Synthesis of sele heating gas sensor based on tin oxide nanowire material

MINISTRY OF EDUCATION & TRAINING HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY INTERNATIONAL TRAINING INSTITUTE FOR MATERIALS SCIENCE - HÀ MINH TÂN SYNTHESIS OF SELF-HEATING GAS SENSOR BASED ON TIN OXIDE NANOWIRE MATERIAL MASTER’S THESIS ELECTRONIC MATERIALS SCIENCE AND ENGINEERING Hanoi - October 2014 HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY INTERNATIONAL TRAINING INSTITUTE FOR MATERIALS SCIENCE MASTER’S THESIS Synthesis of self-heating gas sensor based on tin oxide nanowire material HA MINH TAN Student ID: CB120169 Advisors: PhD NGUYEN VAN DUY A thesis submitted to Ta Quang Buu library, Hanoi University of Science and Technology in partial fulfillment of the requirement for the degree of Master of Science HA NOI – OCTOBER 2014 MASTER THESIS Declaration of Originality “I, the candidate, hereby certify that the thesis comprises only my original work except where indicated; due acknowledgment has been made in the text to all materials used.” Candidate’s signature Ha Minh Tan The Comment of Advisor Advisor’s signature Nguyen Van Duy HA MINH TAN i MASTER THESIS HA MINH TAN ii MASTER THESIS Acknowledgements Firstly, I would like to express the deepest appreciation to my supervisors, Professor Nguyen Van Hieu and PhD Nguyen Van Duy for guiding me to my project They gave me valuable guidance and advice Besides, I would like to thank to all members in Gas Sensor Group at ITIMS for helping me during all the time I my work Finally, I thank to all my friends and family for caring and inspiring me all the time I project HA MINH TAN iii MASTER THESIS Table of Contents Declaration of Originality The Comment of Advisor Acknowledgements Table of Contents Table of Figures List of Tables Acronyms and Abbreviations 10 INTRODUCTION 1 Study motivation Objective of the study New features of the thesis Methodology CHAPTER I – OVERVIEW I.1 Brief history of the evolution of gas sensors I.2 Brief knowledge about gas sensing devices and SnO2 nanowires materials I.2.1 Microstructure and sensing mechanism of SnO2 nanowires I.2.2 Characteristics of gas sensing devices 13 I.3 Joule heating and its application in gas sensing devices 17 I.3.1 Joule heating and heat transfer 17 I.3.2 Overview about gas sensing devices based on self-heating effect 20 I.4 Research’s approach 25 CHAPTER II – II.1 EXPERIMENTAL 26 Preparation of Interdigitated Electrode (IDE) 26 II.1.1 Designing of electrodes 26 II.1.2 Electrode fabrication 26 II.2 SnO2 nanowires growth 28 II.2.1 Equipment, apparatus and chemical preparation 28 II.2.2 Growth procedure of SnO2 NWs at 800 oC 28 II.3 Material characterization 29 II.4 Gas sensing properties investigation 30 II.4.1 HA MINH TAN Measurement system 30 iv MASTER THESIS II.4.2 CHAPTER III – Gas sensing characterization of sensor using self-heating effect 33 RESULTS AND DISCUSSION 34 III.1 Structure and morphology of grown nanowires 34 III.2 Existence of self-heating effect of nanowire networked sensors 37 III.3 Gas sensing performance comparison between sensors heated by external heater and self-heating 41 III.3.1 Sample b1 44 III.3.2 Sample b2 50 III.3.3 Sample b3 55 III.3.4 Sample b4 60 III.3.5 Sample b5 65 III.4 Evaluation of working temperature of self-heated sensor using gas mixing measurement and thermal emission microscopy 70 III.4.1 Gas mixing measurement 70 III.4.2 Temperature evaluation using thermal emission microscope 72 III.5 Self-heating rate 75 III.6 Capability of gas sensor using self-heating effect 77 III.6.1 Selectivity 77 III.6.2 Stability and repeatability 79 III.6.3 Significance of self-heating effect in gas sensing applications 79 CONCLUSION 82 References 83 HA MINH TAN v MASTER THESIS Table of Figures Figure I.1: a) Davey’s lamp – b) Jiro Tsuji and his gas detector using ligh-wave interference – c) Johnson – Williams’s founder Figure I.2: The schematic of the platinum catalyst type of gas sensor _ Figure I.3: a) The structure of resistive gas sensor – b) The working principle using voltage meter, Vh, Vc, Vout, and RL, which represent the heating voltage, circuit voltage, signal voltage, and load resistor, respectively – c) The working principle using current meter _ Figure I.4: a, b) The sensors use thin film material on the silicon substrate – b) The cross at the center of sensor is the micro heater – c) Sensor after packaged Figure I.5: a) the nanowires are printed on the substrate – b) the first integrated nanowire sensor circuitry _ Figure I.6: Microstructure of tin oxide _ Figure I.7: The transform of Oxygen on the surface of SnO2 NWs _ Figure I.8: Physisorption and chemisorption steps involved in forming oxygen ion species on SnO surface 10 Figure I.9: The depletion zone at the surface of nanowires and nanobelts _ 10 Figure I.10: SnO2 is exposed in NO2 gas: low temperature (a), high temperature (b) _ 11 Figure I.11: Direct contact among NW and metal electrode 11 Figure I.12: NWs junctions and potential barrier at the junction _ 12 Figure I.13: Equivalent circuit of total resistance of one networked nanowires _ 12 Figure I.14: VLS mechanism 13 Figure I.15: Changing of resistance of sensor when gas is in 14 Figure I.16: An example graph of the sensitivity versus temperature _ 16 Figure I.17: Heat losses to metal contacts, environment gas and irradiation[1] _ 18 Figure I.18: Model of a gas sensor using micro heater as thermal source[2] _ 20 Figure I.19: a) power and b) temperature of sensor depend on applied AC voltage[5] _ 21 Figure I.20: Temperature versus provided power[5] _ 21 Figure I.21: SEM image of a SnO2 nanowire connected to two Pt microelectrodes fabricated with focused ion beam[6] _ 22 Figure I.22: The sensor setup and principal thermal losses in the suspended nanowire heated by the Joule heat SEM image of the suspended SnO2 chemiresistor[13] 22 Figure I.23: Heat loss depends on temperature and dimension of the nanowires[13] 23 Figure I.24: Schematic description of surface modification by self-heating of a nanowire: nanoparticles were formed by hydrothermal reactionvia Joule heating of a Si nanowires [12] _ 24 Figure I.25: Network structured nanowire on the chip _ 25 Figure II.1: The structure of the interdigitated electrode array 26 Figure II.2: Processes to fabricate the IDE _ 27 Figure II.3: The CVD system 28 Figure II.4: Thermal cycle for fabrication SnO2 _ 29 HA MINH TAN vi MASTER THESIS Figure II.5: The chamber for gas sensing investigation 30 Figure II.6: Schematic of gas-mixing part _ 31 Figure II.7: The SourceMeter, Keithley model K2602A _ 31 Figure II.8: Flow control of the resistance measurement by loading constant power 32 Figure III.1: Image of samples and be marked from b1 to b5 ( left to right) 34 Figure III.2: XRD pattern of SnO2 NWs at 800 oC 34 Figure III.3: Typical FE-SEM images of junction structured tin oxide nanowires oh the 60 μm spacing PIEs a) sample b1 – b) sample b2 – c, d) sample b3 – e, f) sample b4 – g, h) sample b5 35 Figure III.4: The higher magnification SEM image of samples _ 36 Figure III.5: The I-V curve of sample b2 _ 37 Figure III.6: a) The dependence of sensor resistance on temperature and b) loaded power _ 38 Figure III.7: The response of sample b3 to 2.5 ppm NO2 a)using external heater b) and loading constant electrical power _ 39 Figure III.8: Response time and recovery time of sample b3 to 2.5 ppm NO a)using external heater b)and loading constant electrical power _ 40 Figure III.9: The resistance of samples at various temperatures _ 42 Figure III.10: Schematics of equivalent circuit of samples with different number of nanowires junction _ 43 Figure III.11: Resistance of sample b1 in the presence of 2.5 ppm, ppm, 10 ppm and 20 ppm of NO gas using external heater and by loading constant powers a) 150 oC – a’) 16 mW – b) 200 oC – b’) 18 mW – c) 250 oC – c’) 20 mW– d) 300 oC – d’) 22 mW _ 44 Figure III.12: The base resistance of sample b1, a) using external heater, b) using self-heating and c) linear fitting of resistance using external heater and self-heating effect _ 45 Figure III.13: The response of sample b1 using external heater and self-heating 46 Figure III.14: 3D graphs in different angles of response of sample b1 to various concentrations of NO gas at several temperature or loading power _ 47 Figure III.15: Response time and recovery time of sample b1 to 2.5 ppm NO a)using external heater b)and loading constant electrical power _ 47 Figure III.16: Exponential fitting of a) response time and b) recovery time of sample b1 using external heater and self-heating effect 48 Figure III.17: Relation between loading power (mW) and temperature ( oC) of sample b1 by four comparing methods: base resistance, response, response time and recovery time _ 49 Figure III.18: Resistance of sample b2 in the presence of 2.5 ppm, ppm, 10 ppm and 20 ppm of NO2 gas using external heater and by loading constant powers a) 150 oC – a’) 20 mW – b) 200 oC – b’) 25 mW – c) 250 oC – c’) 30 mW– d) 300 oC – d’) 35 mW _ 50 Figure III.19: The base resistance of sample b2, a) using external heater, b) using self-heating and c) linear fitting of resistance using external heater and self-heating effect _ 51 Figure III.20: The response of sample b2 using external heater and self-heating 52 HA MINH TAN vii MASTER THESIS Figure III.21: Response time and recovery time of sample b2 to 2.5 ppm NO a)using external heater b)and loading constant electrical power _ 52 Figure III.22: Exponential fitting of a) response time and b) recovery time of sample b2 using external heater and self-heating effect 53 Figure III.23: Relation between loading power (mW) and temperature ( oC) of sample b2 by four comparing methods: base resistance, response time and recovery time _ 53 Figure III.24: Resistance of sample b3 in the presence of 2.5 ppm, ppm, 10 ppm and 20 ppm of NO gas using external heater and by loading constant powers a) 150 oC – a’) 30 mW – b) 200 oC – b’) 40 mW – c) 250 oC – c’) 50 mW– d) 300 oC – d’) 60 mW _ 55 Figure III.25: The base resistance of sample b3, a) using external heater, b) using self-heating and c) linear fitting of resistance using external heater and self-heating effect _ 56 Figure III.26: The response of sample b3 using external heater and self-heating 57 Figure III.27: 3D graphs in different angles of response of sample b3 to various concentrations of NO gas at several temperature or loading power _ 57 Figure III.28: Response time and recovery time of sample b3 to 2.5 ppm NO a)using external heater b)and loading constant electrical power _ 58 Figure III.29: Exponential fitting of a) response time and b) recovery time of sample b3 using external heater and self-heating effect 58 Figure III.30: Relation between loading power (mW) and temperature ( oC) of sample b3 by four comparing methods: base resistance, response, response time and recovery time _ 59 Figure III.31: Resistance of sample b4 in the presence of 2.5 ppm, ppm, 10 ppm and 20 ppm of NO2 gas using external heater and by loading constant powers a) 150 oC – a’) 90 mW – b) 200 oC – b’) 120 mW – c) 250 oC – c’) 150 mW– d) 300 oC – d’) 180 mW _ 60 Figure III.32: The base resistance of sample b4, a) using external heater, b) using self-heating and c) linear fitting of resistance using external heater and self-heating effect _ 61 Figure III.33: The response of sample b4 using external heater and self-heating 62 Figure III.34: Response time and recovery time of sample b4 to 2.5 ppm NO a)using external heater b)and loading constant electrical power _ 63 Figure III.35: Exponential fitting of a) response time and b) recovery time of sample b4 using external heater and self-heating effect 63 Figure III.36: Relation between loading power (mW) and temperature ( oC) of sample b4 by four comparing methods: base resistance, response time and recovery time 64 Figure III.37: Resistance of sample b1 in the presence of 2.5 ppm, ppm, 10 ppm and 20 ppm of NO2 gas using external heater and by loading constant powers a) 150 oC – a’) 300 mW – b) 200 oC – b’) 350 mW – c) 250 oC – c’) 400 mW– d) 300 oC – d’) 450 mW _ 65 Figure III.38: The base resistance of sample b5, a) using external heater, b) using self-heating and c) linear fitting of resistance using external heater and self-heating effect _ 66 Figure III.39: The response of sample b5 using external heater and self-heating 67 HA MINH TAN viii MASTER THESIS III.4 Evaluation of working temperature of self-heated sensor using gas mixing measurement and thermal emission microscopy III.4.1 Gas mixing measurement In the previous section, we considered three methods based on base resistance, response, response time and recovery time to estimate the loading power to each sample to reach desired actual temperature or external heater temperature However, we must collect all data from these methods, compare them carefully then result a conclusion because not at all of them are always exactly Luckily, there is another method to determine the actual temperature depended on loading power, that is measuring the response of sample to a mixed gas This mixture included an oxidant gas and a reducing gas, specifically in my thesis, 2.5 ppm NO2 and 100 ppm NH3 were used in the investigation NO2 is an oxidant gas; the resistance of the sample will increase in presence of NO2 However, NH3 is a reducing gas, and the resistance will fall when the sample senses this gas The question is the resistance will rise or fall in the presence of this mixture? 2.4k 300 oC 320 oC Resistance (Ohm) 2.2k Sample b3 external heater 340 oC 2.0k 360 oC 1.8k 1.6k 380 oC 400 oC 1.4k 1.2k 420 oC 1.0k 800.0 -500 500 1000 1500 2000 2500 3000 3500 4000 Time (second) Figure III.44: The response of sample b3 to mixed gases at different temperature using external heater HA MINH TAN – ITIMS – K2012 70 MASTER THESIS The answer is that it is up to actual temperature and fraction of gas If we keep a constant fraction of each gas, the used sample is b3, then temperature will be the only factor affect the response of the sample The response of the sample to NO2 is high at low temperature, and it will decrease when temperature rises On the contrary, the response of NH3 will increase when temperature rises Therefore, at the lower temperatures, the resistance of sample will increase when the sample is exposed in mixed gases as shown in Figure III.44 When rising temperature, the response decreases Finally, the resistance fall when temperature is 420 oC 1k Sample b3 self heating 50 mW 54 mW Resistance (Ohm) 900 59 mW 63 mW 800 67 mW 71 mW 75 mW 700 79 mW 600 500 500 1000 1500 2000 2500 3000 3500 Time (second) Figure III.45: The response of sample b3 to mixed gases using self-heating effect at different loading powers Next, we consider the response of sample b3 to this mixture of gas using selfheating effect at different loading power as shown in Figure III.45 The trend of response and resistance is the same case using external heater, and when the loading power is 79 mW, the resistance of the sample is down while the sample is exposed to mixed gases Thus, we can give a conclusion that in case of sample b3, loading to it 79 mW of electric power will drive it up to 420 oC For more detail, we continue to investigate the response of sample b3 in case using both self-heating effect and external heater like illustrated in Figure III.46 The HA MINH TAN – ITIMS – K2012 71 MASTER THESIS external heater warmed up the sample to 300 oC, then loading power to the sample from mW After each cycle, the loading power increased mW Finally, the resistance of the sample fall when it is exposed to mixture at 21 mW of loading power Afterall, we have two equations, which are expressed the relation between loading power and temperature: 300o C  21mW  420 o C  300o C  58mW  o 79mW  420 C  This equation shows us that the corresponding power and temperature obtained from this method are suitable to the previous results obtained from fitting methods 3.0k Resistance (Ohm) 2.5k mW mW Sample b3 external heater 300 oC + self heating mW 13 mW 17 mW 2.0k 21 mW 1.5k 1.0k -500 500 1000 1500 2000 2500 3000 3500 4000 Time (second) Figure III.46: The response of sample b3 to mixed gases using external heater at different loading powers and 300 oC background using external heater III.4.2 Temperature evaluation using thermal emission microscope Thermal (or infrared) emission microscopy is a tool for microelectronic temperature measurement and failure analysis It is a non-contact measurement technique which utilises naturally emitted infrared radiation from a sample It can measure the temperature of very small spot (few micrometers) The measurement was HA MINH TAN – ITIMS – K2012 72 MASTER THESIS taken by applying incremental voltage to sample b2 while measuring the thermal emission energy and mapping them as images Then, applying the emissivity of tin oxide material is 0.5, we obtained the temperature images of the sample as shown in 40 60 80 100 120 140 160 180 200 220 240 50 44.8 Power versus Temperature of sample b2 41.3 37.8 40 Power (mW) 260 34.5 31.3 28.1 30 20 10 2.2 3.3 4.7 6.3 8.1 10.1 12.2 14.5 16.9 19.5 22.3 25.1 4045 53 61 72 85 98 114 131.5 145 159 173 185 199.5 214.5 227.5 244 253 Temperature (oC) Figure III.47: The loading power to sample b2 versus measured temperature; and the temperature mapping of the sample at 40, 114, 199.5 and 253 oC According to Figure III.47, the loading power is linear proportional to actual temperature as initial assuming Furthermore, the heated area is very small whereas the other area remains room temperature It is a big significance in making a complete gas sensor device because the heat from the sensing part will not impact other parts of sensors such as wires, ICs or package Therefore, the sensors will work more stable HA MINH TAN – ITIMS – K2012 73 MASTER THESIS and reliable Additionally, the size of the sensors also be reduced by saving the space for heat insulating 50m Base resistance Sample b2 Response time Recovery time Thermal emission Power (W) 40m 30m 20m 10m 100 120 140 160 180 200 220 240 Temperature (oC) Figure III.48: The relation between loading power to sample b2 and temperature obtained by four methods: response time, themal emission, base resistance and recovery time The result from thermal emission microscopy methods also is conformable to other ones As demonstrated in Figure III.48, the loading power versus temperature curve of thermal emission methods is parallel to response time’s one, with adjacent is about mW It encourages the exactness of fitting response time method, especially in case lacking of thermal emission microscopy equipment in local workstation HA MINH TAN – ITIMS – K2012 74 MASTER THESIS III.5 Self-heating rate In this section, we tend to find what is the best sample which suits to make a gas sensor device using self-heating effect It is based on overall performance of sample such as response, response time, recovery time and power consumption Considering the response, sample b2 gives the best response About the response time and recovery time, there is no sample proved better And the last factor is power consumption that we will investigate clearly Now considering the relation between loading power and actual temperature of samples using fitting recovery time which is Power (mW) the most reliable methods, illustrated in Figure III.49 650 600 550 500 450 400 350 300 250 200 150 100 50 b1 b3 b5 b2 b4 150 200 250 300 o Temperature ( C) Figure III.49: The relation between loading power and actual temperature of samples from b1 to b5 using fitting recovery time As seen in the Figure III.49, the lower resistance sample need higher power to heat it up It is easy to explain by the model parallel circuit as mentioned above Assumes a constant voltage are kept between two electrodes, and k1 pair of junctioned nanowires have total resistance R1=r/k1 used a power 𝑃1 = 𝑖 𝑟/𝑘1 , where i is current and r is resistance of one pair of nanowires, to heat it up to temperature T In the bigger parallel circuit which includes k2 pairs of junction (> k1), the total resistance is R2=r/k2 (smaller than above case) and the total current is k2i/k1 , so the used power that is HA MINH TAN – ITIMS – K2012 75 MASTER THESIS 𝑘2 𝑖 𝑟 𝑘2 𝑖 𝑟 𝑘2 𝑅1 𝑃2 = ( ) = 𝑃1 = 𝑃 = 𝑘1 𝑘2 𝑘1 𝑅2 𝑘1 (Equation 6) such power need to heat the sample up temperature T Therefore, the higher resistance sample requires smaller power to heat up to the same temperature From the relation between loading power and actual temperature of all samples and obtained from all methods, Table was built to demonstrate the conversation between temperature and loading power or self-heating rate of samples According to this table, from sample b1 to sample b5, higher power (in mW) needed to load to sample to rise oC That mean the smaller resistance sample gives better self-heating effect by the higher converted rate from electric energy to thermal energy In conclusion, the higher resistance samples will give better self-heating performance than lower resistance samples (Clue 9) Sample Base Resistance Response Response time Recovery time b1 0.02308 0.04283 0.025 0.03333 b2 0.07133 0.185 0.135 b3 0.35189 0.3935 0.215 0.235 b4 0.59662 0.785 0.725 b5 0.68081 0.84 2.175 1.925 Table 2: Self-heating rate of samples And finally, we have chosen sample b2 to continue to investigate the gas sensing characteristic using self-heating effect in the next section because it satisfies two conditions: higher response and low power consumption HA MINH TAN – ITIMS – K2012 76 MASTER THESIS III.6 Capability of gas sensor using self-heating effect The sample is suitable to be a gas sensor device when it satisfies some requirements such as high sensitivity, fast response and recovery, high selective, stable and in this thesis, also low power consumption is required Thus, the sample b2 was used to test its ability to embed in gas sensor application III.6.1 Selectivity Firstly, we consider the selectivity of sample b2 to various gases like H2, NH3, H2S, Ethanol and NO2 According to Figure III.50, the sample gives a very low response to reduction gases; meanwhile, it senses very much to NO2 gas It is explained by the optimal working temperature, NO2 gas gives the better response at lower temperatures than 300 oC, but the reducing gases only be activated at high temperatures Therefore, self-heating effect can use to control the selectivity of gas sensor Loading low power to the sensor will drive it sense to oxidant gases such as NO2 and loading higher power to the sensor will make it able to sense reducing gases, even to detect reducing gas in mixture of oxidant and reducing gases, as shown in Figure III.45 NO2 2.80k Resistance (Ohm) 2.60k 2.40k 2.20k 2.00k 1.80k 1.60k 1.40k H2 NH3 H2S C2H5OH 1.20k Time (second) Figure III.50: The response of loaded 20 mW sample b2 to several gases: H2, NH3, H2S, Ethanol and NO2 HA MINH TAN – ITIMS – K2012 77 MASTER THESIS Next, we will consider the ability of this sample to sense the reducing gases such as H2, NH3, H2S and Ethanol using self-heating effect at high power 40 mW and Resistance (Ohm) 50 mW as shown in Figure III.51 and Figure III.52 1.8k 1.7k 1.6k 1.5k 1.4k 1.3k 1.8k 1.7k 1.6k 1.5k 1.4k 1.3k 1.8k 1.7k 1.6k 1.5k 1.4k 1.3k 1.8k 1.7k 1.6k 1.5k 1.4k 1.3k H2 50 ppm 100 ppm 50 ppm 200 ppm 100 ppm 200 ppm NH3 100 ppm 100 ppm 200 ppm 200 ppm 400 ppm 400 ppm H2 S 50 ppm 100 ppm 50 ppm 200 ppm 100 ppm 200 ppm Ethanol 100 ppm 200 ppm 100 200 100 ppm 400 ppm 400 500 700 800 40 mW 200 ppm 100 200 400 ppm 400 500 2.2k 2.0k 1.8k 1.6k 1.4k 1.2k 2.2k 2.0k 1.8k 1.6k 1.4k 1.2k 2.2k 2.0k 1.8k 1.6k 1.4k 1.2k 2.2k 2.0k 1.8k 1.6k 1.4k 1.2k 700 800 50 mW Time (second) Figure III.51: The response of sample b2 to various gases H2, NH3, H2S and Ethanol at different loading power (left side – 40 mW, right side – 50 mW) Response 1.55 1.50 H2 1.45 NH3 1.40 H2S 1.35 Ethanol 1.30 1.25 1.20 1.15 1.10 1.05 1.00 20 40 50 Power (mW) Figure III.52: The response of sample b2 to reducing gases versus loading power HA MINH TAN – ITIMS – K2012 78 MASTER THESIS According to Figure III.51 and Figure III.52, Hydrogen always is the worst sensitive, meanwhile, Ethanol give the best response From 20 mW to 40 mW, the response increased very slow, but after 40 mW (over 300 oC), the response increased very fast because this is active temperature range of reducing gas III.6.2 Stability and repeatability Other parameters judgment quality of a gas sensor device that is repeatability of measurements in the same condition at different times and stability during long time working Figure III.53 shown the response of sample b2 while loading 20 mW to 2.5 ppm NO2 There is total ten cycles gas in and gas out, and it is present very good repeatability in response, response time and recovery time The base resistances all are about 1.3 kΩ, and the top resistances all are about 2.74 kΩ, which give the response is about 2.1 time Resistance (Ohm) 3.0k Sample b2 - 20 mW - NO2 2.5 ppm 2.5k 2.0k 1.5k 1.0k 200 600 1000 1400 1800 2200 2600 3000 3400 3800 4200 Time (second) Figure III.53: The repeatability of sample b2 to 2.5 ppm NO2 using self-heating at 20 mW III.6.3 Significance of self-heating effect in gas sensing applications Self-heating effect brings a lot of advantages to the fabrication of gas sensor devices It helps the development and embedding of gas sensors in applications Firstly, the simple fabrication of electrodes and growth material on substrate decrease HA MINH TAN – ITIMS – K2012 79 MASTER THESIS price of gas sensor devices As exposed in Table 3, the cost for an IDE with microheater is high in range from 20 USD to 100 USD, and they not include sensing material Meanwhile, an sensing part fabricated in this thesis have a estimated price under USD Heraeus Sensor Nak-Jin Choi et al [15] Microhotplate Kebaili Corporation In this thesis Power to get 200 oC 600 mW 150 mW 25 mW 30 mW Price 20 USD Unknown 100 USD Under USD Products Table 3: Compare power consumption and price of some electrodes Gas sensors based on self-heating effect consume very low power It opens a new way to deploy gas sensor devices in application Almost gas sensor device work as stationary, or heavy-handedly device in emergency cases as illustrated in Figure III.54a, because they require large amount of energy to heat up the external heater However, the gas sensor devices based on self-heating effect can work independently in long time just with a little battery like Figure III.54b Figure III.54: A small and long lasting gas sensor device fed by a battery HA MINH TAN – ITIMS – K2012 80 MASTER THESIS Doing a simple calculation, a sensing part will consume 20 mW (in case of my thesis) If it is fed by a 3400 mAh Li ion battery then the sensor will last after 630 hours (near 27 days) Imagine if we can reduce the power consumption of the sensing part to few mW, the gas sensor can work for months Those are impressionable number and imply abilities to integrate gas sensor in mobile phone, or in-car environment control system and so on, with out influence the energy system or overall performance of mobile phone or car If we combine this gas sensor using self-heating effect with a solar cell, we will get an unattendant gas sensor device A solar panel has area x cm2 can product 570 mW, and this power is excessive to provide to a gas sensor Imagine that we can deploy gas sensors with solar cells easily in cities to control the environment of urban zone Furthermore, this device can play an important role in early forest fire detect system In jungle, it is hard to provide electrical network or recharge or replace every battery of gas sensor devices Thus, the low power consumption gas sensors devices with solar cells will be the best solution for that HA MINH TAN – ITIMS – K2012 81 MASTER THESIS CONCLUSION In this thesis, the networked nanowires structure was grown on the thermal isolated glass substrate to form gas sensors with different base resistance The gas sensing properties of the fabricated sensors were investigated to nitrogen oxide gas From those results, the self-heating effect was proved by the proportional between constant power loading to sample and temperature of the external heater Furthermore, the correlation of loading power and working temperature was investigated by several methods such as response, base resistance, response time, recovery time and thermal emission microscopy Moreover, the thermal emission microscopy methods proved that the working temperature is a linear function of loading power to the sample Finally, the high self-heating rate of sensor b2 was totally investigated the gas sensing properties to oxidant and reducing gases The sample was shown very good selectivity following loading power: sense oxidant gas at low power and sense reducing gas at high power The stability of the sample also very impressed Especially, response of the sensor to the gases mixture shows selective ability of 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sensors, which used nanowires, and most of the