72 pt 1 in 25.4 mm 54 pt 0.75 in 19.1 mm 54 pt 0.75 in 19.1 mm 54 pt 0.

I. INTRODUCTION

Type I diabetes is a chronic disease of increasing incidence [START_REF] Dabelea | The accelerating epidemic of childhood diabetes[END_REF] with loss of pancreatic -cells, that normally produce and secrete insulin in response to nutrients such as glucose. Therapy implies determination of blood glucose levels and corresponding injections of the potent hormone insulin. More recently transplantation of islets has been established in the case of severe and difficult to control type I diabetes. Considerable hope is placed in differentiation of stem cells though successful protocols are still not available [START_REF] Belmonte | Induced pluripotent stem cells and reprogramming: seeing the science through the hype[END_REF].

The introduction of electrochemical glucose sensors has presented a major breakthrough in diabetes therapy [START_REF] Battelino | The use and efficacy of continuous glucose monitoring in type 1 diabetes treated with insulin pump therapy: a randomised controlled trial[END_REF]. The continuous monitoring of glucose levels and injection of the corresponding amounts of insulin thus became feasible. However, this approach captures only part of the information the organism uses for physiological regulation of *Research supported by the ANR EMERGENCE "HY-BIOPACS" and funds from the Aquitaine Regional Government/FEDER to SR and JL.

Authors Q.V.N., A.Q., J.B.F., Y.B. and S.R. are with the University of Bordeaux 1, UMR CNRS 5218, Talence, FR-33405, France; authors A.C., M.R. and J.L. are with the University of Bordeaux 1, UMR CNRS 5248, Pessac, FR-33600, France (corresponding author phone: 0+33 633 755776; e-mail: j.lang@cbmn.u-bordeaux.fr).

homeostasis. Within the body a group of specialized cells, the so-called -, -and -cells, are arranged in a micro-organ to sense the nutrient levels and demand in the hormone insulin. Biological sensors, such as pancreatic islets, have been shaped during half a billion years of evolution and in contrast to currently available medical devices, they rely on a number of different relevant signals, not only glucose but also several hormones and nutrients other than glucose [START_REF] Macdonald | Glucose-sensing mechanisms in pancreatic beta-cells[END_REF].

The integration of information about the presence of these molecules by pancreatic -cells subsequently provides a precisely tuned signal to regulate cellular actions, such as the release of the potent hormone insulin into the bloodstream. Islet cells, including -cells, are excitable cells similar as nerve cells. They relate signals by changing their electrical properties and this represents the first signal integration step in these cells. Therefore the electrical properties relate precisely the information obtained through different signals and reflects the activity of these cells and the demand of the body for insulin [START_REF] Rorsman | Regulation of Insulin Secretion in Human Pancreatic Islets[END_REF]. Electrical signals can be captured by extracellular electrodes and the corresponding devices are easy to miniaturize and do not produce heat, considerations that are important in the case of implantation [START_REF] Raoux | Bioelectronic Sensing of Insulin Demand[END_REF].

A device extracting information on the activity of betacells may serve as a novel sensor for the demand in insulin and regulate an insulin infusion pump in patients suffering from type 1 diabetes. Such a device may also bypass the shortcoming of currently used sensors, i.e. their incapacity to work in a closed-loop configuration and the ensuing requirement of complex algorithms and user interventions [START_REF] Hovorka | Closed-loop insulin delivery: from bench to clinical practice[END_REF]. Moreover, we propose that such a device may also serve rapidly to monitor the activity of islet-cells prior to their transplantation, in the field of tissue engineering to follow the differentiation of stem-cells into islet cells in a nondestructive manner or to be used in drug screening.

We have previously shown the general feasibility of this approach that is capturing the electrical signals by the use of extracellular electrodes and extracting the relevant information on-line which reflects the ambient levels of glucose and hormones [START_REF] Bornat | Detection of electrical activity of pancreatic -cells using micro-electrode arrays[END_REF][START_REF] Raoux | Non-invasive long-term and real-time analysis of endocrine cells on micro-electrode arrays[END_REF]. However, the electrical signals are of small amplitude and have a low signal-to-noise ratio. Thus information extracted from a single processing algorithm presents a limited reliability. The use of the device beyond research and in a medical setting requires high reliability in the characterization process to ensure the patient security. We propose here an enhanced process based on the parallel processing of the electrical signals in two different frequency bands.

II. EXPERIMENTAL

A. Cell culture

All experimental procedures reported here were in accordance with Bordeaux University policies governing the ethical use of mice for experimentation and the French Ministry of Agriculture and Forestry concerning animal care. Twelve-week-old mice were killed by cervical dislocation and their pancreata were removed and digested with collagenase NB 8 (1.1 PZ-U/ml, Serva Electrophoresis, Heidelberg, Germany). Pancreatic islets were then isolated from exocrine cells by hand-picking under a stereomicroscope (Stemi 2000, Zeiss, Thornwood, NY) and shortly trypsinised (Invitrogen, Carlsbad, CA). Cells from 80-150 islets were then seeded on the centre microelectrode arrays (60MEA200/30iR-Ti-gr, Multichannel Systems, Reuttlingen, Germany) containing 60 circular and planar electrodes in titanium nitride (30 µm diameter. To optimize the attachment of the cells, multielectrode array (MEA) surfaces were treated before seeding with a plasma air and coated for 1-2h with 50-fold diluted Matrigel (growth factor reduced, BD Biosciences, San Diego, CA, USA). After 2 days of culture in 11 mM of glucose, extracellular recordings with MEAs were performed at 37°C in a continuously perifused (0.5-1 ml/min) physiological buffer consisting of (in mM): NaCl 135, KCl 4.8, MgCl2 1.2, CaCl2 1.2, Hepes 10, and glucose 5.5, 8.2, 11 and 15 (pH 7.4 adjusted with NaOH). Each glucose concentration was applied for 20 min.

B. Data acquisition and processing

During the whole experiment, electrical activities generated on each electrode were continuously amplified (gain: 1100) and analogically filtered at 0.1-3000 Hz with a MEA1060-Inv-BC-Standard system (Multichannel Systems). Analog signals were sampled at 10 kHz/12bits with MC_Rack acquisition hardware and software (Multichannel Systems) and stored on a personal computer for further analysis. -for AP-based processing, the amplified raw signal is filtered using a wavelet filter to facilitate AP detection [START_REF] Quotb | Wavelet transform for real-time detection of action potentials in neural signals[END_REF][START_REF] Quotb | NeuroBetaMed: A reconfigurable wavelet-based event detection circuit for in vitro biological signals[END_REF].

We use Stationary Wavelet Transform (SWT), with a Haar mother wavelet; APs detection through an adaptive threshold, which is continuously updated and equals 2x ( is the standard deviation), is performed on the 6 th level of wavelet decomposition. The detection is implemented with negative peaks of the AP signals. A resting period T of a minimum of 5ms and a maximum of 0.5s has to be respected between two spikes (see Fig. 2B). We subsequently compute the APs average frequency as a measure of the global activity, and the AP plateau fraction (ratio active phase/ burst period as defined in the Fig. 2B), as the fraction of time when APs occur in a burst. Indeed, it is well known that trains of rapid oscillations are interspersed by periods of silence, thus creating burst patterns. For this application, we have defined as bursts the presence of at least two directly consecutive spikes.

-for SW-based processing, the amplified raw signal is extracted by using a low-pass Butterworth filter (order of 2) with a cut-off frequency of 1 Hz. Next the following parameters are processed: frequency and amplitude of the slow oscillations. SW frequency is defined by the time between two consecutive positive peaks, while amplitude is the difference between maximum and minimum peak values during the downward phase of one oscillation.

III. RESULTS

Primary -cells were cultured on micro-electrode arrays (MEAs) which allow to measure changes in field potentials due to changes in ion fluxes near or at the cell membrane (see Fig. 1A andB). Perifusion of these cells with low glucose (5.5 mM), a concentration that mimics normoglycemia, did not provoke any changes in the electrical signal (Fig. 1 C). However, when glucose was increased to higher levels, i.e. 11 mM, a concentration mimicking hyperglycemia, two distinct electrical phenomena were observed. First, large oscillations of low frequency appeared with an amplitude of 100 to 150 µV. Second, on top of these slow oscillations we observed rapid, short-lived oscillations of much smaller amplitude (10 to 30 µV; see Fig. 1C). These rapid spikes correspond to action potentials which we had demonstrated previously and described in detail their on-line analysis in real time [START_REF] Raoux | Non-invasive long-term and real-time analysis of endocrine cells on micro-electrode arrays[END_REF].

As glucose alters the physiological activity of -cells, we have cultured these cells on MEAs and superfused them with glucose containing buffers (Fig. 3A). Starting at 3mM glucose, a concentration mimicking hypoglycemia, we gradually increased the level of the sugar every 20 minutes first to 5.5 (normoglycemia) and to hyperglycemic values (8.2, 11 and 15 mM). Subsequently glucose levels were reduced stepwise to 11, 8.2, 5.5 and finally 3 mM. First, neither slow nor rapid oscillations were observed at 3 or 5.5 mM glucose (Fig. 3 B andC, left panels). Second, we observed a very steep increase in frequencies between 5.5, 8.2 and 11 mM glucose and a less pronounced one between 11 and 15 mM glucose. In contrast, the amplitude of slow waves represented an all or none response with a cut-off between 5.5 and 8.2 mM of the sugar reflecting the absence or presence of oscillations (Fig. 3B, right panel). Similar to the changes in frequencies, the plateau phase for rapid oscillations increased in parallel to increases in glucose levels (Fig. 3C, right panel). Decreasing the glucose concentration was well reflected by a decrease in frequencies for both, rapid and slow oscillations. In contrast, there was some delay in the decrease when measuring the plateau fraction.

IV. DISCUSSION

Our previous work [START_REF] Raoux | Bioelectronic Sensing of Insulin Demand[END_REF][START_REF] Bornat | Detection of electrical activity of pancreatic -cells using micro-electrode arrays[END_REF][START_REF] Raoux | Non-invasive long-term and real-time analysis of endocrine cells on micro-electrode arrays[END_REF] and the current report clearly demonstrate the usefulness of pancreatic -cells as biosensors using microelectrodes and recording of their electrical activity. As this approach has initially been pioneered for the use on neurons and heart muscle cells, which express large action potentials, the application to endocrine cells could not have been taken for granted.

We present now a data processing flow based on signal separation in two distinct frequency bands. Simple frequency and amplitude features are extracted in each band, and testify for changes in glucose concentrations. The aim of the parallel processing is to reinforce the result confidence, as the signal in each band is potentially biased by the intrinsic biological We have therefore designed a dedicated recording and processing board (see Fig. 4) with an FPGA from Xilinx TM (Spartan 3E XC3S500E) as computational core. Using this system, we have demonstrated on-line and real-time wavelet filtering and AP detection on 60 parallel channels [START_REF] Raoux | Bioelectronic Sensing of Insulin Demand[END_REF][START_REF] Bornat | Detection of electrical activity of pancreatic -cells using micro-electrode arrays[END_REF][START_REF] Raoux | Non-invasive long-term and real-time analysis of endocrine cells on micro-electrode arrays[END_REF]. Those functions were identified to have the maximum computational cost in the data processing flow given in Fig. 2A. We are now in the process of embedding the remaining functions, i.e. mainly SW processing, on the FPGA.

Our observation on the glucose-dependency of slow and rapid oscillations reveals two important points. First, signals were absent in at glucose concentrations below 8.2. Note that this is in line with observations on insulin secretion in rodents and man, were the cut-off was at about 6 mM, a concentration not tested here [START_REF] Henquin | Nutrient control of insulin secretion in isolated normal human islets[END_REF]. Second, we observed rapid reduction in activity upon reduction of glucose concentration. These properties document that culture on electrodes does not impair the physiology of the biological substrate, the islets. Moreover, these characteristics will facilitate the use as a biosensor as a steep increase in activity was only observed in the physiological relevant range of glucose concentrations. Note that concentrations such as 15 mM or even higher are often used in-vitro but do not occur in live animals or man [START_REF] Rorsman | Regulation of Insulin Secretion in Human Pancreatic Islets[END_REF]. The fact that electrical activity increases only modestly between 11 and 15 mM (as compared to the difference between 8.2 and 11 mM) is therefore not a disadvantage.

As insulin is a very potent hormone and overdosage may induce life-threatening hypoglycemia, the rapid reduction in electrical activity when reducing glucose is of considerable importance. In fact, our data suggest that the classical approach using the plateau fraction may not be the best parameter to regulate insulin delivery, for example by a pump as the return is slower. Moreover, it is much straighter forward to extract frequencies of slow and rapid oscillations than to calculate plateau fractions over an extended time period. The encoding of glucose concentration by frequency shall therefore favor implementation of online real-time data treatment.

Interestingly the amplitude of the slow oscillations did not change once this signal appeared. Use of this all-or-non signal may enhance security and help to avoid hypoglycemia. In the same vein it may serve as internal control for sensor activity as it was the only stable parameter between 8.2 and 15 mM glucose.

V. CONCLUSION

We have observed and extracted two different electrical signals that depend on glucose concentration in pancreatic cells. This shall permit us the construct a valuable algorithm for the regulation of an insulin-delivering pump in the treatment of type I diabetes. A demonstration of the first steps of this algorithm is presented here using off-line computation. An electronic device is under construction, based on an embedded FPGA capable of processing multiple channels in parallel. This device shall be used as a portable and real-time biosensor to regulate insulin delivery from a pump.

Fig. 1 :

 1 Fig. 1: Extracellular recording of electrical signals from mouse islet cells cultured on multi-electrode arrays (MEA). A, Scheme of electrical signals generated by the activity of ion channels in a β-cell cultured on a microelectrode connected to an amplifier. B, 2-days-old culture of mouse islet cells growing on the MEA titanium nitride electrodes (planar, 30 µm diameter; scale bar: 100 µm). C, representative electrophysiological recordings obtained from one electrode of the MEA in B. The null-voltage is indicated by horizontal broken lines. At low glucose concentration (5.5 mM, G5.5) electrical oscillations are absent (left), whereas a concentration mimicking hyperglycaemia (11 mM, G11) induced low frequency oscillations (right, upper trace) on which rapid signals (action potentials) are grafted as can be seen at higher temporal resolution (see arrows at right, lower trace).

Fig. 2 .

 2 Fig. 2. Processing of signals from pancreatic ß-cells . A: Data processing flow for analysis of slow and rapid oscillations. B: Example of rapid oscillations signal and related burst features after pre-amplification (1100x): burst period is the time elapsed between 2 active phases, where an active phase corresponds to at least 2 spikes separated by T (T is in [5ms; 500ms].

For

  the results presented in this paper, we used Matlab software to compute data. As illustrated in figure 2A, two components of the signals are processed in parallel: rapid oscillations or action potential-like signals (APs) which are of relatively high frequency (>3Hz); slow oscillations or slow waves (SW) that are of low frequency and higher amplitude (100 µV). Both signals are modulated by glucose and hormones but APs are generated by single cells whereas SWs are generated by intercellular coupling. Thus SWs provide important and very robust signal with an excellent signal/noise ration. We have therefore attempted to fully exploit these signals as depicted in Fig. 2A for the data processing flow: -signals at the output of the MC_Rack are 12-bit signed numbers, covering the signal range [-200 µV; 200 µV ], sampled at 10kHz. the other pages Paper size this page US Letter

Fig. 3 .

 3 Fig. 3. Slow and rapid oscillations of field potentials in primary islet cells reflect changes in ambient glucose concentrations. A: Scheme of experiments. Islet cells cultured on multi-electrode arrays were perifused first with increasing and subsequently with decreasing glucose concentrations (each step lasted 20 min). B: Results for amplitude and frequency of slow oscillations. C: Results for frequency and plateau fraction of rapid oscillations (action potentials). N=7; **, p<0.02, ***, p<0.01 (Tukey post-hoc test).

  the other pages Paper size this page US Letter heterogeneity of the preparation. Although analyses presented in this paper were conducted off-line, processing functions were specified and dimensioned for future on-chip embedding for on-line processing of multiple signals from a single MEA.

Fig. 4 :

 4 Fig.4: Recording and processing board with an FPGA. Connector on the right is wired for recordings to the MEA and its preamplifier. Raw and processed data are stored on SDRAM cards. Analysis outputs are available on a USB port for display or post-processing.

A novel bioelectronic glucose sensor to process distinct electrical activities of pancreatic beta-cells *

  Quang Vinh Nguyen, Anton Caro, Matthieu Raoux, Adam Quotb, Jean-Baptiste Floderer, Yannick Bornat, Sylvie Renaud, Member, IEEE, and Jochen Lang, Member, IEEE

	Margin requirements for the other pages	54 pt
	Paper size this page US Letter	0.75 in
		19.1 mm
	54 pt	54 pt
	0.75 in	0.75 in
	19.1 mm	19.1 mm
		54 pt
		0.75 in
		19.1 mm

ACKNOWLEDGMENT

We thank J. Gaitan for excellent technical support.


Myline Cottance

Sebastien Nazeer

Gaelle L Rousseau

Bazin Lissorgues

Sébastien Joucla

Blaise Yvert

Noëlle Lewis

Yannick Bornat

S Renaud

G Lissorgues
email: g.lissorgues@esiee.fr

Challenges in recording and stimulation of living neural network based on original micro-electrode array (MEA) developments

INTRODUCTION Emerging technologies in Bioelectronics can provide several fundamental and applied developments in medicine and

For instance extra cellular electrical recording of the central nervous system (CNS) has been used for decades by electro-physiologists to explore fundamental properties of neural networks.

Recent advances in micro and nano technology have opened the way to probe neuronal activity over large populations of neurons thanks to the fabrication of Micro Electrode Arrays (MEAs). Indeed, Micro Electrode Arrays (MEAs) are well suited for the stimulation and recording of neural cells as they correspond to a non-invasive technique allowing long-term stimulation and recording of bio-electrical signals of cultured cells and tissues [START_REF] Morin | Investigating Neural Activity with Planar Microelectrode Arrays: Achievements and New Perspectives[END_REF]. In clinical an therapeutic research, such electrical stimulation of the CNS can be used in the field of neuro-prostheses to try to restore sensory or motor functions like in retinal [START_REF] Meyer | Retina implant -a bioMEMS challenge[END_REF][START_REF] Margalit | Retinal prosthesis for the blind[END_REF], cochlear [START_REF] Wilson | Cochlear implants: Current designs and future possibilities[END_REF] implants or in functional rehabilitation of upper and lower limb [START_REF] Grabow | Spinal Cord Stimulation for Complex Regional Pain Syndrome: An evidence-based Medicine Review of the literature[END_REF], in deep brain stimulation used in case of Parkinson disease [START_REF] Voon | Deep Brain Stimulation: Neuropsychological and Neuropsychiatric Issues[END_REF]. In fundamental research, MEAs are now widely used as a tool to investigate neuronal networks to highlight their organization, connectivity, distribution and interactions between cells. This paper will be divided in two main parts: i) the description of the operation principle of a MEA and its corresponding standard micro-manufacturing, ii) the description of several solutions to improve the action potential (AP) discrimination, which remains an important challenge in neuroscience applications.

II. MEA OPERATION PRINCIPLE AND STANDARD MICRO-

MANUFACTURING

Multi-electrode arrays have been commonly used as a noninvasive in-vitro recording tool to study excitable cells and tissues, such as neurons. A typical MEA system includes four parts which are the following. First the MEA chip itself with its petri dish is used as a substrate to culture neuron cells and detect their electrical activity (spontaneous or stimulationinduced signals). Second, an amplifier circuit is required to filter and amplify the measured signals. Third, a specific stimulating circuit must be defined to apply either voltage or current impulses on specific electrodes to stimulate the cells located on top of them. Fourth, dedicated software is usually used to collect, store and analyze the acquired neural signals.

MEAs can be manufactured using micro-technology. The standard or classical manufacturing process consists in patterning metallic micro-electrodes with their leads using a lift-off method, on either a glass or an oxidized silicon wafer. For this purpose, the wafer is spin-coated with 2 µm of NLOF 2020 (Clariant) photoresist, which is further removed at specific locations by photolithography to define the geometry of the metal layer (electrodes and tracks). In case of platinum MEAs, a first layer of 50 nm of titanium and a second layer of 150 nm of platinum are sputter-deposited over the whole wafer. The wafer is then placed in an ultrasonic bath with a dedicated remover AZ400, leaving only the metal layer deposited directly at the proper location. Then an insulation layer of silicon nitride (Si3N4) is deposited by PECVD (Plasma Enhanced Chemical Vapor Deposition) and further etched at the location of the electrodes, defining the electrode effective sizes. Si3N4 is etched using a SF 6 plasma at locations not protected by the photoresist (i.e., electrodes). Finally, the wafer is cleaned and cut to separate the MEA chips and an annular glass ring is glued with poly-dimethoxy siloxane (PDMS) to constitute a recording chamber around the electrodes called the Petri dish.

The generic structure of the MEA chip is presented on Figure 1, and the corresponding standard fabrication process is shown on Figure 2. The case of 3D electrodes will be described in the next section.

A) High density MEAs and Multi-level recording

One main interest of MEAs is to probe neuronal extracellular electrical activity at several sites simultaneously. In order to improve the localization of the potential fields recorded, it is necessary to increase the number of electrodes, leading to high density MEAs.

To reach this goal, one elegant solution is to define microelectrodes shaped as 3D needles instead of planar electrodes, at the tip of which is the recording site. The 3D shape will allow getting a very close contact to the cells [START_REF] Heuschkel | A three-dimensional multi-electrode array for multi-site stimulation and recording in acute brain slices[END_REF].

In term of manufacturing constraints, the isotropic etching is classically used to etch silicon or glass substrates to process 3D electrodes, either with wet (KOH) or dry (plasma) etching. But isotropic etching limits the electrode pitch regarding its height, preventing the fabrication of dense 3D electrode arrays with high aspect ratios. For example, a 3D electrode of 80 µm height requires a minimum of 160 µm pitch. Therefore, we developed MEAs with 64 (4x16), 256 (8x32) up to 1024 (22x47) recording sites using the Deep Reactive Ion etching (DRIE) technique with no limitations in height and diameter, as shown on Figure 3. Fabricated 3D electrodes of the MEA256 are micro-needles of 80µm in height, 250µm of pitch and lead tracks of 10 µm in width.

Biological tests have been done to record activity from a whole embryonic mouse hindbrain-spinal cord, as illustrated on Figure 4. As expected, increasing the number of recording sites allows new imagery of cellular information, with better discrimination of the involved neural cells, as on Figure 5. Indeed, we observe a loss of information in the case of 64 electrodes considered out of 256, missing a local response of the neural network (white arrow on the figure). Such images are obtained with specific signal processing for spatiotemporal mapping. Another solution to improve action potential discrimination is to increase the number of recording sites vertically in the depth of the tissues. Therefore we developed a new MEA chip as 32 shafts with 8 recording sites on each shaft, with a pitch of 50 µm. The technological process required to defined the shafts is then more complex due to a double side photolithography step followed by 2 DRIE steps (top and bottom), Figure 6.

B) Dedicated signal processing

An alternative strategy to improve action potential (AP) discrimination is to work on signal processing. Indeed, a solution for real-time AP detection is to implement a waveletbased pre-processor which emphasizes AP shapes and attenuates out-of-band noise [START_REF] Quotb | Wavelet transform for realtime detection of action potentials in neural signals[END_REF]. The output of this preprocessor is used to compute an adaptive threshold and detect APs. The preprocessing algorithm is the Stationary Wavelet Transform (SWT), as wavelet filtering is performing in terms of compression and time-frequency localization for feature extraction. SWT algorithm has to be configured to ensure performing AP detection on the considered signal: the mother wavelet is closely related to the AP shape, the wavelet detail level is in accordance with the AP time frequency domain. on the SWT first level detail output (black) C) Detected APs as digital output of the system.

C) Focal stimulation

In case of high density MEAs, one major problem is to avoid cross-talk between two or more electrodes in the stimulation mode.

One way to improve the focality is to force the stimulation current to flow back through a position close to the stimulating electrode. In the literature multipolar electrode configurations are generally considered [START_REF] Houweling | Behavioural report of single neuron stimulation in somatosensory cortex[END_REF][START_REF] Holsheimer | Optimum electrode geometry for spinal cord stimulation: the narrow bipole and tripole[END_REF].

Hence we proposed and patented an alternative solution being to use a ground surface laying on the substrate of the MEA and surrounding all electrodes [START_REF] Joucla | Improved Focalization of Electrical Microstimulation Using Microelectrode Arrays: A Modeling Study[END_REF]. In that case, no additional external ground electrode is needed, since the whole current delivered by the stimulation electrode returns back through the ground surface. We observe on Figure 9 that, compared with the classical monopolar configuration, a better focality can be achieved with this configuration. Using a bipolar stimulation signal of -/+ 2µA during 1 ms shows that the presence of the ground grid has divided the potential field by a factor of 2. Moreover, the potential field focality is more important when the surface conductance of the ground surface is high.

Figure1.

  Figure1. Generic structure of the MEA chip

Figure 3 .

 3 Figure 3. An example of a 256 Electrode array (MEA256) with 3D electrodes.

Figure 5 .

 5 Figure 5. High density MEA for better discrimination.

Figure 6 .Figure 7 .

 67 Figure 6. Principle of multi-level MEA ; fabricated chips In both cases, either horizontal or vertical high density MEAs, the noise level depends on the electrode surface, as measured on Figure 7. The best available solution consists in increasing the effective electrode area while maintaining the diameter of electrode constant, which is possible with new materials like black platinum, titanium nitride or Iridium

Figure 8 .

 8 Figure 8. Example of wavelet based AP detection : A) original signal recorded from excitable cells cultured on commercial MEAs after filtering and digital conversion, B) SWT Sixth level detail output (grey) with threshold computed

Figure 9 .

 9 Figure 9. Ground grid focality improvement.

ACKNOWLEDGMENT

The authors would like to thank the French National Research Agency for their financial support through the ANR Blanc project HYRENE.


Jean-François Ponge
email: ponge@mnhn.fr

Giacomo Sartori

Adriano Garlato

Fabrizio Ungaro

Augusto Zanella

Bernard Jabiol

Silvia Obber

The impact of parent material, climate, soil type and vegetation on Venetian forest humus forms: a direct gradient approach

Keywords: Veneto, humus forms, mull, moder, amphi, aggregate size

The impact of geology, climate, soil type and vegetation on forest humus forms was studied in the Veneto Region (northern Italy). A total of 352 study sites were compared by Redundance Analysis (RDA). Humus forms were described by the structure (micro-, meso-, or macro-aggregated) of the organo-mineral A horizon, by the thickness of litter horizons and by their nomenclature, which followed the morpho-functional classification recently proposed for inclusion in the WRB-FAO. The size of aggregates within the A horizon was distributed along a common gradient embracing geology,

Introduction

Following the United Nations Framework Convention on Climate Change (UNFCCC, 1992), there is an urgent need to characterize organic carbon pools both quantitatively and qualitatively worldwide, in order to (i) optimize models of global climate warming [START_REF] Bottner | Soil organic matter in Mediterranean-type ecosystems and global climate changes: a case study, the soils of the Mediterranean Basin[END_REF][START_REF] Marland | The climatic impacts of land surface change and carbon management, and the implications for climate-change mitigation policy[END_REF][START_REF] Thum | Soil carbon model alternatives for ECHAM5/JSBACH climate model: evaluation and impacts on global carbon cycle estimates[END_REF], and (ii) discern trends in C turnover/sequestering and nutrient availability/retention at ecosystem level (De Deyn et al., 2008;[START_REF] Zhang | Rates of litter decomposition in terrestrial ecosystems: global patterns and controlling factors[END_REF]Egli et al., 2010). Some countries, such as the Netherlands, implemented soil organic carbon (SOC) inventories, based on forest standing crops [START_REF] Nabuurs | Carbon in Dutch forest ecosystems[END_REF] and agricultural soil maps [START_REF] Kuikman | Stocks of C in Soils and Emissions of CO 2 from Agricultural Soils in the Netherlands[END_REF]. However, in forests soils carbon stocks vary to a great extent according to the development of organic layers [START_REF] Schulp | Effect of tree species on carbon stocks in forest floor and mineral soil and implications for soil carbon inventories[END_REF][START_REF] Andreetta | Forest humus forms as potential indicators of soil carbon storage in Mediterranean environments[END_REF][START_REF] Bonifacio | Humus forms, organic matter stocks and carbon fractions in forest soils of northwestern Italy[END_REF], although more stable C stocks in the mineral horizons should not be neglected (Garlato et al., 2009;[START_REF] Rumpel | Deep soil organic matter: a key but poorly understood component of terrestrial C cycle[END_REF]. Humus forms, patterning the way organic matter is distributed and transformed within the forest soil profile [START_REF] Bal | Morphological investigation in two moder-humus profiles and the role of the soil fauna in their genesis[END_REF][START_REF] Klinka | Relationships among humus forms, forest floor nutrient properties, and understory vegetation[END_REF][START_REF] Kindel | Humus form in ecosystems of the Atlantic Forest, Brazil[END_REF], and known as key components of plant-soil relationships [START_REF] Ponge | Humus forms in terrestrial ecosystems: a framework to biodiversity[END_REF][START_REF] Ponge | Plant-soil feedbacks mediated by humus forms: a review[END_REF], are easy to identify directly on the field without expensive laboratory analyses. They also could be mapped with the aid of digital mapping techniques [START_REF] Aberegg | Modelling spatial distribution of soil types and characteristics in a high Alpine valley (Val di Sole, Italy)[END_REF], taking into account their local variability by standardized protocols [START_REF] Ponge | Humus Index: an integrated tool for the assessment of forest floor and topsoil properties[END_REF][START_REF] Lalanne | Opposite responses of vascular plant and moss communities to changes in humus form, as expressed by the Humus Index[END_REF]. The systematic census of humus forms could allow in a near future a clearer assessment of the amount and distribution of fast-recycling (organic horizons) and stable (organo-mineral horizons) carbon at scales varying from local to regional then to global levels [START_REF] Thornley | Soil carbon storage response to temperature: an hypothesis[END_REF][START_REF] Hedde | Dynamics of soil carbon in a beechwood chronosequences forest[END_REF][START_REF] Andreetta | Forest humus forms as potential indicators of soil carbon storage in Mediterranean environments[END_REF]. In parallel, searching proxies for humus forms in geology, climate, soils and vegetation, mapped for a long time or easily accessible by remote sensing, and known as main determinants of forest soil conditions [START_REF] Aberegg | Modelling spatial distribution of soil types and characteristics in a high Alpine valley (Val di Sole, Italy)[END_REF](Egli et al., , 2010;;[START_REF] Li | Soil organic carbon stock is closely related to aboveground vegetation properties in cold-temperate mountainous forests[END_REF], would help to achieve this goal even more rapidly.

A recent study by [START_REF] Ponge | Geology and climate conditions affect more humus forms than forest canopies at large scale in temperate forests[END_REF] showed that at national level (France) forest humus forms were mainly 'explained' (in statistical sense) by geology and climate. Tree canopies (coniferous vs deciduous) exhibit only a minor additive influence. The present study was undertaken in the mountain and hilly part of the Veneto Region (northern Italy), embracing a wide array of climate and geologic conditions on a relatively small area (6,000 km 2 ) owing to its particular position on the southeastern side of the Alps arch and on the northern border of the Adriatic Sea (Del Favero and Lasen, 1993). The aim was to assess whether the influence of (i) components of climate (temperature, precipitation), elevation, aspect, soil type and substrate (carbonated versus silicated parent materials), known to affect forest humus forms in other North Italian contexts (Carletti et al., 2009;[START_REF] Bonifacio | Humus forms, organic matter stocks and carbon fractions in forest soils of northwestern Italy[END_REF][START_REF] Ascher | Are humus forms, mesofauna and microflora in subalpine forest soils sensitive to thermal conditions ?[END_REF], and (ii) vegetation, whose effects have been well-established at a very local level [START_REF] Schulp | Effect of tree species on carbon stocks in forest floor and mineral soil and implications for soil carbon inventories[END_REF][START_REF] Trap | Changes in humus forms and soil N pathways along a 130-year-old pure beech forest chronosequence[END_REF][START_REF] Trap | PLS-regressions highlight litter quality as the major predictor of humus form shift along forest maturation[END_REF], could be retrieved in the regional context of Veneto. For that purpose we used for the first time a new classification of humus forms, based on morpho-functional principles previously defined at European level by [START_REF] Zanella | A European morpho-functional classification of humus forms[END_REF], then refined by [START_REF] Jabiol | A proposal for including humus forms in the World Reference Base for Soil Resources (WRB-FAO)[END_REF] in the frame of the World Reference Base for Soil Resources (IUSS Working Group WRB, 2007.

Materials and methods

Climate, geology and distribution of forest and soil types in Veneto

Veneto is an Alpine Italian Region, displaying an altitudinal gradient from the Mediterranean Sea (Gulf of Venice) up to the summits of the eastern Alps (Carnic Alps, Austrian boundary) (Fig. 1).

Four climatic districts have been described by Del Favero and Lasen (1993).

The Avanalpic climatic district (numbered 1 in Fig. 1) concerns the lowland area between the Mediterranean Sea and the Alpine reliefs. The area is comprised of the wide Veneto plain and a hilly zone at the piedmont of the Alps, with a climatic gradient between them. On the whole, the Mediterranean district is characterized by a mean annual precipitation of 900-950 mm with a maximum in spring, and a mean annual temperature of 12-13°C with July as the warmest month but without any arid summer season. Ericaceous species and sweet chestnut (Castanea sativa Mill.) are common on silicated substrates or on acid soils as opposed to oak (often downy oak, Quercus pubescens Willd.), hornbeam (often hop hornbeam, Ostrya carpinifolia Scop.) and ash (often Manna ash, Fraxinus ornus L.), which grow preferably on carbonated substrates. Remains of the natural oakhornbeam forest which covered the Po plain between 6000 BC and a few centuries ago [START_REF] Susmel | I rovereti di pianura della Szerenissima[END_REF], are nowadays managed as hedgerows in a mechanized agricultural landscape or as small private woods.

The Esalpic district is characterized by Mediterranean-type temperatures but mean annual precipitation is higher (ca. 1500 mm) owing to wet-warm air coming from the sea and raising on prealpine reliefs (Fig. 1). Carbonated substrates (calcareous and dolomitic), largely dominant, are favourable to the development of pure or mixed forests of hop hornbeam, with Manna ash, downy oak, field maple (Acer campestre L.), which occupy about one third of the forest area in Veneto (Del Favero, 2010). Above 800 m altitude, hop hornbeam is replaced by common beech (Fagus sylvatica L.) in thermophile beech forests which constitute the second most important element of forest vegetation.

The more internal Mesalpic district is characterized by a high mean annual precipitation (ca. 1400 mm, snowfall included), which is mostly distributed from April to November. Temperatures are much lower than in the Esalpic district, averaging 7-8 °C. The whole district is covered with mountain beech forests, pure or mixed with Norway spruce [Picea abies (L.) Karst.] and silver fir (Abies alba Mill.), and by mixed spruce-fir forests. The composition of these forests varies according to substrate (95 % carbonated), slope and exposure.

The Endalpic climatic district corresponds to the highest part of the region. The mean annual precipitation is lower than in Mesalpic and Esalpic districts (ca. 1000 mm) and is distributed according to a continental regime with a single peak in July. Mean annual temperature is 5 °C, being too cold for many broadleaved tree species. Above 1500 m altitude, Swiss pine (Pinus cembra L.) is common, while Norway spruce and European larch (Larix decidua Mill.) grow at the same altitude but also lower, often favoured by human activities (pasture or forest management). Spruce forests cover silicated substrates in the high north-eastern part of the district.

In short, there is a gradient of decreasing temperature from the Mediterranean Sea (Avanalpic district) to the higher Carnic Alps (Endalpic district), while precipitation is distributed in a humped back fashion (Fig. 1), maximum precipitation occurring at mid elevation (Esalpic and Mesalpic districts).

Geologically, the study area can be divided, from North to South, into Alpine, Prealpine and Hilly areas. The Alpine sector displays a remarkable lithological variability, from metamorphic acid rocks of the crystalline basement of the Dolomites to the overlying stratigraphic succession (mainly calcareous, dolomitic and terrigenous rocks). In the Prealpine area limestone and marly limestone are common, but in the eastern part basalts of Tertiary volcanism are widespread, while the area of Recoaro and the Piccole Dolomiti (Small Dolomites), due to particular tectonic conditions, show a Permo-Triassic stratigraphic succession, similar to Dolomite reliefs. The Hilly Area is characterized by extremely heterogeneous geological substrates, ranging from limestone of the Berici to volcanic rocks of the Euganean hills with a prevalence of carbonated substrates [START_REF] Antonelli | Carta geologica del Veneto, scala 1:250,000: una storia di cinquecento milioni di anni fa. Regione del Veneto[END_REF].

Lithological variability results in prominent soil heterogeneity [START_REF] Antonelli | Carta geologica del Veneto, scala 1:250,000: una storia di cinquecento milioni di anni fa. Regione del Veneto[END_REF] in mountain areas. On carbonated rocks, shallow soils with a high content in skeleton and a low differentiation of profiles, classified by the World Reference Base (IUSS Working Group WRB, 2007) as Rendzic Leptosols, prevail besides deeper and moderately developed soils with cambic (Bw) horizons (Endoleptic Cambisols [Calcaric, Skeletic]). On silicated rocks with cold climate and high altitude the podzolization process is dominant (Podzols). At lower altitude this process is less intense with translocation of iron and aluminium sesquioxides (Bs horizons) but not of organic matter (Haplic Cambisols [Dystric]).On marly limestone, especially in the Prealpine area, well-differentiated and deep soils free of carbonates dominate even on very steep slopes, with a horizon of clay accumulation (Cutanic Luvisols). In the Hilly Area sandy and marly lithotypes are associated with moderately deep soils, partially decarbonated (Haplic Cambisols [Eutric] and [Calcaric]). In Euganean hills acid soils are prevalent (Haplic Cambisols [Dystric]).

Selection, description and classification of humus profiles

Study sites (N = 348) were selected in order to embrace the widest possible variety of geological, climate, soil and vegetation conditions found in forests of the Veneto region, in the framework of the Soil Map of Veneto Region at 1:250,000 scale (ARPAV, 2005). Humus profiles were described according to the thickness of OL (not retained for data analysis due to strong seasonal variations), OF and OH organic horizons (litter s. l.) and to the structure of the A horizon: organomineral aggregates were classified in macro-(> 4 mm), meso-(2-4 mm), and micro-(< 2 mm) aggregates [START_REF] Zanella | A European morpho-functional classification of humus forms[END_REF]. Humus profiles were then assigned to humus forms according to [START_REF] Zanella | A European morpho-functional classification of humus forms[END_REF]. Table 1 summarizes main features useful for the identification of humus forms found during the survey. Given the scarcity of acid silicated substrates in the study region (Fig. 1) only a restricted array of acidic humus profiles were found, all of them classified as dysmoder, while mull and amphi were represented by all described humus forms. Amphi is a recently acknowledged group of humus forms (mostly carbonated), displaying a combination of moder (in organic horizons) and mull features (in organo-mineral horizons), which were first described under the collective name amphimull [START_REF] Jabiol | Une classification morphologique et fonctionnelle des formes d'humus: propositions du Référentiel Pédologique[END_REF][START_REF] Brêthes | Classification of forest humus forms: a French proposal[END_REF][START_REF] Jabiol | L'humus sous Toutes ses Formes[END_REF][START_REF] Jabiol | L'Humus sous Toutes ses Formes, 2 ème édition[END_REF], then separated from mull under the name amphi [START_REF] Graefe | Gibt es in Deutschland die Humusform Amphi?[END_REF]Galvan et al., 2008) or amphimus [START_REF] Afes | Référentiel Pédologique 2008[END_REF][START_REF] Gobat | Le Sol Vivant: Bases de Pédologie, Biologie des Sols[END_REF] and more recently shared in several humus classification systems [START_REF] Zanella | Toward a European humus forms reference base[END_REF][START_REF] Zanella | A European morpho-functional classification of humus forms[END_REF][START_REF] Jabiol | A proposal for including humus forms in the World Reference Base for Soil Resources (WRB-FAO)[END_REF]. Considered (explained) variables were then the thicknesses of OL, OF, OH and A horizons and the presence of macro-, meso-and micro-aggregates.

Explanatory data (Table 2)

Among distal factors (not affected by humus forms), parent rocks were classified in silicated (most of them acid) and carbonated rocks (limestone, dolomite and marls). At each site, the elevation (a.s.l.) was recorded, as well as the aspect according to the nearest cardinal direction. The climate variables considered were: mean annual precipitation (precipitation, in mm), mean annual temperature (temperature in °C), annual and summer (June-July-August) potential evapotranspiration (in mm) calculated according to [START_REF] Thornthwaite | Instructions and tables for computing potential evapotranspiration and the water balance[END_REF], Gams continentality index (precipitation/elevation), simplified Lang aridity index (precipitation/temperature), and the site's occurrence in one of the four climate districts.

Among proximal or site factors (in mutual relationship with humus forms, [START_REF] Ponge | Humus forms in terrestrial ecosystems: a framework to biodiversity[END_REF][START_REF] Ponge | Plant-soil feedbacks mediated by humus forms: a review[END_REF] forest types were classified in 8 groups: beech, chestnut, other deciduous trees, spruce-beech, sprucepine, spruce-larch, silver-fir and larch forests. A vegetation index, varying along a scale from 1 to 3 expressed the dominance of coniferous versus deciduous canopies within forests. Herbaceous cover was measured as a dummy variable (presence > 50% cover; absence < 50% cover). Soils were classified in six groups based on the World Reference Base (IUSS Working Group WRB, 2007): rzLP = Rendzic Leptosols, CMca = calcareous Cambisols, CMeu = non calcareous Cambisols with high base saturation, LVhe = Luvisols with high base saturation, LVdy = very acid Luvisols, CMdy/PZ = aggregate group embracing Podzols and very acid Cambisols. Several soil analyses were done in the A horizon of humus profiles: pH water (glass electrode method in 1:5 soil:water suspension, ISO 10390:2005), presence of carbonates (effervescence to cold dilute hydrochloric acid, scale 0-4 according to USDA Soil Survey Manual), clay, sand and rock fragments in mass percentages (sieving and sedimentation method, ISO 11277:2009), organic C and N in mass percentages (dry combustion method, ISO 10694:1995 and10878:2009, respectively), and C/N ratio. The pH water of the topsoil was also measured with the same method in a bulk sample from 0 to 40 cm, including the A horizon but not the O horizon.

Data analysis

Data were analyzed by Redundancy Analysis (RDA), a direct gradient multivariate method [START_REF] Van Den Wollenberg | Redundancy analysis: an alternative for canonical correlation analysis[END_REF][START_REF] Kenkel | On selecting an appropriate multivariate analysis[END_REF], allowing discerning trends in a set of explained variables (humus form categories and humus profile features) which could be explained by a set of explanatory variables (geology, climate, soil, vegetation). For the sake of clarity, we projected independent (explanatory) and dependent (explained) variables in separate bi-plots, and dependent variables were arbitrarily subdivided (for easier visual interpretation) in climate and geology in one bi-plot, and vegetation and soil in another bi-plot. All three bi-plots belong to the same analysis.

Major trends detected by visualizing RDA bi-plots were checked for statistical significance by chi-square test. Quantitative variables to be analyzed by chi-square test were classified in two or three categories on the basis of arbitrary class limits, taking into account the need for having balanced class sizes among categories, to the exception of pH, which was divided in two classes with a limit at pH 5.2, separating soils with (pH < 5.2) or without (pH ≥ 5.2) soluble aluminum [START_REF] Walker | Aluminum solubility in organic soil horizons from northern and southern forested watersheds[END_REF], a threshold known to affect the composition of annelid communities [START_REF] Graefe | Critical values of soil acidification for annelid species and the decomposer community[END_REF]. All statistical calculations were performed under XLSTAT ® version 2013.4.05 (Addinsoft, Paris, France).

Results

The main features of the 9 recorded humus forms are presented in Table 2. Most represented humus forms were Oligomull (84 sites) and Eumacroamphi (61 sites), and the least represented ones were Mesomull (8 sites) and Pachyamphi (15 sites). The four mull humus forms (Eumull -Mesomull -Oligomull -Dysmull) were more often recorded on carbonated substrates, with a dominance of macro-and meso-structures in the A horizon. Dysmoder was found exclusively on silicated (mostly acid) substrates with very acid and podzolic soils (CMdy/PZ) and at high altitude. Within the amphi group, which was mostly represented (but not exclusively) on carbonated substrates, there was a trend of increasing dominance of carbonated substrates, from 60 to more than 90%, along the sequence Leptoamphi → Eumesoamphi → Eumacroamphi → Pachyamphi, which was associated with increasing thickness of OF horizon from 1.1 to 2.5 cm and OH horizon from 0.5 to 6.4 cm (Fig. 2). This trend was concomitant with an increase in the representation of shallow or very shallow calcareous soils (rzLP and CMca), from 30 to 80% (Table 2). Amphi humus forms were found near exclusively in Esalpic and Mesalpic climate districts and were absent from Endalpic and Avanalpic districts. Mor and Tangel have not been observed in forest soils of Veneto.

The first canonical component F1 extracted 37% of the explained variance. Mull and moder were projected on opposite sides of this component. Humus forms were distributed along F1 mainly according to the structure of the A horizon, with a gradient from macro-to meso-then to microaggregates (Fig. 3a). The thickness of fragmented and humified O horizons (OF and OH, respectively) varied in a direction opposite to that of OL and A horizons. The ends of the gradient were characterized by Oligomull and Dysmoder, respectively, other humus forms being projected in an intermediary position.

The projection of environmental variables showed that the first canonical component could be interpreted as a composite factor embracing both geological, climate and soil gradients. Among distal factors (Fig. 3b) the positive side of F1 was characterized by silicated rocks (as opposed to carbonated rocks), high elevation, low temperature, low summer and to a lesser extent annual potential evapotranspiration, high Lang index (low aridity), and Mesalpic district (as opposed to Esalpic and Mediterranean districts on left side). Among site factors (Fig. 3c), the positive side of F1 was characterized by most acidic soils (CMdy/PZ: Podzols and dystric Cambisols), low pH (whether A horizon or first top 40 cm), high C/N and organic C, high sand content (as opposed to clay content) and high vegetation index (dominance of coniferous trees), exemplified by spruce-pine forests (right side) opposed to other deciduous forests (left side) with opposite characters (soil types CMeu, LVhe, CMca).

Mean annual precipitation, organic N, exposure (four cardinal directions), Endalpic district, rock fragments content and soil effervescence were projected not far from the origin along F1, thus did not seem to contribute to a great extent to the gradient depicted by F1. Thus temperature and potential evapotranspiration (in particular during summer months) for climate, and pH, organic C and C/N for soil, are given more importance in this gradient than mean annual precipitation and organic N, respectively.

We tested the significance of the gradient from macro-to meso-then to micro-aggregated structure of the A horizon according to some possible proximal (soil, vegetation) and distal (geology, climate) factors (Fig. 4). The impact of geology (silicated vs. carbonated rocks, Fig. 4a), elevation (three classes, < 800m, 800-1500m, > 1500m, Fig. 4b), temperature (three classes, < 6°C, 6-10°C, > 10°C, Fig. 4c), aridity (three classes of Lang index, < 150, 150-250, > 250, Fig. 4d) and climate district (four districts, Fig. 4e) was verified, with a very high significance level (P < 0.0001 for all tests, to the exception of P < 0.001 for Lang index). The impact of vegetation (three classes of vegetation index, Fig. 4f), soil pH (two classes, pH < 5.2, pH ≥ 5.2, Fig. 4g) and clay content (three classes, < 15%, 15-25%, > 25%, Fig. 4h) was verified with a significant level for clay content (P < 0.05) and a highly significant level for vegetation and pH (P < 0.0001). The variation along geological, climate, soil and vegetation gradients of the proportion of meso-aggregated A horizons was much less pronounced than that of micro-and macro-aggregated A horizons, which exhibited strongly contrasted trends, exemplifying the intermediate nature of meso-aggregates.

The second canonical component F2 extracted 21% of the explained variance. Along F2 amphi (negative side) was opposed to both mull and moder (positive side). Humus forms were distributed along this factor mainly according to the thickness of OF and OH horizons, in particular within the amphi group, Pachyamphi (with thickest OF and OH horizons, see Table 2) being projected far from the origin on the negative side of F2, followed by Eumacroamphi then by Eumesoamphi and at last Leptoamphi (Figs. 2 and3a). Within the mull group, Dysmull was opposed to Oligomull along F2, Mesomull and Eumull being in an intermediate position, thus not depicting a similar gradient of thickness of OF (OH absent in mull) horizon (see Table 2). Among distal and site environmental factors, F2 mainly depicted an opposition between silicated and carbonated rocks (Fig. 3b), and a gradient in soil effervescence, clay and rock content (Fig. 3c): very shallow calcareous soils (rsLP) with low clay and high rock fragment content, developed over carbonated substrates are on the negative side of F2 (Fig. 3c).

The thickness of OH horizons, the % of carbonated substrates among recorded profiles (Fig. 2) and the rock fragments content of A horizons (Fig. 5) increased along the gradient Leptoamphi -Eumesoamphi -Eumacroamphi -Pachyamphi. The thickness of the OH horizon and the effervescence level (varying from 0 to 4) were positively correlated with the rock fragment content of the soil on carbonated substrates (r s = 0.26 and 0.37, respectively, P < 0.0001).

Discussion and conclusions

We showed that a large variety of humus forms, mainly associated with carbonated substrates (hard limestone, dolomite and marl), were recorded in Veneto. We also showed that geology, climate, soil and vegetation exert a prominent influence on the distribution of humus forms, especially when considering the micro-, meso-or macro-aggregated structure of the A horizon. The coldest climatic district in the Veneto region is situated in areas with the highest elevation, the most acidic substrate (acid silicated rocks), the most recalcitrant litter (spruce and pine), and a finer structure in the A horizon. This means that all factors (low temperature, high acidity, litter recalcitrance), known to decrease litter decomposition and soil biological activity (reviewed in [START_REF] Ponge | Humus forms in terrestrial ecosystems: a framework to biodiversity[END_REF][START_REF] Ponge | Plant-soil feedbacks mediated by humus forms: a review[END_REF], may affect the size of soil aggregates, whether these factors co-occur or not. In the study region, substrate acidity and litter recalcitrance (spruce and pine) are correlated. Coniferous forest vegetation, especially spruce, is ubiquitous and man-induced for a large part, being mostly established on poorest soils as commonly observed in other regions [START_REF] Willis | Does soil change cause vegetation change or vice versa? A temporal perspective from Hungary[END_REF][START_REF] Wilson | The use of ground vegetation and humus type as indicators of soil nutrient regime for an ecological site classification of British forests[END_REF]. On the contrary elevation and soil acidity are not correlated in Veneto (Fig. 1), where the highest mountain summits and cliffs are of carbonated (dolomitic) nature [START_REF] Arpav | Carta dei suoli del Veneto. Osservatorio Regionale Suolo[END_REF][START_REF] Viero | Laser scanning-based recognition of rotational movements on a deep seated gravitational instability: the Cinque Torri case (north-eastern Italian Alps)[END_REF], while in eastern and western parts of the Alps acidity increases with altitude, since carbonated rocks are eroded at a higher rate than core metamorphic and igneous silicated rocks during orogeny (Frisch et al., 2008), among many other causal factors [START_REF] Körner | The use of 'altitude' in ecological research[END_REF].

The structure of the organo-mineral horizon is mainly governed by the activity of soil organisms, among which annelids, after roots, take a prominent position [START_REF] Wolters | Soil invertebrates, effects on nutrient turnover and soil structure: a review[END_REF][START_REF] Wolters | Invertebrate control of soil organic matter stability[END_REF][START_REF] Zangerlé | Do earthworms and roots cooperate to build macroaggregates ?[END_REF]. Among annelids, large worms (generally earthworms) and small worms (generally enchytraeids) diverge in their tolerance to low temperatures [START_REF] Holmstrup | Small Dendrobaena earthworms survive freezing better than large worms[END_REF], acidity [START_REF] Graefe | Critical values of soil acidification for annelid species and the decomposer community[END_REF], and litter quality [START_REF] Ponge | Soil fauna and site assessment in beech stands of the Belgian Ardennes[END_REF]. Annelids create different structures according to their size, macro-(> 4 mm) and meso-structures (2-4 mm) of mull and amphi humus forms resulting from the burrowing and defecating activity of earthworms (Galvan et al., 2008), while microstructures (< 2 mm) of moder humus forms result mainly from the activity of enchytraeids (Didden, 1990;Dawod and FitzPatrick, 1993;[START_REF] Ponge | Horizons and humus forms in beech forests of the Belgian Ardennes[END_REF]. Enchytraeids, in particular the common, asexual Cognettia sphagnetorum, replace earthworms when conditions become more severe along latitudinal and altitudinal gradients [START_REF] Bernier | Comparative study of soil organic mayers in two bilberryspruce forest stands (Vaccinio-Piceetea): relation to forest dynamics[END_REF][START_REF] Briones | Predicting potential impacts of climate change on the geographical distribution of enchytraeids: a meta-analysis approach[END_REF]. Exclusion mechanisms between enchytraeids and earthworms, whether competitive or behavioral in advance of competition, have been demonstrated [START_REF] Haukka | Growth and survival of Eisenia fetida (Sav.) (Oligochaeta: Lumbricidae) in relation to temperature, moisture and presence of Enchytraeus albidus (Henle) (Enchytraeidae)[END_REF][START_REF] Ponge | Humus forms in terrestrial ecosystems: a framework to biodiversity[END_REF], in addition to abovementioned differences in tolerance, which might explain observed gradients of annelid composition and resulting changes in humus forms [START_REF] Ponge | Humus forms in terrestrial ecosystems: a framework to biodiversity[END_REF].

As expected, main groups of humus forms present in the Veneto region, namely mull, moder and amphi, are distributed according to their main morphological features and their contrasted responses to environmental factors [START_REF] Ponge | Humus forms in terrestrial ecosystems: a framework to biodiversity[END_REF][START_REF] Graefe | Critical values of soil acidification for annelid species and the decomposer community[END_REF][START_REF] Graefe | Gibt es in Deutschland die Humusform Amphi?[END_REF][START_REF] Ponge | Plant-soil feedbacks mediated by humus forms: a review[END_REF]. Our results show a strong contrast between (i) Dysmoder (as the unique representative of the moder group) in environmental conditions favoring fungal and mesofaunal activity (aggregates < 2 mm, mainly done by enchytraeids), as in very acid podzolic soils, and (ii) mull and amphi, representatives of soils with intense bacterial and macrofaunal activity (aggregates > 2 mm, mainly done by earthworms). We hypothesize that the gradient depicted by the first canonical factor of RDA (embracing climate, geology, soil and vegetation) corresponded to the balance between fungal-based and bacterial-based soil trophic networks, a balance largely controlled by the environment [START_REF] Hedlund | Trophic interactions in changing landscapes: responses of soil food webs[END_REF]. The impact of environmental gradient on humus forms is mainly mediated by the activity of annelids (enchytraeids and earthworms) which transform the litter into humus and incorporate it (or not) to mineral horizons, with strong variations according to their size and behavioral (burrowing) type. Low temperature, acidity and poor litter quality favor small-sized annelids (enchytraeids) to the detriment of big-sized annelids (anecic earthworms), medium-sized annelids such as epigeic earthworms being intermediary in their environmental requirements [START_REF] Ponge | Humus forms in terrestrial ecosystems: a framework to biodiversity[END_REF][START_REF] Ponge | Plant-soil feedbacks mediated by humus forms: a review[END_REF]. Awaiting a study embracing both animal communities and humus profiles in a wide range of environmental conditions, this may contribute to explain the observed gradient of aggregate size distribution.

The contrast between mull and amphi was mainly associated with physicochemical properties of parent materials, in particular texture (clay → sand → rock fragments) and calcium content (soil effervescence). Our results do not point to a great importance given to climate in the contrast between amphi and mull, although climate has been suspected to be a driving factor of amphi build-up [START_REF] Graefe | Gibt es in Deutschland die Humusform Amphi?[END_REF]. Amphi, being characterized by thick organic horizons with a well-developed OH horizon (otherwise typical of moder and mor) overlying a macro-or meso-aggregated A horizon (otherwise typical of mull), can be explained by the combination of (i) large earthworm populations with (ii) some factors preventing them to incorporate litter at least during part of the year. The former is linked to calcium availability (here approximated by soil pH and presence of carbonates), a prominent factor of earthworm activity [START_REF] Piearce | The calcium relations of selected Lumbricidae[END_REF], while the latter is linked to climate harshness (summer drought and/or winter frost) and hardness of the parent rock (here approximated by percent rock fragments), known to be stressful in shallow soils [START_REF] Aussenac | Ecology and ecophysiology of circum-Mediterranean firs in the context of climate change[END_REF]. According to present results, and given our still incipient knowledge on amphi humus forms [START_REF] Andreetta | Forest humus forms as potential indicators of soil carbon storage in Mediterranean environments[END_REF], high calcium availability, shallow soils and associated poor water storage capacity seem to be driving factors in the genesis of the most typical humus form of this group: Pachyamphi. In some sense it can be said that on carbonated substrates with summer and/or winter climate stress for earthworm communities the development of a thick OH horizon saturated in Ca may compensate soil shallowness. Galvan et al. (2008) observed that the size of aggregates reflected the size of species which were dominant in the earthworm community, in particular the balance between epigeic (small earthworms) and anecic (big earthworms) species. According to their records in subalpine forests of the Trento Province (northern Italy), the group they called amphi 1 (meso-structured, embracing Eumesoamphi and Pachyamphi in the present classification) was restricted to acid crystalline substrates, while the group they called amphi 2 (macro-structured, embracing Leptoamphi and Eumacroamphi) was found on dolomitic and mixed substrates. This means that substrates poor in nutrients, in particular calcium, are unfavorable to more exacting litter-feeding earthworms, i.e. anecics, a result supported by studies on earthworm communities [START_REF] Nordström | Environmental factors and lumbricid associations in southern Sweden[END_REF][START_REF] Satchell | Potential of the Silpho Moor experimental birch plots as a habitat for Lumbricus terrestris[END_REF][START_REF] Ponge | Interactions between earthworms, litter and trees in an old-growth beech forest[END_REF]. Here we found that the gradient Leptoamphi (macro) → Eumesoamphi (meso) → Eumacroamphi (macro) → Pachyamphi (meso) did not reflect the structure of the A horizon (macro-versus meso-aggregates) but rather the thickness of organic layers, and was positively correlated with the percentage of carbonated substrates among samples (from 60% for Leptoamphi to 90% for Pachyamphi) and the percentage of rock fragments in the A horizon (from 14% for Leptoamphi to 38% for Pachyamphi). This suggests that the richer is the topsoil in rock fragments (in calcareous context) the more difficult the incorporation of organic matter to mineral matter by burrowing earthworms [START_REF] Callaham | Influence of differing land management on the invasion of North American tallgrass prairie soils by European earthworms[END_REF]. In the absence of earthworm records we cannot go deeper in elucidating this causal relationship. The balance between unincorporated carbon and that incorporated by annelids in the mineral soil would not be entirely driven by climate, as suspected so far [START_REF] Bottner | Soil organic matter in Mediterranean-type ecosystems and global climate changes: a case study, the soils of the Mediterranean Basin[END_REF][START_REF] Graefe | Gibt es in Deutschland die Humusform Amphi?[END_REF][START_REF] Ascher | Are humus forms, mesofauna and microflora in subalpine forest soils sensitive to thermal conditions ?[END_REF], although other influences such as phosphorus availability have been suspected [START_REF] Tagger | Characterization of an amphimull under Mediterranean evergreen oak forest (Quercus ilex): micromorphological and biodynamic descriptions[END_REF], but also by the restricted soil volume available for burrowing due to the abundance of rock fragments. This 'rock fragment effect', typical of shallow calcareous soils (rzLP) on dolomite and hard limestone substrates might have important consequences on carbon sequestration [START_REF] Wironen | Exotic earthworm invasion increases soil carbon and nitrogen in an old-growth forest in southern Quebec[END_REF][START_REF] Andreetta | Forest humus forms as potential indicators of soil carbon storage in Mediterranean environments[END_REF][START_REF] Bonifacio | Humus forms, organic matter stocks and carbon fractions in forest soils of northwestern Italy[END_REF], beside climate effects [START_REF] Marland | The climatic impacts of land surface change and carbon management, and the implications for climate-change mitigation policy[END_REF]Egli et al., 2010;[START_REF] Thornley | Soil carbon storage response to temperature: an hypothesis[END_REF] and their interactions with vegetation [START_REF] Paré | Effect of temperature on soil organic matter decomposition in three forest biomes of eastern Canada[END_REF]De Deyn et al., 2008;[START_REF] Podwojewski | Climate and vegetation determine soil organic matter status in an alpine inner-tropical soil catena in the Fan Si Pan Mountain[END_REF] and mineral composition [START_REF] Rasmussen | Mineral control of organic carbon mineralization in a range of temperate conifer forests soils[END_REF]. 1a) and explanatory variables (Fig. 1b) in the plane of the first two canonical factors (see list in Table 1).

Gulf of Venice

Figure captions Figure 1 .

 captions1 Figure captions

Figure 2 .

 2 Figure 2. Distribution of amphi humus forms and thickness of organic horizons according to

Figure 3 .

 3 Figure3. Redundancy Analysis (RDA). Projection of explained variables (Fig.1a) and explanatory

Figure 4 .

 4 Figure 4. Distribution of micro-(< 2 mm), meso-(2-4 mm) and macro-aggregates (> 4 mm)

Figure 5 .

 5 Figure 5. Distribution of amphi humus forms and thickness of organic horizons according to soil

  Fig.1

  Fig.2

  Fig.4

Table 1 .

 1 Criteria used for the classification of terrestrial humus forms from Veneto Region. Never = horizon never present; always = horizon always present; transition O-A < 3 mm = thickness of the junction zone between O (organic) and A (organo-mineral) horizons < 3 mm; bracketed horizon = discontinuous or in pockets; OH < 1cm = thickness of OH horizon < 1 cm; zo = zoogenic; noz = non zoogenic; maA = biomacrostructured A horizon; meA = biomesostructured A; miA = biomicrostructured A; maA ≥ OH/2 = thickness of maA ≥ half that of OH; * = not included in Veneto dataset.

	Main morpho-functional types Humus Form	Diagnostic horizons
		Reference Groups
		(Jabiol et al. (2013)
		Eumull	(OLn), maA
	MULL: never: OH, OFnoz, Anoz, miA; always: maA or meA; transition O-A < 3 mm	Mesomull Oligomull	OLn, (OLv), maA OLn, OLv, (OFzo) maA or meA
		Dysmull	OLn, OLv, OFzo, maA or meA
	MODER: never: maA, OFnoz;	Hemimoder*	OLn, OLv, OFzo, (OH), miA
	always: Anoz or miA; transition O-A ≥ 5mm	Eumoder* Dysmoder	OLn, OLv, OFzo, OH≤1cm, (Anoz) or miA OLn, OLv, OFzo, OH>1cm, (Anoz and OH?2A) or miA
	MOR*: never: maA, meA; never:	Hemimor*	OLn, OLv, OFzo, (OFnoz), (OH), miA or Anoz or E
	maA, meA; always: OFnoz;	Humimor*	OLn, OLv, OFzo, OFnoz, (OH), miA or Anoz or E
	transition O-A < 3 mm	Eumor*	OLn, OLv, OFzo, OFnoz, OH, Anoz or E
		Leptoamphi	OLn, OLv, OFzo, OH < 1cm, maA ≥ OH/2
	AMPHI: never: OFnoz, Anoz; always: OH, maA or meA; always: A ≥ OH/2	Eumacroamphi Eumesoamphi	OLn, OLv, OFzo, OH ≥ 1cm, maA ≥ OH/2 OLn, OLv, OFzo, OH < 3cm, A ≥ OH/2, miA and/or meA or only meA
		Pachyamphi	OLn, OLv, OFzo, OH ≥ 3cm, A ≥ OH/2, miA and/or meA or only meA
	TANGEL*: never: OFnoz; always:	Eutangel*	OLn, OLv, OFzo, OH > 2A, Anoz or meA, transition OH-A < 5 mm
	OH > 2A	Dystangel*	OLn, OLv, OFzo, OH > 2A, Anoz, transition OH-A ≥ 5 mm

Table 2 .

 2 Mean features of Veneto humus forms according to morphology of humus profiles, geology, topography, climate, vegetation and soil characteristics. When data are of analytical nature (measures), values are given as means with standard deviations. When data are of typological nature (occurrences), they are indicated as percent occurrence of the different categories.

Acknowledgements

All data were obtained within the framework of the research project "Soil map of Veneto Region at 1:250,000 scale". This project was financially supported by the Environmental Protection Agency of the Veneto Region (ARPAV), which is greatly acknowledged. The authors also acknowledge two anonymous reviewers, for language editing and many improvements suggested to a previous draft of our paper.

Carletti, P., Vendramin, E., Pizzeghello, D., Concheri, G., Zanella, A., Nardi, S., Squartini, A., 2009. Soil humic compounds and microbial communities in six spruce forests as function of parent material, slope aspect and stand age. Plant and Soil 315, 47-65. Dawod, V., FitzPatrick, E.A., 1993. Some population sizes and effects of the Enchytraeidae


The contribution of grain boundary barriers to the electrical conductivity of titanium oxide thin films Nicolas Martin, 1,a͒ Aurélien Besnard, 1 Fabrice Sthal, 1 Filipe Vaz, 2 and Corinne Nouveau 3 Titanium oxide thin films were prepared by reactive magnetron sputtering. The reactive gas pulsing process was implemented to control the oxygen injection in the deposition process and, consequently, to tune the oxygen concentration in the films from pure titanium to stoichiometric TiO 2 , maintaining a homogeneous in-depth concentration. The electrical conductivity of the films was investigated as a function of the oxygen injection time, the metalloid concentration and temperature, in the range 90-600 K. The curved Arrhenius plots of the conductivity were examined taking into account the grain boundary limited transport model of Werner ͑J. H. Werner ͓Solid State Phenom. 37-38, 213 ͑1994͔͒͒. The grain barrier heights were found to depend significantly on the oxygen supplied into the deposition process and thus, on the oxygen-to-titanium atomic ratio in the films. The analysis as a function of temperature showed that the conduction mechanism in the coatings was not solely limited by the oxygen-to-titanium atomic ratio, but also by the grain boundary scattering. © 2008 American Institute of Physics. ͓DOI: 10.1063/1.2970034͔

The conductivity of polycrystalline films is sensitively related to the potential barriers and space charge regions that are built up around grain boundaries. 1 A strong temperature dependence of the electrical conductivity is commonly observed in metallic and semiconducting films. Furthermore, it is shown that the grain boundaries of polycrystalline semiconductors have a significant influence on the electronic properties. According to the grain boundary model of Seto, 2 if trap states in the intergranular region are present, the capture of the free carriers occurs and thus, the films' conductivity changes. These charged states create potential barriers space charge regions that are built up around the grain boundaries, which then increase the resistance between two neighboring grains. This letter demonstrates that the Werner's theory 3 can be applied to the electrical conductivity behavior versus temperature of titanium oxide thin films. Experimental results showed that for the conduction mechanism, and beyond the oxygen-to-titanium atomic ratio, the transition from metallic-to semiconducting-type behavior of titanium oxide, TiO x thin films ͑with x varying from 0 to 2.0͒ has also an important contribution from the grain boundary scattering.

The TiO x films were deposited on glass and ͑100͒ Si substrates by dc reactive magnetron sputtering from a titanium metallic target ͑purity 99.6%͒ in an Ar+ O 2 gas mixture. The titanium target was sputtered with a constant current density J = 100 A m -2 while the substrates were grounded and kept at room temperature. Argon mass flow rate was set constant in order to reach an Ar partial pressure of 0.25 Pa. Oxygen was introduced using a rectangular modulation pattern of the mass flow rate by means of a re-active gas pulsing process. [4][5][6][7] A constant pulsing period P = 45 s was used, whereas the time of injection t ON of the oxygen gas was systematically changed from 0% to 100% of the period P. The maximum oxygen flow rate was 0.80 SCCM ͑SCCM denotes cubic centimeter per minute at STP͒ during the t ON time whereas the minimum flow was 0 SCCM during the t OFF time ͑oxygen injection completely stopped͒. The deposition time was adjusted in order to deposit thin films with a constant thickness close to 400 nm. The crystallographic structure was investigated by x-ray diffraction ͑XRD͒ using monochromatic Cu K ␣ radiation at a grazing angle = 1°. The chemical composition of the films deposited on silicon wafer ͑100͒ was determined by Rutherford backscattering spectroscopy ͑RBS͒ and nuclear reaction analysis ͑NRA͒. The electrical conductivity of the films deposited on glass substrates was measured in the Van der Pauw geometry for temperatures ranging from 90 to 600 K.

Werner's theory assumes that the fluctuating barrier heights are described by a Gaussian probability distribution, 3

P͑͒ = 1 ͱ 2 e ͑ ¯-͒ 2 /2 2 , ͑1͒
where denotes the mean barrier height and denotes its standard deviation. The current across the spatially inhomogeneous grain barriers is limited by the lowest barrier in the Gaussian distribution. In addition, Werner's theory shows that the slopes of the Arrhenius plots of conductivities are curved upward with decreasing the reverse temperature values. The curved behavior of the plots ln͑ / T͒ is well fitted by a parabola, following: lnͩ

T ͪ= a T 2 - b T -c. ͑2͒
The mean barrier height and the standard deviation are

a͒ = ͱ 2ak 2 q 2 , ͑3͒ ¯= bk q , ͑4͒
where k = 1.38ϫ 10 -23 JK -1 and q = 1.6ϫ 10 -19 As. Figure 1 illustrates the temperature dependent conductivity ln͑ / T͒ for sputtered TiO x thin films in the temperature range 90 to 600 K. The obtained results can be separated in two groups. The first one concerns TiO x thin films sputter deposited with t ON injection times up to 15 s. Electrical conductivity at room temperature ranges from 293 K = 1.10 ϫ 10 4 to 2.14ϫ 10 3 Sm -1 , which corresponds to conventional metallic TiO x thin film values. 8 For coatings deposited with t ON = 5 and 10 s, a typical metallic behavior is observed as a function of temperature. The temperature coefficient of resistance ͑TCR 293 K ͒ calculated at 293 K is reduced from 1.33ϫ 10 -3 to 6.80ϫ 10 -4 K -1 ͑Table I͒. It becomes negative for t ON =15 s ͑TCR 293 K = -1.01ϫ 10 -3 K -1 ͒. Such a decrease of TCR with O / Ti ratio is in agreement with Banakh et al. 8 investigations focused on TiO metallic films. Negative TCR values tend to appear in TiO x thin films where the low free carrier concentration results in a less efficient screening of the point defects. Understanding electrical transport in such TiO x metallic systems ͑point defect concentration reaches several at. %͒ is still an open question. However, the decrease of TCR versus O / Ti ratio and its negative value reached for t ON = 15 s can be related to the Mooij criterion ͑at room temperature, resistivity of 150 ⍀ cm is an universal criterion for the sign of TCR; if the room temperature resistivity of a sample is larger than this value, it is likely to have a negative TCR͒. 9 Such a criterion applied in a large number of amorphous or disordered metal conductors remains one of the most criteria applied to explain the negative TCR values in metallic compounds. 10 Similarly, Riess et al. 1 explained the change of sign of the calculated TCR from positive to negative values taking into account the number of grain boundaries per electron mean free path. For our results, an increase of the t ON injection time obviously leads to an oxygen enrichment of TiO x films, but specially the long range order is reduced ͑from XRD, metallic crystallite size calculated from Scherrer's method reduces from 30 to 5 nm as t ON changes from 5 to 15 s͒. Thus, assuming the same electron mean free path for all TiO x films exhibiting metallic behaviors ͑t ON =5-15 s͒, the number of grain boundaries is enhanced and a negative TCR value can be expected, although the electrical conductivity decreases versus temperature.

The second group of samples involves TiO x thin films prepared with t ON injection times higher than 20 s. Conductivity at room temperature is continuously decreasing from 293 K = 2.53ϫ 10 2 to 2.86ϫ 10 -2 Sm -1 as t ON increases from 20 to 27.5 s. For this kind of films, a characteristic semiconducting behavior is measured as a function of temperature. For semiconductors, the Arrhenius plot of the conductivity versus the reverse of the temperature usually exhibits a linear evolution for temperatures higher than the room temperature. The activation energy E a , which gives evidence that the conduction mechanism is thermally activated can be then calculated. Table I shows that the calculated value for the energy E a increase from 30 to 190 meV as the t ON time increases. It tends to that of stoichiometric TiO 2 compound ͓E a = 650 meV ͑Ref. 11͔͒, which correlates with O / Ti ratios determined by RBS and NRA. As the temperature range extends ͑from 90 to 600 K͒, Arrhenius plots become curved ͑Fig. 1͒ and Werner's theory is relevant to determine the mean heights of the barrier potential ¯and the standard deviation following Eqs. ͑3͒ and ͑4͒. Measured conductivities of TiO x thin films deposited at high t ON times are well described by parabola in agreement with Eq. ͑2͒. Parameters and have been calculated from conductivity measurements versus temperature in Fig. 1 and for rising t ON injection times ͑Fig. 2͒. Both parameters increase with t ON injection time. The mean barrier height changes from 8 to 113 meV and the standard deviation from 9 to 40 meV as the t ON time increases from 20 to 27.5 s. Werner 3 also proposed a homogeneity coefficient H defined as the ratio of to . The larger the H, the more homogeneous is the film. For our TiO x thin films, the H coefficient is enhanced from 0.88 to 3.1 with the t ON injection time, which are typical values previously reported for other semiconducting compounds. [12][13][14] In undoped and substoichiometric TiO 2 thin films, it is commonly admitted that the conductivity change is closely linked to the mobile charge carriers. 15 Their concentration originates from point defects, i.e., mainly oxygen vacancies rather than interstitial titanium atoms. The contribution of the oxygen vacancies to the conductivity mechanism predominates for titanium oxide thin films exhibiting semiconducting behaviors and prepared with low t ON times ͑e.g., O / Ti ratio= 1.43-1.91͒. In addition, the mean heights of the barrier potential are the lowest for the corresponding range of the t ON time ͑ ¯= 8 meV for t ON =20 s͒, which correlates with a conductivity behavior determined by the oxygen vacancies. For the highest t ON times, O / Ti ratio tends to the stoichiometric TiO 2 compounds. The oxygen vacancies concentration is reduced whereas the mean height of the barrier potential is higher than 110 meV. As a result, conductivity is mainly influenced by grain boundary effects and prevails on the point defects.

Summarizing, we have produced TiO x thin films by reactive sputtering using a pulsed injection of the oxygen gas ͑reactive gas pulsing process͒. A systematic change of the t ON injection time of the reactive gas leads to tunable electrical properties of titanium oxides, in agreement with investigations involving other deposition techniques. [16][17][18] For O / Ti atomic ratios close to or lower than one, a metallic behavior is clearly observed with positive and negative TCR values closely linked to the number of grain boundaries per electron mean free path. Titanium oxide semiconducting films are prepared for longer t ON injection times. Conductivity behaviors are found to be not solely ruled by the oxygen vacancies, but also by the potential at the grain boundaries. Point defects prevail for oxygen-deficient titanium dioxide, whereas the heights of the barrier potential become predominant for thin films tending to the stoichiometric TiO 2 compound.

FIG. 1 .

 1 FIG.1. Temperature dependence of the electrical conductivity of TiO x films sputter deposited by the reactive gas pulsing process using various times of injection of the oxygen gas.

1

  Institut FEMTO-ST, 6174 CNRS, Université de Franche-Comté ENSMM UTBM 26, Chemin de l'épitaphe, 25030 Besancon Cedex, France 2 Departamento Fisica, Universidade do Minho, Azurém, 4800-058 Guimarães, Portugal 3 LaBoMaP, Arts et Métiers ParisTech de Cluny, Rue Porte de Paris, 71250 Cluny, France ͑Received 14 May 2008; accepted 23 July 2008; published online 12 August 2008͒

TABLE I .

 I Chemical composition, electrical behaviors, and structure of TiO x thin films as a function of the t ON time. am. denotes amorphous and N. A. denotes not applicable.

	t ON ͑s͒	5.0	10.0	15.0	20.0	23.5	24.5	25.0	26.5	27.5
	͓O͔͑ at. %͒	9.8	33.7	51.3	58.9	64.1	64.8	65.6	66.6	66.6
	O / Ti ratio	0.11	0.51	1.05	1.43	1.79	1.84	1.91	1.99	1.99
	293 K ͑Sm -1 ͒	1.10ϫ 10 4	5.13ϫ 10 3	2.14ϫ 10 3	2.53ϫ 10 2	4.30	1.62	1.27	1.12ϫ 10-1	2.86ϫ 10-2
	Behaviors		← metallic →← semiconducting →
	TCR 293 K ͑K -1 ϫ 10 3 ͒	1.33	0.68	-1.01				N.A.
	E a ͑meV͒		N.A.		30	140	160	150	190	160
	Structure by XRD

←Ti →← am.+ fcc TiO →← am.+ TiO 2 anatase and rutile →