The development of gas sensor technology continues to be an exciting area covered by ACS Sensors. Artificial intelligence (AI) is altering our society, and it is powered by the data. Gas sensors can translate multivariate biochemical information around us into data sources for this paradigm. Gas sensors enable us to track and see the invisible and instantaneous molecular information around us, so that we can predict, prepare, and counteract for unexpected future events. With this, gas sensors are widely being used for advanced engineering applications, including medical (diagnosis), environmental (pollution tracker), industrial (hazards monitor), automotive (explosive monitor), and agricultural (product monitor) applications. Further, the gas sensor market is project to reach $1,336.2 million by 2027, which is one of the biggest markets across sensor technology. (1) In order to create real-time multivariate data sources, gas sensors must be operated without any spatiotemporal limitations. Therefore, the gas sensor must be integrated with the Internet-of-Things (IoTs). There are various types of conventional gas sensing technology including photoionization detectors (PID), infra-red (IR) sensors, and solid-state sensors. PID and IR-based sensors show high sensitivity and fast response time; however, they need high power consumption and complex instruments. Solid-state gas sensors based on charge variation of the materials is the most promising candidate for IoT integration since they can be operated with low power consumption (below mV level) and integrated circuit (IC) integration. Solid-sate gas sensors have been one of the most prolific topics published in ACS Sensors over the last five years. In particular, one trend we have seen at ACS Sensors is a predominance of papers that focus on chemiresistors that detect change in electrical resistance of materials with gas adsorptions. Nanoparticles, carbon nanotubes, silicon nanowires, 2D materials, metal oxide semiconductors (MOSs), and conducting polymers have been reported as materials used to fabricate chemiresistor sensors. Among them, MOSs have been the most widely utilized for real-world applications due to their good stability, low cost, and high sensitivity. A variety of MOSs including SnO₂, WO₃, In₂O₃, CuO, and ZnO, and most commonly, n-type semiconducting oxides, such as SnO₂ and ZnO with wide energy bandgaps, have been reported in ACS Sensors. Recently, the need for high operating temperatures typically above 300 °C has been one of the critical limitations of MOSs for IoT integrations. Many efforts have been made to operate at room temperature via material composite and device optimization; however, these systems still suffered from decreased sensitivity. (2) MXenes have just begun to be used as low-power sensor materials with their high conductivity and rich chemical reactivity. It is expected that MXene gas sensors will continue to show interesting results in the future. (3) With the development of a wide library of sensor materials, various target analytes have been investigated. Since 2016, NOx and NH₃ have been the most reported gases in ACS Sensors studies. This might be due to them being the primary pollutants from various industrial and environmental sources, coupled with the fact that a wide range of channel materials are able to sensitively detect NOx and NH₃. Greenhouse gases such as CO₂, CH₄, N₂O, and O₃ would be important targets for the climate change issue, and the demand for H₂ gas sensors is also expected to increase with the need for a sustainable hydrogen economy. (4) Sensors for detecting exhaled gases from humans will be important for diagnosing various diseases, such as lung cancer and asthma. Very recently, nanoparticle-based chemiresistors have been developed and shown to be effective in diagnosing COVID-19 in exhaled breath. (5) Deep learning-based analytics are desperately needed in the gas sensing fields for noise profiling and hidden signal analyses, which is expected to greatly improve the sensitivity and selectivity of the sensors. In addition, deep learning based on multivariate materials performance data sources will be able to suggest optimized sensor constructs for user-targeted gas analytes. (6) There is plenty of room to develop new materials and analytics for the next-generation of gas sensors. ACS Sensors welcomes innovative sensing solutions that address clear unmet needs. This article references 6 other publications. This article has not yet been cited by other publications. This article references 6 other publications.

中文翻译：

---

气体传感器的现在和未来

气体传感器技术的发展仍然是ACS Sensors涵盖的一个令人兴奋的领域. 人工智能 (AI) 正在改变我们的社会，它由数据驱动。气体传感器可以将我们周围的多元生化信息转化为这种范式的数据源。气体传感器使我们能够跟踪和查看我们周围的不可见和瞬时分子信息，以便我们可以预测、准备和应对意外的未来事件。因此，气体传感器被广泛用于高级工程应用，包括医疗（诊断）、环境（污染跟踪器）、工业（危害监测）、汽车（爆炸监测）和农业（产品监测）应用。此外，气体传感器市场预计到 2027 年将达到 13.362 亿美元，这是传感器技术领域最大的市场之一。(1) 为了创建实时的多元数据源，气体传感器的操作必须不受任何时空限制。因此，气体传感器必须与物联网 (IoT) 集成。有各种类型的传统气体传感技术，包括光电离检测器 (PID)、红外线 (IR) 传感器和固态传感器。基于 PID 和 IR 的传感器具有高灵敏度和快速响应时间；但是，它们需要高功耗和复杂的仪器。基于材料电荷变化的固态气体传感器是物联网集成最有希望的候选者，因为它们可以以低功耗（低于 mV 级）和集成电路 (IC) 集成运行。固态气体传感器一直是发表在 气体传感器必须与物联网 (IoT) 集成。有各种类型的传统气体传感技术，包括光电离检测器 (PID)、红外线 (IR) 传感器和固态传感器。基于 PID 和 IR 的传感器具有高灵敏度和快速响应时间；但是，它们需要高功耗和复杂的仪器。基于材料电荷变化的固态气体传感器是物联网集成最有希望的候选者，因为它们可以以低功耗（低于 mV 级）和集成电路 (IC) 集成运行。固态气体传感器一直是发表在 气体传感器必须与物联网 (IoT) 集成。有各种类型的传统气体传感技术，包括光电离检测器 (PID)、红外线 (IR) 传感器和固态传感器。基于 PID 和 IR 的传感器具有高灵敏度和快速响应时间；但是，它们需要高功耗和复杂的仪器。基于材料电荷变化的固态气体传感器是物联网集成最有希望的候选者，因为它们可以以低功耗（低于 mV 级）和集成电路 (IC) 集成运行。固态气体传感器一直是发表在 基于 PID 和 IR 的传感器具有高灵敏度和快速响应时间；但是，它们需要高功耗和复杂的仪器。基于材料电荷变化的固态气体传感器是物联网集成最有希望的候选者，因为它们可以以低功耗（低于 mV 级）和集成电路 (IC) 集成运行。固态气体传感器一直是发表在 基于 PID 和 IR 的传感器具有高灵敏度和快速响应时间；但是，它们需要高功耗和复杂的仪器。基于材料电荷变化的固态气体传感器是物联网集成最有希望的候选者，因为它们可以以低功耗（低于 mV 级）和集成电路 (IC) 集成运行。固态气体传感器一直是发表在过去五年的ACS 传感器。特别是，我们在ACS Sensors看到的一个趋势是，大量论文专注于检测具有气体吸附作用的材料电阻变化的化学电阻器。纳米粒子、碳纳米管、硅纳米线、二维材料、金属氧化物半导体 (MOS) 和导电聚合物已被报道为用于制造化学电阻传感器的材料。其中，MOS 因其稳定性好、成本低、灵敏度高等优点，在实际应用中得到了最广泛的应用。各种 MOS，包括 SnO ₂、WO ₃、In ₂ O ₃、CuO 和 ZnO，以及最常见的 n 型半导体氧化物，例如 SnO ₂和 ZnO 具有宽能带隙，已在ACS Sensors中报道。最近，对通常高于 300°C 的高工作温度的需求一直是 MOS 用于物联网集成的关键限制之一。通过材料复合和器件优化，已经做出了许多努力以在室温下运行；然而，这些系统的灵敏度仍然下降。(2) MXenes 刚刚开始被用作低功率传感器材料，具有高导电性和丰富的化学反应性。预计未来 MXene 气体传感器将继续显示出有趣的结果。(3) 随着广泛的传感器材料库的发展，已经研究了各种目标分析物。自 2016 年以来，NOx 和 NH ₃是报告最多的气体ACS 传感器研究。这可能是由于它们是来自各种工业和环境来源的主要污染物，再加上多种通道材料能够灵敏地检测 NOx 和 NH ₃的事实。_{CO 2}、CH ₄、N ₂ O 和 O ₃等温室气体将成为气候变化问题的重要目标，对 H _2的需求随着对可持续氢经济的需求，气体传感器也有望增加。(4) 检测人体呼出气体的传感器对于诊断肺癌和哮喘等各种疾病具有重要意义。最近，已开发出基于纳米颗粒的化学电阻器，并显示其可有效诊断呼出气中的 COVID-19。(5) 气体传感领域迫切需要基于深度学习的分析来进行噪声分析和隐藏信号分析，这有望大大提高传感器的灵敏度和选择性。此外，基于多元材料性能数据源的深度学习将能够为用户目标气体分析物建议优化的传感器结构。(6) 为下一代气体传感器开发新材料和分析的空间很大。ACS Sensors欢迎创新的传感解决方案来解决明显未满足的需求。本文引用了其他 6 篇出版物。这篇文章尚未被其他出版物引用。本文引用了其他 6 篇出版物。