Article pubs.acs.org/acssensors
Dynamic Range Enhancement Using the Electrostatically Formed Nanowire Sensor Nandhini Swaminathan,* Alex Henning, Yonathan Vaknin, Klimentiy Shimanovich, Andrey Godkin, Gil Shalev, and Yossi Rosenwaks* Department of Physical Electronics, School of Electrical Engineering, Tel Aviv University, Ramat Aviv − 69978, Israel S Supporting Information *
ABSTRACT: The evolution of nanotechnology based sensors has enabled detection of ultra-low-level concentrations of target species owing to their high aspect ratio. However, these sensors have a limited dynamic range at room temperature characterized by saturation in the sensor response following certain concentration exposure. In this work, we show that the dynamic range towards a target gas can be significantly enhanced using the electrostatically formed nanowire sensor. The size and shape of the nanowire conducting channel are defined and tuned by controlling the bias applied to the surrounding gates. The nanowires thus formed vary in their response, detection limit, and dynamic range for a given target gas exposure depending on its size and shape. By electrostatically tuning to the appropriate nanowire, we can not only enhance the sensor response in the low concentration regime, but also broaden the overall dynamic range capacity using a single sensor. It is demonstrated that the sensor is capable of detecting ∼26−2030 ppm ethanol and ∼40−2800 ppm of acetone efficiently with reasonably high response (≥20%) throughout the whole range. The broad dynamic range concept is also demonstrated using scanning gate microscopy measurements of the device. This represents the first nanotechnology-inspired work towards tunable dynamic range of a sensor using a single electronic device. KEYWORDS: dynamic range, chemical sensor, volatile organic compounds, electrostatically formed nanowire, gas sensor
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performance and, at the same time, overcome the disadvantages involved with the nanomaterials based sensors. While most reports on nanostructured materials based sensors for VOCs focus on enhancing the sensitivity or the detection limit, the dynamic range of the sensor is rarely addressed in the literature. The dynamic range of a sensor refers to the input range of concentrations over which the device results in a meaningful output sensor response and can reliably report a concentration perturbation.20 A sensor is designed to perform within this specified range, the upper threshold of which is usually dictated by saturation effects in the sensor response towards increasing concentrations. Some of the reported metal oxide based sensors have an appreciable concentration detection range for VOCs but require elevated operating temperatures.21−26 Recently, Dong et al. reported a self-grown NiO nanosheets based sensor with excellent performance and wide dynamic range detection for VOC vapors from 5 up to 1000 ppm at 180−260 °C operating temperature.24 An array of SnO2 based thick film sensors with different additives was reported to be highly sensitive for a broad range of ∼100−3000 ppm concentrations of different VOCs at 400 °C.25 Kim et al. reported an MoS2 based room
anotechnology has led to the development of highly efficient sensors with enhanced properties that offer significant advantages over conventional sensors. Nanobiotechnology and human health monitoring are the major areas where nanostructured materials have made a huge impact as highly efficient competitive sensors.1−5 Recent work dedicated to detection of volatile organic compounds (VOCs) aims not only at enhanced sensitivity or improving detection limit, but also at improving other crucial aspects such as selectivity, stability, and response time.5−9 Although metal oxide semiconductors are the most common sensing materials which offer several advantages such as low cost and high sensitivity, they need to be rapidly heated at high temperatures (100−400 °C) for gas sensing applications.10−14 Carbon nanotubes (CNTs) have also demonstrated huge potential as a gas sensor with rapid development over the past few years.15−19 However, the synthesis of pure and identical CNTs with consistent properties required for the sensing application is still costly and challenging.15 In general, high fabrication costs, challenging large-scale integration, poor structural stability, and elaborate chemical modifications to the nanomaterials are some of the key challenges faced by nanomaterials based sensors towards realizing a commercial product. Hence a novel approach is highly desired to incorporate the enormous advantages that nanotechnology has to offer in enhancing the sensing © XXXX American Chemical Society
Received: February 10, 2016 Accepted: April 13, 2016
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DOI: 10.1021/acssensors.6b00096 ACS Sens. XXXX, XXX, XXX−XXX
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Figure 1. (a) Schematic representation of the EFN sensor. (b) Scanning electron microscopy image of the EFN device with zoomed-in view of the active area. The EFN is formed in the ∼650 nm n-doped region sandwiched between the p+-doped regions.
Figure 2. (a) IDS−VDS characteristics of the EFN device measured for different junction gate voltages (VJG = 0 to −0.9 V) at back gate voltage, VBG = 0 V. (b) Simulated cross section of the EFN electron density distribution showing impact of varying VJG and VBG on the EFN size and shape. The corresponding effective diameter (Deff) extracted from the fwhm of the electron density distribution of the EFN is also indicated.
copy measurements prove the general efficacy of the EFN dynamic range detection for any target gas.
temperature sensor to detect different VOCs in the 1−1000 ppm range and show opposite sensing behavior towards some of the VOCs when functionalized with a thiolated ligand.26 Over the past few years, silicon nanowires (SiNW) have also developed as excellent candidates for VOC detection of polar as well as nonpolar analytes.27−32 Recently, SiNW FET modified with trichloro-(phenethyl)silane was demonstrated to be highly sensitive to as low as 5 ppb up to 150 ppb of VOCs linked with gastric cancer.33 To the best of our knowledge, studies on the dynamic operating range for VOC concentrations of SiNW based sensors have not yet been reported. In this work, we show that a broad dynamic detection range is attainable with the electrostatically formed nanowire (EFN) sensor and demonstrate its performance for ethanol and acetone detection. The EFN was introduced as a biosensor by Shalev et al. capable of specific and label free detection of femtomolar protein concentrations.34 In our recent work, the EFN was introduced as a sensor for ethanol detection and characterized by Kelvin probe force microscopy (KPFM) measurements to extract the nanowire diameter.35 In brief, the nanowire in the EFN is not physically synthesized but defined electrostatically in the bulk by appropriate biasing of the surrounding gates. We show here that by electrically tuning the EFN diameter and shape for a particular concentration range, the sensor response as well as the overall dynamic range over which the sensor operates can be highly enhanced. The tunable sensitivity of the EFN towards the VOCs is attributed to the nanowire size and shape controlled electrically. The sensor performance is analyzed and discussed in detail with respect to the nanowire dimensions, extracted using three-dimensional electrostatic simulations. Furthermore, scanning gate micros-
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RESULTS AND DISCUSSION The EFN device (Figure 1a) consists of n- and p-doped silicon regions surrounded by four gates: back gate (VBG), two lateral junction gates (VJG), and a top dielectric (6 nm SiO2) that serves as the molecular gate. The electrostatically formed nanowire is referred to the electron accumulated channel between the source and the drain bordered by depletion regions that are formed by appropriately biasing the back gate and junction gates. The dimension and shape of the EFN thus formed is controlled by the surrounding p−n junctions and can be tuned by varying VJG and VBG. Figure 1b shows a top scanning electron image of the EFN device. The EFN is formed inside the ∼650 nm n-doped region sandwiched in between the p-doped regions. The IDs−VDs device characteristics of the sensor for different junction gate voltages is shown in Figure 2a. The drain current reduces as more negative VJG is applied, corresponding to a narrower channel as reverse bias increases the depletion regions on both sides of the channel. The electrical characteristics of the EFN device were simulated using a three-dimensional device simulator (Synopsys TCAD Sentaurus, MountainView, CA, USA) taking into account the fabrication process steps such as ion implantation and thermal annealing. The simulated electron density distribution at the cross section of the conducting channel in the n-doped region for VJG = −3 V and −15 V at VBG = −0.1 V and −0.7 V is shown in Figure 2b. It is clearly evident that the junction gate bias, VJG, has a significant impact on the size of the EFN for both VBG values. More negative VJG yields a compact, smaller, and more depleted channel. On the other B
DOI: 10.1021/acssensors.6b00096 ACS Sens. XXXX, XXX, XXX−XXX
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ACS Sensors hand, smaller negative VBG elongates the EFN vertically; observed more clearly in the VJG = −0.1 case. The effective diameter of the EFN (Deff) was extracted and thus defined by the full width at half-maximum (fwhm) of the electron density distribution for different gate bias. The simulated IDS−VDS characteristics were fitted to the measured characteristics to obtain a better estimate of the device Deff (Supporting Information). For VBG = −3 V, the estimated EFN Deff ranges from ∼29 to 56 nm corresponding to VJG = −0.8 V and −0.1 V, respectively. Note that the estimated Deff is not quite affected when the VBG is further reduced to −15 V (∼27−53 nm), implying that the back gate bias has more influence on the shape of the EFN compared to the size. The EFN device was mounted in a sealed gas-sensing chamber connected to the gas delivery system. Nitrogen was used as the carrier gas and for diluting the VOC flow into the chamber. The EFN response towards the VOC was quantified by the change in drain current, defined as ΔI/Io = (Io − IVOC)/ Io, where Io and IVOC are the measured drain currents (IDS) in nitrogen and during VOC exposure, respectively. IDS−VBG characteristics were recorded under nitrogen flow before and after injecting the VOC for different junction gate bias VJG. Sensor response of the EFN when operated at various VJG was calculated at a particular VBG. This is demonstrated in Figure 3a for three junction gate bias, VJG = −0.1, − 0.5, and −0.8 V for the case of 500 ppm of ethanol exposure. The EFN corresponding VJG = −0.8 V is a highly sensitive small channel which upon exposure to 500 ppm ethanol depletes the EFN almost completely such that IDS ≈ 0 nA. Thus, varying the back gate to further negative voltages beyond −15 V has no effect on the depleted EFN and IDS is saturated at ∼0 nA. Both ethanol and acetone adsorb on the silanol (Si-OH) group of SiO2 by hydrogen bonding.36−38 Ethanol is also likely to adsorb by weakly bonding to the siloxane sites (Si-O-Si) under high ethanol exposure.36 Adsorption of these VOCs induces a change in the surface charge density equivalent to that of localized negative charges on the SiO2 thus forming a molecular gate. This in turn leads to depletion in the electron accumulated conducting channel thus reducing the drain current upon ethanol/acetone exposure as observed in Figure 3. However, the sensor takes a long time to recover to its baseline once the VOC flow is shut off. Hence gentle heating of the device (ex situ) at 60 °C for 4 min is employed to accelerate desorption of the VOC molecules from the sensor surface. This is demonstrated in Figure 3b, showing complete recovery of the sensor after 765 ppm ethanol exposure. Another important feature of a sensor is the reproducibility of the sensor response in order to achieve a meaningful output. Reproducibility of the EFN sensor towards 1700 ppm of ethanol over 5 cycles is demonstrated in Figure 3c. It can be seen that the EFN shows good reproducibility with slight variation within acceptable limits. The response of varying dimensions of the EFN towards 1040 ppm ethanol and 1300 ppm acetone is depicted in Figure 4. It is evident from the figure that the sensor response increases as VJG and VBG become more negative corresponding to a smaller EFN. When the EFN is smaller, the channel current is more affected by the induced surface potential change due to the analyte adsorption. The enhanced response with more negative VJG EFN is a direct consequence of a smaller conducting channel. Therefore, the response of the sensor towards a particular concentration of target gas can be controlled electrostatically by tuning VJG and VBG. It is also
Figure 3. (a) Semilogarithmic plot of IDS − VBG characteristics of the EFN device in nitrogen (symbol curve) and under 500 ppm ethanol exposure (line curve). Curves represented by different colors correspond to device operated at VJG = −0.1 V, − 0.5 V, and −0.8 V. (b) Semilogarithmic IDS − VBG sensor characteristics depicting recovery of the sensor via gentle heating after 765 ppm ethanol exposure operated at VJG = −0.7 V. (c) Plot showing reproducibility of sensor response over 5 cycles: IDS as a function of time when exposed to 1700 ppm ethanol when operated at VDS = 1 V, VJG = −1.5 V, VBG = −5 V.
observed that the EFN sensor is comparatively more sensitive to ethanol than acetone. This is attributed to (i) hydroxyl group of ethanol, which is more likely to undergo stronger interactions with the Si-OH surface sites than acetone, and (ii) the additional weak bond of ethanol with the Si-O-Si sites.36,39 Figure 5 summarizes the device response for a wide range of EFN diameters and shapes corresponding to different VJG and VBG following exposure to varying concentrations of ethanol and acetone. The response of the EFN corresponding to varying VJG (constant VBG) is shown in Figure 5a,d and the effect of varying VBG (constant VJG) is shown in Figure 5b,e. The corresponding EFN Deff for the different VJG demonstrated in Figure 5a,d at VBG = −3 V ranges from 29 nm (VJG = −0.8 V) up to 52 nm (VJG = −0.2 V). For all EFN configurations, the sensor response increases as the device is exposed to higher C
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Figure 4. Heat map of the EFN response operated at various VJG and VBG towards (a) 1040 ppm ethanol and (b) 1300 ppm acetone.
Figure 5. Sensing performance of the EFN to varying ethanol and acetone exposures: Sensor response as a function of VOC concentration measured at (a,d) different VJG values at VBG = −3 V; and (b,e) different VBG values at VJG = −0.7 V, for ethanol and acetone, respectively. (c,f) EFN response as a function of time at VJG = −0.2 V and VBG = −14 V to various concentration exposures of ethanol and acetone, respectively.
from the IDS−VBG plot for different VJG) is considered as the noise level for the particular EFN configuration, referred to as Inoise. The detection limit (DL) for a particular EFN configuration was estimated as the minimum concentration at which the signal/noise ≥ 3, where signal refers to ΔI. The DL for ethanol is estimated to be ∼26 ppm and ∼40 ppm for acetone corresponding to the EFN at VJG = −0.8 V at VBG = −12 V. It is assumed that the EFN corresponding to all measured VBG and VJG saturates at 2030 ppm ethanol and 2800 ppm acetone exposure, as observed qualitatively. The EFN corresponding to a particular VJG and VBG is then assumed to be
VOC concentrations, and after a particular concentration, the change in response decreases finally leading to saturation. A sharp decrease in the EFN response is observed as the applied VJG increases corresponding to a wider EFN diameter. Similarly the sensor response is considerably enhanced for the EFN corresponding to more negative VBG. The ability to control the EFN response towards a particular concentration of target gas effectively leads to the large dynamic range of the sensor. The dynamic range in this work is defined as follows: The standard deviation in the measured device drain current for a particular VBG and VJG under nitrogen (extracted D
DOI: 10.1021/acssensors.6b00096 ACS Sens. XXXX, XXX, XXX−XXX
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Figure 6. Sensor response of the EFN device operated at different optimum gate bias to span the proposed dynamic range of (a) ∼26−2030 ppm for ethanol and (b) ∼40−2800 ppm for acetone. The horizontal lines denote the calculated dynamic range for the particular EFN configuration such that the sensor response was ≥0.2 throughout.
EFNs, corresponding to lesser negative VJG and VBG although have a relatively poor detection limit, exhibit almost linear response up to high concentrations. Therefore, the EFN can be effectively used to enhance the dynamic range with reasonable response and sensitivity throughout, by switching to the optimum VJG and VBG of operation. The tunable sensitivity of the EFN with respect to the junction gate and back gate bias is attributed to the size and shape of the conducting channel. For a smaller EFN corresponding to more negative VJG and VBG, the channel is almost completely affected and hence more sensitive to even small changes in the surface potential. This is the case corresponding to VJG = −0.8 V at VBG = −3 V as seen in Figure 5a,d and VJG = −0.7 at VBG = −10 V (Figure 5b,e). Here, the EFN response is observed to rise sharply for low concentration exposure and eventually saturates at the maximum response ∼1. The maximum response is a result of IVOC ≪ IO implying that the EFN is highly depleted. Thus, any further increase in the analyte concentration depletes the EFN almost completely and the resulting change in the drain current is negligible. The larger EFNs corresponding to the other VJG and more positive VBG are relatively less depleted (sensor response ≠ 1) when the surface is exposed to higher concentrations of the analyte. Hence these EFNs are comparatively less sensitive. However, in both cases, the EFN corresponding to a particular VJG and VBG saturates after a certain concentration and does not ideally respond to any further increase of the gas exposure as observed in Figures 5 and 6. The following two effects are proposed to be the underlying cause for the saturation: (i) complete coverage of target gas on the available adsorption sites on the surface and (ii) depleted EFN at a distance L > LD below the surface where LD refers to the Debye screening length of the device. The Debye screening length of the EFN device was calculated to be ∼10 nm using L D = √(εOϵSikBT /q2Nd) where ε is the dielectric constant; kB, Boltzmann constant; T, temperature; and Nd, donor density of the n-type region. For the case of VBG = −3 V, the height of the EFN was simulated to be in the range of 27−13 nm for VJG = −0.2 to −0.8 V. As mentioned before, increased adsorption of the VOCs on the molecular gate depletes the EFN, thereby pushing the conducting channel further into the bulk, farther from the molecular gate. Thus, the EFN gradually shifts away from the influence of the adsorbed molecules; beyond the Debye screening length. The dynamic detection range of the EFN was further investigated by scanning gate microscopy (SGM) measurements. SGM is an AFM based method where the AFM tip is used as a local gate to control the conductance in a field effect
saturated when the difference between the current for a particular concentration and that of the above-mentioned (saturated) concentrations is < Inoise (Supporting Information). Consider the plot corresponding to VJG = −0.8 V (brown color) in Figure 5a: although it is most sensitive in the low concentration regime, the response of the sensor saturates after ∼1000 ppm exposure to ethanol. This limits the maximum detection range for this ∼29 nm EFN corresponding to VBG = −3 V and VJG = −0.8 V. On the other hand, for the EFN operated at VJG = −0.6 V (∼31 nm), saturation begins for ∼1500 ppm ethanol exposure. Nevertheless, as observed in the figure, the wider EFN corresponding to VJG = −0.2 V (∼52 nm) is capable of detecting even higher ethanol concentrations until the response does not saturate. A similar effect is also observed upon changing the backgate voltage for a given VJG. The EFN operated in the −10 V VBG is highly sensitive with a steep slope for the response vs concentration plot up to ∼500 ppm ethanol (Figure 3b) and ∼750 ppm acetone (Figure 3e) after which the curve begins to saturate. However, the curve corresponding to VBG = 5 V exhibits an almost linear increase in the high concentration regime. A significant advantage for choosing the optimal VBG of device operation is that a broader detection range is achieved without compromising much on the sensitivity. This is because the sensor response changes more rapidly with varying junction gate bias when compared to that of the back gate. Figure 5c,f shows the response of the sensor operated at VJG = −0.2 V and VBG = −14 V when exposed to ethanol and acetone concentrations, respectively, as a function of time. Note that the sensor saturates above ∼1000 ppm ethanol and ∼1500 ppm acetone for VBG = −14 V even for a wider EFN (VJG = −0.2 V). The sensor responds rapidly to ethanol exposure when compared to acetone and reaches a characteristic equilibrium point corresponding to the concentration exposed. Based on the EFN response towards ethanol and acetone, a set of the optimum values of operation to span the proposed detection range are as depicted in Figure 6. The detection limit and the maximum concentration up to where the sensor can efficiently operate differ depending on the size and shape of the EFN and were estimated as discussed before. The minimum measurable concentration marked in the figure for each configuration was chosen according to the calculated DL (as defined before) and such that sensor response was ≥0.2, while the smaller EFNs, corresponding to more negative values of VJG and VBG, are highly sensitive in the low concentration regime and tend to saturate quickly with increasing analyte exposure (red curve in Figure 6). On the other hand, the relatively larger E
DOI: 10.1021/acssensors.6b00096 ACS Sens. XXXX, XXX, XXX−XXX
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results in tunable sensor response and large overall dynamic range using a single device. Further work aiming at selectivity among VOCs with the EFN sensor is currently underway. We believe that the EFN sensor, with its competitive sensing performance over a broad dynamic range coupled with low-cost fabrication and robustness, has promising potential for future commercialization.
transistor. In the context of this work, the surface potential change induced by analyte adsorption on the EFN surface is emulated by the field effect induced by the (biased) AFM tip on the EFN.40 Depending on the polarity of the tip voltage, the tip induces either a depletion (tip voltage 0 V) of electrons in the EFN channel. Figure 7 shows the sensor response and current
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EXPERIMENTAL METHODS
EFN Device Fabrication. The EFN transistors were fabricated in a semiconductor foundry (TowerJazz, Migdal Haemek, Israel) in a conventional and low-cost complementary metal−oxide semiconductor (CMOS) process with 4 masks to implant the different dopant regions for the channel, source-drain, and junction gate contacts. The actual doping densities, blanket arsenic of 4 × 1017 cm−3, junction gate boron of 2 × 1020 cm−3, and source-drain arsenic of 7 × 1019 cm−3, were determined post-fabrication by time-of-flight secondary ion mass spectrometry (TOF-SIMS). The measured doping density depth profiles served as input for the electrostatic simulations. Boron doped 8 in. SOI wafers with an initial doping density of 1.5 × 1014 cm2 and a thickness of 150 nm were used. The thickness of the buried SiO2 was 1.5 μm. The thermal SiO2 gate dielectric was formed at 1200 °C. The wafer was diced to 1 cm2 squares and Ti/Au contacts were formed by optical lithography and subsequent metal evaporation. Gas Sensing and Electrical Characterization. Sensing of VOCs was carried out in a controlled nitrogen (99.999% purity) atmosphere in a sealed metallic gas chamber connected to a gas dilution system. The target VOC saturated gas was generated using a bubbler system and diluted with nitrogen at controlled gas flow rates using flowmeters (Key Instruments Series FR2000 Acrylic Flowmeters) to generate different concentrations of the VOC in the chamber. IVOC was recorded after exposing the device to ethanol/acetone for 7 min. A photoionization detector (ppbRAE 3000, RAE Systems) was used as the reference sensor; connected to the sensing chamber in order to monitor the analyte concentration. The electrical characterization of the EFN device and the sensing measurements were performed using Agilent B1500A semiconductor device analyzer. Electrostatic Device Simulations. A three-dimensional finiteelement device simulator (Synopsys TCAD Sentaurus, MountainView, CA, USA) was used in order to solve the Poisson equation, and the hole and electron continuity equations for each mesh. The measured doping density depth profiles (TOF-SIMS) within the silicon served as input for the electrostatic simulations. Drift-diffusion transport model together with Boltzmann statistics were assumed throughout the device and the Masetti model for doping-dependent mobility was used in order to account for impurity scattering. The source-drain current was simulated for different configurations of backgate, sidegate, and drain voltages. Scanning Gate Microscopy. Scanning gate microscopy measurements were carried out with a commercial AFM (Dimension Edge, Bruker) inside a nitrogen glovebox with less than 1 ppm of H2O. Highly conductive cantilevers with Pt/Ir coating (PPP EFM, Nanosensors) were used for SGM. To avoid permanent and irreversible charging of the SiO2 top layer, the measurements were performed in intermittent contact mode (tapping) and not in contact mode. In order to minimize the height error of the AFM tip (
