二氧化氮為廣泛存在於我們生活環境中的有害氣體，由於其具有毒性會對人體產生健康的危害，因此我們致力於開發高效準確的氣體感測材料方便未來民眾可以即時監測空氣品質。本研究合成富含缺陷之氧化銦奈米材料，做為化學電阻式氣體感測器之感測材料，用於二氧化氮氣體感測。
本研究首先以黃光顯影及電子束蒸鍍等製程，於矽基板上製作鈦金電極圖案，然後使用水熱法合成氫氧化銦，並在低濃度還原性氣體(乙醇)環境下進行鍛燒後形成磚形氧化銦粉末，再用噴塗方式將氧化銦粉末均勻噴塗至含有電極之矽基板上，形成約1 μm之薄膜，並使用掃描式電子顯微鏡觀察材料表面形貌，氧化銦多呈現磚形形狀，尺寸落在約200 nm，之後使用能量散射X-射線光譜儀(EDS)及X-射線光電子光譜儀(XPS)對材料進行元素分析，確認氧缺陷所占氧化銦之比例，然後以X-射線繞射分析儀(XRD)確認氧化銦的結構與結晶情形，最後用螢光光譜儀(PL)確認材料的光學性質及缺陷組成。
氧化銦感測晶片於紫外光活化下進行250 ppb二氧化氮的氣體感測，其線性靈敏度可達62 ppm1，最低偵測極限可達0.4 ppb，而同濃度條件下測得之臭氧靈敏度則為8.4 ppm1，最低偵測極限可達2.8 ppb，也進行一氧化氮、氨氣、甲醛及二氧化硫等氣體之選擇性，發現其對二氧化氮與臭氧之響應最好，而二氧化氮對臭氧的選擇性約為7 : 1，並在一個月穩定性測試中，電阻和選擇性皆能穩定維持，並且在第二週後仍擁有快速地響應時間和回復時間，證明此感測晶片可以長期使用並維持高穩定性，進一步將此感測晶片與可攜式氣體感測器置於新北市永和環保署測站旁，進行一個月的戶外場域測試，以不同混合比例為預測目標對比環保署數據後通過人工神經網路進行氣體濃度預測，而台灣平均相對濕度為75%，在實驗室環境相對濕度為70%的環境下NO2對O3的選擇性比例為 2 : 1，結果顯示以0.65 NO2 + 0.35 O3為預測目標之ANN模型測試所得之R2值為0.263，MAE則為4.77 ppb，推論感測晶片測試期間室外環境溼度較平均濕度高，造成材料對二氧化氮靈敏度下降。
綜合上述結果，本研究成功大面積合成富含缺陷之氧化銦奈米材料運用於氣體感測，並且在室內環境下進行測試有優良的表現，而室外場域結果因溼度變化原因導致結果較不理想，二氧化氮與臭氧混和比例在0.65：0.35時與環保署數據相比R2為0.263， 而在二氧化氮與臭氧混和比例在0.45：0.55時與環保署數據相比R2則為0.406有較為良好的表現，推論在晶片測試期間戶外環境的相對濕度略高於平均濕度導致在二氧化氮與臭氧混和比例為0.45：0.55時擁有最高的R2。

Nitrogen dioxide is a harmful gas widely present in our living environment. Due to its toxicity, it poses health risks to humans. Therefore, we are dedicated to developing highly efficient and accurate gas sensing materials to enable future residents to monitor air quality in real time. In this study, we synthesized defect-rich indium oxide Nanomaterials as sensing materials for chemoresistive gas sensors used in nitrogen dioxide gas sensing.
The experiment begins by fabricating titanium-gold electrodes on silicon substrates using processes such as photolithography and electron beam evaporation. Subsequently, a hydrothermal method was employed to synthesize brick-shaped In2O3 powder under a low-concentration reducing gas environment (ethanol). Indium oxide powders are obtained by a hydrothermal method and calcination with reducing gas (ethanol) environment, and then the indium oxide powder spray coated uniformly on prepared silicon substrate with sensor electrode, forming a thin film of approximately 1 μm. The surface morphology of the material was observed using a scanning electron microscope (SEM), which revealed a brick-shaped structure with dimensions around 200 nm. Elemental analysis of the material was conducted using techniques such as energy-dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) to determine the proportion of oxygen vacancies in In2O3. The structure and crystallinity of In2O3 were confirmed using X-ray diffraction (XRD). Finally, the optical properties and defect composition of the material were examined using a fluorescence spectrometer (PL).
In2O3 sensor materials were activated under ultraviolet (UV) light and tested for its gas sensing performance towards 250 ppb of NO2, demonstrating a linear sensitivity of 62 ppm-1, and the lowest detection limit can be as low as 0.4 ppb, Under the same concentration conditions, while in the case of ozone (O3) the obtained sensitivity value is only 8.4 ppm–1, and the lowest detection limit can be as low as 2.8 ppb. The selectivity towards other gases such as nitrogen monoxide (NO), ammonia (NH3), formaldehyde (HCHO), and sulfur dioxide (SO2) was also investigated. The results showed that the sensor exhibited the highest response to NO2 and O3, with a selectivity ratio of approximately 7:1 between NO2 and O3. Stability tests carried out over a month demonstrated that both the resistance and selectivity of the sensor remained stable, and it exhibited rapid response and recovery times even after the second week, confirming its long-term usability and high stability.
For field test, In2O3 sensing chip is installed in a smart phone-operated portable gas sensing device. This portable device is then installed at the Yonghe Environmental Protection Agency (EPA) station in New Taipei City for field testing. The collected sensor data were compared with the agency's data and subjected to artificial neural network analysis to predict gas concentrations. The objective was to predict different gas concentration ratios using the Environmental Protection Agency data as a reference and employing an artificial neural network (ANN) for gas concentration forecasting. The average relative humidity in Taiwan is 75%, while the laboratory environment had a relative humidity of 70%. The selectivity ratio of NO2 to O3 under these conditions was 1:2. The results showed that using a 0.65 NO2 + 0.35 O3 mixture as the target for the ANN model yielded an R2 value of 0.263. From the analysis, it is inferred that during the testing period, the outdoor environmental humidity was higher than the average, leading to a decrease in sensitivity of the material to nitrogen dioxide.

Based on the above results, this study successfully synthesized defect-rich indium oxide Nanomaterials for gas sensing applications. The materials performed excellently in indoor environments during testing. However, the outdoor field test results were less promising due to variations in humidity. The gas mixture ratio of NO2 to O3 at 0.65 : 0.35 had an R2 of 0.263 compared to the EPA data, while the ratio of 0.45 : 0.55 showed better performance with an R2 of 0.406. It is suggested that during the chip testing period, the outdoor environment had a slightly higher relative humidity than the average, leading to the highest R2 value for the gas mixture ratio of 0.45 : 0.55.

摘要 I
Abstract III
致謝 VII
圖目錄 XII
表目錄 XV
第一章 緒論 16
1.1 前言 17
1.2 研究動機 18
第二章 文獻回顧 19
2.1 氣體感測器 19
2.1.1氣體感測器種類 22
2.1.2 金屬氧化物半導體氣體感測器 22
2.2金屬氧化物半導體感測機制 22
2.2.1 金屬氧化物氣體化學吸附機制 25
2.2.2 光活化脫附機制 27
2.3 氧化銦概論 29
2.3.1 氧化銦晶體結構 29
2.3.2 氧化銦的合成機制 30
2.3.3 氧化銦n-type半導體特性 32
2.3.4 氧化銦的光致發光性質 33
第三章 實驗設計與使用儀器 35
3.1 實驗架構 35
3.2 感測元件製作與感測材料合成 37
3.2.1 基板電極製作 37
3.2.2 不同溫度鍛燒之氧化銦合成 38
3.2.3 感測晶片製作 40
3.3 材料分析儀器 41
3.3.1 掃描式電子顯微鏡 42
3.3.2 能量色散X-射線光譜儀 42
3.3.3 X-射線光電子光譜儀 42
3.3.4 X-射線繞射分析儀 43
3.3.5 紫外/可見光分光光度計 43
3.3.6 螢光光譜儀 43
3.3.7 拉曼光譜儀 44
3.4 氣體感測 44
3.5 流動式系統 44
3.6 封閉式系統 47
3.6.1 二氧化氮/一氧化氮/氨氣感測 47
3.6.2 甲醛/二氧化硫感測 50
3.7 不同濕度環境之二氧化氮感測 52
3.8 不同濕度環境之臭氧感測 55
3.9 戶外場域感測 57
3.9.1 可攜式氣體感測器 59
第四章 結果與討論 60
4.1 材料分析 60
4.1.1 表面形貌 60
4.1.2 元素成分分析 61
4.1.3 晶體結構 65
4.1.4 光致發光性質分析 67
4.1.5 半導體性質 68
4.2 二氧化氮及臭氧感測結果 70
4.2.1 不同溫度鍛燒形成之氧化銦二氧化氮氣體感測 71
4.2.2 不同濃度二氧化氮氣體感測 72
4.2.3 不同濃度臭氧氣體感測 74
4.3 選擇性結果 75
4.3.1 一氧化氮氣體感測 76
4.3.2 氨氣氣體感測 76
4.3.3 甲醛氣體感測 77
4.3.4 二氧化硫氣體感測 78
4.4 選擇性結果統整 79
4.5 相對溼度對二氧化氮及臭氧感測影響 80
4.6 感測晶片長時間穩定性 82
4.7人工神經網路計算 83
4.7.1戶外場域測試 86
第五章 結論 89
參考文獻 91

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