SnO2 sensor for carbon monoxide detection

Sensors and Actuators B 177 (2013) 770–775

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Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb

Low temperature Pd/SnO2 sensor for carbon monoxide detection Beomseok Kim a , Yijiang Lu a , Ami Hannon b , M. Meyyappan c , Jing Li c,∗ a

ELORET Corporation at NASA Ames Research Center, Moffett Field, CA 94035, USA ERC Incorporated at NASA Ames Research Center, Moffett Field, CA 94035, USA c NASA Ames Research Center, Moffett Field, CA 94035, USA b

a r t i c l e

i n f o

Article history: Received 25 June 2012 Received in revised form 16 October 2012 Accepted 12 November 2012 Available online 1 December 2012 Keywords: Carbon monoxide sensor Low temperature sensing Palladium doped tin dioxide Hydroxypropyl cellulose

a b s t r a c t The development of a tin oxide nanoparticle based sensor for detecting carbon monoxide at low temperature, 60 ◦ C is presented. A combination of three approaches namely, (1) addition of a catalytic metal – 1.5% palladium, (2) optimization of organic binder content, and (3) a proper design of electrodes, leads to high sensitivity, excellent repeatability, and long-term stability in sensor response. The sensors have been tested in dry (<1% RH) and humid (>70% RH) conditions, and no humidity effect on the sensor performance was noticed. The sensors using 15% hydroxypropyl cellulose (HPC) mixed with Pd/SnO2 show sensitivity to CO gas in the parts per million (ppm) level of concentration, 5–10% repeatability in 6–18 ppm CO exposures, and active response for more than 40 days. In addition, the fatigued sensors were recoverable with a brief heating process. Published by Elsevier B.V.

1. Introduction The measurement of atmospheric pollutants and the detection of gas leaks in a closed environment are critical for human health and safety. Semiconducting metal oxide sensors have been under investigation extensively over the last few decades due to their potential in diverse applications. These sensors work based on the principle that when a metal oxide such as SnO2 is heated to a certain high temperature in air, oxygen is adsorbed on the crystal surface with a negative charge. Then donor electrons in the crystal surface are transferred to the adsorbed oxygen, leaving positive charges in a space charge layer. Thus, a surface potential is formed to serve as a potential barrier against electron flow. Inside the sensor, electric current flows through the conjunction parts (grain boundary) of SnO2 micro crystals. The adsorbed oxygen forms a potential barrier at grain boundaries which prevents carriers from moving freely, and the electrical resistance of the sensor is attributed to this potential barrier. In the presence of a reducing gas, the surface density of the negatively charged oxygen decreases, thus reducing the barrier height in the grain boundary and the sensor resistance [1]. Among the metal oxides, SnO2 is the most used material in gas sensing because it is stable and can be used for various applications [1–4] including detection of CO [5–16]. Oxide materials such as SnO2 respond to CO via oxidation of CO molecules by chemisorbed oxygen species to CO2 . Subsequently, considerable changes in the charge carrier density occur on the surface, leading to changes in

∗ Corresponding author. Tel.: +1 650 604 4352; fax: +1 650 604 5244. E-mail address: [email protected] (J. Li). 0925-4005/$ – see front matter. Published by Elsevier B.V. http://dx.doi.org/10.1016/j.snb.2012.11.020

resistivity as mentioned above. The SnO2 sensing layer is usually applied as a paste in a screen printing process followed by sintering. The substrates are provided with electrodes that enable measurement of the resistance of the sensing layer, and heaters to allow heating of the sensing layer in the range of 200–700 ◦ C [2]. Although SnO2 based CO gas sensor has already been well established and commercialized, the sensor technology still needs to be improved in terms of power consumption, size, and cost for industrial and environmental applications. Recently, power consumption of CO sensors has become an active topic in the context of applying this technology to hand-held and mobile devices. CO sensors without heating elements are ideal for such platforms. However, room temperature sensing of CO faces long-term stability problems and therefore, low temperature CO sensors with a reduction in power consumption are highly desirable. In addition, the stability of these sensors is crucial in consumer products, which demand no maintenance and long lifetime. To the best of our knowledge, there is no report on CO sensors for the detection of sub-10 ppm concentration featuring low power consumption with long lifetime [3–6]. Emerging nanomaterials such as carbon nanotubes, graphene and nanowires have been investigated [17–21] but have not achieved these requirements. We have realized combination of the above metrics in the present work by taking the following approaches: (1) incorporating additive metals that are crucial to improve sensitivity and selectivity [22–24] which also lower the operating temperature [7]; (2) mixing binder materials and optimizing the process for long-term stability [8]; and (3) choosing the electrode material and gap size carefully to maintain measurable target resistances for the selected sensing materials [9]. We describe here this low temperature CO sensor consisting

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Table 1 Control and A–H sensors mixed with various % of HPC. Sensor ID (wt./wt.%)

Control

A

B

C

D

E

F

G

H

HPC 1.5% Pd/SnO2 Repeated CO exposures

0 100 Sensor cracks

5 95 Weak response

10 90 Weak response

15 85 Strong reproducible response

20 80 Weak response

15 85 Replica of C

15 85 Replica of C

15 85 Replica of C

15 85 Replica of C

of a narrow gap interdigitated Au electrode (IDE) sensor array. Pddoped SnO2 with hydroxypropyl cellulose (HPC) has been prepared and deposited on the IDE as the sensing material. The sensor performance has been characterized in terms of response, effect of humidity and sensor stability. 2. Experimental work

The sensor base resistance remained under 10 s of k because only 8 and 12 ␮m gap sensors were used. The sensors under various humidity environments were tested using the Environics humidifier (S2040), which was connected to zero air (Airgas) at 0.8 L/min flow introduced into the chamber for an hour. The humidifier was calibrated using a commercial humidity sensor and unless specified, the relative humidity was 35–45% RH most of the time.

2.1. Preparation of sensor elements and sensor chips 3. Results and discussion 1.5% Pd/SnO2 powder was prepared by the following infiltration procedure [10]. SnO2 powder (Alfa Aesar, 99.996%) was mixed with PdCl2 (Aldrich Chemical Co.) solution and sonicated (XL-2000, Misonix, 10 W, 10 min) and the resulting solution was transferred into a crucible and sintered at 550 ◦ C for an hour. This heat treatment in air converted PdCl2 to PdO and removed the chlorine. The powder was recovered and pulverized. Then 5–20% of HPC was added (see Table 1) and a small quantity (0.5 mL) of deionized water was added and mixed. The paste was grinded with mortar and pestle for 10 min. Table 1 provides the information on composition for 8 sensor chips designated A–H. Preparation of the interdigitated electrodes on silicon wafer has been described in our previous publications [25–27]. A standard photolithography process was used to partially etch away the Au film and to define the pattern for the preparation of the sensor chips. The sensing materials were deposited manually with the aid of a pipette on the chips. Finally, the air-dried chips were heated at 300 ◦ C for 10 min and 60 ◦ C for 15 h subsequently. Fig. 1 shows the design layout and SEM image of a representative sensor chip along with the Pd/SnO2 nanocomposite. The chip shows six sensors each with a line space of 8, 12, 8, 12, 25 and 25 ␮m and in the present work, only four of these sensors with the 8 and 12 ␮m gaps have been used.

3.1. Characterization of sensor elements and sensors The morphology and structure of the nanostructures of Pd/SnO2 were characterized using a scanning electron microscope (FESEM, Hitachi S-4800) operating at 20 kV. The particle size of Pd/SnO2 varied from 10 to 50 nm (Fig. 1a) and the Pd/Sn weight ratio was 1.5%, as confirmed by the quantitative energy-dispersive X-ray spectroscopy (EDS, Oxford Instruments) analysis. Powder X-ray ˚ result diffraction (XRD, Scintag XGEN-4000, Cu K␣  = 1.5406 A) confirmed that Pd existed mainly in the form of PdO. Also, no trace amount of chloride was found by EDS and XRD.

2.2. Measurement of the sensor performance The sensor chips were tested using Keithley 2700 (Keithley Instruments, Inc.) data acquisition system. A Kapton heater (3 cm × 3 cm, Omega Engineering, Inc.) was installed on the back of the sensor chips providing constant 60 ◦ C temperature to the sensors. The heater was connected to the power supply. We have chosen 60 ◦ C to prevent any possible condensation of the water. The chips were wired to the data acquisition system and placed in the closed chamber (8.3 L, Thermo Fisher Scientific, Inc.). A commercial sensor, ToxiRAE pro (RAE Systems, Inc.) was also placed all the time in the chamber for calibration purpose which needs heating over 300 ◦ C. The sensors were preheated at least for 30 min for the temperature to reach equilibrium before any CO exposures. Then, the sensor array chips were exposed to CO by manual injection from the top gas inlet into the chamber with a syringe. 5 mL of 1% CO gas (in N2 , Scott Specialty Gases) was injected three times into the chamber at 10 min interval between injections. This amount is equivalent to 6 ppm CO in the commercial sensor. Then, the admitted CO gas was released by opening the chamber slightly. All measurements were done for four sensor chips simultaneously at 60 ◦ C in the chamber.

Fig. 1. (a) High magnification SEM image of Pd/SnO2 nanocomposite. (b) SEM image of sensing materials deposited on a silicon sensor chip and its design. From right to left, interdigitated line spaces are 8, 12, 8, 12, 25, and 25 ␮m respectively. In this article, only the first four narrower gap sensors have been used. (c) Schematic of (b).

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B. Kim et al. / Sensors and Actuators B 177 (2013) 770–775

10

(b)

8 6

Current (µA)

4

(a)

2 0 -2

G1

-4

G2

-6

G3

-8 -10

G4 -2

-1

0 Voltage (V)

1

2

Fig. 2. I–V curves of the sensor chip G. (a) Measured at room temperature. (b) Measured after 60 ◦ C heating for 30 min. The base resistance decreased from 1.3 ± 0.8 M to 59 ± 22 k with heating.

Fig. 2 shows representative current–voltage (I–V) curves of 15% HPC mixed Pd/SnO2 for the sensor chip G under two different temperatures. The measurements were from the first four narrower gap sensors of the sensor chip G (Fig. 1b). The sensor conductivity drastically increased when heated to 60 ◦ C for 30 min indicating that a sensor warm-up time is necessary for this duration to reach a certain optimum resistance. During this warm-up period, the sensor resistance reduced from M level to 10 s of k range. The resistance remained stable after 30 min as long as the temperature was maintained at 60 ◦ C. 3.2. Effect of HPC Composition Table 1 shows a summary of CO response results for various % of HPC mixed sensors. First, the 0% HPC control sample was tested repeatedly at 60 ◦ C and its base resistance increased in an unstable manner after heating/cooling several times, eventually reaching infinity (-circuit became open). The sensing element also showed visual cracks under the optical microscope. This is probably because of poor adhesion of sensing materials to the IDEs and thermal stress within the Pd/SnO2 sensing matrix. When the sensing layer and substrate, which have different thermal expansion coefficients, are subjected to thermal cycling, it can induce a stress in the coating, leading to cracks [11]. From the result of the control sample, we have concluded that the Pd/SnO2 nanocomposite alone has an inherent problem on long-term stability. Addition of binding materials is crucial for long-term stable operation at 60 ◦ C and we have chosen HPC which is a common binding material. Several previous studies have used HPC or organic binders, but for sensor operation at high temperatures of 330–500 ◦ C [9,12]. Thus, our HPC-mixed sensing materials are the first example of applying a binder for low temperature sensor operation. The HPC mixed sensing materials were applied onto 100 ␮m gap PCB board initially. However its base resistance was too big to be stabilized (>1 M). Also we have found that sensing materials on narrow gap Au IDEs (8 and 12 ␮m) were more sensitive than those on Al IDEs. Thus, all the results presented here are for microfabricated Au IDE silicon chips (Fig. 1b). Similar to our observations, Durrani reported that Au with bottom electrode configuration exhibited much higher responses compared to Al or Ag [9]. However, the temperature in Ref. [9] was 200 ◦ C and the CO concentration was 50,000 ppm. It is worth mentioning that our sensors for 6–18 ppm CO exposures at 60 ◦ C are more sensitive for low temperature operation. Thus, the sensors consume much lower power.

The four sensor chips from A to D were fabricated to find an optimal mixing ratio of HPC. The normalized sensor response, (Rt − R0 )/R0 , is used to compare the four sensor chips, where R0 is the initial sensor resistance and Rt is the resistance during the exposure. Among these four sensor chips, only 15% HPC (the sensor chip C) showed strong responses and long term stability, whereas the other sensor chips showed weak responses or instabilities under repeated CO exposures (Table 1). 15% of HPC is chosen to have low impact on the measurable resistance at low temperature, higher responses to CO and improve the binding between the gaps of Pd/SnO2 particles to extend the lifetime. Based on the results, the sensor chips from E to H were fabricated to replicate the sensor chip C and all five sensor chips (C, E, F, G, and H) were subjected to an identical heating procedure, 300 ◦ C for 10 min and 60 ◦ C for 15 h. In the remainder of this article, we would focus more on sensitivity, repeatability, and stability of these five sensors. 3.3. Sensitivity under dry and humid environments The Pd/SnO2 nanocomposite has been extensively studied for improving sensor response and selectivity toward CO detection. Based on extensive studies by Tadeev et al. [13], 1–3 wt.% Pd doped SnO2 shows the maximum sensitivity to CO in the temperature range of 25–100 ◦ C and therefore, we have fixed the Pd/SnO2 ratio at 1.5 wt.%. The exact role of the Pd in the oxidation reaction is not well understood. The observations suggest that the ambient water molecules may be necessary for CO oxidation via surface hydroxyl groups [14]. Also, Pd-doped sensors have been shown previously to have increased sensitivity in the presence of water compared to the case without water at an operating temperature of 300 ◦ C [15]. Significant relative CO response change has been observed under minimal relative humidity rise (5–15% RH or 15–30% RH) at 100 ◦ C [7]. All of the above observations were from Pd/SnO2 nanocomposite without the addition of HPC. We have performed sensor response tests of the sensor chip G at 60 ◦ C under low and high relative humidity (<1 or >70% RH) conditions. The base resistance changed from 247 k in dry air (<1% RH) to 132 k in wet air (>70% RH) purging. The absolute value of the resistance changed significantly in two different humid environments. However their relative changes of the resistance as sensor responses to CO exposures are comparable (Figs. 3 and 4). The calibration curves show consistent sensitivity, 0.0254 ± 0.0007 at low RH and 0.0246 ± 0.0003 at high RH, defined by the slope or (R/R)/(concentration) (see Figs. 3b and 4b). The sensitivity difference was less than 4% even under two extreme RH conditions. Obviously, we could not see any significant improvement of sensor sensitivity in either condition. Thus, we decided to use the normal humid environment in our laboratory without any further humidity control. This proves that the 15% HPC mixed Pd/SnO2 sensors have excellent consistency under either dry or humid environments. 3.4. Sensor repeatability The sensors showed strong sensor response of >0.7 for 18 ppm CO (Fig. 5). Also three distinctive plateaus could be seen with the three CO concentration levels (6, 12, and 18 ppm) by three injections (each was 5 mL of 1% CO in N2 ). Each response for the three serial CO injections is normalized and quantified individually due to slight baseline drift over the course of measurement (see Fig. 5). Then, we have generated calibration curves and their reproducibility studies for the 15% HPC mixed Pd/SnO2 sensors. The relative standard deviation (RSD) of repeated 18 ppm CO exposures of four sensors in the sensor chip H shows repeatability of 5–10% (Table 2) which is significant.

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Table 2 Sensor sensitivity, the slope or (R/R)/(concentration), derived from calibration curves generated from Fig. 5. (R/R)/(concentration)

H1

H2

H3

H4

Average

Std. dev.

RSDa (%)

CO injection 1 CO injection 2 CO injection 3 CO injection 4 CO injection 5

0.0251 0.0279 0.0285 0.0311 0.0287

0.0247 0.0323 0.0357 0.0379 0.0358

0.0241 0.0308 0.0346 0.0362 0.0344

0.0270 0.0311 0.0332 0.0357 0.0333

0.0252 0.0305 0.0330 0.0352 0.0331

0.0013 0.0019 0.0032 0.0029 0.0031

5.0 6.1 9.6 8.3 9.3

Relative standard deviations.

18

-0.4 12

-0.5 -0.6

6

-0.7 -0.8 0

10

Relative Response (Δ R/R0)

0.9

20

Time in min

30

40

0

0.6

0.5

G1 y = 0.0248x + 0.3141 R² = 0.925

0.4

G2 y = 0.0248x + 0.3141 R² = 0.925

0.3 0.2

G3 y = 0.026x + 0.2476 R² = 0.9353

0.1

G4 y = 0.0259x + 0.1107 R² = 0.9608

0

18

-0.4 -0.5

12

-0.6 -0.7

6

-0.8

-0.9

0

10

0.9

0.7

0

-0.3

(b)

0.8

24

-0.2

5

10

15

20

Time in min

0.6

0.5 0.4

G1 y = 0.0246x + 0.3507 R² = 0.9469

0.3

G2 y = 0.0246x + 0.3507 R² = 0.9469

0.2

G3 y = 0.0248x + 0.2993 R² = 0.9492

0.1

G4 y = 0.0242x + 0.1623 R² = 0.9675

0

5

10

The sensor chip C and its replicated sensors showed continuous responses for at least 3 weeks or more. The replicated sensors were exposed five times to 18 ppm CO per day for 3 weeks (Fig. 6b). The sensors were subjected to the established heating procedure of 300 ◦ C for 10 min and 60 ◦ C for 15 h and they showed high sensor response up to 0.8 in the beginning (Fig. 6). Then, the sensor response decreased and stabilized after a week. The replicated sensor chips (E, F, G, and H) also showed similar trends. The sensor response of the stabilized sensors was 0.1–0.3 at 18 ppm CO level. There are sensor-to-sensor variations currently, which may be attributed to the manual deposition process. For example, the initial sensor response of the sensor chips C, E, F, G, and H varies from 0.3 to 0.8. The sensor F was more rapidly deteriorated compared to the other sensors. 3.6. Recovery of the sensor sensitivity Fig. 7a shows response of the sensor chip C after 40 days of repeated CO exposure tests. The sensor response was still 0.2 at 18 ppm CO exposure. However, distinctive plateaus by three serial

15

20

25

Concentration (ppm) Fig. 4. The sensor chip G at 60 ◦ C, (a) at high RH (>70% RH) and (b) calibration curve obtained from (a).

CO injections were diminished. A brief heating (10 min at 300 ◦ C) was sufficient to recover the sensor sensitivity (Fig. 7b). After the short heating process, the responses increased drastically from 0.15 to 0.45 at 18 ppm CO exposure. The three plateaus also showed up

0

Relative Response (ΔR/R 0)

3.5. Long-term stability

0

40

0.7

Concentration (ppm) Fig. 3. The sensor chip G at 60 ◦ C, (a) at low RH (<1% RH), (b) calibration curve obtained from (a). In the curve-fit equation, y-axis is R/R0 , and x-axis is the gas concentration. R2 represents the quality of the curve fit.

30

(b)

0.8

0

25

20

CO Concentration in ppm

-0.3

-0.1

H1

-0.1

H2

-0.2

H3 H4

-0.3

30

24

18

-0.4 -0.5 -0.6

12

-0.7 -0.8

6

CO Concentration in ppm

24

-0.2

30

(a)

0

-0.1

-0.9

0.1

Relative Response (ΔR/R0)

Relative Response (Δ R/R0)

30

(a)

0

Relative Response (Δ R/R0)

0.1

CO Concentration in ppm

a

-0.9 -1

0

30

60

90

120

150 180 Time in min

210

240

270

300

0

Fig. 5. A typical CO response plot of the replicated sensor chip H. All sensor responses were measured in the chamber at 60 ◦ C. CO concentration in ppm was read from the commercial sensor heated to over 300 ◦ C.

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0.8

0.1

C E F

0.7

G

0.6

H

0.5

0.4 0.3 0.2 0.1 0

1

2

3

4

5

6

7

8

9

10

11

C E F

0.7

G

0.6

H

0.5

0.4 0.3

-0.3

12

-0.4 6

-0.5

0

10

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Days

Fig. 6. Summary of repeated measurements of 15% HPC mixed sensor chips (C and E–H) at 18 ppm CO exposure per (a) number of runs and (b) number of days. The sensor chip C had more prior repeated CO exposure history to find an optimal mixing ratio of HPC. All sensor responses were measured at 60 ◦ C in the chamber.

again with the three 6 ppm CO injections. It is likely that contaminants might be deposited on the sensor surface after a month and these were removable with the brief heating process. As mentioned previously, ambient water molecules may be necessary for Pd assisted CO oxidation. However, a competitive molecular water adsorption occurs, shielding the active binding sites for CO at room temperature. Eventually, the water molecules on the surface poison the sensors [7]. We have observed that the Pd/SnO2 sensors in general do not work at room temperature for days, which may be due to the occupied water molecules on the surface of Pd/SnO2 . Previous studies have also shown limitations of CO sensor response at room temperature within several hours after a heating process [3–6]. Thus, we have concluded that modest heating is necessary to prevent sensor poisoning from water modules for long-term operation. In this article, we have suggested 60 ◦ C as an operating temperature and a brief 300 ◦ C heat treatment to remove any contaminants from air onto the sensor surface. This slightly elevated temperature makes our sensor respond for a long period of time. Indeed, the HPC mixed sensors have showed longterm stable operation under the conditions without any physical cracks. Low operating temperature is also favorable to reduce power consumption, as well as to prevent structural transformation of metal oxide sensing materials. The operating temperature of conventional SnO2 sensors is between 200 and 700 ◦ C [2]. Matsuura and Takahata observed a growth in grain size in polycrystalline structures fabricated by sintering SnO2 powder, even after 20 days of operation at 550 ◦ C. The grain size growth during operation has

30

40

0

30

(b)

24

-0.1 18

-0.2 -0.3

12

-0.4 6

-0.5

0

10

0.1 0.0

20

0

-0.6

0.2

18

-0.2

0.1

Relative Response (Δ R/R0)

Relative Response (ΔR/R0)

0.8

(b)

24

-0.1

Time in min

12

Runs 0.9

0

-0.6

0

30

(a)

CO Concentration in ppm

(a)

Relative Response (Δ R/R0)

Relative Response (ΔR/R0)

0.9

20

Time in min

30

40

CO Concentration in ppm

774

0

Fig. 7. The sensor chip C responses at 18 ppm CO (three serial 6 ppm CO injections); (a) after 40-day extensive tests, and (b) after 300 ◦ C 10 min, 60 ◦ C 15 h. All sensor responses were measured at 60 ◦ C in the chamber. This was the 5th CO exposure. CO concentration in ppm read from the commercial sensor heated to over 300 ◦ C.

been reported to be minimized for a sensor operating temperature below 350 ◦ C [16]. 4. Summary We have demonstrated a low temperature sensor for CO detection using Pd/SnO2 nanocomposite synthesized by a simple infiltration process. Addition of a HPC binder shows several improvements in sensor performance. The optimized 15% HPCPd/SnO2 sensors show high sensitivity, excellent repeatability, and long-term stability at 60 ◦ C. The sensors also exhibit excellent consistency under either dry or humid environments. We have shown that the fatigued sensors are recoverable with a brief heating process. Future work will focus on using various binders to minimize baseline drift and develop processes to reduce sensor-to-sensor variations. Acknowledgements This work was funded by the U.S. Department of Homeland Security, HSARPA Cell-All Program via a NASA-DHS interagency agreement (IAA: HSHQDC-08-X-00870). The work conducted by the employees of ELORET Corporation was supported through a subcontract to the University Affiliated Research Center prime NASA contract number NAS2-03144 operated by the University of California at Santa Cruz. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.snb.2012.11.020.

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Biographies Beomseok Kim is a research scientist at ELORET Corporation, which is located at NASA Ames Research Center, Moffett Field, CA. He received his BS degree from Hanyang University in Seoul, South Korea in 1997, and his Ph.D. from Purdue University at West Lafayette, IN in 2004. His research interests include surface chemistry, optical and electrical properties of nanostructured materials. Yijiang Lu is a research scientist at ELORET Corporation in NASA Ames Research Center and has over 20 years experience in analytical chemistry and instrumentation, chemical sensor and gas/vapor dilution, mixing and simulation systems. His expertise is in chemical sensor development, prototype of electronic nose development, system integration engineering (design and built a first nanotechnology based flight unit for space demonstration), GC/MS analysis of chemical and biological samples, materials properties characterization and computer programming for signal processing. Ami Hannon received her Masters degree in Chemical Engineering from San Jose State University, USA, in 2010. Her current research interests are synthesis of nanowires and metal oxides, functionalizing of CNTs and their applications to gas sensors and solar cells. M. Meyyappan is Chief Scientist for Exploration Technology at NASA Ames Research Center. His research interests include nanomaterials such as carbon nanotubes, graphene and inorganic nanowires and application development in electronics, sensors and instrumentation. He is a Fellow of IEEE, ECS, AVS, MRS and AIChE and has received numerous awards for his contributions to nanotechnology. Jing Li is a Principle Investigator at NASA Ames Research Center and has established herself as an internationally recognized expert in chemical sensors applying nanotechnologies. She has over 22 years of experience in R&D and commercialization of chemical sensors and intelligent sensing systems. She has published 40 technical papers, 2 book chapters and has 9 US Patents awarded, all related to chemical sensors and signal processing. She is a past chair of Sensor Division and a board member in the Electrochemical Society (ECS).