CO2 Sensor Research Articles

Adsorption properties of noble-metal (Ag, Rh, or Au)-doped CeO2(1 1 0) to CO: A DFT + U study

Dissolved gas analysis (DGA) is an effective method for fault detection of oil-immersed transformers, and CO is one of the characteristic gases in insulation oil. Therefore, based on density functional theory, the adsorption properties of three noble metals (Ag, Rh, or Au)-doped CeO2 (110) to CO were studied in this paper. The adsorption energy, charge transfer, density of states (DOS), and deformation charge density (DCD) were calculated to analyze the adsorption behavior of CO on the material surface. The frontier molecular orbital, energy band structure, and desorption time were also calculated to evaluate the potential of the three doping systems as CO sensors. The results show that the adsorption properties of Ag-CeO2, Rh-CeO2, and Au-CeO2 to CO are significantly higher than that of pristine CeO2, with adsorption energies are −54.61, −85.78, −205.57 kJ/mol, respectively. However, Rh-CeO2 exhibits superior sensitivity and satisfactory recovery time towards CO compared with Ag-CeO2 and Au-CeO2. Rh-CeO2 also shows excellent selectivity to CO, which is a promising candidate material for CO sensors. The research conducted in this work is intended to contribute to dissolved gas analysis (DGA).

Favorable performance of WSe2 monolayer modified by chromium catalyst for sensing thermal runaway gases H2, CO and C2H4 using first-principles theory

Detections of thermal runaway gases in the Li-ion batteries (LIBs) is a workable method to evaluate its running status. In this work, first-principles theory is adopted to simulate adsorption and sensing performances of Cr-decorated WSe2 (Cr-WSe2) monolayer upon three typical gases, namely H2, CO and C2H4, in the thermal runaway LIBs. Results indicate that Cr-WSe2 monolayer performs physisorption upon H2 with Ead of −0.37 eV and chemisorption upon CO and C2H4 with Ead of −1.62 and −1.41 eV. The Cr adatom causes strong magnetic behavior to Cr-WSe2 monolayer, which impact the magnetic property of the adsorbed gas molecule as well. The analysis of electronic property suggests the strong potential of Cr-WSe2 monolayer as a high-sensitivity CO and C2H4 sensor, and can be applied as a reusable C2H4 sensor after gas desorption for 70.38 s at 398 K. The analysis of work function (WF) reveal its potential as a potential WF-based gas sensor upon H2 and CO as well. The findings in this work uncover the sensing potential of Cr-WSe2 monolayer upon three typical gases of thermal runaway in the LIBs, which can be explored as a nano gas sensor to perform thermal runaway monitoring using the nano-sensing method.

Improving CO2 sensing and p-n conductivity transition under UV light by chemo-resistive sensor based on ZnO nanoparticles

Chemo-resistive gas sensors for CO2 detection were fabricated using ZnO nanoparticles synthesized by the hydrothermal method. The CO2 sensors were activated by thermal and/or UV light exposure. While the resistance changes of sensors exposed to CO2 at high temperatures (150–300 °C) exhibited noise, those activated by UV light remained stable, indicating that UV light can improve CO2 sensing. Good response, short response time (<10 s), stability, a linear calibration curve, and high sensitivity were obtained under UV light. Therefore, the UV-activated sensor could be applied in practical environments for CO2 monitoring. Furthermore, the measurements for CO2 also showed that the p-n transition was observed with changes in temperature. The CO2 sensor acted as p-type at RT, while it acted as n-type at 80 °C. The p-type conductivity of ZnO at RT, which can be attributed to Zn vacancies acting as acceptors, was confirmed through PL and EDX spectra, as well as Hall Effect measurements. It should be noted that the p-n transition in sensors based on undoped materials under UV irradiation at low temperatures (<100 °C) has been less reported. The n-p transition could offer intriguing opportunities to customize the electronic properties of the nanostructured devices.

Carbon Stock and CO2 Fluxes in Various Land Covers in Karang Gading and Langkat Timur Laut Wildlife Reserve, North Sumatra, Indonesia

Mangrove forests play an important role in coastal areas from an ecological perspective, being able to store large amounts of carbon through sequestration and inhibiting climate change processes by absorbing CO2 in the atmosphere. In recent years, there have been changes in the land cover of converted and degraded mangrove forests which have resulted in the release of carbon and an imbalance in soil structure, which in turn cause a flux of CO2 into the atmosphere. This research was conducted at the Karang Gading and Langkat Timur Laut Wildlife Reserve (KGLTLWR) in North Sumatra, Indonesia. The study focused on six different land covers, namely natural forests, restoration, mixed agriculture, paddy fields, oil palm plantation, and ponds. This study aimed to measure the total carbon stock of mangrove forests that have been converted to other land covers and estimate the level of CO2 flux in the area. A total of three transects and six plots for each land cover were used in this study; for tree biomass, a non-destructive method was used by recording every DBH &gt; 5 cm, and for soil carbon, drilling was carried out, which was divided into five depths in each plot. CO2 flux was measured using an Eosense Eosgp CO2 sensor with the static closed chamber method. The highest carbon stock was found at 308.09 Mg ha−1 in natural forest, while the lowest 3.22 Mg ha−1 was found in mixed agriculture. The highest soil carbon was found at 423.59 MgC ha−1 in natural forest, while the lowest 50.44 MgC ha−1 was found in mixed agriculture dry land. The highest average CO2 flux value of 1362.24 mgCO2 m2 h−1 was found in mangrove restoration and the lowest in ponds was 123.03 mgCO2 m2 h−1. Overall, the research results inform how much carbon stock is lost when converted to other land covers so that it can be used as a reference for policy makers to provide future management of mangrove forests and develop mitigation measurements to reduce carbon emissions.

Large animal ventilator-integrated volumetric capnography generates clinically acceptable values of physiologic dead space in anesthetized healthy adult horses.

To evaluate the agreement between the Tafonius large animal ventilator-integrated volumetric capnography (vCap) software and the Respironics NICO noninvasive cardiac output monitor reference system. Data were collected from 56 healthy adult horses undergoing general anesthesia. Animals were placed under general anesthesia and connected to the Tafonius large animal ventilator circle system. A flow partitioning device with CO2 and flow sensors was utilized to couple the endotracheal tube to the NICO monitor. Tafonius CO2 and flow sensors are incorporated into the Y-piece of the breathing circuit. Arterial blood samples were collected to determine the partial pressure of arterial carbon dioxide (PaCO2) immediately before data collection. The PaCO2 was input into the Tafonius and NICO monitor, and dead space ventilation (%Vd), end-tidal CO2 partial pressure (ETco2), mixed-expired CO2 partial pressure (Peco2), and expired tidal volume (Vt) were calculated over a single breath. Multiple measurements were completed for each patient, with a total of 200 paired data points collected for analysis. Data were assessed for normality, and Bland-Altman analysis was performed. Bias and 95% limits of agreement were calculated. The limits of agreement for %Vd of the ventilator-derived measurements fell within ± 10% of the NICO monitor reference method. Our results indicate that, when compared to the NICO monitor method, the Tafonius-integrated vCap software provides clinically acceptable values of Peco2, Vt, and %Vd in healthy adult horses.

Diagnostic accuracy of using capnography in verification of nasogastric tube placement among adult patients in hospital settings: Protocol of a diagnostic study.

To determine the diagnostic accuracy of end-tidal carbon dioxide (ETCO2) detection using capnography for verifying the correct placement of nasogastric tubes (NGTs) among adult patients in hospital settings. A prospective observational diagnostic study will be conducted. Patients ≥ 18-year-old and requiring the insertion of an NGT will be recruited using a convenience sampling method from 39 general medical and geriatric wards, intensive care units, accident and emergency departments, and subacute/rehabilitation/infirmary wards in 21 acute or subacute/convalescent/extended care hospitals. ETCO2 detection by sidestream capnography, which indicates an airway intubation of an NGT when a capnogram waveform or an ETCO2 level > 10mmHg (1.33 kPa) occurs, will serve as the index test. The reference standards will be the X-ray performed and pH value of gastric aspiration (pH ≤ 5.5) after the index test. Each participant will be included only once. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve of capnography will be calculated to assess the diagnostic performance of capnography. The variability in diagnostic accuracy in participants with different characteristics will be explored by using chi-squared or Fisher's exact tests. The time spent and the cost of the tests will be compared using the paired t-test. All statistical tests will be two-sided with a level of significance set at 0.05. This study will provide evidence on the diagnostic accuracy of capnography in verifying NGT placement and its applicability to patients in hospitals settings, since this evidence is limited in the current literature. In addition, it will help identify the optimal combination of tests in verifying the correct placement of NGTs and inform the update of clinical practice guidelines and stakeholders' decisions on the adoption of ETCO2 detection as a routine method for verifying NGT placement. ClinicalTrials.gov ID: NCT05817864.

An ultra-small integrated CO2 infrared gas sensor for wearable end-tidal CO2 monitoring

Human physiological metabolic status can be obtained by monitoring exhaled CO2 concentration, but current CO2 sensors have disadvantages such as large size, high power consumption, and slow response time, which limit their application in wearable devices and portable instruments. In this article, we report a small size, good performance, and large range CO2 infrared gas sensor that integrates a high emissivity MEMS emitter chip, a high detectivity thermopile chip, and a high coupling efficiency optical chamber to achieve high efficiency optical-thermal-electrical conversion. Compared with typical commercial sensors, the size of the sensor can be reduced by approximately 80% to only 10mm×10mm×6.5mm, with the advantages of low power consumption and fast response speed. Further, a monitoring system for end-tidal CO2 concentration installed on a mask was developed using this sensor, and good results were achieved.

Methods of Measuring Air Pollution in Cities and Correlation of Air Pollutant Concentrations

The monitoring of air quality continues to be one of the most important tasks when ensuring the safety of our environment. This paper aims to look at correlations between different types of pollutants, so that robust air quality measurement systems can be deployed in remote, inaccessible areas, at a reduced cost. The first matter at hand was to design an affordable and portable system capable of measuring different air pollutants. A custom PCB was designed that could support the acquisition of readings of, among others, particulate and CO sensors. Then, correlations between the concentrations of different pollutants were analyzed to identify if measuring the concentration of one type of pollutant can allow the extrapolation of the concentration of another. This particular study focuses on the correlations between the concentrations of particulate matter and CO. Finally, after observing a moderate correlation, it was proposed to measure the concentrations of pollutants that require less expensive sensors, and to extrapolate the concentrations of pollutants that require a more expensive sensor to measure their concentration. The link between particulate pollution and CO concentrations was identified and discussed as the result of this study.

Design and experimentation of soil organic matter content detection system based on high-temperature excitation principle

With the continuous development of precision agriculture, the integration of sensor technology, control technology, and agricultural production activities has become increasingly tight. Soil organic matter (SOM) content is an important parameter in precision agriculture, closely related to the growth status of crops. Therefore, in-situ detection of SOM is an important part of variable seeding. Currently, most researchers use spectroscopy to detect SOM. However, the accuracy of spectroscopy is affected by factors such as soil texture, soil moisture content, soil iron oxide content, and soil particle size. Additionally, spectroscopic instruments are expensive and complex. To address these issues, this study designed and developed a real-time detection system for soil organic matter content based on the high-temperature excitation principle. The SOM detection system includes the selection and application of carbon dioxide sensor, the design of detection devices, the design of control systems, and the design of human–machine interface. Benchtop tests showed that the system's response time standard deviation was 0.252 s, indicating good stability. The filtering and cooling effects of the system met the requirements of the detection system. Five different natural soils were collected, and two of them, along with organic soil, were used to create artificially graded soil samples. Multiple linear regression was used for modeling, selecting six models with an R2 greater than 0.8 for accurate prediction of the remaining three different soil textures. The modeling results showed that a heating depth of 10 mm was susceptible to external interference, and the accuracy of the model with a heating depth of 15 mm was similar to that of the model with a heating depth of 20 mm. When the heating time exceeded 10 s, both models with different heating depths had an R2 greater than 0.8. The accuracy of the models increased with increasing heating time. Among them, the 15 mm-20 s model had the highest accuracy, with an average prediction accuracy of 91.4 %, a maximum accuracy of 94.1 %, and a minimum accuracy of 86.7 %. The experimental results showed that the SOM detection system designed in this study had good predictive capabilities for SOM in different soil textures and could achieve in-situ detection of SOM.

Experimental evaluation of airflow guiding components for wind-driven single-sided natural ventilation: A comparative study in a test chamber

Single-sided ventilation is a frequently employed ventilation strategy in contemporary structures, yet its effectiveness is often mediocre, underscoring the need for solutions to enhance its performance. To evaluate the effect of louvres and guide vanes on the effective ventilation rate, 21 different louvre configurations and four guide vane designs were compared with a plain opening for single-sided ventilation in a full-scale experimental test chamber under three different magnitudes of local wind velocity. Ventilation rates were measured using the tracer gas decay method with 12 NDIR CO2 sensors. The findings, obtained under specific test conditions, indicate that deeper openings result in a decline in ventilation rate performance. It was observed that wider guide vanes lead to higher ventilation rates, suggesting their potential to enhance SSV performance. The results reveal that, in most cases, louvres contribute to a decline in the system's performance. However, the ventilation rate is influenced by the angle and number of louvres, with optimal performance observed at specific angles and fewer louvres. These findings provide valuable insights for optimizing the design of airflow-guiding components in wind-driven single-sided ventilation systems, enabling the development of more efficient and customized solutions for natural ventilation in buildings.

An emission based optical CO2 sensor fabricated on grating-like TiO2 substrates using HPTS

TiO2 is a widely used material in various applications, including photo-catalysis, sensing, and dye-sensitized solar cells. In this work, we presented a stable and sensitive CO2 sensor working on principle of emission signals of the HPTS dye immobilized on TiO2 substrates whose effectiverefractive indicesin the parallel and perpendicular grating orientations evidenced earlier. The HPTS exhibited 8.4-fold enhanced emission signal on the offered substrates with respect to the previously reported intensities recorded for the polymeric supports. The emission peaks of the HPTS exhibited CO2 induced intensity quenching when excited at 466 nm. Calibration sensitivity of the offered composites has been tested exposing the sensor materials to varying concentrations of the CO2 between 0.0 and 100.0 % pCO2 and correlating the measured fluorescence intensity with the corresponding CO2 levels. The dye revealed enhanced CO2 induced response exhibiting the I0/100 values of 11.9, 13.3, 11.2 and 6.5. We also recorded bi-exponential excited state lifetimes for the HPTS on four different test materials both in the absence and presence of the CO2. The emission based variations were followed as the analytical signal due to higher CO2-induced relative signal changes than that of the lifetime based variations. Herein we used the ion pair form of the HPTS in a protective chemical microenvironment and obtained considerable long term stability extending to16 mounts which can be attributed to the presence of the 1-butyl-3-methylimidazolium tetrafluoroborate as an internal buffering system in the sensing composition as well as the inert and robust structure of the substrate. The extremely high optical response, advantage of excitation with blue LEDs and long-term stability observed on grating-like TiO2 surfaces make the proposed system a promising design for the quantification of CO2 for further applications.

Comparison of edge computing methods in Internet of Things architectures for efficient estimation of indoor environmental parameters with Machine Learning

The large increase in the number of Internet of Things (IoT) devices have revolutionised the way data is processed, which added to the current trend from cloud to edge computing has resulted in the need for efficient and reliable data processing near the data sources using energy-efficient devices. Two methods based on low-cost edge-IoT architectures are proposed to implement lightweight Machine Learning (ML) models that estimate indoor environmental quality (IEQ) parameters, such as Artificial Neural Networks of Multilayer Perceptron type. Their implementation is based on centralised and distributed parallel IoT architectures, connected via wireless, which share commercial off-the-self modules for data acquisition and sensing, such as sensors for temperature, humidity, illuminance, CO2, and other gases. The centralised method uses a Graphics Processing Unit and the Message Queuing Telemetry Transport protocol, but the distributed method utilises low-performance ARM-based devices and the Message Passing Interface protocol. Although multiple IEQ parameters are measured, the training and testing of ML models is accomplished with experiments focused on small temperature and illuminance datasets to reduce data processing load, obtained from sudden spikes, square profiles and sawteeth test cases. The results show a high estimation performance with F-score and Accuracy values close to 0.95, and an almost theorical Speedup with a reduction in power consumption close to 37% in the distributed parallel approach. In addition, similar or slightly better performance is achieved compared to equivalent IoT architectures from related research, but error reduction of 35–76% is accomplished with an adequate balance between performance and energy efficiency.

Photoreforming of Glycerol Catalyzed by CuO/TiO2 Supported on Hydroxyapatite

Waste bovine bones can be used as a source to produce hydroxyapatite (HAp), which is a good organic adsorbent and used as a support material for metal oxide photocatalysts. In this work, HAp powders were prepared from calcination of bovine bones at 900 °C for 2 h and used as supporting material for a TiO2 photocatalyst incorporating CuO. The hexagonal HAp particles were characterized using Fourier transformed infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The 50 wt% TiO2 and 1 wt% CuO/TiO2 supported on HAp photocatalysts were synthesized by the co-precipitation method and finally calcined at 450 °C for 4 h. The synthesized HAp and catalysts were characterized by FTIR, XRD, BET surface area analysis, SEM, and transmission electron microscopy (TEM). The photocatalytic performance of the synthesized catalysts was performed by photoreforming of glycerol at room temperature using 100 mL of 0.5 M glycerol solution under nitrogen atmosphere, irradiating with low-light intensity 20 W Mercury UV lamp for 7 h. The gaseous products catalyzed by the synthesized catalysts were analyzed using a gas chromatograph. The maximum hydrogen gas production from photoreforming of glycerol at this condition was obtained at 513.7 mmol gcat–1 without carbon dioxide detection after catalyzing by CuO/TiO2/HAp catalyst.

The role of decarboxylation reactions during the initiation of the methanol-to-olefins process

The mechanism for direct CC bond formation during the initiation of the methanol-to-olefins (MTO) process is still under discussion. Carbon dioxide formation is often observed during initiation, but there are only few investigations into the role of decarboxylation. We investigate decarboxylation pathways in the H-SSZ-13 zeolite from methanol to olefins via direct carbon–carbon coupling. Additionally, the rate-determining steps were recomputed in the H-ZSM-5 and H-SAPO-34 zeolite. Gibbs free energy barriers were calculated using periodic density functional theory in combination with CCSD(T) calculations on cluster models. For H-SSZ-13, kinetic batch reactor simulations were performed. We found for H-SSZ-13 that pathways via decarboxylation reactions are equally likely as previously computed pathways including decarbonylation mechanisms (also known as ketene or CO pathway). Lactones formed from ketenes and formaldehyde were identified as the main intermediates. The decarboxylation mechanism has similar barriers in H-SSZ-13, H-ZSM-5, and H-SAPO-34, while the barriers for methylation and decarbonylation reactions are significantly lower in H-ZSM-5 and higher in H-SAPO-34. Decarboxylation reactions of lactones could explain experimentally detected carbon dioxide during the initial phase of the MTO process.

DFT study on adsorption of small gas molecules on Pt-capped armchair and zigzag single-walled carbon nanotubes

The adsorption of small gas molecules (CO, O2 and N2) on Pt-capped armchair and zigzag single-walled carbon nanotubes (SWCNT) has been investigated by density functional theory (DFT) method to determine the potential for gas sensor detection. Results indicated that O2 and N2 molecules with lower adsorption energies (1.66 eV and 1.00 eV) exhibited weak chemical adsorption on SWCNT(4,4)-Pt. However, CO demonstrates strong chemical adsorption with a high adsorption energy of 2.23 eV on SWCNT(4,4)-Pt. The adsorption energy of CO on SWCNT(7,0)-Pt shows the chemical adsorption between CO and SWCNT(7,0)-Pt. In addition, these findings also implied Pt-capped SWCNT could act as small gas molecule sensors to detect CO toxic gas at room temperature. In this system, CO is the electron donor and SWCNT-Pt is the electron receptor. The interaction of Pt and carbon nanotube backbone delocalized π electrons could not only increases the conductivity of SWCNT-Pt, but also enhances the conductivity of SWCNT-Pt-CO. The HOMO-LUMO gap (Δε) of Pt-capped SWCNT(7,0) reduced from 0.43 eV to 0.39 eV after CO adsorption, and the Δε value of Pt-capped SWCNT(4,4) decreased by 0.08 eV. The electrical conductivity of Pt-capped armchair and zigzag SWCNT has increased after the adsorption of CO molecule. The results may be helpful for designing a promising Pt-capped SWCNT-based CO sensors.

Contributions of carotid bodies, retrotrapezoid nucleus neurons and preBötzinger complex astrocytes to the CO2 -sensitive drive for breathing.

Current models of respiratory CO2 chemosensitivity are centred around the function of a specific population of neurons residing in the medullary retrotrapezoid nucleus (RTN). However, there is significant evidence suggesting that chemosensitive neurons exist in other brainstem areas, including the rhythm-generating region of the medulla oblongata - the preBötzinger complex (preBötC). There is also evidence that astrocytes, non-neuronal brain cells, contribute to central CO2 chemosensitivity. In this study, we reevaluated the relative contributions of the RTN neurons, the preBötC astrocytes, and the carotid body chemoreceptors in mediating the respiratory responses to CO2 in experimental animals (adult laboratory rats). To block astroglial signalling via exocytotic release of transmitters, preBötC astrocytes were targeted to express the tetanus toxin light chain (TeLC). Bilateral expression of TeLC in preBötC astrocytes was associated with ∼20% and ∼30% reduction of the respiratory response to CO2 in conscious and anaesthetized animals, respectively. Carotid body denervation reduced the CO2 respiratory response by ∼25%. Bilateral inhibition of RTN neurons transduced to express Gi-coupled designer receptors exclusively activated by designer drug (DREADDGi ) by application of clozapine-N-oxide reduced the CO2 response by ∼20% and ∼40% in conscious and anaesthetized rats, respectively. Combined blockade of astroglial signalling in the preBötC, inhibition of RTN neurons and carotid body denervation reduced the CO2 -induced respiratory response by ∼70%. These data further support the hypothesis that the CO2 -sensitive drive to breathe requires inputs from the peripheral chemoreceptors and several central chemoreceptor sites. At the preBötC level, astrocytes modulate the activity of the respiratory network in response to CO2 , either by relaying chemosensory information (i.e. they act as CO2 sensors) or by enhancing the preBötC network excitability to chemosensory inputs. KEY POINTS: This study reevaluated the roles played by the carotid bodies, neurons of the retrotrapezoid nucleus (RTN) and astrocytes of the preBötC in mediating the CO2 -sensitive drive to breathe. The data obtained show that disruption of preBötC astroglial signalling, blockade of inputs from the peripheral chemoreceptors or inhibition of RTN neurons similarly reduce the respiratory response to hypercapnia. These data provide further support for the hypothesis that the CO2 -sensitive drive to breathe is mediated by the inputs from the peripheral chemoreceptors and several central chemoreceptor sites.

Low-cost urban carbon monitoring network and implications for china: a comprehensive review.

The development and renewal of gas sensor technology have enabled more and more low-cost gas sensors to form a carbon monitoring network to meet the requirements of the city. In the context of China's commitment to achieving the "double carbon" target by 2060, this paper reviews the principles of four standard gas sensors and the application of several low-cost sensors in urban carbon monitoring networks, with the aim of providing a practical reference for the future deployment of carbon monitoring networks in Chinese cities. Moreover, the types, prices, and deployment of the sensors used in each project are summarized. Based on this review, non-dispersive infrared sensors have the best performance among the sensors and are commonly used in many cities. Lots of urban climate networks in cities were summarized by many reviews in the literature, but only a few sensors were studied, and they did not consider carbon dioxide (CO2) sensors. This review focuses on the dense CO2 urban monitoring network, and some case studies are also discussed, such as Seoul and San Francisco. To address the issue of how to better ensure the balance between cost and accuracy in the deployment of sensor networks, this paper proposes a method of simultaneously deploying medium-precision and high-precision fixed sensors and mobile sensors to form an urban carbon monitoring network. Finally, the prospects and recommendations, such as different ways to mitigate CO2 and develop an entire carbon monitoring system for future urban carbon monitoring in China, are also presented.

DFT study of Ag-X (X = Pd, Pt, Ag) decorated (8,0) single wall carbon nanotube for spintronic applications

The main purpose of the present article is an investigation of the electronic and magnetic properties of (8,0) single-wall carbon nanotube (CNT80) decorated with a diatomic configuration of Ag and X (X = Pd, Pt, and Ag). Density functional theory and the Grimme-D2 approach in spin polarization mode are employed. It is concluded that Ag and X are adsorbed on CNT80 in the dimer form rather than singly atomic adsorption. The spin-distinct electronic band structure and the densities of states are also calculated. The calculations show that Ag-Pd/CNT80 is a bipolar semiconductor with an energy gap of 0.27 eV for spin-up, 0.47 eV for spin-down, and 0.15 eV for spin-flip electrons. Ag-Pt/CNT80 is an anti-ferromagnetic p-type indirect semiconductor with a gap of 0.187 eV for temperatures below 188 K. After 188 K up to around 330 K, this structure converts to an indirect bipolar semiconductor, with an energy gap of 0.31 eV (0.37 eV) for the spin-up (down) channel. Adsorption of Ag dimer onto CNT80 leads to the p-type nonmagnetic semiconductor. As an application of the proposed materials, the absorption of CO as a polar molecule on the Ag-Pd/CNT80 structure is also investigated, and a proposed structure as a spintronic CO sensor is introduced.

Evaluation of Different Natural Ventilation Strategies by Monitoring the Indoor Air Quality Using CO2 Sensors.

Indoor air quality is a characteristic that depends on air pollutants inside a building and that can be affected by different ventilation strategies. There is strong evidence linking poor indoor air quality (IAQ) and harmful health effects, especially on vulnerable collectives, such as children in schools. Due to this concern, this work aims to provide guidance on the design of highly efficient ventilation strategies to improve the air quality of schools' classrooms. For this, IAQ monitoring has been carried out in eight educational in real conditions centres using CO2 concentration as an IAQ indicator. Variables such as the presence of students and their number, activity developed in the classroom and ventilation strategy used together with break time duration have been also recorded to analyse their influence on CO2 concentration levels. Concluding results have allowed us to determine the maximum number of students allowed in a closed room to maintain CO2 levels at normal concentrations and the time needed to reduce these CO2 levels depending on the ventilation strategy adopted. Moreover, it has been discussed how surrounding school conditions (pollution or noise) and the building isolation are impacting the final IAQ in the classrooms studied.

NANOCOMPOSITE-BASED THIN FILM CARBON MONOXIDE SENSORS

Over the past decade, organic semiconductors have been of great interest in basic research and practical applications. Composites based on organic materials have become widespread due to their unique properties and partial biodegradability: they are also suitable as sensitive materials — sensors for detecting various gases. One such gas is carbon monoxide or a different carbon monoxide. Carbon monoxide occurs wherever conditions exist for incomplete combustion of carbon-containing substances. One of the industrial industries where carbon monoxide is emitted in large volumes is the oil and gas industry. The main source in this industry are flares for combustion of associated gases, during the operation of gas turbine plants, as well as exhaust gases from internal combustion engines of construction, drilling equipment, vehicles, etc. Due to the high toxicity of carbon monoxide, it is necessary to create highly sensitive materials for CO sensors. So, when inhaling small concentrations of carbon monoxide (up to 1000 mg/m3), a person feels heaviness in the head, dizziness, nausea, a feeling of pleasant exhaustion, due to which a person cannot soon leave the affected area, and with prolonged (2–3 months) contact with CO, chronic carbon monoxide poisoning is possible at a concentration of 10-50 mg/m3. Therefore, the search for a new material having high sensitivity and selectivity to carbon monoxide is relevant. The purpose of this study is to develop a highly sensitive electronic gas sensor for detecting carbon monoxide at room temperature. The films were made by irrigation from a polymer solution containing graphene oxide and carbon nanotubes. The morphology of the surface of thin polymer films was investigated, spectral chemical analysis was carried out, voltampere characteristics of sensors were measureed0 and an IoT (Internet of Things) solution for remote monitoring was developed. The results show a good response and repeatability of the results at room temperature, allowing the thin films of the graphene polymer-CNT oxide composite to be considered a promising electronic sensor material for CO detection.