Satoshi Tominaka
email: tominaka.satoshi@nims.go.jp

François-Xavier Coudert

Thang D Dao

Tadaaki Nagao

Anthony K Cheetham

Insulator-To-Proton-Conductor Transition in a Dense Metal-Organic Framework

Metal-organic frameworks (MOFs) are prone to exhibit phase transitions under stimuli such as changes in pressure, temperature or gas-sorption because of their flexible and responsive structures. Herein, we report that a dense MOF, ((CH3)2NH2)2[Li2Zr(C2O4)4], exhibits an abrupt increase of proton conductivity from <10 -9 S cm -1 to 3.9 × 10 -5 S cm -1 at 17°C (activation energy, 0.64 eV) by exposure to humidity. These conductivities were determined using single crystals, and the structures were analyzed by X-ray diffraction and X-ray pair distribution function analysis. The initial anhydrous structure transforms to another dense structure via topotactic hydration (H2O/Zr = 0.5), wherein one fourth of Li ions are irreversibly rearranged and coordinated by water molecules, and this structure further transforms into a third crystalline structure by water uptake (H2O/Zr = 4.0). The abrupt increase of conductivity is reversible and is associated with the latter reversible structure transformation. The H2O molecules coordinated to Li ions, which are formed in the 1st-step transformation, are considered to be the proton source, and the absorbed water molecules, which are formed in the 2ndstep, are considered to be proton carriers.

Phase transitions in solid-state materials lead to non-linear changes in properties that can play key roles in the development of innovative, functional materials. Nanoporous metal-organic frameworks (MOFs), which are composed of metal cations and anionic organic linkers, 1 exhibit an unusual range of phase transitions under relatively mild conditions because of their flexible and responsive structures. For example, both high spin-low spin 2 and open pore-closed pore transitions have been observed as a function of temperature and guest loading. 3 In the case of dense MOFs, 4 a reversible, pressure-induced transition with extensive bond rearrangements has recently been described. 5 Herein, we report that a dense anhydrous MOF, (dma)2[Li2Zr(ox)4], I, (dma = dimethyl ammonium, ox = oxalate) transforms to another dense structure, phase II, via topotactic hydration. Phase II exhibits an abrupt increase of proton conductivity by at least four orders of magnitude on further exposure to humidity, which transforms the structure to another crystalline phase, III. When the humidity is reduced, it is not possible to return to phase I, but only to phase II. In general, humidity-induced phase transitions are rare because changes in humidity are normally insufficient to induce a change in the crystal structure of a dense material. To our knowledge, the only previous examples concern disorder-order transitions in organic materials, 6,7 crystal structure transformations in salts by hydration (e.g., iron sulfate), 8 and structural transformations in microporous MOFs. 9 Figure 1a shows humidity-dependent proton conductivities measured by the single crystal impedance method (Fig. S1). 10,11 The assynthesized crystal, I, is insulating up to 50% RH with a conductivity that is lower than the detection limit of the system (~5 × 10 -9 S cm -1 ). However, increasing the humidity to 67% results in an abrupt transition to a state with a conductivity of 3.9 × 10 -5 S cm -1 at 17°C; this in fact is phase III. With decreasing humidity, the conductivity slightly decreases but retains a high value of 1.6 × 10 -5 S cm -1 down to RH = 33% (corresponding to phase II). The high conductivities are stable overnight and comparable to those of classic solid-state materials (10 -3 to 10 -8 S cm -1 ) [START_REF]Proton conductors: Solids, membranes and gels (materials and devices)[END_REF] as well as MOF-based materials. 10,[START_REF] Hurd | [END_REF][14][15][16][17][18] On further lowering the RH to 25% the material becomes insulating again due to the formation of II, but the high conductivity can be recovered by increasing the humidity to 67% (Fig. S1). These single-crystal measurements using microelectrodes themselves indicate the potential application of this material as a conductivity switching device in response to humidity changes, as reported for electronic conductivity 19,20 and magnetic properties. By measuring the temperature-dependent conductivities in the range of 20-36°C at a constant humidity of RH = 61% (Fig. S2), we obtained the Arrhenius plots (Fig. 1b). The activation energy Ea for the conduction is 0.64 eV and the pre-exponential factor σ0 is 3.8 × 10 8 S cm -1 K. The activation energy is similar to anhydrous inorganic crystals (e.g., KH2PO4, 0.60 eV) 10,[START_REF] Colomban | Proton conductors: Solids, membranes and gels (materials and devices)[END_REF] and a layered MOF hydrate ((NH4)2(adp)[Zn2(ox)3]•3H2O (adp = adipic acid), 0.63 eV) [START_REF] Sadakiyo | [END_REF] , and slightly larger than a layered inorganic hydrate ([HUO2PO4]•4H2O, 0.38 eV). 10,[START_REF] Colomban | Proton conductors: Solids, membranes and gels (materials and devices)[END_REF] This high activation energy (cf. aqueous solution, <0.1 eV; gels and polymer electrolytes, <0.3 eV), 10 as well as the small humidity dependence in the RH in the range 67-33%, suggests that protons do not transport through free water molecules adsorbed on the surface but through the framework and/or micropores. 10 Since the conductivity depends on humidity, the mobile ions are judged to be protons, not other ions such as Li + .

In order to understand the role of humidity, [24][25][26] water vapor adsorption-desorption isotherms (Fig. 1c and Fig. S3) were measured at 25°C. The adsorption isotherm of the 1 st cycle shows two-step adsorption: The 1 st -step (P/P0 = 0.3, number of H2O molecules per (dma)2[Li2Zr(ox)4], n = 0.72) is associated with a structural transformation from I to another crystalline phase, II, as shown in the powder X-ray diffraction (PXRD) patterns of the samples sealed under humidity control (Fig. 1d); The 2 ndstep (P/P0 = 0.58, n = 4.0) is associated with a further transformation to another crystalline phase, III, as shown in Fig. 1d, and accounts for the abrupt increase of proton conductivity. The desorption isotherm shows that this 2 nd -step adsorption is reversible with hysteresis, and the humidity jump from P/P0 = 0.40 to 0.51 can be ascribed to the rapid release of water vapor from the material. On the other hand, the transition from I to II is irreversible (n = 0.62 at P/P0 = 7.2 × 10 -3 ). In the 2 nd -cycle adsorption measurements (where n was re-defined to be 0 at P/P0 < 4.2 × 10 -4 ), the material gradually adsorbed water to P/P0 = 0.2 (n = 0.55), and then shows the same uptake around P/P0 = 0.58 (n = 4.0) when II transforms back to III. The abrupt transformation might be accounted for by a gate effect occurring in II, 27 whereby the most flexible molecules (i.e., dma cations) are considered to open channels for water diffusion towards the center. Alternatively, such abrupt adsorption-desorption isotherms with hysteresis are typical for crystalline hydrates where hydrophilicity is different at different hydration levels. 28 Single crystals of the parent, insulating phase I, were synthesized by solvothermal reaction between lithium nitrate, zirconium butoxide, and oxalic acid in dimethylformamide. The crystals are colourless prisms, adopting the monoclinic I2/a space group [a = 16.1266( 5), b = 16.6648 (6), c = 15.4756(4), β = 91.161(3) at 302 K; Table S1]. I forms a three-dimensional anionic framework composed of tetrahedrally coordinated Li + and dodecahedrally coordinated Zr 4+ cations connected by oxalate anions, C2O4 2-: ox (Figure 2a-c). As is common in anionic MOFs, 29 the negative framework charge (-2/Zr) is neutralized by the presence of an amine, in this case dma cations; (CH3)2NH2 + ions are located between ZrO8 polyhedra, and the square channels are filled with their methyl groups (Fig. 2c S1]. The reaction of I to form II adds a single water molecule to one in four of the lithium cations (Fig. 2f and Fig. S5), increasing its coordination number from 4 to 5. For structure determination of II, we cut a small region from a single crystal of I that had been hydrated, thereby obtaining a single crystalline domain; this is because the transformation of I to II lead to the formation of twin domains. Like I, the structure of II is dense (SAV = 3%, 36 Å 3 for an isolated void in the unit cell, Fig. S6), 30 but the water vapor isotherms indicate that these isolated voids are mostly accessible and can be filled with water molecules due to the flexible framework and/or with the motion of dma molecules. 31 The composition of II calculated from the crystallographic data corresponds to the CHN elemental analyses (found, calcd. in %: C(25.66, 25.81), H(3.19, 3.04), N(5.06, 5.02)), which also confirms that the phase transformation does not change the N/C ratio, so there is no replacement of dma by water. The amount of coordinated water was confirmed by thermogravimetric analysis (Fig. S7), which shows an endothermic loss at around 100°C (obs. 1.5 wt%, calc. 1.6 wt%). The transformation of I to II can be understood by careful comparison of their crystal structures. Both structures have square, one-dimensional channels formed by [Zr(ox)4] 4-anions which are connected by the Li + cations (Fig. 2a and2e). The channels are filled by dma cations and no significant micropores exist, as discussed above. The structure of I adopts an I 0 O 3 network according to the nomenclature of Cheetham et al.; 32 there is no extended inorganic connectivity. However, on hydration, LiB moves laterally and binds the water molecule (Fig. 2b) to form an inorganic chain of edge-sharing LiO5 units (Fig. 2f and2g), and thus, the connectivity of II becomes I 1 O 2 . At the same time, half of the [Zr(ox)4] 4- anions, ZrA and ZrC (Fig. 2b), rotate such that the structure retains the square channels. The arrangements of Zr 4+ cations can be regarded as constant during this transformation, and the unit cell relationships are illustrated in Fig. 2d and2h. The crystallographic relationship between the parent crystal and the hydrated phase is retained, as expected for a topotactic reaction. Topotactic reactions are known to be useful for synthesizing new materials that cannot be accessed by other methods, 33- 36 and this is a new example in a dense MOF. 37 The direct structural transformation via a topotactic route is also supported by PXRD data (Fig. S8), which shows that the Bragg peaks of I decrease with the increase in peaks of II. The lattice parameters of both phases are constant during the hydration (Fig. S9 and Table S2), indicating that this transition is first-order and abrupt rather than continuous. The formation energy from I with water vapor to II is calculated to be in the range of chemisorption (-108 kJ mol -1 ) by density functional theory (DFT) calculations; 38,39 in other words, the transformation is energetically strongly favorable. The irreversible transformation to II is reasonable because the dehydration of II with retention of its framework structure requires only 113 kJ mol -1 , which is only by 5 kJ mol -1 larger than the formation energy of I from II (Table S3 and CIF files).

Because III is formed from twin domains that are present in II and sensitive to humidity, we have been unable to determine its crystal structure. However, since the transformation between II and III is reversible, we can assume that the connectivity is mostly retained. In light of this, we used pair distribution functions (PDFs) in order to analyze the local and middle-range order of III. The PDFs (Fig. 3) were obtained by analyzing the X-ray total scattering patterns of the samples sealed in glass capillaries under humidity control (Fig. S10). Regarding I and II, the PDFs were simulated from their crystal structures (Fig. S11), and the peaks assigned to atomic pairs as shown in Fig. 3a. The peaks in the range of 2-4.5 Å represent the Zr(ox)4 coordination units and are consistent in all three phases. The PDFs of I and II are different in the longer distance regions, reflecting their different crystal structures. On examining the PDF of III, it is clearly very similar to that of II in the range 2-6.5 Å (Fig. 3b), indicating that the structure around the zirconium/oxalate unit is preserved. At longer distances, however, we can see the loss of large peaks (e.g., Zr-Zr pairs at 8.49 Å) which suggests that the long range order is not as good in III. In order to accommodate 4 water molecules per Zr ions in III, the framework must expand without changing the overall connectivity and the water molecules (which are probably extra-framework rather than coordinated) are placed in the expanded channel structure. This interpretation is consistent with our observation that the transformation between II and III is reversible.

Regarding the proton source, the DFT calculations using the structure of II show that the proton transport from the dma cations to the oxygen atoms requires significant energy; for example, transfer to the water molecules needs 220 kJ mol -1 , which rules out proton conduction involving the dma cations. Charge distribution analyses of II (Fig. S12-14) reveals that the coordinating water molecules contribute to the screening of cationic charge of LiB (Fig. 2f) by 28% (Fig. S14), which in turn indicates partial deprotonation of the water molecules, namely, the water molecules coordinated to Li ions are considered to be the proton source. Though the coordinated water molecules hydrogen bond with oxalate molecules (Fig. S15), II is not conductive, meaning that the protons do not transport through oxalate ions (e.g., intramolecular proton transport) 40 as shown in Fig. S16 and need additional water molecules as carriers.

The humidity-induced insulator-to-proton-conductor transition is a rare phenomenon. The layered system, hydrogen uranyl phosphate, and related materials show a gradual insulator-to-proton-conductor transition by hydrate formation. [START_REF] Colomban | Proton conductors: Solids, membranes and gels (materials and devices)[END_REF]24 The gradual feature is probably due to the amorphous structure of the anhydrous phase. MOFs, however, provide new opportunities, 4 though the tendency of many MOFs to be unstable in the presence of moisture may lead us to expect them to be unlikely candidates for such behaviour. However, a layered MOF, (NH4)2(adp)[Zn2(ox)3]•nH2O (n = 0, 2 and 3), shows an abrupt insulator-to-proton conductor transition with water uptake (n = 0 to 2) and a conductor-to-superprotonic conductor transition around 100%RH. 26 Our material is three dimensional and exhibits an abrupt transition at the middle RH range of 58%, probably because of the dense crystalline nature of the insulating phase, II, and its transition to another crystalline structure of the hydrate phase, III. The abrupt change of conductivity is reversible, suggesting potential applications of such materials in sensors in response to humidity changes.

Supporting Information

Experimental details, impedance data, crystal structure data, dynamic vapor sorption, X-ray total scattering data, TGA data, PXRD analysis, single crystal micro-FTIR, quantum chemistry calculations, detailed analysis on the crystal structures. This material is available free of charge via the Internet at http://pubs.acs.org.

21

 21 Figure1ashows humidity-dependent proton conductivities measured by the single crystal impedance method (Fig.S1).10,11 The assynthesized crystal, I, is insulating up to 50% RH with a conductivity that is lower than the detection limit of the system (~5 × 10 -9 S cm -1 ). However, increasing the humidity to 67% results in an abrupt transition to a state with a conductivity of 3.9 × 10 -5 S cm -1 at 17°C; this in fact is phase III. With decreasing humidity, the conductivity slightly decreases but retains a high value of 1.6 × 10 -5 S cm -1 down to RH = 33% (corresponding to phase II). The high conductivities are stable overnight and comparable to those of classic solid-state materials (10 -3 to 10 -8 S cm -1 )[START_REF]Proton conductors: Solids, membranes and gels (materials and devices)[END_REF] as well as MOF-based materials.10,[START_REF] Hurd | [END_REF][14][15][16][17][18] On further lowering the RH to 25% the material becomes insulating again due to the formation of II, but the high conductivity can be recovered by increasing the humidity to 67% (Fig.S1). These single-crystal measurements using microelectrodes themselves indicate the potential application of this material as a conductivity switching device in response to humidity changes, as reported for electronic conductivity19,20 and magnetic properties.21

Figure 1 .

 1 Figure 1. Abrupt increase in proton conductivity with relative humidity. (a) Humidity dependence of proton conductivity data obtained by single crystal impedance measurements at 17°C. The arrows show the direction of humidity change from 0% up to 67%, and then down to 25%. The triangles indicate data below the detection limit (100 GΩ). The data were obtained along the c axis of the parent crystal. (b) Arrhenius plots of the temperature dependence of conductivity at RH = 61% (phase III). (c) Water adsorptiondesorption isotherms at 25°C. The vertical axis shows the number of adsorbed water molecules per (dma)2[Li2Zr(ox)4] unit. (d) Powder diffraction patterns collected under humidity control. The samples were sealed in glass capillaries in dry air (RH = 0%, as-synthesized phase I) and in humidified nitrogen at RH = 53% (phase II), 62% (phase III), 0% after holding at 62% (phase II).

  and S4). The overall composition of I is (dma)2[Li2Zr(ox)4]. The chemical compositions were determined by CHN elemental analysis at the Department of Chemistry, University of Cambridge (found, calcd. in %): C(26.05, 26.23), H(2.89, 2.91), N(4.98, 5.10). There is no porosity in I (solvent accessible volume, SAV = 0%). The structure of phase II was determined by single crystal diffraction and its composition is (dma)2[Li2(H2O)0.5Zr(ox)4]. II crystallizes in the triclinic space group P1 [a = 8.5302(6), b = 8.5902(6), c = 16.1582(12), α = 89.309(6), β = 78.004(6) and γ = 68.812(6) at 299 K; Table

Figure 2 .

 2 Figure 2. Topotactic hydration of phase I (a-d) to form phase II (e-h). (a, e) The square one-dimensional channels are retained during the hydration reaction. The channels are filled with dimethylammonium cations, but they are omitted for clarity (both are dense structures). (b, f) The topotactic conversion can be interpreted by rotation of Zr polyhedra (ZrA and ZrC, black arrows), which is triggered by hydration of LiB and its movement into the gap between LiC and LiD. In phase II, the hydrated Li, LiB, is highlighted in red. LiA has long coordination with OD (2.32 Å) and negligibly weak coordination with OB (2.50 Å). OA and OC are non-coordinating oxygen atoms. (c, g) Side-view of the channels. Dimethylammonium cations lie between two Zr polyhedra along the c axis in I, and along the b axis in II. Hydrogen atoms on methyl groups are omitted for clarity. (d, h) Crystallographic orientation relationships. Unit cells (yellow) and cuboids formed by Zr polyhedral chains (black dotted line).

Figure 3 .

 3 Figure 3. Pair distribution function analysis of phases I, II and III. (a) Comparison of X-ray pair distribution functions of the samples sealed at RH = 0% (I), at 53% (II) and (III). The data were plotted with offsets for clarity. The peaks around 0.9 Å (*) are attributable mainly to termination errors caused by the Fourier transformation (Qmax = 17.1 Å -1 ). (b) Difference of PDFs between II (53%) and III (62%).

Acknowledgements

This work was supported by Advanced Investigator Award from the European Research Council (ERC) and the World Premier International Research Center Initiative on "Materials Nanoarchitectonics (WPI-MANA)" from MEXT, Japan. F.-X. C. acknowledges the access of HPC resources from GENCI-IDRIS (grant i2014087069). We thank Micromeritics Japan for the help in the water vapor isotherm measurements, and Surface Measurement Systems and Nippon Science Core for the help in the dynamic water vapor sorption measurements.


David Tomecek

Martin Hruska

Premysl Fitl

Jan Vlcek

Eva Maresova

Sarka Havlova

Lionel Patrone

Martin Vrnata

Phthalocyanine Photoregeneration for Low Power Consumption Chemiresistors

Keywords: phthalocyanine chemiresistors, nitrogen dioxide detection, photoregeneration, lightstimulated NO2 desorption, photoinduced spectral changes, low power consumption

It is well-known that the applicability of phthalocyanine chemiresistors suffers from long recovery time after NO2 exposure. This circumstance enforces the necessity to operate the sensors at elevated temperatures (150-200 °C), which shortens the sensor lifetime and increases its power consumption (regardless, a typical measurement period is longer than 15 min). In this paper, we propose a new method for fast and effective recovery by UV-vis illumination at a low temperature (55 °C). The method is based on short illumination following short NO2 exposure. To support and optimize the method, we investigated the effects of light in the wavelength and intensity ranges of 375-850 nm and 0.2-0.8 mW/mm2, respectively, on the rate of NO2 desorption from the phthalocyanine sensitive layer during the recovery period. This investigation was carried out for a set of phthalocyanine materials (ZnPc, CuPc, H2Pc, PbPc, and FePc) operating at slightly elevated temperatures (55-100 °C) and was further supported by the analysis of UV-vis and FTIR spectral changes. We found out that the light with the wavelength shorter than 550 nm significantly accelerates the NO2 desorption from ZnPc, CuPc, and FePc, and allows bringing the measurement period under 2 min and decreasing the sensor power consumption by 75%. Possible mechanisms of the light-stimulated desorption are discussed.

Downloaded via AIX-MARSEILLE UNIV on January 2, 2019 at 22:27:20 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

familiar phthalocyanine polymorphs are α, β, χ, and τ. The first two, the α and β forms, are common in phthalocyanine thin films. [START_REF] Kadish | The Porphyrin Handbook: Phthalocyanines: properties and materials[END_REF][START_REF] Novotný | The growth of zinc phthalocyanine thin films by pulsed laser deposition[END_REF] In particular, NO2 detection by various Pc morphologies was reported in ref [START_REF] Pizzini | Influence of the structure and morphology on the sensitivity to nitrogen oxides of phthalocyanine thin-film resistivity sensors[END_REF]. However, the strong interaction of Pcs with NO2 (bonding energy ≈ 0.4 eV) results in long recovery times, which imposes serious limits on the real applicability of the sensors.17,23 While the effects of short-time and low-concentration exposures can usually be reversed by temperature elevation (150-200 °C) in a stream of pure air,24 longer exposures to higher concentrations even lead to irreversible changes in sensor properties. These changes were ascribed to the gradual transformation of the original Pc+NO2 -complex to other species with an even stronger bonding.17 The stronger bonding "freezes" the thermal recovery mechanism as the hypothetical recovery temperature rises above the phthalocyanine degradation temperature. To mitigate the risk of sensor damage, the exposure times and doses were shortened and decreased by many researchers. [START_REF] Brunet | An optimized gas sensor microsystem for accurate and real-time measurement of nitrogen dioxide at ppb level[END_REF][START_REF] Wilson | A microprocessorcontrolled nitrogen dioxide sensing system[END_REF][START_REF] Zhou | A study of the response rate to nitrogen dioxide exposure in metal phthalocyanine thin film sensors[END_REF] Other papers suggested nanostructuring of Pcs or a kind of NO2 pre-exposure or preannealing to facilitate the NO2 release. [START_REF] Jalil | Fully Integrated Organic Nanocrystal Diode as High Performance Room Temperature NO2 Sensor[END_REF][START_REF] Newton | NO2 detection at room temperature with copper phthalocyanine thin film devices[END_REF][START_REF] Sadaoka | Fast NO2 detection at room temperature with optimized lead phthalocyanine thin-film structures[END_REF] Another approach that was demonstrated on Ti(Pc)2 and Lu(Pc)2 consisted of the application of UV light to accelerate the recovery. [START_REF] Baldini | Reversible and selective detection of NO2 by means of optical fibres[END_REF][START_REF] Bueno | Reversible NO2 Optical Fiber Chemical Sensor Based on LuPc2 Using Simultaneous Transmission of UV and Visible Light[END_REF] To avoid the long recovery times or sensor degradation at elevated temperatures, we propose to use and to tune the last strategy: the application of intensive light in UV and visible regions to stimulate the NO2 desorption (see Video S1) at an ambient or only slightly elevated temperature (55-100 °C). So far, the illumination has been carried out either by using a UV mercury lamp with a broad spectrum with multiple wavelengths (applied at once) or only one narrow-band LED in the UV region at a single illumination intensity. [START_REF] Baldini | Reversible and selective detection of NO2 by means of optical fibres[END_REF][START_REF] Bueno | Reversible NO2 Optical Fiber Chemical Sensor Based on LuPc2 Using Simultaneous Transmission of UV and Visible Light[END_REF] Therefore, in this work, we investigate the photoregenerating effects of light with various wavelengths in the range of 375-850 nm on various phthalocyanine derivatives (ZnPc, CuPc, H2Pc, PbPc, and FePc) at various intensities. We show that certain wavelengths in the UV-vis region (depending on the phthalocyanine derivative) are quite effective in the stimulation of NO2 desorption, thus shortening the recovery time by up to 90%.

■ EXPERIMENTAL SECTION

Preparation of the Phthalocyanine Sensitive Layers. Phthalocyanine chemiresistors were prepared by organic molecular evaporation (OME) in high vacuum conditions (≈ 1 × 10-4 Pa) on planar 2.5 × 2 mm2 alumina substrates equipped with two interdigital Pt electrodes (25 μm in width, 35 μm far from each other).32 Phthalocyanine powders were bought from Sigma-Aldrich and used for the chemiresistors without further purification. The evaporation of phthalocyanines (ZnPc, CuPc, H2Pc, PbPc, and FePc) was carried out at various temperatures and growth rates summarized in Table S1. Phthalocyanine layers (250 nm thick) grew at ambient temperature on substrates that were situated 22.5 cm from the evaporation crucible. Thicknesses of the chemiresistor layers were measured with a profilometer (Kla Tencor P-6) and microscope (Tescan FE-SEM MIRA). The layers were further characterized by optical and IR spectroscopies (HR2000+ and Nicolet iS5). Parameters of the Photoregeneration and Sensor Operation Details. Chemiresistor sensing characteristics were measured on pretreated sensor samples after thermal stabilization at 100 °C and double photoinitiation by light with wavelength (λ) of 441 nm and intensity (G) of 0.8 mW/mm2 for 30 s. The pretreatment was used in order to minimize their baseline (i.e., R0 = resistance in the synthetic air as a reference atmosphere) shift during the measurement. Sensor resistance was measured with an Agilent 34410A (R < 1.5 GΩ) or Keithley 6517B (R > 1.5 GΩ) apparatus in a constant gas flow of 25 mL/min. Sensing characteristics were investigated for each combination of phthalocyanine and illumination wavelength (i.e., 5 × 13 matrix) by the application of testing sequences described in the following protocol: 1. Stabilization = resistance stabilization in the reference atmosphere (the criterion for the stability was ΔR/R ≤ 1%/ min), 0-10 min. 2. Sensing = exposure to 0.2-1.6 ppm of NO2 in the reference atmosphere, 30 s. 3. Rinsing = exposure to the reference atmosphere to rinse unbonded NO2, 10-30 s. 4. Photoregeneration = chemiresistor illumination by light, 30 s. 5. Evaluation = did the resistance returned to its original value (step 1)? Yes = go to step 6; No = go back to step 4, 30 s. 6. Repetition = going back to step 1 to investigate repeatability (min 3×).

The sequence protocol is also shown in Figure 1. The individual sequence steps 1-6 are marked in the figure. The chemiresistor characteristics were calculated from the testing sequences and expressed as two quantities: normalized response magnitude NRM = (Rb -Rs)/Rb and regeneration degree RD = (Rr1 -Rs)/(Rb -Rs). The NRM is a relative change of the sensor resistance during the exposure to NO2 and represents sensor sensitivity. The RD is a relative return of the resistance to its baseline representing the degree of sensor recovery after the NO2 exposure. The photoregeneration of chemiresistors (step 4) was carried out by power LEDs (375-850 nm) refocused by two-lens optics to reach maximal spatial homogeneity of light intensity on the sensor (better than ±5% for the LEDs except 500 nm; for 500 nm, better than ±8%). The illumination setup is depicted in Figure 2. All diodes were spectrometrically and radiometrically characterized by using a spectrophotometer (HR2000+), a calibrated UV-vis reference source (DH-2000), and an optical fiber with a cosine corrector. Diode operating conditions were adjusted to obtain four different average light intensities (G) on the chemiresistors (G = 0.2, 0.4, 0.6, and 0.8 mW/mm2). Further details about the illumination are available in Table S2 and Figure S1 in the Supporting Information. Chemiresistor temperature was monitored and controlled by using an integrated Pt heater at the back side of the ceramic substrate. The chemiresistors were tempered at 55, 70, 85, or 100 °C excluding step 4 in the testing sequence. During step 4, the temperature mildly raised as a result of light absorption (tito = max +8 °C, see Figures 1 and6). During that step, we kept the constant heating power equal to the value from the previous step. This approach allowed to us effectively avoid the artifacts in resistance signals that originate in the PID controller's reaction to the change of the temperature. In the end, we repeated spectroscopic characterizations of the chemiresistive layers to compare the spectra before and after illuminations (G = 0.8 mW/ mm2 for 2 h and G = 7.3 mW/mm2 for 1 h, λ = 441 nm).

■ RESULTS AND DISCUSSION

The chemiresistor characteristics were calculated as two quantities, NRM and RD (defined above), obtained from the testing sequences measured for each combination of phthalocyanine (MPc) and wavelength (λ) at various temperatures (T), illumination intensities (G), and concentrations (c). Photoregeneration of ZnPc Chemiresistors at Various Temperatures, Illumination Intensities, and NO2 Concentrations. Photoregeneration at Various Temperatures. ZnPc chemiresistors were photoregenerated with certain effectivity by all the wavelengths (RD ≫ 0%). However, the regeneration degree (RD) significantly depended on the operating temperature and sensor baseline for the measurement. For this reason, the baseline value was always indicated and kept uniform for all measurements at the selected operating temperatures. Under these conditions, it was revealed that the regeneration degree (i.e., the effectivity of the photoregeneration process) increased with descending wavelength. For the temperature of 55 °C and baseline of (320 ± 9) MΩ, the wavelengths longer than 550 nm had an approximately constant RD in the range from 10% to 17%. (The intervals of the baseline values were constructed as a mean value of Rb ± corrected sample standard deviation of Rb. The same methodology was also applied for the NRM intervals construction.) We labeled this region as the low effectivity photoregeneration (LEP) region due to the small effects of the illumination on the resistance recovery to its original values. From 550 nm going down, the RD was increasing. It went from 35% for 518 nm to 96% for 375 nm (see the black curve in Figure 3a). This region is further referred to as the high effectivity photoregeneration (HEP) region. This character of the RD = RD(λ) dependence and the separation of RD values in two regions was preserved even if the operation temperature was altered. The values just slightly dropped. For the temperatures of 70, 85 and 100 °C with the corresponding baselines (301 ± 10) MΩ, (302 ± 13) MΩ, and (252 ± 8) MΩ, the RD stayed in the intervals of (9-16%), (7-12%), and (<12%), respectively, in the LEP region. In the HEP region, the RD decreased more significantly with the increasing temperature, providing the intervals of (33-81%), (24-59%), and (20-50%), respectively (Figure 3a). At the same time, the NRM increased with temperature from 0.25 ± 0.02 for 55 °C to 0.55 ± 0.02 for 100 °C, indicating repeatable increase of sensitivity. On the contrary, for the series of measurements at one temperature, the NRM was preserved approximately constant for all sequences with no trend. This should mean that the state of the films was not significantly changing between the consecutive measurements and, in other words, that the illuminations should provide only the desorption of the captured NO2 without the undesirable drift of baseline or/ and NRM values. Regarding the influence of the temperature, it seems that the photoinitiation at higher temperatures resulted in cleaner films with lower concentration of adsorbates, thus becoming more attractive for NO2 capture. A higher amount of captured NO2 then needed a longer illumination period to get desorbed. Typical examples of raw data are available in the Supporting Information (Figures S2 andS3). Photoregeneration at Various Illumination Intensities. To further investigate the nature of the photoregeneration processes, we carried out a series of measurements at a constant temperature of 55 °C and various intensities of illumination (0.2, 0.4, 0.6, and 0.8 mW/mm2). During all these measurements, we also kept the constant baseline value of 310 ± 18 MΩ. Under these circumstances, the RD was found to be more or less linearly proportional to the intensity of the illumination (Figure 3b). This finding is particularly promising for the applicability of the chemiresistors in practice as it should allow to easily adapt the photoregenerating effect to reproducibly restore the original sensor state after the exposures to various concentrations, ideally in one short photoregenerating step. The NRM was approximately constant 0.26 ± 0.02 for all sequences with no significant trend.

Mechanism of Photoregeneration. Considering the mechanism, two main types have been proposed for photoinduced molecular desorptions: (1) DIET (desorption or dissociation induced by electronic transitions) and ( 2) LITD (laser-induced thermal desorptions).34 In our case, the experimental evidence seems to disqualify the latter mechanism. The sensors were tempered at a selected temperature before exposure to light. At the beginning of the exposure (step 4 of the testing sequences described in the Experimental Section), the sensor heating power was fixed and the light was allowed to further heat the phthalocyanine layer by absorption. Differences in the layer temperature were proportional to the phthalocyanine absorption coefficient and are plotted in Figure 6. For ZnPc, the maximal layer temperatures during the "55 °C measurement" were 62 °C (55 + 7 °C) for illumination by 0.8 mW/mm2 of 723 or 592 nm due to the absorption in ZnPc's Q-band.15 Nevertheless, the regeneration degree was considerably lower for those wavelengths than for 441 nm, for example, where the absorption of ZnPc is negligible and hence the temperature rise is smaller (58.7 °C, i.e., 55 + 3.7 °C). This research finds a partial parallel in the class of inorganic semiconductors where UV-vis light can be used to activate the sensors to operate at ambient temperature. [START_REF] Park | UV-enhanced NO2 gas sensing properties of SnO2-Core/ZnO-shell nanowires at room temperature[END_REF] It has been reported that the application of light can also accelerate the regeneration of such sensors based on the following model (we will refer to it as RecDes, recombinative desorption model). At first (1), the light generates a hole in a semiconductor's valence band exciting the electron to the conduction band. Second (2), the hole reacts with negatively charged chemisorbed species to release them. [START_REF] Zhang | Room temperature responses of visible-light illuminated WO3 sensors to NO2 in sub-ppm range[END_REF] Extending the mechanism to chemisorbed NO2, we obtain eq 3. hυ → e + h -+ (1)

h + O2 (ads) → O2(gas) + -(2) h + NO2 (ads) → NO2(gas) + -(3)
In the end, the photoexcited electron from eq 1 is trapped in another hole because holes are major charge carriers in phthalocyanines as they are p-type semiconductors.37 This model is consistent with the increase in the resistance of ZnPc after illumination, which was observed regardless of whether the sensor was exposed to NO2 before. This model also predicts a threshold for the effective wavelengths as it requires sufficient energy to promote the electron across the band gap. The band gap was reported to be approximately 2 eV for ZnPc, which corresponds to the wavelength of 620 nm. [START_REF] Senthilarasu | Characterization of zinc phthalocyanine (ZnPc) for photovoltaic applications[END_REF] This value was found close to the border of the HEP region (see Figure 3a). Nevertheless, the tight correlation between the RD(λ) and ANO2(λ) also suggests another model based on the direct absorption of light by the chemisorbed NO2 (NLA model). It was reported that 90% of light energy absorbed by NO2 is supposed to be converted to vibrational motion that could stimulate the rate of molecular desorption.39 These effects have been already used for photoacoustic detection of NO2 by amplitude-modulated high-power light emitting diodes.39 Both models would expect the proportionality between the light intensity and rate of NO2 desorption. Sensitivity vs Concentration. The proposed method was further investigated in order to determine its NO2 detection limit. It was found out that the NRM is a linear function of NO2 concentration in the range from 0.2 to 0.9 ppm with an estimated detection limit of 20 ppb. The detection limit was calculated according to the methodology reported in ref 40. This demonstrates the preservation of sensitivity achieved by the traditional "steady state approach" methods while the measurement cycle duration is significantly reduced (∼2 vs ∼15 min).24 For the concentrations exceeding 0.9 ppm, the trend was still monotonic, but its slope was mildly decreasing (Figure 4b). Impact of the Method on Sensor Power Consumption. To evaluate the impact of the proposed method on the sensor power demand, we first calculated the consumption of our chemiresistors operating according to the "standard" optimized protocol reported in ref [START_REF] Brunet | An optimized gas sensor microsystem for accurate and real-time measurement of nitrogen dioxide at ppb level[END_REF]. Then we compared it with the consumption when following the protocol proposed in this article. The standard 15 min protocol for one measurement consists of 2 min of exposure to NO2 at 80 °C, 12 min of cleaning at 180 °C, and 1 min of stabilization again at 80 °C. For such a regime, the average power demand of our chemiresistors was calculated as 116 mW (3/15 × 45 mW + 12/15 × 134 mW). According to the new method, the chemiresistors operated at 55 °C, consuming 23 mW for 14.5 min and 121 mW (23 + 98 mW) for 0.5 min during the photoregeneration step with the 441 nm LED. As a result, the average consumption was ca. 26 mW, which was more than 4 times better when compared with the standard protocol. The consumption could be even better after improving the focus optics, as only ca. 4 mW (0.8 mW/mm2 × 5 mm2) is needed to promote the photoregeneration. Photoregeneration of the Other Phthalocyanine Chemiresistors (CuPc, H2Pc, PbPc, and FePc) at the Temperature of 55 °C. Photoregeneration of CuPc Chemiresistors. CuPc chemiresistors, with the baseline set at 106 ± 2 MΩ, did not photoregenerate with wavelengths greater than 550 nm (RD ∼ 0%). The photoregeneration was observed first with 518 nm (RD = 37%) and with even shorter wavelengths it was more and more effective (RD = 58-244%, Figure 5). The trend was analogous to the one observed for ZnPc, but the difference of the photoregeneration effectivities between the LEP and HEP regions was greater. The highest achieved RD values indicate that, in some cases, it was possible to "overregenerate" the chemiresistor set at a certain baseline while fulfilling the stability criterion of ΔR/R ≤ 1%/min. The "overregeneration" was probably caused by the photoinduced desorption of some part of the chemisorbed O2 or by the photoinduced desorption of the residual traces of NO2, which were not removed during the photoinitiation procedure described in the Experimental Section. However, the "overregeneration" is not a desirable effect, because it brings an issue connected with the requirement of the preservation of sensor baseline. The baseline value should be conserved for all the measurements to ensure the preservation of a specific film state necessary for correct comparison of consecutive detections and regenerations. In this case, the "overregeneration" was compensated by inserting an extra cycle with the same exposition to NO2 but followed by the photoregeneration with a lower illumination intensity or shorter illumination time. This, with regard to the dependence of the RD on the illumination intensity discussed above and a similar dependence on time, allowed return to the original baseline value while preserving the sensor sensitivity, because the NRM was approximately constant 0.61 ± 0.04 for all sequences with no trend as in the case of ZnPc. To complete this point, it should be noted that the direct return to the original baseline after the "overregeneration" solely by the exposure to the NO2 gas (without the subsequent illumination) did not provide comparable results as the NRM was decreasing proportionally to the dose of NO2 used for the baseline compensation. Photoregeneration of PbPc Chemiresistors. PbPc chemiresistors, working at the baseline of 15.3 ± 0.2 MΩ, did not significantly photoregenerate with any wavelength in the range from 375 to 850 nm (RD = -3-17%, Figure 5). As the photoregeneration was not effective in this case, we had to use the classical thermal recovery mechanism to regenerate the sensors. After 10 steps of illumination for each wavelength, step 4 in our methodology was replaced by a temporal increase of the operating temperature. It was increased from 55 to 130 °C for 30 s, and it went back to 55 °C to check the progress of the regeneration. With this approach, we managed to get an approximately constant NRM of 0.68 ± 0.02 for all sequences with no trend as in the case of other phthalocyanines. However, we encountered increasing instability of sensor baselines. This instability had to be compensated, so it resulted in dramatic prolongations of settling times. Nevertheless, despite these prolongations, it was problematic to fulfill the stability criterion defined in the experimental section. Due to these effects, PbPc cannot be considered as a suitable material for gas detection by our method. Photoregeneration of FePc Chemiresistors. As opposed to PbPc, FePc chemiresistors, operating at the baseline of 1.050 ± 0.002 GΩ, photoregenerated with all the wavelengths (RD ≫ 0%) and the RD significantly increased with descending wavelength as for ZnPc and CuPc (see Figure 5). However, the regeneration was much more intensive. For the wavelengths 678 nm+, the RD varied in the range from 30% to 99%. Then it rose to 156% for 630 nm and to several thousand percent for the light of 518-375 nm. These huge "overregenerations" complicated the measurement as the sensors were returning to their baselines very slowly (one return took practically several hours or days). To compensate this, we used controlled NO2 expositions to speed up the baseline return (without the subsequent illumination). Probably as a result of this approach, the NRM was mildly decreasing in the sequence of the experiments. At the end, it had 50% of its original magnitude. In spite of this, the application of FePc for NO2 detection seems to be prospective in combination with either longer wavelengths or significantly lower intensities (∼0.01 mW/ mm2) of the shorter wavelengths. Photoregeneration of H2Pc Chemiresistors. H2Pc chemiresistors, with the baseline set at 176 ± 26 GΩ, did not satisfactorily photoregenerate with any wavelength in the range measured. In terms of the RD, the values obtained were even negative in the range from -124% to -18%. The reason for the negative values could be that illumination causes a temporal increase in the layer conductivity and generates new free charge carriers, which seem to have much longer lifetime in H2Pc than in the other phthalocyanines. This could be connected with H2Pc's significantly higher resistance baseline. So, at the time of the RD evaluation, some of these photocarriers were probably still present there (see Figure S4). A similar effect has already been observed for amorphous VOPC and named as persistent photoconductivity (PPC).41 If we waited a longer time before the evaluation of the photoregeneration (30 min, not 30 s as defined in the methodology), we obtained small positive values of the RD, mostly close to 0% (Figure S4). The inefficiency of the photoregeneration in the case of H2Pc forced us to apply thermal regeneration by temporal increases of the operating temperature to 90 °C. The was approximately constant, equal to 0.28 ± 0.04 with no statistically significant trend. Comparison, Implications for the Mechanism. Extending the study to the phthalocyanine materials other than ZnPc revealed the importance of the central cation for the process of photoregeneration. The phthalocyanines (ZnPc, CuPc, H2Pc, PbPc, and FePc) divided into two groups differing in the ability to photoregenerate. ZnPc, CuPc, and FePc exhibited photoregeneration; H2Pc and PbPc did not. This division seems to correspond with the symmetry of the molecules. Zn2+, Cu2+, and Fe2+ cations are small and fit the cavity of the macrocycle, letting the phthalocyanine preserve its planar structure with the symmetry D4h. H2Pc's hydrogens reduce its symmetry to D2h and PbPc's large Pb2+ cation that distorts the planarity of the molecule reduces the symmetry to C4v.15 Regarding the mechanism of desorption, from the viewpoint of the models considered above, the universal shape of the RD(λ) for various phthalocyanines (it differs just by a multiplicative scaling factor) seems to favor the one based on the direct absorption of light by the chemisorbed NO2. The RecDes model would expect some shifts of the RD(λ) curve based on the variations of the band gaps (CuPc ∼ 1.7 eV).42 However, the precise value of the band gap widths may be difficult to consider as the literature contains rather a range of values for each phthalocyanine. Stability of the Phthalocyanine Sensitive Layers under Illumination (Spectral Study). UV-vis spectra and FTIR spectra of the layers were consistent with those in the literature. The comparison is provided in the Supporting Information. Effects of the Illuminations on UV-Vis Spectra of the Phthalocyanine Layers. The Pc spectra did not change significantly with the layer illuminations at working conditions for photoregeneration (441 nm, 0.8 mW/mm2, 2 h). Based on these findings, we are convinced that, under the working conditions, there are no irreversible changes in the layers caused by the illuminations. We believe that the effects of light are restricted only to (i) the photostimulated desorption of the species adsorbed on the surface of the phthalocyanine layers (NO2, O2, H2O) and (ii) the generation of photoinduced mobile charge carriers. However, we observed some changes of FePc and PbPc UV-vis spectra after stronger illuminations (7.3 mW/mm2, 1 h). In these particular cases, the stronger illuminations led to small depreciations of the Q absorption bands (626 nm, -6%; 719 nm, -3%, respectively, Figure 6). We think that these depreciations were caused by partial temperature-stimulated recrystallizations of the FePc and PbPc layers, as those layers exhibit some level of absorption of the 441 nm light. The temperature rose by more than several tens of degrees (°C) for the stronger illuminations and hence could provide the energy to the layers to recrystallize. PbPc, for example, is known to have two polymorphs differing in their absorption spectra: (i) monoclinic with the absorption maxima at 740 nm and (ii) triclinic with the maxima at 900 nm.43 It has been reported that the annealing process can induce the recrystallization of the as-deposited monoclinic phases to the more thermodynamically stable triclinic form.43 On the contrary, the absorption of the layers of the other phthalocyanines (ZnPc, CuPc, and H2Pc) is negligible in the spectral region around 441 nm and thus their temperature rises were insufficient to alter layer morphology. Effects of the Illuminations on FTIR Spectra of the Phthalocyanine Layers. The FTIR spectra remained unchanged for the working intensity of the illuminations (0.8 mW/mm2), supporting the interpretation mentioned above and the claim of stability. After the stronger illuminations (7.3 mW/mm2), we again recorded the almost identical spectra containing only minor changes of very weak bands for ZnPc at 668 or 434 cm-1 and CuPc at 571 cm-1 (Figure S5). A possible explanation of these changes may lie in the stimulated desorption of several adsorbates (NO2, O2, H2O) which are present in phthalocyanine layers at ambient conditions.

■ CONCLUSIONS

ZnPc, CuPc, and FePc thin layers containing certain amounts of NO2 as a result of a chemiresistive detection process were found to photoregenerate when they were exposed to light with a wavelength shorter than 550 nm. Such light demonstrated its capability to stimulate NO2 desorption from the layer, accelerating its recovery to the original state Figure 6. UV-vis spectra of the phthalocyanine sensitive layers before (gray area) and after (red dashed curve) illumination (7.3 mW/mm2, 1 h). The graphs contain superimposed curves (STR) illustrating temperature effects of illumination on the chemiresistors (0.8 mW/ mm2). before the detection of NO2. This effect was ascribed either to the generation of holes in the organic semiconductor that can recombine with the chemisorbed species or to the direct desorption induced by electronic transitions originating from the light absorption in chemisorbed NO2. It was shown that photoregeneration can be conducted at ambient or slightly elevated temperatures (55-100 °C), thus opening the possibility of simple phthalocyanine based chemiresistors operating at low temperatures. Lower temperatures imply lower electrical consumption (ca. 25%) and longer lifetime of the sensors. Moreover, we modified the kinetic operating procedure suggested in ref 25 benefit not only from the considerable acceleration of measurement (Tmeas.cycle was ∼ 2 min, more than 7 times faster than the traditional optimized approach presented in ref [START_REF] Brunet | An optimized gas sensor microsystem for accurate and real-time measurement of nitrogen dioxide at ppb level[END_REF], but also from the preservation of the limit of detection (<20 ppb) and the improved baseline stability (→ better repeatability of the measurement). The photoregeneration effects were further found to be approximately linearly dependent on the light intensity and also proportional to the operating temperature and the phthalocyanine type. From a practical standpoint, it has been shown that photoregeneration could help phthalocyanine based sensors to become more than a viable alternative to conventional techniques for NO2 monitoring.

■ ASSOCIATED CONTENT *S Supporting Information

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acssensors. 8b00922. Evaporation parameters and details about the sensitive layers; details about the illumination; typical raw data of ZnPc photoregeneration; persistent photoconductivity of H2Pc; UV-vis and FTIR spectra of the sensitive layers and their comparison with the literature; effects of the illuminations on FTIR spectra of the phthalocyanine layers (PDF) Animated video of the photoregeneration (AVI)

■ AUTHOR INFORMATION

Corresponding Author *E-mail: vrnatam@vscht.cz.

ORCID

Martin Vrnata: 0000-0002-1199-1458

Notes

The authors declare no competing financial interest.

Figure 1 .

 1 Figure 1. Testing sequence for the investigation of phthalocyanine photoregeneration. The individual sequence steps are marked with numbers: (1) stabilization, (2) sensing, (3) rinsing, (4) photoregeneration, (5) evaluation, and (6) repetition.

Figure 2 .

 2 Figure 2. Illustration of the illumination setup. Sensors were illuminated by power LED diodes (375-850 nm) refocused by two lens optics to reach maximal spatial homogeneity of light intensity.

Figure 3 .

 3 Figure 3. Dependence of the regeneration degree RD on the wavelength of the incident illumination and the influence of (a) sensor operating temperature (55, 70, 85, and 100 °C) and (b) intensity of illumination (0.2, 0.4, 0.6, and 0.8 mW/mm2). The absorption spectrum of NO2 in the gaseous phase at 20 °C (dotted line) was taken from the database (ref 33).

Figure 4 .

 4 Figure 4. (a) Illustration of the stability of the baseline 320 ± 9 MΩ, constant value of the NRM 0.25 ± 0.02, and evolution of the regeneration degree RD. The data consists of sequence steps 1-5 recorded during the measurement of ZnPc at 55 °C illuminated by light of various wavelengths (0.8 mW/mm2). The wavelength position (x-axis) is an auxiliary variable proportional to time (1 nm = 6 s). The beginning of each sequence is positioned on the nominal wavelength of the LED used for the photoregeneration. (b) Dependence of the NRM on the concentration of NO2 (0.2-1.6 ppm) for a ZnPc chemiresistor operating at 55 °C. The inset contains an example of the raw data recorded for the concentration of 0.55 ppm illustrating good repeatability and short measurement cycle duration. The photoregenerations were carried out by the 441 nm light.

Figure 5 .

 5 Figure 5. Dependence of the regeneration degree RD on the phthalocyanine material (FePc, ZnPc, H2Pc, PbPc, and CuPc). The absorption spectrum of NO2 in the gaseous phase at 20 °C (dotted line) was taken from the database (ref 33).

■ ACKNOWLEDGMENTS

This work was supported by Czech Science Foundation (GACR), Projects No. 17-13427S and No. 18-09347S and also by Ministry of Education, Youth and Sports within the projects LTC17058 and 8J18FR011 and by COST Action CA15107 MultiComp. Financial support from specific university research (MSMT No 21-SVV/2018) and PHC Barrande 2018 is also acknowledged.


Salah Eddine Elayoubi
email: salaheddine.elayoubi@cen-tralesupelec.fr

Sana Benjemaa

Zwi Altman

Ana Maria Galindo Serrano

Sana Ben Jemaa

Ana Galindo-Serrano

Ana Galindo

5G RAN slicing for verticals: Enablers and challenges

Keywords: Mobile networks, 5G, Slicing, Network design -----

come

INTRODUCTION

While third and fourth generation mobile networks revolutionized social behaviors by enabling the generalization of social networking on mobile devices, fifth Generation (5G) networks are expected to revolutionize our living environments, our cities and our industry by connecting everything. 5G is thus expected to mark a disruptive change and not to be a business-as-usual evolution of 4G networks limited to higher user throughputs but has to cover the needs of smart cities and vertical industries. In addition to the so-called enhanced Mobile Broadband (eMBB) service, the 5G design has to meet the requirements of two "new" mobile services: massive Machine Type Communications (mMTC), characterized by a very large density of connected objects and Ultra-Reliable Low Latency Communications (URLLC), characterized by stringent requirements in terms of low latency and high reliability. This is illustrated in Figure 1 along with some associated vertical use cases.

Considering each service type separately and building a network accordingly would likely end up with very different Radio Access Network (RAN) designs and architectures. However, only a common RAN that accommodates all three service types is an economically and environmentally sustainable solution. In addition, 5G is viewed not only as a new radio and core, but also as an orchestration platform where verticals build specialized services for their customers [START_REF] Elayoubi | 5G innovations for new business opportunities[END_REF]. This creates a large number of services, that belong to the above-defined three service families (eMBB, URLLC and mMTC) [2], but with a plethora of requirements. The slicing concept has then emerged as an efficient way for serving all these services on a common infrastructure [START_REF] Foukas | Network Slicing in 5G: Survey and Challenges[END_REF]. A slice may describe an end-to-end relationship, i.e., its functionalities may also cover the 5G RAN. A network slice can be considered as an independent network, with the corresponding advantages e.g., for security and guaranteed Service Level Agreement (SLA). However, in contrast to deploying independent network infrastructures as it was the case in former mobile radio generations, the slices may be implemented, completely or partially, on a common infrastructure layer, including assets such as spectrum. This paper discusses how the RAN can be sliced for satisfying heterogeneous service requirements while sharing the same radio and processing resources. For doing so, we show how 5G new radio features, like tiling and puncturing, can be exploited and how different functions can be placed and chained using practical examples. In particular, we provide suggestions on how the network functions on lower layers can be configured for the different slices and how the architecture has to be adapted so that the service performance targets are met. We also give a special emphasis on the resource allocation techniques that are suitable for different use cases, including scheduling and channel access, and on how the corresponding slices interact among them at the RAN level. We provide discussions on the relevant challenges and corresponding open research problems.

SLICING GRANULARITY AT THE RAN

Before entering into the different options for defining a slice, we note that slicing has also been imagined as a mean for simplifying and optimizing network and infrastructure sharing between operators. In this context, one slice could be associated with an operator's virtual network deployed on another operator's infrastructure. We note that slicing for dynamic sharing of infrastructure and/or spectrum between operators is out of the scope of this paper.

Option 1: one slice per family of services

The simplest way for defining slicing is to consider a slice per family of services, for example one for smartphones (eMBB service), one for autonomous driving (URLLC service) and one for the Internet of Things (IoT, mMTC service). However, this approach does not consider the heterogeneity of requirements within each family of services. For example, the URLLC service includes a large set of use cases with very different requirements, ranging from wide area haptic services with very low end-to-end latency and low mobility requirements, to local networks of moving robots with stringent reliability constraints.

Option 2: one slice per set of technical requirements

A more general approach is to define a small number of technical slices starting from use-case requirements (bandwidth, latency, security, volume of messages, scalability, mobility, etc.) and grouping services that belong to the same family (in terms of requirements). While this approach solves the above mentioned issue (heterogeneity of requirements within the same 5G service family), other issues arise. For instance, slices offering the same type of services to different players (e.g., Renault or PSA), with different SLAs still need to be differentiated and isolated.

Option 3: one slice per vertical customer

We now consider an alternative approach with a slice per vertical customer. This option does not, however, correspond to a clear definition of slices. For instance, if we consider a business customer from the automotive domain, we can identify several services with heterogeneous requirements: -Entertainment (high throughput, close to eMBB), -Mission critical/autonomous driving (low latency high availability close to URLLC), -Data retrieving for maintenance or tracking (low throughput, close to mMTC). These different services cannot be managed by a single slice properly given the heterogeneity of their requirements.

Option 4: one slice defined per business customer and technical requirements

The analysis of the previous three options calls for a large number of slices, defined on business and SLA bases. For example, this option defines a slice for a specific automotive customer for entertainment on board, another one for the same customer for autonomous driving, while another slice is dedicated to autonomous driving for another automotive customer, and so on. This option is coherent with the definition of "a network slice instance" given in the 3GPP standard [START_REF]Technical Specification Group Services and System Aspects; System Architecture for the 5G System; Stage 2 (Release 15)[END_REF]. In practice, the operator may propose to the customer (Vertical) a network slice (e.g., URLLC for automotive industry) with configurable characteristics. The deployed slice instance (URLLC for automotive industry of customer x) would correspond to the customization of this Network slice to respond to the specific agreed SLA. In 3GPP [START_REF]Technical Specification Group Services and System Aspects; System Architecture for the 5G System; Stage 2 (Release 15)[END_REF], a UE can select a specific slice knowing its Single Network Slice Selection Assistance Information (S-NSSI). This slice identifier consists of two components: -A Slice/Service type (SST), which refers to the expected slice behaviour in terms of features and services. Three standardized SST values are defined in [START_REF]Technical Specification Group Services and System Aspects; System Architecture for the 5G System; Stage 2 (Release 15)[END_REF], namely eMBB, URLLC and mMTC in order to provide a way for establishing global interoperability for slicing (e.g. in case of roaming), but additional SSTs can be defined. -A Slice Differentiator (SD), which is optional information that complements the SST to differentiate amongst multiple slices of the same Slice/Service type, in order to differentiate two slices corresponding to different customers, with different SLA requirements for example.

RAN SLICING IMPLEMENTATION

Starting from the granularity of slicing of option 4 above, we here identify how these slices are mapped and implemented on the RAN level in a cost-effective way in terms of radio resource consumption. We start from the lower layers up to network function selection, configuration and chaining for each slice.

Slice isolation and spectrum sharing

One of the main challenges in implementing slicing in the RAN consists in designing and managing several slices on the same shared infrastructure in an efficient manner, while guaranteeing the agreed SLA for each of them. This brings us to the "slice isolation" concept that forbids any mutual impact between coexisting slices. The isolation concept is not clear today when it comes to resource allocation (while it is easy to understand in other domains such as security), but it is of common understanding to consider that two slices are isolated as long as the actions performed on one slice do not result in an SLA violation on the other slice.

Depending on the way the spectrum is shared and the slices are multiplexed in the RAN, the degree of isolation of slices from a performance perspective varies [START_REF] Rost | Network Slicing to Enable Scalability and Flexibility in 5G Mobile Networks[END_REF]. At the extreme left of Figure 2, a slice corresponds to a stand-alone network, with its specific spectrum and infrastructure. On the opposite, at the extreme right side, slices are limited to core network and resource allocation in the RAN is sliceindependent, possibly implementing 4G-like Quality of Service (QoS) differentiation mechanisms. Intermediate solutions are also possible, with slices going lower in the protocol stack when moving left. It is worth noting that customization and isolation increase when moving left, at the expense of higher needs in terms of infrastructure deployment.

Fig. 2. RAN slice multiplexing options.

While neither of the slicing options in Figure 2 are to be discarded, the extreme cases correspond to very specific situations (a stand-alone network vs. a 4G-like RAN). We propose a general slice implementation as an intermediate degree of isolation. In this proposed scheme, the physical (PHY) and Medium Access (MAC) layers common to all slices (except those on dedicated or unlicensed spectrum), and the higher layers, are slice specific. For these higher layers, a specific network function selection, configuration and chaining is to be for each slice. This chaining aims at achieving specific requirements (e.g., suppressing some processing functions for reducing latency). For example, handover management functions can be suppressed for slices serving fixed nodes, and packet fragmentation can be removed for slices transporting short but critical packets.

Tiling and scheduling

A first radio feature that is considered as an essential enabler for slicing at the RAN level is the tiling scheme [START_REF] Rost | Network Slicing to Enable Scalability and Flexibility in 5G Mobile Networks[END_REF]. This latter is a practical implementation of the so-called flexible numerology concept of 5G. Recall that resource allocation in 4G is based on a time-frequency grid, with a basic allocation of one Resource Block (RB) composed of 7 subcarriers of 15 KHz each allocated during a slot of 0.5 ms. 5G offers the opportunity of serving different services using different subcarrier spacing and/or Transmission Time Interval (TTI) lengths. The principle is that time-frequency resources with the same numerology are grouped together within a tile (or RB Group, RBG). This reduces the processing burden associated to scheduling as it restricts the positions where users of different services may be allocated and minimizes border issues (interference between different numerologies). Figure 3 illustrates this concept with the following design principles [START_REF] Pedersen | A flexible 5G frame structure design for frequency-division duplex cases[END_REF]: -For eMBB: Start transport (TCP) sessions with short TTI size to quickly overcome the slow-start phase (third tile of Figure 3), then use a medium TTI (e.g., 1 ms, first tile of Figure 3) to minimize control overhead. -For mMTC: use a lower bandwidth with a longer TTI size to save device energy and increase coverage (similar to the Narrow Band IoT concept of 4G). This is illustrated by tile 2 in Figure 3. -For URLLC: use short TTIs (e.g., 0.25 ms) to meet latency requirements. Larger subcarrier spacing can also be useful for some URLLC use cases (e.g., in vehicular case against Doppler effect), see tile 3 of Figure 3.

It is worth noting that the tiling concept can be extended to mixed waveforms (e.g., CP-OFDM for eMBB and a filtered version for mMTC). We now explore the usage of the tiling concept for optimal resource allocation for slices. The scheduler has the role of allocating resources to comply to SLAs with the corresponding QoS requirements for the different slices, with possibly highly heterogeneous requirements. The scheduler complexity can be simplified by (i) dynamically determining the tile composition and (ii) by mapping the slices to these tiles. Using such a mapping, a simpler management of numerology and other PHY/MAC parameters such as TTI length and waveform parameters can be achieved.

We note that multiplexing in time is easy as 3GPP imposes symbol alignment between tiles, ensuring orthogonality. As of frequency multiplexing, in order to guarantee orthogonality between adjacent tiles, 3GPP advocates the insertion of guard bands between tiles with different subcarrier spacings.

Puncturing concept for URLLC scheduling

The tiling concept is not sufficient, alone, for meeting the requirements for URLLC services, especially for applications with a very bursty traffic. Instead of over-provisioning the URLLC tile, the puncturing (or preemption) mechanism has been proposed in [START_REF]G PPP FANTASTIC-5G project, Deliverable D3.2[END_REF] with the following implementation: -In the downlink, as the scheduling is performed by the base station, if an urgent URLLC packet arrives while all resources are occupied by ongoing eMBB transmissions, the base station preempts some already allocated resources, leading to a loss for the preempted eMBB user, recovered by retransmissions. This is illustrated in Figure 3 where the third tile is extended in the frequency domain during one slot to serve an urgent URLLC packet. -In the uplink, when a device has an urgent packet to transmit, it transmits it with a higher power on a resource that may be occupied by an eMBB user, so that the receiver can decode its transmission. For the preempted eMBB packet, it can be recovered iteratively (after decoding the URLLC packet), or by retransmissions.

Slice identification and mapping

An important issue is the identification of the slice to which a flow of packets belongs, so that a RAN network function needs may apply a potential specific treatment to them. We give the example of the scheduler that is nowadays able to handle a limited number of traffic classes, e.g., via the 4G QoS Class Identifier (QCI). However, the multiplication of slices with specific SLAs will make the task harder for these network functions if they have to handle directly the slice identifier. A RAN slice management entity, such as the Software-Defined Mobile Network Controller (SDM-X) in [START_REF] Rost | Network Slicing to Enable Scalability and Flexibility in 5G Mobile Networks[END_REF], could facilitate this task by: (1) performing the function chaining for flows, depending on the SLAs associated to their slices. For instance, Packet Data Convergence Protocol (PDCP) functions related to header compression may be suppressed for some URLLC and mMTC slices [START_REF] Silva | Impact of network slicing on 5G Radio Access Networks[END_REF], (2) selecting the corresponding configurations at PHY layer for packets belonging to flows of a given slice. For instance, massive MIMO techniques are to be activated for eMBB slices only and channel coding is to be selected based on the reliability targets, (3) mapping the slice SLA to a QoS identifier and to a tile in order to reduce scheduler complexity.

Architectural considerations

The network architecture will have a paramount impact on the service latency and the application should be placed closer to the users with critical latency needs. Figure 4 presents three different network architectures which will respond to the different service latency requirements. As presented in (a), when service latency requirement is not very stringent i.e., more than 20 ms, the application can be placed in a centralized application entity. When the application requires an end-to-end latency lower than 10 ms, the application should be lowered to a Centralized Unit (CU), which is also known as Mobile-Edge Computing (MEC). Finally, when the provided service requires very low latency, i.e., 1 ms, the application should be placed in the radio site, the closest possible to the user. A slice manager will have to be integrated at each level i.e., centralized application entity, CU and Radio site, to correctly conduct the traffic corresponding at each slice in each level. Note that, as different slices coexist in the same geographical area, the RAN architecture has to be flexible, allowing the coexistence of the three architectures, with an adequate dimensioning of processing resources at the distributed and centralized units.

Slice-specific configuration

A slice specific configuration can be performed so that the QoS requirements of the underlying service can be met, including selection of lower layer RAN functions [START_REF] Silva | Impact of network slicing on 5G Radio Access Networks[END_REF]. Table 1 illustrates an example of four slices sharing the infrastructure in a vehicular environment, defined as proposed in section II (i.e., service/industry/customer based): -Two slices belonging to the same automotive customer, one for entertainment on board (eMBB) and one for safety messages (URLLC), -One slice for gathering the information sent periodically from sensors on the road (mMTC) -One eMBB slice for smartphones of pedestrians. The table reuses some of the concepts developed in the sections above and shows the best per-slice configuration for different network functions.

CHALLENGES FOR RAN SLICING

While the above detailed radio features facilitate the implementation of slicing, there are still many challenges when it comes to resource allocation and management.

Resource allocation

The cohabitation of a large number of slices poses many challenges related to resource allocation to slices and flows, considering not only radio resources but also processing ones (for MEC and virtual radio functions). One of the major open research problems consists in adapting existing resource allocation schemes, designing and developing new ones and fitting them into the new context of slicing in the RAN. These schemes have to ensure jointly QoS for individual slices, fairness between slices and overall resource efficiency. A number of papers provide an overview on fairness in multiresource allocation. One of the most promising works in this field is that of [START_REF] Ghodsi | Multi-resource fair queueing for packet processing[END_REF] that proposes the so-called Dominant Resource Fair (DRF) queuing as a scheduling algorithm, generalizing the concept of virtual time for resource sharing in clusters or routers equipped with middle boxes. [START_REF] Bonald | Multi-Resource Fairness: Objectives, Algorithms and Performance[END_REF] examines the objectives of mostly advocated resource allocation principles, such as Proportional Fairness (PF), DRF and the proposed Bottleneck Max Fairness (BMF).

While many of these approaches may be relevant in the context of slicing, there are several related open questions:

(1) How fairness is defined for services that do not require high throughputs but rather massive connectivity, high reliability or low latency? (2) Is a scheduler based on weighting the different slices corresponding to their priorities able to manage resource allocation for the ensemble of traffic of the different tenants served by different slices? (3) During high load, is puncturing (i.e., preemption of resources by a higher priority service, see 3.3) enough to manage the traffic and service mix? (4) Is it needed to reserve resources to enforce SLAs for all slices? (5) If resource reservation is necessary, how much should be reserved and what about over-provisioning?

Keeping in mind that due to the random nature of traffic, for given reservation levels and scheduling strategy, the answer to the dimensioning exercise is probabilistic. If reservation is performed, the non-reserved resources should be shared among the slices according to the scheduling policy.

In order to be more specific, we discuss the different options for allocating resources to URLLC services. Table 2 presents different URLLC use cases and their generated traffic types and shows how resources have to be allocated to the corresponding slices and how they interact with the general eMBB slice. This table is not meant to be exhaustive, but shows a wide range of resource allocation schemes for these types of services, leading to interesting research perspectives.

SLA monitoring

Monitoring capabilities are necessary for the customer to verify that the network delivers the desired service with the associated SLA, but it has also the function of alerting the customer in case the SLA cannot be fulfilled anymore. This is essential for critical applications, so that the cus-tomer can adopt appropriate security measures, e.g., stop the equipment relying on the network for connectivity, or inform that some functions are temporarily deactivated. Note that the alerting function would take advantage of associating the SLA monitoring to prediction capabilities regarding the risk of SLA non-fulfilment in the future.

Monitoring of legacy RAN is performed using (aggregated) metrics coming from base stations, namely at cell level, or from traces from UEs. The information reported at the radio access level corresponds to the service class granularity (e.g., per QCI in 4G), and hence is less precise than the service granularity at higher layers. As stated earlier, the RAN should be slice aware, and should be able to differentiate slices in order to fulfill the corresponding SLAs. Hence it should be possible to monitor separately users belonging to different slices. In addition, monitoring SLA for slices in a virtual network requires monitoring both physical and virtual resources. We finally note that slice monitoring has to report Key Performance Indictors (KPI) that are user-related

Waveform

OFDM Filtered-OFDM for coping with the possible asynchronicity [START_REF]G PPP FANTASTIC-5G project, Deliverable D3.2[END_REF] OFDM OFDM

Subcarrier spacing

30 KHZ for coping with Doppler effect [START_REF]G PPP FANTASTIC-5G project, Deliverable D3.2[END_REF] 30 KHZ for coping with Doppler effect 3.75 KHz 15 KHz

MIMO scheme

Predictor antenna for solving the channel aging problem [START_REF] Phan-Huy | 5G on Board: How Many Antennas Do We Need on Connected Cars?[END_REF] 2*2 Transmit Diversity Receive diversity Grid of Beams [START_REF] Panzner | Deployment and implementation strategies for massive MIMO in 5G[END_REF] Retransmissions Classical HARQ (Hybrid Automatic Repeat Request)

No HARQ or automatic retransmission (without waiting for acknowledgement) [START_REF] Singh | Contention-Based Access for Ultra-Reliable Low Latency Uplink Transmissions[END_REF] Multiple transmissions of each packet Classical HARQ

Scheduling scheme

Proportional fair scheduling Reserved pool, non-scheduled (contention-based) [START_REF] Singh | Contention-Based Access for Ultra-Reliable Low Latency Uplink Transmissions[END_REF] Scheduled on multiple uplink resources for providing diversity against collisions

Proportional

Fair scheduling

Architecture

Content on a distant server or regional caches Application server deployed close to the edge, e.g., in road-side units Centralized data gathering and processing server Contents on a distant server (a) Wide area coverage slice with distant applications (e.g., eMBB), while the Packet Gateway (PGW) is in the CU.

(b) Slice with regional footprint and medium sensitivity to latency (e.g., augmented reality).

Both applications and PGW are in the CU.

(c) URLLC slice with very stringent latency constraints (e.g. industrial control). Virtual PGW (vPGW) and applications are in the radio site. (throughputs, delays, reliability), but also network-related (per slice load and energy efficiency). The latter KPIs are challenging to assess as they are related to the infrastructure that is shared between slices.

Multi-tenant slicing in the RAN

Slicing is expected to facilitate openness of the network to third parties, or tenants (e.g., a virtual network operator or a vertical). Openness of the network to third parties is regarded as a key issue as it may encourage some vertical players to use operators' networks rather than deploying their own infrastructure. At the RAN level, different options for openness are possible, following the degree of control the tenant has on the slice, from monitoring only to full control. The option that corresponds to the lowest opening degree grants full control to the operator, while the third party is allowed to access to monitoring KPIs. In this case, the operator is in charge of guaranteeing the fulfillment of the SLA, that corresponds to e.g., the QoS provided to the end-users of the slice. The operator is the owner of the network and is responsible for the network operation and management.

The other extreme option corresponds to a full control of the network slice by the third party. The operator only provides the infrastructure to the third party which is in charge of operating the slice. Here we may have several suboptions: the slices are pre-designed by the operator and are provided to the third party as "plug-and-play" slices; or the third party performs design/composition of the slice by using virtual functions offered by the operator or even by onboard-ing its own functions. From a RAN point of view, as the operator is leasing the control of a part of its network to a third party, the slice should be deployed on a dedicated spectrum, which may raise regulatory issues if the slice is deployed on licensed spectrum.

In the intermediate option, the slice is operated by the MNO and partially controlled by the third party. The slice owner can control some network functions or change some configurations in the network. Consider for example the "Factory of the Future" vertical, where the slice is typically deployed on a limited area, and where the slice owner may want to have a higher involvement in the slice design and the network optimization functions. For instance, the throughput/coverage required in each area of the factory may change in time depending on mobile robots' trajectories, installation of new machines, changes in the internal organization targets, etc. The slice owner may want to re-plan the resources accordingly, including transmitted powers and beamforming schemes. This option is feasible as long as the isolation of the slice is guaranteed; in particular, the actions performed on this slice do not harm the rest of the operator network. This can be performed for example through the selection of certain network functions and their allowed configurations (configurable parameters and their ranges).

More generally, this intermediate openness raises several issues about the impact of a specific third party on the global performance of the network, and on defining the responsibilities of the slice owner and of the operator when performance degradation occurs in the network. [START_REF]5G-PPP use cases and performance evaluation modeling[END_REF].

Use case Traffic type Resource allocation for the corresponding URLLC slice

Interaction with eMBB slice Industry automation (controlled indoor environment) Periodic generation of packets by a limited number of machines Persistent (cyclic) resource reservation for each UE [START_REF] Han | Periodic Radio Resource Allocation to Meet Latency and Reliability Requirements in 5G Networks[END_REF]. As the amount of resources is to be pre-determined and cannot be changed dynamically, an over-allocation is advocated along with a continuous channel estimation that adapts the allocation to radio condition variation on a scale of several milliseconds. Any resources in the URLLC traffic cycle that are not reserved for URLLC can be used for eMBB. The amount of reserved resources is to be updated depending on variations in traffic and radio conditions Sporadic generation of packets by a large number of machines Cyclic reservation of a pool of common resources. Several copies of each packet may be sent for combating collisions and different copies may be combined for increasing reliability [START_REF] Singh | Contention-Based Access for Ultra-Reliable Low Latency Uplink Transmissions[END_REF].

Traffic safety (vehicular environment)

Periodic packets sent by cars

Reservation of a pool of common resources.

eMBB and URLLC resources are orthogonal in the same cells, but interference may happen between URLLC service in one cell and eMBB service in another cell that, for instance did not activate the URLLC slice. Correlated packet generation due to unexpected events Preemption of resources from the other slices when the packet flood is detected eMBB resources are pre-empted for serving high priority URLLC traffic. Higher-layer actions are needed, e.g., change in video encoding, otherwise dropping may occur.

Tactile Internet (wide area coverage)

Persistent traffic generated by well-localized UEs (e.g., around medical centers) URLLC slice is always on and resources are continuously reserved on the end-toend path eMBB and URLLC resources are orthogonal in the same cells, but interference may happen with other cells that do not have the URLLC slice activated Occasional point-to-point slice establishment (e.g., for emergencies) Ad-hoc URLLC slice establishment and resource reservation Some eMBB QoS problems may occur at URLLC slice establishment. The eMBB slice is to be reconfigured (e.g., via admission control, dropping or higher layer mechanisms) as tactile Internet slices are in general long-living.

CONCLUSION

This paper has investigated the slicing concept in the 5G RAN with the objective of identifying the plausible options for implementing the slicing concept at the RAN level to respond to the needs of verticals. While the lower layers need not know the exact ID of the slice, they should be able to respond to their heterogeneous requirements. Different concepts and challenges related to RAN slicing and their management have been described. The tiling concept allows implementing different PHY/MAC configurations on the same spectrum, and a slice management entity maps slices to tiles at a relatively long time scale. The low level scheduler that operates per-tile dynamically allocates resources to flows while the differentiated scheduling mechanism remains an open research problem. The degree of openness of the RAN slices to third parties or tenants, such as verticals, that may be willing to be involved in slice monitoring and configuration, in another open issue that introduces new challenges to RAN management.

Fig 1 .

 1 Fig 1. 5G as enabler for new services While the utility of slicing for serving vertical use cases is commonly understood, there is still no consensus on the slice granularity nor the slice implementation on the RAN. In [8], the authors identify the different requirements for slicing in the RAN, including efficiency, protection, differentiation and slice-awareness. [3] discusses the management and orchestration for end-to-end slices, including infrastructure layer, network function layer and service layer, but does not enter into the RAN implementation details. [5] Focuses on the architectural dimension for slicing, including network function chaining, leveraging on the concept of Software Defined Mobile Network Control (SDN-C).This paper discusses how the RAN can be sliced for

Fig. 3 .

 3 Fig.3. Example of tiles. A first 4G-like is used for general eMBB services in scheduled mode. The second tile is allocated to mMTC services in a contention-based mode. The third tile with a smaller TTI and a larger SCS is suitable for URLLC transmissions but also for eMBB flows in their slow start phase.We now explore the usage of the tiling concept for optimal resource allocation for slices. The scheduler has the role of allocating resources to comply to SLAs with the corresponding QoS requirements for the different slices, with possibly highly heterogeneous requirements. The scheduler complexity can be simplified by (i) dynamically determining the tile composition and (ii) by mapping the slices to these tiles. Using such a mapping, a simpler management of numerology and other PHY/MAC parameters such as TTI length and waveform parameters can be achieved.We note that multiplexing in time is easy as 3GPP imposes symbol alignment between tiles, ensuring orthogonality. As of frequency multiplexing, in order to guarantee orthogonality between adjacent tiles, 3GPP advocates the insertion of guard bands between tiles with different subcarrier spacings.

Fig. 4 .

 4 Function placement for different slices, focusing on PHY, MAC, Radio Link Control (RLC) and Radio Resource Control (RRC).

TABLE 1 NETWORK

 1 FUNCTION CONFIGURATION FOR DIFFERENT SLICES

Slice 1 (automotive, eMBB): Entertainment on Board Slice 2 (automotive, URLLC): Assisted driving and safety Slice 3 (mMTC): Road sensors Slice 4 (public, eMBB): Smartphones for pedestrians Communication mode

	UE to Base Station (BS) communi-	Vehicle to Vehicle (V2V) and	UE to BS communications	UE to BS communi-
	cations (uplink and downlink)	Vehicle to Infrastructure (V2I),	(uplink)	cations (uplink and
		exploiting the Device to Device		downlink)
		(D2D) communications concepts.

TABLE 2 RESOURCE

 2 ALLOCATION PRINCIPLES FOR URLLC SLICES AND THEIR INTERACTIONS WITH THE EMBB SLICE. DETAILED USE CASE DESCRIPTIONS