| 11. |
- Nguyen, Xuan Thai, et al.
(författare)
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Gas sensor array based on tin oxide nano structure for volatile organic compounds detection
- 2020
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Ingår i: Vietnam Journal of Science and Technology. - : Vietnam Academy of Science and Technology. - 2525-2518. ; 58:2, s. 189-196
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Tidskriftsartikel (refereegranskat)abstract
- The detection of volatile organic compounds (VOCs) is essential in practicalapplication in breath analysis. Thus, gas sensors based on metal oxide have been fabricated, butthey lacked selectivity. One approach to resolve this task is to use an array of highly sensitiveand selective sensors as an electronic nose. Here a gas sensor array based on Tin oxide nanostructurewith temperature modulation techniques was presented. A Platinum micro-heater isaccompanied with the array gas sensor. The gas sensor array was composed of five singlesensors, and that single sensor is located at different site from the micro heater and works atdifferent temperatures. The gas sensing properties of the gas array sensors were investigatedwith VOC gases such as Ethanol, Methanol, Iso-propanol, and Acetone as well as NH3, H2, andH2S. We also confirm the good selectivity of the array sensor for Ethanol, Methanol, Isopropanol,Acetone, NH3, H2, and H2S by using radar graphic method.
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| 12. |
- Son, Dang Ngoc, et al.
(författare)
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A novel design and fabrication of self-heated In2O3 nanowire gas sensor on for ethanol detection
- 2022
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Ingår i: Sensors and Actuators A-Physical. - : Elsevier. - 0924-4247 .- 1873-3069. ; 345
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Tidskriftsartikel (refereegranskat)abstract
- Many attempts have been made on the design and fabrication of low-power consumption gas sensor for application on the Internet of Things and portable devices. The performance of gas sensors includes sensitivity, selectivity, and power consumption, which are strongly dependent on the configuration of the device such as the gap size between two electrodes, the sensing material, and operation principle. Here, self-heated In2O3 nanowire-based gas sensors were designed and fabricated by on-chip growth technique via thermal evaporation to work at room temperature. The effect of electrode gap (10-40 mu m) on the power consumption and gas sensing performance of the In2O3 nanowire sensors was studied. With the large gap of 40 mu m, the sensor exhibited excellent sensing characteristics of low power consumption (1.06 mW) with ability to detect ethanol gas down to 20 ppm effectively. We also examined the role of nanowire conductivity in the performance of the self-heated sensor in the detection of reducing gas. The sensor demonstrated rapid response and recovery times of less than a minute, exceptional stability, and remarkable recovery.
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| 13. |
- Thai, Nguyen Xuan, et al.
(författare)
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Prototype edge-grown nanowire sensor array for the real-time monitoring and classification of multiple gases
- 2020
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Ingår i: JOURNAL OF SCIENCE-ADVANCED MATERIALS AND DEVICES. - : VIETNAM NATL UNIV. - 2468-2284 .- 2468-2179. ; 5:3, s. 409-416
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Tidskriftsartikel (refereegranskat)abstract
- The monitoring and classification of different gases using a single resistive semiconductor sensor are challenging because of the similar response characteristics. An array of separated sensors can be used as an electronic nose, but such arrays have a bulky structure and complex fabrication processes. Herein, we easily fabricated a gas-sensor array based on edge-grown SnO2 nanowires for the real-time monitoring and classification of multiple gases. The array comprised four sensors and was designed on a glass substrate. SnO2 nanowires were grown on-chip from the edge of electrodes, made contact together, and acted as sensing elements. This method was advantageous over the post-synthesis technique because the SnO2 nanowires were directly grown from the edge of the electrodes rather than on the surface. Accordingly, damage to the electrode was avoided by alloying Sn with Pt at a high growth temperature. The sensing characteristics of the sensor array were further examined for different gases, including methanol, isopropanol, ethanol, ammonia, hydrogen sulphide and hydrogen. Radar plots were used to improve the selective detection of different gases and enable effective classification. (C) 2020 The Authors. Publishing services by Elsevier B.V. on behalf of Vietnam National University, Hanoi.
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| 14. |
- Thai, Nguyen Xuan, et al.
(författare)
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Realization of a portable H2S sensing instrument based on SnO2 nanowires
- 2020
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Ingår i: Journal of Science: Advanced Materials and Devices. - : Elsevier BV. - 2468-2284 .- 2468-2179. ; 5:1, s. 40-47
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Tidskriftsartikel (refereegranskat)abstract
- Monitoring of toxic gas in air is important because air pollution, especially in developing countries, has rapidly become severe. The high cost of installation and maintenance of a stationary analysis system by using methods such as gas chromatography limits its applications. Low-power, portable devices with relatively low-cost gas sensors are effective for mapping pollution levels in real-time in urban areas and in other living environmentts. Herein, the realization of a portable H2S sensing instrument based on SnO2 nanowires is reported. The sensor chip was prepared by the on-chip growth of SnO2 nanowires directly from the edges of Pt electrodes. The electronic system and software for signal acquisition, data processing, data storage, and output of the instrument were developed. A prototype for zero series of the instrument was also realized. The instrument is capable of monitoring H2S gas in air at ppm level and in biogas production with satisfation.
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| 15. |
- Duoc, Vo Thanh, et al.
(författare)
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New Design of ZnO Nanorod- and Nanowire-Based NO2 Room-Temperature Sensors Prepared by Hydrothermal Method
- 2019
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Ingår i: Journal of Nanomaterials. - : HINDAWI LTD. - 1687-4110 .- 1687-4129.
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Tidskriftsartikel (refereegranskat)abstract
- Room-temperature gas sensors are attracting attention because of their low power consumption, safe operation, and long-term stability. Herein, ZnO nanorods (NRs) and nanowires (NWs) were on-chip grown via a facile hydrothermal method and used for room-temperature NO2 gas sensor applications. The ZnO NRs were obtained by a one-step hydrothermal process, whereas the NWs were obtained by a two-step hydrothermal process. To obtain ZnO NW sensor, the length of NRs was controlled short enough so that none of the nanorod-nanorod junction was made. Thereafter, the NWs were grown from the tips of no-contact NRs to form nanowire-nanowire junctions. The gas-sensing characteristics of ZnO NRs and NWs were tested against NO2 gas at room temperature for comparison. The gas-sensing characteristics of the sensors were also tested at different applied voltages to evaluate the effect of the self-activated gas-sensing performance. Results show that the diameter of ZnO NRs and NWs is the dominant parameter of their NO2 gas-sensing performance at room temperature. In addition, self-activation by local heating occurred for both sensors, but because the NWs were smaller and sparser than the NRs, local heating thus required a lower applied voltage with maximal response compared with the NRs.
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| 16. |
- Duoc, Vo Thanh, et al.
(författare)
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Room temperature highly toxic NO2 gas sensors based on rootstock/scion nanowires of SnO2/ZnO, ZnO/SnO2, SnO2/SnO2 and, ZnO/ZnO
- 2021
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Ingår i: Sensors and actuators. B, Chemical. - : Elsevier. - 0925-4005 .- 1873-3077. ; 348
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Tidskriftsartikel (refereegranskat)abstract
- Grafted structures between SnO2 and ZnO nanowires were realized in a two-step process of growth. First, the rootstocks of SnO2 or ZnO nanowires were synthesized by thermal evaporation technique. Second, a thin Au layer was sputter deposited on the sample and synthesis of nanowire scions of ZnO or SnO2, respectively, on the rootstocks was realized by thermal evaporation technique again. In both growth steps, SnO2 powder or a mixture of ZnO and carbon powders was use as source materials for the synthesis. Different rootstock/scion combinations of SnO2/ZnO, ZnO/SnO2 nanowires (called heterostructures) and ZnO/ZnO, SnO2/SnO2 nanowires (called homostructures) were synthesised. The fabricated grafted nanowires were examined by field-emission scanning electron microscope and their compositions were analyzed by energy dispersive spectroscopy and X-ray diffraction analysis. The test results indicate that this type of nanostructure material is very promising for NO2 gas sensing at ppt level at room temperature. Among the fabricated structures the SnO2/ZnO nanowires showed the best sensing performance with the high sensitivity and fast response and recovery time. We also discussed the gas sensing mechanism of the fabricated sensors based on the band diagram.
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| 17. |
- Jiao, Mingzhi, et al.
(författare)
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Controlled Synthesis and Understanding of Growth Mechanism : Parameters for Atmospheric Pressure Hydrothermal Synthesis of Ultrathin Secondary ZnO Nanowires
- 2016
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Ingår i: Journal of Scientific Research and Reports. - 2320-0227. ; 9:5, s. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- Synthesis of ultrathin ZnO nanowires gains great attention from research community because oftheir large potential in applications involving optoelectronics and sensors. In this study, a lowpressure and low-temperature hydrothermal synthesis of ultrathin ZnO nanowires is studied tounderstand the growth mechanisms better. To achieve this aim, an about 10 nm thin Zn seed layerwas sputter-deposited on a silicon (100) wafer for the hydrothermal growth of ZnO nanowires in anequimolar aqueous solution of Zn(NO3)2 and hexamethylenetetramine. X-ray diffraction analysis confirmed that the Zn layer was self-oxidized into ZnO in air soon after deposition and thenfunctioned as the seed for the preferred growth of c-oriented ZnO nanorods. Different growthconditions were investigated to identify how concentration, temperature, and time influence the finalmorphology of the synthesized ZnO nanostructures. It was found that under the atmosphericpressure, concentration and temperature have to be higher than 0.0025 M and 50°C, respectively,for the ZnO nanorods to nucleate and grow densely. Low concentration gives sparse and randomlyoriented nanorods, whereas high concentration gives dense and vertical nanorods. Ultrathin ZnOsecondary nanowires with an average diameter of less than 20 nm were successfully synthesizedin a solution with concentration of 0.005 M at 90°C for about 16 h. By analyzing the scanningelectron microscopy images of the ZnO nanostructures obtained at different growth conditions, amechanism is proposed for the growth of the ultrathin secondary ZnO nanowires. This findingprovides a cost-effective and straightforward pathway to prepare ultrathin ZnO nanowires.
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| 18. |
- Tan, Ha Minh, 1989-, et al.
(författare)
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Novel Self-Heated Gas Sensors Using on-Chip Networked Nanowires with Ultralow Power Consumption
- 2017
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Ingår i: ACS Applied Materials and Interfaces. - : American Chemical Society (ACS). - 1944-8244 .- 1944-8252. ; 9, s. 6153-6162
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Tidskriftsartikel (refereegranskat)abstract
- The length of single crystalline nanowires (NWs) offers aperfect pathway for electron transfer, while the small diameter of the NWshampers thermal losses to tje environment, substrate, and metal electrodes.Therefore, Joule self-heating effect is nearly ideal for operating NW gassensors at ultralow power consumption, without additional heaters. Therealization of the self-heated NW sensors using the “pick and place”approach is complex, hardly reproducible, low yield, and not applicable formass production. Here, we present the sensing capability of the self-heatednetworked SnO2 NWs effectively prepared by on-chip growth. Ourdeveloped self-heated sensors exhibit a good response of 25.6 to 2.5 ppmNO2 gas, while the response to 500 ppm H2, 100 ppm NH3, 100 ppm H2S,and 500 ppm C2H5OH is very low, indicating the good selectivity of thesensors to NO2 gas. Furthermore, the detection limit is very low, down to 82parts-per-trillion. As-obtained sensing performance under self-heating modeis nearly identical to that under external heating mode. While the power consumption under self-heating mode is extremely low,around hundreds of microwatts, as scaled-down the size of the electrode is below 10 μm. The selectivity of the sensors can becontrolled simply by tuning the loading power that enables simple detection of NO2 in mixed gases. Remarkable performancetogether with a significantly facile fabrication process of the present sensors enhances the potential application of NW sensors innext generation technologies such as electronic noses, the Internet of Things, and smartphone sensing.
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| 19. |
- Thai, Nguyen Xuan, et al.
(författare)
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Multi gas sensors using one nanomaterial, temperature gradient, and machine learning algorithms for discrimination of gases and their concentration
- 2020
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Ingår i: Analytica Chimica Acta. - : ELSEVIER. - 0003-2670 .- 1873-4324. ; 1124, s. 85-93
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Tidskriftsartikel (refereegranskat)abstract
- In this work, four identical micro sensors on the same chip with noble metal decorated tin oxide nanowires as gas sensing material were located at different distances from an integrated heater to work at different temperatures. Their responses are combined in highly informative 4D points that can qualitatively (gas recognition) and quantitatively (concentration estimate) discriminate all the tested gases. Two identical chips were fabricated with tin oxide (SnO2) nanowires decorated with different metal nanoparticles: one decorated with Ag nanoparticles and one with Pt nanoparticles. Support Vector Machine was used as the "brain" of the sensing system. The results show that the systems using these multisensor chips were capable of achieving perfect classification (100%) and good estimation of the concentration of tested gases (errors in the range 8-28%). The Ag decorated sensors did not have a preferential gas, while Pt decorated sensors showed a lower error towards acetone, hydrogen and ammonia. Combination of the two sensor chips improved the overall estimation of gas concentrations, but the individual sensor chips were better for some specific target gases. (C) 2020 Elsevier B.V. All rights reserved.
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| 20. |
- Thanh Hoan, Nguyen, et al.
(författare)
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Novel Time Series Bagging Based Hybrid Models for Predicting Historical Water Levels in the Mekong Delta Region, Vietnam
- 2022
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Ingår i: CMES - Computer Modeling in Engineering & Sciences. - : Tech Science Press. - 1526-1492 .- 1526-1506. ; 131:3, s. 1431-1449
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Tidskriftsartikel (refereegranskat)abstract
- Water level predictions in the river, lake and delta play an important role in flood management. Every year Mekong River delta of Vietnam is experiencing flood due to heavy monsoon rains and high tides. Land subsidence may also aggravate flooding problems in this area. Therefore, accurate predictions of water levels in this region are very important to forewarn the people and authorities for taking timely adequate remedial measures to prevent losses of life and property. There are so many methods available to predict the water levels based on historical data but nowadays Machine Learning (ML) methods are considered the best tool for accurate prediction. In this study, we have used surface water level data of 18 water level measurement stations of the Mekong River delta from 2000 to 2018 to build novel time-series Bagging based hybrid ML models namely: Bagging (RF), Bagging (SOM) and Bagging (M5P) to predict historical water levels in the study area. Performances of the Bagging-based hybrid models were compared with Reduced Error Pruning Trees (REPT), which is a benchmark ML model. The data of 19 years period was divided into 70:30 ratio for the modeling. The data of the period 1/2000 to 5/2013 (which is about 70% of total data) was used for the training and for the period 5/2013 to 12/2018 (which is about 30% of total data) was used for testing (validating) the models. Performance of the models was evaluated using standard statistical measures: Coefficient of Determination (R2), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Results show that the performance of all the developed models is good (R2 > 0.9) for the prediction of water levels in the study area. However, the Bagging-based hybrid models are slightly better than another model such as REPT. Thus, these Bagging-based hybrid time series models can be used for predicting water levels at Mekong data.
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