Julien Marchalot
email: julien.marchalot@univ-lyon1.fr

Renaud Gelszinnis
email: renaud.gelszinnis@univ-lyon1.fr

Anne-Laure Deman
email: anne-laure.deman-him@univ-lyon1.fr

Magalie Faivre
email: magalie.faivre@univ-lyon1.fr

Jean-François Chateaux
email: jean-francois.chateaux@univ-lyon1.fr

Charlotte Rivière
email: charlotte.riviere@univ-lyon1.fr

Hichem Mertani
email: hichem.mertani@lyon.unicancer.fr

Rosaria Ferrigno

MANIPULATION OF RARE CELLS IN MICROFLUIDIC DEVICES USING MAGNETOPHORESIS AND DIELECTROPHORESIS BASED ON COMPOSITE-PDMS

Keywords: capture, separation, composite-PDMS, dielectrophoresis, magnetophoresis

Enrichment of rare cell populations, such as Circulating Tumor Cells (CTCs) or parasitized Red Blood Cells (RBCs), is a tremendous challenge. Indeed, technologies must be able to reach high both purity and recovery rates while keeping the cells intact for downstream analysis. Two main approaches, affinity-based and label-free methods, have already been demonstrated in microfluidic format. Among them, the use of field gradients, electrical field for dielectrophoresis and magnetic field for immuno-magnetic separation, has gained a large interest. This paper demonstrates that PDMSbased composite materials present many advantages over metallic microstructures for the fabrication of active microfluidic devices. Indeed, we showed that these materials, combining properties of both the matrix and doping particles, allows the easy and fast integration of metallic microstructures using soft-lithography approach while preserving O 2 plasma bonding properties of PDMS substrate and avoiding cumbersome alignment procedure. Here, we focused on two different composites: (i) PDMS doped with carbon nanoparticles (C-PDMS) to obtain conductive polymer and (ii) PDMS doped with iron carbonyl microparticles (i-PDMS) to give this composite, ferromagnetic properties. We demonstrated that 3D conductive or ferromagnetic microstructures were easily obtained. C-PDMS electrodes showed dielectrophoresis capture of CTCs from a flowing model blood sample hence highlighting the interest of the composite material. Similarly, i-PDMS allowed the trapping of magnetically labelled cancer cells flowing at its vicinity, thanks to the generation of high magnetic field gradient.

INTRODUCTION

Cells at very low concentration, typically less than 1000 target cells per milliliter of body fluids, are considered as circulating rare cells or low-abundance cells. A typical example is Circulating Tumor Cells (CTCs) that are at a concentration as low as 1 to 100 CTCs/mL of peripheral blood from a human cancer patient. Enumeration of such rare cells presents medically important applications such as in cancer diagnosis and prognosis, non-invasive prenatal diagnosis and cell-based therapies. Therefore, there is a tremendous challenge [START_REF] Jung | Advances and critical concerns with the microfluidic enrichments of circulating tumor cells[END_REF] in the development of technologies and devices able to manipulate them, more specifically to enrich, capture, separate them from a sample containing a large amount of other cells. Such technologies must demonstrate high purity and recovery rate while keeping the cells intact for downstream analyses. Two main approaches, affinity-based [START_REF] Plouffe | Xx[END_REF][3][4] and label-free [5][START_REF] Lee | Xx[END_REF][7] methods, have already been demonstrated in microfluidic format. For both approaches, the use of field gradient, electrical field for dielectrophoresis (DEP) and magnetic field for immuno-magnetic separations, has gained a large interest [START_REF] Jung | Microfluidic devices for the isolation of circulating rare cells: a focus on affinity-based, dielectrophoresis and hydrophoresis[END_REF]. However, to be applied to real clinical samples and become commercial products, these devices and methodologies still need development. The generation of controlled field gradient in microfluidic format necessitates the integration of heterogeneous materials. Indeed, although most of the microfluidic systems are fabricated in polymer materials, microsystems integrating active functions -requiring the generation of either magnetic or electric field gradients -necessitates the integration of metallic materials in these polymers. Poly-DimethylSiloxane (PDMS) is largely exploited in microfluidic devices due to its biocompatibility, optical properties and ease of microstructuration. However, the combination of PDMS with other materials can be challenging, as ferromagnetic and conductive materials cannot be efficiently sealed to PDMS using simple O 2 plasma treatment. This heterogeneous integration can result in tightness issue and be very cumbersome when precise alignment is required. Moreover, it has been shown that the integration of 3D microstructures can improve active function performances [START_REF] Martinez-Duarte | Microfabrication technologies in dielectrophoresis applications-A review[END_REF][START_REF] Park | 3-D electrode designs for flow-through dielectrophoretic systems[END_REF][START_REF] Jung | Six-stage cascade paramagnetic mode magnetophoretic separation system for human blood samples[END_REF]. However, 3D microstructure fabrication and integration are more challenging than conventional 2D coplanar patterns.

The objective of this proceeding is to demonstrate that the implementation of composite PDMS materials can be a simple and efficient method to circumvent previous challenges. These materials, which are composed of a PDMS matrix doped with nano-and/or microparticles, present new properties compared to the native PDMS. In our case, we focused on two different composites: (i) PDMS doped with carbon nanoparticles (C-PDMS) to obtain conductive polymer [START_REF] Brun | Characterization of C-PDMS electrodes for electrokinetic applications in microfluidic systems[END_REF] and (ii) PDMS doped with iron carbonyl microparticles (i-PDMS) to give this composite, ferromagnetic properties [START_REF] Faivre | Magnetophoretic manipulation in microsystem using i-PDMS microstructures[END_REF]. First, we report on the technological process developed to integrate composite-PDMS microstructures into microfluidic channels and then, demonstrate their DEP and magnetophoretic functionalities.

EXPERIMENTAL SECTION

Preparation of Composite-PDMS Material

Two different dopant particles were used in this work: (i) carbon black nanoparticles (20 to 60 nm in diameter, Vulcan XC72-R, Cabot Inc.) to prepare C-PDMS and (ii) carbonyl iron microparticles (dry powder, 7 µm diameter, 97% Fe basis, Sigma-Aldrich) for i-PDMS. Particles and PDMS mixture (10/1 w/w of monomer and curing agent respectively, Silgard from Samaro) were thoroughly mixed (4-15 min) in a mortar until obtaining an homogeneous paste before reticulation. Based on previous results [START_REF] Brun | Characterization of C-PDMS electrodes for electrokinetic applications in microfluidic systems[END_REF][START_REF] Faivre | Magnetophoretic manipulation in microsystem using i-PDMS microstructures[END_REF], we used optimum particle concentration in order to achieve the highest material characteristics while preserving its capacity to be molded. These concentrations were 25% w/w for C-PDMS to reach a conductivity of 10 S m -1 and 83% w/w for i-PDMS attaining a magnetic relative permittivity µ r of 2.28. These values were comparable to the values obtained in other references [START_REF] Niu | Characterizing and patterning of PDMS-based conducting composites[END_REF][START_REF] Abonnenc | Magnetic track array for efficient bead capture in microchannels[END_REF] but are still lower than bulk materials. Although they were sufficient to give to composite-PDMS new functionalities, it will be interesting in the future to investigate other dopants (particle size, shape and nature) in order to improve their characteristics.

Fabrication of the Microfluidic Devices

Microfluidic devices were prepared by using a soft-lithography approach. In our case (Fig. 1), the process was composed of three successive steps. First, the mold was obtained using photolithography (Fig. 1 (a) and(b)). Then, composite-PDMS paste was plastered on dedicated areas of the master (Fig. 1 (c)). After cleaning eventual excess of composite-PDMS, the composite was baked in an oven (75°C, 60 min). Then, pure PDMS was poured on the top of the whole master and the whole system was baked (75°C, 60 min) a second time in order to cure pure PDMS. Composite-PDMS/PDMS slab was then peeled off from the master and bound by O 2 plasma to a glass slide. As presented in Fig. 2, two different microfluidic configurations were designed in order to demonstrate DEP and magnetophoresis functions using composite material. In the case of DEP configuration (Fig. 2a), two C-PDMS electrodes (50 or 100 µm thick) were embedded in channels having walls of identical thickness (50 or 100 µm). We used two electrode geometries: (i) a geometry where electrodes were face-to-face and (ii) one where electrodes were shifted. In both cases, the channel width was 500 µm and the minimal distance between the electrodes was 200 µm. The shape of the electrodes were right-angle isoscele triangles with a height of 150 µm. At a concentration of 25 wt%, C-PDMS is a viscous, paste-like material, that is not easily patterned in acute angles. In this work, we chose the shape of the triangular electrodes in order to limit problems of reproducibility during fabrication. In the case of i-PDMS, the viscosity being lower, we managed to design i-PDMS microstructures down to 50 µm [START_REF] Faivre | Magnetophoretic manipulation in microsystem using i-PDMS microstructures[END_REF]. However, in magnetophoresis configuration (Fig. 2 (b)), we designed a 45 µm thick and 1000 µm wide PDMS microchannel incorporating in the center of the channel 20 diamond shape i-PDMS microstructures (500 µm wide and 45 µm thick).

Cell Preparation

MDA-MB-231, MCF7, HBL100 are immortalized cell lines of human breast cancer. Cells were grown in Dubelcco's Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-strptomycin (PS). Cells were incubated in a 5% CO 2 and 95% O 2 atmosphere at 37°C. When necessary, cells were collected after upon trypsin incubation, washed and suspended in the appropriate medium.

For DEP experiments, after collect, cells were centrifuged twice in DMEM and then suspended in DEP buffer composed of 8.5% (w/v) sucrose, 0.3% (w/v) glucose and 0.7% (v/v) DMEM in distilled water. Conductivity and pH of this buffer were respectively 100 µS/cm and 7. Cells concentration were typically in the range of 4-8× 10 6 /mL. CTCs experiments were performed using a mixture of MDA-MB-231 and Red Blood Cells (RBCs) as a model. Peripheral blood samples were collected from healthy donor from Etablissement Français du Sang (EFS). RBCs were separated from white blood cells and platelets by centrifugation in Phosphate Saline Buffer solution (PBS) and then diluted with DEP buffer at a concentration of 50× 10 6 /mL. MDA-MB-231 and RBCs were finally mixed at a ratio of 1:10. For magnetophoresis experiments with magnetically labelled cells, we used GFP modified MDA-MB-231. These cells were labeled with a suspension of maghemite nanoparticles provided by C. Ménager (Laboratoire PESCA, UMR7195, Université Paris 6, France) and were treated as described elsewhere [START_REF] Faivre | Magnetophoretic manipulation in microsystem using i-PDMS microstructures[END_REF]. Samples injected in the microsystem were at the concentration of 6× 10 6 /mL. In preliminary experiments, we used microbeads to model cell behaviours. Magnetically labelled cells were modeled by 12 µm in diameter superparamagnetic microparticles (magnetite in a polystyrene copolymerisate) whereas unlabeled cells were modeled using 10 µm in diameter non-magnetic fluorescent microparticles. These particles were suspended at a concentration of 160 /µL in filtered PBS with 3.6% w/w dextran (Mw = 2× 10 6 leuconostoc spp. From Sigma Life Science). Dextran was used to reduce sedimentation of the particles during the time of the experiment.

Experimental Set-Up

Microsystems were placed on an inverted epifluorescence microscope (LEICA DMI4000B) and a camera (LEICA DFC340 FX) was used for data acquisition. Image J® was used to perform image analysis and to retrieve bead and cell trajectories. Before operation, microsystems were passivated with 2% bovine Serum Albumin (BSA) in PBS in order to avoid any non-specific adsorption and then rinsed with PBS. A syringe pump (Harvard Apparatus) was used to inject the solutions. Electrical fields were supplied through a waveform generator (Agilent 33521A) and a High Voltage Amplifier (FLC Electronics Voltage Amplifier A800) connected to the microsystems. In this work, the voltage used for DEP experiments are expressed as pea-to-peak voltage.

For magnetophoresis experiments, the external magnetic field was generated by two permanent magnets (Nd/Fe/Br 25× 10× 5 mm 3 , 1.2 T at the pole, polarization in the longest dimension) whose position was secured in a home-made plastic holder. Relative position of the magnets and microfluidic channel was optimized elsewhere [START_REF] Faivre | Magnetophoretic manipulation in microsystem using i-PDMS microstructures[END_REF] at a value of 10 mm .

RESULTS AND DISCUSSION

DEP Capture Using C-PDMS Electrodes

When subjected to a gradient of electrical field, a dielectric particle, such as a biological cell, experiences a DEP force expressed as:

( ) 2 3 DEP Re 2 E F ∇ = CM m f r πε ( 1 )
where m ε is the permittivity of the medium, r is the particle radius, ( )

+ - = ( 2 )
where subscript term p, respectively m, refers to the particle, respectively to the medium and the term * ( )

p f drag r v v F - = πη 6 ( 3
)
where η is the fluid viscosity, p v the velocity of the particle and f v the fluid velocity.

We demonstrated in previous works the capacity of C-PDMS electrodes embedded in PDMS microchannel to carry out DEP and electrical lysis [START_REF] Brun | Characterization of C-PDMS electrodes for electrokinetic applications in microfluidic systems[END_REF][START_REF] Brun | A New Microfluidic Device for Electric Lysis and Separation of Cells[END_REF] in stagnant mode. However, these results were obtained using parallel plane electrodes where gradient of electrical field where induced by electrode roughness and therefore were not adapted for rare cell capture. Here, we used geometries as presented in Fig. 2(a) in order to quantify cell capture yield (defined as the ratio between the number of captured target cell to the total number of target cells flowing) of MDA-MB-231 cancerous cells. On the application of the electric field (3.75 kV/cm 1 MHz), MDA-MB-231 cells flowing in both geometries were captured at the tips of the C-PDMS electrodes as shown in Fig. 3 (a). First, we evaluated the yield for 50 µm thick electrodes embedded in two microchannel geometries, face-to-face and shifted. As presented in Fig. 3 (b), for both geometries, the yield decreases with flow rate. For, face-to-face, it decreases from 80 to 40 % as the flow rate is increased from 10 to 40 µL/h. Indeed, the increase of the flow rate results in the increase of the drag force for a constant DEP force. We can also notice that in the case of the shifted geometry, the yield remains larger than in the face-to-face one. In this case, the yield is 94% at 10 µL/h and 67% at 40 µL/h. Therefore, the shifted geometry exhibits a larger influence zone (zone where DEP F > drag F ) than the face-to-face geometry. Even if capture yield is an important figure of merit for rare cell capture, the throughput must also be sufficiently high in order to treat a large volume of sample in a minimum of time. We show in Fig. 3 (c) that by using thicker electrodes (100 µm), it is possible to maintain a large yield for higher flow rate. Indeed, this yield ranges from 96% to 79% for flow rates ranging from 10 to 80 µL/h. We can deduce that thanks to 3D C-PDMS electrodes, DEP capture throughput can be increased while keeping a large capture yield. This yield is in the same order of magnitude as previously published works [START_REF] Mcfaul | Technologies for label-free separation of circulating tumor cells: from historical foundations to recent developments[END_REF] where yield ranges from 60 to 96% at flow rates ranging from 1 mL/h to 6 µL/h. The increase of throughput can also be obtained using parallelization. In Fig. 4 (a), we used a bipolar configuration to trap cells in parallel microchannels using a minimum of electrical connections. This preliminary experiment demonstrated that we were able to capture HBL-100 and MCF7 cancerous cells in parallel with MDA-MB-231. In this experiment, as the DEP electrodes were associated in series (bipolar configuration), we used in order to capture cells the maximum voltage available with our instrumentation, i.e. 800 Vpp corresponding to an electric field of 6.7 kV/cm per channel. This value is larger than the value used to perform capture in a single channel. We assume that this bipolar configuration, where three microchannels are in parallel, increases ohmic losses and therefore only part of the electric field was used to perform DEP. In future, it will be interesting to investigate capture yield and throughput of such a microdevice while trying to reduce ohmic losses. We also carried out qPCR on cells lysated on-chip after DEP capture in order to demonstrate that molecular integrity was conserved. We were able to detect MCF7 and MDA-MB-231 specific markers (ER1 receptor and vimentin) in the lysate sample. DEP capture using our approach is therefore adapted for molecular downstream analyses. Finally, preliminary results on the capture of MDA-MB-231 mixed with RBCs suspension for a CTCs concentration ratio of 1:10 are shown in Fig. 4 (b). In this figure, we can clearly observe the capture of cancerous cells at the tip of the C-PDMS electrode while RBCs are flowing along the fluid stream. To be captured, cancerous cells were attracted by the gradient of electrical field (0.75 kV/cm at 140 kHz) arising at the electrode tip and were deviated from

Magnetophoresis Capture Using i-PDMS Microstructures

When placed in a magnetic field gradient ( ( ) B . ∇ , a magnetic microparticle is submitted to a magnetic force that is expressed as follow:

( )B B F ∇ Δ = . 3 4 3 χ µ π o mag r (4)
where r is the microparticle radius,

( f χ ).
Therefore, in a non-magnetic medium (such as water), the microparticle can be attracted or repelled by magnetic field gradient, depending on its magnetic properties. As for DEP, this force competes against hydrodynamic drag force as expressed in equation (3). The optimization of magnetophoresis capture by maximizing mag F over drag F have led to the integration in microfluidic channels of microstructures able to generate high spatially controlled gradient of magnetic field. We first demonstrated that i-PDMS, compared to pure PDMS, was able to generate such gradients using 12 µm superparamagnetic microparticles (

3 10 44 . 8 - × = m χ
) and non-magnetic particles. The beads were flowed at 50 µL/h in a PDMS microchannel containing 500 µm diamond i-PDMS structures. Fig. 5 presents a stack of videomicroscopy images that highlight particle trajectories. In absence of an applied magnetic field (Fig. 5 (a)), both paramagnetic and non-magnetic particles experienced only hydrodynamic force and therefore exhibited the same trajectories that illustrated the fluid velocity field lines. When placed in a magnetic field (Fig. 5 (b), trajectories were different. In the case of paramagnetic beads, we can observe that beads flowing sufficiently closed to i-PDMS microstructures were attracted towards them and were captured. Paramagnetic particles were experiencing a gradient of magnetic field generated by i-PDMS microstructure sufficiently large to outreach drag force. Particles flowing further away from the i-PDMS microstructures -i. e. closer to the channel walls -did not seem affected. Indeed, the gradient generated is local around the microstructures. In comparison, non-magnetic bead trajectories were not affected by the gradient. Then, we investigated the influence of flow rate on the capture yield. This yield was estimated by using the bead deviation defined by

downstream upstream Y Y Y - = Δ
where upstream Y is the y coordinate of the bead 500 µm upstream from the i-PDMS microstructure and downstream Y is the y coordinate of the bead 500 µm downstream from this microstructure (Fig. 6 (a)). Depending on this parameter, we defined three areas in the microchannel: (i) a capture area where all beads flowing were captured by the i-PDMS microstructure, (ii) a deviation area where beads were not captured but the magnetic force was sufficiently strong to deviate the beads resulting in We investigated three different flow rates: 50, 200 and 500 µL/h in 45 µm high and 1 mm wide microchannel. The evolution of these area widths with the flow rate is presented in Fig. 6 (b). As expected, the increase of the flow rate results in the decrease of the capture area (from 70% to 13% ) and the increase of the deviation area (from 20% to 47%). However, globally the influence of the i-PDMS microstructures was decreased as we can observe increase of the area where beads were not affected by the gradient of magnetic field. Finally, we tested the efficiency of our i-PDMS microstructures for the capture of magnetically labelled MDA cancerous cells (Fig. 7). As presented in Fig. 7, we can observe 5 i-PDMS microstructures located along the microfluidic channel. After injection, magnetically labelled cancerous cells were captured around the i-PDMS posts. Future works will have to evaluate the potential separation of cancerous cells flowing in blood. In this case, labelling of CTCs will be performed using antigen/antibody affinity between CTCs and magnetic nanoparticles.

CONCLUSIONS

This paper demonstrates that PDMS-based composite materials present many advantages over metallic microstructures for the fabrication of active microfluidic devices. Indeed, we showed that these materials, combining properties of both the matrix and doping particles, allows the easy and fast integration of metallic microstructures using soft-lithography approach while preserving O 2 plasma bonding properties of PDMS substrate and avoiding cumbersome alignment procedure. We demonstrated that 3D conductive or ferromagnetic microstructures were easily obtained with respectively, C-PDMS and i-PDMS. Depending on the doping agent properties (particle size, doping ratio), we managed to obtain structures of various shapes (triangles, squares and discs) with characteristic dimensions down to 50 µm using protocols based on replica molding adapted from soft-lithography. These microstructures were then integrated in microfluidic PDMS channels in order to evaluate their capacity for rare cell enrichment. C-PDMS was used to carry out dielectrophoresis isolation whereas i-PDMS was demonstrated suitable for magnetophoresis trapping. The principle of the DEP trapping system presented hereby was to create regions of high gradient of electric field and DEP traps at the tip of C-PDMS electrodes designed with triangular shape. We first highlighted the benefit of 3D electrodes embedded in microfluidic channel obtained easily thanks to C-PDMS composite to improve trapping efficiency. Metastatic breast cancer cells (MDA-MB-231) were injected in the different devices at flow rates ranging from 5 to 80 µL/h and the trapping yield was experimentally evaluated. Cell trapping yields of 97% at 20 µL/h and 78% at 80 µL/h were achieved for 100 µm thick C-PDMS electrodes. Preliminary results on the isolation of MDA-MB-231 from RBCs suspension for a CTCs concentration ratio of 1:10 were also obtained. In the case of i-PDMS, we fabricated microsystems integrating 50 µm thick, diamond microstructures. We evaluated the magnetic trapping capacities of this material by injection of a suspension of superparamagnetic particles in the channel and obtained capture yield up to 70% at 50 µL/h with i-PDMS microstructures. This approach was then used to demonstrate trapping of magnetically labeled MDA-MB-231 cells.

Figure 1 :

 1 Figure 1: Schematic representation of the fabrication process developed to integrate composite-PDMS microstructures in a PDMS microfluidic channel. (a) the substrate was coated with a photoresist layer, (b) the master was obtained for replication, (c) the composite-PDMS was plastered and cured, (d) pure PDMS was poured and cured, (e) the PDMS slab was peeled off and inlets and outlets were punched, (f) and (f') the PDMS slab was then bound to a glass slide by O 2 plasma (in the case of C-PDMS, the glass slide was pre-patterned with Au tracks to achieve electrical connections between C-PDMS electrodes and Cu wires soldered to Au tracks).

Figure 2 :

 2 Figure 2: (a) DEP configuration in face-to-face and shifted designs featuring embedded C-PDMS electrodes, a SEM image is provided to show detail of the tip of the C-PDMS electrodes), (b) magnetophoresis configuration with i-PDMS diamond microstructures, a SEM image is provided to show detail of a i-PDMS microstructure.

2 E

 2 ∇ is the gradient of the square norm of the electric field. The CM depends on the frequency and is defined by:

  permittivity, σ the conductivity, ω the angular frequency and 1 -= j . When flowing in microfluidic channel, particles are also subjected to the drag force defined by Stokes' law:

Figure 3 :

 3 Figure 3: (a) Optical image of captured MDA-MB-231 cancerous cells at the tip of C-PDMS electrodes in face-to-face (flow rate of 15 µL/h) and shifted geometries (flow rate of 40 µL/h with 50 µm thick channel), (b) Evolution of capture yield of MDA-MB-231 cells as a function of flow rate for the 50 µm thick face-to-face and shifted configurations, (c) Evolution of capture yield of MDA-MB-231 cells as a function of flow rate for 50 and 100 µm thick shifted configuration. DEP parameters were an applied electric field of 3.75 kV/cm at 1 MHz.

  their streamline path. Electrical field was chosen in order to minimize DEP force on RBCs ( ( ) work will include the quantification of the capture yield in the case of a mixture of cancerous cells (MCF7, HBL-100 and MDA-MB-231 with RBCs).

Figure 4 :

 4 Figure 4: (a) Optical image showing three pairs of C-PDMS electrodes connected in bipolar configuration in three parallel microchannels used for cancerous cell lines capture using DEP (6.7 kV/cm at 1 MHz, 20 µL/h), (b) optical image showing the capture of CTCs (MDA-MB-231) in RBCs flowing sample at 5 µL/h (parameters were 0.75 kV/cm at 140 kHz). Microchannels were 100 µm thick.

  the difference of magnetic susceptibilities between the particle ( p χ ) and the surrounding fluid

Figure 5 :

 5 Figure 5: Z-stack projection of videomicroscopic images representing paramagnetic beads and non-magnetic beads flowing, under a flow rate of 50 µL/h, at the vicinity of an i-PDMS microstructure in absence (a) and in presence (b) of an external magnetic field.

Figure 6 :

 6 Figure 6: (a) Schematic representation explaining the measurement of the parameter

Figure 7 :

 7 Figure 7: Bright field images of magnetically labeled cells captured on five different i-PDMS microstructure (post n°1, n°4, n°8, n°12 and n°18) in a microsystem integrating 20 i-PDMS microstructures

Proceedings of the 4th European Conference on Microfluidics -Microfluidics 2014 -Limerick,December 10-12, 2014 © SHF 2014

Proceedings of the 4 th European Conference on Microfluidics -Microfluidics 2014 -Limerick, December 10-12, 2014 © SHF 2014

ACKNOWLEDGEMENTS

All the experiments presented were performed on NanoLyon facilities. More precisely, Jérôme Degoutte and Nicolas Terrier are thanked for their technical help. This work was supported by CNRS, ANR Oncoscreen, LabEx IMUST and Région Rhône-Alpes. FST (Facultée des Sciences et des Technologies) and Collegium C2I@Lyon are also acknowledged for their contribution to build bio/nano experimental facilities. The authors thanks Institut Néel for i-PDMS magnetic characterization and fruitful discussions. They also thank C. Ménager (Laboratoire PESCA, UMR7195, Université Paris 6, France) for providing the maghemite nanoparticles. R.G. is thankful to DGA and CNRS for a PhD fellowship.


Livier Serna-Mansoux
email: livier.serna@supmeca.fr

Dominique Millet
email: dominique.millet@supmeca.fr

Emilie Chapotot
email: e.chapotot@estia.fr

FOR A SUSTAINABLE DIALOGUE: THE GREEN-USE (GU) LEARNING CYCLES CONCEPT

Product design is now driven to the satisfaction of requirements all along the life cycle of the product, with an increased concern in environmental impact. A new concept, the Green-Use (GU) Learning Cycles, is proposed. It is used to determine the way a continuous, adaptive interaction between user and product can be established to improve environmental performance during use. It is structured by two levels of analysis (macro and micro) and a cyclic nature. These levels are the "Incremental user involvement levels", and the "Environmental Impact in Use". They are modelled around the notion of an evolution in cycles, from the initial state of the system product-user to a final stage which results in optimal use with minimal environmental impact. This work includes experimentation to support the new concept proposed, as well a method to use it.

INTRODUCTION

Product design has lately been turning to the satisfaction of requirements all along the life cycle of the product, with an increased concern in environmental impact. Influenced by this, several proposals for product interaction favouring an environmentally friendly use (environmentally friendly use) have appeared. There is, nevertheless, a need for an approach that will address the changing circumstances associated with product use through time.

According to UNEP, the global materials' use increased eight-fold during the 20th Century. This means that presently, around 60 billion metric tonnes are calculated to be used per year. Since the Second World War, the use of renewable biomass has been replaced by the exploitation of mineral materials, and there's no evidence that this will slow down in the future. With increasing world population (it is calculated there will be 9 billion people in 2050), consumption per-capita of products and resources will only grow, with evident negative impact on the Earth's ecosystem. Sustainable consumption becomes then one of the global priorities [START_REF]UNEP Year Book 2010: New Science and Developments in Our Changing Environment[END_REF].

On the other hand, Mont [START_REF] Mont | Institutionalisation of sustainable consumption patterns based on shared use[END_REF] states that the concern with consumption and product use in environmental terms is a relatively new approach. The consumption was viewed as part of the production phase and in consequence, as being a matter of technological improvements. Yet, although some technological innovations have indeed been made, the increasing scale of product consumption render them insufficient to address the environmental problems the world faces at present. The effort should include the way people consume and use products.

More specifically, consumption can be viewed like a twofold issue: one the one part, the product consumption as a an operation mainly concerned with how many units are bought and eventually disposed of in a given society. On the other hand, the use of the product, whereas more complex to analyse, influences its life-cycle as well as environmental issues such as household energy use levels (e.g., home appliances). Thus, by analysing the ways people use a product, new opportunities to modify the negative impact on the environment can be explored.

In this paper a new concept coined Green-Use (GU) Learning Cycles, is proposed. As it will be seen in the subsequent sections, there has been a surge of research in terms of the relationship between product use and environmental concerns such as pollution and energy expense. The scope of those studies have normally covered the interaction between user and product in a limited range of time and interaction style. In general, three areas of study were detected to present a pertinent opportunity for the Green-Use (GU) Learning Cycles concept to contribute.

The first is related with the timespan of interaction between user and product when the former is either learning or applying the acquired knowledge on how to exploit the functions of the latter in the most environmentally friendly way. The second addresses the approach of current research, which only concerns itself with one interaction, or several non-interdependent interactions. This, whereas easier to observe, is not a useful representation of reality, where several interactions occur at the same time between not only user and product, but context as well. Finally, the third is concerned with the limitation and delimitation of disciplinary approaches to the problem of environmentally friendly use. On one side of the scope, there are propositions driven by technology ignoring the behavioural realities of the product-user interaction. On the other, cognitive approaches that dismiss the possibilities of technology and product architecture and focus on "educating" the user to achieve environmentally friendly use.

These concerns are covered in the section "Interaction and environmentally friendly use of products". Experimentation have been carried out by the authors to support the pertinence of some of these concerns.

Then the GU Learning Cycles concept is presented and explained. In general terms, GU Learning Cycles concept proposes to determine the way a continuous, adaptive interaction between user and product can be established to improve envi-ronmental performance during use. It proposes two levels of analysis (macro and micro) and a cyclic nature. The first criterion is the "Incremental user involvement levels", which reflect the users interaction with the product according to environmental attributes. The second criterion, "Environmental Impact in Use", uses a referential "Theoretical Minimal Environmental Impact Factor" (TMENIF) calculated according to the product's architecture and technical functionality. There is an evolution in cycles, from the initial state of the system product-user to that in which GU Learning Cycles result in optimal use with minimal environmental impact. This work proposes a method for the GU Learning Cycles concept and exemplifies it with a theoretical case.

INTERACTION AND ENVIRONMENTALLY FRIENDLY USE OF PRODUCTS

In this section, three main aspects of product use oriented in terms of environmental concerns are presented. The aim is to understand how the GU Learning Cycles concept can contribute to the inclusion of sustainability into the use phase of a product. Experimentation has been done to complement the literature review.

People forget

Studies show that users tend to react positively to environmental awareness when first approached, but then return to old use habits (which can sometimes be environmentally counter productive). We developed an experiment in which the tendency to rebound to higher levels of consumption after having reacted to an environmental awareness campaign was shown. The experiment was based on the methodology proposed by Lilley in [START_REF] Lilley | Sustainable design education -considering design for behavioural change[END_REF]. It considers 3 information modalities to build a link between user and product (Fig. 1), relating the power to make decisions. This power can either be focused on the human being direct action, or on the product function that "forces" the user to act in a certain way.

For our experiment we decided to consider the possibilities of behaviour influence with an existing product. The power of decision rests on the user's side (the upper part of Lilley's Fig. 1). We developed a mix where three types of "eco feedback" are used in two different chronological combinations: "persuasion by information", "persuasion by positive motivation", and "persuasion by guilt". The case study was the consumption of disposable towel paper from the dispenser in office toilettes. The 2 combinations were applied in two separate campaigns, each through a 3 month period.

The first campaign was developed with a group of 14 persons, 10 women and 4 men, between 25 and 59 years old. The "eco feedbacks" were communicated to the subjects in the following combination : 1) persuasion by information, 2) persua- sion by positive motivation, 3) persuasion by guilt. The second campaign was developed with a different group of people, in a different working space from campaign 1. It was comprised of group of 18 persons, 6 women and 12 men, between 25 and 51 years old. The "eco feedbacks" were communicated in the following order: 1) persuasion by information, 2) persuasion by guilt, 3) persuasion by positive motivation (Fig. 2 and Fig. 3).

Both campaigns include measurements before, during, and after the different eco-feedbacks are communicated, and thus we can see the reaction and behaviour change in the subjects. In order to appreciate the overall impact of the campaigns, we recorded the measurement before, the lowest measurement during the campaigns, and the measurement after the campaigns. Out of the results we can observe that the tendency in most of the subjects is to return to higher consumptions after the campaign has finished (Fig. 4 and Fig. 5). This implies the subjects either forget or loose interest in maintaining the changed behaviour (in this case, lower consumption of disposable towel paper).

Simultaneous interactions does not equal the sum of them

The environmentally-driven design of interactions, with the aim of reducing the energy consumption or extend the product's life for example, has commonly been approached as the inclusion of new interactions that would counteract non eco-friendly uses. Yet, it has been recognised that human behaviours can modify the intended function of a product by "misusing" it, this is, by changing the original intention of the product. This, according to Scott, can range from rejection, misuse or hacking [START_REF] Scott | Designing change by living change[END_REF] that counteracts use efficiency. Wever [START_REF] Wever | User-centred design for sustainable behaviour[END_REF] offers a good review of what has been done in terms of modifying or even proposing new design approaches to consider human behaviour and interaction with the product when addressing environmental concerns. Out of all the approaches, the behaviour-centred approach, developed further in [START_REF] Scott | Designing change by living change[END_REF] is the most promising. It includes in the design problem the practices of the user, and in doing so, questions the existing interactions of products further than to answer to a human material need. Nevertheless, as in almost all of the design approaches being proposed in the sustainable design realm, the prospective part is left to an unbounded and rather unchecked process within the method. The possible deviation of product use due to human behaviour has not been considered explicitly to improve environmentally friendly use. The fact that people evolve and change their use-pattern can still offer insights on how to design products that would take advantage of this human behaviour evolution. Designed functions have always needed a close account of human reactions to them, and so the same should be done when addressing environmental concerns in use. Just as the average user will not really use the different power levels available in a typical vacuum cleaner (the average user will just switch to the highest level), the same user may not understand an environmentally oriented feature and end up not using it properly (or at all).

Aggregation and eco-learning in product use

As Lilley has pertinently proposed, the changes towards environmentally friendly use can go in two different directions: either towards the user's power to change or towards the product's functions that forces use in a certain way (Fig. 1). This, in new product solutions means the appropriate combination of both. In reality, though, external circumstances (external to the problem of environmentally friendly use) such as discipline segmentation and teamwork challenges, have mostly resulted in approaches that push mostly from the behavioural or from the technological part of the product. Sustainable solutions can be, for example, driven from the manufacturing or materials side of the product life cycle. Because it is an important factor to pollution and nature's degradation, the chemical composition of the product's materials was one of the first issues addressed by sustainable design. Several methods have been proposed. Yet, as shown in [START_REF] Stephen Poole | Technological trends, product design and the environment[END_REF], [START_REF] Hauschild | Design for environmentdo we get the focus right?[END_REF], [START_REF] Shih | Intelligent evaluation approach for electronic product recycling via case-based reasoning[END_REF], [START_REF] Kobayashi | A systematic approach to ecoinnovative product design based on life cycle planning[END_REF], [START_REF] Smith | Rule-based recursive selective disassembly sequence planning for green design[END_REF], [START_REF] Westkmper | Life cycle management and assessment: Approaches and visions towards sustainable manufacturing[END_REF], solutions pushed by the technical side of the product development address the manufacturing and/or materials problem, but also result in the product's architecture being modified. As a consequence of that, a modification in the user interactions arises. Nevertheless, since the userproduct interactions don't count for the initial approach, they are usually ignored in the results.

On the other hand, sustainable product research pushed from disciplines more connected to human behaviour and preferences hardly challenge the product's existing architecture in a direct way. They focus on human practices, habit modification and awareness. They have been useful in understanding consumer and user perceptions towards the product functions, and lately, the emergence of a "dematerialization" approach has been growing. Works like [START_REF] Heiskanen | Can services lead to radical eco-efficiency improvements? -a review of the debate and evidence[END_REF], [START_REF] Dobers | Eco-efficiency and de-Scenarios for new industrial logics in recycling industries, automobile and household appliances[END_REF], and [START_REF] Cooper | Inadequate life? evidence of consumer attitudes to product obsolescence[END_REF] explore the paradigm change to a longer life for products and the reduction in mass production. This evidently points towards a modification in environmental concerns from a purely materialistic point of view, which can result in a modification of product architecture. This in turn, will mean a modification in product use and user behaviour towards it. Yet, a thorough study of the implications of technical modifications or aggregations of a product in the use phase has not been considered under these approaches as important as the material or technological study.

THE GREEN-USE (GU) LEARNING CYCLES

In order to respond to the need to address both human and technical issues related with environmentally friendly use, we have developed a concept called Green-Use (GU) Learning Cycles. It focuses the product development process in the nature of the interactions between user and product. These can be related to (Fig. 6):

A) Functional needs: what the user wants the product to do in the first place, how the primary concern of the user is satisfied by the use of the product. This approach is somewhat larger than the purely functional approach classically addressed in product design. Usually, the way the product satisfies a need considers use at most from an ergonomic point of view. Nevertheless, extending the approach from an interaction point of view, the bio-mechanical relationship with the product (how it is gripped, operated, assembled, etc.) is only but a part of the analysis. The product is the materialization of the interaction between user and context to satisfy a need (e.g., how a user interacts with a coffee ingredients in order to satisfy its need for a coffee materializes in a coffee machine). This may seem only pertinent for new products, but the analysis on existing products and its context is useful too. Considering our aim is to implement the Green-Use (GU) Learning Cycles either on existing or on new products, it is important to explain the usefulness in product architectures already in the market. The insights given by a interactive approach to functional needs satisfaction can inform us where in the "use" phase the interaction between user and product can be improved without modifying the existing architecture, where can the product be partially modified (upgraded, as in [START_REF] Pialot | How to explore scenarios of multiple upgrade cycles for sustainable product innovation: the upgrade cycle explorer tool[END_REF]), or where the interaction can be exploited for our specific purpose of enhancing environmentally friendly use.

B) Contextual needs: these extend the relationships between user and product to the specific context where the product is positioned. Considering again the example of the coffee machine, the contextual needs address concerns such as the placement of the product (e.g. public place vs. private household), the number of different users it will have, how many times a day it will operate, where and when will it will be receive maintenance, and the such. In terms of our environmental concerns, this is essential to understand energy consumption and eventually, the repair, update, recycle or discard circumstances.

C) Evolutionary needs: these are poorly exploited if not completely ignored in the present product design approach. Product obsolescence and innovation as it has been traditionally understood consider the replacement of the product as the optimal situation. For this reason, it is only lately, triggered by the need to address global pollution and excess of energy consumption, that product development has turned to consider the possibility of the product being consciously designed to last more than it has up until now. As a result, the evolution of the user needs should be considered, both in terms of the functional and of the contextual needs. The main direction is always towards environmental awareness and best use of the product in terms or environmental impact.

These three types of interactions are the basis for the GU Learning Cycles approach. An analysis of the targeted product under their approach is considered the foundation of the concept. How the concept is constructed and structured, however, lies on a different levels of analysis (macro and micro) under which both the user and the product are observed. These levels are deployed through time, to be able both to understand and to influence the interaction cycles that happen between the product and the user. The levels of analysis (macro and micro), which will be explained in the following section, are:

a) The "Incremental user involvement levels", which reflect the user's progress in terms of interacting with the product according to environmental principles. This is a analysis that takes in account the phase of use in its long term cycle.

b) The "Environmental Impact in Use", uses a referential "Theoretical Minimal Environmental Impact Factor" (TMENIF) calculated according to the products architecture and technical functionality. It analyses the particular use on a particular moment.

In terms of the cyclic approach, it oscillates from descriptive to prescriptive(Fig. 7). This means that in at times the information will be retrieved for the description of the situation as it is. At other moments of the development process, specially once the information for the descriptive phase has been recovered, the decision on what should be done (prescriptive) can be implemented. This oscillation, and the exact form and style the prescriptive phase will take, depend on three factors: 1)The complexity of the product: mainly related with technological concerns, some products will be limited in its prescriptive powers (persuasion by coercion) throughout the evolution of the use interaction product-user. Nevertheless, this can be shifted depending on the company's strategic planning. 2)The nature of the product's universe: there are products that follow a very fast track of functional change, and thus the cyclic approach has to take in account both technological and new uses paradigms shifts, and environmental awareness evolution. 3)The strategic vision of the company: the need to take in account the company's vision and mission as an actor in the market influences the nature of the cycles in that it can consider different types of products (e.g., a base product where the use evolves in terms of the service of the company, a product that evolves itself, a product that replaces parts of itself, a product that is completely replaces at a certain moment).

The GU Learning Cycles concept applies both to new product development and existing products with upgradable processes. In the section where the method is explained this will be further clarified. As an introduction, it is just important to notice that the integration of the GU Learning Cycles Concept in the ongoing improvement of existing products is coupled with the upgradable products vision developed by [START_REF] Tchertchian | Modular grouping exploration to design remanufacturable products[END_REF], [START_REF] Pialot | How to explore scenarios of multiple upgrade cycles for sustainable product innovation: the upgrade cycle explorer tool[END_REF]. This vision considers the rationalization of materials as an environmental long-term perspective. In this context, GU Learning Cycles concept can pertinently contribute by completing the product life cycle's analysis with the use phase.

Incremental user involvement levels

The "Incremental user involvement levels" are proposed in order to understand how the user's interaction with the product changes through time. The specific objective is to focus on the interaction related with environmental impact. Nevertheless, since the product and the user have a holistic interaction, the way the use evolves is not exclusively related to environmental concerns. We need then to have a general picture in order to focus on whatever part of the "use phase" may impact the environment.

Several approaches to understand user interactions with the product exist in the literature. These approaches come either from industrial ergonomics, studies to understand how a user learns to use a product, or how the user interacts with product messages. Some of these examples address the environmental factor, and we can find interesting insights in [START_REF] Schmalz | Simultaneous application of design for sustainable behavior and linked benefit strategies in practice[END_REF], [START_REF] Langdon | Prior experience in the use of domestic product interfaces[END_REF], [START_REF] Krippendorff | The Semantic Turn[END_REF], [START_REF] Norman | The design of future things[END_REF].

Schmalz [START_REF] Schmalz | Simultaneous application of design for sustainable behavior and linked benefit strategies in practice[END_REF] considers the design for environmentally friendly use. In order to achieve it, a certain classification of interactions is proposed. In his research, he divides them into "functionality matching", "eco-feedback", "scripting", and "forced functionality". This is close to Lilley's interpretation of the decision power for change in use patterns [START_REF] Lilley | Sustainable design education -considering design for behavioural change[END_REF]. The notion of evolution through time, though, is not explored.

Langdon [START_REF] Langdon | Prior experience in the use of domestic product interfaces[END_REF] is concerned with product familiarity, and so he addresses the problem of time, even if in a rather limited scope. The proposal revolves around the loop "perceptioncognition-action". The individual develops perceptions of the product, then performs actions based on what he/she understands of this perception. Langdon takes the levels proposed by Rasmussen in 1986 [START_REF] Rasmussen | Information Processing and Human-Machine Interaction[END_REF] to understand user's processing of the actions taken. These can be: 1) "skill-based", where there's a rapid automated response, 2) "rule-based" where some conditional "ifthen" reasoning is present, and 3) "knowledge-based", where the reasoning is connected with symbolic notions extracted from mental models and induction.

The previous model is related in some ways to the three levels proposed by Norman [START_REF] Norman | The design of future things[END_REF]. He considers the first level to be "visceral", where the processing is deterministic, automatic, and subconscious, a result of our biological heritage. The second level is "behavioural". One key concept in this level is expectation. The expectation of the results of actions is somewhat related to the "rule-based" processing of Rasmussen. The third level Norman establishes is the "reflective" one, where self-awareness is located, and from where the analyses of the past and imagined futures are developed. This, again, is close to the "knowledgebased" level of Rasmussen, with its mental models and generalisations.

Neither Norman, nor Langdon or Rasmussen establish a chronological explicit sequence though. The one that evokes something of the like is Krippendorff ( [19] ch 3.6.7.). He establishes three phases of incremental involvement of the user and the product: recognition, exploration, and reliance. Each of these considers different kinds of user involvements, and different solutions in the product architecture to achieve them. Whereas recognition must be embedded in the product architecture in a very direct and explicit way, exploration and reliance are connected more with the interaction happening through time between the user and the product.

Another important insight is related to the factors that intervene in the "learnability" ( [START_REF] Krippendorff | The Semantic Turn[END_REF], ch 3.6.8.) of a product, which can be abstracted to three general principles: 1) diversity, the possibility to use the product in different ways and still make it work, 2) optimisation, giving the user the possibility to find short-cuts, and economizing effort, and 3) play, the possibility to have fun with the product.

In this work, we propose the "Incremental user involvement levels" definition, based on the observation of the user interaction with the product. The evolution proposed to be the reference are the three levels of "recognition", "exploration", and "reliance" the user passes through in learning to use the product. The way to measure the achievement of any of these phases is proposed to be done through the observation of the user when interacting with the product. The notion of automatic action is connected with the "recognition" phase, where as number of actions, dependence between actions and time involved in achieving the use of the product are the criteria related to the other two phases ("exploration" and "reliance"). The "indicator" serves to define the level where the user is according to Fig. 8. The guidelines for each level are shown in Fig. 9.

Environmental Impact in Use

The "Environmental Impact in Use" is connected to the results of the actions taken by the user on the product, and which result in a certain impact on the environment. The different impacts on the environment are classified by: 1) energy consumption: related to products that need an en- ergy source to function, such as electronic or fuel based products (telephones, computers, cars, coffee machines, etc.).

2) waste production: related to the by-products which are the result of the function, such as exhaust gases in cars, processed or discarded excess in machines, packaging associated with the product that's discarded once use begins.

3) material consumption (e.g., by replacement of parts as a result of degradation or misuse).

4) water consumption: for products that use water to work (e.g., showers, washing machines, faucets).

Depending on each of these, the minimal impact in use of the product is calculated. This is called "theoretical minimal environmental impact factor" (TMENIF) mainly because it doesn't consider the variability and uncertainty related with human interaction. It is taken as a reference to approach to, but not as an absolute and compulsory goal. The procedure to calculate the product's impact on the environment is adapted from the work of [START_REF] Millet | How to identify the most promising areas of environemental improvement at the early design stages of the design process?[END_REF], as well as from the product specifications.

THE GU LEARNING CYCLES CONCEPT'S METHOD

The concept of GU Learning Cycles has been developed to be integrated either in the design process of new products, or the improvement process of existing products. Since the main objective is to drive the user towards an environmentally friendly interaction with the product, the concept works within a context of use, may this be already existing or in the making.

The method to apply the GU Learning Cycles concept unfolds as follows ((Fig. 10): 1) Calculate the environmental impact profile of the product.

2) Define the interaction strategy based on usability principles and the cyclic approach that derives from the use of the Incremental user involvement levels, so that the user will be put in the track of the "recognition-exploration-reliance" path.

3) Follow up the user's performance by recording and analysing data on the user-product interaction via the "Incremental user involvement levels" and the "Environmental Impact in Use".

4) Loop to step 2, always adjusting the strategy to improve performance or adapt to user's changes.

When using the GU Learning Cycles Concept in a product development process, the method falls within the loop between "concept search" and "conceptual design". It is once the problem has been understood, that the design team can integrate the need for the product to be environmentally friendly not only in use, but in general (Fig. 11). On the other hand, when applying the GU Learning Cycles Concept to an existing product, a different process approach is taken. Information about product and use, even productuser scenarios, is readily available. It is then approached as an "input-output" process, where the output is the improved product-service system (Fig. 12).

Product's environmental impact profile

In terms of the first phase, the retrieval of the environmental impact profile of the product, we begin by locating the pertinence in the larger life cycle of the product. We consider as a reference for the environmental profile of the product the eight generic phases referred to by [START_REF] Gehin | Integrated design of product lifecycles -the fridge case study[END_REF]: (1) material extraction and 4) product assembly, (5) product distribution, (6) product use, [START_REF] Hauschild | Design for environmentdo we get the focus right?[END_REF] product take-back, (8) component end-of-life. We then choose the sixth phase, product use, and concentrate on the analysis of it in order to understand the way the product may impact the environment when used.

Different methods to assess the impact exist, and in [START_REF] Dreyer | Comparison of three different lcia methods: Edip97, cml2001 and eco-indicator 99[END_REF] there is a pertinent comparison between three of such methods: EDIP97 (Environmental Design of Industrial Products 1997), CML2001 (Life Cycle Assessment -An Operational Guide to the ISO Standards 2001), and Eco-Indicator 99. In the end, since the assessment used for the GU Learning Cycles concept limits itself to the use phase, we decide to follow the direction taken by [START_REF] Tchertchian | Design for remanufacturing: What performances can be expected?[END_REF]. They propose the Eco Indicator 99 due to the fact that it can render a single score. Their work includes the addition of four complementary indicators from the CML for objectivity and support purposes.

What we consider as the environmental profile of the product in the use phase is the performance explained previously in the section "Environmental Impact in Use". The TMENIF of the product is that performed with optimal product conditions and a simulation of use that would mean the minimal impact possible. This will most probably not be achieved during real use, or else not continuously, due both to human variability and product's degradation. Nevertheless, it will serve as a beacon to understand the real use and see if its impact evolves towards the TMENIF (which would be ideal) or away from it.

In order to illustrate what the GU Learning Cycles Concept can do, we consider the coffee machine example. The authors' research group is currently developing a long-term project revolving around the notion of upgradable/renewable products. This project accommodates the concept presented in this work by threading the upgrade/renew cycles of the product from a technical point of view, with the evolution of use we have talked about. In this case, the classifications used to explain the concept are "energy consumption" and "material consumption". The TMENIF for each impact is based on the ideal use, without errors or variability. This, as mentioned, will just serve as a guideline to know if real use is approaching it. In Fig. 13 the graph as it would be used is illustrated. The objective is to bring the "normal" use as close as possible to the TMENIF.

Interaction strategy

In phase two, the interaction strategy answers three questions: 1) What actions from the user conform a environmentally friendly use? 2) How do these actions relate to the learning process of the user "recognition-exploration-reliance"? 3) How will the product and the user interact to achieve environmentally friendly use? 4)How will the follow-up of the environmentally friendly use be done?

The interaction between product and user to answer to the first question should be simulated, whether the product is being designed or exists already. A use sequence must be visualized in order to understand how the product is to be designed or adapted to facilitate and optimal use (from the environmental point of view). Once the evolution path "recognitionexploration-reliance" explained previously is understood, it must be connected with the specific actions of the product analysed in order to understand where each action is taking place (the "recognition" level, or any of the others). The nature of the interaction can then be better specified, whether it will be embedded in the product architecture, with affordances or component semantics [START_REF] Krippendorff | The Semantic Turn[END_REF] or triggered through out the use of the product with feedback strategies.

Continuing with the coffee machine example, in Fig. 14, the upgrade or renewal cycles are planned to take place periodically. Throughout each lapse of time, an example of the reinforcement of an environmentally correct use of the product is made by interacting with the user in different operations. The product can store the historical information of the user in order for the upgrade to be not only technical but also in terms of the use of the product by the person. Along with the upgrade or renewal of the component or the whole product, information about historical use that has been stored can then be retrieved (thus calculating the "environmental impact in use"). Technical upgrades can then be customized to enable the best interaction possible between user and product to maintain or improve a low environmental impact.

User's performance follow-up

The performance of the user in terms of the interactions with the product are registered and analysed periodically in order to validate the strategy chosen before, or else to detect changes. This is why the concept has a cyclic nature. The loop is part of the method, as human behaviour rarely stays the same. The strategy can be adapted to be more persuasive or evolve according to the expertise acquired by the user. Continuing with the coffee machine example, and the strategy drafted in Fig. 14, the follow-up of the user's performance could show that the first target ("Switch on/off properly", be aware of energy consumption) hasn't been accomplished in the time interval theoretically considered in the beginning. The strategy of interaction can change in terms of persuasion style, until the registered data of energy consumption approaches the TMENIF. In Fig. 15 an illustration of the cyclic nature behind the follow-up is shown. The user's performance is terms of the environmental practice targeted is registered and the product adapts in terms of the success achieved. This illustration shows an interaction strategy based on information feedback, but it can be envisioned to include technical functionalities that would be activated in order to facilitate the environmentally friendly use or adapt it to a particular practice.

Discussion

The GU Learning Cycles Concept is an approach to product use that aims at achieving the lowest environmental impact possible in the use phase of a product. It proposes a cyclic, evolutionary interaction between user and product, where the latter adapts the communication needs of the former throughout the use phase of the product. It is the response to three general areas of opportunity in the environmentally driven design of products: the fact the user needs continuous follow-up in order to sustain continued environmentally friendly uses of the product; the problem of a one-time, generally initial interaction (commonly informative) that not always ensures prolonged eco-friendly use of the product; and the possibilities yet open to exploration in the realm of environmentally friendly use in product design. The GU Learning Cycles Concept considers the interaction of product and user from an environmental impact point of view. It proposes a several levels of analysis (macro and micro) as the guide to be able to know if the user is approaching environmentally friendly use or not. The Concept can be used in new product development processes, but one of its advantages is that it can be used to adapt and improve on existing products. The way to do so has been explained and illustrated. The different types of product interactions, whether they are embedded in the product as affordances or other semantic materialisations, or are an augmentation of the product (e.g., sensors) is one of the key areas to explore further. The nature of the evolution depending on the type of product, user needs and specific functionalities is also one aspect that will be refined as the Concept is tested. The contributions of it can help in the development of long-term use products, that an adapt to present context of technology and society.

FIGURE 1 .

 1 FIGURE 1. LILLEY'S STRATEGIES FOR DESIGNING SUS-TAINABLE BEHAVIOUR [3].

FIGURE 2 .

 2 FIGURE 2. ORDER FOR CAMPAIGN 1.

FIGURE 3 .

 3 FIGURE 3. ORDER FOR CAMPAIGN 2.

FIGURE 4 .

 4 FIGURE 4. TENDENCIES IN CONSUMPTION FOR CAMPAIGN NO. 1.

FIGURE 5 .

 5 FIGURE 5. TENDENCIES IN CONSUMPTION FOR CAMPAIGN NO. 2.

FIGURE 6 .FIGURE 7 .

 67 FIGURE 6. APPROACH FOUNDATIONS FOR THE GU LEARN-ING CYCLES CONCEPT

FIGURE 8 .

 8 FIGURE 8. INCREMENTAL USER INVOLVEMENT LEVELS.

FIGURE 9 .

 9 FIGURE 9. INCREMENTAL USER INVOLVEMENT LEVELS' GUIDELINES.

FIGURE 10 .

 10 FIGURE 10. "GU LEARNING CYCLES" APPLICATION METHOD.

FIGURE 11 .

 11 FIGURE 11. "GU LEARNING CYCLES" IN A NEW PRODUCT DESIGN PROCESS.

FIGURE 12 .

 12 FIGURE 12. "GU LEARNING CYCLES" IN AN EXISTING PRODUCT SITUATION.

FIGURE 13 .

 13 FIGURE 13. THEORETICAL MINIMAL IMPACT FACTOR VS. NORMAL USER IMPACT FACTOR.

FIGURE 14 .

 14 FIGURE 14. GU LEARNING CYCLES CONCEPT ILLUSTRA-TION: COFFEE MACHINE.

FIGURE 15 .

 15 FIGURE 15. ILLUSTRATION OF STRATEGY ADAPTATION.


T Honorio

L Brochard

M Vandamme

of the apparent Biot coefficient in stacked clay nanolayers

Keywords: saturated clays, molecular scale, effective stress, confined fluids ICE

Effective stresses and estimations

NOTATION

• b apparent Biot coefficient

INTRODUCTION

The concept of effective stress introduced by Terzaghi (1936) is widely employed in geomechanics. The Terzaghi effective stress σ t is the difference between the total external stress σ and the pressure of water Pw:

σ t = σ -Pw (1)
This concept is generally assumed valid despite the hierarchical character of pore sizes in clay-rich soils and rocks. As sketched in Figure 1, clays have a multiscale microstructure with hierarchical pore size distribution. The basic structural units of clays are thin (∼ nm) mineral layers. The ordering of those sheets, isomorphic substitutions as well as the different types of ions in pore solution lead to the variety of clays found in nature. The mineral layers are locally organized in stacks. The space in-between mineral layers can be filled by water in smectites due to their moderate structural charge [START_REF] Meunier | Clays[END_REF]). The characteristic size of the pores at that scale is on the order of the size of water molecules.

About 90% of the porosity in clays refers to pores smaller than 50 nm (e.g. [START_REF] Cariou | Couplage hydro-mcanique et transfert dans largilite de Meuse/Haute-Marne: approches exprimentale et multi-chelle[END_REF]). The assumptions and state equations of poromechanics are generally based on bulk thermodynamics. However, at the nanoscale fluid-solid molecular interactions become significant formulations not accounting for interface effects may not hold. Fluid molecules in micropores (pores with a diameter < 2 nm) which interact with the atoms of the solid are said confined or adsorbed and exhibit physical behaviors that differ from the bulk. Additionally, since the size of atoms and molecules is not negligible with respect to the associated length scale of the pore, even basic concepts such as pore size become ambiguous at the nanoscale.

The apparent Biot coefficient b is defined as follows:

b = ∂σ ∂Pw V (2)
Whenever the concept of Terzaghi effective stress holds, the apparent Biot coefficient is strictly 1. Research on simple confined fluids [START_REF] Brochard | Poromechanics of microporous media[END_REF] shows that due to interfacial effects b can be larger than 1 or even negative. One can reasonably wonder whether strains at the scale of clay layers are still governed by the Terzaghi effective stress.

In the absence of interfacial effects, Coussy (2010) shows that Terzaghi effective stress principle holds whenever the solid skeleton is poorly compressible and the pores are saturated. At the nanoscale however, due to interfacial effects, even for rigid solid layers and saturated pores, apparent Biot coefficients different from 1 can appear as discussed in the following.

Here, it is reported molecular simulations results of saturated clays layers from which the apparent Biot coefficient is derived as a function of the basal spacing. The clay studied is a montmorillonite with sodium interlayer ions (noted Na-Mmt). The present study is limited to the case of saturated clays, i.e. the water pressure is greater than the saturation vapor pressure of water at a given temperature. For the sake of comparison, results for a Lennard-Jones fluid confined in a slit pore are also provided.

MATERIALS AND METHODS

Molecular simulations of realistic clay systems and of a Lennard-Jones (LJ) fluid confined in-between LJ walls are performed. In both cases, the simulations are performed in grand canonical ensemble for the fluid (i.e. the volume V and the temperature T of the entire system and the chemical potential of the fluid µw are fixed; whereas the pressure P and entropy S of the entire system as well as the number of fluid molecules Nw fluctuate). At a given temperature, note that an imposed µw corresponds to an imposed fluid pressure Pw since at constant temperature the chemical potential of water µw = f (Pw, T ) is a function of the fluid pressure. This thermodynamic ensemble mimics the drained condition encountered in many geotechnical applications. For both systems (Na-Mmt and LJ), the ranges of temperatures and pressures of fluid were chosen so that the bulk fluid is in its liquid state (saturated conditions). Moreover, in all simulations, the solid layers are kept rigid (incompressible). The total pressure P is computed from virial expression as in [START_REF] Allen | Computer Simulation of Liquids[END_REF]. Note that the space and time averages of the virial stresses converges to Cauchy stress tensor [START_REF] Zhou | A new look at the atomic level virial stress: on continuum-molecular system equivalence[END_REF]. The solid layers are interacting via long-range electrostatic forces that are disturbed by electrostatics and depletion effects due electrolyte confinement, these interactions lead to the difference between P and Pw.

Molecular simulations of Na-Mmt are detailed in Honorio et al. (2017). Here, the results at 300 K and 500 K considered in [START_REF] Honorio | Hydration phase diagram of clay layers and particles from molecular simulations[END_REF] 2014). ClayFF force field [START_REF] Cygan | Molecular Models of Hydroxide, Oxyhydroxide, and Clay Phases and the Development of a General Force Field[END_REF] and SPC/E water model [START_REF] Berendsen | The missing term in effective pair potentials[END_REF]) are employed. Simulations are performed with Towhee [START_REF] Martin | MCCCS Towhee: a tool for Monte Carlo molecular simulation[END_REF]. A slit pore is considered and series of simulations are run for different basal spacings d (i.e., center-to-center distance of clay layers). Figure 2 displays snapshots of equilibrium configurations of Na-Mmt in 0W, 1W and 2W states.

Additionally, a 2D LJ system is studied, in which the interactions are described by a 12-6 and 9-3 Lennard-Jones potentials, respectively:

U f f (r) = 4ε LJ σ LJ r f f 12 - σ LJ r f f 6 (3) U f s (r) = ε LJ 2 15 σ LJ r f s 9 - σ LJ r f s 3 (4)
where r f f is the distance between fluid molecule, r f s is the shortest distance between the fluid molecule and the solid wall, ε LJ and σ LJ are the LJ parameters with dimensions of energy and length, respectively. Simulations are run with LAMMPS [START_REF] Plimpton | Fast Parallel Algorithms for Short-Range Molecular Dynamics[END_REF] and further detailes are provided in Brochard et al. (2017).

RESULTS

Figure 3 shows the confining pressure isotherms of Na-Mmt at 300, 400 and 500 K for five different water pressures Pw.

The confining pressure P is the normal pressure acting on solid clay layers (z-direction here) P (d) = -σzz and oscillates as function of the basal spacing d. For each curve, Pw is estimated from the average of the computed P corresponding to d > 20 Å. This definition of Pw is necessary due to the difficulty in identifying the precise µw corresponding to a target pressure Pw. Note that for d > 20 Å, P only fluctuates around an average value.

Confining pressure isotherms have an oscillating aspect due to the structuration of fluids in small pores. Each oscillation n corresponds to a hydration state nW , i.e., the fluid is structured in n layers within the pore. Clays generally exhibit oscillations corresponding to one (1W ), two (2W ) and three (3W ) water layers. 0W refers to the dehydrated state and the "pore water" state is called ∞W. In Figure 3, 0W state corresponds to the first branch decreasing with d, the first oscillation corresponds to 1W and the second oscillation to 2W . Oscillations related to subsequent hydration states could not be directly identified with the accuracy of the molecular simulations. However, since the hydration states are separated by the average diameter of a water molecule, the basal spacings corresponding to 3W and subsequent hydration states can be approximately determined.

As detailed in Brochard et al. (2017), the basal spacings between the defined hydration states are unstable, i.e. they are not observed at the layer scale when the confining pressure is controlled. Only the portions of confining pressure isotherms that decrease with the basal spacing are stable (recall that, in a thermodynamic equilibrium, a state is stable if the pressure does not increases with volume). The system at the scale of a clay particle (or stack of layers) may however assume a deformation corresponding to an average basal spacing d = du, where du is a basal spacing in the unstable domain. This deformation is reached by mixing of stable states within the particle, as detailed in [START_REF] Honorio | Hydration phase diagram of clay layers and particles from molecular simulations[END_REF].

Following [START_REF] Honorio | Hydration phase diagram of clay layers and particles from molecular simulations[END_REF], confining pressure isotherms can be also studied in terms of disjoining pressure Π defined as the difference between the confining pressure P (d) and the water pressure Pw:

Π = P (d) -Pw (5)
Here, the disjoining pressure isotherms obtained at any given Pw, at a given temperature, almost overlap with each other when plotted versus basal spacing. The differences between the Π isotherms are not significant with respect to the amplitude of the oscillations associated to 1W and 2W states. Also, these differences are on the order of the fluctuations associated with the simulations. Therefore, Π seems to depend only on the basal spacing d and on the temperature T , but not on the water pressure Pw.

The results in Figure 3 are used to estimate the apparent Biot coefficient of clay layers at a given temperature as a function of the basal spacing d as shown in Figure 4. Large fluctuations of b are observed, which is expected provided the fluctuations in the confining pressure isotherms. Fluctuations of the apparent Biot coefficient are smaller at high temperatures. The red rectangles depict the stable domains corresponding to a confining pressure in the range Pw ± 50 MPa. Considering these domains only, apparent Biot coefficients approximately remain within the range between 0 and 1.

For basal spacings larger than 15 Å (3W ) at 500 K, the apparent Biot coefficient can be fairly approximated by 1. For 0W , 1W and portions of 2W states, b fluctuates and is on average less than 1. Therefore, deformations of clay layers, due to interfacial effects, are not necessarily governed by the Terzaghi effective stress when the interlayer contains 2 layers of water molecules or less and at lower temperatures.

Confining pressure isotherms and apparent Biot coefficients are also obtained for the confined LJ fluid. In Figure 5 (a), it can be observed that the confining pressure isotherms of confined LJ fluid also exhibit oscillations, but with more clearly defined hydration states thanks to more accurate results. Again, the portions for which the pressure increases with the basal spacing are unstable. For a given reduced basal spacing d * = d/σ LJ , the reduced confining pressure P * = P σ 2 LJ /ε LJ evolves linearly with the reduced bulk pressure of the fluid P * w = Pwσ 2 LJ /ε LJ (Figure 5 (b)). The apparent Biot coefficient (i.e. the slope of these lines) is therefore constant with Pw. In Figure 5 (c) it can be observed that the apparent Biot coefficient is strongly dependent on the basal spacing d and can reach both very high values (b = 15.4 for d * = 1.575 Å) and negative values (b = -0.61 for d * = 2.025 Å). These large variations can be found in both stable and unstable domains. This simple example proves that, due to interfacial effects, the pressure in the fluid is not directly tranferred to the solid, (P -P 0 -bPw) 2 is the uncertainty of the confining pressure (P 0 is the least square estimate of the Y-intercept of P (Pw)). The red rectangles are portions of the stable domains corresponding to a confining pressure in the range Pw ± 50 MPa. Simulations at lower temperature are expected to produce results with more variability since water molecules might not have enough kinetic energy (directly related to the temperature) to escape from some configurations associated with local energy minimum. Since a GCMC simulation is basically insertion/deletion of water molecules, in hydration states with less water, the difference of one single molecule impacts non-negligibly the results which can also translate in more variability.

following the concept of effective stresses. This is true even for an incompressible solid saturated by a liquid.

Compared to the LJ system, clay layers are subjected to the particularities of water behavior (Brochard and Honorio 2017), ion correlations and heterogeneity of clay layers (e.g. granularity and isomorphic substitutions). One may attribute to these aspects the reasons why less strong variations in apparent Biot coefficient are observed in clay layers than in the LJ system. This hypothesis would need further investigations.

Other molecular-scale informed studies [START_REF] Le | A two-scale non-local model of swelling porous media incorporating ion size correlation effects[END_REF]) [START_REF] Mainka | Application of a Multi-Scale form of Terzaghis Effective Stress Principle for Unsaturated Expansive Clays to Simulate Hydro-Mechanical Behavior During Hydration[END_REF]) resort to Density Functional Theory (DFT) and Mean Spherical Approximations (MSA) to compute the disjoining pressure in clays. Contrary to molecular simulations, analyses based on DFT/MSA and Poisson-Boltzmann distribution cannot capture the non-monotonous character of counterions distribution within clay micropores [START_REF] Tinnacher | Ion adsorption and diffusion in smectite: Molecular, pore, and continuum scale views[END_REF]). Here, an explicit electrolyte accounting directly for dipole, ion and clay surface (cross-)interactions (including aspects related to the preferential adsorption sites on layers rough surface [START_REF] Underwood | Ion Adsorption at Clay-Mineral Surfaces: The Hofmeister Series for Hydrated Smectite Minerals[END_REF])) was considered.

CONCLUSION

In this article, it was showed that interfacial effects alter the way the pressure of fluids is transferred to the solid phases in materials with nanometric pores, even if the solid remains poorly compressible. This is clear in simulations of confined simple fluids. In realistic molecular simulation of clays, interfacial effects are also manifest, but apparent Biot coefficients remain in the range 0 to 1 for stable basal spacings larger than 1.5 nm. These results limit the validity of analysis not coping with interfacial effects (such as the original Terzaghi effective stress principle) at the clay layer nanoscale to only some specific conditions. This is not inconsistent with experimental observations at the macroscale, since micropores is just one class of pores in clay-rich materials [START_REF] Cariou | Couplage hydro-mcanique et transfert dans largilite de Meuse/Haute-Marne: approches exprimentale et multi-chelle[END_REF]).

Considering that larger pores present apparent Biot coefficients equal to 1, after upscaling, the effective (macroscopic) Biot coefficient must be close to 1 (provided that, as observed here, the apparent Biot coefficients of micropores remains close to 1).

  • d basal spacing • d * = d/σ LJ reduced basal spacing • N number of values of confining pressure computed at each basal spacing and temperature • Nw number of fluid molecules • P confining pressure • P 0 is the least square estimate of Y-intercept of P (Pw) • Pw pressure of water • P * = P σ 2 /ε LJ reduced confining pressure • P * w = Pwσ 2 /ε LJ reduced bulk pressure of the fluid • r f f distance between fluid molecule • r f s shortest distance between the fluid molecule and the solid wall • S entropy • T temperature • U f f and U f s energy of interaction in 12-6 and 9-3 Lennard-Jones potential, respectively. • V volume Manuscript received. . . Published online at www.geotechniqueletters.com ¡ * Universit é Paris-Est, Laboratoire Navier (UMR 8205), CNRS, ENPC, IFSTTAR, 6 & 8 Avenue Blaise Pascal, 77455 Marne-la-Vall ée, France †Current address: Universit é Paris-Est Cr éteil, Laboratoire Mod élisation et Simulation Multi-Echelle, MSME UMR 8208 CNRS, 94010, Cr éteil cedex, France; tulio.honorio-de-faria@upec.fr

Fig. 1 .

 1 Fig. 1. Multiscale microstructure of clays. Micropores are identified at the layer scale (right), mesopores at the clay particle scale (center), and macropores at the clay matrix scale (left).

  are recalled and new results at 400 K and other imposed water pressures Pw at 300 K and 500 K are also presented. The elemental composition of the montmorillonite studied is: Na + 6 .[Si 62 Al 2 ][Mg 4 Al 28 ]O 160 (OH) 32 .nH 2 O. The isomorphic substitutions are randomly located in the octahedral and tetrahedral sheets. The location of these substitutions is reported to induce only minor effects on thermodynamic results Ngouna et al. (

Fig. 2 .

 2 Fig. 2. Snapshot of the configurations of Na-Mmt at 300K under a water pressure Pw of 49 MPa in 0W, 1W and 2W states, i.e. with 0, 1 and 2 layers of interlayer water, respectively (the corresponding basal spacings are d = 9.55, 12.75 and 15.15 Å, respectively). A projection in the ac plane of the triclinic periodic super-cell is shown. Atoms are colored as follows: Mg, pink; Na, blue; Si, yellow; O, red; H, white; Al, green.

Fig. 3 .Fig. 4 .

 34 Fig. 3. Confining pressure isotherms of Na-Mmt at a 300, b 400 and c 500 K as a function of the basal spacing and water pressures Pw. The dashed lines depict the minimum and maximum values of the imposed water pressures Pw. The stable portions corresponding to 0W , 1W and 2W states are represented by the gray rectangles; the range associated with 3W (light yellow rectangle) is estimated accounting for the average diameter of a water molecule of circa 3.55 Å (i.e. the LJ radius of oxygens in SPC/E model).

  Fig. 5. a Confining pressure isotherms of LJ fluid between 9-3 LF walls in 2D as a functions of the basal spacing for different pressures of fluid reservoir P * . The stable portions are identified by the gray rectangles (only for the curve with P * = 0.13, for the sake of clarity). The red rectangles are portions of the stable domains corresponding to a confining pressure in the range P * < 1. b Confining pressure of LJ fluid as a function of P * for some fixed basal spacings d. c Apparent Biot coefficient as a function of the basal spacing d. The corresponding stable portions are also shown.

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ACKNOWLEDGEMENTS

Funding through the project TEAM2ClayDesicc from the French national Research Agency (Agence Nationale de la Recherche contract ANR-14-CE-05-0023-01) is gratefully acknowledged.