P Letertre-Gibert

G Vourc'h

I Lebert

M Rene-Martellet

V Corbin-Valdenaire

D Portal-Martineau

J Beytout

O Lesens

Lyme Snap: a feasibility study of on-line declarations of erythema migrans in a rural area of France

la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

ABSTRACT

The incidence of Lyme borreliosis remains a matter of debate, but it can be estimated using the incidence of erythema migrans (EM), which is pathognomonic of the first phase. The aim of this prospective pilot study was to assess the feasibility of the on-line declaration of EM in rural areas where the incidence of Lyme borreliosis was previously estimated at 85 per 100,000 inhabitants per year.

The study was limited to a rural area (Les Combrailles, Auvergne) of approximately 52,800 inhabitants and was preceded by an information campaign for the inhabitants and the healthcare professionals. Patients who sent a photo of the suspected EM by email or MMS message between April 2017 and April 2018 and who accepted to answer a questionnaire were included in the study. Two physicians then evaluated the quality of the photographs and the probability of EM. In parallel, the number of EM seen by physicians and pharmacists in the area over the given period was recorded.

Out of the 113 emails and MMS messages received, 73 people were outside of the trial area or period and 9 did not complete the questionnaire. The photos of the remaining 31 people were analysed. The median age was 51.5 years old ([38-58] IQR) and 18 (58%) were women.

Seven people (25%) stated that they did not have a smartphone and in 9 cases (29%) the photo was sent by a third party. The quality of the photos was considered very good in 22 (71%) cases, good in 7 (23%) cases, and average in 2 (6%) cases. The probability of EM was determined to be strong or possible in 12 (38%) cases, i.e. an estimated incidence of 22.7 per 100,000 inhabitants. Over the study period, 40 physicians and 20 pharmacists were contacted on a monthly basis. A median of 5 physicians [3 ;7] and 4 pharmacists [3 ;7] answered each month for a total of 18 and 36 declared EM respectively. The EM (strong probability/possible) collected by on-line declaration and those declared by healthcare professionals were all sent between April and October 2017. The total time spent on the information campaign and collection has been estimated at 265 hours (divided between 10 people) for an overall cost of 10,669 Euros.

The incidence of EM recorded by on-line self-declaration in our study seems to be lower than in previous studies, the under-reporting was probably linked to the low use of new technologies in the rural areas. Increasing the human resources and finances appears difficult to achieve in practice over a longer time period but the development of an application for the automatic recognition of EM could be one method for a more exhaustive collection in the long term and at lower cost.

INTRODUCTION

Lyme borreliosis (LB), caused by Borrelia burgdorferi sensu lato in Europe and transmitted by ticks of the genus Ixodes, has become a public health problem. The controversy surrounding the disease is notably fuelled by a debate concerning its actual incidence. Although the infections linked to tick bites are probably an emerging problem, the uncertainty regarding the incidence of LB is an obstacle to the knowledge of its evolution over time and of its importance in terms of public health [START_REF] Paules | Tickborne diseases -Confronting a growing threat[END_REF][START_REF] Rosenberg | Vital Signs: Trends in Reported Vectorborne Disease Cases -United States and Territories, 2004-2016[END_REF]. Moreover, knowledge of the areas at risk is an important element in the diagnosis, which is based on a clinical, biological and epidemiological triad [START_REF] Shapiro | Lyme Disease in 2018: What Is New (and What Is Not)[END_REF]. It also allows better targeting of preventative actions.

The assessment of the incidence of LB in France is currently based on the National Reference Centre as well as the Sentinelles network (voluntary report by general practitioners), which is coordinated by the Institut de Veille Sanitaire (InVS), and has been active since 2009. The diagnosis of LB is based on the EUCALB clinical and biological criteria [START_REF] Stanek | Lyme borreliosis : clinical case definitions for diagnosis and management in Europe[END_REF]. A significant increase in the French national incidence was seen in 2016, with a median of 84 cases per 100,000 inhabitants, up to 105 in Auvergne, the region of our study [START_REF] Fournier | Épidémiologie de la borréliose de Lyme en médecine générale, France métropolitaine, 2009-2016[END_REF][START_REF] Septfons | Epidemiology of Lyme borreliosis through two surveillance systems: the national Sentinelles GP network and the national hospital discharge database, France, 2005 to 2016[END_REF]. This increase could be attributed to the start of the national plan against LB, with awareness-raising measures for the general public and healthcare professionals (Ministère des Solidarités et de la Santé, 2016). However, it cannot be excluded that the incidence is truly increasing.

The rise in the number of smartphones and the development of telemedicine [START_REF] Boiteux | Cardiauvergne is a remote monitoring and care coordination service for patients with severe heart failure[END_REF][START_REF] Gossec | An e-health interactive self-assessment website (Sanoia ® ) in rheumatoid arthritis. A 12month randomized controlled trial in 320 patients[END_REF][START_REF] Gilmore | Automated decision support in melanocytic lesion management[END_REF] makes it possible to consider collection of EM by self-declaration, based on the sending of digital photographs. This self-declaration is also used in other epidemiological follow-ups ("Signalement tiques", ongoing study being carried out by INRA, Institut National de la Recherche Agronomique). However, the efficacy of this method can meet with several difficulties, such as reduced diffusion of information and digital tools in rural areas. The quality of the photography may also prove to be an impediment when trying to make a confident diagnosis.

We therefore wanted to evaluate the feasibility of an on-line declaration of EM for estimating the incidence of LB via the sending of a digital photo, in a rural area of France (Les Combrailles, Auvergne), known for having a significant part of the tick population carrying Borrelia burgdorferi s.l. [START_REF] Boyard | Reproducibility of local environmental factors for the abundance of questing Ixodes ricinus nymphs on pastures[END_REF]. In parallel to the collection from the general public, the number of EM seen by doctors and pharmacists in the area (31 physicians and 20 pharmacists) during the study period was collected by an INRA scientist. Case report forms were provided to these healthcare professionals and a monthly reminder was sent by email to collect the number of EM identified. The sending of a photo was not required.An initial delivery of the questionnaire was made at the start of the month and a reminder was sent at the end of the month to the doctors and pharmacists that had not replied.Finally, an evaluation of the cost and the time required for the information campaign and the collection was carried out.

MATERIALS and METHODS

This

RESULTS

At the end of the study, 113 emails or MMS messages had been received, including 30 photographs of erythema that appeared in the area and period of the study (Figure 1). Thirty patients with a median age of 51 years were included in the study. Their characteristics are summarised in Table 1.

All participants except 2 considered the sending of the photograph to be easy. However, in 8 cases (27%) the photo was sent by a third party (4 by family members, 2 by a pharmacist, 1 by a nurse and 1 by a doctor). The quality of the photographs was determined to be very good in 22 cases (73%), good in 6 (20%) and average in 2 cases (7%). The results of the joint analysis of the photograph and questionnaire are summarised in Figure 1. Erythema migrans probability was determined to be strong or possible in 40% of cases.

In the 12 probable or possible cases, 10 (83%) appeared in June and July 2017, 2 people did not notice the tick and in the 10 others, the erythema appeared within a median of 2 days ([1 ;7] IQR) after the bite. Ten people received an antibiotic therapy (6 with amoxicillin, 2 with doxycycline and 2 could not remember the name).

Concerning the questionnaire for professionals, 45 replies were received from 10 different physicians (out of 40). A median of 5 physicians replied per month [3][4][5][6][7] (participation rate of 10%), for 18 declared cases of EM during the all study. Forty-three replies were received from 8 different pharmacists (out of 20). A median of 4 pharmacists replied per month [3][4][5][6][7] (participation rate of 20%), for 36 declared EM during the all study. Only 6 of these patients seen by professionals stated that they were participating in the Lyme Snap study, the information was missing for the other ones.

No EM were declared by the population nor the healthcare professionals after October 2017.

The photographs received were mainly from the north of the Combrailles area.

The incidence of EM in the year (probability considered as strong/probably based on the photos, i.e. 12 per 52,800 inhabitants) was estimated at 22.7 per 100,000 inhabitants per year.

The time spent in the briefings, the poster advertising and the information for the healthcare professionals was estimated at 183 hours (8 people involved), and the time required for the collection of the information and the classification of the EM (4 people involved) was estimated at 82 hours. The total cost in terms of human resources amounted to 8,061 Euros.

The cost (travel and material) for the information campaign amounted to 2,608 Euros. The overall cost was 10,669 Euros.

DISCUSSION

In this study we investigated the feasibility of self-declaring EM in rural areas by sending a digital photograph of a skin lesion. This method of collecting EM by on-line declaration is certainly attractive but it faces the problems of feasibility.

A study carried out in the same rural area in 2005 and 2006 found an incidence of EM (declared by the doctors) of 66 to 104 per 100,000 inhabitants [START_REF] Beytout | Lyme borreliosis incidence in two French departments: correlation with infection of Ixodes ricinus ticks by Borrelia burgdorferi sensu lato[END_REF], which is 3 to 4 times higher than the incidence estimated from the self-declarations in our study. Likewise, in our study, the number of EM reported by physicians and pharmacists in the same period was greater than those collected by self-declaration, despite a low rate of participation of healthcare professionals. However, the diagnoses of EM declared by healthcare professionals were not verified by our team, which may have resulted in an over-declaration on their part.

The possible under-reporting may be linked to several factors: (a) the possible low use of new technologies in the rural areas could have been the cause of the low number of self-declared cases. (b) A geographical effect exists with fewer photos received from the southern area, an area less accessible, with fewer healthcare professionals and with a lower population but also with a lower known density of ticks. (c) A temporal effect also existed during the study with a maximum number of photographs received during the 7 first months (April-October).

However, it is difficult to know if this was due to the fact that the information drive was not repeated (the study then being forgotten), or simply because Ixodes ticks are known to be less active during this period. The information campaign should probably have been repeated during the study, but with a more significant spending and human mobilisation. A larger scale study would require repeated information drives and more resources.

It is important to note that the majority of the exposures to ticks were due to gardening activities, an activity usually sparsely highlighted in the prevention strategies, which mostly targets hikers. However, the people who sent the photographs were mainly inhabitants of the area and rarely tourists, who would have been less informed of the study.

Several factors that could contribute to feasibility issues, particularly in a large-scale study, have been identified. Firstly, we received many messages and emails that were not related to EM (mainly chronic aspecific symptoms). Although they underline the need to inform the public, these messages interfere with the study and significantly increase the workload. Then again, in the context of a larger study, the human resources needed to sort out and reply to these inappropriate declarations would be considerable. Furthermore, the call-back for suspected cases in order to obtain the clinical history data, essential for the analysis of the photographs, was very time-consuming; And even when the message contained a photograph of the skin lesion, over half were not EM. The questionnaire was a key element for classifying the probability of EM based on the significance of the history but effectively required additional time. This method of collection for the estimation of the incidence of EM is probably not the most appropriate due to the low number of EM collected, despite the significant human and financial resources. Nevertheless, to date, no other collection method appears to be satisfactory [START_REF] Cartter | Lyme disease surveillance in the United States: Looking for ways to cut the Gordian knot[END_REF].

Since the quality of the photographs received during the study was very good, it is possible to envisage an automatic recognition application for EM combined with a few short questions in order to assess the probability of EM. This technique, which has already been validated for the diagnosis of melanoma, could help with diagnosis but also with an epidemiological collection while limiting, after the implementation phase of the application, the financial and human cost.

  photograph and the probability of EM.


Haifei Gao

Cristine Goncalves

Téo Gallego

Marc Francois-Heude

Virginie Malard

Véronique Mateo

M Lemoine

Virginie Cendret

Cristine Gonçalves

Marc François-Heude

François Lemoine

Florence Djedaini-Pilard

Vincent Moreau

Chantal Pichon
email: chantal.pichon@cnrs.fr

Patrick Midoux
email: patrick.midoux@cnrs-orleans.fr

Comparative binding and uptake of liposomes decorated with mannose oligosaccharides by cells expressing the mannose receptor or DC-SIGN

Keywords: oligosaccharides, glycolipids, liposomes, dendritic cells, Mannose Receptor

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Dendritic cells (DCs) are the most powerful professional antigen presenting cells for cancer immunotherapy by inducing cytotoxic CD8 + T lymphocytes against tumor cells [1][2][3][4].

Nowadays, antigens can be proteins, peptides, DNA or mRNA [5][6][7][8][9][10][11][12]. However, a selective transport of antigens is required to favor their intracellular delivery in DCs in vivo. For this purpose, liposomes are powerful carriers and their decoration with ligands recognizing specific receptors on DC surface can improve the targeting and endocytosis of antigens.

Carbohydrate-based targeting is an obvious manner to enhance the capture and uptake by DCs of antigen pay loaded liposomes because DCs express several sugar receptors binding oligosaccharides [13][14][15][16]. The Mannose Receptor (MR) (CD206) and the DC-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN) (CD209) induce a clathrin-dependent mediated endocytosis of terminal "high-mannose oligosaccharides". In contrast to MR expressed also in various kind of cells including monocytes, macrophages, subsets of endothelial cells, retinal pigment epithelium, kidney mesangial cells, and tracheal smooth muscle cells, DC-SIGN is only expressed by DCs [17]. In humans, DCs in mucosal sites, skin and lymph nodes express preponderantly DC-SIGN [18]. It is not expressed by monocytes, activated monocytes, T cells, activated T cells, B cells, activated B cells and CD34 + bone marrow cells. DC-SIGN expressing cells are present in the T cell area of lymph nodes, tonsils and spleens. In skin, dermal DCs express DC-SIGN but not Langerhans cells nor macrophages. Mature DCs only express DC-SIGN allowing the endocytosis of antigens and their presentation by the MHC type I and II [18][19][20][21]. In blood, plasmacytoid DCs do not express DC-SIGN while myeloid DCs do. DC-SIGN plays an important role in DCs adhesion to naive T lymphocytes and endothelium of blood and lymphatic vessels, in their migration, in inflammation, in the activation of primary T cells, and in triggering of the immune response [22]. While MR recognizes mannose located at the end of the carbohydrate chains, DC-SIGN preferentially binds to branched mannose [16]. DC-SIGN recognizes also fucosylated glycans such as the blood-type Lewis antigens (Le a , Le b , Le X , Le Y , and sulfo-Le a ) [23]. Liposomes decorated with Lewis antigens were used to deliver tumor antigens and induce anti-tumour T cell responses [24,25]. Thus, targeting this receptor would both increase uptake and reduce the antigen dilution after in vivo administration. α-D-mannopyranosyl derivatives are usually used because they are available under forms that can be easily conjugated to various carriers but the binding affinity typically is weak (K ~ 10 -3 M -10 -4 M). The multivalent decoration of proteins, polymers or liposomes with monosaccharide units increases the apparent affinity by 1 or 2 orders of magnitude [26,27]. High-mannose oligosaccharides such as Man9 and Man8 exhibiting high affinity (K = 10 -6 M) for membrane lectins should be more attractive targeting ligands, but their synthesis is hard, expensive and yields are weak. Therefore, pseudo-Man9 (PMan9), pseudo-Man8 (PMan8), pseudo-Man5 (PMan5) and pseudo-Man4 (PMan4) mimicking the High-mannose oligosaccharides or moieties were synthetized in which triazole groups replaced some mannopyranosyl residues [28,29]. PMan4 mimics the Manα1-2Manα1-2Manα1-3Man tetrasaccharide (D1 arm) of Man9; PMan5 the Manα1-2Manα1-6 (Manα1-2Manα1-3)Manα1-pentasaccharide (D2 and D3 arms) of Man9 and Man8; Man-tri the Manα1-6(Manα1-3)Manα1-trisaccharide (D2 and D3 arms) of Man5, Man6 and Man7 (Supplementary Figure 1). Interestingly, affinities of the same order of magnitude against lectins were observed for pseudo-Mann/Mann pairs in the case of the higher homologues supporting their functional equivalency. The relative affinity of PMan9, PMan8 and PMan5 was ~2-fold lower than Man9, Man8 and Man5, respectively [29]. Compared to the methy-α-D-mannoside (MeαMan) the relative affinity of PMan5, PMan4 and Man-tri with Concanavalin A (ConA) was 20.8-, 3.8-, and 11-fold higher, respectively and with the recombinant human macrophage mannose receptor it was 30.6-, 2.12-and 10-fold higher, respectively [29].

In this work, we synthetized a series of glycolipids comprising either mannose, a tri-antenna of α-D-mannopyranoside, the [Manα1-3(Manα1-6)Man], the pseudo-Man4 or the pseudo-Man5. Next, we compared the binding and uptake of a series of fluorescein-labelled liposomes decorated with these glycolipids by DC2.4 cells expressing the mannose receptor, DC-SIGN HEK293T cells expressing DC-SIGN and human monocytes derived DCs (hMo-DCs).

Results and discussion

Synthesis of Mannosylated lipids and liposomes preparation

the mannose structures (Figure 1B) [30]. Archaeal lipids exhibiting adjuvant properties independent on Toll-like receptors activation could be benefit to boost the immune response [31][32][33]. Thus, various azido glycosides (2a-7a) were linked by "click chemistry" to the diether lipid with more than 95% of yield leading to glyco-diether lipids 2-7. For this purpose, the propargyl-PEG8-diether was synthetized (Figure 2). Then, fluorescein-labelled liposomes (Flu-Lip) were prepared comprising DPPC (47.25%), DOPE (47.25%), one glyco-diether lipid (5%) and Flu-DOPE (0.5%) (Supplementary Figure 2). The corresponding liposomes (1b-7b) exhibited a size of ~150 nm in diameter and a negative ζ potential varying with the sugar polar head nature (Table I).

Binding to mannose specific lectins

The binding of the liposomes to ConA and BC2LA was evaluated as a function of their oligomannose structures. The Flu-Lip equipped with Tri-Man (1), Man-tri (4), PMan4 (6) and PMan5 (7) showed better and similar apparent binding to ConA than with Man (3) (Figure 3A).

The binding profile was similar with BC2LA excepted that the binding of Man-tri-spa (5b) was lower than Man-tri (4b) (Figure 3B). There was a weak binding of Glc (2b) due to a small affinity of ConA for α-D-glucosyl residues. In contrast, Glc (2b) did not interact with BC2LA. Thus, those oligomannose structures conserved their binding capacity to lectins after their linkage to the diether lipid and insertion in the lipid bilayer of liposomes. The results were in agreement with data reported in literature indicating that compared to MeαMan, the relative affinity to ConA of a tri-antenna mannopyranoside, PMan5 (7a), PMan4 (6a) and Man-tri (4a) was 16-, 20.8-, 3.8-and 11-fold, respectively [29]. Here, the binding of liposomes PMan4 (6b) was similar to PMan5 (7b).

Binding and uptake of liposomes by DC2.4 cells and DC-SIGN expressing HEK293 cells

DC2.4 cells express the MR while DC-SIGN HEK293 cells express only DC-SIGN

(Supplementary Figure 3). Flow cytometry was used to assess the binding and uptake of Flu-Lip by these cells and analyses were performed as described in Supplementary Figure 4 to that observed with Man (3b), Man-tri-spa (5b) and PMan4 (6b) (Figure 4Ba).

In cells expressing DC-SIGN, the highest binding and internalization was observed with Mantri (4b). The uptake was 2-to 3-fold higher than with Tri-Man (1b), PMan4 (6b) and PMan5 (7b) (Figure 4Bb). The monensin enhancement was lower (< 2.5) in DC2.4 cells (Figure 4Ca) than in DC-SIGN HEK293 cells (> 4) (Figure 4Cb). In the latter cells, this enhancement increased with liposomes concentration indicating that liposomes accumulated in acidic compartments. In DC2.4 cells, the monensin enhancement for Man-tri (4b) and Man-tri-spa (5b) (even Tri-Man (1b)) was high at low concentration and then dropped to even the value of 1 meaning that fluorescein was in a neutral environment which could result from escape of liposomes from acidic compartments. However, it was difficult to conclude about different intracellular processing of liposomes internalized via MR or DC-SIGN because the cell types were different. Altogether, the results indicated that Man-tri (4b) provided better uptake by DC-SIGN positive cells than MR positive cells. Conversely, we observed better selectivity and uptake of Tri-Man (1b) by MR positive cells. MR is a monomeric membrane-bound protein allowing mannose binding to two (or more) separate but interacting carbohydrate recognition domains (CRDs) within the mannose receptor [34][35][36]. The structure of the triantenna α-mannopyranoside in Tri-Man (1) is more adapted to bind to separate CRDs of MR than the tri-mannose structure of Man-tri (4). Conversely, the presence of the branching α(1,2) mannose on Man-Tri (4b) increases their binding toward DC-SIGN as reported [37].

Comparatively, PMan4 (6) and PMan5 (7) did not provide benefit in terms of binding and uptake of the liposomes.

Binding and uptake of liposomes by hMo-DCs

The same experiments were performed on hMo-DCs that expressed both MR and DC-SIGN.

The MFI on the surface of the cells incubated with Tri-Man (1b), Man-tri (4b), Man-tri-spa (5b), PMan4 (6b), and PMan5 (7b) was saturable indicating a receptor mediated binding of those liposomes (Figure 5A).

In contrast, the binding of Man (3b) increased linearly with the concentration and was not saturable. The intracellular MFI of Man-tri-spa (5b) was higher than Man-tri (4b) and it was much higher than Tri-Man (1b) (Figure 5B). The intracellular MFI with PMan4 (6b) was close to that with Tri-Man (1b) but higher than with PMan5 (7b).

Conclusion

This work revealed that decorating DPPC/DOPE liposomes with a tri-antenna αmannopyranoside (Tri-Man) (1) is beneficial for targeting liposomes to MR while decoration with a [Manα1-3(Manα1-6)Man] (Man-tri) (4) is beneficial for targeting DC-SIGN.

Compared to Tri-Man (1) and Man-tri (4), there was no great benefit to use other complex mannose structures such as PMan4 (6) and PMan5 (7) in terms of binding and uptake efficiency. In contrast to MR expressed in various kind of cells, DC-SIGN is expressed preponderantly on DCs at mucosal sites, in skin and lymph nodes in humans. In skin, DCs express DC-SIGN but not Langerhans cells nor macrophages. Overall, the results suggest that antigen carried by liposomes prepared with Man-tri (4) would be more selective in vivo for DCs thanks to better recognition by DC-SIGN. Evaluating the selectivity of the targeting, immune responses and therapeutic efficacy induced upon administration of antigens pay loaded liposomes decorated with Tri-Man (1) or Man-tri (4) would be of great importance.

However, a murine model expressing DC-SIGN is imperative. Recently, it was reported that mDC-SIGN mice expressing CD209a/SIGNR5 display overlapping similarities between hDC-SIGN and CD209a/SIGNR5 [38]. A humanized DC-SIGN murine model is also available [39]. These models may be an interesting approach for these investigations after determining whether the binding and uptake of liposomes with Man-tri (4) and Tri-Man (1) with their DCs are identical to that reported here on hDC.

Experimental

All reagents were purchased from Sigma unless otherwise stated and used without further purification. The tri-antenna of α-D-mannopyranoside diether lipid (Tri-Man) (1) was synthetized as described [40]. 1-azido-β-D-glucopyranoside (Glc-azide) (2a) and 1-azido-α-D-mannopyranoside (Man-azide) (3a) were purchased from Sigma.

Synthesis of 3,6-di-O-(α-D-mannopyranosyl)-α-D-mannopyranosylazide (Man-tri azide) (4a)

The sugar was synthesized as described [29].

Synthesis of 5-azidopentanoic acid

The compound was synthetized as described [41,42]. To a stirred solution of 5-bromovalericacid (5 g; 27.61 mmol) in dry DMF (50 mL) was added sodium azide (2.15 g; 33.14 mmol; 1.2 eq). The mixture was stirred for 2 h at 80°C, and then diluted with EtOAc (50 mL). The organic phase was washed with brine (2 x 100 mL), water (2 x 100 mL), dried over sodium sulfate, filtered and concentrated. The crude product was purified by "manual" flash chromatography (Cyclohexane/ EtOAc, 5/5) to give the compound (1.90 g; 48%). 1 H NMR (CDCl3, 300 MHz) δ(ppm) 11.11 (s, 1H, COOH); 3.33 (t, J = 6.6 Hz, 2H, CH2d); 2.43 (t, J = 7 Hz, 2H, CH2a); 1.85-1.55 (m, 4H, CH2b, CH2c). 13 [43] (1.5 g, 1.4 mmol) in methanol (30 mL) was hydrogenated in a Hcube (Mode Full H2, 1 mL.min-1, 25 °C) on a Pd/C 10 % cartridge for 36 h. Methanol was removed under reduced pressure to afford the crude β-amine (1.45 g, 99%) pure enough for the next step. The crude β-amine (1g; 0.95 mmol) was dissolved in dry dichloromethane (CH2Cl2) (40 mL) at room temperature and in this addition order 5-azidopentanoic acid (200 mg; 1.15 mmol) beforehand dissolved in dry CH2Cl2 (1 mL), HATU (726 mg; 1.91 mmol) and DIPEA (332 µL; 1.94 mmol) were added. The mixture was stirred under argon atmosphere for 36 h, then diluted with CH2Cl2 (10 mL), the organic phase washed with satured NaHCO3 (2 x 10 mL) and water (2 x 10 mL), dried over sodium sulfate, filtered, and concentrated. The crude product was purified by "automatic" flash chromatography (H2O/MeCN, 70/30 to 0/100) to afford the compound (620 mg; 55%). 1

Synthesis of 2,4-di-O-benzoyl-3,6-di-O-(2,3,4,6-tetra-O-acetyl-α-D-mannopyranosyl)-β-D-mannopyranosylamido-5-azido-pentanamide

A solution of 2,4-di-O-benzoyl-3,6-di-O-(2,3,4,6-tetra-O-acetyl-α-D-mannopyranosyl)-α-D- mannopyranosylazide

Synthesis of 3,6-di-O-(α-D-mannopyranosyl)-β-D-mannopyranosylamido-5-azidopentanamide (Man-tri-spa azide) (5a)

To a solution of 2,4-di-O-benzoyl-3,6-di-O-(2,3,4,6-tetra-O-acetyl-α-D-mannopyranosyl)-β-D-mannopyranosylamido-5-azido-pentanamide (128.5 mg, 0.122 mmol) dissolved in MeOH (3.5 mL) was added 1M sodium methoxide solution (3.68 mL, 3.68 mmol; 30 equiv.) The mixture was stirred for 7 days at 30°C then neutralized with Amberlite ® IR120 H + resin, filtered, and concentrated. The crude product was purified by "automatic" flash chromatography (H2O/MeCN, 95/5 to 0/100) to afford the compound 5a (47.7 mg, 69% containing 9% of α anomer). 1 [29] (84 mg, 0.124 mmol) and DIPEA (22 µL, 0.129 mmol) in DMF (5 mL) was stirred for 2h at room temperature under argon. A solution of 5-azidopentanoic acid (18 mg, 0.125 mmol), DIC (40µL, 0.253 mmol) and HOBt (34 mg, 0.251mmol) in DMF (5 mL) was prepared 2 h before use. The two solutions were mixed and stirred for 24 h at 60 °C. DMF was removed in vacuo, the crude product passed through a sephadex column and then purified by HPLC to afford compound 6a (22 mg, 23%) as a white solid. 1 [29] (150 mg, 0.211mmol) and DIPEA (36 µL, 0.211 mmol) in DMF (5 mL) was stirred for 45 min at room temperature under argon. A solution of 5-azidopentanoic acid (31 mg, 0.216 mmol), DIC (71µL, 0.455 mmol) and HOBt (54 mg, 0.399 mmol) in DMF (5 mL) was prepared 30 min before use. The two solutions were mixed and stirred for 24 h at 60 °C. DMF was removed in vacuo, the crude product passed through a sephadex column and then purified by HPLC to afford compound 7a (25 mg, 11%) as a white solid. 1

Synthesis of 2-Amidoethyl 3-O-[1-(2-O-(α-D-mannopyranosyl)-α-D-mannopyranosyl)-1,2,3-triazol-4-yl]methyl-α-D-mannopyranoside-5-azido-pentanamide (PMan4azide) (6a)

A solution of 2-Aminoethyl 3-O-[1-(2-O-(α-D-mannopyranosyl)-α-D-mannopyranosyl)- 1,2,3-triazol-4-yl]methyl-α-D-mannopyranoside hydroformate

Synthesis of 2-Amidoethyl 3,6-di-O-[1-(α-D-mannopyranosyl)-1,2,3-triazol-4-yl]methyl-

α-D-mannopyranoside-5-azido-pentanamide (PMan5 azide) (7a) A solution of 2-Aminoethyl 3,6-di-O-[1-(α-D-mannopyranosyl)-1,2,3-triazol-4-yl]methyl-α- D-mannopyranosidehydroformate

Synthesis of Propargyl-PEG8-amine

Azide-PEG8-alcohol (138 mg, 0.35 mmol) (Broadpharm) was solved in 5 ml DMF and cooled to 0°C. NaH (17 mg, 0.7 mmol) was added portion wise and stirred for 10 min at 0 °C before adding of 80% propargyl bromide solution (75 μl, 0.7 mmol). After stirring overnight at room temperature, 20 ml water was added and the product was extracted with 2 x 25 ml ether. The organic layer was dried on MgSO4, filtered and concentrated under pressure. The crude product was purified by silica gel chromatography (CH2Cl2/CH3OH, 95:5) to yield azide product as colorless oil (140 mg, 92%). The azide group was then reduced in amino group in THF/water (4:1; v:v) in the presence of triphenylphosphine (109 mg, 0.45 mmol) under N2 atmosphere. The alkyne-PEG8-amine was used in next step without further purification.

Synthesis of Propargyl-PEG8-diether

The acid diether lipid (76 mg, 0.124 mmol) prepared as described [40] in 20 ml CH2Cl2 containing HBTU (52 mg, 0.136 mmol) was stirred at room temperature for 30 min. Then, the propargyl-PEG8-Amine (46 mg, 0.113 mmol) and DIPEA (18 mg, 0.136 mmol) were added to the above solution and stirred overnight at room temperature. The solution was washed with aqueous solution of 1N HCl and brine. The organic phase was dried on MgSO4 and concentrated under reduced pressure. The crude product purified by flash chromatography on silica gel (CH2Cl2/CH3OH, 98/2) yielded alkyned-lipid as colorless oil (92 mg, 80%); Rf = 0.23 (DCM/CH3OH, 95/5). 1 The size and ζ potential of liposomes were measured in Hepes by using the SZ-100 Analyser (Horiba Scientific).

Man-Liposomes recognition by lectins

ConA from Canavaliaensiformis (Jack bean) binds to terminal α-D-mannosyl and α-Dglucosyl residues with a Kd of 8.75 10 -4 M for MeαMan. BC2LA a lectin from Burkholderiacenocepacia displays mannose specificity with a Kd for MeαMan of 2.75 10 -6 M [44,45]. It binds also to all αMan-terminating oligosaccharides. Interactions between liposomes and lectins were measured by GLYcoPROFILE ® technology from GLYcoDiag (Orléans, France). This method is a lectin array-based assay which uses customized lectin immobilized 96-well plate (LEctPROFILEpalte) (GLYcoDiag) [46]. Samples of liposomes (2.7 mM) were diluted in PBS supplemented with 1mM CaCl2 and 0.5 mM MgCl2 and incubated (50 µL / well) in lectin plates during 1h. After washing with PBS (three times), fluorescence was read with the Fluostar (BMG labtech).

Cells and cell culture

All reagents were purchased from ThermoFisher Scientific unless otherwise stated and used without further purification. The DC2.4 cell line was a murine dendritic cell line maintained in RPMI supplemented with 10% fetal calf serum (FCS), glutamine (2 mM), penicillin (100 U/mL) and streptomycin (100 μg/mL) (complete medium) [47]. The DC-SIGN HEK293 cell line -kindly given by O. Schwartz (Pasteur Institute, Paris, France) -was a human cell line obtained by transduction of HEK293T cells with lentivirus encoding the DC-SIGN human lectin (CD209) [30]. DC-SIGN HEK293 cells grew in DMEM complete medium. All cells grew in humidified air with 5% CO2 at 37 °C and were Mycoplasma free when checked by using the MycoAlert1 Mycoplasma Detection Kit (Lonza). hMo-DCs were obtained as described [48]. PBMC were freshly isolated from leukapheresis residues (EFS, Paris, France) collected from healthy volunteers after informed written consent). CD14-positive cells were isolated from PBMCs using a magnetic cell sorting (MiltenyiBiotec) and then cultured in the presence of 10% human AB serum RPMI medium, GM-CSF (100 ng/mL; Gentaur) and IL-4 (10 ng/mL; MiltenyiBiotec). min before measurement at a final concentration of 0.03 mg/mL in order to measure the fluorescence intensity upon neutralization of acid intracellular compartments [26,49].

Binding and uptake of liposomes

  . The mean of the fluorescence intensity (MFI) of cells incubated with Flu-Lip was first measured without any treatment (NT), the second time in the presence of Trypan blue (TB) and the third time in the presence of monensin (MO). The MFI decrease upon TB treatment quenching fluorescein fluorescence on the cell surface indicated that ~ 70% of liposomes associated to the cells were bound on the cell surface; the remaining MFI came from the fluorescence of intracellular liposomes. The MFI increase upon MO treatment raising the quenching of the fluorescein fluorescence in acid intracellular compartments indicated that liposomes trafficked through endosomes and lysosomes. This series of MFI measurements allowed determination of the amount of liposomes bound and internalized by the cells and thanks to the MO treatment the type of uptake. On this base, the cell surface binding upon 3h incubation at 37°C was determined from MFI measured without any treatment minus MFI measured in the presence of TB. Of note: cells were harvested without trypsin in order to prevent harvesting of liposomes bound on the cell surface. The intracellular quantity of liposomes was determined from MFI measured upon monensin treatment -which rose the fluorescein fluorescence quenched in acid intracellular compartments such as endosomes and lysosomes -minus fluorescence (MFI-MFITB) corresponding to liposomes bound on the cell surface. Moreover, increased MFI upon monensin treatment meant that liposomes uptake likely occurred through acidic compartments such as endosomes and lysosomes, presumably via clathrin-dependent endocytosis. Although, Tri-Man (1b) bound more on the surface of DC2.4 cells, their intracellular quantity was close

  C NMR (CDCl3, 75 MHz) δppm 179.6 (COOH); 51.0 (C-d); 33.4 (C-a); 28.1(C-c); 21.8 (C-b) (Supplementary Figure5a).

  H NMR CDCl3, 300 MHz) δ(ppm) 8.19-7.40 (m, 10H, 2 C6H5COO); 6.52 (d, J = 9 Hz, 1H, NHCO); 5.75 (t, J = 9.9 Hz, 1H, H-4A); 5.70-5.62 (m, 2H, H-1A + 1H); 5.37 (dd, J = 3.4 Hz, J = 10Hz, 1H, H-3C); 5.31 (dd, J = 1.7 Hz, J = 3.4 Hz, 1H, H-2B or H-2C); 5.23 (t, J = 10 Hz, 1H, H-4C); 5.09 (t, J = 9.6 Hz, 1H, H-4B); 5.00 (dd, J = 3.5 Hz, J = 9.7 Hz, 1H, H-3B); 4.90 (d, J = 1.8 Hz,

  08 ([C-2, C-3, C-5]-ABC, C-4A); 66.30 (C-6A); 65.92 (C-4B, C-4C); 62.29 (C-6B, C-6C); 51.03 (C-d); 35.48 (C-a); 28.16 (C-c); 22.23 (C-b); 20.82, 20.67, 20.61, 20.55, 20.36, 20.26 (CH3COO) (Supplementary Figure 5b). ES-HRMS: [M + Na] + = 1195.3706 m/z calculated for C53H64N4NaO26; found 1195.3715.

  H NMR (D2O, 300 MHz) δ(ppm) 5.21 (d, J = 1 Hz, 1 H, H-1A) 5.11 and 4,84 (2d, J = 1.7Hz, 2H, H-1B, H-1C); 4.11-3.55 (m, 18H, H-2A to C, H-3A to C, H-4A to C, H-5A to C, 2 H-6A to C)); 3.31 (t, J = 6.6 Hz, 2H, CH2d); 2.34 (t, J = 7 Hz, 2H, CH2a); 1.73-1.48 (m, 4H, CH2b, CH2c). 13 C NMR (75 MHz,D2O) δppm 176.91 (NHCO); 102.13, 99.52 (C-1B, C-1C); 80.69, 77.78, 75.77, 73.41, 72.70, 70.57, 70.38, 70.04, 69.88, 69.80, 66.84, 66.73, 66.66, 65.43 (C-1A, [C-2, C-3, C-4, C-5]-ABC, C-6A); 61.06, 60.96 (C-6B, C-6C); 50.75 (C-d); 34.92 (C-a); 27.43 (C-c); 22.29 (C-b) (Supplementary Figure 5c). ES-HRMS: [M + Na] + = 651.2337 m/z calculated for C23H40N4NaO16; found 651.2338.

  H NMR (D2O, 400 MHz) δ(ppm) 8.12 (s, 1H, H-5 triazole); 6,28 (d, J = 1,8 Hz, H, H-1B); 5.06 (d, J = 1.3 Hz, 1H, H-1C); 4.80-4.63 (m, 4H, H-1A, H-2B, OCH2CCHN3); 4.15 (dd, J = 2.5 Hz, J = 6.7 Hz, 1H, H-3B); 4.07-3.99 (m, 2H, H-2A, H-2C); 3.81-3.25(m, 18H, H-3A, H-3C, H-4A to C, H-5A to C, 2 H-6A to C, CH27, CH28 ); 3.24 (t, J = 4.8 Hz, 2H, CH2d); 2.20 (t, J = 5.55 Hz, 2H, CH2a); 1.62-1.45 (m, 4H, CH2b, CH2c). 13 C NMR (D2O, 100 MHz) δppm 176.59 (NHCO); 144.49 (C-4 triazole); 124.71 (C-5 triazole); 101.96 (C-1C); 99.50 (C-1A); 84.89 (C-1B); 78.66, 76.58, 76.17, 73.49, 72.71, 70.21, 69.83, 69.78, 66.61, 65.84, 65.48, 61.57, 60.91, 60.76, 60.35 ([C-2, C-3, C-4, C-5, C-6]-ABC, C-8 and OCH2(CCHN3)); 50,65 (C-d); 38,80 (C-7); 35.20 (C-c); 27.42 (C-b); 22.69 (C-a) (Supplementary Figure 5d). ES-MS: [M + Na] + = 776.3 m/z calculated for C28H47N7NaO17; found 776.6.

  , 65.67, 63.48, 61.80, 60.59 ([C-2, C-3, C-4, C-5, C-6]-ABC, C-8 and OCH2(CCHN3)); 50,83 (C-d); 39.03 (C-7); 35.39 (C-c); 27.63 (C-b); 22.90 (C-a) (Supplementary Figure 5e). ES-MS: [M + Na] + = 857.3 m/z calculated for C31H50N10NaO17; found 857.5.

  H NMR (CDCl3, 600 MHz) δ(ppm) 7.11-7.13 (m, 1H, NH); 4.08 (s, 2H, CH2C≡CH); 3.89-3.92 (m, 1H, CHC=O); 3.75-3.79 (m, 1H, CH2-O); 3.54-3.72 (m, 33H, CH2-O); 3.42-3.50 (m, 4H, CH2-NH,CH2-O); 3.32 (s, 1H, CH≡C); 1.06-1.81 (m, 52H, 24CH2, 4 CH); 0.84-0.87 (m,18H, 6 CH3).

  Two days before experiments, DC2.4 and DC-SIGN expressing HEK293 cells were seeded in 24-well culture plates (1 × 10 5 cells/cm 2 ). hMo-DCs were used after for 5 days of culture in the presence of 10% human AB serum RPMI medium, GM-CSF and IL-4. The day of the experiments, the medium was removed, the cells washed with PBS and incubated for 3h with Flu-Lip in serum free medium. Cells were harvested without trypsin, collected into FACS tubes and washed with PBS. The cell-associated fluorescence intensity was measured with a flow cytometer (FORTESSA x 20, Becton Dickinson) with λex = 488 nm; λem = 530 ± 30 nm. The fluorescence intensity was expressed as the mean fluorescence intensity (MFI) of 10 000 cells. Each tube was analyzed three times. The first time in PBS (total fluorescence), the second time in the presence of Trypan blue (TB) added into the tube at a final concentration of 0.004 % to quench the fluorescein fluorescence associated on the surface of cells. The third time, the fluorescence intensity was measured in PBS in the presence of monensin added 30

Figure 1 :

 1 Figure 1: (A) Structure of the trimannosylated diether lipid (Tri-Man) (1). (B) Glycal azide

Figure 2 :Figure 3 :

 23 Figure 2: Synthesis of the Propargyl-PEG8-diether and glycal-diether lipids

Acknowledgements

We warmly thank Dr. L. Landemarre from GLYcoDiag (Orléans, France). We thank D.

Gosset 1 , the P@CYFIC platform at CBM and C. Baillou 3 for their technical assistance in flow cytometry. The authors acknowledge Drs. D. Lesur (UMR 7378) and S. Pilard (Plateforme Analytique, UPJV, France) for MS and HPLC. This work was supported by grants from "Région Centre Val de Loire" (APR IR 2015 VACARME project), European Community (Univax:www.UniVax-FP7.eu). Haifei Gao received 2 years fellowship from "Région Centre Val de Loire" (APR IR 2015 VACARME project). We certify that there is no conflict of interest, no competing interest and no disclosure.


Akira Otsuki
email: akira.otsuki@univ-lorraine.fr

Luc De

La Mensbruge

Andrew King

Silvia Serranti

Ludovica Fiore

Giuseppe Bonifazi

Non-destructive characterization of mechanically processed waste printed circuit boards -particle liberation analysis

Keywords: Metal deportment/concentration, liberation, elemental analysis, micro X-ray fluorescence, synchrotron, tomography, recycling

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Waste Electrical and Electronic Equipment (WEEE) is one of the fast-growing waste categories in the European Union, with the growth rate of 3-5 % per year (Eurostat, 2018). It is about 3 times higher than the rate of municipal waste. This is the result of massive production of the WEEE and its market expansion based on the technological progress.

PCBs are the fundamental components of any Electrical and Electronic Equipment (EEE); they represent about 3 wt% of the total electronic waste but they contain precious metals such as gold, silver and palladium as well as base metals such as copper [START_REF] Kaya | Recovery of metals and nonmetals from electronic waste by physical and chemical recycling processes[END_REF]. Thus, there is a huge need and potential for recovering valuable materials from WEEEs. Generally, PCB recycling, finalized to recover metallic fractions includes three stages: the process starts with the pre-treatment which include composition analysis and selective disassembly [START_REF] Kaya | Recovery of metals and nonmetals from electronic waste by physical and chemical recycling processes[END_REF]. Then PCBs are reduced in size through mechanical / physical processes such as shredding, crushing, pulverizing and screening [START_REF] Duan | Liberation of valuable materials in waste printed circuit boards by high-voltage electrical pulses[END_REF][START_REF] Ogunniyi | Chemical composition and liberation characterization of printed circuit board comminution fines for beneficiation investigations[END_REF]Wen et al., 2005;[START_REF] Zhao | Recovery of copper from printed circuit boards[END_REF]. Finally, chemical treatments are carried out (i.e. pyrometallurgical and hydrometallurgical processes) [START_REF] Lister | Recovery of critical and value metals from mobile electronics enabled by electrochemical processing[END_REF][START_REF] Veit | Recovery of copper from printed circuit boards scraps by mechanical processing and electrometallurgy[END_REF]. However, their complex and heterogeneous structures (e.g. mixture of number of different metals, plastics, and ceramics in different sizes) and their variation with time, according to technological improvement as well as primary raw material exploitation strategies, lead to the technical difficulties and environmental issues for their effective pre-concentration stages to improve their recycling. One of the limitations is a lack of proper characterization method to quantitatively evaluate the distribution and liberation/association of different components that are spatially different/heterogeneous, without performing strong milling actions.

There are different categories of particle characterization that can be summarized in: destructive and non-destructive ones, as well as those based on imaging and image analysis [START_REF] Otsuki | Characterisation and beneficiation of complex ores for sustainable use of mineral resources: refractory gold ore beneficiation as an example[END_REF]. In both case, any information about elemental concentration/distribution or similar information inside the particles, can be collected. Destructive methods are usually based on the preliminary sample dissolution into acid and the further measurement of the elemental composition by using a chemical method (e.g. atomic absorption spectroscopy, inductively coupled plasma atomic emission spectrometry). Average values of the different metals, referred to a specific sample, is thus obtained.

Non-destructive methods, quick and easy to apply in terms of particle manipulation, can be directly applied without performing any acid digestion. Among them, the most commonly utilized method is X-Ray Fluorescence (XRF). This elemental analysis is based on measurement of the intensities of the X-rays emitted by secondary excitation. The primary beam irradiates the specimens exciting chemical elements to emit secondary spectral lines that have characteristic wavelengths for each element and intensities related to their concentration. Imaging and image analysis that are major point of this study can be performed with the particles immobilized into resin or mobile particles dispersed under the imaging equipment, such as optical microscope, scanning electron microscope. Following this approach, it is then possible to identify the particle liberations/associations that can be spatially heterogeneous. In this paper, we propose a couple of new solutions belonging to this latter approach, i.e. imaging based methods, using X-Ray based analytical devices.

All the analytical tests were carried out with the samples resulting from processing steps specifically set up to selectively concentrate and recover valuable metals from Printed Circuit Boards (PCBs). More specifically in this work we focused on discussing the applications of different non-destructive characterization methods (laboratory and large scale facility based) to study and understand the liberation and metal/non-metal deportment. Those methods can be applied in different stages of the beneficiation (milling and sieving in this specific case study), in order to enhance the metal recovery for recycling purpose.

The degree of liberation, indicating how much the target component is liberated from the non-valuable components, is one of the most important factors to determine the successful enrichment of metals through the subsequent processes, such as physical separation and hydrometallurgical process [START_REF] Koyanaka | Effect of impact velocity control on selective grinding of waste printed circuit boards[END_REF][START_REF] Duan | Recovery of metals from waste printed circuit boards by a mechanical method using a water medium[END_REF][START_REF] Otsuki | Characterisation and beneficiation of complex ores for sustainable use of mineral resources: refractory gold ore beneficiation as an example[END_REF].

There are two major methods, both applied in the mineral processing sector, to analyze the degree of liberation of a component in a sample. They are area counting (e.g. [START_REF] Goodall | The use of QEMSCAN and diagnostic leaching in the characterization of visible gold in complex ores[END_REF] and particle counting (e.g. [START_REF] Abouzeid | Mineral Processing Laboratory Manual[END_REF]. The first method analyzes the surface area of target component/mineral according to the total surface area of the particles containing the target investigated. It has been utilized in the major liberation analyzers associated with the automated Scanning Electron Microscopy (SEM) systems. The current trend in the mineral liberation analysis is shifted towards the generation of large data sets through this automated SEM, such as MLA/QEM-SCAN (e.g. [START_REF] Goodall | An overview of the advantages and disadvantages of the determination of gold mineralogy by automated mineralogy[END_REF][START_REF] Otsuki | Characterisation and beneficiation of complex ores for sustainable use of mineral resources: refractory gold ore beneficiation as an example[END_REF]. This system was developed to analyze the liberation of minerals and have been attracting a lot of attention from both the industry and academic. However, it can be easily identified the potential "intrinsic" difficulty in its application to the analysis of complex electronic wastes due to the nature of samples, furthermore the associated analytical software is specifically designed and set up to analyze only minerals.

The second method, i.e. particles counting, analyzes the number of particles containing the target material liberated over the total number of particles containing the target material [START_REF] Abouzeid | Mineral Processing Laboratory Manual[END_REF]. This approach can be associated with the computer aided optical microscopy.

Both the previously mentioned approaches are 2D based. A 3D based analytical techniques can also be utilized, that is tomography proposed to apply in this paper for the determination of degree of liberation of mechanically processed PCB particles for the first time as far as the authors' best knowledge.

Tomography is another characterization approach to apply. It is a non-destructive method to image the internal structure of an object by the irradiation of X-ray/neutron. The images of the analyzed samples are thus displayed with different grey level tones depending on the constituting materials characteristics. [START_REF] Lin | Cone beam X-ray microtomography for three-dimensional liberation analysis in the 21st century[END_REF] showed the importance of the determination of the degree of liberation through the evaluation of the volumetric mineral grade distribution, starting from the evaluation of the images (i.e. layers), exhibiting significant grey level differences, of particles constituted by dolomite and sphalerite. The same approach is difficult to achieve for particles resulting from the comminution of complex and heterogeneous electronic wastes. Printed circuits boards can be characterized due to the presence of several matrices/materials/elements (i.e. plastics, metals. alloys, etc.) presenting a different response to X-ray. [START_REF] Zeng | Contrast Enhancement Methods Based on Gray and Its Distance Double-Weighting Histogram Equalization for 3D CT Images of PCBs[END_REF] analyzed uncrushed printed circuit boards utilizing a 3D analytical approach based on the Cone Beam Computed Tomography. They worked on the contrast characteristics of the 3D images trying to identify the difference in chemical compositions, based on the differences in the grey levels. Their study did not allow to associate brightness (i.e. image grey level values and resulting voxels associated to the 3D reconstruction) to particles' compositions. On the other hand, this aspect is of great relevance to perform PCBs milled products (i.e. particles) composition determination and material/element deportment and liberation/association assessment as performed in this work for the first time.

Within the above outlined frame, this study analyzed the liberation of metals in comminuted PCBs by hammer mills, using (a) a bench top micro XRF mapping and performing elemental analysis by a portable XRF, (b) optical microscopy based imaging and (c) 3D reconstructed images obtained from Synchrotron X-Ray Tomography. The results of all the procedures were finally discussed with specific reference to the metal degree of liberation and different metal associations. The advantages and disadvantages of the three different methods proposed were also discussed as a summary of the work.

MATERIALS AND METHODS

Materials

Printed circuit boards (origin confidential) were comminuted through shredding and hammer milling followed by sieving. The shredder (Broyeurs-Compacteurs-Destructeurs, BLik) with six thick rotary blades, and equipped with a round sieve opening of 1 cm, was used to crush PCB particles. The hammer mills used were Broyeur Raymond (Laboratoire Stein et Roubaix; called HM1 in this article) with 12 hammers, 5 mm round sieve openings and approximately 630 cm 3 free space inside and AR6539 (FORPLEX 00; called HM2 in this article) with 6 hammers, 1.5 mm round sieve openings, 10 cm mill diameter. Hammer milling has been reported as a selective liberation method for metals from PCBs based on the impact force applied through rotating hammers (e.g. [START_REF] Koyanaka | Effect of impact velocity control on selective grinding of waste printed circuit boards[END_REF]Otsuki et al., 2019-a;Otsuki et al., 2019-b). In this study, two size fractions (i.e. 0.125-0.350 mm, 0.350-0.500 mm) were selected based on our preliminary study identifying the significant difference in the degree of liberation in order to demonstrate the three different approaches to determine the degree of liberation (Eq.1; [START_REF] Abouzeid | Mineral Processing Laboratory Manual[END_REF].

(1)

Where 'Nunclocked', indicates the number of free particles of the metal of interest and 'Nlocked' is the number of interlocked particles, either with other metals or with non-metallic fraction, i.e. plastics, glass and ceramics.

In this study, three different methods were performed in order to identify valuable materials for recovery and to evaluate the degree of liberation in two different size fractions. Finally, the results obtained were compared. The three methods are: micro XRF (sections 2.2.2 and 3.2), optical microscopic analysis (sections 2.3 and 3.3), tomography (sections 2.4 and 3.4). Also, a square peace cut off from the uncrushed PCB was used to analyze the elemental composition prior to the comminution. X-ray fluorescent (XRF) analysis was applied to evaluate the elemental composition of the uncrushed and crushed PCBs.

Methods

Elemental analysis: portable XRF

XRF measurements for crushed PCB particles and uncrushed PCB characterization were performed with the portable XRF machine (Niton XL3t GOLDD+, Thermo Scientific) in-stand where the analyser was locked on a stationary stand and remotely operated through a connected PC. The Mining Cu/Zu testing mode equipped the full fundamentals parameter algorithm was used and the measurement duration was 120 s / point. Particles were put into a plastic container with X-ray thin film (TF-160-255, MYLAR, Port St. Lucie, FI, USA) window facing the X-ray beam and they were measured to have the elemental composition. The minimum 5 points from each sample were measured while their average and 95% confidence interval were calculated.

For the uncrushed PCB, 20 different points were measured while their average and 95% confidence interval were also calculated.

Elemental analysis: Micro XRF

Micro X-Ray Fluorescence (micro-XRF) can be used to analyse both qualitative and quantitative composition of samples and allows high sensitive and non-destructive analysis of elemental composition [START_REF] Bruker | Physical Principles of Micro-X-ray Fluorescence -M4 Tornado[END_REF]. In this study, chemical composition and element distribution were obtained using a Bruker M4 Tornado micro X-ray-fluorescence with a Rhodium filament. The applied measurement conditions for the analyses were: pixel time 6 ms/pixel, high voltage 40 kV, anode current 500 μA, step size 50 μm, and cycles 2.

Micro-XRF was applied to obtain the chemical maps of the PCB samples. With the M4 Tornado software, these results can be presented as element distribution maps with element intensities in false colors. Using micro-XRF to produce element maps is a potentially way of determining the elements present and their distribution in the sample.

Sample preparation

The micro-XRF analysis was carried out for uncrushed PCB in order to obtain the complete mapping. Crushed PCB particles were gently mixed and a small portion was dispersed on a plexiglass support. In some cases, overlapped particles were manually separated by using a spatula. To avoid particle dispersion and their movement during acquisitions, the plexiglass support was lined with a transparent film (Supplementary Figure 1). At the end of this sample preparation procedure, the micro-XRF analysis was performed to evaluate the elemental composition.

Particle counting

The ImageJ, 64-bit version Java 1.8.0_112 (70MB), was used for particle counting.

The manual counting method was used by the "Cell counter" plug-in (Plugin -Analyze -Cell Counter). This plug-in consists of increasing the number of particle as they are selected by the user. For example, Figure 1 shows the procedure used to calculate the number of particles present in the samples analysed.

Optical microscopic analysis

A binocular optical microscope was used to capture images for their analysis to perform the liberation analysis of mechanically processed PCB particles. The optical microscope (Nikon SMZ 1000 with the eyepieces C-W10xB/22 Nikon) with objective lens (Plan Apo 1xWD70, Nikon) was used. It was connected to a PC with the digital camera head (Digital Sight DS-Ri1, Nikon) to save images as digital data. The light source was given by using KL 1500 LCD SCHOOT. The details of the analysis will be given in the following sections.

Sample preparation

The aim of optical microscopic observation was to count metal, non-metal, and locked particles and total number of particles by observing representative samples of the crushed PCB particles, and to calculate the degree of liberation. The comminuted sample stored in a plastic container was gently mixed, its small portion was taken, and gently dispersed on a glass petri dish to aim one particle layer without overlapping. In addition, if necessary, overlapped particles were manually separated by using a spatula prior to the commencement of image acquisition.

Then, particles are ready to observe under the microscope.

The optical microscope was focused on particles and start taking images. A series of images of the sample was taken aiming to capture approximately 1000 particles and build a map of particle images. The particle numbers were aimed to count enough number of particles to achieve a statistically representative analysis.

Particle counting

Images taken at different spots of a sample were merged, and the number of aluminum, copper and other type of metallic particles (e.g. alloys) were counted with the software ImageJ after the analysis preparation steps being introduced in the following sections.

The aim of this work is to evaluate the degree of liberation of metal particles; thus, the composite particles (e.g. plastic-metal composite) were considered as locked particles. The direct use of the image analysis software to process a raw image could not be achieved. The ImageJ software can recognize the shape, the brightness and the color of the particles. Thus, for example, a composite of three particles is defined as 3 separated particles according to the software regardless the fact that they are locked. Such analysis is inappropriate and its correction was necessary. In addition, the contrast between particles and the background was not very high.

Black plastics coexisted with white and clear white plastics; thus, a black or a white background cannot help to improve the contrast of all the particles. Supplementary Figure 2 shows the optical microscopic images of crushed PCB particles in 0.125-0.350 mm size fraction. The other graphic software (Inkscape) was used to manually identify individual particles prior to particle counting.

To solve the problems of the direct analysis with the ImageJ, small dots with different colors were plotted on top of each image (Figure 2 (a)) with another software Inkscape to identify the particles before counting with the ImageJ. Different colors were assigned to the different types of particles (e.g. metals, plastics) and their liberations/associations (i.e. liberated, locked). Then, the number of particles can be counted directly by using the ImageJ software upon keeping the dots with applying a white background.

Each image was binarized using the ImageJ software. The color of the particles and their shape can then be easily identified.

Inkscape allowed to combine all the images into one file and to build the entire surface to study (Figure 2 (b)). The same particles between different images were identified and counted only once with this method. Plastic particles were identified in pink dots while metallic particles were given in red dots. Lines were also drawn to limit the surface to study when the same particles were observed in different images.

Tomography

The images resulting from tomographic analysis showed as the color of plastic particles vary between black and grey while metallic particles are seen much more bright. The brightest particles in PCBs accounted for Cu. Stucks of 2D images can be used for 3D reconstruction; but this study worked on mainly 2D images with the use of neighboring images to capture the association of the particles situated in the specific 2D cross sections selected for this investigation. Measurements were made in Pisché beamline at synchrotron Soleil [START_REF] King | Tomography and imaging at the PSICHE beam line of the SOLEIL synchrotron[END_REF], a light beam dedicated to X-ray diffraction and tomography by absorption contrast at high level of energy (20-50 keV). This beam line allowed us to optimize the setting for improving the contrast between different particles utilizing the strong X-ray and variety setting options while our preliminary study by using a laboratory X-ray tomography machine showed the difficulty to achieve that objective due to its limitation for distinguish different particles by keeping a good contrast between different particles.

For the sample HM 2b (0.125-0.350 mm), 624 cross sectional images were made with the sample within a four centimeter high plastic tube. The aim is to analyse different layers of the sample and to realize the same work of particle counting as for optical microscopic observation.

Particle counting

The 624 cross sectional images were obtained as a continuous images of the sample. Then, the shape, structure and association of particles were observed and studied. Inkscape was used to identify metal and plastic particles with the same methodology applied to the optical microscopic image analysis. In average 250 particles were counted on each image (the diameter of circular section was 1 cm). Eight cross sectional images significantly separated each other were used to count more than 1000 particles for the representative analysis and describe the sample in order to avoid counting the same particles repeatedly from the neighboring images. They are the #1, 100, 200, 300, 400, 550, 600, and 624. The size of particles in the HM 2b sample are below 350 μm; thus the gap of more than 20 images was enough to observe and count totally different particles.

The #500 had many artefacts, and the measurement was thus replaced by the analysis of the image #550. A typical image after the contrast optimization used for the analyses is given in Fig. 2 (c) with different color dots assigned to plastic (pink) and metal (red) particles shown in Fig. 2 (d).

RESULTS AND DISCUSSION

Portable XRF measurements

Supplementary Table 1 shows the results of XRF analyses of the crushed PCBs with the hammer mill (a) in comparison with the uncrushed PCB (b). The size of particles are in the range of 0.125-0.350 mm and 0.350-0.500 mm. The metals with the abundant concentrations were listed. The Cu is the major element (35% in uncrushed PCB) of this PCB that corresponds to the optical microscopic observations and agreed with literature (e.g. [START_REF] Ghosh | Waste printed circuit boards recycling: an extensive assessment of current status[END_REF], followed by Al and Si (Supplementary Table 1). Other metal elements are also detected; but it was hard to identify as liberated particles under the microscope due to the trace elemental concentration and the possible alloy formation. In this study, we focused on Cu and Al for the determination of their degree of liberation.

The uncrushed PCB contains nearly three times higher Cu than the crushed ones. This indirectly indicated that the Cu was successfully separated into other size fractions from the fractions of 0.125-0.500 mm. There was more than 30% of copper in the uncrushed PCB determined from the results of the 20 measurements in its different locations. The uncrushed PCB also contained 13% of sulphur while the crushed PCB contained much smaller than 1% (results not shown in Supplementary Table 1). This indicates that the rejection of sulphur from the size fractions studied and enrichment in other size fractions. On the other hand, the aluminium concentration in non-treated PCB was close to two times smaller than the one in the crushed PCB (1.6% to 3.1-4.5% in 0.125-0.50 mm). This means that the aluminium was enriched into the size fraction studied after the hammer milling, especially in 0.125-0.350 mm.

The elemental concentration in this uncrushed PCB varied: the 95% confidence interval of Cu was 4.95% while the one of Al% was 0.15 from the measurement of 20 different locations.

Generally speaking, the elemental distribution within the uncrushed PCB is not homogeneous which agreed with the micro-XRF results shown in the section 3.2, and thus studying a series of different spots is required to have statistically representative results and capture the clear idea of their compositions. More discussion on the portable XRF results can be found in (Otsuki et.al, 2019-a).

Micro XRF measurements

Uncrushed PCB

Figure 3 shows the digital image and micro-XRF elemental mapping, indicating the element distributions of the uncrushed PCB. The micro-XRF analysis made it possible to identify the chemical elements and to associate them with their functions.

The copper (Cu, Figure 3 (c)) is the major element of this PCB due to its good characteristics of electrical and thermal conductivity. The superficial green layer of PCB is called solder mask. It is a thin layer of polymer, like a lacquer, which is applied in PCBs to protect against the oxidation and to avoid the formation of bridges between close welds [START_REF] Mitzner | Complete PCB Design Using Or CAD Capture and layout[END_REF]. The solder mask contains silicon (Si, Figure 3 (f)), which is used to control the viscosity of the liquid welding mask before polymerization, barium (Ba, Figure 3 (d)) and sulfur (S, Figure 3 (f)), used as a flame retardant [START_REF] Woolley | Corrosives on a PCB: Finding the source[END_REF]. The serigraphy (letters, numbers and symbols) that identifies the components on the board, is made of titanium (Ti, Figure 3 (e)). Other materials present inside the PCB are the ceramics; these possess insulating, semi-conductive, superconductivity, piezoelectric and magnetic properties which made them fundamental materials for microchips and other components present in printed circuits. A ceramic material usually consists of a metallic element and a non-metallic element, such as SiO2 or Al2O3 [START_REF] Veit | Electronic waste. Recycling Techniques[END_REF]. In fact, Figure 3 (f) indicates the presence of silicon in the chips mounted on the board. In the assembly and interconnection of silicon chips, welding plays a crucial role. The soldering based on lead and tin (63% Sn and 37% Pb) are the classic connection material; Figure 3 (g) show the presence of tin (Sn) and lead (Pb) based solders used for the connection. The sample also contains the bromine (Br, Figure 3 (h)). Bromine is used as a flame retardant, in order to prevent the propagation of an accidental combustion in the electric circuits of electrical and electronic equipment. Noticeable and aligned Br concentration was identified. One can see the PCB producer's intention to segregate several different small equipment colonies to avoid the fire propagation to all the surface. About precious metals such as silver (Ag) and gold (Au), they are found in specific areas such as inside the microprocessor circuit and in contacts. Specifically, connector pins are made of gold and nickel alloy while the gold present in the microprocessor is pure (Figure 3 (j)).

Crushed PCB

The two different particles size classes (i.e. 0.125-0.350 mm, 0.350-0.500 mm) were analyzed, using micro-XRF based mapping in order to identify the alloys, the metals constituting the individual particles and thus the degree of liberation. The analysis showed that most of the metallic particles were weakly locked (<20-30% of particle surface) with plastic, glass fiber, or other metals, in different degrees. The majority of those composites contain small quantities of secondary element (e.g. Br in Cu host in Figs. 4 (b); Si and Ca in Al host in Fig. 4 (d)) that are hard to recognize under the optical microscope due to their small quantities and similar optical properties with the host material most of the cases. Degree of liberation varies with the type of elements (i.e. Cu, Al, other metals) and particle size. Figure 4a, 4b, 4c and4d show some locked and unlocked Cu and Al particles identified in the sample HM2b (0.125-0.350 mm). In general, the combination of micro-XRF mappings and stereomicroscope images can help a good identification of liberation/association of metallic components with the PCB particles mechanically processed.

Table 1 summarizes all the results of the analyses carried out on the size fraction 0.125-0.350 mm (HM2b) by using the combination of stereomicroscope images and micro-XRF mapping.

The results indicated that the population of unlocked Al particles (1.88%) were twice of the one of Cu (0.94%), out of 319 particles counted, and the degree of unlocked Al particles (86%) was higher than Cu (30%). Their degree of liberation will be further discussed, together with the results of the coarser size fraction (0.350-0.50 mm). Figures 4e, 4f, 4g and 4h show some locked and unlocked copper and aluminium particles identified in the sample HM2a (0.35-0.50 mm). Although the trend is similar with the fine size (0.125-0.350 mm, Figures 4 (a)-(d)), the analysis showed that composite particles were strongly locked (<60-70% of particle surface) with plastic, glass fiber, or other metals, in wider range of locking degrees (10-70%) than the fine size fraction (10-30%, Figures 4 (a)-(d)). Also, more elements are associated with the host metallic element (e.g. Cu with Al, Si, Ca, Fe, Cu and Br in Table 1 also shows the results obtained for the HM2a sample (0.350-0.500 mm). These show that the population of unlocked Al particles (1.20%) were the same as Cu (1.20%), out of 249 particles counted although their degree of liberation is smaller (15% Cu, 60% Al) than the ones in the fine size fraction (30% Cu, 86% Al in 0.125-0.350 mm) and will be further discussed together with the results of finer size fraction.

The combination of the stereomicroscope and the micro-XRF analyses showed that most of the metallic particles are locked with plastic, glass fiber and/or other metals. This analysis made it possible to determine the distribution of Cu and Al in the particles and therefore to evaluate their degree of liberation. As shown in Table 1, in the coarse size fraction (0.350-0.50 mm), the number of locked particles is higher than the fine size fraction (0.125-0.350 mm). Table 1 shows the degree of liberation of Cu and Al, calculated by using the results of the combination of stereomicroscope and micro-XRF mapping. Apart from Al in 0.125-0.350 mm (86%), the degree of liberation based on this particle counting method is generally low (<60%) as shown in the Table 1, since the detection of small quantities of other elements within the host metallic elements (Cu, Al) decreases the degree of liberation based on the particle counting. Area counting would increase the degree of liberation and the results could be more representative and useful, especially for the separation/process unit operations utilizing surface or bulk properties of materials of our interest (e.g. Cu, Al) for their selective recovery for recycling. The comparison between the particle counting and area counting is out of focus of this paper and will be published in a separate paper.

Optical microscope analysis

Table 2 shows the results of particle analysis of the HM2b sample with the size fraction 0.125-0.350 μm with the optical microscope. The 18 images were recorded after spreading the particles on a glass surface. In each image, the number of liberated/unlocked and locked copper, aluminium, other metals (e.g. alloys) particles were counted. Then, the percentage of the copper, aluminium and total metal were calculated for each image and summarized to capture all the information for the entire surface. The results indicated the Cu 1.66%, Al 4.15% were presented as unlocked particles out of 1326 particles counted.

The efficiency of hammer milling to liberate metals was determined by calculating the degree of liberation of main metals, i.e. Cu, Al, alloys. The results showed a high degree of liberation reaching 85% of Cu, 90% of Al bearing particles. Thus, in total 89% of metal particles were liberated in this size fraction after the hammer milling. The precision of the value could depend on the operator. S/he has to identify the locked particles by differences in shape, contrast, brightness and color of the particles within the grains. Then, there are potentially three major source of errors: (1) a size of the plastic or the metal locked in the grain can be relatively small to be distinguished under the optical microscope that aims to capture many particles for a representative measurement; (2) the contrast between copper and black plastic particles is huge and could hinder those plastic particles; (3) 2D image observation that could be difficult to identify whether particles are locked or liberated but simply overlapped or attached by the electrostatic forces. The 3rd issue can be addressed by using the 3D information extracted from tomographic images and applied in this study. Therefore, there has to be a good balance between the number of particles counted and the image quality of the particles. In addition, a proper dispersion of individual particles without overlapping each other is significantly important. The HM2a sample containing coarser particles (0.350-0.500 mm) was also analyzed in order to compare the results with the finer size fraction (0.125-0.350 mm, Table 2). Over 28 images taken, 1234 particles were counted and analyzed. Almost all the copper particles were locked with plastic or other metals (aluminum, alloys). Also, for aluminum particles or other metals (e.g. tin, alloys), the degree of liberation was low. It means that the size reduction through the hammer milling was not sufficient in this size fraction. Less than 15% of the copper was liberated while 53% of aluminum did. In general, the degree of liberation of metals was 45% that was significantly lower than the value obtained by the finer size fraction (89% in 0.125-0.350 mm). The above mentioned trend observed by the optical microscopic image analysis is similar with the results obtained by the combination of the stereomicroscope and micro-XRF imaging although their degree of liberation is higher (85% Cu and 90% Al in 0.125-0.350 mm in Table 2) than the latter combination (30% Cu and 86% Al in 0.125-0.350 mm in Table 1). This can be due to the different nature of the two methods applied, as mentioned in the previous sections, especially in terms of recognition of composite particles.

Tomographic image analysis

Total 2050 particles were counted over the images of the HM2b (0.125-0.350 mm) crushed sample. Approximately 250 particles were identified in each image. The challenge was associated with the contrast of each image to identify the dark plastic particles. Some particles seen as isolated in one cross sectional 2D image can be locked with other particles. Thus, the neighboring images were also checked to identify whether they are really isolated or not, with the utilization of the 3D information to track the whole surface of the particles. By knowing such potential errors and utilizing 3D option, the degree of measurement errors kept low with respect to the total number of particles counted in each image. Table 3 contains all the measurement results of particle analysis of the HM2b sample with the size fraction 0.125-0.350 mm with the tomographic images.

Through the analyses of tomographic images, it was rather difficult to distinguish the different types of metals due to the small difference in their grey levels. Thus, only the liberation of the total metal particles (bright particles in tomographic images) was determined. This is different from the case of [START_REF] Lin | Cone beam X-ray microtomography for three-dimensional liberation analysis in the 21st century[END_REF] who studied only two mineral components that have the significant grey level difference indicated by the complete spectra isolation. The liberation % of metal was 80.26% for 152 particles. The value is close to the one identified with the analysis of the optical microscopic images (89%), but away from the one obtained with the micro-XRF analysis (54%). With tomographic images, the identification of the nature of particles is rather limited with the grey scale difference given in the tomographic images due to the limited access to the different range of colors associated with them. On the other hand, utilizing both the grey level and shape of the particles can help us the particle composition. For example, the shape of cable for the brightest particle allows us to identify it as copper cables. With the micro-XRF mapping, the detection of small quantities (<20-30% of particle surface) of secondary elements in the host metallic particles (e.g. Br in Cu, Si and Ca in Al) made the degree of liberation by the particle counting method lower than the other two methods.

Comparison between the analyses using micro XRF and image analyses

The three methods provided the similar results in terms of the general trend (i.e. higher degree of liberation with fine particles than coarse particles) with some variation in the absolute values in the degree of liberation and some access limitation (i.e. synchrotron X-ray tomography). The micro-XRF results showed the lower degree of liberation values than the other two methods, by particle counting. This is due to the capability of micro-XRF to detect small quantities of secondary material(s) within the host Cu/Al particles while those secondary materials can be hard to recognize due to their quantities and/or similar optical/physical properties with their host by using either optical microscope or tomography images.

In any of the three methods, the experimental work in the above-mentioned image analyses showed that the precision of the data and analysis could depend on the contrast and the resolution of the images. In addition, the preliminary knowledge about the nature of the sample (e.g. composition, association) would be of great help for the better analyses, as applicable to all the other analyses (e.g. electron microscopic analyses). Table 4 shows the summary of advantages and disadvantages of micro-XRF, optical microscopic and synchrotron tomographic image analyses for the mechanically processed PCB particles.

The light elements (for example the C present in the plastics) cannot be analyzed by micro-XRF because are weak absorbers and relatively strong scatterers of X-rays. During the optical microscopic observations, the presence of the different types of the color and brightness of particles prevented us from select the best background for all the particles in order to maximize the contrast. In tomography, the grey scale and the artifacts made difficult the identification of the light plastic particles seen as dark spots. Meanwhile, it was relatively easy to identify the locked particles with the both optical microscopic and tomographic images while the tomographic images allowed us see the entire structure of each particle using the 3D information captured. identified in the coarse size fraction whose trend agreed with the anticipation.

Onsite sampling and measurement to evaluate the degree of liberation and processing performance tuning and the metal recovery performance prediction would be highly efficient and beneficial for recycling process in the future. In order to achieve those goals, next steps would be the application of the proposed methods to confirm their applicability to different materials as well as optimization and automation of the image analysis procedures. Figures Table 1. Metal and plastic particles counted using the stereomicroscope images and micro-XRF mapping, and calculated degree of liberation of metals in hammer mill products 0.125-0.350 mm (HM2b) and 0.350-0.500 mm (HM2a).

Tables and

Particle size

Cu Al

Fig. 1

 1 Fig. 1 goes here.

Fig. 2

 2 Fig. 2 goes here.

Fig

  Fig. 3 goes here.

Fig. 4

 4 Fig. 4 goes here.

Figure 4

 4 Figure 4(f); Al with Si, Ca and Fe in Figure 4 (h)) than the ones in fine size fraction (e.g. Cu with

Fig. 1 .

 1 Fig. 1. Particle counting using the "Cell counter" plug-in inside ImageJ environment.

Fig. 2 .Fig. 3 .Fig. 4 .

 234 Fig. 2. (a) Individual particles assigned with dots, and (b) combined images with the dots. Sample HM2b 0.125-0.350 mm. (c) A cross section of tomographic image after contrast adjustment and (d) dots assigned for particles. Sample HM2b 0.125-0.350 mm.

Table 1 goes here.

 1

Table 2 goes here.

 2

Table 3 goes here.

 3

Table 4 goes here.

 4

Table 2 .

 2 Metal particles counted using the optical microscopic images, and calculated degree of liberation of metals in hammer mill products 0.125-0.350 mm (HM2b) and 0.350-0.500 mm (HM2a).

		% unlocked
		particles against
	Total	total number of
	number	particles
	of	counted
	particles
	counted

Table 3 .

 3 Metal and plastic particles counted using the tomographic images. Sample HM2b (0.125-0.350 mm).

	Image number	Number of particles Metal Unlocked Locked	Total	% unlocked metal particles against total number of particles counted	Degree of liberation (%)
	1	9	2	266	3.38	81.82
	100	12	2	260	4.62	85.71
	200	9	3	330	2.73	75.00
	300	16	3	260	6.15	84.21
	400	13	6	260	5.00	68.42
	550	18	2	206	8.74	90.00
	600	21	5	247	8.50	80.77
	624	24	7	221	10.86	77.42
	TOTAL	122	30	2050	5.95	80.26

Table 4 .

 4 Advantages and disadvantages of micro-XRF, optical microscopic and tomographic image analyses for mechanically processed printed circuit board particles.

	Micro XRF	Optical microscope	Synchrotron tomography
	Advantages	Drawbacks	Advantages	Drawbacks	Advantages	Drawbacks
	Fast multi-	Light elements	Particles can be	Results could	Large number of	Difficulty to
	elemental and	(Li, Be, B, C, N,	directly	depend on the	particles can be	distinguish
	non-destructive	O and F) are	manipulated to	operator's skill	imaged in a	different
	analysis.	weak absorbers	disperse under	and knowledge	short period of	metals using
	No need of	and relatively	the microscope	about the	time.	their
	sample	strong scatterers	prior to the	sample.		differences in
	preparation.	of X-rays, cannot	commencement			grey levels in
		be analyzed.	of the image			the presence
			acquisition.			of many
						different
						components.
	The creation of	The detection	Access to the full	Time	3D image	Resolution
	elemental maps	limit (LOD) for	color range of the	consuming; use	acquisition to	depending on
	was realized to	heavy elements is	particles in the	of 2D image	study the whole	the machine
	check the	greater than 20	sample.	could be	particle surface.	and setting.
	chemical	ppm.		difficult to
	composition and			study
	its			overlapped
	distribution/assoc			particles and
	iation.			particle
				association in
				the vertical
				direction.

ACKNOWLEDGEMENTS

The author would like to acknowledge the contribution from Ms. Lisa Gasser for sample preparation. A part of results in liberation analysis in this article was presented in Sardinia 2017.

Tomography measurement was performed in synchrotron SOLEIL in using the beamline Psiché.

CONCLUSIONS

The degree of liberation of mechanically processed PCB particles were analyzed by using the images obtained by three different methods, including the methodological developments, for the recycling oriented non-destructive characterization. The three methods were: micro-XRF, optical microscope, and synchrotron x-ray tomography.

The micro-XRF analysis provided the elemental distribution maps of the sample surface and associate them with their functions. It was possible to identify the materials (ceramics, metals, etc.) that are interesting for the material recovery, determine the distribution of the detected element and evaluate the degree of liberation of copper and aluminum in the PCB samples.

The analyses of tomographic images used mainly 2D cross sectional images but also 3D information to investigate whether particles were liberated or not in their whole surfaces. That is one of the major advantages over the analyses of micro-XRF and optical microscopic images.

The other difference is that the utilization of color of the particles in the sample. Optical microscopic images can utilize the variety of colors to distinguish different particles while the tomographic images assign only the grey level difference that makes difficult to distinguish different particles with small grey level difference.

Although the similarities/differences among three methods were discussed, the common issues were also identified. The good knowledge of the sample would be of a great help for the operator to distinguish different particles and decide the particle liberation or locked. On the other hand, their accuracy could depend on the operator's judgment and knowledge about the sample to identify and distinguish different particles and the image resolution. The degree of liberation of metals determined by the optical microscope and tomographic image analyses were very close (81% with tomography; 89% with optical microscope), but different from the ones obtained through the micro-XRF mapping (54%) by the particle counting. In general, the metal particle liberation was very high in the fine size fraction while many locked particles were

Supplementary materials

Supplementary Figure 1. Sample disposition inside the Bruker M4 Tornado. Supplementary Figure 2. Optical microscope images combined for further process. Sample HM2b 0.125-0.350 mm.

35

Supplementary Table 1. Concentrations of the major elements identified by the portable X-Ray Fluorescence (XRF). The analysis is divided by size fractions and for the different hammer mills used (HM1 and HM2). The metal (wt.%) on the uncrushed PCBs is given at the bottom of the XRF analysis. The 95% confidence interval and absolute uncertainties for XRF and PGAA respectively are also given next to each metal% under the symbol of +/-[Adapted from (Otsuki et al., 2019)].