Gas Concentration Research Articles

Nagynyomású hidrogénatmoszférás kemence gyártása szénacélok elridegedésének vizsgálatához

Összefoglalás. A hidrogén tárolása iránti igény egyre növekszik, melynek oka az, hogy a hidrogén mint alternatív energiahordozó jelentős szerepet játszik a szén-dioxidkibocsátás-csökkentési törekvésekben. Azonban, az elridegedési folyamatok körében a hidrogén által előidézett károsodások jelentik a legkomolyabb problémát az acélokra nézve. Kutatómunkánk során egy nagynyomású hidrogénatmoszférás hőkezelésre alkalmas autoklávot terveztünk, majd gyártottunk. Az autoklávban P355 NH minőségű alapanyagból kimunkált szabványos Charpy-féle ütőpróbatesteket hőkezeltünk 150 °C-on, 40 bar túlnyomáson, 200 órán keresztül, tiszta hidrogén atmoszférában. A vizsgálatok eredményei alapján megállapítottuk, hogy a jelentős mértékű elridegedés a hidrogénezési folyamat után sem történt. Summary. The demand for hydrogen storage is growing. The primary reason for this is that hydrogen as an alternative energy carrier is playing a significant role in carbon reduction efforts as a fuel for road and maritime transport. In addition, hydrogen can be seen as a long-term flexible energy storage option. Hydrogen as an energy carrier is expected to play a significant role in residential and industrial use in the future. A first step in this development is the mixing of hydrogen with natural gas in small quantities. Increasing the share of hydrogen would not only reduce CO2 emissions, but would also facilitate the development of different hydrogen production methods and thus reduce production costs. The upper safety limit for hydrogen blending with natural gas is set by the national specification of the natural gas supply, possible material quality restrictions and the tolerance of the most sensitive equipment in the network. For this reason, the maximum allowable hydrogen content in natural gas is generally limited to 2,5%. However, among the embrittlement processes, hydrogen-induced damage is the most serious problem for both non-alloy and low-alloy steels. Atomic hydrogen diffuses in steel at high rates. The diffusion rate is orders of magnitude higher than that of other elements; this is due to the small atomic diameter of hydrogen. To investigate the degradation of different carbon steels in a high-pressure hydrogen atmosphere, a hydrogenation furnace was designed and fabricated at the Department of Materials Science and Engineering at BME. The hydrogenation furnace is the main part of a complex mechanical engineering system, for the operation of which the mechanical, heating, electrical supply, control and gas handling components are indispensable. The entire design process of the furnace was led by József Blücher, Professor Emeritus at BME, with the help of the engineers and technicians working on the project. Standard Charpy impact test specimens were machined from P355 NH grade material to test the embrittlement of carbon steels. The hydrogenation temperature was 150 °C, the internal overpressure in the chamber was 40 bar, the hydrogenation time was 200 hours and the atmosphere was hydrogen gas of purity 5.0. The impact test was carried out at -20, 0 and +20 °C. Based on the results of the tests, it can be concluded that there was no significant degree of degradation both before hydrogenation and after prolonged exposure to hydrogen. It can be concluded that the tube material used as a sample is suitable for operation in a hydrogen medium. Based on the analysis of the burst areas and impact values of the impact test specimens, it was concluded that hydrogen did not cause any observable damage to the test material.

AI-Enabled Portable E-Nose Regression Predicting Harmful Molecules in a Gas Mixture.

The biomimetic electronic nose (e-nose) technology is a novel technology used for the identification and monitoring of complex gas molecules, and it is gaining significance in this field. However, due to the complexity and multiplicity of gas mixtures, the accuracy of electronic noses in predicting gas concentrations using traditional regression algorithms is not ideal. This paper presents a solution to the difficulty by introducing a fusion network model that utilizes a transformer-based multikernel feature fusion (TMKFF) module combined with a 1DCNN_LSTM network to enhance the accuracy of regression prediction for gas mixture concentrations using a portable electronic nose. The experimental findings demonstrate that the regression prediction performance of the fusion network is significantly superior to that of single models such as convolutional neural network (CNN) and long short-term memory (LSTM). The present study demonstrates the efficacy of our fusion network model in accurately predicting the concentrations of multiple target gases, such as SO2, NO2, and CO, in a gas mixture. Specifically, our algorithm exhibits substantial benefits in enhancing the prediction performance of low-concentration SO2 gas, which is a noteworthy achievement. The determination coefficient (R2) values of 93, 98, and 99% correspondingly demonstrate that the model is very capable of explaining the variation in the concentration of the target gases. The root-mean-square errors (RMSE) are 0.0760, 0.0711, and 3.3825, respectively, while the mean absolute errors (MAE) are 0.0507, 0.0549, and 2.5874, respectively. These results indicate that the model has relatively small prediction errors. The method we have developed holds significant potential for practical applications in detecting atmospheric pollution detection and other molecular detection areas in complex environments.

Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence

Abstract. Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open-data, open-science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.11388387, Smith et al., 2024a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO2e yr−1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.

Mechanisms associated with sulfidation gas release, desulphurisation and degradation of rubber powder in crumb rubber modified asphalt

ABSTRACT Odorous sulphidation gases are released during the construction of crumb rubber-modified asphalt (CRMA), causing pollution to the environment. To study the associated mechanism of sulfidation gas (H2S, CH4S, COS and CS2) release and the desulphurisation and degradation of CR in asphalt, the release law of sulphidation gas of CRMA was studied by a gas detector. Gel permeation chromatography (GPC), fluorescence microscope, toluene insoluble (TI) and potentiometric titration tests were used to study the desulphurisation and degradation of CR. The results showed that vulcanised CR in CRMA led to the generation of sulphidation gas with the increase in temperature, time and stirring speed. The average molecular weight of CRMA increased, while the TI and unsaturation (A) decreased after the desulphurisation and degradation of CR. Under the influence of temperature, heating time and stirring speed, the A was reduced by 0.72%∼8.87%, 1.18%∼10.69% and 0.75%∼8.12%, respectively. There was a strong correlation between the concentration of sulphidation gas and the desulphurisation and degradation parameters of CRMA. The reaction of ·H, –CH3, CO with the –SxH generated by the C–S, S–S, C=C fracture during the desulphurisation and degradation of CR was the main reason for the generation of sulphidation gas.

Distinguishing methane from other hydrocarbons using machine learning and atmospheric pressure plasma optical emission spectroscopy

The ability to detect gas molecule and assign a concentration offers an inventive solution in the field of plasma integrated with machine learning. The most important finding of this work is firstly, to develop an algorithm for gas-molecule identification using three different hydrocarbons (CH4, C2H2, C2H6) and secondly, organize a model for detecting gas concentration (classification). For this reason, initially eight different gases evaluated. The study confirms the present of the unique emission lines as a gas indicator, i.e., a wavelength peak related to hydrocarbons identified via increasing in C x H y concentration. By means of unique variable important in projection, hydrocarbons can be distinguished. Our proposed Chemometric analysis strategy examined on >1000 samples and results development of suitable techniques that are sufficiently rapid, accurate and innovative. This demonstrates the potential for real-time, portable, and continuous monitoring of trace gases with potential applications in medical, environmental, and industrial gas sensing.

Experimental Evidence of Primary Permeability at Very Low Gas Content in Crystal‐Rich Silicic Magma

AbstractEruptive dynamics is influenced by gas escape from the ascending magma. Gas pathways form in the magma via bubble coalescence, leading to gas channeling. Magmatic crystals play a key role in gas channel formation. This work constrains experimentally decompression‐induced coalescence in high‐crystallinity silicic magmas without external deformation, focusing on low gas content and bimodal crystal size (microlites and phenocrysts). All percolating samples have permeabilities of 10−14 m2 at bulk porosities of 7–10 vol% and bulk crystallinities up to 75 vol%. Our results demonstrate the possibility of coalescence‐related outgassing at high pressure (120–350 MPa) and without external strain, which corresponds to magma stagnating deep in a volcanic conduit. Channeling at such low gas content implies that bimodal crystallinity favors effusive over explosive volcanic behavior. It may also be the missing physical mechanism explaining gas transfer across magmatic systems despite high melt viscosity and low or absent magma extrusion.

Techno-economic analysis of water-based CO2 capture method based on adiabatic compressed air energy storage: Comparison with monoethanolamine-based CO2 capture method

Carbon dioxide (CO2) capture and storage is considered an effective measure to mitigate climate change, used to reduce CO2 emissions from industrial sectors, especially for coal-fired power plants. In our previous work, a novel water-based CO2 capture (WCC) method based on adiabatic compressed air energy storage (A-CAES) was developed. This method is simple and environmentally friendly. However, unlike the widely used monoethanolamine (MEA)-based CO2 capture (MCC) technology, which consumes low-grade thermal energy, the WCC technology consumes high-grade electrical energy. Therefore, in this work, a comprehensive techno-economic analysis of the WCC technology is conducted and compared with the MCC technology from the perspective of carbon emission reduction. A universal economic assessment criterion of CO2 capture cost based on electricity prices is proposed, and the techno-economic analysis is based on the cost in 2022 USD ($). The result shows that the CO2 capture cost of the WCC system ranges from 53.74 to 71.70 $/tonne CO2 due to the different factors considered in computational models, taking 63.57%–84.81% of the MCC system under the same capture rate (85%). The dynamic payback period of the WCC system ranges from 7.14 years to 20.52 years, while the MCC system failed to recover capital throughout the entire lifecycle. Moreover, the CO2 capture cost of the WCC system can be reduced to below carbon tax (43 $/tonne CO2) when the CO2 concentration in the feed flue gas is above 18 vol%, achieving positive benefits with no carbon trading required, which means the WCC system can achieve positive profitability for higher CO2 concentration emission sectors. The results provide significant guidance for developing and promoting the WCC technology.

Assessing nitrous oxide emissions from algal-bacterial photobioreactors devoted to biogas upgrading and digestate treatment

Nitrous oxide (N2O) emissions in High Rate Algal Ponds (HRAP) can negatively affect the sustainability of algal-bacterial processes. N2O emissions from a pilot HRAP devoted to biogas upgrading and digestate treatment were herein monitored for 73 days. The influence of the pH (7.5, 8.5, and 9.5), nitrogen sources (100 mg L−1 of N–NO2-, N–NO3-, and N–NH4+) and illumination on N2O emissions from the algal-bacterial biomass of the HRAP was also assessed in batch tests. Significantly higher N2O gas concentrations of 311.8 ± 101.1 ppmv were recorded in the dark compared to the illuminated period (236.9 ± 82.6 ppmv) in the HRAP. The batch tests revealed that the highest N2O emission rates (49.4 mmol g−1 TSS·h−1) occurred at pH 8.5 in the presence of 100 mg N–NO2-/L under dark conditions. This study revealed significant N2O emissions in HRAPs during darkness.

Highly sensitive QCM gas sensor based on ZIF-8-derived porous carbon and multi-walled carbon nanotubes decorated nanocomposite for salmon meat freshness detection

The concentration of amine gases are often used as an indicator of the freshness of seafood. However, currently used detection methods are usually complex to operate, have excessive time periods. Therefore, it is necessary to design and develop a sensor that can quickly and accurately detect a wide range of target amine gases with ease of operation and excellent performance. This paper demonstrated a quartz crystal microbalance (QCM) gas sensor based on ZIF-8-derived porous carbon and multi-walled carbon nanotubes decorated nanocomposite (ZIF-C/MWCNTs). The ZIF-C/MWCNTs composite was successfully prepared by high temperature carbonization of ZIFs templates and room temperature diffusion method. Our prepared sensor was operated at room temperature (25℃) and relative humidity (35 %), the results indicated that the limit of detections (LODs) of the QCM sensor for methylamine (MA), trimethylamine (TMA), ammonia (NH3) and dimethylamine (DMA) were 3.12 μmoL·L−1, 1.44 μmoL·L−1, 1.97 μmoL·L−1 and 2.81 μmoL·L−1, respectively. Finally, the improved QCM sensor was used to detect salmon meat stored at 4℃ and these results of these assays were juxtaposed with those obtained through Microdiffusion as an indicator of salmon meat freshness. The sensor was expected to be a potential device to detect the freshness of instant seafood quickly and accurately.

Prediction of oxygen content in flue gas of power plant with stacked target-enhanced autoencoder and attention-based LSTM

Accurate and robust measurement of the oxygen content in the flue gas of power plant is significant to optimal the coal combustion process. Conventional hard measurement algorithms have low accuracy, short lifetime and high cost. Therefore, it is urgent to establish a precise and reliable soft measurement model. However, how to extract effective feature representations from complex process data is still the difficult and hot spot in the soft measurement field. The paper develops a novel soft measurement model, which integrates stacked target-enhanced autoencoder (STAE) with attention mechanism-based long short-term memory (ALSTM) in view of the above issues. The data cleaning strategy is firstly designed to filter the redundant data from the original data. Then STAE is developed to extract the useful features, which introduces target output into each autoencoder to ensure the feature representation is output-related and stacks several autoencoder units to learn high-level information. The extracted hierarchical features can not only represent the input data, but also have high correlation with the target output. A three-layer-based attention network is designed to allocate different weights on the different levels’ features. Finally, due to the dynamic characteristic of the problem, a LSTM-based prediction network is dexterously designed to learn the potential relation from extracted features to target output, i.e., oxygen content. Numerous real-word data is collected from a 300 MW power plant and extensive experiments are conducted. The maximum prediction errors of A and B are 0.42 and 0.41. The 95.1 % prediction errors of A side are within [−0.2, 0.2], and the 96.2 % prediction errors of B side are within [−0.2, 0.2].

Study of spatiotemporal evolution of coupled airflow–gas–dust multi-field diffusion at low-gas tunnel

The increasing level of mechanization in coal mining means more dust and gas are generated during excavation operations in tunnels. The high concentrations of dust and gas severely affect production efficiency and the physical and mental health of workers. Here, Ansys Fluent simulations were performed to derive the spatiotemporal evolution of coupled airflow–dust–gas diffusion in a low-gas excavation face. The aim was to optimize pollution control by determining the optimal duct distance, L, from the working face in the excavation tunnel. Our results showed that the airflow field affects the coupled diffusion and transport of dust and gas. According to a comparison of the effects of different duct distances from the working face, when L = 6 m, the average dust concentration in the tunnel is low (257.6 mg/m3), and the average gas concentration in the tunnel is 0.28 %, which does not exceed the safety limit. Accordingly, the optimal distance of the duct for pollution control is 6 m. The results of field measurements supported the validity of the simulation. Our findings can be used to improve the air quality in tunnels, thereby keeping miners safe and the working area clean.

Microbial treatment of waste crumb rubber: Reducing energy consumption and harmful emissions during asphalt production process

The emergence of crumb rubber modified asphalt (CRMA) has promoted the recycling utilization of waste tires and the improvement of asphalt performance. However, its unsatisfactory storage stability and high construction temperature have brought about excessive energy consumption and environmental challenges. In this study, the waste crumb rubber (CR) was bio-desulfurized by the synergy between two types bacteria for 7 days and 14 days, respectively. On this basis, bio-desulfurization crumb rubber modified asphalt (BCRMA) was prepared. The desulfurization effect of CR was characterized. Thermal storage stability and environmental performance of BCRMA were mainly investigated. The results showed that bio-desulfurization increased the number of pores, surface roughness and specific surface area of CR, and decreased the content of sulfur element. Bio-desulfurization of CR improved the insufficient thermal storage stability of rubberized asphalt and reduced the risk of system segregation. Bio-desulfurization CR has been proven to be a promising environmentally friendly material that can effectively lower the release concentration and release type of harmful flue gas from CRMA. This study makes the large-scale promotion and application of CRMA possible.

Integrating Dynamic State Information to Enhance Gas Concentration Modeling Accuracy

Integrating Dynamic State Information to Enhance Gas Concentration Modeling Accuracy

Capsules for the Diagnosis and Treatment of Gastrointestinal Motility Disorders- A Game Changer.

Over the last few decades, there have been remarkable strides in endoscopy and radiological imaging that have advanced gastroenterology. However, the management of neurogastroenterological disorders has lagged behind, in part handicapped by the use of catheter-based manometry that is both non-physiological and uncomfortable. The advent of capsule technology has been a game changer for both diagnostic and therapeutic applications. Here, we discuss several capsule devices that are available or under investigation. There are three technologies that are FDA approved. Wireless motility capsule measures pH and pressure and provides clinically impactful information regarding gastric, small intestine and colonic transit, without radiation that has been demonstrated to guide management of gastroparesis, dyspepsia and constipation. Wireless ambulatory pH monitoring capsule is currently the gold standard for assessing gastroesophageal acid reflux. In the therapeutics arena, an orally ingested vibrating capsule has been recently FDA approved for the treatment of chronic constipation, supported by a robust phase 3 clinical trial which showed significant improvement in constipation symptoms and quality of life. There are several capsules currently under investigation. Smart capsule bacterial detection system and Capscan® are capsules that can sample fluid in the small or large bowel and provide microbiome analysis for detection of small intestinal bacterial (SIBO) or fungal overgrowth (SIFO). Another investigational gas sensing capsule analyzing hydrogen, CO2, volatile fatty acids and capsule orientation, can measure regional gut transit time and luminal gas concentrations and assess gastroparesis, constipation or SIBO. Therapeutically, other vibrating capsules are in development. Innovations in capsule technology are poised to transform our ability to investigate gut function physiologically, and non-invasively deliver targeted treatment(s), thereby providing both accurate diagnostic information and luminally-directed, safe therapy.

Preparation of ZnO Thick Films Activated with UV-LED for Efficient H2S Gas Sensing

In this work, ZnO thick films were synthesized via two simple and easy methods, mechanochemical synthesis and screen-printing deposition. The ZnO powders were obtained through milling at low temperature with milling times of 20, 40, and 60 min. The ZnO thick films were fabricated by depositing 10 cycles of ZnO inks onto glass substrates. The characterization of ZnO thick films revealed a thickness ranging from 4.9 to 5.4 µm with a surface roughness between 85 and 88 nm. The structural analysis confirmed a hexagonal wurtzite crystalline structure of ZnO, both in powders and in thick films, with a preferred orientation on the (002) and (101) planes. Nanostructures with sizes ranging from 36 to 46 nm were observed, exhibiting irregular agglomerated shapes, with an energy band found between 2.77 and 3.02 eV. A static experimental set up was fabricated for gas sensing tests with continuous UV-LED illumination. The ZnO thick films, well adhered to the glass substrate, demonstrated high sensitivity and selectivity to H2S gas under continuous UV-LED illumination at low operating temperatures ranging from 35 to 80 °C. The sensitivity was directly proportional, ranging from 3.93% to 22.40%, when detecting H2S gas concentrations from 25 to 600 ppm.

Realization of CO2 gas sensors and broadband photodetectors using metal/high-k CeO2/p-Si heterojunction

Realization of high-k dielectric oxide material-based devices such as photodetectors (PDs)/gas sensors fabricated on silicon substrate seems to be the utmost promising as a cost-effective approach to use in next generation optoelectronic field. We have explored metal/CeO2/p-Si heterojunction to construct as a broadband (BB) PD and CO2 gas sensor device. The effect of post-annealing procedure on photodetection and CO2 gas sensing characteristics were correlated using AFM, XRD, XPS, Raman and UV–Vis studies. At 0 V bias, the fabricated as-deposited Au/CeO2/p-Si PD device exhibits outstanding performance with enhanced responsivity of 85 AW−1 (at 910 nm), detectivity of 1.36×1015 Jones (at 850 nm), EQE of 1.3×104 % (at 850 nm), faster rise and fall times of 124 ms and 107 ms (at 900 nm). On the other hand, the photodetection characteristic parameters were slightly deteriorated as a function of annealing with respect to the as-deposited device. One of the causes for this fact was attributed to the increase in rms surface roughness (AFM) and decrease in absorbance of CeO2 thin film (UV–Vis). Additionally, Ag/CeO2/p-Si heterojunction was studied as a CO2 gas sensor and evaluated response/recovery times as a function of CO2 gas concentration. Sensing responses of CeO2 as-deposited, CeO2-400, CeO2-500, CeO2-600 and CeO2-700 °C were around 58, 60, 62, 81 and 90 %, respectively, when exposed to 200 ppm of CO2. Thus, we validate that the prospect of integrating enhanced performance in BB PDs and CO2 gas sensors using metal/CeO2/p-Si heterojunction could serve as a basic building block in near future optoelectronic applications. Furthermore, the effect of post-annealing temperature on the morphological, structural, BB photodetection and CO2 gas sensing properties were discussed in detail.

Thermodynamic Computational Method of Thermal Decomposition Gas Content in Transformer Oil Considering Temperature and Competitive Reaction

Thermodynamic Computational Method of Thermal Decomposition Gas Content in Transformer Oil Considering Temperature and Competitive Reaction

RGO/CuCl-Based Flexible Gas Sensor for High-Concentration Carbon Monoxide Gas Detection at Room Temperature.

Carbon monoxide (CO) gas sensors are widely used, especially for environmental monitoring in confined spaces such as the landscape of mining cave ruins in mining parks, which is essential for ensuring the health and safety of tourists and staff. In this paper, a flexible CO gas sensor based on polyimide, interdigital electrodes, and reduced graphene oxide (RGO)/cuprous chloride (CuCl) composite film is designed and manufactured for reliable room temperature detection of high-concentration CO gas. The structure size of RGO/CuCl gas-sensitive film is 5 × 5 mm. The RGO with a 62.65% C-C bond is prepared by the thermal reduction method. The test results show that the sensor has a high response in the range of 400-2000 ppm CO gas concentration, and the maximum response is 1.56. The linear correlation coefficient of the sensor is 0.981, which indicates that the sensor has good output response characteristics. The response time of the sensor for 400 ppm CO gas is 332 s, which indicates that the sensor has a fast response rate. Furthermore, compared with other gases, the sensor shows higher gas selectivity for CO gas. This sensor has the characteristics of small size and easy attachment; therefore, it can be installed on the shoulder or helmet of tourists' safety suits, providing personalized real-time warning prompts for tourists' physical health status.

Solid-liquid particle flow sealing mucus (PFSM) in enhancing coalbed methane (CBM) recovery: Multiple-perspectives analysis and mechanism insights

The paper presents an in-depth investigation of solid-liquid two-phase particle flow sealing mucus (PFSM) for enhanced coalbed methane (CBM) recovery. PFSM is composed of solid waste particles such as fly ash and rubber particles. The PFSM is assessed using multiple-perspectives analysis, which includes measurements of water retention, pressure expansion, rheological characteristics, adhesion, wettability, microscopy and field case studies. Single-factor and multi-factor studies are used to optimize slurry material ratios. The results show that PFSM has outstanding water retention characteristics, with over 80 % retention for 30 days at 30 °C, and impressive expansion performance, with 9.52 % at 0.6 MPa. The shear thinning curve conforms to the Cross model. After 30 s, the final contact angle is 75.17 °, which is about 6 ° smaller than that of cement based materials. Field experiments show that, after applying PFSM, the drainage gas concentration can be improved at least 60 % comparing to other sealing materials. This research findings could offer novel insights into enhancing CBM extraction, indicating potential for safer and more efficient coal mine production.

A cellulose nanocrystal-based dual response of photonic colors and fluorescence for sensitive benzene gas detection

Benzene, as a common volatile organic compound, represents serious risk to human health and environment even at low level concentration. There is an urgent concern on visualized, sensitive and real time detection of benzene gases. Herein, by doping Fe3+ and graphene quantum dots (GQDs), a cellulose nanocrystal (CNC) chiral nematic film was designed with dual response of photonic colors and fluorescence to benzene gas. The chiral nematic CNC/Fe/GQDs film could respond to benzene gas changes by reversible motion. Moreover, chiral nematic film also displays reversible responsive to humidity changes. The resulting CNC/Fe/GQDs chiral nematic film showed excellent response performance at benzene gas concentrations of 0–250 mg/m3. The maximal reflection wavelength film red shifted from 576 to 625 nm. Furthermore, structural color of CNC/Fe/GQDs chiral nematic film change at 44 %, 54 %, 76 %, 87 %, and 99 % relative humidity. Interestingly, due to the stability of GQDs to water molecules, CNC/Fe/GQDs chiral nematic film exhibit fluorescence response to benzene gas even in high humidity (RH = 99 %) environment. Besides, we further developed a smartphone-based response network system for quantitively determinization and signal transformation. This work provides a promising routine to realize a new benzene gas response regime and promotes the development of real-time benzene gas detection.