Exhaled Human Breath Research Articles

Fabrication of Au-decorated V2O5 based sensor for ultra trace level detection of ammonia in an environment resembling human exhaled breath

Ammonia stands out as a significant breath biomarker for kidney-related diseases. Here we present the fabrication of a gold (Au) decorated V2O5 based sensor designed for detecting ammonia at parts per billion (ppb) level. The V2O5 particles were synthesized by thermal decomposition of ammonium metavanadate (NH4VO3) instead of using tedious and expansive synthesis routes. The product of the thermal decomposition of NH4VO3 was characterized utilizing various analytical techniques. Then this product (V2O5) was used for gas sensing study as original and when decorated with gold. The V2O5 based sensor, decorated with gold (Au) for a duration of 10 s, exhibits favorable characteristics including a linear response range spanning 50–5000 ppb, heightened sensitivity, stability, and remarkable resistance to humidity within the range of 50–90 % relative humidity (RH). Remarkably, the sensor demonstrates insensitivity towards higher concentrations of possible interfering liquid vapors. The sensor exhibits response and recovery times of 36 s and 300 s, respectively, in the presence of 1000 ppb ammonia and has the potential for accurately detecting and quantifying ammonia in an environment resembling human exhaled breath. The sensing device based on this material will be a valuable tool for clinical applications.

Long-lifespan, biodegradable, self-disinfecting, and gas-sensing electronic mask with a Janus-structured all-natural fiber network for personal healthcare

Conventional disposable surgical masks have become an integral part of our daily lives, however, present a limited filtration efficiency, brief operative lifespan, and inability to degrade naturally, bringing a heavy burden to the environment. Moreover, these masks cannot efficaciously eliminate bacteria, potentially causing secondary and cross infections among users, thereby failing to curb the spread of infectious diseases. Herein, a fire-new, long-lifespan, biodegradable, self-disinfecting, and gas-sensing electronic-mask is nano-engineered with a Janus-structured all-natural fiber network (SA-CPN) constructed from animal-collagen and plant-fibers. SA-CPN demonstrates exceptional filtration performance (99.9%) for PM2.5 and maintains outstanding filtration efficiency after 10 test-cycles or 32 h in high-humidity conditions. SA-CPN exhibits robust antibacterial origins for extended periods, with antibacterial rates of 98.30%, 99.36%, and 98.11% against P aeruginosa, S aureus, and E coli, respectively, and can effectively filter airborne bacterial aerosols. Moreover, SA-CPN achieves real-time detection of ammonia concentrations, effectively identifying ammonia levels in exhaled human breath and external environments, and monitoring the human respiratory rate, potentially identifying underlying health conditions. The directional water vapor transmission capability of SA-CPN improves comfort when wearing. Notably, SA-CPN can fully biodegrade within 5 h under enzyme action. The proposed multifunctional electronic mask, featuring biocompatibility, biodegradability, self-disinfection, and ammonia sensing capabilities, holds significant promise in personal medical protective equipment for health monitoring and disease prevention.

Co3O4/CQDs composite for selective ammonia detection in exhaled human breath analysis

Co3O4 was synthesized using electrospinning method and different amounts of carbon quantum dots (CQDs) were subsequently doped into the Co3O4 matrix via grinding, resulting in Co3O4/CQDs composite materials with various ratios. Gas sensing tests revealed that the resulting composite Co3O4/CQDs sensors exhibited excellent performance at a low temperature of 50°C, with outstanding selectivity towards ammonia gas and rapid response and recovery characteristics. Specifically, response and recovery time for 50 ppm ammonia gas were 14 s and 164 s, respectively. The outcomes of the exhalation simulation test utilizing sensors composed of this material demonstrate that the sensor's response to simulated chronic kidney disease breath closely approximates that of pure biological samples (1.08), exceeding the average response value of healthy exhaled breath samples (1.0). This demonstrates the sensor's capability to differentiate between healthy individuals and chronic kidney disease patients despite significant water vapor and carbon dioxide interference. This study provides valuable insights for the development of more efficient ammonia sensors and their role in the early detection of chronic kidney disease.

Portable and Hand-Held Ammonia Gas Sensor Enables Noninvasive Prediagnosis of Helicobacter pylori Infection.

Disease diagnosis of Helicobacter pylori (Hp) through human exhaled breath analysis has attracted considerable attention. However, conventional methods, such as carbon 13 (13C) breath test and infrared spectrometers, are facing the challenge of achieving portability and reliability synchronously. Herein, we report a portable and hand-held Hp analyzer using a bimetallic PtRu@SnO2-based gas sensor for the prediagnosis of Hp infection, which is based on detecting ammonia (NH3) as a potential biomarker in exhaled breath. Owing to the surface functionalization through highly catalytically active bimetallic PtRu nanoparticles (NPs) prepared by a photochemical reduction strategy, the PtRu@SnO2-based sensor exhibits high sensitivity and selectivity toward trace-level (200 ppb) NH3 even at high-humidity surroundings (80% RH). Consequently, the designed portable and hand-held Hp analyzer makes the accurate determination of NH3 at 800 ppb in exhaled breath. The tuning of energy band structure and electrical characteristics and the catalytic modulation of NH3 oxidation by PtRu NPs are proposed to be the reasons behind the enhanced NH3 gas-sensing performance, as confirmed by in situ analysis using an online MKS MultiGas 2030 FTIR gas analyzer. This work paves the way for the prediagnosis of Hp infection using a metal oxide gas sensor.

Deep-Learning-Based Blood Glucose Detection Device Using Acetone Exhaled Breath Sensing Features of α-Fe2O3-MWCNT Nanocomposites.

Owing to the correlation between acetone in human's exhaled breath (EB) and blood glucose, the development of EB acetone gas-sensing devices is important for early diagnosis of diabetes diseases. In this article, a noninvasive blood glucose detection device through acetone sensing in EB, based on an α-Fe2O3-multiwalled carbon nanotube (MWCNT) nanocomposite, was successfully developed. Different amounts of α-Fe2O3 were added to the MWCNTs by a simple solution method. The optimized acetone gas sensor showed a response of 5.15 to 10 ppm acetone gas at 200 °C. Also, the fabricated sensor showed very good sensing properties even in an atmosphere with high relative humidity. Since the EB has high humidity, the proposed sensor is a promising device to exactly detect the amount of acetone in EB with high humidity. The sensor was powered by a 3200 mAh battery with the possibility of charging using mains electricity. To increase the reliability and calibration of the sensing device, a practical test was taken to detect acetone EB from 50 volunteers, and a deep learning algorithm (DLA) was used to detect the effect of various factors on the amount of acetone in each person's acetone EB. The proposed device with ±15 errors had almost 85% correct responses. Also, the proposed device had excellent response, short response time, good selectivity, and good repeatability, leading it to be a suitable candidate for noninvasive blood glucose sensing.

The detection of acetone in exhaled breath using gas Pre-Concentrator by modified Metal-Organic framework nanoparticles

Volatile organic compounds (VOCs) from exhaled breath are promising indicators for the diagnostics of human health conditions. However, the composition of breath is rather complex, including water vapors and various tiny amounts of gases and biomarkers. Pre-concentrator plays a significant role in capturing and concentrating target gas in the gas mixture. In this work, the MIL-101 (Cr) nanoparticles are coated with polydimethylsiloxane (PDMS) through physical vapor deposition process to concentrate acetone under high humidity and room temperature. Experimentally, the newly developed material exhibits significant improvement in signal intensity that is 76.3 times greater than a commercial reference material under relative humility of 80 %. The detection range is also proven to be desirable (from 100 ppb to 2500 ppb), capturing the spectrum of acetone concentrations typically found in human exhaled breath. Moreover, following a thermal desorption process, the device demonstrates a high degree of linearity with a coefficient of 0.9956. The modified metal–organic framework materials are made into a flexible thin-film-shape device, that could be embedded in a facemask. The proposed device could meet the critical requirements for sampling, concentrating and detecting of exhaled breath biomarkers, thereby opening a new opportunity as part of the flexible electronic systems on face masks to facilitate quantitative breath analyses.

Assemble and validation of a simulated device of human exhaled breath aerosols for screening of illicit drug abuse by HPLC-TQ-MS/MS detection

Collecting exhaled breath aerosols (EBA) as a sample has a great potential to monitoring illicit drug abuse due to advantages of simple, non-invasiveness and unrestricted sampling. However, scarcity of positive samples has cramped development of more efficient techniques for monitoring illicit drug abuse in EBA. In this work, a simulated human exhaled breath aerosol (SHEBA) generating device based on Venturi jet principle was constructed by integrating nebulizing unit and collection unit to prepare positive EBAs. By means of ultra high-performance hyphenated with triple quadrupole tandem mass spectrometry (HPLC-TQ-MS/MS), using caffeine as a target drug, the device parameters were investigated by studying the effects of flow rates of nebulizing and auxiliary gases, drug concentration and etc., the performance was further validated by commonly abused drugs such as amphetamines (AMP, MAMP, MDA and MDMA). Electret material as adsorbent was used to collect SHEBAs generated by the device, achieving HPLC-TQ-MS/MS detection of the captured drugs at 40.0–2000.0 pg/filter. By this way, caffeine content in EBAs from six volunteers was successfully detected in the range of 51.6 ± 6.8–708 ± 51 pg/filter after drinking the caffeinated beverage. These validation experiments proved that SHEBA generating device could not only meet to the requirement of EBA analysis for illicit drug abuse at trace levels, but also provide the correction factors to calibrate the lower detection value caused by incomplete material adsorption.

Functionalized N95 Face Mask with a Chemical-Free Paper-Based Collector for Exhaled Breath Analysis: SARS-CoV-2 Detection with a Printed Immunosensor as a Case Study.

Exhaled breath electrochemical sensing is a promising biomedical technology owing to its portability, painlessness, cost-effectiveness, and user-friendliness. Here, we present a novel approach for target analysis in exhaled breath by integrating a comfortable paper-based collector into an N95 face mask, providing a universal solution for analyzing several biomarkers. As a model analyte, we detected SARS-CoV-2 spike protein from the exhaled breath by sampling the target analyte into the collector, followed by its detection out of the N95 face mask using a magnetic bead-based electrochemical immunosensor. This approach was designed to avoid any contact between humans and the chemicals. To simulate human exhaled breath, untreated saliva samples were nebulized on the paper collector, revealing a detection limit of 1 ng/mL and a wide linear range of 3.7-10,000 ng/mL. Additionally, the developed immunosensor exhibited high selectivity toward the SARS-CoV-2 spike protein, compared to other airborne microorganisms, and the SARS-CoV-2 nucleocapsid protein. Accuracy assessments were conducted by analyzing the simulated breath samples spiked with varying concentrations of SARS-CoV-2 spike protein, resulting in satisfactory recovery values (ranging from 97 ± 4 to 118 ± 1%). Finally, the paper-based hybrid immunosensor was successfully applied for the detection of SARS-CoV-2 in real human exhaled breath samples. The position of the collector in the N95 mask was evaluated as well as the ability of this paper-based analytical tool to identify the positive patient.

Systematic study of polymer gas sampling bags for offline analysis of exhaled breath

Polymeric bags are a widely applied, simple, and cost-effective method for the storage and offline analysis of gaseous samples. Various materials have been used as sampling bags, all known to contain impurities and differing in their cost, durability, and storage capabilities. Herein, we present a comparative study of several well-known bag materials, Tedlar (PVF), Kynar (PVDF), Teflon (PTFE), and Nalophan (PET), as well as a new material, ethylene vinyl copolymer (EVOH), commonly used for storing food. We investigated the influences of storage conditions, humidity, bag cleaning, and light exposure on volatile organic compound concentration (acetone, acetic acid, isoprene, benzene, limonene, among others) in samples of exhaled human breath stored in bags for up to 48 h. Specifically, we show high losses of short-chain fatty acids (SCFAs) in bags of all materials (for most SCFAs, less than 50% after 8 h of storage). We found that samples in Tedlar, Nalophan, and EVOH bags undergo changes in composition when exposed to UV radiation over a period of 48 h. We report high initial impurity levels in all the bags and their doubling after a period of 48 h. We compare secondary electrospray ionization and proton transfer reaction mass spectrometry in the context of offline analysis after storage in sampling bags. We provide an analytical perspective on the temporal evolution of bag contents by presenting the intensity changes of all significantm/zfeatures. We also present a simple, automated, and cost-effective offline sample introduction system, which enables controlled delivery of collected gaseous samples from polymeric bags into the mass spectrometer. Overall, our findings suggest that sampling bags exhibit high levels of impurities, are sensitive to several environmental factors (e.g. light exposure), and provide low recoveries for some classes of compounds, e.g. SCFAs.

Evaluation of tetrachloroethylene (PCE) and its degradation products in human exhaled breath and indoor air in a community setting

Tetrachloroethylene (PCE) is a widely utilized volatile chemical in industrial applications, including dry cleaning and metal degreasing. Exposure to PCE potentially presents a significant health risk to workers as well as communities near contamination sites. Adverse health effects arise not only from PCE, but also from PCE degradation products, such as trichloroethylene (TCE) and vinyl chloride (VC). PCE, TCE, and VC can contaminate water, soil, and air, leading to exposure through multiple pathways, including inhalation, ingestion, and dermal contact. This study focused on a community setting in Martinsville, Indiana, a working-class Midwestern community in the United States, where extensive PCE contamination has occurred due to multiple contamination sites (referring to 'plumes'), including a Superfund site. Utilizing proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS), PCE, TCE, and VC concentrations were measured in the exhaled breath of 73 residents from both within and outside the plume areas. PCE was detected in 66 samples, TCE in 26 samples, and VC in 68 samples. Our results revealed a significant positive correlation between the concentrations of these compounds in exhaled breath and indoor air (Pearson correlation coefficients: PCE = 0.75, TCE = 0.71, and VC = 0.89). This study confirms the presence of PCE and its degradation products in exhaled breath in a community exposure investigation, demonstrating the potential of using exhaled breath analysis in monitoring exposure to environmental contaminants. This study showed the feasibility of utilizing PTR-TOF-MS in community investigations to assess exposure to PCE and its degradation products by measuring these compounds in exhaled breath and indoor air.

A hybrid learning approach to better classify exhaled breath's infrared spectra: A noninvasive optical diagnosis for socially significant diseases.

Early diagnosis is crucial for effective treatment of socially significant diseases, such as type 1 diabetes mellitus (T1DM), pneumonia, and asthma. This study employs a diagnostic method based on infrared laser spectroscopy of human exhaled breath. The experimental setup comprises a quantum cascade laser, which emits in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3-12.8 μm (780-1890 cm-1), and a Herriott multipass gas cell with a specific optical path length of 76 m. Using this setup, spectra of exhaled breath in the mid-infrared range were obtained from 165 volunteers, including healthy individuals, patients with T1DM, asthma, and pneumonia. The study proposes a hybrid approach for classifying these spectra, utilizing a variational autoencoder for dimensionality reduction and a support vector machine method for classification. The results demonstrate that the proposed hybrid approach outperforms other machine learning method combinations.

BreathXplorer: Processing Online Breathomics Data Generated from Direct Analysis Using High-Resolution Mass Spectrometry.

Nontargeted breath analysis in real time using high-resolution mass spectrometry (HRMS) is a promising approach for high coverage profiling of metabolites in human exhaled breath. However, the information-rich and unique non-Gaussian metabolic signal shapes of real-time HRMS-based data pose a significant challenge for efficient data processing. This work takes a typical real-time HRMS technique as an example, i.e. secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS), and presents BreathXplorer, an open-source Python package designed for the processing of real-time exhaled breath data comprising multiple exhalations. BreathXplorer is composed of four main modules. The first module applies either a topological algorithm or a Gaussian mixture model (GMM) to determine the start and end points of each exhalation. Next, density-based spatial clustering of applications with noise (DBSCAN) is employed to cluster m/z values belonging to the same metabolic feature, followed by applying an intensity relative standard deviation (RSD) filter to extract real breath metabolic features. BreathXplorer also offers functions of (1) feature alignment across the samples and (2) associating MS/MS spectra with their corresponding metabolic features for downstream compound annotation. Manual inspection of the metabolic features extracted from SESI-HRMS breath data suggests that BreathXplorer can achieve 100% accuracy in identifying the start and end points of each exhalation and acquire accurate quantitative measurements of each breath feature. In a proof-of-concept study on exercise breathomics using SESI-HRMS, BreathXplorer successfully reveals the significantly changed metabolites that are pertinent to exercise. BreathXplorer is publicly available on GitHub (https://github.com/HuanLab/breathXplorer). It provides a powerful and convenient-to-use tool for the researchers to process breathomics data obtained by directly analysis using HRMS.

Nylon 6 film coated with poly-tetrahydrofuran sol–gel solution in face mask as a non-invasive in vivo sampling device for caffeine in human exhaled breath aerosol

Caffeine is an alkaloid compound that can excite the central nervous system and effectively relieve fatigue in moderation. However, excessive caffeine consumption can block blood vessels, raising blood pressure and increasing the risk of atherosclerosis. The International Agency for Research on Cancer of the World Health Organization has listed caffeine in category 3 carcinogens, so it is crucial that caffeine be detected easily and accurately. Exhaled breath aerosol (EBA), which consists of a large number of volatile substances and complex biological matrices, can not only reflect the physiological state of the human body, ingested substances, and environmental exposures; on the other hand, the characteristics of non-invasive sampling also make EBA analysis has a broad application prospect in the field of human health monitoring and disease diagnosis. This paper used a combination of nylon 6 film coated with poly-tetrahydrofuran (PTHF) and a medical N95 mask to construct a convenient and direct sampling device, which can be used to collect caffeine ingested by humans non-invasively from EBA. Volunteers wore a mask for a defined period of time after consuming a certain amount of caffeine. The samples were next back-extracted with methanol and detected and analyzed using gas chromatography-high resolution mass spectrometry (GC-HRMS). The results showed that under the optimized analytical conditions, the PTHF-coated nylon 6 film was effective in collecting caffeine from human EBA, and the peak time of caffeine was 23.44 min. The mask-loaded coated device in this study has the advantages of being comfortable and efficient, safe and non-invasive as well as easy to operate, and by combining with mass spectrometry molecular techniques it can achieve high sensitivity and specificity analysis of trace components, which is expected to be used for the early diagnosis of respiratory diseases in clinical analysis.

Femtosecond Laser Ionization Mass Spectrometry for Online Analysis of Human Exhaled Breath.

A variety of organic compounds in human exhaled breath were measured online by mass spectrometry using the fifth (206 nm) and fourth (257 nm) harmonic emissions of a femtosecond ytterbium (Yb) laser as the ionization source. Molecular ions were enhanced significantly by means of resonance-enhanced, two-color, two-photon ionization, which was useful for discrimination of analytes against the background. The limit of detection was 0.15 ppm for acetone in air. The concentration of acetone in exhaled breath was determined for three subjects to average 0.31 ppm, which lies within the range of normal healthy subjects and is appreciably lower than the range for patients with diabetes mellitus. Many other constituents, which could be assigned to acetaldehyde, ethanol, isoprene, phenol, octane, ethyl butanoate, indole, octanol, etc., were observed in the exhaled air. Therefore, the present approach shows potential for use in the online analysis of diabetes mellitus and also for the diagnosis of various diseases, such as COVID-19 and cancers.

In Situ Collection and SERS Detection of Nitrite in Exhalations on Facemasks Based on Wettability Differences.

As one of the common carriers of biological information, along with human urine specimens and blood, exhaled breath condensate (EBC) carries reliable and rich information about the body's metabolism to track human physiological normal/abnormal states and environmental exposures. What is more, EBC has gained extensive attention because of the convenient and nondestructive sampling. Facemasks, which act as a physical filter barrier between human exhaled breath and inhaled substances from the external environment, are safe, noninvasive, and economic devices for direct sampling of human exhaled breath and inhaled substances. Inspired by the ability of fog collection of Namib desert beetle, a strategy for in situ collecting and detecting EBC with surface-enhanced Raman scattering is illustrated. Based on the intrinsic and unique wettability differences between the squares and the surrounding area of the pattern on facemasks, the hydrophilic squares can capture exhaled droplets and spontaneously enrich the analytes and silver nanocubes (AgNCs), resulting in good repeatability in situ detection. Using R6G as the probe molecule, the minimal detectable concentration can reach as low as 10-16 M, and the relative standard deviation is less than 7%. This proves that this strategy can achieve high detection sensitivity and high detection repeatability. Meanwhile, this strategy is applicable for portable nitrite analysis in EBC and may provide an inspiration for monitoring other biomarkers in EBC.

P-N Heterojunction formation: Metal Sulfide@Metal Oxide Chemiresistor for ppb H2S Detection from Exhaled Breath and Food Spoilage at Flexible Room Temperature.

The development of a portable, low-cost sensor capable of accurately detecting H2S gas in exhaled human breath at room temperature is highly anticipated in the fields of human health assessment and food spoilage evaluation. However, achieving outstanding gas sensing performance and applicability for flexible room-temperature operation with parts per billion H2S gas sensors still poses technical challenges. To address this issue, this study involves the in situ growth of MoS2 nanosheets on the surface of In2O3 fibers to construct a p-n heterojunction. The In2O3@MoS2-2 sensor exhibits a high response of 460.61 to 50 ppm of H2S gas at room temperature, which is 19.5 times higher than that of the pure In2O3 sensor and 322.1 times higher than that of pure MoS2. The In2O3@MoS2-2 also demonstrates a minimum detection limit of 3 ppb and maintains a stable response to H2S gas even after being bent 50 times at a 60° angle. These exceptional gas sensing properties are attributed to the increase in oxygen vacancies and chemisorbed oxygen on In2O3@MoS2-2 nanofibers as well as the formation of the p-n heterojunction, which modulates the heterojunction barrier. Furthermore, in this study, we successfully applied the In2O3@MoS2-2 sensor for oral disease and detection of food spoilage conditions, thereby providing new design insights for the development of portable exhaled gas sensors and gas sensors for evaluating food spoilage conditions at room temperature.

Hf3C2O2 MXene: A promising NH3 gas sensor with high selectivity/sensitivity and fast recover time at room temperature

Owing to metallic conductivity, tunable surface chemistry, mechanical flexibility, high surface area and chemical stability, MXenes have emerged as promising candidates for room-temperature gas sensors. In this study, gas sensing performances of the newly synthesized Hf3C2 MXene with oxygen termination toward a wide range of common molecules (NH3, H2O, H2S, H2, CO2, CO, CH4, N2 and NO) were investigated by first-principles density functional calculations. With the most negative adsorption energy, the highest charge transfer and the shortest adsorption distance, the adsorption of NH3 among the investigated gases causes the most significant changes in electrical conductivity and work function of Hf3C2O2 substrate, thus holds the biggest gas response. Only the NH3 exhibits strong chemical interactions with Hf3C2O2, and other gas molecules are weakly chemisorbed or physisorbed. All these indicate that Hf3C2O2 exhibits high selectivity and sensitivity to NH3. The adsorption energy of NH3 falls within the appropriate range for room-temperature gas sensors, enabling Hf3C2O2 to maintain NH3 sensitivity while also achieving a fast recovery time. Furthermore, giving that human exhaled breath does not affect, and may even enhance, the selectivity and sensitivity of Hf3C2O2 towards NH3, Hf3C2O2 can serve effectively as an NH3 sensor in human disease detection.

Sensitive Detection of OCS Using Thermal Conversion Combined with Spectral Reconstruction Filtering Differential Optical Absorption Spectroscopy.

Carbonyl sulfide (OCS) is a toxic gas produced during industrial processes that poses risks to both human health and industrial equipment. Therefore, detecting OCS concentrations plays a crucial role in early hazard warning. This paper presents an online system for detecting OCS at the ppb level using thermal conversion and spectral reconstruction filtering differential optical absorption spectroscopy (SRF-DOAS). First, OCS, which is not suitable for DOAS due to its weak absorption characteristics, is completely transformed into SO2 with strong absorption characteristics under high-temperature conditions. Then, the spectral reconstruction filtering method (SRF) is proposed to eliminate the noise and interference. The core idea of the method is to arrange the spectrum according to the spectral intensity from small to large rather than wavelength, reconstructing the spectrum into a new spectrum with linear characteristics. The reconstructed spectrum can remove noise and interference by linear fitting and retain the characteristic of SO2 oscillation absorption. Next, we demonstrate the ability of the reconstructed spectral method to remove noise and interference by comparing the spectra of the inverse-reconstructed gas mixture and SO2. The relative deviation of 0.88% at 100 ppb and detection limit of 7.26 ppb*m for OCS were obtained using the SRF-DOAS method. Finally, the reliability of the system was confirmed by measurements of OCS concentrations in mixture gas of OCS and air, as well as in human exhaled breath.

Oxygen vacancy-mediated metal-organic gel-derived α-Fe2O3 for anomalous acetone sensing behavior

The development of acetone gas sensors with high sensitivity, low detection limits and scalability holds significant importance for industrial production safety and disease diagnosis. Herein, oxygen vacancies-enriched α-Fe2O3 nanoparticles (M-Fe2O3 NPs) were synthesized through a novel metal-organic gel template strategy. Gas sensing experiments revealed that the prepared M-Fe2O3 sensor displayed unique p-type semiconductor behavior, distinct from the n-type commercial α-Fe2O3 (C-Fe2O3) sensor. Moreover, the sensor demonstrated excellent acetone sensing performance, including high response (2.6 @ 20 ppm), low detection limit (0.5 ppm), remarkable repeatability and selectivity, even under 80% relative humidity (RH), displaying impressive response and recovery properties. The enhanced p-type sensing properties of the M-Fe2O3 sensor were attributed to oxygen vacancies facilitating inversion (hole) layer formation and accelerating chemical reactions on the sensing materials surface, as evidenced by gas sensing performance data and O2-TPD characterization. Finally, the feasibility of preliminary diabetes diagnosis was demonstrated by detecting acetone levels in human exhaled breath. This work not only presents a straightforward approach for designing oxygen vacancies-enriched metal oxides but also has potential applications in constructing high-performance acetone sensing systems for diabetes diagnosis.

The recent progress on nanomaterial-based chemosensors for diagnosis of human exhaled breath: a review

The recent progress on nanomaterial-based chemosensors for diagnosis of human exhaled breath: a review