Thibaut De Terris
email: thibaut.de_terris@ensam.eu

Olivier Andreau

Patrice Peyre

Frédéric Adamski

Imade Koutiri

Cyril Gorny

Corinne Dupuy

Optimization and comparison of porosity rate measurement methods of Selective Laser Melted metallic parts

Keywords: Additive manufacturing, Selective Laser Melting, Porosity, Lack of fusion, Key-hole, Density measurement, Archimedes method, Helium pycnometry, Micrographic cross section

The systematic occurrence of porosities inside selective laser melted (SLM) parts is a well-known phenomenon. In order to improve the density of SLM parts, it is important not only to assess the physical origin of the different types of porosities, but also to be able to measure as precisely as possible the porosity rate so that one may select the optimum manufacturing parameters. Considering 316L steel parts built with different input energies, the current paper aims to (1) present the different types of porosities generated by SLM and their origins, (2) compare different methods for measuring parts density and (3) propose optimal procedures. After a preliminary optimization step, three methods were used for quantifying porosity rate: the Archimedes method, the helium pycnometry and micrographic observations. The Archimedes method shows that results depend on the nature and temperature of the fluid, but also on the sample volume and its surface roughness. During the micrographic observations, it has been shown that the results depend on the magnification used and the number of micrographs considered. A comparison of the three methods showed that the optimized Archimedes method and the helium pycnometry technique gave similar results, whereas optimized micrographic observations systematically underestimated the porosity rate. In a second step, samples were analyzed to illustrate the physical phenomena involved in the generation of porosities. It was confirmed that: (1) low Volume Energy Density (VED) causes nonspherical porosities due to insufficient fusion, (2) in intermediary VED the small amount of remaining blowhole porosities come from gas occlusion in the melt-pool and (3) in excessive VED, cavities are formed due to the key-hole welding mode.

Introduction

The development of Metallic Additive Manufacturing (AM) has greatly expanded since the early 2000s. AM enables the production of components with complex geometries which are impossible to fabricate with conventional processes (forge, foundry,…). Metallic AM processes can be classified in two main categories: (1) direct deposition techniques and (2) powder bed fusion techniques. The first category consists in depositing matter via projected powder or a feeding wire, melted by either a laser or an electric arc. In the second category, the powder-bed can be melted using a laser beam, such as Selective Laser Melting (SLM), or using an electron beam as in the Electron Beam Melting process (EBM). A third technology, the Metal binder jet printing, is also in full development [START_REF] Nandwana | Powder bed binder jet 3D printing of Inconel 718: Densification, microstructural evolution and challenges[END_REF]. There is growing interest in AM because of the wide range of metallic materials that can be used to produce increasingly complex parts. Different applications in various fields such as aeronautics and space, transport, energy, medical, [START_REF] Herderick | Additive manufacturing of metals: A review[END_REF][START_REF] Vayre | Metallic additive manufacturing: state-of-the-art review and prospects[END_REF][START_REF] Epma | Introduction to additive manufacturing technology, a guide for designers and engineers[END_REF][START_REF] Herzog | Additive manufacturing of metals[END_REF][START_REF] Sames | The metallurgy and processing science of metal additive manufacturing[END_REF] already exist. Moreover, AM can provide mechanical properties that are similar or better than conventional processes (such as casting or forging) [START_REF] Herzog | Additive manufacturing of metals[END_REF][START_REF] Sames | The metallurgy and processing science of metal additive manufacturing[END_REF].

There are two main common defects in SLM which directly influence the mechanical properties of the parts: a deleterious surface roughness (with Ra usually superior to 7 µm) and the systematic occurrence of porosities inside the final parts. These defects and their origin are well described by [START_REF] Debroy | Additive manufacturing of metallic components -Process, structure and properties[END_REF] for Ti-6Al-4V and 316L stainless steel. [START_REF] Fatemi | Multiaxial fatigue behavior of wrought and additive manufactured Ti-6Al-4V including surface finish effect[END_REF] also indicates that compared to wrought parts, SLM parts have a significantly lower fatigue life behavior in multiaxial loading conditions, due to internal defects which cause stress concentration.

There are three 1 st order parameters in SLM which directly impact the quality of the fusion: the laser power P (W), the scanning speed V (mm.s -1 ) and the laser beam diameter D (mm). These parameters can be united in a single parameter called Volume Energy Density (VED) [START_REF] Mancisidor | Reduction of the residual porosity in parts manufactured by selective laser melting using skywriting and high focus offset strategies[END_REF][START_REF] Wang | Mechanisms and characteristics of spatter generation in SLM processing and its effect on the properties[END_REF][START_REF] Gunenthiram | Experimental analysis of spatter generation and melt-pool behavior during the powder bed laser beam melting process[END_REF] (Eq. 1). It is also possible to consider other parameters such as the powder layer thickness Δh (µm) or the hatch spacing H (µm) between adjacent fusion lines.

= 4 * * * (1)
With: VED : Volume Energy Density (J.mm -3 ), P : laser power (W), V : scan velocity (mm.s -1 ), D : laser beam diameter (mm)

Several recent works [START_REF] Kaufmann | Influence of process parameters on the quality of aluminium alloy en AW 7075 using Selective Laser Melting (SLM)[END_REF][START_REF] Gu | Influences of Energy Density on Porosity and Microstructure of Selective Laser Melted 17-4PH Stainless Steel[END_REF][START_REF] Campanelli | Capabilities and Performances of the Selective Laser Melting Process[END_REF] have shown that increased VED favors densification. Below a given VED threshold, SLM conditions do not allow for sufficient re-melting of the prior layer, leading to a lack of fusion (LOF) which results in residual pores forming in-betweens layers. Studies also show that small (< 10 µm) blowhole pores (coming from gas entrapment in powder particles and in the powder layer or from powder humidity) are formed throughout the VED range [START_REF] Debroy | Additive manufacturing of metallic components -Process, structure and properties[END_REF]. At high VED, and depending on powder material, the porosity rate may once again increase as shown by [START_REF] Choi | Densiication Behavior of 316L Stainless Steel Parts Fabricated by Selective Laser Melting by Variation in Laser Energy Density[END_REF] and [START_REF] Kasperovich | Correlation between porosity and processing parameters in TiAl6V4 produced by selective laser melting[END_REF].

Various physical phenomena (Figure 1) can explain the presence of local unmelted zones inside a part. These are listed here below:

-Inappropriate manufacturing parameters, mostly corresponding to insufficient VED, can lead to poor overlap between SLM fusion beads (= fusion lines) and thereby increase the amount of unmelted zones. Too much hatching distance and excessive powder layer thickness can also generate a lack of cohesion between SLM beads [START_REF] Li | Densification behavior of gas and water atomized 316L stainless steel powder during selective laser melting[END_REF]. -A high VED leads to the formation of a vapor plume. The interaction between this vapor plume (generated above the impact zone) and the laser can lead to the formation of porosities [START_REF] Andreau | Texture control of 316L parts by modulation of the melt pool morphology in selective laser melting[END_REF]. As shown by [START_REF] Gunenthiram | Analysis of laser-melt pool-powder bed interaction during the selective laser melting of a stainless steel[END_REF] this vapor plume is composed of macro droplets and nanocondensates which interfere with the laser by absorbing the radiation, hence limiting the bead penetration and possibly promoting LOF. -The presence of spatter ejections on the powder bed can also generate porosities. The size of the spatters, usually much larger than the powder grains (< 50 µm), can prevent the powder from spreading homogeneously around the spatter, thus increasing the risk of LOF [START_REF] Wang | Mechanisms and characteristics of spatter generation in SLM processing and its effect on the properties[END_REF][START_REF] Taheri Andani | A study on the effect of energy input on spatter particles creation during selective laser melting process[END_REF].

According to [START_REF] Wang | Mechanisms and characteristics of spatter generation in SLM processing and its effect on the properties[END_REF] there are three types of spatter ejections : (1) metal jet caused by the recoil pressure of the vapor plume associated with the extreme expansion of the powder phase gas, (2) droplet spatters ejected from the turbulent melt-pool flow, (3) powder spatters generated at the powder layer/melt-pool front interface. -The phenomenon of powder denudation investigated in [START_REF] Matthews | Denudation of metal powder layers in laser powder bed fusion processes[END_REF] where the powder surrounding the bead is attracted towards it and causes a lack of powder on both sides of SLM beads. This has two effects: (1) the local powder thickness for the next layer is higher, (2) a non-optimal lateral overlap between beads, due to an excessive hatching distance, which can be a source of LOF [START_REF] Li | Densification behavior of gas and water atomized 316L stainless steel powder during selective laser melting[END_REF]. -Melt-pool hydrodynamic instabilities like balling (favored by low VED) or humping (which appears at high laser powers and velocity) [START_REF] Kasperovich | Correlation between porosity and processing parameters in TiAl6V4 produced by selective laser melting[END_REF][START_REF] Gunenthiram | Analysis of laser-melt pool-powder bed interaction during the selective laser melting of a stainless steel[END_REF] and vaporization affect bead geometry.

Figure 1 -main physical phenomena occurring during Selective Laser Melting

Noting the importance of bead dimensions combined with the hatching distance H (µm) and the layer thickness Δh (µm), Tang [START_REF] Tang | Prediction of lack-of-fusion porosity for powder bed fusion[END_REF] suggested a formula (Equation 2) to geometrically estimate if the overlap is sufficient to avoid LOF. In the Equation 2, W is the SLM bead width and e is the SLM bead depth (in µm) measured in a cross-section which is perpendicular to the scan direction as described in Figure 2.

It can be clearly seen in Figure 2 that to avoid LOF between each of the SLM beads, W must be higher than H in order to guarantee a sufficient lateral overlap, and e must be higher than Δh to provide a sufficient remelting (vertical overlap) of the previous layers and avoid LOF between each of the SLM layers.

∆ 1 (2)
With : H : hatching distance (µm), W : SLM bead width (µm), Δh : layer thickness (µm), e : SLM bead depth (µm) [START_REF] Tang | Prediction of lack-of-fusion porosity for powder bed fusion[END_REF] As indicated before, LOF porosities exhibit angular and random morphologies (Figure 3a), of relatively large sizes (<< 100 µm) and contain unmelted powder. They are located mainly in-between SLM beads and come either from a poor choice of parameters or from process instabilities.

Figure 2 -illustration of the key dimensions to estimate the formation of LOF, according to

A number of near-spherical porosities will always remain, even with a correctly optimized SLM process. They can be divided in two types: blowhole pores and key-hole pores.

-Blowhole pores (Figure 3b) reflect the presence of gas bubbles trapped in the material upon solidification. They are mostly dependent on the properties of the powder bed (compactness, powder contamination) and on the work atmosphere (shielding gas, humidity) as explained by [START_REF] Debroy | Additive manufacturing of metallic components -Process, structure and properties[END_REF]. A powder layer usually has a compactness of around 50 %. During the melting of a layer, a fraction of the gas contained between the powder particles cannot escape before the solidification and gets entrapped as bubbles in the SLM bead. These spherical porosities are located in the heart of a bead and are much smaller than those related to the key-hole. -At high laser intensity (for I > 10 6 W.cm -² according to [START_REF] William | Laser Material Processing[END_REF]) the SLM welding regime turns from a conduction mode into a key-hole mode [START_REF] Qi | Selective laser melting of Al7050 powder: Melting mode transition and comparison of the characteristics between the keyhole and conduction mode[END_REF]. Recoil pressure on the melt-pool generated by intense metal vaporization can create a vapor capillary (key-hole). When the laser beam is absorbed by the key-hole walls rather than the layer surface, this significantly increases the penetration depth and generates thin and deep fusion beads (Figure 3c) as shown by [START_REF] Fabbro | Melt pool and keyhole behaviour analysis for deep penetration laser welding[END_REF]. In this case, porosities come from the collapse of key-hole walls under the action of surface tensions. The destabilization and resulting closure forms near-spherical large cavities with entrapped gas, located near the SLM bead root. Previous works [START_REF] Qi | Selective laser melting of Al7050 powder: Melting mode transition and comparison of the characteristics between the keyhole and conduction mode[END_REF][START_REF] Fabbro | Melt pool and keyhole behaviour analysis for deep penetration laser welding[END_REF] considered the Width-to-Depth Ratio of fusion beads (WDR= W/e) to distinguish conduction mode welds (for WDR >1) from key-hole mode welds (WDR <<1).

Examples of typical porosities obtained during our SLM experiments on 316L steel are shown in Figure 3.

Figure 3 -types of porosities obtained on 316L steel: (a) lack of fusion, (b) blowhole, (c) key-hole cavity

The generation of porosities is a function of manufacturing conditions. It is important to know their physical origins to be able to limit their formation. It is also important to develop experimental methods that permit the analysis of porosity amounts as quickly and as efficiently as possible. Using either micrographic analysis of cross sections [START_REF] Kasperovich | Correlation between porosity and processing parameters in TiAl6V4 produced by selective laser melting[END_REF][START_REF] Parimi | Microstructural and texture development in direct laser fabricated IN718[END_REF], Archimedes method [START_REF] Spierings | Comparison of density of stainless steel 316L parts produced with selective laser melting using different powder grades[END_REF][START_REF] Spierings | Comparison of density measurement techniques for additive manufactured metallic parts[END_REF] or computed tomography [START_REF] Kasperovich | Correlation between porosity and processing parameters in TiAl6V4 produced by selective laser melting[END_REF][START_REF] Spierings | Comparison of density measurement techniques for additive manufactured metallic parts[END_REF][START_REF] Wits | Porosity testing methods for the quality assessment of selective laser melted parts[END_REF], a number of recent works have considered how porosity amounts vary according to SLM conditions,. However, there are very few studies that compare experimental methods to one another [START_REF] Spierings | Comparison of density measurement techniques for additive manufactured metallic parts[END_REF][START_REF] Wits | Porosity testing methods for the quality assessment of selective laser melted parts[END_REF][START_REF] Wang | Scanning optical microscopy for porosity quantification of additively manufactured components[END_REF], and there is a lack of details about which experimental procedures are the most reliable for estimating porosity amounts. Another problem is the lack of uniformity in the results of many recent studies. For example [START_REF] Wits | Porosity testing methods for the quality assessment of selective laser melted parts[END_REF] shows a high degree of correlation between Archimedes method and micrographic analyses, while [START_REF] Spierings | Comparison of density measurement techniques for additive manufactured metallic parts[END_REF] shows these methods yield different results.

The objective of the present paper is: (1) to compare and validate several experimental methods for evaluating closed porosities in SLM parts, (closed porosities are those that are completely isolated inside of the metal, whereas open porosities are pores near the part surface that are not completely enclosed, as shown in Figure 4), and (2) to apply the methods to the study of porosity formation in 316L stainless steel samples.

Figure 4 -open and closed porosities

Experimental methods

Material

The material used for SLM experiments was a gas-atomized 316L stainless steel powder. Particles had a spherical morphology, with a few agglomerated satellites. Their size was between 25 µm (D10) and 60 µm (D90) (Figure 5). The theoretical density of 316L stainless steel is 7.99 g.cm -3 according to the supplier material data sheet. The chemical composition is given in Table 1.

Table 1 -chemical composition of the powder (material data sheet)

SLM conditions

The test samples used for this study were manufactured using an SLM125 HL machine, from SLM Solutions GmbH, under an argon atmosphere and less than 500 ppm O2. They were rectangular cuboids of 10 x 10 x 25 mm.

The manufacturing parameters were kept similar, except for the scanning speed V, as summarized in the Table 2. The manufacturing strategy also remained the same (number of contours, lasing strategy and scheme, hatch distance).

Samples

The Archimedes method

The Archimedes measurements were performed according to the method described by [START_REF]ASTM International, Standard Test Method for Density Of Powder Metallurgy (PM) Materials Containing Less Than Two Percent Porosity[END_REF]. The device used was a Mettler Toledo MS104TS hydrostatic weighing system equipped with a MS-DNY-43 solid sample weighing module. This technique is based on the principle of Archimedes: "A body wholly or partly immersed in a fluid is buoyed up by a force equal to the weight of the fluid displaced" [START_REF] York- | Encyclopedic Dictionary of Polymers[END_REF] (the volume of the displaced fluid is therefore equal to the immersed volume of the body), which enables to determine the volume of the samples, and therefore their density. Samples are weighed in the air and then in a fluid as shown in (Figure 6).

Figure 6 -Archimedes method density measurement

The measurements make it possible to know the mass in the air (Mair) and the mass in the fluid (Mfluid) of each sample. And, knowing the density of the fluid (ρfluid, which varies with the temperature) and of the air (ρair), it becomes possible to calculate the density of the samples according to the Equation 3[28]:

= ! " # $ * % ! " # & (3)
With ρsample : sample density measured (g.cm -3 ), Mair : the mass of the sample in air (g), Mfluid : the mass of the sample in fluid (g), ρair : air density (g.cm -3 ), ρfluid : fluid density (g.cm -3 )

The comparison of the results obtained with the theoretical density of the material enables to calculate the porosity rate of the samples (Equation 4):

% ()*)+,-. = 100 " # * 100 01 2 0 3 (4)
In this study, each sample was measured 10 times, and different fluids (demineralized water, pure ethanol and acetone) were tested. Corresponding fluid properties are shown in Table 3. Between each measurement the samples were oven-dried (110°C, 30 minutes) to evaporate the water trapped in the open pores, in order not to influence the mass in the air during the next measurement. During the measurements it was noticed that air bubbles tend to settle on the surface of the samples because of the surface asperities. In order to improve the density results accuracy, air bubbles shall be removed. Hence, the samples were previously soaked and stirred in an auxiliary beaker containing the same fluid as the one used for the measurements, and the bubbles were evacuated with a brush. The measurements in the fluid were performed with no visible bubbles remaining on the surface of the sample. With this method, a simple measurement takes about twenty seconds, not accounting for the sample preparation time and the analysis of the results, as well as the 10 necessary measurements.

Fluids

Helium pycnometry

The Helium pycnometry measurements were performed on a Micromeritics AccuPyc 1330 device. This technique makes it possible to determine the absolute density of a sample (solid or powder) after the measurement of its volume. The measurement process consists in placing a sample in a tank whose volume V1 is calibrated and perfectly known, at atmospheric pressure Pa. This tank is then filled with helium at a pressure P1. The gas is then expanded to a pressure P2 in another atmospheric pressured empty vessel (called expansion), of a volume V2 (Figure 7).

Figure 7 -helium pycnometry density measurement

The pycnometer measures the volume of a displaced gas from a primary tank (Vtank) at a pression P1 to an expansion tank (Vexpansion) at a pression P2. The pressure variation permits to determine the volume of the sample (Vsample) and the application of the Mariotte's law allows calculating this volume (Equation 5):

= 0 45 6 4 24 7 1 (5)
With Vsample : sample volume measured (cm 3 ), Vtank : volume of the sample tank (cm 3 ), Vexpansion : volume of the expansion tank (cm 3 ), P1 : gas pressure in the sample tank (kPaG), P2 : gas pressure in the expansion tank (kPaG), Pa : atmospheric pressure (kPa)

Since the mass has been measured accurately beforehand, and knowing the volume of the sample, it is possible to calculate its density. In the case of helium pycnometry, several purge cycles are previously performed to remove all the air present in the tank and in the open pores of the sample. Then 10 successive measurements are made while keeping the tank closed and airtight. Samples were ovendried at 110°C during 30 minutes, and air cooled before helium pycnometry measurements. This method, composed of 10 cycles, takes about 45 minutes per sample.

Micrographic cross section

SLM Samples were cut, resin mounted and polished to realize micrographs. These micrographs were acquired on the XY (perpendicular to the manufacturing direction) and YZ (parallel to the manufacturing direction) planes (Figure 8) using a ZEISS Axio Imager optical microscope. Three different magnifications were compared (x50, x100 and x200) as well as various number of micrographs. The images were acquired in similar light conditions and were binarized using the same threshold. They were analyzed by image processing (Python script) to know the porosity rate of the sample (ratio between the number of black pixels and the number total of pixels). It has to be noticed that, unlike the first two methods, micrographic analysis provides a porosity rate and not a density measurement.

Figure 8 -micrographic cross sections porosity measurement

According to [START_REF] Gu | Influences of Energy Density on Porosity and Microstructure of Selective Laser Melted 17-4PH Stainless Steel[END_REF], micrographs can also be used to calculate pore circularity (PC) and determine their origins. The closer (PC) is to 1 (which is the maximum), the more circular is a pore. A low PC corresponds to LOF porosities whereas higher PC provides an estimation of entrapped gas porosities. This shape factor can be calculated with the following formula (Equation 6) where PC is the pore circularity, A the pore area (pix²) and Pp the pore perimeter (pix) :

8 = 4 * * 9 ( (6)
With: A : the pore area (pix²), Pp : the pore perimeter (pix)

This analysis is complementary to the Archimedes method or helium pycnometry because it allows to locate the pores in the sample, in order to estimate their size and shape. However it should be reminded that the closed pores related to a lack of fusion are full of powder whereas retained powder is removed during the polishing of the surface. This can induce a difference between the results of the various methods, especially for samples containing many LOF porosities. On the other hand, the metallographic method does not take into account the entire sample, but is only representative of the observed zones. This method last at least three minutes, considering only the micrographs acquisition of 4 different analyzed surfaces.

Comparison and optimization of experimental methods for porosity rate determination : experimental results and discussion

To achieve the most accurate measurements possible with the Archimedes and micrographs methods, various tests were conducted to determine the ideal measurement conditions for both methods.

Optimization of the Archimedes method

Concerning the Archimedes method, different fluids (such as demineralized water, pure ethanol and acetone) were tested. Then the influence of surface roughness and sample volumes on measurement accuracy was addressed.

First, it appears clearly that demineralized water shows the lowest porosity rate among all the fluids (unlike [START_REF] Spierings | Comparison of density of stainless steel 316L parts produced with selective laser melting using different powder grades[END_REF] which does not show differences between water and acetone), but the highest standard deviation. Pure ethanol exhibits the highest porosity rate with the lowest standard deviation (Figure 9). Since this true density value is not exactly known during the measurement, the theoretical density was considered and determined via tables (such as the International Alcoholometric Tables [START_REF]OIML, International Alcoholometric Tables[END_REF]), knowing the temperature of the fluid.

The end result is therefore particularly dependent on the chemical composition and temperature of the fluid, and the accuracy with which the temperature is measured. Thus, a slight inaccuracy in the measurement of the fluid temperature combined with a large ∆ρ parameter (Table 3) has a clear influence on the final result. As an example, in the case of a sample with a low porosity rate (~ 0.5 %), a variation of ± 0,5 °C on the measured temperature leads to a difference of ± 9,2 % on porosity rate with ethanol, whereas the same measurement using demineralized water would lead to a difference of ± 3,5 %. This trend tends to decrease with higher porosities.

In addition, the differences obtained can be related to the difference in surface tensions between the fluids (Table 3). This difference affects the ability of the fluid to correctly wet the entire surface of the samples. Due to its low surface tension, ethanol is expected to better wet the samples, and thus yield lower porosity rates than those obtained with demineralized water. However, the results do not confirm this assumption. An explanation may be that low surface tensions stabilize occluded bubbles in a fluid, thus stabilizing air bubbles.

The comparison of experimental data provides similar evolution of porosity rate with experimental conditions for the three fluids. It was chosen to perform further optimization with water as the standard deviation obtained with demineralized water remained around 10% of the porosity rate value. Moreover, the choice of demineralized water is also validated by the fact that pure acetone and ethanol are hygroscopic. This property makes their purity deteriorate with time, as they absorb the water from the air.

In a second step, samples were polished to modify their surface roughness (Sa in µm) in order to address the influence of surface finish on the accuracy of density measurements, through possible variations of wetting. Indeed it was supposed that a sample with a high Sa is more likely to entrap air bubbles and to affect results. Three Sa conditions were compared: as SLM-built (~ 12 +/-2 µm for the 7 experimental conditions), mirror polished (~ 0.01 µm) and sand blasted (~ 4 µm). It can be seen that for "as manufactured samples" (high Sa), the porosity rate and the standard deviation are lower than for the "mirror polished" (Figure 10). A possible explanation may be that mirror polishing or sandblasting texturize the surface relatively homogeneously, thus making it hydrophobic according to a possible "Lotus Effect" [START_REF] Zhang | Lotus effect in wetting and self-cleaning[END_REF]. Indeed, lotus leaves are well known to be hydrophobic : water droplets falling onto the leaves will bead of and roll on, but they do not wet the surface. This is due to the surface micro-texture of the leaves. They are covered with micro-papilla (~ 10 µm height), themselves covered with nano-papilla (~100 µm). It provides air pocket formation, thus, water can only interact with the peaks of the roughness surface instead of wetting the entire surface, including peaks and valleys. First, the formation of micro air pocket at the sample surface can distort the results, and the wettability of the samples being greatly reduced. This would lead to an overestimation of the measured volume, and an underestimation of porosity rate. On the other hand, the "as manufactured" surface can absorb the fluid by capillarity and increase the wettability of the surface.

Figure 10 -comparison of the porosity rate of P2 to P7 samples according to their surface finish (experiments in water)

Finally, samples were cut to determine the influence of the analyzed volume. Initially they were around 2.5 cm 3 and they were cut to obtain samples of 1 cm 3 . Results show that the higher the samples volume, the lower the porosity rate as well as the standard deviation (Figure 11). This means that minimizing the specific surface (S/V) is a key-point for stabilizing results.

To conclude, results presented here indicate that the Archimedes method should be preferentially used with demineralized water on "as manufactured" samples of at least 2 cm 3 in volume. Depending on experimental conditions, variations of up to +/-20 % can occur for porosity rate values in the 1-5 % range. Other precautions are also recommended before starting measurements: (1) to clean samples in ultrasound bath to evacuate the powder stuck on the surface, (2) to dry them between each measurement and evacuate visible air bubbles by immersing samples in a beaker containing demineralized water and softly brushing them before measuring in the fluid.

It has also been observed that the larger the samples (at least 2 cm 3 ), the more accurate the measurements and the lower the errors. For this reason, samples of 2.5 cm 3 have been preferentially considered in this study. However, using larger volumes can become problematic for both Archimedes method and helium pycnometry for which the size of the measurement cell is limited.

Figure 11 -porosity rate of P2 to P7 samples according to their analyzed volume

Micrographic method

The micrographic method can be applied with different magnifications (x 50, x 100 and x 200) and the final results can vary a lot according to the number of pictures and the magnification considered.

The first step of the optimization was to determine which magnification is suitable for the porosity rate measurement. Indeed, a too low magnification could occult the small porosities, and a too high magnification could not be representative of the global sample. Microscope technical characteristics are summarized in the Table 4. Two areas of ~9,5 mm 2 , corresponding to one x 50 micrograph, were first analyzed for different samples. Then, the same areas were analyzed with the x 100 and x 200 magnifications (respectively 4 micrographs/area and 16 micrographs/area). It can be seen that the use of magnification increasingly important for the analysis tends to increase standard deviation (Figure 12) and to modify the porosity rate: porosity rates higher than 1 % (P6, P7) will tend to decrease, whereas under 1% they will increase. Those effects are more visible for samples with higher porosity levels, and are confirmed by [START_REF] Spierings | Comparison of density measurement techniques for additive manufactured metallic parts[END_REF]. In addition, the higher the porosity rate, the greater the standard deviations. Indeed, as porosities are not homogeneously distributed in the material, the porosity rate can vary between each micrograph leading to an increase in the standard deviation.

Micrographs obtained with a x100 magnification have pixel size of 0.69 µm which means first that porosities with an area upper to 0.5 µm² can be detected and taken into account (which is subject to a correct contrast between the metal and the porosity when acquiring the micrographs, as well as a good definition of the porosities contours). That is also why, this magnification was selected for porosity analysis.

Magnification

-Main technical characteristics of the optical microscope Figure 12 -porosity rate of 5 samples according to the micrographic magnification (analyzed surface = 19 mm²)

In a second step, the number of pictures required to provide satisfactory results was determined with the x100 magnification. For the previous samples (Figure 13) it appears that for the highest porosity rates (> 1%), at least 20 micrographs are needed to obtain a stabilized value (Figure 13a) whereas Figure 13b shows that the standard deviation is not stabilized before using 45 micrographs. For samples with a porosity rate below 1%, only 20 micrographs are shown to be sufficient to obtain stabilized porosity rates and standard deviations.

Finally, a possible procedure would be as follows: (a) a first micrograph has to be taken to estimate the porosity rate at x100 magnification, (b) if the value is higher than 1%, 45 micrographs have to be considered (analyzed area ~ 107 mm²) and if the value is lower than 1%, 20 micrographs are enough (analyzed area ~ 47 mm²).

For those reasons, the next micrographic analyses were carried out with the x100 magnification and with either 20 or 45 micrographs for each analyzed surface.

Figure 13 -porosity rate (a) and standard deviation (b) of P2 to P7 samples according to the number of micrographs analyzed

Comparison of the optimized measurement methods

Density measurements for Archimedes and helium pycnometry methods, and porosity calculations for the three methods are compared in Figure 14 with error bars corresponding to the standard deviations.

Figure 14 -(a) density measurements and (b) porosity rate estimation for P2 to P7 samples (50 to 250 J/mm 3 )

First of all, it clearly appears that at low VED, the energy injected in the powder is not large enough to perfectly melt it. This results in very porous samples (P2 = 50 J/mm 3 ). An increase of the VED leads to a better densification of the samples (P3 = 75 J/mm 3 , P4 = 100 J/mm 3 ). Above a certain VED threshold (>120 J/mm 3 ), the porosity rate increases in correlation with the formation of a key-hole regime (samples P6 = 200 J/mm 3 and P7= 250 J/mm 3 ). This tendency is well known and several authors [START_REF] Kaufmann | Influence of process parameters on the quality of aluminium alloy en AW 7075 using Selective Laser Melting (SLM)[END_REF][START_REF] Gu | Influences of Energy Density on Porosity and Microstructure of Selective Laser Melted 17-4PH Stainless Steel[END_REF][START_REF] Campanelli | Capabilities and Performances of the Selective Laser Melting Process[END_REF] have already observed it on various materials (such as aluminum alloys, maraging steels, stainless steels) processed using various manufacturing parameters.

The increase in porosity rate observed at high VED, and assumed to be due to the destabilization of the key-hole welding mode is in full agreement with a recent simulation work by Tang [START_REF] Tang | A numerical investigation on the physical mechanisms of single track defects in selective laser melting[END_REF].

Moreover, it can be seen (Figure 14a) that the two methods (Archimedes and Pycnometry) which give a quasi-direct access to the density of each sample give rather similar results with less than 0.3 % difference in porosity rate (Figure 14b). This is in contradiction with [START_REF] Wits | Porosity testing methods for the quality assessment of selective laser melted parts[END_REF] who did not find a good accuracy in pycnometry measurements of samples having a low porosity rate (<0.5%). The reason why lower porosity rates are obtained with helium pycnometry is possibly due to the fact that open pores are more likely to be filled with small helium atoms (0.31 Å) than with larger water molecules (2.75 Å) . Thus fewer porosities will be considered with helium measurement. Another explanation is related to the difference of dynamic viscosities of helium and water, the first one being more than 40 time less viscous (Helium 25°C, 1 bar : 19.68.10-6 Ns/m² ; water 25°C, 1 bar : 891.10-6 Ns/m²). This is assumed to be the main reason why the density values obtained by helium pycnometry are greater than those obtained by the Archimedes method.

Considering these results and the theoretical density of the material (stainless steel 316L : ρtheoretical = 7,99 g.cm -3 ), it becomes possible to calculate the porosity rate of each sample, and for each measurement method (Figure 14b). However each theoretical density should be used with caution, and operators have to keep in mind that it probably does not correspond to the reality. Indeed, it is know that light elements used in alloys processed with SLM or EBM tend to evaporate [START_REF] Mukherjee | Printability of alloys for additive manufacturing[END_REF][START_REF] Klassen | Numerical simulation of multi-component evaporation during selective electron beam melting of TiAl[END_REF], which modify the chemical composition and thus the material density.

According to Delesse's principle, which states that "the ratio of the area occupied by a component relative to the entire profile area is a consistent estimate of the volume fraction of the component in the object" [START_REF]Stereology Terms | Stereology Information Center[END_REF], we should measure similar porosity rates with the Archimedes' method, the gas pycnometry and the micrographic cross section.

However, it appears that the micrographic cross sections method tends to underestimate the porosity rate, even if several cross sections are considered (parallel and perpendicular to the building direction), unlike [START_REF] Wits | Porosity testing methods for the quality assessment of selective laser melted parts[END_REF] who shows similar results between the Archimedes method and the micrographic cross sections method. We can find that [START_REF] Mayhew | Caveat on the use of the Delesse principle of areal analysis forestimating component volume densities[END_REF] explains that the Delesse's principle should be used carefully, and can be applied only if equal reference areas are used. It means that the each micrograph must have the same size, which is our case in this study. This does not explains the underestimation of the porosity rates.

A possible explanation could be due to the porosities morphology, which is mainly random and irregular in additive manufacturing (especially for LOF at low VED, Figure 3a). Depending on the depth at which the section is made, the porosity section is very different and the Delesse's principle is not checked (Figure 15). That is why it can be necessary to repeat this method several times for a same sample (with a light polishing step between each observations), in order to stabilize the result by calculating an average porosity rate value over several sections.

Figure 15 -porosity cross sections according to the depth of the micrographic section

Another explanation may be that the sample surface or near-surface porosity rate, which are usually higher due to contour-hatching transitions, are not considered in the micrographic observation.

It is interesting to notice that in the case of the sample P2 (50 J/mm 3 ), LOF porosities are full of unmelted powder, which is taken into account during the Archimedes' Method or gas pycnometry. This gives the real volume of void for each porosity of the sample but, during the sample preparation for the micrographic cross sections analysis, this unmelted powder is evacuated from porosities and tends to distort the measured void volume.

Figure 16 and Figure 17 show micrographic cross-sections of each sample, before and after being etched with 92:5:3 reagent (92% HCl + 5% H2SO4 + 3% HNO3, recommended in [START_REF] Vander | Metallographic Techniques for Tool Steels[END_REF]) to reveal SLM beads. It can be seen that at low VED (sample P2, 50 J.mm -3 ), porosities are mainly LOF. The increase of the VED progressively leads to a better densification (sample P4). The remaining porosities are very localized melting defects (angular porosities) or entrapped gases (rounded porosities). These entrapped gas porosities can be promoted by the occurrence of a key-hole regime (larger pores), or by the presence of gas or humidity in the powder bed. Then, an excessive VED will melt the powder in key-hole mode and no longer in conduction mode, hence the presence of gas porosities (samples P5 to P7, respectively 125 and 250 J.mm -3 ).

Bead geometries were analyzed on micrographic cross-sections (Figure 17), allowing to measure width to depth ratios (WDR). All the WDR are comprised between 0.48 and 0.8 (Table 6), which indicates that for all the experimental conditions e >> D, and that a full conduction regime was not achieved. For all SLM conditions, bead shapes suggest the occurrence of key-hole formation, even if key-hole porosities are not visible in each sample micrographic cross sections (samples P2 or P3 for example).

Moreover, [START_REF] Tang | Oxides, porosity and fatigue performance of AlSi10Mg parts produced by selective laser melting[END_REF] suggests that lack of fusion porosity can be predicted by the SLM bead overlap versus their dimensions (Eq. 2). In the case where the bead overlap is inferior to 1, incomplete melting is avoided. It means that the overlap of SLM beads is sufficient between each bead of each layer, and between each layers of the sample to avoid LOF. However, for all the conditions considered, the bead overlap is superior to 1 (Table 6), which means that Eq. 2 is not fully reliable to estimate the full consolidation limits. Logically, the dimensional ratio calculated by eq.2 decrease as the densification increase, such as with sample P2 and sample P4 (respectively 1,78 ±0,09 and 1,18 ±0,08) (regardless gas porosities). This means that, even such ratios are superior to 1, they can be considered as an accurate geometrical method for estimating a-priori the degree of consolidation from the dimensions of single melt-pool geometries.

One explanation is that, at high VED, eq.2 is no longer relevant because porosities are not LOF anymore but entrapped gas due to the key-hole mode.

Table 6 -porosity measurements, bead dimensions and bead overlaps for P2, P4, P5, P7 samples

The repeatability of the three methods is related to the standard deviations of the samples compared to their average porosity rate. The Table 7 shows that Helium pycnometry and Archimedes methods exhibit an error ratio equal or lower than 10% for 10 measurements. This shows that several measurements (10 in our case) give quite similar results. However, repeatability is probably not the best criterion for choosing one method over another. We advise instead to choose the method depending on the type of sample (shape, size, destructible or not), the results we want to obtain (type of porosity, location, average porosity rate, trend between samples), the material available and the time allotted.

Sample s referen ces

Conclusion

Based on a detailed comparison of three experimental methods, it can be concluded that the Archimedes' method carried out in demineralized water is a reliable technique for estimating porosity rate in SLM samples.

Pycnometry measurements using helium and independent measurements of masses and volumes can be considered the most accurate technique for measuring porosity. However, because helium pycnometry is very time consuming, this method is ill-adapted as a systematic porosity rate control method. The results obtained with the Archimedes' method are very similar to those obtained by helium pycnometry. Because the Archimedes' method is both rapid and reliable, it is an efficient alternative to helium pycnometry. Another advantage of the Archimedes' method is that it is a nondestructive technique.

To ensure the reliability of the Archimedes' method, some preliminary precautions are necessary: air bubbles must be evacuated with the aid of a brush before weighing the samples in the fluid and sufficiently large samples (2 cm 3 minimum) must be used. However, open porosities and powder grains agglomerated on the surface are known to skew the measurements.

On the other hand, the position and the type of porosities present in the samples can only be determined by micrographic cross-section analysis. Because this method measures a 2D fraction area of a 3D porosity, the technique tends to underestimate the real porosity rate. Moreover, the volume of the pores cannot be accurately measured, especially in the case of irregular LOF pores.

Finally it has been shown that the VED input affects the overall porosity rate. Low input energies favor LOF pores, while excessive energies promote key-hole pores and spatters. Between these two extremes there is a wide range of VED in which it is fairly easy to densify material up to 99%, whereas if the SLM parameters are correctly optimized, densities up to 99,95% [START_REF] Mancisidor | Reduction of the residual porosity in parts manufactured by selective laser melting using skywriting and high focus offset strategies[END_REF] can be achieved.

Acknowledgments

Authors would like to deeply thank the French Aerospace Lab (ONERA), and particularly Marc THOMAS, Odile LAVIGNE and Stefan DRAWIN for allowing them to carry out helium pycnometry measurements.

They would also like to thank BPI France for financial support of the FAIR project and Air Liquide for helpful discussions and technical support.

Figure 5 -

 5 Figure 5 -316L powder, (a) particles morphology and (b) size distribution

Figure 9 -

 9 Figure 9 -comparison of the porosity rate of P2 to P7 samples according to the fluid used

Figure 16 -Figure 17 -

 1617 Figure 16 -micrographic cross-sections of samples P2, P4, P5 and P7 samples (50, 100, 125 and 250 J/mm 3 ) corresponding to respectively 1.8 %, 1.1%, 1.7 % and 5 % porosity rates (Archimedes method)

Table 2 -manufacturing parameters of each samples 2.3. Experimental methods and procedures for density measurements

 2

		P (W)	V (mm/s)	D (mm)	Volume Energy Density (J.mm -3 )
	P2 P3 P4 P5 P6 P7	235	1221 814 611 489 305 244	0,07	50 75 100 125 200 250

Table 3 -physical properties of fluid used in Archimedes method (Δρ = variation of density in the 15-25°C temperature range)

 3

		Density (20°C)	Surface tension (20°C, 1 bar)	Dynamic Viscosity (20°C)	Δρ (15°C -25°C)
	Demineralized Water Pure Ethanol Pure Acetone	0,9982 g.cm -3 0,7892 g.cm -3 0,7845 g.cm -3	72,8.10 -3 N.m -1 22,3.10 -3 N.m -1 23,7.10 -3 N.m -1	0,913.10 -3 Pa s 1,095.10 -3 Pa s 0,316.10 -3 Pa s	0,20 % 1,09 % 1,31 %

Table

Table 7 -Repeatability of the measurement for each method, where % P is the average porosity rate; σ is the standard deviation and ER the error ratio (ER=(σ*100)/%P)

 7

			Pycnometry	Archimedes' Method	Micrographic cross section
		%P	σ	ER	%P	σ	ER	%P	σ	ER
	P2 P7	1.539 3.751	0.168 0.118	10.9% 3.1%	1.835 4.040	0.188 0.172	10.2% 4.3%	1.009 2.412	0.43 0.499	42.6% 20.7%


Shuqing Cui

Afsaneh Marandi

Gaëlle Lebourleux

Mireille Thimon

Maxime Bourdon

Chaoben Chen

Maria Inês Severino

Victoria Steggles

Farid Nouar

Christian Serre
email: christian.serre@ens.fr

Heat properties of a hydrophilic carboxylate-based MOF for water adsorption applications

Keywords: Metal-organic frameworks, specific heat capacity, thermal conductivity, adsorption, thermodynamic efficiency

The development of new porous materials is expanding the boundaries of applications related to gas adsorption, including gas separation, catalysis, drying and energy storage.

The specific heat capacity and thermal conductivity of the adsorbent materials are important parameters in the engineering process. For instance, in the adsorptive heat pump technology, the energy generation and transfer by the adsorbent during the adsorption and desorption process of the adsorbate directly determines the energy efficiency of the working cycle. However, the thermal properties' data for the novel types of adsorbent materials, metal-organic frameworks (MOF), is often lacking in the literature. This work followed a protocol particularly relevant for the measurement of MOFs' thermal properties under powder form. A very promising hybrid material for energy storage, separation and other applications, MIL-160, has been tested as a reference. The specific heat capacity of the material was measured at temperatures ranging from 20 °C to 75 °C with a heat flow type differential scanning calorimeter (DSC). The thermal conductivity was measured with a transient heating source technique within a similar temperature range. By fitting the experimental data to the Clausius-Clapeyron model, the performance of this material in the application of adsorptive heat pump was obtained.

Introduction

The superior adsorption performance of modern porous solid materials incited the development of various technologies including gas storage and separation, dehumidification, cooling, and heating. In an adsorption process, the guest molecules attach to adsorption sites on the surface of the host molecules, creating a relatively stable phase by interactions of chemical bonds between the adsorbate and the adsorbent. The adsorbent can later release the adsorbate when receiving external energy input. The whole process involves a large amount of energy conversion under heat form, while porous solids often have high specific heat capacity and low thermal conductivity due to open pore structure and high pore volume, which often lead to a reduction in the sorption performance.

As a new class of porous solids, metal-organic frameworks have aroused a great interest for its potential in the immense possibilities of fine-tuned adsorptive properties [START_REF] Maurin | The new age of MOFs and of their porous-related solids[END_REF]. Also, water has been considered as the best green sorbate due to its broad applicability, non-toxicity and large enthalpy during sorption. Since the discovery of water-stable MOFs, the The pore-filling step of water in MOF for the adsorption application in practice should be reversible. Water molecules interact with the polar sites in MOF's structure via hydrogen bonds, but not via strong coordination bonds within the frameworks. This pore-filling mechanism is different from a typical chemisorption and can have a smaller adsorption enthalpy close to the water evaporation heat. As a consequence, a strategy of developing novel sorbents is to create ordered large pores to enhance the cyclic adsorption capacity In this work, a simple method and protocol is presented for the measurement of heat transfer properties of MOF bulk materials for adsorption applications. The specific heat capacity and thermal conductivity are key parameters in the design of adsorptive based energy transformation devices. A hydrophilic Al furane dicarboxylic based MOF, MIL-160(Al), which is one of the most promising adsorbents to date in the storage and transformation of low-grade energy is taken as an example [32]. The thermal efficiency of an adsorptive heat pump employing the adsorbent is also derived.

Experiments

1.1 Material preparation MIL-160(Al) was synthesized via an up-scale version of the process reported in a previous study [32]. In short, Al(OH)(CH3COO)2 (0.6 mol, 93.7 g; Aldrich, 90%) and 2,5-furandicarboxylicacid (0.6 mol, 97.3 g) were mixed in distilled water (600 mL) and stirred under reflux condition for 24 h. The mixture was filtered and washed with ethanol at room temperature. The resulting white solid in powder form was dried under 100℃, yielding 111.5g activated MIL-160(Al) (90%).

The Brunauer-Emmett-Teller (BET) surface calculations were carried out from N2 adsorption-desorption isotherms measured at liquid nitrogen temperature (77 K) after dehydration under vacuum at 423 K for 12 h using Micromeritics Tristar 3020. The pore volume was taken by a single point method at relative pressure (p/p0) = 0.99. The high-resolution X-ray powder diffraction-pattern of MIL-160 was recorded in two hours within the 4-60 ° 2θ range, with a step of 0.002° and a λ equal to 1.540598 Å.

Water-sorption isotherms were measured by an intelligent dynamic vapor sorption instrument (DVS Vacuum, SurfaceMesurementSystems Ltd.) connected to a humidity generator. The experiments were carried out in the temperature range of 20-60 °C at the relative vapour pressure precisely (RH=0-95%). The humidity was controlled by using two mass-flow controllers with dry air and pure vapour, respectively. The precise humidified airflow passed through two thermogravimetric balances with the sample in one and blank for another. Prior to the adsorption experiment, the samples were dehydrated at 150°C for 12 h under high vacuum (< 10 -6 torr).

Specific heat capacity

The specific heat capacity is directly linked to the thermal loss in an adsorption process -a test with two empty cells (which will be called "blank"); -a test with the sample in the measurement cell and the reference cell remaining empty.

It is imperative to use the same "measurement" cell for both tests as well as an identical temperature program.

To compare the impact of water sorption, both dry and fully loaded samples were measured.

For the loaded sample, before the test, the powder of MIL-160(Al) was saturated under an air-vapor mixing flow of 30% RH at 20°C for 2 hours to ensure it achieved the uptake equilibrium at this state. The sample was weighed and inserted into a batch cell. The powder was carefully packed into the cell to ensure the homogeneity of the measured sample. The initial mass was 400.85 mg.

Results and discussion

Characterization of MIL-160(Al)

After purification and activation, the BET specific surface area and pore volume of the sample were found to be 1200 m 2 /g and 0.398 cm 3 /g respectively (Fig 3a).The PXRD pattern and thermalgravimetric of the MIL-160(Al) powder (Fig 3b,c) are consistent with previously synthesized with small scale process reported in [32]. Water adsorption isotherms for MIL-160 are step-wise curves with reflection point at around 8% P/P0 and the majority uptake (>90%) is complete at 20% P/P0 (Fig 3d). The position of adsorption stage varies very little under different temperature and can be neglected as we only focused on the full uptake conditions. The maximum uptake at P/P0=0.9 reaches around 0.4 g/g dry mass. There is barely sorption hysteresis at all temperatures so that the adsorption and desorption routines almost coincide with each other which is an advantage to be integrated into an active mechanic system. The isosteric heat ΔHads of water adsorption can be calculated from the adsorption isosteres according to the Clausius-Clapeyron relation, given by [35]:

∆ ( ) = R d(ln P) d (-) (2)
Where ΔHads, R, P, T and w represent the isosteric enthalpy of adsorption, universal gas constant, pressure, temperature, and water uptake. The isosteric enthalpy of adsorption is obtained as a function of water uptake and adsorption isotherms measured across a wide temperature range with a linear interpolation method. The ΔHads drops very quickly to 50 kJ/mol at the water uptake w=0.02 g/g dry mass, maintains this value until 0.3 g/g dry mass and varies a little thereafter. This plateau of the ΔHads indicates reversible adsorption-desorption phenomena. The heat capacity of the sample can be calculated as the following equation:

( ) = A -A m (1)
where Cp (T) is the heat capacity of the sample in J/(g. K) at a temperature T; As and Ab are sample and blank output signals in μV; ms is mass of the sample in mg; is the heating rate in K/s.

The experimental conditions were adopted to measure a representative sample of 400 mg on macroscopic level and minimize the impact of the heating rate. The calculation of Cp We listed the heat capacity of the dry material at a set of temperatures in Table 1 for the The more water the MOF contains, the higher its specific heat capacity. A reduction of 30% on the Cp can be observed when the desorption is complete on the loaded sample. In a typical thermodynamic cycle of the adsorption heat pump, the sorbents with higher water uptake is often heated to desorption temperatures with external energy input and the released heat during temperature decreasing is to be evacuated. The necessary energy cost to power the cycling operation would be higher when using the heat capacity measured at different uptake state than in a calculation based only on the value of dry materials.

Thermal conductivity

The thermal conductivity of the sample can be calculated from the following equation:

= ρ ( 1
)
where e is the thermal effusively in W.s 1/2 /(m 2 .K), k is thermal conductivity in W/(m.K), ρ is the density in kg/m 3 .

The calculated thermal conductivity of one sample was shown in Table 2, which slightly decreased with temperature increasing for each state of water uptake. The average values are similar to conventional sorbents. The case of Loaded sample was saturated at 25°C and 30%RH. The relative humidity in the environment maintained at 30% when increasing the temperature so that water uptake would not have an evident change. The case of Dry sample was for dried adsorbent with less than 5%RH at different temperature. The case of Open system was the saturated sample undergoing the increase of temperature in an open environment so that the RH decreased accordingly. As the saturated MIL-160(Al) can be completely regenerated below 90 °C in either open or closed mechanic systems, results at three typical temperatures were listed to demonstrate the measurement of its thermal conductivity: 25 °C, the hydrophilic MIL-160(Al) is easily saturated; 40°C, the vapour starts to be released in an open system; 70°C, desorption is complete in an open system A drop of thermal conductivity by 15% in average was obtained when vapour is completely desorbed from the saturated sample. The packed density also impacts the thermal conductivity. The measured thermal conductivity of differently packed powder is shown in Table 3. The packed density and thickness was closed to the operational conditions where the effect due to macroscopic void volume was also taken into consideration. The packed pressure of the powder layer was 3.5 kPa and the samples were tested with different level of external compression. A shaped sample under bead form with size of 0.4 to 0.6 mm was shown to represent the realistic condition in the application of adsorption heat pump. The effective thermal conductivity of the beads is close to the loosely compacted powder which is a quite low value.

Since a low conductivity has a negative impact in the dynamic performance of the sorption cycle, different strategies could be followed to improve the thermal efficiency, such as packing the powder with higher bulk density, shaping the powder with variable binders (e.g. silicate), and mixing in highly conductive additives (e.g. graphite, thermal conductivity 1400 w/(m. K), heat capacity 0.7 J/(g. K) in the same temperature range). However, the additives will sacrifice the power density and energy storage density of the MOF in a mechanic system, thus requiring further optimization in different working environment.

The pursuing in very high packed density is not recommended because of the drawback that the mass transfer becomes weaker which lowers the specific power. In practice, it is advised to coat the powder on the highly conductive surface to improve heat transfer. The COP of the adsorption cooling cycle is calculated as the ratio of cold energy produced to the heat consumed during the isosteric heating and isobaric desorption [7].

COP = Q %& Q ' ( Q % (3)
This equation can be expressed as the refrigerant (water) evaporation heat over the sum of the specific heating process (Qist) and the latent heat of desorption process (Qde). Assuming in adsorption and desorption, the adsorbent reaches thermodynamic equilibrium state at given temperature and pressure, the COP of the operational cycles of 5/30/85°C is 0.76. On the contrary, if the values of the heat properties were taken for the dry MOF, the corresponding calculation on the COP would render 0.79, with a positive deviation of 4%.

The COP value makes MIL-160(Al) highly competitive to most conventional and innovative sorbents in the application of water adsorption cooling such as SAPO-34, TAPSO and AIPO-18 [36].

Conclusions

In this work, a simple method that measures the heat properties of bulk porous materials is applied on MIL-160(Al), an hydrophilic MOF highly performant in water vapor adsorption processes. Both the thermal capacity and conductivity of the MOF was measured with high resolution and accuracy in the common working range of an adsorption cooler. The specific heat capacity of MIL-160(Al) demonstrated a slightly incremental tendency with temperature. The heat capacity is undesirably higher than the commonly used zeolites such as SAPO-34, TAPSO, and their thermal conductivity is quite close. However, this difference has little impact on the COP of a thermal driven adsorption process given the fact that the adsorption enthalpy is two orders of magnitude larger.

Since water adsorption was proven to become a more and more important subject in both fundamental research and technology development thanks to the rapid development of innovative sorbents, the method and protocol presented here will serve as a reference technique to characterize the key thermal properties of the adsorbents in various sorption systems.

  adsorption applications based on water-MOFs pairs have promoted cross-border research between fundamental chemistry and thermal engineering [2][3][4]. The unique functions of MOFs in tuning the hydrophilicity and water uptake show prospects in the improvement of energy efficiency in specific working environment [5]. Variable concepts have made progress in the aforementioned applications, especially in cooling [6][7][8], water production[9][10][11][12] and drying[13][14][15].

[

  16][17]. A higher fraction of void volume would result in undesirable heat properties that have a negative impact on the cycling sorption performance.The charging and discharging of thermal energy accompanying the cyclic ad-desorption operations involves heat retention by the sorbents and thus a rapid temperature swing of the MOFs. Because a miniscule movement along the step-wise sorption isotherms of MOFs may engender a great amount of change in water uptake, precise measurement of specific heat capacity and thermal conductivity has a significant impact on the evaluation and prediction of the adsorption performance, especially in a dynamic modeling work. Yet very few values have been reported in the literature and most researchers adopt an average heat capacity of 1 J/(g. K). Huang et al.[18] have reported a thermal conductivity below 0.1 W/ m K of MOF-5 at room temperature after shaping, which is much lower than the single crystal. Purewal et al. [19] have showed that this value can increase by 5 times with 10wt% graphite additives. Ming et al. [20] measured the specific heat capacity of MOF-5 as 0.72 J/g K, similar to alumina and graphite. Erickson KJ et al.[21] found HKUST-1 composite with a thermal conductivity of 0.27 W/ m K. These results remain in the range of low heat transfer performance similar to conventional adsorbents such as zeolite type X, zeolite type CHA, carbon-or silica-based matrix encapsulating phase change materials (PCM), etc.[22][23][24][25][26][27] The differential scanning calorimetry is a dominant technique in the direct measurement of heat properties for its simple operation and wide adaptability to variable working conditions [28]. Frazzica et al. [29] developed a methodology to directly measure the heat transfer properties of AQSOA Z02 in an adsorptive heat pump application with similar techniques. BASF and co-workers [30] carried out the room temperature thermal conductivity test of MOF-5 for gas storage by a DSC and a xenon thermal flash diffusivity instrument. Mu and Walton [31] measured the specific heat capacity of several MOFs by using DSC coupled with a thermal gravimetric analyzer covering 50 to 200 °C to verify their thermal stability.

[

  33]. The DSC used in the experiment is μSC, a Tian-Calvet type microcalorimeter manufactured by Setaram Instrumentation, France. With this instrument, measurements can be realized under isothermal conditions or with a constant heating rate ranging between controlled precisely by a Peltier element based thermostat, that surround the sample on all sides. It is equipped with four calorimetric wells that enable two simultaneous tests for two samples and two references. The measurement cell is made of Hastelloy C276 with an internal volume of 850 μL and is able to measure solid, liquid samples or blends. A bunch of Peltier elements are positioned around the cell to measure the temperature difference between the sample and the environment in 3D. This arrangement allows for measuring thicker samples on larger volume closer to real conditions.

Figure 1 .

 1 Figure 1. μSC experimental platform. Left: Setaram μSC Type Tian-Calvet. Middle: 4 calorimetric wells. Right: measurement cell The determination of the specific heat capacity of MIL-160(Al) using the continuous temperature programming method requires the realization of two different and successive tests:

  The following experimental profile has been employed:-stabilization at 20 °C during 1800s -heating from 20 ° C to 75 °C to 0.2 ° C / min -stabilization at 75 °C during 1800s2.3 Thermal conductivityThermal conductivity is measured with a C-ThermTCi sensor from C-Therm, Canada. The C-Therm TCi employs a modified Transient Plane Source technique. Instead of a common used laser light heating source, a known current is applied to the sensor's spiral heating element, providing a small amount of heat (Fig 2.). A guard ring around the sensor is simultaneously charged to support a one-dimensional heat exchange between the primary sensor coil and the sample. The current applied to the spiral element results in a rise in temperature at the interface between the sensor and sample, which induces a change in the voltage drop of the coil. The thermal diffusivity and conductivity is derived from the temperature increasing curves versus heating time. The temperature increasing thus the voltage rise is steeper for materials with lower thermal conductivity and flatter for higher thermal conductivity.

Figure 2 .

 2 Figure 2. Thermal conductivity experimental platform. The thermal conductivity is linked to the density of the sample. Powders of MIL-160(Al) have been compressed in to bloc under pressure. Again, a humid sample was obtained by saturating the packed powder under an air-vapor mixing flow of 30%RH at a lower temperature for 2 hours to ensure it achieved the loading equilibrium at this state. The whole analysis instrument was placed in a small climate chamber to regulate the RH. A dry sample for comparison was obtained by heating the humid sample under 90°C for 2 hours.

Figure 3 .

 3 Figure 3. Characterization of MIL-160(Al). (a) Nitrogen gas sorption isotherm. (b) Powder X-Ray diffraction pattern (λCu≈1.5406 Å) (c) Thermogravimetric analysis under air atmosphere (heating rate of 3°C/min) (d) Water vapor sorption isotherm at 298K

Figure 4 .

 4 Figure 4. Thermograms superposition of blank and sample

  was carried out from 20 to 75°C that is the operational temperature range of MIL-160(Al) for an adsorption heat pump system. The measured result of the highly loaded sample on each point of this temperature range is shown in Fig 5. The measured specific heat capacity remains almost constant with a slight increase by 3% over the temperature range.

Figure 5 .

 5 Figure 5. Evolution of the Cp of the sample between 20 °C and 75 °C

2. 4

 4 Fig. 5. The adsorbent exchanged water Δw by more than 30 wt% dry mass via a cyclic sorption process. The hydrophilic nature enables a typical evaporation temperature of 5-7°C. The desorption temperature below 90°C allows the use of low-grade heat source. MIL-160(Al) is approved as one of the most promising adsorbents for this application in the literature.

Figure 5 .

 5 Figure 5. Water sorption isosteres of MIL-160(Al). Black dashed frameworks: adsorption

Table 1 .

 1 Comparison of the heat capacity between dry and highly loaded samples,

		measured Cp in J/(g.K)
	Sample	24.8 °C	45.0 °C	70.0 °C
	Highly loaded	1.588	1.605	1.617
	Dry	1.117	1.125	1.160

Table 2 .

 2 Comparison of the thermal conductivity between dry and highly loaded samples,

	Sample 1	25.4 °C	43.6 °C	72.3 °C
		Effusivity (Ws ½ /m².K)	k (W/m. K)	Effusivity (Ws ½ /m².K)	k (W/m. K)	Effusivity (Ws ½ /m².K)	k (W/m. K)
	Loaded	172..173	0.071	160.732	0.069	157.723	0.068
	Dry	131.356	0.061	129.141	0.061	127.240	0.060
	open system	171.189	0.071	160.617	0.068	127.206	0.060

Table 3 .

 3 Impact of the compression force on the thermal conductivity

		Temperature	Packed pressure	Test condition	k (W/m. K)
	Loaded 1	25.4 °C	3.5 kPa	loosely	0.071
	Loaded 2	25.3°C	3.5 kPa	3.5 kPa	0.078
	Loaded 3	25.3°C	3.5 kPa	12.95 kPa	0.108
	Loaded 4	26.1°C	3.5 kPa	25.91 kPa	0.117
	bead0.4-0.6mm	26.5°C	-	loosely	0.065

Acknowledgements


Yongliang Li

Jing Cai

Longjia Yan

Wanzheng Zhang

Li Li

Zhiyun Du

Yanxiong Fang

Changzhi Dong

B Meunier

Huixiong Chen

Pritam Das

Jean-Christophe Remigy

Jean-François Lahitte

Andries D Van Der Meer

Barbara Garmy-Susini

Clémence Coetsier

Sandrine Desclaux

Patrice Bacchin
email: bacchin@chimie.ups-tlse.fr

Phenothiazine-based theranostic compounds for in vivo near-infared fluorescence imaging of β-amyloid plaques and inhibition of Aβ aggregation

Keywords: Poly ( -caprolactone) CHT: Chitosan HUVEC: Human umbilical vein endothelial cells EGM-2: Endothelial growth medium -2 DAPI: 6-Diamidino-2-Phenylindole poly ( -caprolactone), chitosan, double porous, membrane, biocompatibility, cell culture

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

Introduction

Tissue engineering relies on the use of artificial degradable porous material scaffold integrated with biological cells or molecules to regenerate tissues [1]. The scaffold material should offer specific functionalities to accomplish this goal. Several studies show that 3D structures of the support material control the cell growth [2]. The material composition is a key point that controls the biocompatibility, the cell adhesion and optionally the biodegradability. The material engineering must be tailored to the biological strategy. In recent studies, artificial vascular grafts generally have been fabricated from synthetic polymers, such as polyester, e.g. polycaprolactone (PCL) or polylactic acid (PLA) or polylactic-co-glycolic acid (PLGA) or polyurethane [3,4]. This kind of polymer scaffolds can provide sufficient mechanical strength and are considered biocompatible and biodegradable without any toxic by-products. However, they are hydrophobic in nature and lack reactive functional sites for further biofunctional modification [5] which led to the development of innovative hybrid materials by mixing both synthetic and natural polymers [6]. Natural carbohydrate polymers like chitosan (CHT) on the other hand can provide an excellent candidate for biomedical vascular grafts application, mostly in combination with other synthetic polymers [7][8][9][10][11]. CHT is a linear polysaccharide composed of glucosamine and N-acetyl glucosamine units connected through β-1,4-glycosidic bond and produced from the highly abundant natural polymer, chitin. It is biocompatible, bioresorbable, hydrophilic and non-toxic. It has high affinity towards proteins and provides antibacterial, hemostatic, fungistatic, antitumor and anticholesteremic properties [12][13][14][15][16]. It can provide a favorable environment for cell attachment as chemical structure of CHT is similar to glycosaminoglycans (GAGs), which are native components of extracellular matrix (ECM) [17,18]. However, it has low mechanical properties in wet conditions and high hydrophilicity, which can be easily optimized by blending with synthetic polymers.

Blending can also improve the low degradation rate of the synthetic polymers in physiological conditions. It is well accepted that blending these two kind of polymers will be very advantageous, which can significantly reduce all the disadvantages and combine the benefits of the individual polymers providing a superior material with good tissue compatibility and sufficient mechanical strength [19][20][21].

The 3D structure of the material should enable to host the cells but also to distribute the nutrients and to favor the removal of cellular metabolic products.

In the last decades, various scaffolds have been developed more often from an assembly of simple fibers.

The study of PCL/CHT blend with electrospinning method is extensively researched and well adaptable for better cell attachment with good dynamic properties [9,10,12,[19][20][21][22][23][24][25]. However numerous studies report on the difficulties encountered for electrospinning pure chitosan as the structure is mechanically weak, limiting practical processing [26][27][28][29]. Furthermore, it is difficult to manage the multiple functionality requirements with an assembly of fibers. The use of membranes appears as an interesting alternative to tune the porosity and to manage the mass transport properties. The different level of membrane porosity can be adjusted in order to have both macrovoids to host the cells and interconnected micropores network to ensure the transportation of molecules [30]. Solvent mixing with PCL and CHT was more conveniently used compared to melt blending which is quite difficult to perform as CHT decomposes before undergoing melting. Although it is also difficult to make a homogeneous blend in solvent mixing due to the high viscosity of CHT in solvent and also the scarcity of good mutual solvents.

Several efforts were made as Honma et al. [25,31] produced PCL/CHT blend casting by using common solvent as 1,1,1,3,3,3-hexa-fluoro-2-propanol (HFIP) solution. They showed that PCL/CHT can be processed by using HFIP but this solvent is very expensive, carcinogenic and difficult to remove during washing [32]. Although a different approach was reported to find a good mutual solvent [33][34][35][36][37][38]. Among them a suitable approach could be to dissolve CHT in 0.5 M acetic acid and PCL in glacial acetic acid where the authors [35] were able to obtain a mixture of these two solutions at a low concentration of polymer but it was not effective at high concentration [31] as in our case. In another study, a solvent mixture of formic acid/acetone was reported to be used to develop PCL/CHT nanofibers at high concentration of polymers. In this case, it was forming beads-like morphology indicating incomplete dissolution of the polymer [39]. Recently, formic acid/acetic acid mixture [40] with certain ratio has produced a mutual solvent for both polymers with minimal degradation and phase segregation but with faster dissolution. Despite so many combination of solvents, the author [40] have reported that the formic acid/acetic acid mixture produced the bead free and least toxic scaffold and the solvent can be easily removed during washing.

Here we propose a new scaffold based on polymer membrane technologies to meet the needs and the constraints discussed above. The main objectives are to obtain a biocompatible and biodegradable material with open macrovoids for three-dimensional cell culture and interconnected microporosities to transport nutrients, oxygen, between the macrovoids and supernatant. The membranes were fabricated from a PCL/CHT blend with a modified liquid induced phase inversion technique in order to create macrovoids on the surface. The percentage ratio of PCL/CHT (100/0, 90/10, 80/20, 70/30 w/w %) blend was changed to investigate a range of chemical interactions, miscibility and biodegradability. The morphology of the developed materials was observed by SEM and the physico-chemical properties of the blends were characterized by ATR-FTIR mapping, XRD and DSC. In addition, enzymatic degradation study was performed by using lipase (from Pseudomonas cepacia; 7U/ml) at 37 o C in phosphate buffer saline (PBS) at physiological pH. Change in morphological properties and weight loss (%) were monitored at predetermined time intervals of the degradation study. To test the biocompatibility and potentialities of the membranes as a small diameter vascular graft for cardiovascular system disease, cell culture was performed with human umbilical vein endothelial cells (HUVECs) up to 3 days and results were observed in laser scanning confocal microscopy.

Materials and methods

Materials

CHT (MW 190-310 kDa, 75-85% de-acetylation degree, CAS Number 9012-76-4) was purchased from Sigma-Aldrich and PCL (MW 80 kDa, CAPA TM 6800, CAS Number 24980-41-4) was purchased from Perstorp Holding AB, Sweden. Isopore ® Polyester (PET) track-etched membranes (with 10 µm pore diameter), used as macrovoid generator, were purchased from Sterlitech, USA. Acetic acid, formic acid, sodium hydroxide and sodium azide (NaN3) were purchased from Sigma-Aldrich. Lipase from Pseudomonas cepacia (activity: 35U/mg, CAS Number 9001-62-1) were purchased from Sigma-Aldrich. Phosphate buffer saline (PBS) was purchased from Fisher Scientific (CAS Number 7778-77-0). Human umbilical vein endothelial cells (HUVECs) were purchased from Lonza and the corresponding culture medium (EGM-2: basal medium with supplement mix, CC-22011) was obtained from Promocell. Collagen I (rat-tail) were obtained from Santa Cruz. Trypsin-EDTA, Formaldehyde, 6-Diamidino-2-Phenylindole (DAPI), and Alexa Fluor 488 Phalloidin were purchased from Thermo Fisher. Triton X-100, bovine serum albumin (BSA) were purchased from Sigma Aldrich.

Methods

Development of the membrane with a double porosity level

The membranes were developed by modified liquid induced phase inversion method by diffusion between a solvent as formic acid/acetic acid (FA/AA) mixture and non-solvent as NaOH aqueous solution. PCL and CHT with a ratio 100/0, 90/10, 80/20 and 70/30 (w/w%) were dissolved in FA/AA (w/w%) mixture. The polymer concentration in the solution was expressed in wt.% as followed: CHT (wt. %) = 100

(1)

Polymer (wt. %) = 100 !"#$%&
(2)

The polymer solution was casted on a glass plate using a casting knife in order to achieve a thickness around 250 µm at 23 o C. The track-etched membrane was at first immersed in the solvent mixture to fill the pores with solvent mixture, slowly wiped out to remove excess solvent and slowly applied on the casted polymer solution (Fig. 1). [41] to explain the formation of skinned membrane with macrovoids and sponge structure; the nascent skin playing an equivalent role like our track-etched membrane as discussed in Sec. 3.7.

After the membrane formation, when it turned opaque and detached from the glass plate, the tracketched membrane was removed gently. The PCL/CHT membrane was washed several times in ultrapure water and stored in ultrapure water at 4 o C.

The surface where the macrovoids were open towards the non-solvent (i.e. where the track-etched membrane was applied) is denoted as top surface and the other surface, which was facing the glass plate, is denoted as the bottom surface.

Viscosity measurements of the polymer solution

The viscosity of the polymer solution was measured by Rheometer Anton Paar Physica MCR 301, France. After complete dissolution of the solution, a 0.6 ml volume was injected on a cone plate rheometer (diameter 50 mm). The viscosity was measured at a shear rate from 2 to 100 s -1 at 20 o C. All the measurements were performed inside a close chamber in order to avoid the solvent evaporation and dissolution of water from air moisture.

Scanning electron microscopic (SEM) analysis

SEM analysis (Phenom XL, Fondis Biotech, France) were done on both double and single porous membranes to evaluate all the developed blend morphology from the top surfaces and the cross sections.

All the samples were coated with gold and analysis were performed at an accelerating voltage of 10kV.

The surface porosity was also determined from the SEM images by using ImageJ [42] software and reported in Table 1.

Attenuated total reflection (ATR)-Fourier transformed infrared (FTIR) spectroscopic analysis and mapping

FTIR analysis were done by using a Nexus Nicolet (USA) FTIR Microscope system with an ATR diamond crystal at 45 o angle. Prior to the examination, 1cm 2 sample was cut and measurements were done on both surfaces (three times) of each sample. Each point was scanned sixteen times with a resolution of 8 cm -1 and the spectral range was 650 -4000 cm -1 . The ATR correction was applied on all the spectra [43]. FTIR chemical mapping on either side of the membrane also performed using an infrared spectrometer IN10MX Thermoscientific (USA) with an ATR germanium crystal of a 25° angle.

A square sample of 6 mm 2 was studied. Data were analyzed on a 50 µm × 50 µm surface for each point (one point was measured every 50 µm) with a spectral resolution of 8 cm -1 . Each measurement was scanned by sixteen times with the spectral range 650 -4000 cm -1 .

X-ray diffraction (XRD) analysis

The crystalline structure of membrane sample (5 mm × 5 mm) was investigated by XRD analysis using a D4 Endeavor X-ray diffractometer (CuKα1 = 0.154056 nm and CuKα2 = 0.154044 nm; generator 40 eV; 40 mA, Bruker AXS, Karlsruhe, Germany) from 10° to 100° at a scan speed of 21.7 sec /step that is equal to 0.02 o (2-theta).

Differential scanning calorimetric (DSC) measurements

DSC experiments were conducted (DSC TA instrument Q2000, France) in order to evaluate thermal properties of the PCL/CHT blend membranes. The membranes were dried at 37 o C and were cut in a dimension of 3 mm 2 . The sample was put inside an aluminum pan and mechanically covered by an aluminum cap. The pre-weighted aluminum pan was placed inside the DSC machine and equilibrate at 20 o C. The temperature scanning was performed at a constant heating rate of 10 o C min -1 , from 20 to 80 o C without preheating step. The melting point (Tm) of PCL in the blend by varying CHT wt.% (pure PCL melting point is 60 o C) determined.

Enzymatic degradation of the blend

The membranes were dried in vacuum at 37 o C until constant weight was reached and were cut in 6 mm × 6 mm pieces. The initial weight (wi) was taken (in mg up to the fifth decimal point). Then the samples were placed in a 5 ml vials containing 3 ml of PBS 1× solution, 0.6 mg (7U/ml) of lipase (from Pseudomonas cepacia) and 0.05 wt.% NaN3. The entire procedure was done in a sterile condition and vials were sealed and stored in incubator at 37 o C. The enzyme solution was changed every day in order to maintain the same enzymatic activity during the whole process. The same procedure was done without the enzyme as a control. Three consecutive samples were taken out after 6 hours of incubation and every one-day intervals until 10 days. The samples were washed with copious deionized water, dried at 37 o C in vacuum until constant weight. The final weight, ( ) , was taken.

The weight loss, ( *+,, %, was calculated by the following equation:

( *+,, % = 100 -. /-0 -. (3)
Where, ( 1 , is the initial weight and, ( ) , the final weight.

Scanning electron microscopic images of the degraded membranes were taken and the ageing solution was collected to observe the change in pH.

Cell culture and study by laser scanning confocal microscopy

Membranes were cut with diameter of 2.2 cm and washed with sterile phosphate-buffered saline (PBS) three times. The samples were put in 12 well plate and kept in sterile PBS suspension at 4 °C for overnight before the cell seeding. Then the samples were washed again with sterile PBS, 1 ml collagen I (0.1 mg/ml in PBS) was added in the well plate and incubated for 30 minutes at 37 °C. Then the well plate was taken out from the incubator, washed with PBS and incubated for 1 hour with EGM-2 culture medium (Lonza). Meanwhile, human umbilical vein endothelial cells (HUVECs from Lonza) were trypsinized (passage 4) and collected from a confluent T175 flask. The well plate was taken inside a sterile hood and the incubated culture medium was discarded. Then, 3 ml of homogeneous cell suspension (4 × 10 6 cells/ml or 10 6 cells/cm 2 ) was pipetted in each well plate and incubated at 37 °C for 2 hours to ensure complete attachments. The well plate was taken out of the incubator, replaced with fresh culture medium to remove non-attached cells and incubated again.

After 3 days, the well plates were taken in sterile hood and prepared for cell staining. At first the well plates were washed with PBS and the cells were fixed by adding 4% formaldehyde for 15 minutes. Then the wells were washed with PBS and kept in a permeabilization buffer (PB; 9:1 v:v ratio of 11 mg/ml BSA with 1% Triton X-100 in PBS) at room temperature for 15 minutes to block any non-specific protein-binding sites. Phallodin-488 and DAPI (Actin Green 488, NucBlue, Thermo Fisher Scientific)

were added together in the concentration of 1 drop/ml and 1:4000 in PB, respectively, and incubated at room temperature for 1 hour. To prevent photo-bleaching, the well plates were protected from light exposure from this step onwards. Then the well plates were washed thoroughly with PBS and imaged with confocal microscopy (Zeiss LSM 510, Nikon) in 20× and 60× magnification (Fig. 12.). As supplementary information, other biological characterizations have been performed with human mesenchymal stem cells (MSCs) in a successive z-stack confocal analysis on these 3D scaffolds [44] and the hydraulic permeability of HUVECs layers have been measured in a microfluidic organ-on-chip device [44,45].

Results and discussion

Polymer-solvent-non solvent optimization

Chitosan (CHT) and polycaprolactone (PCL) are polymers with very different chemical properties and finding a common solvent to develop a membrane was an important challenge. Moreover, maintaining an optimum viscosity was very important to achieve the double porous membrane structure. The solvent optimization have been partially based on viscosity measurement of the polymer casted solution (Fig.

2) as it was an important parameter that directed the size of the macrovoids during solvent exchange.

During solvent mixing, a visible reduction of the viscosity has been observed by dissolving PCL in the common solvent after 2-3 hours at temperature more than 35 o C, probably due to the hydrolysis of ester bonds of PCL. In order to avoid the reduction of viscosity, different factors were tuned. CHT was dissolved in the solvent mixture at first at 55 o C for 12 h and then PCL was added when the temperature was below 35 o C. In the common solvent, formic acid was found more responsible for the breakage of PCL ester bonds, although higher wt% of formic acid was better for faster and bead free dissolution. For these reasons, the solvent was also optimized for each PCL/CHT polymer blend according the following composition: PCL/CHT 100/0 (15 wt.%) in FA/AA 70/30 (w/w) %, PCL/CHT 90/10 and 80/20 (14 wt.%) in FA/AA 60/40 (w/w) % and PCL/CHT 70/30 (10 wt%) in FA/AA 50/50 (w/w) % (Table 1). In these conditions of composition and temperature, a clear, light yellow and viscous solution was obtained within two hours. After this dissolution step, the polymer solution was kept in stand for 10-20 minutes before starting the membrane casting. Due to high viscosity of CHT in the solvent mixture, PCL/CHT blend beyond 70/30 ratio was not successful as it was difficult to make a homogeneous mixture of polymer solution by mechanical stirrer and to avoid phase segregation between the two polymers.

Viscosity of CHT was remarkably high in the solvent mixture (Fig. 2) that dissolving pure CHT above 4 wt.% was difficult and concentration lower than 4 wt.% are not sufficient to make a double porous membrane certainly due to lack of good entanglement between the polymer chain or a phase inversion leading to polymer particles.

The viscosity of the final polymer solution of pure PCL, CHT and the different blends were measured and reported in Fig. 2. Results showed that the viscosity of pure CHT of only 4 wt.% solution was significantly higher than the viscosity of PCL/CHT 100/0 of 15 wt.% solution in the common solvent.

This was due to several factors. First of all, the molecular weight of CHT (190 kDa -310 kDa) was higher than the molecular weight of PCL (80 kDa). Secondly, CHT has higher affinity towards the solvent due to the presence of stronger secondary interaction between the functional groups of CHT and the common solvent. As a result, CHT polymer chains likely to be deployed in the solvent leading to higher viscosity [46]. On contrary, in acidic solvent, the viscosity of PCL could be decreased to some extent due to a decrease of the polymer chain length via breakdown of ester linkages. All these effects are responsible for the high difference of solution viscosity between these two polymers. Concerning the non-solvent, concentration of NaOH more than 0.5 M in the non-solvent bath was responsible to make the membrane fragile by breaking the ester bonds in PCL during membrane formation. Concentration lower than 0.2 M was not sufficiently concentrated to allow the formation of macrovoids. We also varied the concentration of the NaOH solution depending upon the viscosity of the casted solution in order to get consistent macrovoids height of about 50-70 % of the total membrane thickness. Finally, a 0.3 M NaOH solution was used for PCL/CHT 100/0 (15 wt.%) and 0.5 M NaOH solution was used for the rest of the PCL/CHT blend.

Morphology of the double porous membrane

After the membrane fabrication, the top surface and the cross section morphological characteristics were observed in SEM (Fig. 3.). All the scaffolds, which were produced by using the track-etched membrane, are showing double porosity where the macrovoids are open towards the top surface and connected with the spongy microporous network. From the cross section view, it was observed that the localized arrival of the non-solvent inside the polymer solution were creating the macrovoids which were increasing by increasing CHT wt.%. The macrovoids diameter were around 20±3 -90±5 µm and the diameter of interconnected micropores were around 7±3 µm (except the PCL/CHT 70/30 ratio for which the micropore diameter was 20±5 µm (Table 1)).

Chemical characterization by ATR-FTIR spectra

The representative FTIR spectra of the bottom surface of the membrane are shown in Fig. 4. (A). All the stretching and bending vibrations are found to be well matching with the reported values [31]. In crude CHT, the broad peak at 3364 cm -1 was found due to stretching vibration of intramolecular hydrogen bonding between N-H and O-H. The peak at 2880 cm -1 was due to the asymmetric bending of C-H group. The N-H and C-O-C peaks were observed at 1651 cm -1 and 1070 cm -1 respectively. In PCL, the peaks at 2946 cm -1 and 1726 cm -1 represent the characteristic peaks for C-H and ester carbonyl (C=O) groups respectively. In PCL/CHT blend, by decreasing CHT proportion, the stretching vibration of intramolecular hydrogen bonding between N-H and O-H, shifted towards higher wavenumber region from 3364 cm -1 in PCL/CHT 70/30 to 3437 cm -1 in PCL/CHT 90/10. In addition, the C-H stretching of PCL shifted also towards higher wavenumber region from 2943 cm -1 in PCL/CHT 70/30 to 2946 cm -1 in PCL/CHT 90/10. From all these results, no additional peak was observed indicating presence of no covalent bonding between the two polymers occurred. However, it is clear that the characteristic peak of the blend membrane were constantly shifting by changing the composition likely due to the secondary interaction between the functional groups of two polymers [20,47] The penetration depth of ATR-FTIR absorption, 2 3 , for a sample is given by the following equation

Fig. 1 .

 1 Fig. 1. Double porosity development by modified liquid induced phase inversion process with the following steps: PCL/CHT membrane casting, applying the track-etched membrane before immersing in non-solvent bath and removing track-etched membrane after membrane formation. SEM images of PCL/CHT 100/0 represent double porosity and single porosity on top surface and cross section of the same membrane.

Fig. 2 .

 2 Fig. 2. Viscosity [Pa.s] vs shear rate [1/s] measurement of PCL/CHT 100/0 (15 wt.%), PCL/CHT 90/10 (14 wt.%), PCL/CHT 80/20 (14 wt.%), PCL/CHT 70/30 (10 wt.%) and PCL/CHT 0/100 (4 wt.%) scaffolds respectively in solvent FA/AA mixture.

Fig. 3 .

 3 Fig. 3. SEM micrographs of membranes on the top surface and cross section with double porosity (using track-etched membrane): (A, B) PCL/CHT 100/0, (C, D) PCL/CHT 90/10, (E, F) PCL/CHT 80/20, (G, H) PCL/CHT 70/30. Single porosity (without using track-etched membrane): (I, J) PCL/CHT 100/0, top surface and cross-section, respectively.

  . These interactions indicate no phase separation occurs between CHT and PCL in accordance with Sarasam et al. [34] and She et al. [38] who observed a negative Flory Huggins parameter for these two polymers.

Fig. 4 .

 4 Fig. 4. (A) ATR-FTIR spectra of PCL/CHT scaffold on bottom surface where; PCL/CHT 100/0 in red, PCL/CHT 90/10 in green, PCL/CHT 80/20 in purple, PCL/CHT 70/30 in blue and CHT crude in cyan color respectively. (B, C & D) ATR-FTIR spectra of PCL/CHT 90/10, 80/20 & 70/30 scaffold respectively on either side of same membrane where; top surface in red and bottom surface in blue color respectively.

  and θ are the wavelength and incident angle (30 o ) respectively. = 6> is the ratio of refractive index of the sample to that of prism. The refractive indices of germanium and polymeric materials are 4.0 and ≈1.5, [31] respectively. By putting the wavenumbers corresponding to the characteristic absorption, we obtain a penetration depth around ≈3 µm, which means that the ATR-FTIR spectra could only gather the information from first few micrometer depth of the surface, whereas the thickness of the membrane sample were around 80 µm.The comparison of ATR-FTIR spectra for either side of the same blend membrane is presented in Fig.4 (B, C, D). One can note that the intensities of specific bands of PCL and CHT are almost the same on the both surface of PCL/CHT 90/10 and PCL/CHT 80/20 membrane indicating almost homogeneous blend. Whereas, in the case of PCL/CHT 70/30, the CHT characteristic peak were higher on the bottom surface indicating probable phase segregation of PCL and CHT through the membrane thickness. From this ATR-FTIR study, one can conclude no phase separation occurs due to the interaction between PCL and CHT but a segregation could occur through the membrane thickness from the composition of PCL/CHT 70/30 due to distinguished chemical properties of the polymer mentioned earlier. ATR-FTIR chemical mapping (Fig. 5) of two characteristic bands were observed to highlight the difference of the membrane surface chemistry; C=O (1726 cm -1 ) for PCL and intramolecular hydrogen bonded N-H and O-H (3364 cm -1 ) for CHT [21]. NIR Fluorophores Phenothiazine-based theranostic compounds for in vivo near-infared fluorescence imaging of b-amyloid plaques and inhibition of Ab aggregation YongLiang Li, Jing Cai, Longjia Yan, Wanzheng Zhang, Le Li, Zhiyun Du, Yan XiongFang, ChangZhi Dong, Bernard Meunier, Huixiong Chen

Table 1 .

 1 Summary of the polymer blend membrane properties with distinct concentration in correlation with viscosity and pore diameter, melting point.

			PCL/CHT percentage Ratio
		100/0	90/10	80/20	70/30	0/100
	Total Polymer
	Conc. (w/w%)	15	14	14	10	4
	Solvents
	HCOOH/AcOH (w/w%)	70/30	60/40	60/40	50/50	50/50
	Nonsolvent
	NaOH (M)	0.3	0.5	0.5	0.5	-
	Macrovoid diameter (µm) *	20±3	56±5	67±5	90±5	-
	Micropore diameter (µm) *	7±3	7±3	7±3	20±5	-
	Surface Porosity (%) *	40±5	50±5	53±5	45±5	-
	Viscosity of
	polymer sol.
	(Pa.s) @shear rate 2 sec 1 §	0.153	0.293	0.987	0.338	3.89
	M.P. of PCL in
	the Blend (Tm) o C Ψ	61.59	62.78	63.19	61.70	-
	* Data were obtained by ImageJ software	§ From Fig. 2
	Ψ From Fig. 6.B