Nanoparticle Design and Assembly for p-type Metal Oxide Gas Sensors

Metal oxide semiconductors have wide band gaps with tailorable electrical properties and high stability, suitable for chemiresistive gas sensors. p-Type oxide semiconductors generally have less sensitivity than n-type counterparts but...

Dopant Mediated Surface Charge Imbalance in Enhancing Performance of Metal Oxide Chemiresistive Gas Sensors

Chemically pristine and untailored metal oxide based gas sensors usually suffer the brunt of poor sensitivity and selectivity. Doping with suitable element has been an efficient strategy to encounter above...

State-of-the-Art Research on Chemiresistive Gas Sensors in Korea: Emphasis on the Achievements of the Research Labs of Professors Hyoun Woo Kim and Sang Sub Kim

This review presents the results of cutting-edge research on chemiresistive gas sensors in Korea with a focus on the research activities of the laboratories of Professors Sang Sub Kim and Hyoun Woo Kim. The advances in the synthesis techniques and various strategies to enhance the gas-sensing performances of metal-oxide-, sulfide-, and polymer-based nanomaterials are described. In particular, the gas-sensing characteristics of different types of sensors reported in recent years, including core–shell, self-heated, irradiated, flexible, Si-based, glass, and metal–organic framework sensors, have been reviewed. The most crucial achievements include the optimization of shell thickness in core–shell gas sensors, decrease in applied voltage in self-heated gas sensors to less than 5 V, optimization of irradiation dose to achieve the highest response to gases, and the design of selective and highly flexible gas sensors-based WS2 nanosheets. The underlying sensing mechanisms are discussed in detail. In summary, this review provides an overview of the chemiresistive gas-sensing research activities led by the corresponding authors of this manuscript.

Simulating Defects in Environmental Sensor Networks Using Stochastic Sensor Models

Chemiresistive gas sensors are an important tool for monitoring air quality in cities and large areas due to their low cost and low power and, hence, the ability to densely distribute them. Unfortunately, such sensor systems are prone to defects and faults over time such as sensitivity loss of the sensing material, less effective heating of the surface due to battery loss, or random output errors in the sensor electronics, which can lead to signal jumps or sensor stopping. Although these defects usually can be compensated, either algorithmically or physically, this requires an accurate screening of the entire sensor system for such defects. In order to properly develop, test, and benchmark corresponding screening algorithms, however, methods for simulating gas sensor networks and their defects are essential. In this work, we propose such a simulation method based on a stochastic sensor model for chemiresistive sensor systems. The proposed method rests on the idea of simulating the defect-causing processes directly on the sensor surface as a stochastic process and is capable of simulating various defects which can occur in low-cost sensor technologies. The work aims to show the scope and principles of the proposed simulator as well as to demonstrate its applicability using exemplary use cases.

Growth Mechanisms of ZnO Micro-Nanomorphologies and Their Role in Enhancing Gas Sensing Properties

Zinc oxide (ZnO) is one of the main functional materials used to realize chemiresistive gas sensors. In addition, ZnO can be grown through many different methods obtaining the widest family of unique morphologies. However, the relationship between the ZnO morphologies and their gas sensing properties needs more detailed investigations, also with the aim to improve the sensor performances. In this work, seven nanoforms (such as leaves, bisphenoids, flowers, needles, etc.) were prepared through simple wet chemical synthesis. Morphological and structural characterizations were performed to figure out their growth mechanisms. Then, the obtained powders were deposited through screen-printing technique to realize thick film gas sensors. The gas sensing behavior was tested toward some traditional target gases and some volatile organic compounds (acetone, acetaldehyde, etc.) and compared with ZnO morphologies. Results showed a direct correlation between the sensors responses and the powders features (morphology and size), which depend on the specific synthesis process. The sensors can be divided in two behavioral classes, following the two main morphology kinds: aggregates of nanocrystals (leaves and bisphenoids), exhibiting best performances versus all tested gases and monocrystal based (stars, needle, long needles, flowers, and prisms).