Houda Brahimi
email: hbrahimi@laas.fr

P Lacroix

Olivier Llopis
email: llopis@laas.fr

Optimization of a microwave frequency discriminator based on an optical delay line

A microwave frequency discriminator based on an optical delay line is studied. This system features a noise floor below -150 dBc/Hz at 10 kHz offset. The noise mechanisms are studied in order to determine the main noise contributors.

I. INTRODUCTION

Optical delay lines or resonators are ideal devices to get an ultra high Q factor at microwave and millimeter wave frequencies. As an example, optical microwave oscillators [START_REF] Yao | Progress in the optoelectronic oscillator -a ten year anniversary review[END_REF] take benefit of these devices, to reach an ultra high spectral purity. Another application example is the microwave frequency discriminator based on an optical delay line [START_REF] Volyanskiy | Applications of the optical fiber to the optical fiber to the generation and to the measurement of low-phase-noise microwav signals[END_REF][START_REF] Onillon | Optical links for ultra-low phase noise microwave oscillators measurement[END_REF], which can be used to characterize ultra high spectral purity oscillators, such as optical microwave oscillators. Also, a high spectral purity oscillator can be realized with such a system, simply by locking on it a conventional microwave oscillator. In this case, the source phase noise becomes the phase noise floor of the discriminator. The advantage of this approach rely in the fact that this system does not require a loop gain higher than unity at microwave frequencies, which means that a microwave amplifier is not absolutely necessary in the system. Indeed, the microwave amplifier is, very often, the main phase noise source in microwave optical systems [START_REF] Onillon | Optical links for ultra-low phase noise microwave oscillators measurement[END_REF].

In this paper, a microwave frequency discriminator based on a 4 km fiber optics delay line is studied. After a brief description of the system, which uses a classical topology, the measurement of its noise floor is performed using an ultra low phase noise source : a sapphire oscillator. Then, the noise contribution of each element of the system is investigated.

II. OPTICAL DELAY LINE MICROWAVE FREQUENCY

DISCRIMINATOR : SYSTEM DESCRIPTION The optical delay line frequency discriminator is a classical microwave delay line discriminator in which the microwave delay line is replaced by a long optical delay line. The system is depicted in Figure 1 : a low phase noise mixer compares the signal coming from a reference path to the one coming from the delay line, in which the oscillator under test frequency noise has been converted into phase fluctuations. A phase shifter, in the reference path, allows a 90° average phase between the two signals in order for the mixer to perform in phase detection mode. Then, the output signal is amplified and analyzed on a FFT spectrum analyzer. The discriminator sensitivity being proportional to the time delay, the improvement resulting from the use of optics in place of a microwave coaxial cable is in the range of a few hundred to one thousand. This would lead to an improvement of the phase noise floor between 40 dB to 60 dB, if the other elements of the system were unchanged. Unfortunately, the use of optics adds some extra noise, both at low offset frequencies (modulation 1/f noise) and at higher offset frequencies (microwave additive noise).

The additive microwave phase noise is the degradation of the signal to noise ratio due to the losses in the optical link. This noise contribution can be estimated using the following formula [START_REF] Onillon | Optical links for ultra-low phase noise microwave oscillators measurement[END_REF][START_REF]Fiber optics communications systems[END_REF] : were P opt is the optical power on the photodiode, S is the photodiode sensitivity, RIN is the laser relative amplitude noise (natural value), k is the Boltzman constant, T the absolute temperature, R d the photodiode load, q the electron charge and m the modulation index. Generally, the losses in the optical fiber spool are lower than the modulator losses (0.2 dB/km, with a total length of 4 km). This means that the laser RIN dominates in this equation and that it is mandatory to choose a laser with an extremely low RIN. For this reason, we use an EM4 DFB laser, featuring a 60 mW optical output power and a measured microwave RIN lower than -160 dB/Hz at 10 GHz. We also try to maintain a high modulation index using a medium power amplifier (25 dBm output) which does not impact on the phase noise performance for two reasons : it is located before the splitting of the two path and its additive phase noise is very low (AML amplifier specified for low phase noise).

In most systems of this type, the photodiode output is amplified before performing the phase detection. This second amplifier is located at a very critical point of the system and its phase noise can be directly detected by the mixer. In a preceding version of our system, we have used a microwave carrier cancellation approach in order to cancel the 1/f noise of this amplifier [START_REF] Onillon | Optical links for ultra-low phase noise microwave oscillators measurement[END_REF], but this result in a system which is difficult to use and which is also very sensitive to vibrations. In this new system, a simpler configuration has been used : this amplifier has been removed and the photodiode is directly connected to the mixer RF port. This reduces of course the mixer phase detection factor K φ , but our K φ is still relatively high (~ 100 mV/rad) thanks to the high modulation index of the optical link.

III. SYSTEM EVALUATION WITH A MICROWAVE OSCILLATOR BASED ON A 5 GHZ SAPPHIRE RESONATOR

The phase noise floor measurement of a delay line discriminator is quite difficult. The classical approach suppresses the delay, in order to cancel the sensitivity of the system to the source phase noise. This technique is valid for classical microwave frequency discriminators. However, in the case of the microwave-optical frequency discriminator, some noise processes may occur in the optical delay line itself, and it is thus important to characterize the system including this long delay line.

The only technique in this case is to use an ultra high spectral purity source, such as a sapphire microwave oscillator, to check the ability of the microwave-optical measurement bench to characterize such a source. An oscillator of this type at 4.87 GHz is available in our laboratory. It had been realized with a low phase noise SiGe amplifier and a WGM sapphire resonator (Q L ≈ 60,000) [START_REF] Cibiel | Optimization of an ultra low phase noise Sapphire SiGe -HBT oscillator using nonlinear CAD[END_REF].

The phase noise of this oscillator has been measured close to the carrier using an Agilent E5052 phase noise measurement bench. Although the E5052 is based on conventional microwave sources, it uses a full cross correlation approach (two reference sources) which allows the measurement of ultra low phase noise sources at offset frequencies lower than 1 kHz.

Then the oscillator has been connected to the microwave optical frequency discriminator and the result is plotted in Fig. 2. As shown, the sapphire oscillator is effectively measured by the microwave-optical discriminator, with a better precision and on a wider range of baseband frequencies than with the Agilent system, although the first spurious peak of the 4 km delay line is clearly visible on this plot around 53 kHz, and prevents phase noise measurement in its vicinity. As shown on this graph, the measured phase noise is -151 dBc/Hz at 10 kHz. It is difficult to know if this value corresponds to the oscillator under test phase noise or to the frequency discriminator noise floor, but it is already very low and beyond to the state of the art of these systems [START_REF] Onillon | Optical links for ultra-low phase noise microwave oscillators measurement[END_REF]. Our goal now is to understand which device still limits this performance, particularly in the 1/f region.

IV. ANALYSIS OF THE DIFFERENT NOISE CONTRIBUTIONS

The noise contributions in such a system comes from either the optical devices or the microwave devices, and is different whether the devices are located between the two arms of the phase detector or at the system input. The phase noise due to the optical to electrical conversions can be measured using the residual phase noise approach, just like for the measurement of the additive phase noise of a microwave amplifier.

Optical noise (short delay) compared to amplifier noise : Figure 3 depicts the measured residual phase noise of two microwave amplifiers, measured with a -25 dBm input signal, which is compared to the residual phase noise of the optical link with short delay. One of the amplifiers is a conventional 30 dB gain wide bandwidth amplifier (2-18 GHz), while the other one is a low phase noise AML 25 dB gain amplifier. The optical link phase noise is relatively low, and is a little lower than the AML phase noise. This means that the use of an amplifier at the optical link output would degrade the phase noise performance, and that a better performance can be obtained without any amplifier, providing that the output signal is high enough to get a sufficient phase detection coefficient K φ on the mixer. This is the reason why no output RF amplifier is used in our experiment.

Optical noise (long delay) :

Another interesting point is to investigate on a possible noise contribution coming from the long optical delay line. This contribution may arise from optical interferometric processes in the delay line, such as Rayleigh scattering.

We found experimentally an increase of the overall noise at high optical power in the delay line (> 10 mW), and an optical attenuator has been added to reduce this power down to a few mW in the 4 km fiber. Every electronic or optoelectronic device sustaining a current features a low frequency 1/f type fluctuation of this current, which can be converted into phase noise by the system nonlinearities. This is the case of laser diodes and photodiodes.

The conversion of these noise contributors in a nonlinear system is a complex process, which can only be described using a specific CAD approach (such as the conversion matrices in harmonic balance) and a precise model of the devices. We have developed such a model for a microwave optical link using Agilent ADS platform [START_REF] Brahimi | A CAD Approach of microwave optical systems including noise performance[END_REF][START_REF] Brahimi | CAD of microwave optical systems for time&frequency applications[END_REF], but the approach presented in this paper will be more experimentally based. It will be connected later on to the model of ref. [START_REF] Brahimi | A CAD Approach of microwave optical systems including noise performance[END_REF][START_REF] Brahimi | CAD of microwave optical systems for time&frequency applications[END_REF].

One of the results obtained with our nonlinear model shows that the direct conversion of the photodiode 1/f noise into phase noise should be relatively weak [START_REF] Brahimi | CAD of microwave optical systems for time&frequency applications[END_REF], because the capacitance of a reverse biased photodiode is almost constant and there is no way for this current fluctuation to affect the phase of the RF signal. We have therefore focused our experimental investigations on the laser 1/f noise, and the way it may be converted into a phase fluctuation of the RF modulation. Like any frequency source, laser noise can be split into two components : amplitude noise and frequency (or phase) noise.

amplitude noise is easy to measure with a photodiode. In case of any doubt on the type of 1/f noise measured, it is possible to split the optical signal on two identical photodiodes, and to perform a cross spectrum analysis in order to reject the uncorrelated photodiodes noises.

The EM4 laser relative intensity noise has been measured, and is plotted in Figure 4. The measurement is performed in a Faraday's shielded room, and both the laser and the photodiode are battery biased.

As it is shown in Figure 4, the laser RIN improves at high optical power (or high bias current), both for the noise floor and the 1/f components. The measurement of the laser frequency noise at low offset frequencies is more difficult. Indeed, in optics, the classically measured parameter is the laser spectral width, which is obtained either by mixing the laser signal to the one of a reference laser, or by using a long delay line and a homodyne approach. However, the spectral width measurement gives very little information on the laser frequency fluctuations, particularly at low offset frequencies. In order to investigate on this parameter, a measurement bench very similar to the microwave frequency discriminator has to be set up in the optical domain : a short (coherent) optical delay line (L = 1 m) is used to convert the laser frequency fluctuations into phase fluctuations, and these phase fluctuations are detected by a photodiode acting as a mixer [START_REF] Sorin | Frequency-Domain Analysis of an Optical Fm Discriminator[END_REF]. It is also possible to use a pair of photodiodes (see Figure 5) arranged to get opposite output currents, in order to cancel the contribution of the laser amplitude noise (equivalent device of a microwave balanced mixer). The most difficult step in this experiment is the system calibration. This is performed in our case by carefully modifying the laser bias current and detecting the corresponding shift in the output voltage, the laser wavelength sensitivity to its bias current being previously measured on an optical spectrum analyzer.

The measurement of the EM4 laser frequency noise is presented in Figure 6. Contrarily to the RIN data, the 1/f frequency noise is lower at low bias current. This means that the choice of a bias current level is difficult and cannot be based only on these two measurements: we have to determine if the main component in the 1/f phase noise observed on the microwave signal going through the optical link is related to a conversion of the laser amplitude noise or of the laser frequency noise. To this purpose, various experiments have been performed using a microwave network analyzer, with a similar approach as the one described in ref. [START_REF] Eliyahu | RF Amplitude and Phase-Noise Reduction of an Optical Link and an Opto-Electronic Oscillator[END_REF] for microwave optical oscillators. The sensitivity of the microwave phase to a variation of the optical power has been studied, using an optical attenuator to modify the laser power, but the variation in RF phase has been found to be almost constant in our case versus this parameter (contrarily to [START_REF] Eliyahu | RF Amplitude and Phase-Noise Reduction of an Optical Link and an Opto-Electronic Oscillator[END_REF]). The same experiment has thus been tried again with a variation of the laser wavelength, obtained by varying the laser bias. This time, a strong and almost linear variation of the RF phase has been observed, with a slope of 125°/nm. This RF phase sensitivity factor has then been used together with the laser frequency noise data (Figure 6) to calculate the contribution of the laser frequency noise to the RF phase noise. In Figure 7, this contribution is represented, together with two others contributions to the microwave optical frequency discriminator noise floor : the input amplifier additive phase noise and the mixer phase noise. As it is clearly on this graph, the contribution of the laser frequency fluctuations is the dominant contribution to the system noise floor. Also plotted is the experimental data for the frequency discriminator noise measured with the sapphire oscillator. As shown, the phase noise calculated from the laser frequency noise conversion is pessimistic compare to the measured noise floor. The difference can be due either to calibration uncertainties in the laser frequency noise measurement or to a small change in the system configuration when the RF phase sensitivity to the variation of the laser wavelength has been measured. However, this study demonstrates the influence of the laser frequency noise, and open the way to an improvement of the experiment. Further system optimization will require to be able to find a compromise between the constraints on the additive phase noise floor, which is mainly related to the signal to noise ratio in the optical link and thus requires the laser to work at high current, and the constraints on the 1/f phase noise, which supposes a low laser 1/f frequency noise, and thus a relatively low laser bias current. A microwave phase noise measurement bench based on an optical delay line has been studied. This measurement state the performance, and its performance can still be improved if the main noise conversion processes involved in the system are fully understood. In this paper, the importance of the laser noise (both AM and FM noise), has been demonstrated through an experimental approach. Further improvements in performance are thus foreseen in a near future.

Figure 1 .

 1 Figure 1. Optical-microwave frequency discriminator test configuration

Figure 2 .

 2 Figure 2. Phase noise of a 4.87 GHz sapphire oscillator measured with the optical delay line frequency discriminator, and using an Agilent E5052 crosscorrelation phase noise measurement bench

Figure 3 .

 3 Figure 3. Residual phase noise of two microwave amplifiers (including a low phase noise AML amplifier), and of a MZ based optical link without any amplification at the photodiode output

Figure 4 .

 4 Figure 4. EM4 DFB laser RIN, measured at different bias current

Figure 5 .

 5 Figure 5. Laser frequency noise measurement bench

Figure 6 .

 6 Figure 6. EM4 DFB laser frequency noise, at different bias currents

Figure 7 .

 7 Figure 7. Contributions to the microwave discriminator noise floor

ACKNOWLEDGMENT

We wish to thank the French National Space Center (CNES) and the Midi Pyrénées Regional Council for their contribution to this study.


Georges Zissis

Spiros Kitsinelis

Lydie Arexis-Boisson

Christophe Martinsons

Pierre Boulenguez

Samuel Carre

LEDs and Solid-State Lighting: the potential health issues

Solid-state lighting (SSL) is expected to become the most widely used type of light source, promising to bring significant energy savings as it replaces older technologies. However, due to specific spectral characteristics of white light emitting diodes (LEDs), as compared to other artificial sources, some concerns have been raised regarding safety. SSL products should be proven to be at least as safe as the products they intend to replace, and new or unusual conditions of usage should be considered. This paper deals with potential health issues related to LED lighting, with a focus on light flickering and the "blue light hazard". An overview is given on current studies and latest expert opinions on photobiological safety. Following our measurements, the risk groups of a few consumer LED lamps are determined. We also make recommendations on how to limit the risk through regulation at the EU level. In addition, we have studied the flickering of fifty LED lamps, which were found to have widely varying behaviour (ranging from zero to one hundred per cent flickering). This last result is rather embarrassing because light flicker may cause temporary illness and visual fatigue. It is rather clear that the potential impacts of LED products on human health and well being has to be taken into account seriously before low quality and potentially harmful products submerge the European market.

Introduction

Solid-state lighting (SSL) is currently revolutionizing the field of lighting and its practices. In the long term, inorganic and organic light emitting diodes (LEDs) will become the most widely used light sources. White LEDs have shown a steady growth of their luminous efficacy for more than fifteen years; promising to bring significant energy savings as they replace older lighting technologies. However, as any new or emerging technology, SSL products should be proven to be at least as safe as the products they intend to replace. Also, in new lighting applications where older technologies could not be employed, the safety of SSL products should be assessed considering new or unusual conditions of usage.

The potential risks posed by SSL to the human health can be classified into the three following categories:

 potential risks due to the emitted optical radiations: interactions of the optical radiations with the skin and the eye (photobiological safety), undesired effects of optical radiations on vision (glare and flickering effects in particular);  effects of optical radiations on circadian rhythms;  electrical safety;  and potentials risks due to exposure to electromagnetic fields.

The first two points are due to the specific spectral characteristics of white LEDs as compared to other artificial light sources. This paper focuses on these issues, and more especially on the blue light hazard and flickering. A paper section is devoted to each one of those points. Experimental results obtained at both LAPLACE 1 and CSTB 2 are used to support the discussion. 1 Laboratoire plasma et conversion d'énergie (LAPLACE) -UMR5213 -Toulouse, France

Photobiological hazards

Photobiological hazards are related to the effects of optical radiation on the skin and the eye. The interactions of radiation with biologic systems occur through absorption, with the radiant energy being transferred to the biological tissues. Two main mechanisms can be distinguished [1]:  heat related, where radiant energy is converted into molecular movement (kinetic energy) such as vibration, rotation and translation;  photochemistry, where radiant energy causes excitation of atoms or molecules, displacing the outermost valence electrons to higher orbital energy levels. This energy can subsequently be utilized in (photo-)chemical reactions yielding 'photoproducts'.

Two key features of LEDs have attracted the attention of lighting specialists, ophthalmologists and photobiologists:  most LEDs are small sources emitting very bright visible light;  the vast majority of commercial LEDs producing white light rely on a chip emitting blue light associated with layers of phosphors to produce longer wavelengths by fluorescence. As a consequence, the emission spectrum of a white LED consists in a narrow blue primary peak and a large secondary peak in the yellow-orange-red region. These two peaks are separated by a region of very low emission in the blue-green part of the spectrum. Such typical white light LED spectrum is illustrated on Figure 1. Note that LEDs currently used in SSL emit negligible amounts of ultraviolet and infrared radiations, hence only visible light related effects are under scrutiny.

Radiation hazards for the human eye

The exposure levels needed to produce thermal damage on the retina cannot be met with light emitted by LEDs of current technologies. As far as the eye is concerned, adverse photochemical effects of light are summarized in Figure 2. In general, photochemical damages on the retina depend on the accumulated dose to which the subject was exposed (i.e. short exposure of high intensity or low intensity over longer periods).

The only effect of acute exposure to UV, particularly UVB and UVC below 300 nm, is photokeratitis of the cornea and conjunctiva. The accepted threshold levels for photokeratitis is 3-4 mJ/cm 2 at 270 nm and 10 mJ/cm 2 at 300 nm. Infrared radiation may be responsible for cataracts; the accepted threshold is in the order of 4 W/cm 2 for wavelengths higher than 800 nm [START_REF]Health Effects of Artificial Light, Report of Scientific Committee on Emerging and Newly Identified Health Risks (SCENHIR)[END_REF]. As LEDs used in lighting applications emit negligible amounts of UV and IR, it should not be expected to contribute to the apparition of photokeratitises and cataracts. However, chronic effects of exposure to LED light are unknown. It should be noted that chronic UV exposure from sunlight might cause corneal lesions (climatic droplet keratopathy), as well as cortical and nuclear cataracts of the lens.

As far as other wavelengths are concerned, visible light is focused on the retina by the cornea and the crystalline lens. The amount of light falling on the retina is directly proportional to the radiance of the light source. Due to the high brightness of LEDs, the retinal illuminance levels are potentially high and must be carefully considered. For this reason, it is important to consider the potential retinal toxicity of LEDs.

Radiations in the blue end of the spectrum have long been known to provoke photochemical retinal injuries [START_REF] Ham | [END_REF]. The underlying physiological mechanism causes important injuries for exposures over ten seconds. Symptoms include permanent scotoma (or "blind spot"), and there is a strongly suspected link with age-related macular degeneration (AMD) [4]. Light-induced retinal degeneration is known to involve complex series of events such as apoptosis (cellular death), inflammatory response, and free radicals, but the full understanding of the phenomenon is still an active research field in ophthalmology.

Retinal blue light exposure can be estimated using the ICNIRP 3 guidelines [START_REF]Guidelines on Limiting Exposures to Non-ionizing Radiation[END_REF]. A quantity called the blue-light weighted radiance L B can be obtained as a function of the viewing distance and the exposure time. It can be calculated as follows:

L B (x,J ) = L 300nm 700nm ò (x,J, l)B(l)dl
Where L( x , ϑ, λ) is the spectral radiance at wavelength λ at a position x on a surface in a direction defined by angle ϑ to the normal of the surface and B(λ) is the Blue Light Hazard sensibility function given in Figure 3. Maximum permissible exposure values (MPEs) were set by ICNIRP to provide limits for L B as a function of exposure time [START_REF]International Commission on Non-Ionizing Radiation Protection, Guidelines on Limits of Exposure to Broad-Band Incoherent Optical Radiation (0.38 µm to 3 µm)[END_REF]18]. These limits are dependent on the exposure time. In addition L B is not intended to be measured for infinitesimal solid angle and surface, but averaged over a finite field of view called the "effective field of view" (FOV). The FOV is precisely defined by the ICNIRP guidelines. It increases with the exposure time in order to account for the spreading of the image of the light source on the retina with the micro-movements of the eye.

For all LEDs and products using LEDs, a photobiological blue light hazard assessment must be carried out to determine whether or not the MPEs can be exceeded in the conditions of usage. The main tool to perform photobiological risk assessment is the CIE S009 publication whose content was transposed in an international standard (IEC 62471) and other national standards (IESNA RP27, JIS C8159, etc.).

Based on IEC 62471, lamps and lamp systems are classified into risk groups for various photobiological hazards. The risk group depends on the maximum permissible exposure time (MPE time) assessed at a given viewing distance:

 Exempt Group (RG0: no risk): MPE not exceeded within 10 4 s;  Risk Group 1 (RG1: low risk): MPE not exceeded within 10 2 s;

 Risk Group 2 (RG2: moderate risk): MPE not exceeded within 2,5x10 -1 s (eye blink time)  Risk Group 3 (RG3: high risk): MPE exceeded even for momentary or brief exposure (less than 2,5x10 -1 s).

For the past few years, blue light exposure data have been provided by LED manufacturers, professional lighting associations, independent laboratories, and governmental agencies. It was found that the retinal blue light exposure levels L B produced at a distance of 200 mm from the user by blue and cold-white LEDs (bare LEDs and LEDs equipped with a focusing lens) exceed the MPEs limits set by ICNIRP after an exposure time comprised between a few seconds for high power blue LEDs to a few tens of seconds for high power cold-white LEDs. Figure 4 shows L B for the six blue LEDs chosen by the ANSES working group [START_REF]Effets sanitaires des systèmes d'éclairage utilisant des diodes électroluminescentes (LED), Saisine n°2008-SA-0408[END_REF] and published in [8]. In this example, the LEDs were operated such that they emitted a radiant flux of 0,5W, which is about half the rated maximum value. These L B curves exhibit a first plateau corresponding to a uniform luminance when the FOV is smaller than the light source. When the FOV is greater than the size of the effective light source, the luminance L B decreases following a 1/t law. The second plateau corresponds to a constant FOV, when the exposure time is comprised between 10 s and 100 s. After 100 s, the FOV increases again and the luminance L B decreases again as 1/t. In this example, the maximum permissible exposure times of these LEDs are between 15 s and 20 s. These values correspond to the Risk Group 2 (moderate risk).

For this study, we used various single LEDs under conditions of constant luminous flux. When coldwhite LEDs were operated such as to provide a luminous flux of 100 lm, the exposure limit value was never reached and the risk group was always 0 (no risk). By increasing the luminous flux to 200 lm, all the cold-white LEDs fell into risk group 2 (moderate risk) with maximum permissible exposure times comprised between 40s and 100s. Similarly, neutral-white LEDs operated at a luminous flux of 100 lm all fell in risk group 0. When operated at 200 lm, the exposure limit value was reached at an exposure time of about 100 s, thus the studied products fell into the risk group 1 (low risk). Warm-white LEDs never exceeded the exposure limit value and were always in risk group 0 (no risk), even when they were operated at a flux of 200 lm. In fact these warm-white LEDs should reach a luminous flux of at least 500 lm to belong to risk group 1 (low risk). Table 1 recapitulates these results. The photobiological safety of a final SSL product (lamp, luminaire, etc.) must be assessed independently of its LED components. As a matter of fact, the L B value of an SSL product is generally very different from the L B value of the LED components that it uses. For instance, a higher L B can be obtained for a luminaire using an assembly of low L B LEDs. On the opposite, a lower L B can be obtained for a luminaire using a diffuser in front of a high L B LED.

The IEC 62471 standard defines two different criteria to determine the viewing distance. Light sources used for general lighting service should be assessed at the distance corresponding to an illuminance of 500 lx. Other types of light sources should be assessed at a fixed distance of 200 mm.

For LED components, there is no ambiguity in the distance since LED components are not used very often in general lighting. In this case, IEC 62471 requires using the distance of 200 mm. The application of the IEC 62471 measurement technique at 200 mm leads to a classification in risk group 2 (moderate risk) for some high power blue and cold white LEDs.

However, the choice of the viewing distance in IEC 62471 is sometimes ambiguous and not realistic in the context of the real usage conditions. For instance, let us mention stage lighting (i.e. theatres and concert halls) where artists are exposed to illuminance levels higher than 500 lx. Applying the 500 lx criterion would underestimate the exposure while the 200 mm criterion would largely overestimate it.

In a more common context, directional household lamps fall under the 500 lx criterion, which corresponds to a typical viewing distance of a few meters. It is however quite common to have shorter viewing distances, as short as 200 or 500 mm at home. Another example is street lighting where the illuminance level is much lower than 500 lx, typically a few tens of lx. Assessing the blue light hazard associated of a street lighting luminaire by using the 500 lx illuminance distance is clearly inappropriate.

It is interesting to note that the strict application of CIE S009 and IEC 62471 to indoor LED lamps and luminaires lead to RG 0 and RG 1 classifications, similar to traditional indoor light sources (fluorescent lamps, incandescent and halogen lamps). Nevertheless, several measurement campaigns using the 200 mm viewing distance revealed that some indoor LED lamps and luminaires belong to RG2 while traditional indoor light sources (fluorescent and incandescent) remain in RG0 or RG1. This result shows that LED technology potentially increases the blue light hazard in home applications where the viewing distance is not limited, notably when light sources are accessible to children and other sensitive people. At the time of this writing, the general public is not aware of the potential since no mandatory labelling system exists for SSL products.

As a consequence, the potential toxicity of some LED components viewed at short distances cannot be neglected. When the viewing distance is increased to one meter, the maximum permissible exposure time rapidly increases to a few thousands of seconds, up to a few tens of thousands of seconds. These rather long exposure times provide a reasonable safety margin to assert than there is virtually no possible blue light retinal damage from LEDs at reasonably large viewing distances (statement valid for state of the art LEDs at the time of writing).

However, lamp installers and users awareness on the notion of a safety distance should be raised.

The safety distance of a SSL product would be the minimum distance for which the blue light hazard risk group does not exceed RG1.

For SSL products aimed at consumer applications (retrofit LED lamps, for instance), the policy makers in collaboration with health authorities advocate the adoption of a regulation to limit the risk group to RG1 at the minimum viewing distance encountered at home, which is 200 mm. Equivalently a mandatory safety distance less than or equal to 200 mm should be required. The measurement campaigns carried out by several laboratories showed that the vast majority of indoor LED lamps and luminaires already comply with this requirement. It is not a critical issue for the LED industry Other widely used lighting sources, particularly high intensity discharge lamps (metal-halide lamps for instance), are also in RG2. However, this last example is intended for clearly identified usages and can only be installed by professionals presumably aware of the safety distance required to limit the exposure.

In addition, the maximum exposure limits defined by the ICNIRP and used to define the Risk Groups in both IEC 62471 and CIE S009 are not appropriate for repeated exposures to blue light as they were calculated for a maximum exposure of one 8-hours day but do not take into account lifetime exposure effects. Moreover, neither CIE S009 nor IEC 62471 account for specific light sensitivities, such as:  individuals having pre-existing eye condition for which artificial lighting can trigger or aggravate pathological symptoms;  aphakics (i.e. absence of crystalline lens) and pseudophakics (i.e. artificial crystalline lenses) persons, who consequently either cannot or insufficiently filter short wavelengths (particularly blue light);  children, as their visual system is not mature;  and elderly people, as their skin and eyes are more sensitive to optical radiation

The case of the skin

As far as interactions with the skin are concerned, the general population should not be concerned by risks arising from the use of LEDs in lighting.

Thermal effects from visible or IR radiation emitted by lighting sources are unlikely to cause any serious health effects in healthy skin; problems may only arise with excessively intense sources and close proximity with such sources (adherence to DIN 33403 for pain thresholds [START_REF]Climate at the workplace and its environments[END_REF] or more conservative expansion of the ICNIRP limit to exposure times over 10 s). Considering the data on UV effects, the sunburn reaction would appear to be the practical key for proper control of UV exposure levels on the skin, both for short-and long-term health effects. In contrast to persons deliberately exposing themselves to sunbeds for cosmetic or presumed health effects, persons staying indoors do not expect to be exposed to UV radiation from the artificial lighting system, and LEDs should therefore evidently be adequately low in UV output.

Only a small number of people suffering from photosensitive syndromes might see an aggravation of their pre-existing condition triggered by exposure to LEDs emitted blue light. Patients taking photosensitizing drugs should also be aware of a potential risk.

Light Flickering hazards

Flicker is the modulation of the light output that can be induced by fluctuations of the mains voltage supply, residual ripples in the DC current powering, or deliberate modulations of the LED input current such as the pulse-width modulation (PWM) used for dimming applications.

It is known that exposure to light flicker (in particular at frequencies between 3 Hz and 55 Hz) can cause photosensitive epileptic seizures in various forms, depending on the individual and his visual pathology, the contrast, the wavelength and the viewing angle or distance [10].

According to the literature, light flicker is not usually perceptible at frequencies higher than 70 Hz, but it can still affect people. For example, people suffering from migraines are more likely to be sensitive to flicker at high frequencies [START_REF] Shady | [END_REF]. Also, for people suffering from specific medical conditions, flicker may have some serious consequences.

Light flicker combined to rotating motion or spatial patterns may be responsible for stroboscopic effects. Stroboscopic effects might induce hazards to workers in proximity to rotating machines and tools.

On the opposite, pulsed lights may also have some positive effects: it has been reported that the pulsed operation of lamps could offer opportunities for energy savings according to the Broca-Sulzer effect [START_REF] Hart | In Adler's physiology of the eye. Clinical application[END_REF][START_REF] Jinno | [END_REF] due to enhanced perceived brightness. Thus, it is argued that energy savings can be achieved by using pulsed LEDs at very high frequency. In that case it is absolutely necessary to understand the influence of flicker on humans in order to avoid any deleterious effects appearing with products using that type of pulsed light.

In this section, we present original results that prove that some readily available consumer SSL products have very high flicker behaviour and can potentially be harmful for the end-user.

Commercially available LED lamps may have serious light flickering behaviour at twice the mains frequency (in Europe mains frequency is 50 Hz thus the observed residual flicker frequency is equal to 100 Hz). This light flicker is mainly due to the residual voltage fluctuation after the AC/DC rectifier in the lamp power supply. For this paper, we developed an experimental method to quantify flicker and then evaluate the behaviour of various commercially available products.

Definition and Experimental evaluation of flickering

There are two widely accepted metrics for measuring lamp flicker. Figure 5 is used to illustrate these two metrics. The first, called the per cent flicker, uses the maximum and minimum points of the fluctuation levels through the following equation:

t L (%) = 100 ∆ L L av
The second metric is the flicker index and requires the calculation of the areas above and below the average level of the signal [START_REF]IES lighting handbook[END_REF].

FI =

Surface zone 1 (Surface zone 1) + (Surface zone 2)

For the moment, no regulation of light flicker is implemented in the EU regulations. In the USA, the present Energy Star specifications for lamps set maximum Flicker Index values for flicker frequency of 120 Hz or higher. Draft 4 of Energy Star requirements released in late April 2013 requires that all marketed lamps should have a maximum flicker index at those frequencies and above. It defines a maximal flicker index requirement for dimmable lamps and under any dimming condition as follows: FI £ 0, 001 ´ flicker frequency in Hz

The above formula defined an increase of the threshold with frequency in order to account for situations that might occur with pulse-width modulation supply. This criterion leads to FI<1,2 for USA and FI<1,0 for Europe. The rational used by the US Environmental Protection Agency (EPA) to establish that limit appears to originate from experiments on high-quality conventional light sources, including CFLs, performed by the US Department of Energy (DoE). In this work, the highest FI value is 0,11 for magnetically ballasted CFLs. There is also a statement suggesting a value of 0,15 for magnetically ballasted fluorescent lamps. In addition, the IES lighting handbook [START_REF] Rea | The IESNA Lighting Handbook: Reference & Application, 9th Edition[END_REF] presents a maximum flicker index value of 0,20 related to ballasted High Pressure Sodium lamps. A number of LED manufacturers are asking for a higher limit value, but none of their arguments are based on factual data. The 0,12 value might be fixed in the next months.

In order to evaluate the light flickering magnitude, a specific experimental set-up was designed in the LAPLACE laboratory. It is described in Figure 6. The set-up is based on an integrating sphere equipped with a selenium cell and a Tektronix 2002B oscilloscope for detecting and recording the light waveforms. A digital multi-metre is used to independently measure the average light output, directly proportional to the luminous flux of the lamp. All lamps were operated at 230 V, 50 Hz (mains) via a controlled voltage power supply. More than fifty different lamps of different brands have been tested with this device. In our evaluation, the per cent flicker, as defined above, is used. However, as shown in Figure 7, we demonstrated experimentally that for periodic waveforms, there is an almost linear relationship between per cent flicker and flicker index. Figure 8 shows the experimental per cent flicker values for some tested lamps. It should be noted that a 100 W incandescent lamp has a flicker percentage of 10% due to the filament temperature variation that follows the power waveform. Good quality CFLs may reach a per cent flicker of 20%. The highest Flicker Index value for tested CFL lamps was found to be 0,14, a value rather compatible with the EPA requirements.

Figure 8: Some experimental percentage flicker values of various lamp technologies as obtained in LAPLACE laboratory and EU-PremiumLight projects

The situation is completely different for LEDs. As can be seen in Figure 8, LEDs had completely arbitrary behaviours. Some of them feature high quality power supplies that include reliable AC/DC rectifiers and filters. They displayed very low flicker, close to zero (not measurable). Other devices had per cent flicker values up to 100%. In this case, the light output goes off every 10ms. Eight LED lamps were found to fully respect the conditions imposed by the Energy Star requirements (Flickering Index < 0,1), whereas all examined CFLs fulfilled that condition.

It should be noticed that Kitsinelis et all [START_REF] Kitsinelis | Proceedings of 13th Int. Symposium on the Science and Technology of Lighting Systems[END_REF] proposed a very effective way to detect light flickering using the camera of a cellular phone. Figure 9 shows the obtained results by this method. The simplicity of the method allows its use by the general consumer: just use a smart phone with an integrated camera, target the lamp and look at the phone screen. If striations appear around the lamp (dark fringes), then flicker is present. The contrast between the fringes is a straightforward estimation of the "flicker depth". The spatial frequency of the fringes is related to the flicker frequency and the frame rate of the camera.

Conclusions

Solid-state lighting (SSL) and more especially light-emitting diodes (LEDs) are presented as the next generation of light sources that may amount to 70-80% of the light source market by 2020. LEDs will unquestionably help making energy savings in both indoor (residential and tertiary) and outdoor lighting sectors. However, recent work showed that this technology might have some impact on human health. This paper addressed potential health issues related to LEDs and based on original experimental data. More especially, we focused on the photobiological effects of blue light and light flickering phenomena.

Concerning the blue-light hazard, and more particularly in consumer applications (retrofit LED lamps for instance), we strongly support the adoption of a regulation to limit the risk group to RG1 at the minimum viewing distance encountered at home, which is 200 mm. The measurement campaigns carried out by the authors, as well as by several other independent laboratories, showed that most indoor LED lamps and luminaires already comply with this requirement. It is not a critical issue for the LED industry. However, the notion of a safety distance would actually be more appropriate to communicate to the installers and to the users, especially to the general public. The safety distance of an LED based product would be the minimum distance for which the blue light hazard risk group does not exceed RG1 and this value must be indicated on the package. For LED products handled exclusively by professionals, all necessary measures to limit the final risk group to RG1 have to be taken and guaranteed by the installers.

In addition, none of the single-die LEDs studied in the present work fell in high risk group (RG 3), corresponding to a maximum permissible exposure time of less than 0,25 s. Blue LEDs and coldwhite LEDs according to their colour temperature and their brightness may belong at maximum to risk group 2, especially if beam collimators are used. Likewise, neutral-white LEDs may belong to risk group 1. On the contrary, warm-white LEDs studied here all belonged to risk group 0.

Concerning light flicker, we tested more than fifty different lamps for flickering. Our samples included LED lamps as well as some CFLs and incandescent lamps as benchmarks. The highest Flicker Index value for tested CFL lamps was found to be of 0,14. LED lamps had completely arbitrary behaviour. Some of them, built with high quality power supply, displayed zero flicker (not measurable) while some other devices reached per cent flicker values of up to 100%. In fact only eight LED lamps have been found to fully respect the Energy Star requirement (Flicker Index < 0.1), while all the tested CFLs fulfilled that condition. Consumer should be vigilant about that fact. In this paper, we described a rapid method to detect flicker using a smart phone camera.

There is no clear requirement concerning light flicker limitation in Europe, which is clearly unacceptable. On the opposite, the value of FI<0,12 was proposed in the USA by the EPA in their last draft of Energy Star requirements. The requirement seems to be very stringent and is said to threaten some innovations such as the ac-LED technology. A limit value of about 0,25 may be more realistic at least for applications in which light flicker is not a critical issue.

All in all, the European Union must rapidly engage in a systematic and cross-disciplinary research effort to better understand and quantify potential health effects, and ultimately enforce a consistent regulation protecting end-users while promoting innovation in the growing SSL market.

Figure 1 :

 1 Figure 1: The two components of a typical white high-brightness LED spectrum.

Figure 2 :

 2 Figure 2: Adverse photochemical effects on the eye tissues as a function of wavelength [2]

Figure 3 :

 3 Figure 3: Blue light hazard function as given by [6]

Figure 4 :

 4 Figure 4: Variation of L B with the exposure time determined for six types of blue LEDs (measured by CSTB). The red curve is the exposure limit value. The intersect point corresponds to the maximum permissible exposure time. It can be used to determine the risk group [8]

Figure 5 :

 5 Figure 5: Definition of light flickering metrics [16]

Figure 6 :

 6 Figure 6: Diagram of the flicker measuring set up in LAPLACE

Figure 7 :

 7 Figure 7: Correlation between flicker percentage and flicker index as measured in LAPLACE laboratoryOur set of test lamps included LEDs, as well as CFLs and incandescent lamps used as references. Figure8shows the experimental per cent flicker values for some tested lamps. It should be noted that a 100 W incandescent lamp has a flicker percentage of 10% due to the filament temperature variation that follows the power waveform. Good quality CFLs may reach a per cent flicker of 20%. The highest Flicker Index value for tested CFL lamps was found to be 0,14, a value rather compatible with the EPA requirements.

Figure 9 :

 9 Figure 9: Flicker detection using the built-in camera of a cellular phone obtained by LAPLACE. Flicker is leading to the appearance of dark fringes in the image.

Table 1 : Risk groups and maximum exposure times for various LED lamps as measured by CSTB

 1 None of the studied single-die LEDs presented a high risk (risk group 3). Blue LEDs and cold-white LEDs may belong to risk group 2, according to their colour temperature and their operating point. Likewise, neutral-white LEDs may belong to risk group 1. On the contrary, all warm-white LEDs belonged to risk group 0.Several classes of products and applications based on bare LEDs or LEDs covered by a focusing lens (collimator) could result in high levels of retinal blue light exposure when viewed from a short distance. Such conditions may occur because: of testing and adjustments of high power blue and cold white LEDs by operators in lighting manufacturing facilities or by lighting installers;  bright cold white LED lamps in the visual field of children;  automotive LED daytime running lights when activated near children and other sensitive people.  LED lamps sold for home applications (consumer market) in which case lamps can be viewed at distances as short as 200 mm.

	LED type	Luminous flux (lm)		Risk Group	Max exposure time (s)
	Cold White	100 200	RG0 RG2	No Risk Moderate Risk	-40s-100s
	Neutral White	100 200	RG0 RG1	No Risk Low risk	-100 s
		100	RG0	No Risk	-
	Warm White	200	RG0	No Risk	-
		500	RG1	Low risk	100 s


Sarah Troilo

Arnaud Besserer

Christophe Rose

Safwan Saker #

Lucas Soufflet

Nicolas Brosse

Urea-formaldehyde resin removal in medium density fiberboards by steam explosion: developing nondestructive analytical tools

Keywords: MDF waste, medium density fiberboards, UF resin removal, near-infrared spectroscopy, correlative microscopy, fiber recovery

The cascading recycling of wood waste is currently a hot topic. Medium density fiberboard (MDF) is a material whose consumption has been increasing worldwide for several decades. However, current wood waste treatment processes do not allow for efficient recycling. The potential of steam explosion (SE) treatment was investigated for stripping off the ureaformaldehyde (UF) resin and the production of clean fibers from MDF. Hot liquid water during the hydrothermal stage and water expansion during the decompression stage of SE provoked (1) the hydrolytic breakdown of UF and the removal of > 80% of the resin from the fibers and (2) efficient defibration of MDF producing ≈ 67% of fibers with similar morphological features when compared with MDF fibers. Near infrared spectroscopy (NIRS), nitrogen quantification and confocal laser scanning microscopy/ scanning electron microscopy-wavelength dispersive spectroscopy were used to evaluate the SE effect on UF removal from MDF fibers. The sample clusters obtained by principal component analysis of NIRS spectra were correlated with nitrogen content and processing conditions used. This work brings versatile solutions based on hydrothermal treatments, namely SE, for diverse low environmental impact and valorization routes of MDF waste. We showed that MDF processing treatment must be chosen wisely according to the future valorization of the MDF targeted.

INTRODUCTION

Wood is a renewable material with valuable properties including recyclability. Current consumption trends are leading to ever increasing volumes of waste wood, which may constitute a feedstock for the cascade production of new products. 1 Among wood-based manufactured products, medium density fiberboard (MDF) has been used since 1965 to produce a core stock for the furniture industry. 2 Over the last few decades, household consumption habits have changed as the lifespan of interior furniture has decreased. As a result, the world production of fiberboard was multiplied by 4 between 2000 and 2020 and since 2015, the global production is over 100 million m 3 . 3 These evolutions have led to a sharp increase in waste furniture. For MDF alone, the volume of waste generated in the last five years worldwide is estimated at 220 million m 3 and growing. [START_REF] Irle | Advanced Recycling of Post-Consumer Solid Wood and MDF[END_REF] However, unlike other wood products, there is no industrial scale process for the recovery or recycling of MDF and most of the panels are currently incinerated or landfilled.

Recycling wood waste and especially MDF is challenging because of the presence of cured residual adhesive on the surface of the fibers. The poor end-of-life management of MDF panels has a negative environmental impact including the generation of hazardous gases during thermal treatment and pollutants can be released into the environment. [START_REF] Girods | Low-Temperature Pyrolysis of Wood Waste Containing Urea-Formaldehyde Resin[END_REF][START_REF] Lee | Formaldehyde Release from Medium Density Fiberboard in Simulated Landfills for Recycling[END_REF] Recycling MDF is therefore a major issue for the furniture industry and the wood sector in general. 1 Urea-formaldehyde (UF) resins are the most widely used in the wood sector because of their high reactivity, good performance and low price. [START_REF] Dunky | Urea-Formaldehyde (UF) Adhesive Resins for Wood[END_REF] It has been shown in previous studies that the presence of residual cured UF resin on the surface of the wood fibers negatively impacts the properties of the panels formed from recycled wood. [START_REF] Moezzipour | Chemical Changes of Wood Fibers after Hydrothermal Recycling of MDF Wastes[END_REF][START_REF] Zhong | Impacts of Urea-Formaldehyde Resin Residue on Recycling and Reconstitution of Wood-Based Panels[END_REF] Cured UF resins have a relatively low water resistance and can be degraded by hydrolysis. [START_REF] Fleischer | Hydrolyse von Harnstoff-Formaldehyd-Harzen: AufloÈsung des SpangefuÈges in Holzwerkstoffen durch hydrolytischen Abbau der Leimfuge[END_REF] As a result, hydrolytic strategies have been proposed for UF removal prior to the reuse of wood-based panels. [START_REF] Lubis | The Removal of Cured Urea-Formaldehyde Adhesive towards Sustainable Medium Density Fiberboard Production: A Review[END_REF] Neutral and acidic hydrolysis can removed ~ 50% and ~ 70% respectively of UF resin from MDF fibers. [START_REF] Lubis | Hydrolytic Removal of Cured Urea-Formaldehyde Resins in Medium-Density Fiberboard for Recycling[END_REF] Hydrothermal treatment led to a reduction in resin content but it also resulted in a reduction in the average length and width of the fibers, thus reducing the potential for further fiber recovery. [START_REF] Gibier | Furniture Wood Waste Depollution through Hydrolysis under Pressurized Water Steam: Experimental Work and Kinetic Modelization[END_REF][START_REF] Hagel | Fractionation of Waste MDF by Steam Refining[END_REF] The steam explosion (SE) technology is both energy efficient and versatile. The technology was initially developed to manufacture chipboard panels [START_REF] Mason | Process and Apparatus for Disintegration of Wood and the Like[END_REF][START_REF] Ziegler-Devin | Steam Explosion Pretreatment of Lignocellulosic Biomass: A Mini-Review of Theorical and Experimental Approaches[END_REF] and is particularly mature for cellulosic bioethanol 1,[START_REF] Fernandes | Enzymatic Saccharification and Bioethanol Production from Cynara Cardunculus Pretreated by Steam Explosion[END_REF][START_REF] Chen | Pretreatment Efficiency and Structural Characterization of Rice Straw by an Integrated Process of Dilute-Acid and Steam Explosion for Bioethanol Production[END_REF] . This process was also recently described for biomolecules and biopolymers extraction or the valorization of biomass from phytotechnology. [START_REF] Chadni | Steam Explosion Process for the Selective Extraction of Hemicelluloses Polymers from Spruce Sawdust[END_REF][START_REF] He | Lignin-First Integrated Steam Explosion Process for Green Wood Adhesive Application[END_REF][START_REF] Mougnala Moukagni | Extraction of Acetylated Glucuronoxylans and Glucomannans from Okoume (Aucoumea Klaineana Pierre) Sapwood and Heartwood by Steam Explosion[END_REF][START_REF] Simangunsong | Steam Explosion of Beech Wood: Effect of the Particle Size on the Xylans Recovery[END_REF] Several studies examined the importance of water content in hydrolytic processes during SE pretreatments. [START_REF] Sui | Effects of Water States on Steam Explosion of Lignocellulosic Biomass[END_REF]24 However, these phenomena are still largely unknown. The utilization of SE as a pretreatment for MDF recovery was reported in the literature [START_REF] Wan | Recycling Wood Composite Panels: Characterizing Recycled Materials[END_REF] but due to technical limitations, this study was carried out at a relatively low pressure/temperature (0.16 MPa, 113°C). More recently, hydrolysis of UF resin from wood waste during SE was studied. [START_REF] Gibier | Furniture Wood Waste Depollution through Hydrolysis under Pressurized Water Steam: Experimental Work and Kinetic Modelization[END_REF] Temperature and steam ratio improved the UF removal from waste, but neither the treatment homogeneity nor clear correlation could be established between ammonia and formaldehyde emissions.

Processes for removing resin from wood must be coupled with effective technologies for quantifying resin in the bulk and at the fiber scale. The cured resin is opaque and therefore difficult to identify. Near-infrared spectroscopy (NIRS) is a promising non-destructive and contactless method for waste wood sorting because it can distinguish treated wood from untreated waste wood. [START_REF] Mauruschat | Application of Near-Infrared Spectroscopy for the Fast Detection and Sorting of Wood-Plastic Composites and Waste Wood Treated with Wood Preservatives[END_REF][START_REF] So | The Application of near Infrared (NIR) Spectroscopy to Inorganic Preservative-Treated Wood[END_REF] Confocal laser scanning microscopy (CLSM) has been developed to detect or visualize UF resin. [START_REF] Pakdel | Quantification of Urea Formaldehyde Resin in Wood Fibers Using X-Ray Photoelectron Spectroscopy and Confocal Laser Scanning Microscopy[END_REF] The combination of the localization of the region of interest by CLSM and the morphology by scanning electron microscopy (SEM) is valuable to perform insitu analysis on the fibers. The elemental mapping analysis of nitrogen can be performed by SEM coupled with energy dispersive spectroscopy (EDS) and its quantification achieved by wavelength dispersive spectroscopy (WDS). [START_REF] Tessier | Determining the Nitrogen Content in (Oxy)Nitride Materials[END_REF] This work aims to examine and optimize the effect of SE processes performed at high pressure, namely 0.9-1.9 MPa, on MDF waste. For an efficient recovery of MDF, two effects are sought: the elimination of the glue on the surface of the fibers and the recovery of long (0.5 mm -14 mm) wood fibers with a good yield. The impact of the treatment parameters on the fiber's composition and the role of the water states in the hydrolytic degradation of the resin were investigated. The study focused on a multi-processes approach that optimized resin removal, maximized defibration and minimized the use of water to recover MDF fibers for future recycling.

MATERIALS AND METHOD

MDF characterization

Because we wanted here to evaluate the UF removal potential of SE and decrease the variability associated with the material, we used newly manufactured MDF. Standard MDF panels were purchased from EGGER (EGGER Brilon GmbH & Co, Germany). The MDF samples were sawn into cubes of side 20 mm to obtain sample sizes comparable to industrially ground waste wood panels for recycling. The moisture content of the MDF samples was 6%.

Resin removal and MDF fragmentation

The experiments were carried out in two different reactors to optimize the resin removal and MDF fragmentation.

The resin removal was optimized by a standard hydrothermal treatment. MDF samples were treated by Hot Pressurized Water treatment (HPW) in a 10 L Parr reactor with a Parr 4842 temperature controller (Parr Instrument Company, Moline, IL, USA) at medium pressure (1 MPa) at 180°C for 15 minutes. Distilled water was in excess in the process to ensure the highest resin removal rate. The ratio biomass/water was 1/25.

To optimize the fragmentation of the material and the water consumption, MDF samples were treated by SE. Technically, the SE prototype used in this study (ADF, France) consists of a steam generator that feeds the pressurized reactor containing the MDF to reach and maintain the set temperature. The biomass was introduced horizontally in a 4.8 liters reactor and additional water was injected into the pressurized SE reactor. Saturated steam at high pressure (1.6 MPa) was injected in the reactor at 180°C for 15 minutes. The opening of a pneumatic valve dropped the pressure in the reactor and the exploded biomass was released into the discharge tank (Figure S1). The samples were treated by SE with additional water (SEW) with a ratio biomass/water from 1/1 to 1/10.

To reduce the water consumption, SE experiments were carried out without the injection of additional water with different retention times (from 5 to 20 minutes) and pressures (from 1.6 to 2.3 MPa). The results of the preliminary study were used to select the experimental conditions.

Fibers drying

As the SE generates effluents, the fibers had to be separated from the effluents and dried. The fibers were separated from the liquid products by centrifugation at 7000 RPM for 10 min at room temperature (Thermo Scientific Multifuge X4R Pro, USA). Supernatant was removed and kept for subsequent analysis and fiber pellets were dried at 80°C for 24h and pressurized by air pulse.

Finally, fibers were sieved (300-850 µm mesh) and fiber size repartition was analyzed. The complete process is depicted in Figure 1.

Figure 1. Process flowchart

Pollutants quantification

To determine the rate of UF-resin removal in different SE conditions, nitrogen and formaldehyde were measured on the fibers. An elemental combustion analysis was performed on a Thermo Scientific Flash EA 112 (USA) to determine the percentage of nitrogen on the fibers. The samples were grounded into a homogeneous powder. The combustion of the samples was performed at 950°C in the presence of copper oxide under oxygen flow for 15 seconds and produces CO 2 , H 2 O, SO 2 and NO x which were reduced to nitrogen by copper. The combustion products were then measured by gas chromatography under the conditions determined by the manufacturer. The results were recorded and analyzed by the software Eager 300.

Formaldehyde emissions were measured according to the perforator method EN ISO 12460-5 (AFNOR, 2016) and a high-performance liquid chromatography (HPLC) method was used to quantify the formaldehyde content on fibers after hydrothermal extraction. Previous works showed UF resin can be efficiently extracted by hydrothermal treatment. [START_REF] Hagel | Fractionation of Waste MDF by Steam Refining[END_REF][START_REF] Ren | Degradation of Urea-Formaldehyde Resin Residues by a Hydrothermal Oxidation Method into Recyclable Small Molecular Organics[END_REF] Thus, the fibers were autoclaved at 121°C for 20 min to extract the formaldehyde. Before the analysis, the samples were derivatized with a solution of 2,4 dinitrophenylhydrazine (2,4 DNPH). 500 mg of 2,4 DNPH and 0.5 mL of phosphoric acid (H 3 PO 4 ) 85% were dissolved in 49.5 mL of acetonitrile. The pH of the samples was adjusted to 5. One milliliter of the sample was centrifuged at 12 000 RPM for 10 min and the supernatant was passed through a 0.45 diameter nylon filter. 20 µL of the sample, 30 µL of 2,4 DNPH solution and 950 µL of acetonitrile were mixed in a 1.5 mL vial and injected into the HPLC. Formaldehyde analyses were performed on a C18 Luna column (50 mm × 2.1 mm, 1.7 µm particle size) (Acquity, UPLC, Waters, USA) using a HPLC (Thermo Scientific, Dionex Ultimate 3000, USA). The wavelength was set to 365 nm.

Separation was achieved with a mixture of water/acetonitrile (40:60, v/v). The flow rate was 0.3 mL/min and the injection volume was 1 µL. The total run time was 12 min.

NIRS

The measurements were performed on a Perkin Elmer NIRS spectrometer (USA) equipped with an IngaAs detector and a CaF2 beam splitter. Three samples of 5 g from each condition were analyzed and five spectra for each sample were recorded from 10,000 to 4,000 cm -1 with a 2 cm -1 resolution. As described previously, only the spectral region between 6950 and 5500 cm -1 was further considered for analysis. [START_REF] Fackler | Fungal Decay of Spruce and Beech Wood Assessed by Near-Infrared Spectroscopy in Combination with Uni-and Multivariate Data Analysis[END_REF] The log10 (1/R) of the spectral data was calculated. This process is typically used for quantitative analysis. [START_REF] Schwanninger | A Review of Band Assignments in near Infrared Spectra of Wood and Wood Components[END_REF] Then second derivative was calculated as previously described. [START_REF] Sandak | Near Infrared Spectroscopy as a Tool for Archaeological Wood Characterization[END_REF] In lab developed scripts based on RStudio and the plugin Chemospec were used to analyze the raw data. [START_REF] Hanson | An R Package for Chemometric Analysis of Spectroscopic Data (Package Version 4.4.97[END_REF] Principal component analysis (PCA) was performed to analyze a limited set of independent and significant variables. The chemical differences of the samples were visualized in a scatter plot and the loadings were analyzed to identify the main contributive variables.

CLEM

In-situ analysis were performed by Correlative Light and Electron Spectroscopy (CLEM) to observe the removal of the resin on the fibers by combining images from a CLSM and a SEM.

The sample were mounted on a stub accommodated on a specific holder (shuttle and find holder for material sciences, Zeiss GmbH, Germany). The holder has three L-shaped registration markers defining a coordinate system that can be quickly located and calibrated semiautomatically in the "Shuttle & Find" module of Zen software (Zeiss GmbH, Germany) on both CLSM and SEM microscopes. The areas of interest were first identified under a confocal microscope and the images were saved including the "shuttle and find" coordinate system. Then the same areas of interest were recovered under the SEM (Sigma HDVP and EVO 15, Zeiss GmbH, Germany) to perform electronic imaging and microanalysis with an EDS (SDD X max 80mm 2 , Oxford instrument, UK) and a WDS detector (IncaWave 600, Oxford instrument, UK).

To perform spectral deconvolution, samples were stained in 0.1% aqueous safranin O (Merck) for 5 min and rinsed until the water became clear. They were mounted onto SEM specimen stubs and observed on a confocal LSM 780 r (Zeiss GmbH, Germany) equipped with a spectral deconvolution mode. The settings were optimized to ensure maximum distinction between stained resin and fibers into green and red emission light, respectively. Uncoated-control fibers, UF coated-control fibers and UF-resin were used as references and were compared to SE treated samples.

After the observation on the confocal microscope and prior to the observations on the SEM, the samples were coated under a high vacuum mode with 2 nm of platinum (ACE600 metallizer, LEICA, Germany).

EDS and WDS analyses

The field of observation was relocated to a FE-SEM (Sigma HDVP, Zeiss GmbH, Germany) to perform EDS analysis and then under an EVO15-SEM equipped with a WDS detector (Zeiss GmbH, Germany). The WDS is an INCA Wave that can accommodate six crystals and is equipped with a crystal optimized for nitrogen analysis LSM80E (Oxford Instruments, UK).

Surface images for the selection of sites of interest were acquired from a high definition backscattered detector (HDBSD) (Zeiss GmbH, Germany).

The working distance on the EVO15 was 9 mm. The acceleration voltage and the beam current were set to 10 Kv and 5 nA respectively for the nitrogen measurements performed on the fibers.

The specific peaks of nitrogen were acquired and deconvoluted with the Energy+ 250 interface of the INCA software. The calibration and the optimization of the detection of the nitrogen peak were carried out under the conditions of acquisition starting from a pellet of glue powder with the WAVE interface of the INCA software suite (Oxford Instruments). For each sample, the relative elemental percentage of nitrogen was measured on 9 pellets of 8 mm diameter and 0.5 mm thickness. The reference used for nitrogen content was cured UF resin.

X-ray tomography

One cube of side 20 mm was scanned on a 39 Watt Tomograph (RX Solution, France) with a high tension of 0-130 kW and an anode current of 0-300 μA. The voxel size was 10.67 µm. A subsample of 500 slices amongst the 1131 slices was selected for the 3D reconstruction using Fiji software [START_REF] Schindelin | Fiji: An Open-Source Platform for Biological-Image Analysis[END_REF] .

RESULTS AND DISCUSSION

Hot Pressurized Water treatment (HPW)

In a first attempt, the effect of a standard hydrothermal treatment (i.e without decompressive explosion) was experimented by treating MDF samples by HPW in a closed high-pressure reactor at 180°C for 15 min (Table 1, run 1). Perforator extraction coupled with HPLC analysis showed a total removal of formaldehyde emissions after treatment (2.4 mg/100 g of dry mass MDF before treatment to non-detectable after HPW). Hydrolysis of UF resin was reported to produce mainly urea, ammonia and formaldehyde. [START_REF] Gibier | Furniture Wood Waste Depollution through Hydrolysis under Pressurized Water Steam: Experimental Work and Kinetic Modelization[END_REF] Quantification of nitrogen by the Kjeldahl method was used as an indicator of resin removal performance. HPW led to a 91% (± 1%) reduction in nitrogen content (Table 1) and to a 94 % reduction in formaldehyde content (± 1%) in the fiber.

In order to analyze the effect of the treatment on the fragmentation of the sample, a defibration class (dc) was defined as followed: 0 = unaltered sample, 1 = sample swelling, 2 = partial defibration and 3 = total defibration. As shown in Table 1 and Figure 2, HPW treatment of MDF led to a swelling of the sample without disruption of MDF ultra-structure (defibration class = 1, Table 1). However, the fragmentation of the material can be required for the future use of the recovered fibers.

Steam explosion treatment (SE and SEW)

MDF was treated by SE using 4 temperatures and 4 residence times as summarized in Table 1 (runs 2-10). The condition sets used in this study were selected considering a visual effect of the material. Technically, the SE pilot consists of a steam generator that feeds the pressurized reactor containing the MDF to reach and maintain the set temperature. During the explosive discharge, the fibers are recovered in the explosion tank with condensed water. For the runs 11-15 (SEW), the water content was increased by injection of additional water in the pressurized SE reactor before heating by steam injection. Standardized analysis (see Materials and Method section) showed that formaldehyde emissions from all SE and SEW treated fibers were below the detection limit. Regarding the evaluation of the efficiency of the resin removal, nitrogen quantifications were carried out. As seen in Table 1, SE treatment (runs 2-10) allowed the removal of 55 %-83 % of the resin from the fibers. For run 2, performed at the lowest SE severity a partial defibration of MDF was observed (see Fig. 2). In contrast, runs 3-10 allowed total defibration (Fig. 2.) probably because of the explosive decompression step, involving a well-known water expansion. As previously proposed in a study aiming at the defibration of bast fibers, the high-speed extrusion of MDF form the reactor to the cyclone during the explosive decompression could also induce a high mechanical stress to the material causing its total disruption [START_REF] Kessler | Steam Explosion of Flax -a Superior Technique for Upgrading Fibre Value[END_REF] .

Interestingly, it was observed that a decrease of the ratio solid: liquid improved the removal of the resin. A comparison of run 3 and runs 11-15 showed that a SEW carried out with the same severity but with a higher water content resulted in a significant decrease in N%, from ≈ 1.3 % to ≈ 0.6-0.8 % which correspond to the removal of ≈ 85 % of the resin. This observation is in line with previous works dealing with the SE pre-treatment of lignocellulosic biomass. These studies have shown that an increase in condensed water content during the cooking step of SE could promote hydrolysis reactions through autohydrolysis mechanisms. [START_REF] Sui | Effects of Water States on Steam Explosion of Lignocellulosic Biomass[END_REF] However, Table 1 shows that resin removal reached a limit and that from a 1: 6 ratio onwards, increasing the volume of water did not significantly improve adhesive removal (runs 14 and 15). Increasing the severity of steam treatments allowed a gradual removal of resin up to 80 % and that a further increase of severity did not improve the resin removal. [START_REF] Hagel | Fractionation of Waste MDF by Steam Refining[END_REF] In accordance with this work, it appeared from our study that ≈ 15-20 % of the UF is strongly linked to the fibers and is highly recalcitrant.

NIRS characterization

NIRS which was successfully used to describe UF synthesis was experimented in this work as a non-destructive technique to characterize samples subjected to HPW and SE treatments. [START_REF] Minopoulou | Use of NIR for Structural Characterization of Urea-Formaldehyde Resins[END_REF] NIRS acquisition (n = 15) were first performed on uncoated-control fibers, coated-control fibers (containing UF resin) and treated by HPW (positive control of the resin removal) and compared with cured UF resin. A PCA was performed on the second derivative spectra. Based on the signal to noise ratio of the spectra, spectral region of interest was selected between 7000 cm -1 and 4500 cm -1 (Figure S2). The variability analysis showed three spectral regions with high variability: one between 6858 cm -1 and 6630 cm -1 , another one between 5978 cm -1 and 5726 cm -1 and the last one between 5500 cm -1 and 4570 cm -1 (Figure S3).

In order to determine the best conditions for analysis, PCA was performed on each subregion.

Plotting of PCA of the components 1 and 2 performed on the region between 5500 cm -1 and 4570 cm -1 allowed the best discrimination between wood and resin materials (Figure S4) but the best correlation between NIRS samples clusters and nitrogen content was obtained for the area between 5500 cm -1 and 4570 cm -1 (Fig. 3A) with components 2 and 3 plotted. This subregion has thus been selected for subsequent analysis. As shown on figure 3B, after PCA samples fall in significant distinct clusters that were correlated with their relative nitrogen content. Variability analysis of the mean second derivative spectra and loadings analysis showed that the bands at 5070 cm -1 and 4978 cm -1 were found to be present in cured UF and in coated-control fibers but not in uncoated-control fibers (Fig. 3A andS5). These bands were found to be significant contributors to the variance explained on principal components 2 and 3 (Figure S5).

These bands have thus been used as a marker of UF resin in subsequent analysis.

NIRS analysis was then performed on fibers treated by SE. Combining variability analysis and loadings analysis from PCA allowed to validate the attribution of the bands 5070 cm -1 and 4978 cm -1 to the resin (Figure S6). The plotting of the spectral region (Fig. 4A) showed clearly a decrease of the amplitude of UF resin marker bands in all samples proceed by SE.

Plotting of PCA of the components 2 and 3 (Fig. 4B) confirmed trends observed on second derivative spectra (Fig. 4A). NIRS allowed discrimination of samples in clusters according to the The tighter the scatter plot, the more homogeneous the treatment. Thus, increasing the retention time from 5 to 10 minutes allowed to improve the homogeneity of the treatment without decreasing thermohydrolysis efficiency of UF resin. Taking together, treating the fibers at 190°C for 10 min allowed to obtain a good compromise between the retention time, the homogeneity of the treatment, the resin removal and the defibration of the material. derivative was calculated between 5500 cm -1 and 4500 cm -1 (n=15). The plot shows PC2 and PC3 scores. For each cluster the nitrogen content is indicated.

Fibers yield, morphology and resin mapping

Hydrothermal treatments previously described in the literature on MDF recycling lead to a fiber shortening of ~ 30% [START_REF] Lubis | The Removal of Cured Urea-Formaldehyde Adhesive towards Sustainable Medium Density Fiberboard Production: A Review[END_REF] . Steam refining performed in comparable conditions lead to a fiber yield of ~ 75% [START_REF] Hagel | Fractionation of Waste MDF by Steam Refining[END_REF] . In this study, regardless of the experimental SE or SEW conditions considered (Table 1, runs 2-15), a comparable fiber yield of 80% w/w (± 2 %) was achieved. Regarding the fibers morphology, fibers resulting from run 6 were further analyzed. The fiber size distribution is reported in Table 2. The size of the wood fibers used in the manufacture of MDF panels is between 0.5 and 6 mm depending on the wood species and the manufacturing process used [START_REF] Benthien | Investigation of the Interrelations between Defibration Conditions, Fiber Size and Medium-Density Fiberboard (MDF) Properties[END_REF] . A picture of the three fiber fractions obtained after SE 6 is given in Figure S7. For comparison, Xray tomography of the wood fibers in the MDF panel board was done (Fig S7A). Interestingly, in these conditions SE allowed the recovery of more than 67% of the fibers with a length above 300 µm without visible alteration of the fiber morphology. The different fiber fractions could be reused in different applications such as new panels or bio based composite materials. To map the UF resin on the fibers, optical fluorescence microscopy was used. A preliminary study was carried out to validate the staining method using safranin. Safranin-stained unresinated fibers and UF resin were observed under a confocal microscope to acquire specific fluorescence emission spectra. The maxima emission of the resin and the wood being distinct, it is possible to apply a spectral deconvolution at any pixel of the microscope image in order to attribute a signal to the resin (green) (Fig. 5A) and to the wood (red) (Fig. 5B). Indeed, after staining, the cell walls of wood containing cellulose and lignin produced a red fluorescence. [START_REF] Bond | Safranine Fluorescent Staining of Wood Cell Walls[END_REF] The fiber staining method made it possible to visualize the distribution of resin on MDF fibers with high sensitivity and specificity. [START_REF] Grigsby | Determination of Resin Distribution and Coverage in MDF by Fiber Staining[END_REF] It is therefore suitable for comparing non-treated MDF fibers with a high amount of UF resin and treated MDF fibers (run SE6) with a residual amount of UF resin.

The images on Figure 5 are representative of the observed phenomenon. coated-control fibers (Fig. 5C) showed green patches on wood fiber in red. This patchy distribution of UF resin was observed previously. [START_REF] Loxton | Resin Distribition in Medium Density Fiberboard. Quantification of UF Resin Distribution on Blowline-and Dry-Blended MDF Fiber and Panels[END_REF][START_REF] Thumm | Visualisation of UF Resin in MDF by Cathodoluminescence/ Scanning Electron Microscopy[END_REF] In order to validate that green signal was resulting from UF resin occurrence, correlative CLSM-SEM microscopy coupled to WDS analysis was carried out.

Briefly, after observation of fields of interest with CLSM, these fields could be relocated under the SEM and an overlay of the two images could be obtained. Then EDS and WDS spectral acquisition could be done on specific region of interest on fibers or fiber pellets. CLEM-EDS and WDS microanalysis confirmed the localization of nitrogen coming from UF in the green areas (Figure S8, S9). These observations validate the methodology. Treated fibers (SE6, Fig. 5D) displayed a strong decrease of the green fluorescence linked to the resin and instead showed a yellow orange fluorescence. Three dimensional reconstructions showed the intrinsic embedding of the UF resin in the fiber making its total removal impossible without destroying the fibers (Figure S10) and are in agreement with the previous reports of UF resin penetration into the fibers leading to its recalcitrance [START_REF] Hagel | Fractionation of Waste MDF by Steam Refining[END_REF][START_REF] Xing | Characterization of Urea-Formaldehyde Resin Penetration into Medium Density Fiberboard Fibers[END_REF] . These images confirmed an efficient resin removal from the steam exploded fibers. CLEM-EDS allowed the UF mapping on fibers but is not quantitative. Thus, SEM-WDS quantification was performed on pellets of milled fibers. Relative nitrogen quantifications are indicated in Figure 5. Interestingly, fibers resulting from SE6 treatment differed significantly from coated-control fibers but not from uncoated-control fibers (ANOVA, P = 0.81). This nondestructive in-situ semi-quantitative analysis estimated a relative resin removal on the fibers treated by SE of about 88% which is in the same range as the bulk elemental combustion analysis.

CONCLUSION

Compared to hot pressurized water treatment, steam explosion is a very promising process for the recovery of MDF fibers, allowing 83% of the resin removal accompanied with an efficient fragmentation in a very short time and a water consumption divided by 3. MDF waste must be treated according to its future recovery to choose the most suitable treatment. A detailed analysis of the fibers was conducted to characterize the fibers. PCA performed on NIRS data has great potential for distinguishing waste MDF and recovered fibers. The loadings analysis confirmed the decrease of the resin on recovered fibers. Combining CLSM and SEM allowed the observation and in situ quantification of the reduction of UF resin coverage on MDF fibers. The work that we are currently carrying out in the perspective of industrial developments aim to (1) validate the results obtained on real MDF waste; (2) take interest in the decontamination of the aqueous effluents of the process which were not addressed in this article; (3) transfer the batch process into a continuous process. We hope that these prospects will pave the way for industrial recycling of MDF with a better environmental impact than its current end-of-life management.

ASSOCIATED CONTENT

Figure 2 .

 2 Figure 2. Effect of the treatment on the MDF fragmentation and defibration class definition, 0 = unaltered sample, 1 = sample swelling, 2 = partial defibration, 3 = total defibration.

Figure 3 .

 3 Figure 3. NIRS detection of UF resin in MDF samples. A) Mean second derivative of cured UF

  treatment parameters. HPW fibers were really closed to uncoated-control fibers and SE fibers fall in an intermediate cluster between coated-control fibers and HPW. The fibers treated by SE at 190°C for 10 and 20 min are not discriminated. The high dispersion of the fibers treated by SE at 190°C for 5 min reflected the high variability of the treatment. Interestingly, the variability of the sample (95% CI ellipses) was decreasing with the increase of the residence time in the reactor.

Figure 4 .

 4 Figure 4. NIRS monitoring of SE effect on MDF fibers. A) Second derivative, B) PCA of

Figure 5 .

 5 Figure 5. From left to right, CLSM (maximal intensity projection), SEM and CLEM images of

Table 1 .

 1 HPW, SE and SEW with reaction conditions and nitrogen content.

	Run Process	Pressure (MPa)	T (°C)	t (min) S/L	N (% of total elements)	N removal (%)	Defibration class
	MDF						4.15 ± 0.03		0
	1	HPW	1.6	180	15	1/25	0.40 ± 0.03	-92%	1
	2	SE	1.6	180	10		1.00 ± 0.01	-76%	2
	3	SE	1.6	180	15		1.27 ± 0.01	-69%	3
	4	SE	1.6	180	20		0.70 ± 0.02	-83%	3
	5	SE	1.9	190	5		0.83 ± 0.01	-80%	3

Table 2 .

 2 Particle size distribution of MDF fibers treated by SE (run SE6)

	Sieve Mesh	Fraction type	Material captured
	> 850 µm	Coarse fibers (a)	28% ± 3%
	300 µm -800 µm Medium coarse fibers (b)	35% ± 3%
	< 300 µm	Fines (c)	37% ± 7%

Supporting information. The supporting information is available free of charge on the ACS Publication website.

Steam explosion schematic view. Determination of the informative region of second derivative spectra. Variability analysis on second derivative spectra calculated between 7000 cm-1 and 4500 cm-1 and identification of the three sub regions of interest. PCA analysis with PC1 and PC2. Variability and loadings analysis for UF bands identification between 5500 cm-1 and 4570 cm-1. Variability and loadings analysis on SE and HPW samples between 5500 cm-1 and 4570 cm-1. Fibers treated by SE6. CLEM-EDS analysis of UF-resin on wood fibers. CLEM-EDS analysis of UF-resin on wood fibers with EDS nitrogen mapping. CLSM 3D reconstruction of MDF fibers.

AUTHOR INFORMATION

Corresponding Author

Nicolas Brosse E-mail: nicolas.brosse@univ-lorraine.fr

Author Contributions

Sarah Troilo: Investigation and Conceptualization. Arnaud Besserer: Methodology. Analysis.

Investigation. Christophe Rose: Investigation and analysis. Safwan Saker: technical assistance.

Lucas Soufflet: Project administration and funding. Nicolas Brosse: Project administration and supervision.

Notes

The authors declare no competing financial interest.

Funding Sources