Environmental Sensors Research Articles

Wind Source Localization System Based on a Palm-Sized Quadcopter

In this study, we implemented a compact wind direction sensor on a palm-sized quadcopter to achieve wind source localization (WSL). We designed an anemotaxis algorithm based on the sensor data and experimentally validated its efficacy. Anemotaxis refers to the strategy of moving upwind based on information on the wind direction, which is essential for tracing odors propagating through the air. Despite the limited research on quadcopter systems achieving WSL directly through environmental wind measurement sensors, debate remains regarding the relationship between sensor placement and the anemotaxis algorithm. Therefore, we experimentally investigated the placement of a wind direction sensor capable of estimating wind source direction even when propellers are rotating. Our findings demonstrated that placing the sensor 50 mm away from the enclosure of the quadcopter allowed accurate wind direction measurement without being affected by wake disturbances. Additionally, we constructed an anemotaxis algorithm based on wind direction and speed data, which we integrated into the quadcopter system. We confirmed the ability of the quadcopter to execute anemotaxis behavior and achieve WSL irrespective of environmental wind strength through wind source localization experiments.

The LTAR Grazing Land Common Experiment at the Central Plains Experimental Range: Collaborative adaptive rangeland management.

Semiarid rangelands throughout the western Great Plains support livestock production and many other ecosystem services. The degree to which adaptive multi-paddock (AMP) grazing management approaches can help achieve desired ecosystem services remains unclear. At the Central Plains Experimental Range in northeastern Colorado, a management-science partnership with a diverse stakeholder group is comparing collaborative adaptive rangeland management (CARM), designed to incorporate AMP principles, to traditional rangeland management (TRM), consisting of season-long grazing during the growing season. Each treatment was implemented on a set of 10, 130-ha pastures paired by soils, topography, and plant communities to evaluate how CARM affects vegetation (composition and production), livestock production (steer weight gain), and wildlife habitat (vegetation structure for grassland birds). For the first 5 years of the experiment, CARM cattle were managed as a single herd using AMP grazing with planned year-long rest in 20% of the pastures. Relative to TRM, CARM enhanced heterogeneity in vegetation structure across the landscape, benefiting two grassland bird species. However, this came at the cost of 12%-16% lower steer weight gains in CARM versus TRM and declining populations of a third bird species of conservation concern in both treatments. Here we discuss how increased understanding of ecological and social processes during the experiment's first 5 years led to changes in the CARM treatment and management objectives during the next 5 years. We also discuss how innovations in remote sensing, environmental sensors, ecosystem modeling, social learning, and economic analyses are being integrated into and supported by the CARM experiment.

Gone with the wind: environmental variation influences detection efficiency in a coastal acoustic telemetry array

Range tests play a critical role in designing acoustic telemetry studies, guiding equipment configuration, deployment techniques, and the analysis of animal movement data. These studies often strive to capture the effects of environmental variation on detection efficiency over time but are frequently limited in spatial and temporal scale. This could lead to disparities between test results and the circumstances encountered during animal tracking studies. In this study, we evaluated detection range and efficiency at two distinct spatial and temporal scales in a dynamic intertidal ecosystem. Two range tests were conducted, the first being a small-scale study using 6 receivers deployed over 1 month. Using modern acoustic receivers with built-in transmitters and environmental sensors, we then conducted a large-scale range test with 22 receiver stations over a full year to approximate the area and duration of a typical animal movement study. Differences in detection range between the two studies occurred as a result of environmental variation and tag power output, with midpoint ranges estimated as 123 m (small scale, low power), 149 m (small scale, high power) and 311 m (large scale, very high power). At both scales, wind speed emerged as the most influential factor explaining temporal variation in predicted detection efficiency. However, this effect was modulated by wind direction which varied as a result of land sheltering and fetch between the two study scales. At the small scale, detection efficiency decreased with winds from the south and east, while at the large scale, northern and westerly winds were most detrimental. Water temperature had a positive effect on predicted detection efficiency at both scales, while relative water level was positive at the small scale and negative at the large scale. Additional factors, including precipitation and Topographic Position Index, were found to influence detection efficiency at a large scale. Moreover, sensors associated with receivers in the larger array revealed the significant influences of receiver tilt and ambient noise. These discrepancies in the outcomes of the two studies underscore the critical role of scale in range test design and emphasize the need for long-term, in situ range testing at relevant spatial scales.

Self-powered and speed-adjustable sensor for abyssal ocean current measurements based on triboelectric nanogenerators

The monitoring of currents in the abyssal ocean is an essential foundation of deep-sea research. The state-of-the-art current meter has limitations such as the requirement of a power supply for signal transduction, low pressure resistance, and a narrow measurement range. Here, we report a fully integrated, self-powered, highly sensitive deep-sea current measurement system in which the ultra-sensitive triboelectric nanogenerator harvests ocean current energy for the self-powered sensing of tiny current motions down to 0.02 m/s. Through an unconventional magnetic coupling structure, the system withstands immense hydrostatic pressure exceeding 45 MPa. A variable-spacing structure broadens the measuring range to 0.02–6.69 m/s, which is 67% wider than that of commercial alternatives. The system successfully operates at a depth of 4531 m in the South China Sea, demonstrating the record-deep operations of triboelectric nanogenerator-based sensors in deep-sea environments. Our results show promise for sustainable ocean current monitoring with higher spatiotemporal resolution.

Implementation and Evaluation of Attention Aggregation Technique for Pear Disease Detection

In this study, a novel approach integrating multimodal data processing and attention aggregation techniques is proposed for pear tree disease detection. The focus of the research is to enhance the accuracy and efficiency of disease detection by fusing data from diverse sources, including images and environmental sensors. The experimental results demonstrate that the proposed method outperforms in key performance metrics such as precision, recall, accuracy, and F1-Score. Specifically, the model was tested on the Kaggle dataset and compared with existing advanced models such as RetinaNet, EfficientDet, Detection Transformer (DETR), and the You Only Look Once (YOLO) series. The experimental outcomes indicate that the proposed model achieves a precision of 0.93, a recall of 0.90, an accuracy of 0.92, and an F1-Score of 0.91, surpassing those of the comparative models. Additionally, detailed ablation experiments were conducted on the multimodal weighting module and the dynamic regression loss function to verify their specific contributions to the model performance. These experiments not only validated the effectiveness of the proposed method but also demonstrate its potential application in pear tree disease detection. Through this research, an effective technological solution is provided for the agricultural disease detection domain, offering substantial practical value and broad application prospects.

Crop Monitoring System with Water Moisture Levels Using Controller

This paper presents a Crop Monitoring System (CMS) designed to effectively manage crop water moisture levels through automated irrigation control. The system incorporates soil moisture sensors and environmental sensors for real-time data collection, which is then processed by a controller to determine optimal irrigation schedules and water application rates. By integrating predefined thresholds and algorithms, the controller ensures precise irrigation tailored to specific crop and soil conditions, thus preventing both under- watering and over-watering. Additionally, the CMS features wireless communication capabilities, enabling remote monitoring and adjustment of irrigation settings by farmers. This remote accessibility facilitates timely interventions and optimizations, even in the absence of farmers in the fields. Overall, the CMS enhances crop health, improves resource efficiency, and conserves water in agriculture. By leveraging advanced sensor technologies and intelligent control algorithms, this system offers a sustainable solution for precision agriculture, contributing to increased yields while minimizing water usage and environmental impact. This project intends to make farming as mechanized and labor-free as possible.

A highly responsive, moisture resistant diabetes diagnostic gas sensor with Pt-loaded porous GO/ZnO

Achieving high response of metal-semiconductor oxide gas sensors in humid environment is a collective goal of the scientific community. Herein, a gas sensor based on porous graphene oxide (GO) and zinc oxide (ZnO) composite (PGZ) decorated by Pt catalysts is presented for valid acetone detection with high moisture resistance. By deposit Pt nanoparticles on the surface of PGZ to form Pt/PGZ, its responsiveness and moisture resistance are both further improved. The Pt/PGZ sensor with optimized Pt (Pt 200/PGZ) loading displays a response of 150.2 acetone at 220 °C for 50 ppm acetone, which is nearly 3.5 times than PGZ composite (42.9). In addition, the Pt/PGZ gas sensor has a high response (Ra/Rg=44.5) even at 90 % relative humidity of 50 ppm acetone. It also has excellent stability (less than 5 % fluctuation for 10 cycle responses and 8 weeks intermittent tests) and fast response/recovery time (4 s/7 s). Herein offers a new strategy for achieving high response of gas sensors in high humidity environments.

Eco-friendly triboelectric nanogenerator for self-powering stacked In2O3 nanosheets/PPy nanoparticles-based NO2 gas sensor

As atmospheric issues and energy crises worsen, developing environmentally friendly, low-cost, high-performance self-powered gas sensing systems for gas pollutant monitoring is crucial for the development of ecological civilization. In this work, an eco-friendly self-powered nitrogen dioxide (NO2) sensor (EFNS) system based on an eco-friendly triboelectric nanogenerator (EF-TENG) is reported. The system comprises a power supply unit (EF-TENG) and a sensing unit (In2O3/PPy sensor), connected through a signal stabilization circuit. EF-TENG utilizes eco-friendly and biodegradable gelatin and PLA/PBAT as the friction layer. By introducing leaf structures on the gelatin surface using a template method, the output voltage and current of EF-TENG were increased by 1.44 and 1.67 times, respectively. The peak power density and root mean square power density of EF-TENG reached 1386 mW m−2 and 185.35 mW m−2, respectively. Additionally, EF-TENG exhibited excellent long-term stability, maintaining a stable output voltage (∼24 V) after rectification and voltage stabilization treatment under conditions of 15–55°C and 40–80 % RH. Additionally, an In2O3/PPy heterostructure sensor was prepared, and the EFNS system was constructed through impedance matching effects, revealing the NO2 response mechanism of the In2O3/PPy heterostructure. This achieved a wide detection range and highly sensitive (Vg/Va = 355 %@30 ppm) detection of NO2. This work provides insights into eco-friendly self-powered gas sensors and sensing mechanisms, offering ideas for the development of environmental monitoring sensors and clean energy harvesting devices.

A review of lysimeters from the perspective of measurement performance and intelligent development in China

AbstractLysimeters are critical instruments for studying infiltration, runoff and evapotranspiration processes in the hydrological cycle and play a critical role in promoting efficient water‐saving irrigation. This paper provides a systematic review of the development process and research status of lysimeters, progressing from simple to complex designs, from single instruments to clusters, and from manual measurement to intelligent monitoring. The working principles of various types of lysimeter were first described based on Chinese lysimeter patents over the past 20 years. Second, this paper analyses the measurement performance and application scope of different lysimeters and further studies the weighting stability of various weighing lysimeters. Third, by analysing sources of measurement error, the reliability improvement methods of lysimeters are analysed from the aspects of environment control and sensor compensation. Fourth, this paper reviews typical research on the automation and informatization of lysimeters and discusses future intelligent developments and application prospects for lysimeters in complex environments. Finally, the measurement performance of different lysimeters is analysed based on experimental data sets. This paper puts forward some suggestions for developing lysimeters with high performance, high efficiency and high reliability, hoping to promote the development of intelligent agriculture.

A Portable Agriculture Environmental Sensor with a Photovoltaic Power Supply and Dynamic Active Sleep Scheme

A portable environmental sensor for agricultural applications is proposed that addresses key challenges in power supply, data transmission, and monitoring efficiency. The sensor features a photovoltaic power supply and a PID-based dynamic active–sleep scheme for sustainable energy management, maintaining optimal battery levels under varying solar conditions. Its compact, waterproof, and dustproof design (90 mm × 90 mm × 150 mm, 844 g) ensures robust and reliable operation in diverse agricultural environments. High-precision digital sensors monitor temperature, humidity, light intensity, and CO2 concentration. Equipped with low-power NB-IoT technology, the sensor supports real-time remote environmental monitoring. Our experimental results show effective continuous operation, accurate environmental measurements, and performance comparable to established data loggers. The advanced power management and precise sensing capabilities make this sensor a competitive solution for improving smart agriculture practices, particularly in resource-limited or off-grid settings.

Nanopore-Based Single-Molecule Investigation of Cation Effect on the i-Motif Structure.

The i-motif, a secondary structure of a four-helix formed by cytosine-rich DNA (i-DNA) through C-C+ base pairing, is prevalent in human telomeres and promoters. This structure creates steric hindrance, thereby inhibiting both gene expression and protein coding. The conformation of i-DNA is intricately linked to the intracellular ionic environment. Hence, investigating its conformation under various ion conditions holds significant importance. In this study, we explored the impact of cations on the i-motif structure at the single-molecule level using the α-hemolysin (α-HL) nanochannel. Our findings reveal that the ability of i-DNA to fold into the i-motif structure follows the order Cs+ > Na+ > K+ > Li+ for monovalent cations. Furthermore, we observed the interconversion of single-stranded DNA (ss-DNA) and the i-motif structure at high and low concentrations of Mg2+ and Ba2+ electrolyte solutions. This study not only has the potential to extend the application of i-motif-based sensors in complex solution environments but also provides a new idea for the detection of metal ions.

MEMS reconfigurable terahertz meta-absorber with polarization-dependent and sensing characteristics

This study presents and demonstrates a design of a micro-electro-mechanical system (MEMS) reconfigurable terahertz (THz) metamaterial absorber (TMA) that shows tunable free spectra range with a maximum value as 166 GHz in transverse magnetic mode and switchable resonance from 1.24 THz to 1.53 THz. The unit structure of TMA consists of two movable rectangular resonators aside and an x-shaped resonator at the center comprising two c-shaped resonators connected upside down. The material configuration of TMA is typical of the metal–insulator-metal sandwich configuration. That is a bottom Au layer preventing the penetration of the THz wave, a dielectric SiO2 layer to accommodate and absorb the incident wave, and a patterned Au structure array to select the resonant frequency. The electromagnetic response of TMA could be flexibly modulated when the structure is reconfigured by changing the gaps between x-shaped resonators and rectangular resonators based on the MEMS platform. Meanwhile, owing to the asymmetry of resonant structure, the electromagnetic response of TMA could be tuned from single-, dual-, triple- quad-resonances by varying the polarization state of incidence. Furthermore, the sensitivity of TMA is explored and demonstrated with remarkable linearity under a variation of the surrounding environment refractive index from 1.0 to 2.0. The feasibility of TMA is validated as the experimental absorption spectra are well meet the simulation results. The above results indicate the proposed TMA possesses great potential applications in multiple resonance switches, polarization switches, and highly efficient environmental sensors.

Very-large-scale-integrated high quality factor nanoantenna pixels.

Metasurfaces precisely control the amplitude, polarization and phase of light, with applications spanning imaging, sensing, modulation and computing. Three crucial performance metrics of metasurfaces and their constituent resonators are the quality factor (Q factor), mode volume (Vm) and ability to control far-field radiation. Often, resonators face a trade-off between these parameters: a reduction in Vm leads to an equivalent reduction in Q, albeit with more control over radiation. Here we demonstrate that this perceived compromise is not inevitable: high quality factor, subwavelength Vm and controlled dipole-like radiation can be achieved simultaneously. We design high quality factor, very-large-scale-integrated silicon nanoantenna pixels (VINPix) that combine guided mode resonance waveguides with photonic crystal cavities. With optimized nanoantennas, we achieve Q factors exceeding 1,500 with Vm less than 0.1 . Each nanoantenna is individually addressable by free-space light and exhibits dipole-like scattering to the far-field. Resonator densities exceeding a million nanoantennas per cm2 can be achieved. As a proof-of-concept application, we show spectrometer-free, spatially localized, refractive-index sensing, and fabrication of an 8 mm × 8 mm VINPix array. Our platform provides a foundation for compact, densely multiplexed devices such as spatial light modulators, computational spectrometers and in situ environmental sensors.

The perspectives of doing, being, belonging, becoming on older homecare recipients’ use and experiences with technologies in the Assisted Living Project in Norway

ABSTRACT The Assisted Living project (2016-2019) aimed to investigate older adults’ needs for digital technology for daily support and to develop technology solutions in collaboration with the user group. This paper presents data extracted from three sub-studies: Sub-study 1 investigated older homecare recipients’ use of and attitudes towards digital technology, sub-study 2 explored assisted living residents’ needs and requirements for technology, and sub-study 3 explored their experiences with environmental sensor technology to support safety and daily living. The aim was to explore how the occupational science concepts of doing, being, belonging, and becoming can provide a deeper understanding of technology use among participants in the Assisted Living Project. This study demonstrates that for older adults in the Assisted Living project to become technology users required both personal motivation and cognitive capacity for learning to use the device and become familiar with the technology, and access to internet and digital tools. Digitalization in society leads to new challenges for all citizens, especially those who are less familiar with using digital technology. By applying an occupational science perspective to technology use, this paper contributes to creating awareness about digital exclusion and occupational injustice. It provides a deeper understanding of use and non-use and the digital divide, such as the consequences of not having access to digital healthcare services, that may lead to breaches of democratic human rights.

Experimental study on practical application of optical fiber sensor (OFS) for high-temperature system

This study explores the application of Raman scattering-based optical fiber sensors (OFSs) in extreme environments, specifically focusing on a loop heater vessel with temperatures ranging from 200 °C to 680 °C. This condition generally covers the advanced reactor designs, such as Sodium-cooled Fast Reactor and High Temperature Reactor. Various optical fiber combinations were employed for temperature measurements, taking into consideration the operating temperature of the target equipment. Two types of OFSs, gold-coated and polyimide-coated, were utilized. Protective tubes made of stainless steel (STS) and carbon were introduced to ensure reliable temperature data collection in high-temperature settings. Results indicate that the STS tube with a gold-coated OFS exhibited the highest consistency and agreement with thermocouple measurements, making it suitable for extreme environments. The study emphasizes the applicability of this system in high-temperature environments, such as liquid metal reactors, high-temperature thermal energy storage system, and hydrogen production system, for environmental monitoring.

Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaverse

Research background: Multi-modal synthetic data fusion and analysis, simulation and modelling technologies, and virtual environmental and location sensors shape the industrial metaverse. Visual digital twins, smart manufacturing and sensory data mining techniques, 3D digital twin simulation modelling and predictive maintenance tools, big data and mobile location analytics, and cloud-connected and spatial computing devices further immersive virtual spaces, decentralized 3D digital worlds, synthetic reality spaces, and the industrial metaverse. Purpose of the article: We aim to show that big data computing and extended cognitive systems, 3D computer vision-based production and cognitive neuro-engineering technologies, and synthetic data interoperability improve artificial intelligence-based digital twin industrial metaverse and hyper-immersive simulated environments. Geolocation data mining and tracking tools, image processing computational and robot motion algorithms, and digital twin and virtual immersive technologies shape the economic and business management of extended reality environments and the industrial metaverse. Methods: Quality tools: AMSTAR, BIBOT, CASP, Catchii, R package and Shiny app citationchaser, DistillerSR, JBI SUMARI, Litstream, Nested Knowledge, Rayyan, and Systematic Review Accelerator. Search period: April 2024. Search terms: “digital twin industrial metaverse” + “artificial Intelligence of Things systems”, “multisensory immersive extended reality technologies”, and “algorithmic big data simulation and modelling tools”. Selected sources: 114 out of 336. Published research inspected: 2022–2024. PRISMA was the reporting quality assessment tool. Dimensions and VOSviewer were deployed as data visualization tools. Findings & value added: Simulated augmented reality and multi-sensory tracking technologies, explainable artificial intelligence-based decision support and cloud-based robotic cooperation systems, and ambient intelligence and deep learning-based predictive analytics modelling tools are instrumental in augmented reality environments and in the industrial metaverse. The economic and business management of the industrial metaverse necessitates connected enterprise production and big data computing systems, simulation and modelling technologies, and virtual reality-embedded digital twins.

Hydrophobic TPU/CNTs-ILs Ionogel as a Reliable Multimode and Flexible Wearable Sensor for Motion Monitoring, Information Transfer, and Underwater Sensing.

Ionogel-based sensors have gained widespread attention in recent years due to their excellent flexibility, biocompatibility, and multifunctionality. However, the adaptation of ionogel-based sensors in extreme environments (such as humid, acidic, alkaline, and salt environments) has rarely been studied. Here, thermoplastic polyurethane/carbon nanotubes-ionic liquids (TPU/CNTs-ILs) ionogels with a complementary sandpaper morphology on the surface were prepared by a solution-casting method with a simple sandpaper as the template, and the hydrophobic flexible TPU/CNTs-ILs ionogel-based sensor was obtained by modification using nanoparticles modified with cetyltrimethoxysilane. The hydrophobicity improves the environmental resistance of the sensor. The ionogel-based sensor exhibits multimode sensing performance and can accurately detect response signals from strain (0-150%), pressure (0.1-1 kPa), and temperature (30-100 °C) stimuli. Most importantly, the hydrophobic TPU/CNTs-ILs ionogel-based sensors can be used not only as wearable strain sensors to monitor human motion signals but also for information transfer, writing recognition systems, and underwater activity monitoring. Thus, the hydrophobic TPU/CNTs-ILs ionogel-based sensor offers a new strategy for wearable electronics, especially for applications in extreme environments.

A fluorescence switch-off nanosensor for sensitive determination of the antiandrogen drug flutamide in pharmaceutical and environmental samples. Analytical method greenness, blueness, and whiteness assessment

A fast, practical, and non-hazardous switch-off fluorescent nanosensor for the non-fluorescent antiandrogen drug flutamide (FLU) was developed from nitrogen/sulfur co-doping of carbon quantum dots (N,S-CQDs). For the first time, the highly fluorescent N,S-CQDs were generated via one-pot microwave-assisted synthesis in only 3 min using facilely available precursors (sweet yellow pepper and thiourea). The sensor is characterized by a narrow particle size distribution, high doping efficiency (N, 42.05 % and S, 8.28 %), reproducibility, and high emission at 410 nm after excitation at 330 nm. FLU efficiently and quantitatively turned off the fluorescence of the prepared N,S-CQDs via a synergistic combination of static quenching and inner filter effect. The furnished nanosensor showed good linearity (r = 0.9999) for FLU analysis within concentrations ranged from 1.0 to 30.0 µg mL−1 with a detection limit of 0.293 µg mL−1 and quantitation limit of 0.886 µg mL−1. The selectivity of the probe was confirmed in the presence of co-administered drugs, possible co-existing materials, and various metal ions. The N,S-CQDs interestingly showed acceptable cytocompatibility and low toxicity, as revealed by the MTT assay. This feature bestows the N,S-CQDs a practicability as an environmental sensor. Thus, the proposed approach was implemented for FLU analysis in pharmaceutical tablets, tap water, and river water with good percentage recoveries (99.59 ± 1.28%, 99.49 ± 1.75%, and 101.21 ± 1.67%, respectively) and without interferences. Furthermore, the approach was positively assessed with respect to greenness, blueness, and whiteness. The high values of the analytical greenness score AGREE (0.78), the chiefly green ComplexGAPI pictogram, the Blue Applicability Grade Index BAGI (72.5), and the RGB12 (93.6) show the high greenness, blueness, and whiteness features of the method that confirm its minor environmental impact, excellent applicability, and sustainability, respectively.

Optical Bistability of Graphene Incorporated into All-Superconducting Photonic Crystals

We investigated optical bistability and its temperature dependence in a composite system composed of an all-superconducting photonic crystal and graphene. The photonic crystal, constructed from two types of superconducting sheets, and which is temperature-sensitive and can greatly localize the electric field, alternately supports a defect mode in a cryogenic environment. Graphene is located at the strongest site in the electric field, so the third-order nonlinearity of graphene is enhanced tremendously, and, subsequently, low thresholds of optical bistability are achieved in the near-infrared region. The thresholds of optical bistability and the interval between the upper and lower thresholds decrease with the increase in environmental temperature, while the bistable thresholds increase with the addition of the incident wavelength. Furthermore, the critical threshold triggering optical bistability can be modulated by environment temperature and the periodic number of photonic crystals as well. The simulations may be found to be applicable for all temperature-sensitive optical switches or sensors in cryogenic environments.

Low ppm NO2 detection through advanced ultrasensitive copper oxide gas sensor

The imperative development of a cutting-edge environmental gas sensor is essential to proficiently monitor and detect hazardous gases, ensuring comprehensive safety and awareness. Nanostructures developed from metal oxides are emerging as promising candidates for achieving superior performance in gas sensors. NO2 is one of the toxic gases that affects people as well as the environment so its detection is crucial. The present study investigates the gas sensing capability of copper oxide-based sensor for 5 ppm of NO2 gas at 100 °C. The sensing material was synthesized using a facile precipitation method and characterized by XRD, FE-SEM, UV–visible spectroscopy, photoluminescence spectroscopy, XPS and BET techniques. The developed material shows a response equal to 67.1% at optimal temperature towards 5 ppm NO2 gas. The sensor demonstrated an impressive detection limit of 300 ppb, along with a commendable percentage response of 5.2%. Under optimized conditions, the synthesized material demonstrated its high selectivity, as evidenced by the highest percentage response recorded for NO2 gas among NO2, NH3, CO, CO2 and H2S.