be written as:

tan(ψ) = sin(ω c T ) cos(ω c T ) -1 (10)
Giving that r is the ratio between the chatter frequency and the natural frequency and G(ω c ) is the real part of the transfer function for the critical stability (Eq. 11), critical depth cut is given in Eq.12. Finally, the spindle speed n(k) for each stability lobe k = 1, 2, 3, ... is calculated and the routine will repeat the procedure by scanning the chatter frequencies.

G(ω c ) = 1 -r 2 k x [(1 -r 2 ) 2 + (2ξ r) 2 ]
(11)

a lim = -1 2K x G(ω c ) (12) n(k) = 120π f c 2ψ + 3pi + 2kπ (13)

Figure 1 -

 1 Figure 1 -Chip removal in orthogonal turning. (adap. from Hajdu et al. (2015))

Figure 2 -

 2 Figure 2 -Diagram of stability lobes (Lu et al., 2018).

Figure 3 -

 3 Figure 3 -1D vibration-assisted machining (adap. Brehl and Dow (2008))

Cutting parameters and dynamics conditions

In order to compare the results obtained and the ones already published the routine must consider the same parameters used by [START_REF] Palacios | Combination of simulated annealing and pseudo spectral methods for the optimum removal rate in turning operations of nickel-based alloys[END_REF]. The workpiece is an cold worked Inconel 718 bar with 12.4 mm diameter, havind around 30 HC hardness, and its behavior is studied near the depth cut limit a lim .

Based on the results obtained by [START_REF] Palacios | Combination of simulated annealing and pseudo spectral methods for the optimum removal rate in turning operations of nickel-based alloys[END_REF], the tool-holder have only one vibration mode with modal values of f = 1650 Hz, ζ = 0.0662 and m = 0.2866 kg. In addition, [START_REF] Palacios | Combination of simulated annealing and pseudo spectral methods for the optimum removal rate in turning operations of nickel-based alloys[END_REF] also presented in Figure 4 the cutting conditions that produce a stable, unfilled circles, and unstable, triangles, scenario.

According to [START_REF] Brehl | Review of vibration-assisted machining[END_REF], the operational VAM frenquecy is usually, approximately, 20 or 40 kHz and the amplitude magnitude is between 3 and 20 µm. If this boundary values are not respected, the tool vibration can become unstable, resulting in possible impact damage to the cutting tool, poor surface finish and reduction of the cutting tool life. In simulation it is used 20 kHz with 10 µm. The cutting conditions simulated are: (1) stable condition without VAM: f z = 0.1 (mm/rev) (V f = 40 mm/min), (2) unstable condition without VAM: f z = 0.6 (mm/rev) (V f = 120 mm/min) and

(3) VAM applied to f z = 0.6 (mm/rev) (V f = 120 mm/min). In all cases spindle Speed Ω = 200 rpm.

RESPONSIBILITY NOTICE

The author(s) is (are) the only responsible for the printed material included in this paper.


Fábio De Oliveira Campos

Anna Carla Araujo

Shiv Gopal Kapoor

Experimental Comparison of Micromilling Pure Titanium and Ti-6Al-4V WCMNM 2018

Keywords: micromilling, titanium, machinability

Pure titanium is the ideal metallic material to be used for producing dental implants due to its good corrosion resistance and biocompatibility. However, pure titanium does not present high mechanical resistance, which can be a limiting factor. Recently, the pure titanium is being replaced by titanium alloy with aluminum and vanadium (Ti-6Al-4V). This study deals with micromilling machinability of pure titanium and Ti-6Al-4V considering mechanical properties, the forces measured during the process, surface roughness, top burr height, and chips morphology. The cutting tests are performed for the constant depth of cut and cutting speed, and a range of feed per tooth from 0.5 to 4.0 µm/tooth. Results show no significant differences in roughness and burr formation whereas higher forces are found for the titanium alloy compared to pure metal. Both materials produce long chips for smaller feeds.

Introduction

Pure titanium (CP-Ti) is the ideal titanium-based material to be used in the manufacturing of implants because of its properties: good corrosion resistance, biocompatibility and reasonable mechanical resistance [START_REF] Rach | Titanium alloys for biomedical applications[END_REF][START_REF] Niinomi | Mechanical biocompatibilities of titanium alloys for biomedical applications[END_REF]. However, due to fatigue failure the chances for a surgery for implant removal are seen to be increased [START_REF] Zaffe | Accumulation of aluminium in lamellar bone after implantation of titanium plates, Ti-6Al-4V screws, hydroxyapatite granules[END_REF]. The titanium alloy (Ti-6Al-4V) presents higher mechanical resistance preserving the essential properties for implants, although it can be dangerous for health after a long time use of these implants [START_REF]Review on Machinability of Titanium Alloys: The Process Perspective[END_REF].

Titanium based metals are considered difficultto-machine materials, especially due to their low thermal conductivity [START_REF]Review on Machinability of Titanium Alloys: The Process Perspective[END_REF][START_REF] Ezugwu | Titanium alloys and their machinability -a review[END_REF][START_REF] Kikuchi | The use of cutting temperature to evaluate the machinability of titanium alloys[END_REF]. Although there are a few studies that covered some aspects of micromilling titanium alloys [START_REF] Carou | Latest advances in the micromilling of titanium alloys: a review[END_REF][START_REF] Kim | Experimental Study on Machinability of Ti-6Al-4V in Micro End-Milling[END_REF], there is a lack of comprehensive study on the micromilling machinability of titanium alloys. The present work compares the micromilling machinability of pure titanium grade 2 and Ti-6Al-4V that includes cutting forces, surface roughness, top burr height and chips morphology analysis.

Experimental Work

Experiments are conducted using the statistical design of experiment approach in order to characterize the influence of feed per tooth on cutting forces, surface roughness, top burr height and chips morphology and the results are compared for both titanium-based materials including pure titanium and titanium alloy (Ti-6Al-4V).

Material and experimental apparatus

Pure titanium (CP-Ti) grade 2 and Ti-6Al-4V workpieces were prepared from annealed bars. Microstructures of both materials were analysed under an optical microscope after a chemical attack with Kroll's reagent and are shown in Fig. 1. It can be seen that pure titanium is composed by equiaxed coarse alpha grains with dimension in the order of 20-30 µm. Titanium alloy presents equiaxed alpha grains mixed with alpha/beta small regions in between them. Mechanical properties of CP-Ti grade 2 and Ti-6Al-4V were obtained from literature [START_REF] Froum | Dental Implant Complications: Etiology, Prevention, and Treatment[END_REF]. These include flexural modulus of 105 GPa and flexure strength 345 MPa, for pure titanium whereas Ti-6Al-4V has flexural modulus of 105 GPa and flexural strength of 900 MPa. Vickers hardness tests were also carried out for both materials using loads of 30 kgf for cycles of 20 s. The hardness values for pure titanium and Ti-6Al-4V were found to be 168 HV30 and 318 HV30, respectively.

The micromilling experiments were performed on a CNC Mini-mill/GX using 500 µm carbide squareend-mills with 2 flutes. The microtools were analysed under a Zeiss scanning electron microscope, model DSM 940. The measurements yielded the cutting edge re radius of 2-2.5 µm, corner radius of 10 µm and helix angle of 26° as can be seen in Fig. 2. For force measurements, the Kistler dynamometer MiniDyn 9256C2, the Kistler charge amplifier 5070A10100 and the data acquisition board USB 6251 from National Instruments were used. Figure 3 shows the axis configuration of force measurements in relation to the workpiece. Force results were analysed using the average of the maximum resultant force per tool revolution for 40 revolutions Three roughness measurements were performed along the feed direction on the bottom surface of each machined groove as showed in Fig. 4. Cut-off filter used was 0.08, according to ISO 4288-1996.

Top burr height measurement was performed by taking the profile of each groove as showed in Fig. 5. Five measurements in different positions along the groove were made. Also, SEM images were used to visually analyse burr formation. Chips were collected in all experiments. For the chips morphology and grooves surface analysis SEM and USB AM3715TB Dino-Lite Edge handheld digital microscope images were used.

Experimental procedure

Before the actual experiments, the workpieces were pre-machined to avoid axial depth of cut variation. The cutting speed of 37.7 m/min. (4000 rpm), feed of 120 m/min. (feed per tooth of 0.015 mm) and axial depth of cut of 30 µm with a 3 mm diameter tool were employed in machining tests.

Feed per tooth range considering the cutting edge radius value (re = 2.0-2.5 µm) was chosen in order to clearly detect both ploughing and shearing regions. The cutting speed, axial depth of cut and cutting length were kept constant during machining. The full immersion machining was chosen so that the tool would engage in both up and down milling. The cutting parameters are shown in Table 1.

In order to study the tool wear influence on the measured outputs, the tests were conducted in two batches. The tests in batch A were performed with increasing feed per tooth and the tests in batch B were done with decreasing feed per tooth, as shown in Table 2.

Results and Discussion

In this section, the machinability measures including cutting forces, surface roughness, top burr height and chip morphology are analysed as a function of feed per tooth in micro-milling of both pure titanium and titanium alloy. It can be seen, as expected, titanium alloy with aluminium and vanadium presented higher strength and hardness than pure titanium.

Cutting forces analysis

Maximum resultant force results for batches A and B for CP-Ti and Ti-6Al-4V are shown in Fig. 6. The error bars in Fig. 6 represent +/-1.96σ and they correspond to a 95% confidence interval. For both materials, there was a significant difference between the batches, indicating that tool wear probably had a significant influence on force results. The influence of feed per tooth on machining forces was found to be as expected. The higher forces are seen with increasing feed per tooth since the chip area increases with feed.

Further, due to its higher mechanical resistance and hardness, titanium alloy presented higher forces for both batches. However, it can be seen that difference between the batches was higher for the titanium alloy, indicating the tool wear had more influence for this material.

Surface roughness analysis

Figure 7 presents the influence of feed per tooth on surface roughness for pure titanium and titanium alloy, considering both batches of experiments. Three regions with different trends can be identified in the figure . In Region I, between feeds of 0.5 to 1.5 µm/th, the roughness decreased when feed per tooth is increased. In Region II, between 1.5 and 3.5 µm/tooth, it can be seen that the roughness initially increased and then decreased or maintained at the same level. In Region III, between 3.5 and 4.0 µm/tooth, the roughness showed a rapid growth for higher feed values. The Region I in Fig. 7 shows a decrease in roughness when feed/tooth is small, because in this region, the ploughing phenomenon occurs, where the material is plastically deformed rather than removed by shearing. The Region II presents a transition phase from ploughing to shearing and has feed values around the cutting edge radius (re = 2.0-2.5 µm). The Region III corresponds to pure shearing and roughness presents behaviour similar to the conventional macro milling, where roughness increases for higher feed values.

Also, it can be seen in Fig. 7, a large variation in roughness value for some feed values between batches A and B. This can be related to the fact that roughness is deeply connected to the corner radius of the tool and can vary with tool wear. Regarding the comparison of roughness values between pure titanium and Ti-6Al-4V, it can be seen that there is no significance difference in roughness results between the two materials.

Top burr height analysis

For the top burr height results, the average was computed between the batches for up and down milling as burr measurements are found inherently noisy. The results are presented in Fig. 8. It can be seen that, in general, up milling presented a better result in terms of lower top burr height than down milling, which is also confirmed by SEM images of machined channels (Fig. 9) for both materials. The lower burr formation in up milling can be explained by the fact that in up milling chip thickness starts with small values meaning that a small volume of material is being deformed and removed. When the tool is in the down milling region, a higher volume of material, which has already been deformed, generates the top burr. Figure 8 indicates that top burr values are higher for small feeds per tooth, which can also be confirmed by observing the SEM images in Fig. 9. Indeed, higher feeds lead to smaller top burr heights. This happens because as feed per tooth decreases and gets closer to the cutting edge radius, shearing of the material starts to be replaced by ploughing mechanism where the material is plastically deformed more than machined through shearing. By comparing the burr height results of CP-Ti with Ti-6Al-4V, it can be seen that the results are similar with the exception of a few specific points and no significant difference could be determined.

Chips morphology analysis

Microchips images for the pure titanium and titanium alloy obtained from the experiments using the feed per tooth of 0.5 and 4.0 µm/toot, are shown in Fig. 10. Analysing the images, it can be seen that lower feeds generated long and continuous chips. When increasing feed per tooth, microchips became very short going from a length of more than 1 mm for 0.5 µm feed per tooth to around 200 µm for 4 µm/tooth. Usually, short chips are preferred in machining, as long chips can roll up the tool and have more chances to be cut again during the process, which can prejudice surface finish. Also, chips are responsible for removing heat from the cutting region. Therefore, the longer a chip takes to break away, the longer it requires to remove heat and cool the toolmaterial contact region. However, the chip length rapidly decreased after machining with feeds above 1.5 µm/tooth. The long chips for the small feeds probably happened because the chip thickness is given by the feed per tooth. The thicker the chips, more difficult it is for them to curl while in contact with the rake surface of the microtool. Probably, the chips break when they start to curl during the cutting process.

For titanium alloy, the chip length decreased with increasing feed per tooth varying from a length of around 0.5 mm for 0.5 µm feed per tooth to around 200 µm for 4 µm/tooth. Feeds higher than 2.0 µm/tooth showed smaller chips. For 0.5 and 1.0 µm/tooth feeds, despite them being longer than for other feeds, the chips are found curly in shape, which is a more desirable shape than the snarled one as they are less likely to cause damage to the tool or the machined surface.

Conclusions

This work presented a comparison between the micromilling machinability of pure titanium and Ti-6Al-4V at different feeds per tooth (from 0.5 to 4.0 µm/th). The machinability measures included the cutting forces, surface roughness, top burr height and chips morphology. The following conclusions can be drawn from this study:

• Titanium alloy presented higher strength and hardness, but similar elastic modulus as pure titanium. The mechanical properties directly influenced the forces during micromilling processes. Cutting forces for titanium alloy were higher than for CP-Ti and results indicated a high influence of tool wear for machining Ti-6Al-4V;

• Surface roughness results show no significant difference between the two materials. The general behavior of the influence of feed per tooth on roughness identified the three cutting regimes: ploughing, transition from ploughing to shearing and shearing;

• Top burr height measurements indicated similar results for both pure titanium and titanium alloy. Also, up milling presented better results in terms of smaller top burr heights than down milling because in up milling a small volume of material is plastically deformed while in down milling a higher volume has the possibility of becoming burrs;

• Chips morphology results showed that for pure titanium, chips changed from a snarled long shape to short chips with increasing feed. For the titanium alloy, with higher feeds, the chips are found to be curly and short.

Fig. 1 .

 1 Fig. 1. Microstructure of pure titanium and Ti-6Al-4V.

Fig. 2 .

 2 Fig. 2. Cutting edge radius, helix angle and corner radius

Fig. 3 .

 3 Fig. 3. Cutting force measurement directions.

  profilometer Form Talysurf Intra120 with stylus 112/2009, and 2 µm corner radius was used.

Fig. 4 .Fig. 5 .

 45 Fig. 4. Surface roughness measurement.

Exp

  3.5; 3.0;2.5; 2.0;1.5;2.0;0.5 4 to each level of feed per tooth (0 to 32 mm)

Fig. 6 .

 6 Fig. 6. Experimental cutting force results.

Fig. 7 .

 7 Fig. 7. Surface roughness results.

Fig. 8 .

 8 Fig.8. Top burr height results for up and down milling.

Fig. 9 .

 9 Fig. 9. Scanning electron microscope images: a) CP-Ti -1.0 µm/th; b) CP-Ti -3.5 µm/th; c) Ti-6Al-4V -1.0 µm/th; d) Ti-6Al-4V -3.5 µm/th.

Fig. 10 .

 10 Fig. 10. Digital microscope images of chips: a) CP-Ti -0.5 µm/tooth; b) CP-Ti -4.0 µm/tooth; c) Ti-6Al-4V -0.5 µm/tooth; d) Ti-6Al-4V -4.0 µm/tooth.

Table 1 .

 1 Cutting data.

	Parameter	Value
	Tool diameter	500 µm
	Spindle speed	18000 rpm
	Cutting speed	28.3 m/min.
	Feed per tooth	0.5 -4.0 µm
	Axial depth of cut	40 µm
	Radial depth of cut	500 µm
	Cutting length	4 mm
	Cutting system	Dry cutting

Table 2 .

 2 Design of experiments.

Acknowledgements

The authors would like to acknowledge CNPq for the research resources used during the development of this work and for Sandwich Scholarship number 3602-15-0.


Fábio De Oliveira Campos

Anna Carla Araujo

Shiv Gopal Kapoor

Journal of Micro-and Nano-Manufacturing 1 Experimental Comparison of Micromilling Pure Titanium and Ti-6Al-4V

Pure titanium is the ideal metallic material to be used for producing dental implants due to its good corrosion resistance and biocompatibility. However, pure titanium does not present high mechanical resistance, which can be a limiting factor. Recently, the pure titanium is being replaced by titanium alloy with aluminum and vanadium . This study deals with micromilling machinability of pure titanium and Ti-6Al-4V considering mechanical properties, the forces measured during the process, surface roughness, top burr height, and chips morphology. The cutting tests are performed for the constant depth of cut and cutting speed, and a range of feed per tooth from 0.5 to 4.0 µm/tooth. Results show no significant differences in roughness and burr formation whereas higher forces are found for the titanium alloy compared to pure metal. Both materials produce long chips for smaller feeds.

INTRODUCTION

Pure titanium (CP-Ti) is the ideal titanium-based material to be used in the manufacturing of implants because of its properties: good corrosion resistance, biocompatibility and reasonable mechanical resistance [START_REF] Rack | Titanium alloys for biomedical applications[END_REF][START_REF] Niinomi | Mechanical biocompatibilities of titanium alloys for biomedical applications[END_REF]. However, due to fatigue failure the chances for a surgery for implant removal are seen to be increased [START_REF] Froum | Dental Implant Complications: Etiology, Prevention, and Treatment[END_REF]. The titanium alloy Ti-6Al-4V presents higher mechanical resistance preserving the essential properties for implants, However, several studies have reported that Ti-6Al-4V alloy might cause some long-term health problems to the patient due to the release of aluminum and vanadium inside the person organism. Diseases like Alzheimer, neuropathy and osteomalacia have been reported as long-term consequences of the presence of these elements in the body of patients as they remain in the human body for several years [START_REF] Mjöberg | Aluminum, Alzheimer's disease and bone fragility[END_REF]. Zaffe et al. [START_REF] Zaffe | Accumulation of aluminium in lamellar bone after implantation of titanium plates, Ti-6Al-4V screws, hydroxyapatite granules[END_REF] analyzed titanium plates and Ti-6Al-4V screws removed from patients that presented local inflammation and biopsies. They found out indications that biological perturbations may be related to aluminum release from the tested biomaterials. Titanium based metals are considered difficult-to-machine materials, especially due to their low thermal conductivity [START_REF] Ezugwu | Titanium alloys and their machinability -a review[END_REF][START_REF] Veiga | Review on Machinability of Titanium Alloys: The Process Perspective[END_REF]. Kikuchi [START_REF] Kikuchi | The use of cutting temperature to evaluate the machinability of titanium alloys[END_REF] performed an experimental study where the cutting temperature was estimated by measuring the thermal electromotive force a tool-workpiece thermocouple during milling of four different dental materials: pure titanium, Ti-6Al-4V, Ti-6Al-7Nb and brass. A high difference between the cutting temperature of the alloys and pure titanium was detected due to the low thermal conductivity. Micromilling of titanium alloys presents the same difficulties of the mesoscale process, but with the additional factor of size effect. In micromilling, cutting edge radius dimension is often of similar dimension to the undeformed chip thickness. This change of the cutting mechanics leads to the appearance of the minimum chip thickness, below which there would be no actual material cutting, but only the plastic deformation of the material followed by elastic recovery, phenomenon called ploughing [START_REF] Chae | Investigation of micro-cutting operations[END_REF]. Rezaei et al. [START_REF] Rezaei | Determination of minimum uncut chip thickness under various machining conditions during micro-milling of Ti-6Al-4V[END_REF] aimed to define the minimum chip thickness of Ti-6Al-4V alloy during micromilling by analyzing cutting forces, specific cutting forces, surface roughness and the grooves surface images. The transition from ploughing to shearing was different when analyzing forces (6-12 μm/tooth) and roughness (1.5-6 μm/tooth). Titanium alloy Ti-6Al-4V has been extensively studied in recent years. Carou et al. [START_REF] Carou | Latest advances in the micromilling of titanium alloys: a review[END_REF] produced a review on micromilling of titanium and its alloys. It summarizes the main published papers on topics like surface integrity, cutting tools, cooling systems and finite element modelling. Özel et al. [START_REF] Özel | Micro milling of titanium alloy Ti-6Al-4V: 3-D finite element modeling for prediction of chip flow and burr formation[END_REF] developed a finite element model to predict burr formation in micromilling of Ti-6Al-4V alloy considering the variation of the cutting edge radius. As titanium is a difficult to machine material, it wears the tool quickly. Therefore, they analyzed the variation of the edge radius with cutting length and its influence in top burr height and concluded that a bigger cutting edge radius leads to higher burr formation. Cheng et al. [START_REF] Cheng | Experimental study on a novel minimization method of top burr formation in micro-end milling of Ti-6Al-4V[END_REF] developed a method for minimization of burr formation in micromilling of Ti-6Al-4V by coating the surface to be machined with a resin and then removing it. In the experimental validation of the method, their results showed that feeds per tooth smaller than minimum chip thickness presented higher burr formation for down milling cutting. Also, they found out that feed per tooth is the main parameter influencing top burr size. Thepsonthi and Ozel [START_REF] Thepsonthi | Multi-objective process optimization for micro-end milling of Ti-6Al-4V titanium alloy[END_REF] applied an experimental design based on Taguchi method to verify the optimal cutting conditions for micromilling Ti-6Al-4V alloy. They used three factors (feed per tooth, spindle speed and depth of cut) with three levels each. They analyzed burr formation and surface roughness. Their result showed that higher feed rates lead to better surface finishing and higher depths of cut lead to less burr formation. However, most published papers do not cover machinability criteria as a whole like surface roughness, burr formation, cutting forces, tool wear etc. Kim et al. [START_REF] Kim | Experimental Study on Machinability of Ti-6Al-4V in Micro End-Milling[END_REF] developed one of the most complete published works on micromilling machinability of Ti-6Al-4V. They analyzed the effects of cutting speed and feed per tooth in cutting forces, surface roughness, burr formation and microchips morphology and found out that lower feeds lead to higher burrs and that cutting speed did not present a big influence in burr formation. Also, they found that increased cutting speed lead to smoother surface finishing as well as higher feeds. However, their study lacked a material characterization which could explain some of the results they presented. There is also almost no study dealing with machinability of pure titanium in micromilling. Therefore, there is a lack of a complete study aiming to fully characterize the machinability characteristics of Ti-6Al-4V and pure titanium. The present work compares the micromilling machinability of pure titanium grade 2 and Ti-6Al-4V in different feed per tooth analyzing cutting forces, surface roughness, top burr height and chips morphology analysis.

EXPERIMENTAL WORK

Experiments are conducted using the statistical design of experiment approach in order to characterize the influence of feed per tooth on cutting forces, surface roughness, top burr height and chips morphology and the results are compared for both titanium-based materials including pure titanium and titanium alloy (Ti-6Al-4V).

Material and experimental apparatus

Two workpiece types were used: annealed commercial pure titanium (CP-Ti) grade 2 and annealed commercial Ti-6Al-4V. The initial workpiece dimensions are 50 x 25,4 x 5 mm.. Microstructures of both materials were analysed under an optical microscope after a chemical attack with Kroll's reagent and are shown in Fig. 1. It can be seen that pure titanium is composed by equiaxed coarse alpha grains with dimension in the order of 20-30 µm. Titanium alloy presents equiaxed alpha grains mixed with alpha/beta small regions in between them. Mechanical properties of CP-Ti grade 2 and Ti-6Al-4V were obtained from literature [START_REF] Chae | Investigation of micro-cutting operations[END_REF]. These include flexural modulus of 105 GPa and flexure strength 345 MPa, for pure titanium whereas Ti-6Al-4V has flexural modulus of 105 GPa and flexural strength of 900 MPa. Vickers hardness tests were also carried out for both materials using loads of 30 kgf for cycles of 20 s. The hardness values for pure titanium and Ti-6Al-4V were found to be 168 HV30 and 318 HV30, respectively. The micromilling experiments were performed on a CNC Mini-mill/GX using 500 µm Mitsubishi Materials (MS2MSD0050) carbide square end mills without coating and with rake angle of 30°. The microtools were analyzed under a Zeiss scanning electron microscope, model DSM 940. The measurements yielded the cutting edge r e radius of 2-2.5 µm, corner radius of 10 µm and helix angle of 26° as can be seen in Fig. 2. For force measurements, the Kistler dynamometer MiniDyn 9256C2, the Kistler charge amplifier 5070A10100 and the data acquisition board USB 6251 from National Instruments were used. Figure 3 shows the axis configuration of force measurements in relation to the workpiece. Cutting force signals were analyzed using a fast Fourier transform (FFT) in order to identity if there is no influence of frequency band of interest and remove noise out of this range. After filtering, the average of the maximum resultant force per tool revolution for 40 revolutions is evaluated for each experiment. For roughness and top burr height measurements, a profilometer Form Talysurf Intra120 with stylus 112/2009 with 2 µm corner radius was used. Three roughness measurements were performed along the feed direction on the bottom surface of each machined groove as showed in Fig. 4. Cut-off filter used was 0.08, according to ISO 4288-1996. Top burr height measurement was performed by taking the profile of each groove as showed in Fig. 5. Five measurements in different positions along the groove were made. Also, SEM images were used to visually analyze burr formation. Chips were collected in all experiments. For the chips morphology and grooves surface analysis SEM and USB AM3715TB Dino-Lite Edge handheld digital microscope images were used.

Experimental procedure

Before the actual experiments, the workpieces were pre-machined to avoid axial depth of cut variation. The cutting speed of 37.7 m/min. (4000 rpm), feed rate of 120 m/min. (feed per tooth of 0.015 mm) and axial depth of cut of 30 µm with a 3 mm diameter tool were employed in machining tests. Feed per tooth range considering the cutting edge radius value (r e = 2.0-2.5 µm) was chosen in order to clearly detect both ploughing and shearing regions as minimum uncut chip thickness for these materials lies between 1.5 and 3 µm. The cutting speed, axial depth of cut and cutting length were kept constant during machining. The full immersion machining was chosen so that the tool would engage in both up and down milling. The Fx direction of the dynamometer is aligned with feed direction The cutting parameters are shown in Table 1. In order to study the tool wear influence on the measured outputs, the tests were conducted in two batches. The tests in batch A were performed with increasing feed per tooth and the tests in batch B were done with decreasing feed per tooth, as shown in Table 2.

RESULTS AND DISCUSSION

In this section, the machinability measures including cutting forces, surface roughness, top burr height and chip morphology are analyzed as a function of feed per tooth in micro-milling of both pure titanium and titanium alloy. It can be seen, as expected, titanium alloy with aluminum and vanadium presented higher strength and hardness than pure titanium.

Cutting forces analysis

Maximum resultant force results for batches A and B for CP-Ti and Ti-6Al-4V are shown in Fig. 6. The error bars in Fig. 6 represent +/-1.96σ and they correspond to a 95% confidence interval. For both materials, there was a significant difference between the batches, indicating that tool wear probably had a significant influence on force results. The influence of feed per tooth on machining forces was found to be as expected. The higher forces are seen with increasing feed per tooth since the chip area increases with feed. Also, variation on cutting force values was higher for feed per tooth from 2.5 to 4 µm/tooth as seen by the error bars. This was due to vibration on the machine-tool when volume of chip removal was increased. Further, due to its higher mechanical resistance and hardness, titanium alloy presented higher forces for both batches. However, it can be seen that differences between the batches was higher for the titanium alloy, indicating the tool wear had more influence for this material.

Surface roughness analysis

Figure 7 presents the influence of feed per tooth on surface roughness for pure titanium and titanium alloy, considering both batches of experiments. Three regions with different trends can be identified in the figure. In Region I, between feeds of 0.5 to 1.5 µm/tooth, the roughness decreased when feed per tooth is increased. In Region II, between 1.5 and 3.5 µm/tooth, it can be seen that the roughness initially increased and then decreased or maintained at the same level. In Region III, between 3.5 and 4.0 µm/tooth, the roughness showed a rapid growth for higher feed values.

The Region I in Fig. 7 shows a decrease in roughness when feed/tooth is small, because in this region, the ploughing phenomenon occurs, where the material is plastically deformed rather than removed by shearing. The Region II presents a transition phase from ploughing to shearing and has feed values around the cutting edge radius (r e = 2.0-2.5 µm). The Region III corresponds to pure shearing and roughness presents behavior similar to the conventional macro milling, where roughness increases for higher feed values. Also, it can be seen in Fig. 7, a large variation in roughness value for some feed values between batches A and B. This can be related to the fact that roughness is deeply connected to the corner radius of the tool and can vary with tool wear. Regarding the comparison of roughness values between pure titanium and Ti-6Al-4V, it can be seen that there is no significance difference in roughness results between the two materials.

Top burr height analysis

For the top burr height results, the average was computed between the batches for up and down milling as burr measurements are found inherently noisy. The results are presented in Fig. 8. It can be seen that, in general, up milling presented a better result in terms of lower top burr height than down milling, which is also confirmed by SEM images of machined channels (Fig. 9) for both materials. The lower burr formation in up milling can be explained by the fact that in up milling chip thickness starts with small values meaning that a small volume of material is being deformed and removed. When the tool is in the down milling region, a higher volume of material, which has already been deformed, generates the top burr. Figure 8 indicates that top burr values are higher for small feeds per tooth, which can also be confirmed by observing the SEM images in Fig. 9. Indeed, higher feeds lead to smaller top burr heights. This happens because as feed per tooth decreases and gets closer to the cutting edge radius, shearing of the material starts to be replaced by ploughing mechanism where the material is plastically deformed more than machined through shearing. By comparing the burr height results of CP-Ti with Ti-6Al-4V, it can be seen that the results are similar with the exception of a few specific points and no significant difference could be determined.

Chips morphology analysis

Microchips images for the pure titanium and titanium alloy obtained from the experiments using the feed per tooth of 0.5 and 4.0 µm/toot, are shown in Fig. 10. Analysing the images, it can be seen that lower feeds generated long and continuous chips. When increasing feed per tooth, microchips became very short going from a length of more than 1 mm for 0.5 µm feed per tooth to around 200 µm for 4 µm/tooth. Usually, short chips are preferred in machining, as long chips can roll up the tool and have more chances to be cut again during the process, which can prejudice surface finish. Also, chips are responsible for removing heat from the cutting region. Therefore, the longer a chip takes to break away, the longer it requires to remove heat and cool the tool-material contact region. However, the chip length rapidly decreased after machining with feeds above 1.5 µm/tooth. The long chips for the small feeds probably happened because the chip thickness is given by the feed per tooth. The thicker the chips, more difficult it is for them to curl while in contact with the rake surface of the microtool. Probably, the chips break when they start to curl during the cutting process. For titanium alloy, the chip length decreased with increasing feed per tooth varying from a length of around 0.5 mm for 0.5 µm feed per tooth to around 200 µm for 4 µm/tooth. Feeds higher than 2.0 µm/tooth showed smaller chips. For 0.5 and 1.0 µm/tooth feeds, despite them being longer than for other feeds, the chips are found curly in shape, which is a more desirable shape than the snarled one as they are less likely to cause damage to the tool or the machined surface.

CONCLUSIONS

This work presented a comparison between the micromilling machinability of pure titanium and Ti-6Al-4V at different feeds per tooth (from 0.5 to 4.0 µm/tooth). The machinability measures included the cutting forces, surface roughness, top burr height and chips morphology. The following conclusions can be drawn from this study: • Titanium alloy presented higher strength and hardness, but similar elastic modulus as pure titanium. The mechanical properties directly influenced the forces during micromilling processes. Cutting forces for titanium alloy were higher than for CP-Ti and results indicated a high influence of tool wear for machining Ti-6Al-4V; • Surface roughness results show no significant difference between the two materials. The general behavior of the influence of feed per tooth on roughness identified the three cutting regimes: ploughing, transition from ploughing to shearing and shearing; • Top burr height measurements indicated similar results for both pure titanium and titanium alloy. Also, up milling presented better results in terms of smaller top burr heights than down milling because in up milling a small volume of material is plastically deformed while in down milling a higher volume has the possibility of becoming burrs; • Chips morphology results showed that for pure titanium, chips changed from a snarled long shape to short chips with increasing feed. For the titanium alloy, with higher feeds, the chips are found to be curly and short.

ACKNOWLEDGMENT

The authors would like to acknowledge CNPq for the research resources used during the development of this work and for Sandwich Scholarship number 3602-15-0.


Pierre Thouvenot

Guillaume Vales

Hélène Bracq-Dieye

Nathalie Tessaud-Rita

Alexandra Moura

Mylène M Maury

Marc Lecuit
email: marc.lecuit@pasteur.fr

Alexandre Leclercq
email: alexandre.leclercq@pasteur.fr

MALDI-TOF mass spectrometry-based identification of Listeria species in surveillance: a prospective study

Keywords: Listeria identification, MALDI-TOF, mass spectrometry, food, public health surveillance

This study aimed to evaluate MALDI-TOF MS for species discrimination of Listeria in the context of routine surveillance. MALDI-TOF MS yielded 100% accuracy for the identification of L. monocytogenes, L. innocua, L. ivanovii, L. fleischmannii, L. grayi, L. seeligeri, L. weihenstephanensis and L. welshimeri, as confirmed by whole genome analyses.

Highlights

 MALDI-TOF MS correctly identifies human pathogenic Listeria species.

 Prospective collected isolates (n=1,201) were identified with 100% of accuracy.

 Reliable identification is linked to a good quality reference library of MALDI-TOF MS spectra.

 MALDI-TOF MS is a fast and cost-effective tool for routine Listeria identification.

Listeria monocytogenes is a Gram-positive bacillus and the cause of listeriosis, a severe human foodborne infection (Vazquez-Boland et al., 2001). It belongs to the genus Listeria, which currently includes 17 species: L. aquatica, L. booriae, L. cornellensis, L. fleischmannii, L. floridensis, L. grandensis, L. grayi, L. innocua, L. ivanovii, L. marthii, L. monocytogenes, L. newyorkensis, L. riparia, L. rocourtiae, L. seeligeri, L. weihenstephanensis and L. welshimeri [START_REF] Orsi | Characteristics and distribution of Listeria spp., including Listeria species newly described since 2009[END_REF]. Of these, five are routinely isolated from food: L. monocytogenes, L. innocua, L. ivanovii, L. seeligeri, and L. welshimeri, but only L. monocytogenes, and rarely L. ivanovii, are of medical concern [START_REF] Guillet | Human listeriosis caused by Listeria ivanovii[END_REF]. In the context of Listeria surveillance, it is therefore critical to use an accurate, simple, rapid and cost-effective method to distinguish between these species. Current identification tools, such as API-Listeria (bioMérieux, Marcy l'Etoile, France) [START_REF] Bille | API Listeria, a new and promising one-day system to identify Listeria isolates[END_REF], PCR serogrouping [START_REF] Doumith | Differentiation of the major Listeria monocytogenes serovars by multiplex PCR[END_REF] and 16S rRNA gene sequencing [START_REF] Sontakke | Use of broad range16S rDNA PCR in clinical microbiology[END_REF] are expensive and time-consuming.

Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) has become a reliable tool for bacterial identification in clinical microbiology [START_REF] Angeletti | Matrix assisted laser desorption time of flight mass spectrometry (MALDI-TOF MS) in clinical microbiology[END_REF]. The identification accuracy, low cost of reagents/consumables per sample after purchasing and maintenance of equipment, and speed of data acquisition are the most prominent advantages of this technology. MALDI-TOF MS has been successfully used for the detection of L. monocytogenes from selective enrichment broth [START_REF] Jadhav | Detection of Listeria monocytogenes from selective enrichment broth using MALDI-TOF Mass Spectrometry[END_REF], rapid identification of Listeria species [START_REF] Barbuddhe | Rapid identification and typing of Listeria species by matrix-assisted laser desorption ionization-time of flight mass spectrometry[END_REF][START_REF] Rychert | Multicenter evaluation of the Vitek MS matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of Gram-positive aerobic bacteria[END_REF][START_REF] Hsueh | Bruker biotyper matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of Nocardia, Rhodococcus, Kocuria, Gordonia, Tsukamurella, and Listeria species[END_REF][START_REF] Jadhav | Rapid identification and source-tracking of Listeria monocytogenes using MALDI-TOF mass spectrometry[END_REF][START_REF] Ojima-Kato | Matrix-assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Can Precisely Discriminate the Lineages of Listeria monocytogenes and Species of Listeria[END_REF], discrimination of lineages [START_REF] Ojima-Kato | Matrix-assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Can Precisely Discriminate the Lineages of Listeria monocytogenes and Species of Listeria[END_REF] and subtyping of Listeria monocytogenes [START_REF] Barbuddhe | Rapid identification and typing of Listeria species by matrix-assisted laser desorption ionization-time of flight mass spectrometry[END_REF][START_REF] Jadhav | Rapid identification and source-tracking of Listeria monocytogenes using MALDI-TOF mass spectrometry[END_REF][START_REF] Ojima-Kato | Matrix-assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Can Precisely Discriminate the Lineages of Listeria monocytogenes and Species of Listeria[END_REF]. Previous studies used the Andromas MALDI-TOF MS system (Paris, France) [START_REF] Farfour | Evaluation of the Andromas matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of aerobically growing Gram-positive bacilli[END_REF], the Shimadzu Corporation MALDI-TOF MS system (Kyoto, Japan) [START_REF] Jadhav | Detection of Listeria monocytogenes from selective enrichment broth using MALDI-TOF Mass Spectrometry[END_REF][START_REF] Jadhav | Rapid identification and source-tracking of Listeria monocytogenes using MALDI-TOF mass spectrometry[END_REF][START_REF] Ojima-Kato | Matrix-assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Can Precisely Discriminate the Lineages of Listeria monocytogenes and Species of Listeria[END_REF] or the Vitek MALDI-TOF MS system (bioMérieux, Marcy l'Etoile, France) [START_REF] Rychert | Multicenter evaluation of the Vitek MS matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of Gram-positive aerobic bacteria[END_REF], and did not exhibit high species identification accuracy.

The Bruker Daltonics (Bremen, Germany) MALDI-TOF MS system has been used with success, but on a limited number of phenotypically identified strains and to establish mass spectral fingerprints of some reference strains (Barbuddheet al., 2008;[START_REF] Hsueh | Bruker biotyper matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of Nocardia, Rhodococcus, Kocuria, Gordonia, Tsukamurella, and Listeria species[END_REF].

In the context of a National Reference Centre for Listeria, that receives around 1,800 Listeria isolates per year from clinical (20%) and food (80%) origins, we evaluated the Bruker Daltonics system of MALDI-TOF MS Biotyper as a method for rapid identification of L. monocytogenes and the 16 other Listeria spp. described until now. We also compared the results to phenotypicbased identification. We first performed a validation study, and then used this system prospectively in the context of Listeria surveillance in France. Its accuracy was confirmed by bacterial identification using average nucleotide identity BLAST (ANIb) determined from whole genome sequences [START_REF] Goris | DNA-DNA hybridization values and their relationship to whole-genome sequence similarities[END_REF].

A validation set of 386 Listeria strains representative of Listeria genus and L. monocytogenes diversity [START_REF] Chenal-Francisque | Clonogrouping, a Rapid Multiplex PCR Method for Identification of Major Clones of Listeria monocytogenes[END_REF] was first analyzed (Table 1). A particular focus was given to L. monocytogenes (n=353), to fully cover the diversity of this species, which is the main common pathogenic Listeria isolated in clinical and food microbiological laboratories and responsible for human listeriosis. In addition, a set of 34 non-Listeria isolates corresponding to frequent contaminants often phenotypically misidentified as Listeria were used as negative controls (Table 2). A prospective analysis was then carried out for all the Listeria strains received at the French National Reference Center of Listeria (NRCL) in 2016 (n=1,201, Table 3).

Strains were grown overnight (18h) on Brain Heart Infusion (BHI; Becton Dickinson Difco, Franklin Lakes, USA) agar plates at 35°C. The samples were prepared by full protein extraction and analysed according to the Bruker Daltonics instructions. As described in previous studies [START_REF] Barbuddhe | Rapid identification and typing of Listeria species by matrix-assisted laser desorption ionization-time of flight mass spectrometry[END_REF][START_REF] Hsueh | Bruker biotyper matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of Nocardia, Rhodococcus, Kocuria, Gordonia, Tsukamurella, and Listeria species[END_REF][START_REF] Capocefalo | MALDI-TOF MS: a rapid microbiological confirmation technique for food and water analysis[END_REF], this full protein extraction was crucial to obtain reliable Listeria identification to the species level (data not shown). Briefly, colonies were transferred into a 2-ml screw-cap extraction tube (Eppendorf, Germany) containing 300 μl of distilled water and then mixed with 900 μl of absolute ethanol by pipetting. The suspension was pelleted by centrifugation at 13,000 rpm for 2 min, air dried, and then reconstituted with 50 μl of 70% formic acid (Sigma-Adlrich, Darmstadt, Germany) before the addition of 50 μl of acetonitrile (Sigma-Aldrich) to the mixture [START_REF] Bizzini | Performance of matrixassisted laser desorption ionization-time of flight mass spectrometry for identification of bacterial strains routinely isolated in a clinical microbiology laboratory[END_REF]. The mixture was then centrifuged at 13,000 rpm for 2 min. Next, 1 µL of the supernatant was deposited in duplicate spots onto a polished steel MALDI-TOF MS target plates (Bruker Daltonics, Bremen, Germany) and air dried at room temperature. As quality control system, 1 µL of Bruker Bacterial Test Standard (BTS; Bruker Daltonics) was also used at the beginning and end of every series of samples. Dried spots were overlaid with 1 µl of a HCCA matrix (a saturated solution of α-cyano-4-hydroxycinnamic acid (HCCA) in acetonitrile 50%, water 47.5% and trifluoroacetic acid 2.5%; Bruker Daltonics) and let air dry again at room temperature according to manufacturer's instructions (Bruker Daltonics). The MALDI-plate was inserted into the source of a microFlex LT/SH MALDI-TOF MS instrument (Bruker Daltonics) with a 60-Hz nitrogen laser (337 nm wavelength) and automatically read. The spectra were collected in the linear positive mode in a mass range covering m/z 1,960-20,132 in the FlexControl v3.4 software (Bruker Daltonics). All spectra ranging from the mass-to-charge ratio (m/z) 2,000-20,000, corresponding to the resulting ribosomal protein profiles, were analyzed using the MALDI BioTyper (MBT) compass explorer software v4.1.60 (Bruker Daltonics) and compared to reference spectra of the MALDI BioTyper Reference library (database [DB-5989] MS; Bruker Daltonics) for automatic identification. The whole treatment from processing acquired spectra to identification was performed automatically without user intervention using the integrated pattern matching algorithm of the software [START_REF] Barbuddhe | Rapid identification and typing of Listeria species by matrix-assisted laser desorption ionization-time of flight mass spectrometry[END_REF]. Scores of ≥2.000 indicated species-level identification, scores of 1.700-1.999 indicated genus-level identification, and scores of <1.699 indicated no reliable identification. For each isolate, 2 spots were submitted to two analyses to obtain at least 4 identical and reliable scores results (2.0 ≤ score ≤ 3.0). Automatized bacterial identification were valid if the BTS was identified as Escherichia coli DH5-alpha. All isolates with discrepant identification results between the molecular and Bruker Biotyper methods were tested twice.

Conventional identification was carried out by API-Listeria (bioMérieux) combined with hemolysis test on horse blood agar according to manufacturer's instructions [START_REF] Bille | API Listeria, a new and promising one-day system to identify Listeria isolates[END_REF].

PCR serogrouping of Listeria isolates was determined by a multiplex PCR and interpreted as described by [START_REF] Doumith | Differentiation of the major Listeria monocytogenes serovars by multiplex PCR[END_REF] and [START_REF] Leclercq | Characterization of the novel Listeria monocytogenes PCR serogroupingprofile IVb-v1[END_REF]. Genome sequences were obtained after DNA extraction (DNeasy Blood & Tissue kit, Qiagen, Denmark), library preparation (Nextera XT DNA Sample kit, Illumina, California, USA) and sequencing using NextSeq 500 ( 2x 150 bp) platform (Illumina, California, USA), according to the manufacturer's protocol.

Sequence assemblies were built using CLC Assembly Cell 4.3.0. (Qiagen, Hilden, Germany) from FqCleaner filtered reads with an average read coverage higher than 40X, as described previously [START_REF] Moura | Real-time whole-genome sequencing for surveillance of Listeria monocytogenes, France[END_REF]. Genome-based species identification was determined by average nucleotide identity BLAST (ANIb) analysis against the Listeria species reference genomes deposited at NCBI database (https://www.ncbi.nlm.nih.gov), as described previously [START_REF] Goris | DNA-DNA hybridization values and their relationship to whole-genome sequence similarities[END_REF]. The congruence between MALDI identification results and those obtained by classical reference methods and whole genome sequencing was evaluated.

The accuracy of MALDI-TOF identification results is shown in Table 1. Unambiguous identification at the species level was obtained for the 8 most frequently isolated species: L. monocytogenes (353/353), L. welshimeri (3/3), L. innocua (4/4), L. ivanovii (4/4), L. fleischmannii (3/3), L. grayi (2/2), L. seeligeri (4/4), and L. weihenstephanensis (1/1). For strains with subspecies variants (L. ivanovii, L. fleischmannii and L. grayi), MALDI-TOF MS provided a correct species identification, but not at the sub-species level. As expected, since the corresponding reference profiles are absent from the current version of MALDI Biotyper reference library, unreliable identification was obtained for L. grandensis, L. rocourtiae, L. aquatica, L. cornellensis, L. riparia, L. floridensis, L. booriae and L. newyorkensis. These last species could not be identified by API-Listeria. Of note, these species have never been isolated in the context of Listeria surveillance in France. Finally, L. marthii, a rarely isolated species, was always misidentified as L. monocytogenes with acceptable scores, also due to the lack of reference profile for this species in the database. None of the negative controls were misidentified as Listeria species (Table 2).

We then applied this method for the prospective identification of 1,201 strains received in the context of Listeria national surveillance in France from April 2016 to December 2016 (Table 3). These strains were isolated from human (n=299), food (n=731), environmental (n=155), animal (n=2) or unknown origin from owncheck food manufacturers (n=14) samples. In total, 5 species were correctly identified at the species level and included L. monocytogenes (n=1,112), L. innocua (n=65), L. welshimeri (n=20), L. seeligeri (n=3) and L. ivanovii (n=1) isolates. All isolates were correctly identified by MALDI-TOF MS at the species level, as confirmed by ANIb identification from whole genome sequence analysis. This work demonstrates the complete reliability of MALDI-TOF mass spectrometry as a rapid (less than 40 minutes) approach for the identification of Listeria in human, animal, food, and environmental microbiology, with 100% of accuracy for L. monocytogenes, L. innocua, L. ivanovii, L. fleischmannii, L. grayi, L. seeligeri, L. weihenstephanensis and L. welshimeri identification. This study also underlines the importance of a good quality and continuously updated reference MBT library for accurate identification of Listeria.

Vazquez-Boland, J.A., Kuhn, M., Berche, P., Chakraborty, T., Dominguez-Bernal, G., Goebel, W., Gonzalez-Zorn, B., Wehland, J., Kreft, J., 2001. Listeria pathogenesis and molecular virulence determinants. Clin. Microbiol. Rev. 14, 584-640. a according to [START_REF] Doumith | Differentiation of the major Listeria monocytogenes serovars by multiplex PCR[END_REF] and [START_REF] Leclercq | Characterization of the novel Listeria monocytogenes PCR serogroupingprofile IVb-v1[END_REF]. PCR serogroup L comprised strains of serovars 4a, 4ab, 4c of L. monocytogenes and other species, except L. booriae, L. cornellensis, L. grandensis, L. newyorkensis, L. riparia, L. rocourtiae, and L. weihenstephanensis.

b Compared with genome-based species identification using the average nucleotide identity BLAST (ANIb) analyses.

Table 1

 1 Results of species and subspecies identification by applying the MALDI-TOF MS method on a validation set of 386 Listeria isolates a . species, the PCR serogroups and the hemolysis results on horse blood TOF MS are given in the fourth column relatively to API-Listeria identification and genomebased identification results by average nucleotide identity BLAST (ANIb).

				Correct
	Species/subspecies	PCR serogroups b	Hemolysis	MALDI-TOF
				identification (%)
	L. monocytogenes	IIa, IIb, IIc, IVb, IVb-v1, L	+	353/353 (100)
	L. innocua	L	-	4/4 (100)
	L. ivanovii	L	+	4/4 (100)
	L. ivanovii subsp. ivanovii	L	+	3/3 (100)
	L. ivanovii subsp. londoniensis	L	+	1/1 (100)
	L. welshimeri	L	-	3/3 (100)
	L. seeligeri	L	+	4/4 (100)
	L. grayi	L	-	2/2 (100)
	L. gayi subsp. grayi	L	-	1/1 (100)
	L. grayi subsp. murrayi	L	-	1/1 (100)
	L. fleischmannii	L	-	3/3 (100)
	L. fleischmannii subsp. coloradensis	L	-	1/1 (100)
	L. fleischmannii subsp. fleischmannii L	-	2/2 (100)
	L. weihenstephanensis	/	-	1/1 (100)
	L. marthii	L	-	0/4 (0) c
	L. aquatica	L	-	0/1 (0) d
	L. booriae	/	-	0/1 (0) d
	L. cornellensis	/	-	0/1 (0) d
	L. floridensis	L	-	0/1 (0) d
	L. grandensis	/	-	0/1 (0) d
	L. newyorkensis	/	-	0/1 (0) d
	L. riparia	/	-	0/1 (0) d
	L. rocourtiae	/	-	0/1 (0) d

a Isolates were selected to represent the diversity of Listeria species. The second and third columns indicate, for each c Misidentified species d Non-identified species or low scores of identification (scores ≤ 1.99)

TABLE 2 .

 2 Results of species identification by applying the MALDI-TOF MS method on a negative controls set of 34 non Listeria isolates.

	Species	MALDI-TOF score	Correct MALDI-TOF identification a
	Achromobacter xylosoxidans	2.148	1/1 (100%)
	Bacillus cereus	1.86-2.13	3/3 (100%)
	Bacillus circulans	1.91	1/1 (100%)
	Bacillus pumilus	1.85	1/1 (100%)
	Carnobacterium maltaromaticum	2.15	1/1 (100%)
	Enterococcus faecalis	2.22-2.62	17/17 (100%)
	Erysipelothrix rhusiopathiae	2.18	1/1 (100%)
	Microbacterium arborescens	2.22	1/1 (100%)
	Staphylococcus epidermidis	1.81-2.04	7/7 (100%)
	Staphylocccus warneri	2.1	1/1 (100%)

a compared with genome-based species identification using the average nucleotide identity BLAST (ANIb) analyses

Table 3 .

 3 Results of species identification by applying the MALDI-TOF MS method on a validation set of 1201 Listeria isolates.

	Species	PCR serogroups a	Hemolysis	Correct MALDI-TOF MS identification b
	L. innocua	L	-	65/65 (100%)
	L. ivanovii	L	+	1/1 (100%)
	L. monocytogenes	IIa, IIb, IIc, IVb, IVb-v1	+	1112/1112 (100%)
	L. seeligeri	L	+	3/3 (100%)
	L. welshimeri	L	-	20/20 (100%)

ACKNOWLEDGMENTS

We thank Dr. Martin Wiedmann (Cornell University, USA) for providing type strains of L. marthii, L. grandensis, L. aquatica, L. cornellensis, L. riparia andL. floridensis, Dr. Leo Meile (Swiss Federal Institute of Technology Zurich, Switzerland) for L. fleischmannii, Dr. C. Bizet (Collection de l'Institut Pasteur, France) for providing type strains of L. weihenstephanensis, L. booriae, L. newyorkensis and the access to the Bruker Daltonics MALDI-TOF MS system. We are also thankful to the P2M platform (Institut Pasteur, Paris, France) for genome sequencing. This work was supported by Institut Pasteur and Public Health France.

Conflict of interest: none