Acetone Concentration Research Articles

Microfabricated interdigital capacitive sensor and resonant sensor based on PPy/MoO3 hybrids for sensitivity-enhanced ammonia detection at room temperature

This paper proposes a microwave transduction-based gas sensor based on polypyrrole/molybdenum oxide composite (PPy/MoO3) hybrid material. Optimization of sensing material, measurement platform and fabrication techniques are carried out to achieve excellent ammonia gas real-time detection. Capacitance parameters analysis for the gas sensing response of capacitive sensor is proceeded based on PPy, MoO3, and PPy/MoO3 hybrids at room temperature. The results show that the PPy/MoO3 hybrid material exhibits a sensitivity-enhanced response to ammonia. The PPy/MoO3 capacitive sensor has good linearity (R2 =0.987), fast response, and good repeatability within 5–100 ppm ammonia concentration. Frequency parameters analysis for the gas sensing response of microwave resonator sensor is proceeded based on PPy/MoO3 hybrids in the range of 10 ppm to 100 ppm ammonia concentration at room temperature. The proposed microwave sensor has good linearity (R2 =0.991), good repeatability with 8 MHz standard deviation, high stability with gas response variation less than 2%, and anti-humidity capacity. Among 100 ppm concentration of isopropanol, acetone, ethanol, methanol and ammonia, ammonia exhibits 97.5 MHz frequency shift, which proves high sensitivity and good step toward selectivity. Therefore, this work could be regarded as a promising candidate in ammonia sensing application based on microwave solution.

Mixed Potential Type Acetone Sensor with Ultralow Detection Limit for Diabetic Ketosis Breath Analysis.

Breath analysis using gas sensors is an emerging method for disease screening and diagnosis. Since it is closely related to the lipid metabolism and blood ketone concentration of the body, the detection of acetone content in exhaled breath is helpful for the screening and monitoring of diabetes and ketosis. The development of an acetone sensor with high selectivity, stability, and low detection limit has been the research focus for this purpose. Here, we developed a mixed potential type acetone sensor based on Gd2Zr2O7 solid electrolyte and CoSb2O6 sensing electrode. The developed sensor exhibits an extremely low detection limit of 10 ppb, enabling linear detection for acetone in an extremely wide range of 10 ppb-100 ppm. The good results of systematic evaluation on selectivity, repeatability, and stability prove the superior reliability of the sensor, which is a prerequisite for the application in actual breath detection. The ability of the sensor to distinguish healthy people from diabetic ketosis patients was confirmed by using the sensor to detect the breath of healthy people and diabetic patients, proving the feasibility of the sensor in the diagnosis and monitoring of diabetic ketosis.

Experimental and Simulation Studies of Acetone Detection By Pt-Au Nanofilm Sensors

Introduction Acetone in exhaled breath is a biomarker of diabetes. However, since it is a very stable substance, its detection by chemical sensors has been a challenging task. Alloy nanoparticles have attracted great attention because of their great catalytic performance, and it has been reported that the response to acetone can be improved by functionalizing oxide semiconductors (In2O3) with PtAu nanoparticles [1]. However, the mechanism of better response to acetone has not been fully understood, which is partly because the effects of alloying and supporting materials cannot be separated in the composite material systems. In this study, we demonstrate that PtAu-alloy nanofilms, where the effect of supporting materials is eliminated, show a greater response to acetone than Pt nanofilms. Furthermore, the impact of alloying on sensing performance was studied by high-throughput atomistic simulation with neural network potentials. Method First, we fabricated Pt and PtAu nanofilm sensors. As the Pt and PtAu nanofilms, Pt and Pt/Au were deposited, respectively, by electron beam evaporation method. The thickness of Pt film is 3 nm, whereas Pt/Au thicknesses are 2.5 nm/0.5 nm. The electrodes consisted of 40-nm Pt and 40-nm Au layers, and they were annealed in N2 ambient for 1 hour at 300 oC. XRD measurements were performed to evaluate the alloy states for three samples: Pt (20nm), Au (20 nm), and PtAu (18 nm). The PtAu film for XRD was fabricated by repeating sequential depositions of 5-nm Pt and 1-nm Au three times. All the films were annealed for 1 hour at 300 oC in N2 ambient. The sensor responses to acetone were evaluated by measuring the resistance of Pt and PtAu at 260 oC under the following sequences.i) Dry air (15 min)ii) 1-ppm acetone in dry air (2 min)iii) Dry air (3 min)We applied DC current of 100 µA and the voltage difference between the terminals were measured. To examine the factors that contribute to the difference in sensing performance of PtAu and Pt nanofilms, we calculated the reaction pathway using the nudged elastic band method. All calculations were carried out with PFP version 2.0.0 on Matlantis [2]. DFT-D3 was used to describe the van der Waals interaction [3]. Results Pt, Au, and PtAu samples showed (111) peaks in the XRD analysis. The position of (111) peak of PtAu located between those of Pt and Au peaks, suggesting that PtAu was successfully alloyed. By applying the Vegard’s law, the composition of PtAu was determined to be 0.823:0.177, which is consistent with the thickness ratio. When acetone was exposed, the resistance of the devices decreased. The response of PtAu to acetone was greater than that of Pt. In addition, the responses of Pt and PtAu devices were proportional to the square root of the concentration of acetone. The limit of detections (LOD) determined by 3σ method were 76 ppb for Pt and 14 ppb for PtAu. Discussion We considered that H atoms introduced by CH dissociation of acetone prevent the adsorption of oxygens from the atmosphere and reduce the surface scattering of electrons, leading to a decrease in the resistance of Pt nanofilms. The Nudged Elastic Band method was used to calculate the activation energy of CH dissociation of acetone on the surface of Pt and PtAu. PtAu slab was prepared by replacing Pt atoms partly with Au atoms. The calculations showed that the activation energy for PtAu was 64-meV lower than that of Pt. In the transition state, the dissociated H atom stayed at the bridge site of Pt. When Pt atoms are substituted with Au atoms, the distance between Pt’s at the bridge site expands due to the large lattice constant of Au. As a result, the transition state became more stable on PtAu surface than on Pt surface. In fact, we confirmed that the activation energy was lowered as the Pt-Pt distance increased. Conclusion We demonstrated, for the first time, that PtAu nanofilm sensors show a greater response to acetone than Pt nanofilm. The atomic simulation demonstrated that the dehydrogenation of methyl group of acetone is the fundamental mechanism of the acetone sensing, and that the lattice expansion induced by replacing Pt with Au contributed to stabilize the transition state and to reduce the activation energy. Further optimization of the alloy composition should be essential to achieve a more highly sensitive acetone sensor.

Application and integration of deep learning in FAIMS for identifying acetone concentration

In practical applications, analytical instruments are used for both qualitative and quantitative analysis. However, for high-field asymmetric-waveform ion mobility spectrometry (FAIMS), most studies to date have been focused on the qualitative analysis of substances, with limited research on quantitative analysis. Explored here is the feasibility of using deep learning in FAIMS for quantitative analysis, aided by redesigning the FAIMS upper computer. Integrating spectrum creation and deep learning analysis into the FAIMS upper computer boosts the processing and analysis of FAIMS data, laying a foundation for applying FAIMS practically. For analysis using image processing, multiple FAIMS spectral lines obtained under different conditions are converted into a three-dimensional thermodynamic map known as a FAIMS spectrum, and multiple FAIMS spectrum are preprocessed to obtain the data set of this experiment. The principles of partial-least-squares regression and the XGBoost and ResNeXt models are introduced in detail, and the data are analyzed using these models, while exploring the effects of different model parameters and determining their optimal values. The experimental results show that the pre-trained ResNeXt deep learning model performs the best on the test set, with a root mean square error of 0.86 mg/mL, indicating the potential of deep learning in realizing quantitative analysis of substances in FAIMS.

A comprehensive meta-analysis of genetic parameters for resilience and productivity indicator traits in Holstein cattle

Selection for resilience indicator (RIND) traits in Holstein cattle is becoming an important breeding objective as the worldwide population is expected to be exposed to increased environmental stressors due to both climate change and changing industry standards. However, genetic correlations between RIND and productivity indicator (PIND) traits, which are already being selected for and have the most economic value, are often unfavorable. As a result, it is necessary to fully understand these genetic relationships when incorporating novel traits into selection indices, so that informed decisions can be made to fully optimize selection for both groups of traits. In the past 2 decades, there have been many estimates of RIND traits published in the literature, albeit in small populations. To provide valuable pooled summary estimates, a random-effects meta-analysis was conducted for heritability and genetic correlation estimates for PIND and RIND traits in worldwide Holstein cattle. In total, 926 heritability estimates for 9 PIND and 27 RIND traits, along with 362 estimates of genetic correlation (PIND × RIND traits) were collected. Resilience indicator traits were grouped into the following subgroups: Metabolic Diseases, Hoof Health, Udder Health, Fertility, Heat Tolerance, Longevity, and Other. Pooled estimates of heritability for PIND traits ranged from 0.201 ± 0.05 (energy-corrected milk) to 0.377 ± 0.06 (protein content), while pooled estimates of heritability for RIND traits ranged from 0.032 ± 0.02 (incidence of lameness, incidence of milk fever) to 0.497 ± 0.05 (measures of body weight). Pooled estimates of genetic correlations ranged from -0.360 ± 0.25 (protein content vs. milk acetone concentration) to 0.535 ± 0.72 (measures of fat-to-protein ratio vs. milk acetone concentration). Additionally, out of 243 potential genetic correlations between PIND and RIND traits that could have been reported, only 40 had enough published estimates to implement the meta-analysis model. Our results confirmed that the interactions between PIND and RIND traits are complex, and all relationships should be evaluated when incorporating novel traits into selection indices. This study provides a valuable reference for breeders looking to incorporate RIND traits for Holstein cattle into selection indices.

Electrochemical Nonenzymatic Acetone Sensing: A Novel Approach of Biosensor Platform Based on CNT/CuO Nanosystems

AbstractA promising approach for noninvasive medical diagnosis may be to measure the VOCs produced by metabolic changes or pathological disorders in human sweat, such as measuring the acetone levels in the presence of diabetes. Acetone is a by‐product of fat catabolism and serves as an indicator of ketosis and diabetes. The measurement of acetone may be used instead of glucose monitoring. Current research aims to develop and improve noninvasive methods of detecting acetone in sweat that are accurate, sensitive, and stable. The carbon nanotubes (CNTs)–copper oxide (CuO) nanocomposite (NC) improves direct electron transport to the electrode surface in this study. The complex‐precipitation method is used to make this NC. X‐ray diffraction (XRD) and scanning electron microscopy (SEM) are used to investigate the crystal structure and morphology of the prepared catalyst. Using cyclic voltammetry (CV) and amperometry, the electrocatalytic activity of the as‐prepared catalyst is evaluated. The electrocatalytic activity in artificial sweat solution is examined at various scan rates and acetone concentrations. The detection limit of the CNTs‐CuO NC catalyst is 0.05 mm, with a sensitivity of 16.1 mA cm−2 µm−1 in a linear range of 1–50 mm. Furthermore, this NC demonstrates a high degree of selectivity for various biocompounds found in sweat, with no interfering cross‐reactions from these species. The CNT‐CuO NC, as produced, has good sensitivity, rapid reaction time (2 s), and stability, indicating its potential for acetone sensing.

UiO-66-NH2-PEI combined with a hand-held catalytic combustion sensor for trace acetone detection in exhaled breath

The trace acetone determination in breath can be regarded as a noninvasive method for diagnostic of diabetes. There is an urgent demand to develop a simple method for acetone detection which can be easily performed at home. Here, UiO-66-NH2@PEI with the appropriate aperture size combined with the hand-held sensor was used to construct the adsorption–desorption sensing platform for separation and enrichment of acetone in exhaled breath (EB). UiO-66-NH2@PEI can realize the selective adsorption, desorption and separation for acetone in EB. The flameless combustion hand-held sensor can sensitively respond to acetone in the range of 0.2–12.0 ppm and it can achieve the accurate determination of acetone content in EB of diabetic patients. The hand-held sensor is inexpensive, lightweight and easy to operate, which has great application prospects for the widespread use for diabetic patients in family life.

A comparison study on the acetone sensing performance of preeminent nanostructures of SnO2 for diabetes diagnosis

Metal oxide semiconductor-based acetone sensors are of great need owing to their cost-effective easy production for real-time applications. Experiments on different morphologies of metal oxide nanostructures are gaining momentum for enhancing acetone sensing properties. 1D nanofibers and dangling bonds-rich facet exposed materials are eminent nanostructures in this field. In this article, we compare the acetone-sensing abilities of these nanostructures, including nanofibers and facet-exposed nanostructures. Acetone sensing qualities of the fabricated sensors were tested at different temperatures varying from 100 to 350 °C. Due to a significant number of dangling bonds on the surface, the octahedral nanoparticle sensor produced a higher response than the other sensors. At their respective operating temperatures, each of the manufactured sensors was capable of detecting a very low concentration of acetone (1 ppm). All of the samples had acceptable response and recovery times. The octahedral nanoparticle sensor’s excellent repeatability, reproducibility, and long-term stability made it a good choice for real-time detection of acetone in the exhaled breath of individuals with diabetes. In patients with diabetes, the exhaled breath exhibits an acetone concentration exceeding 1.8 ppm, whereas in healthy persons, this concentration typically falls between the ranges of 0.3–0.9 ppm.

Effect of various concentrations of common organic solvents on the growth and proliferation ability of Candida glabrata and their permissible limits for addition in drug susceptibility testing.

Dimethyl sulfoxide (DMSO), acetone, ethanol, and methanol are organic solvents commonly used for dissolving drugs in antimicrobial susceptibility testing. However, these solvents have certain antimicrobial activity. Currently, standardized criteria for the selection and dosage of drug solvents in drug susceptibility testing research are lacking. The study aims to provide experimental evidence for the selection and addition limit of drug solvents for the in vitro antifungal susceptibility test of Candida glabrata (C. glabrata). According to the recommendation of the Clinical and Laboratory Standards Institute (CLSI) M27-A3, a 0.5 McFarland C. glabrata suspension was prepared and then diluted 1:1,000. Next, a gradient dilution method was used to prepare 20%, 10%, 5%, and 2.5% DMSO/acetone/ethanol/methanol. The mixture was plated onto a 96-well plate and incubated at a constant temperature of 35 °C for 48 h. The inhibitory effects of DMSO, acetone, ethanol, and methanol on C. glabrata growth and proliferation were analyzed by measuring optical density values at 600 nm (OD600 values). After 48 h incubation, the OD600 values of C. glabrata decreased to different extents in the presence of the four common organic solvents. The decrease in the OD600 values was greater with increasing concentrations within the experimental concentration range. When DMSO and acetone concentrations were higher than 2.5% (containing 2.5%) and methanol and ethanol concentrations were higher than 5.0% (containing 5.0%), the differences were statistically significant compared with the growth control wells without any organic solvent (P < 0.05). All four organic solvents could inhibit C. glabrata growth and proliferation. When used as solvents for drug sensitivity testing in C. glabrata, the concentrations of DMSO, acetone, ethanol, and methanol should be below 2.5%, 2.5%, 5%, and 5%, respectively.

Rapid Determination of Five Residual Solvents in Ursodeoxycholic Acid Raw Materials

The chromatographic conditions were optimized using headspace gas chromatography, and a simple and rapid method was established for the simultaneous determination of five residual solvents in ursodeoxycholic acid raw materials. The corresponding quality standards were revised. The research results demonstrate that by utilizing a capillary column with a stationary phase consisting of 5% phenyl-95% dimethylpolysiloxane (HP-5, 30 m × 0.32 mm, film thickness 1.0 µm) and a flame ionization detector in conjunction with a headspace injection system and a programmed temperature ramping method, satisfactory analytical results can be achieved. The specific operating conditions are as follows: an initial column temperature of 45 °C, followed by a column temperature increase at a rate of 5 °C per minute up to 60 °C, then a further increase at a rate of 10 °C per minute up to 100 °C, and finally a rapid increase at a rate of 40 °C per minute up to 200 °C, where it is held for 10 min. Nitrogen is employed as the carrier gas at a flow rate of 1 mL/min with a split ratio of 14:1. The headspace vial temperature is maintained at 100 °C, with a sample equilibration time of 45 min. The concentration of methanol ranged from 0.06 mg/mL to 0.3 mg/mL, and the concentrations of acetone, tert-butanol, ethyl acetate, and triethylamine showed a good linear relationship with the peak area within the range of 0.1 mg/mL to 0.5 mg/mL (r = 0.999); The quantitation limits for methanol, acetone, tert-butanol, ethyl acetate, and triethylamine were 4.2, 0.9, 1.5, 1, and 0.1 μg/mL, respectively, with detection limits of 1.2, 0.25, 0.025, 0.3, and 0.025 μg/mL, respectively. The recovery rates of each solvent ranged from 92.9% to 106.0%, with RSD% (n = 9) less than 3.8%; the method exhibited good repeatability, with RSD% (n = 6) less than 2.5%. Furthermore, the robustness is good. The established method is simple, accurate, specific, and highly sensitive, and can be used for the simultaneous and rapid determination of five residual solvents in ursodeoxycholic acid raw materials.

Acetone and nanoparticles effect on performance and exhaust emissions of a diesel engine

This research investigated the effects of acetone and metal nano magnesium oxides (MNMgOs) on combustion and emissions in diesel engines. Tests were conducted at various load conditions at a speed of 1500 rpm. The results showed that the use of a low percentage (2 %) of acetone led to increases in instantaneous energy changes, cylinder pressures (CP), heat release rates (HRR), mean gas temperatures (MGT), and pressure rise rates (PRR). However, an increase in acetone concentration and the use of Acetone + MNMgOs resulted in a decrease in combustion parameters. Concentrations of 2 %, 5 %, and 10 % acetone reduced carbon monoxide (CO) emissions by 7.85 %, 11.35 %, and 2.23 % respectively, hydrocarbons (HC) by 10.84 %, 15.86 %, and 3.02 % respectively, and nitrogen oxides (NOx) emissions by 3.79 %, 2.02 %, and 10.25 % respectively. The combined use of acetone and MNMgOs resulted in a reduction of 1.10 % in CO emissions, 1.48 % in HC emissions, and 10.62 % in NOx emissions.

162 Evaluating the Potential of a Thermal Imaging System to Identify Subclinical Mastitis in Dairy Cattle

Abstract The objective was to evaluate the potential for the use of a thermal imaging system for the identification of subclinical mastitis in dairy cows. Multiparous Holstein dairy cows (n = 131) within 150 days in milk (DIM; range 65 to 155) were enrolled in the study at a commercial dairy farm in central Texas. Milk samples (10 mL) were collected from each quarter separately and evaluated for somatic cell counts (SCC; n*1000), fat (%), protein (%), lactose (%), SNF (%), BHBA (mM/L), acetone (mM/L), and milk urea nitrogen (MUN; mg/dL). A minimum of four thermal images per cow representing all four quarters were captured using a handheld infrared camera (Fluke TiS 75+) from approximately one-meter distance from the cow. All images were taken inside the milking parlor and after the morning milking during February 2023 to minimize the impact of daily ambient temperatures. Skin temperatures from each quarter (maximum, minimum, average) were extracted using Fluke Connect software. A total of 524 quarter-level milk samples and corresponding udder images were obtained, and 10 images were discarded from analyses due to the lack of appropriate resolution and focus. To prevent collinearity, a correlation matrix was developed using PROC CORR in SAS and variables with significant correlations were removed from the model. Subclinical mastitis was defined at the quarter level when SCC &amp;gt; 250,000. Statistical analyses were performed using mixed linear regression models (PROC MIXED) with cow and DIM as random effects in the model, and logistic regression model (PROC LOGISTIC) was fitted to evaluate the probability of the disease based on temperature and milk variables. Maximum and average udder temperatures did not demonstrate a significant relationship with subclinical mastitis status whereas minimum udder temperature was greater in sick quarters (29.6 ± 0.52 vs 27.5 ± 0.45; P = 0.003). Increased minimum udder temperature was also associated with BHBA (P &amp;lt; 0.0001), acetone (P &amp;lt; 0.0004), and MUN (P &amp;lt; 0.0007) concentrations in milk. Cows with subclinical mastitis had decreased BHBA (0.14 ± 0.037 vs 0.28 ± 0.031; P = 0.0036) and acetone (0.017 ± 0.003 vs 0.044 ± 0.003; P &amp;lt; 0.001). Odds of subclinical mastitis were associated with MUN values in milk (OR 0.94; CI 0.89 - 0.98) but not with any udder surface temperature variables. We conclude that an increase in the minimum temperature of the udder could be used as an indicator of subclinical mastitis but studies with larger datasets and using advanced image analysis techniques are warranted to validate these results.

PVA Coated Glass Substrates for Acetone Detection

Technology advancement in photonics has progressively tailor human need in healthcare industries. Inventing a new medical device or application for the mental and health sectors have make disease diagnosis easier. Without prevention, the number of sufferers may rise quickly. Studies have identified a way to diagnose diabetes illness by measuring a person's acetone level. The existing blood test have inferiority in term of invasive and dangerous if not handled properly. In this report, acetone concentration has been detected using a simple, low-cost Polyvinyl Alcohol (PVA) coated glass substrate platform as a potential diagnosis tool for diabetes patient. Based on the experiment results, the proposed sensor exhibits exceptional sensing performances for acetone detection in term of sensitivity, linearity, repeatability, stability and hysteresis

LiFe[formula omitted]O[formula omitted]-based gas sensor: A machine learning approach for selective VOCs detection

This work presents the development of novel LiFe5O8 micro-flowers through a single-step microwave-assisted hydrothermal approach. LiFe5O8 micro-flowers were used as a sensing element for the detection of highly cross-sensitive volatile organic compounds (VOC). Various characterization methods were also used to validate the material characteristics of the sensor. The measured response/recovery curve revealed that these unique micro flowers can detect even at 5 ppm concentrations of acetone, ethanol, and methanol with response values of 1.17, 1.37, and 1.23 at 100 °C respectively. The sensor’s selectivity issue was addressed by employing simpler Machine Learning (ML) algorithms (decision tree, random forest, K-nearest neighbor, and support vector machine) using the measured response values ranging from 5 ppm to 200 ppm. Further, the classification of the mixture and pure gases was performed using a random mixture of the three VOCs to enhance the selectivity. The article compares various extracted features to determine the best feature set for the deployed ML algorithms. Optimization algorithms such as grid and randomized search were employed to identify the most suitable parameters for achieving the best models. The testing results report an average classification accuracy of 98% and an R2-score of 0.98 for the three gases from the best model.

Highly sensitive chemoresistor based on Ag/TiO2/FTO sandwich structure for evaluation of component concentration in mixed ambient

The performance of membrane electrode assemblies (MEAs) in direct methanol fuel cells (DMFCs) can be greatly affected by ethanol as an impurity in methanol fuels. It is thus necessary to explore an effective method for accurately detecting the ethanol concentration in a mixed atmosphere of methanol and ethanol. Herein, we developed a chemoresistor based on Ag/TiO2/FTO sandwich structure and achieved accurate prediction for the concentration of each component in methanol-ethanol mixed atmosphere. First principles calculations were first performed to reveal the gas adsorption characteristics of TiO2 sensitive layer in different resistive state. It was indicated that methanol and ethanol molecules could be clearly distinguished by TiO2-based device in the high resistive state. In the gas-sensing test, the response value of Ag/TiO2/FTO chemoresistor in the high resistive state to 1 ppm methanol was 2.55, 14.8, 13.19, 15.04 and 17.34 times higher than that of the same concentration of ethanol, acetone, isopropanol, acetic acid and methyl formate, respectively. Meanwhile, when the device was in direct current mode after the response, an ultra-fast recovery characteristic (0.7 s) was observed due to the resistive switching function. Finally, the prediction of the component gas concentration in the methanol-ethanol mixed atmosphere was achieved by combining the optimized neural network algorithm. The present work brings new inspiration for future research on gas sensors.

Development and integration of a hierarchical Pd/WO3 acetone-sensing device for real-time exhaled breath monitoring with disposable face mask

This study introduces an inventive acetone-sensing device seamlessly integrated into a disposable face mask, enabling real-time continuous breath monitoring. The sensor demonstrates exceptional sensitivity, registering a response of 8.22 at 1 ppm and an impressive sensor response of 57.33 at 100 ppm of acetone concentration. Particularly noteworthy is the remarkable lower limit of detection (LOD) of 0.076 ppm within the concentration range of 0.1–0.8 ppm, underscored by a robust R2 value of 0.994. To validate practicality, the Pd/WO3 sensor was fabricated onto cellulose paper and utilized for real-time breath analysis, yielding a substantial sensor response of 1.70 at 8 vol% (equivalent to a single exhale breath volume). The unique design incorporates a built-in disposable face mask, facilitating dependable and convenient real-time breath analysis. Additionally, this research explores the profound impact of introducing acetone and Pd atoms on the energy levels and dipole moments. The species elucidated through density functional theory (DFT) investigations encompassing WO3, WO3-acetone, Pd-WO3, and Pd-WO3-acetone species. This work presents an innovative and cost-effective approach for developing a portable, non-invasive, and highly sensitive acetone-sensing device, effectively integrated into a disposable face mask for real-time breath analysis. This pioneering technology holds immense potential for various applications in healthcare and beyond.

Purification and Characterization of Alkaline Protease Isolated from Cotton (Gossypium hirsutum) Seeds

Proteases are widely utilized both in physiological and commercial fields such as medicine, food, detergent, and leather. Plant-originated proteases play a significant role in several biomedical fields due to their easy accessibility and activity. Pakistan is an agro-based country and can be an ideal place for the isolation of industrially important proteases from plant sources such as cotton, which is the main crop and frequently available and low cost. Purification of protease was carried out by fractionation with two-fold acetone, ethanol, methanol and various concentrations (40-80%) of ammonium sulphate. The precipitates formed were collected after centrifugation and dialyzed for 24 hours against universal buffer pH 7.0 and was centrifuged in a cooled refrigerated. The dialyzed sample was loaded on Sephadex G–100 gel column. The fractions of the samples were collected and their absorbance of protein was monitored at 280 nm. The homogeneity of the purified enzyme was checked by SDS gel electrophoresis The purified protease enzyme has optimum activity at 30°C and pH 8.0 when casein was used as substrate. The Km and Vmax values of purified cotton seed's alkaline protease activity was recorded as 0.03M and 17 μmol/minute respectively. Protease activity was increased by the addition of cysteine but inhibited by Iodoacetic acid and β-Mercaptoethanol and decreased with some metal ions. These characteristics of the purified enzyme allowed classifying it as a cysteine protease. In conclusion, this study suggests that the alkaline protease enzyme is the best choice for commercial use

Accurate Determination of Trace Water in Organic Solution by Quantitative Nuclear Magnetic Resonance.

A new method accompanied by a derived equation for accurate determination of trace water was developed by using quantitative 1H nuclear magnetic resonance (qNMR) spectroscopy. Given that the response for each chemically distinct moiety is uniformly proportional to the number of the corresponding resonant nuclei within the analyte, it is practicable to directly quantify the water content via its proton number using qNMR. In this study, three water standards with known water contents (e.g., 10.02, 1.006, and 0.103 mg/g), which were accurately determined by a well-established Coulometric Karl Fischer (CKF) titration method, were measured by using the developed qNMR method. An excellent agreement between the results from these two methods was obtained. Then, the water content of Sudan I was determined by high-field NMR (HF-NMR) spectroscopy, and the water contents of acetone and bioethanol were measured by low-field NMR (LF-NMR) spectroscopy. These results were compared with the water content measured by the CKF method to confirm the applicability of the established qNMR method. The developed method can eliminate the influences of environmental humidity and background water in the solvent; subsequently, the results calculated by the derived equation were comparable to the nominal values. Under the optimal conditions, the limit of quantitation of this method was as low as 6.7 μg. The recommended sample sizes for practical samples with various water contents (e.g., 10.02, 1.006, and 0.103 mg/g) were determined to be 5, 50, and 60 mg, respectively, which are much smaller than those required for the CKF method. The new method has a static and stable process without any side reactions, and the traceability to the SI unit can be directly achieved through the NMR internal standard. This method overcomes the limitations of the CKF method, especially for measuring methanol-insoluble substances.

Elucidating the Role of Ion Suppression in Secondary Electrospray Ionization.

Ion suppression is a known matrix effect in electrospray ionization (ESI), ambient pressure chemical ionization (APCI), and desorption electrospray ionization (DESI), but its characterization in secondary electrospray ionization (SESI) is lacking. A thorough understanding of this effect is crucial for quantitative applications of SESI, such as breath analysis. In this study, gas standards were generated by using an evaporation-based system to assess the susceptibility and suppression potential of acetone, deuterated acetone, deuterated acetic acid, and pyridine. Gas-phase effects were found to dominate ion suppression, with pyridine exhibiting the most significant suppressive effect, which is potentially linked to its gas-phase basicity. The impact of increased acetone levels on the volatiles from exhaled breath condensate was also examined. In humid conditions, a noticeable decrease in intensity of approximately 30% was observed for several features at an acetone concentration of 1 ppm. Considering that this concentration is expected for breath analysis, it becomes crucial to account for this effect when SESI is utilized to quantitatively determine specific compounds.

Effects of Catalyst Ink Storage on Polymer Electrolyte Fuel Cells

The shelf-life of catalyst ink for fabricating polymer electrolyte fuel cells (PEFCs) is relevant for large-scale manufacturing with unforeseen production stops. In this study, the storage effects on the physicochemical characteristics of catalyst ink (Pt/C, Nafion, 2-propanol, water) and subsequently manufactured catalyst layers are investigated. Sedimentation analysis showed that catalyst particles are not fully stabilized by charge interaction induced by Nafion. Acetone was found to be an oxidation product, even in freshly prepared ink with platinum catalyzing the reaction. Rotating disk electrode analysis revealed that the electrochemically active surface area is, overall, minimally increased by storage, and the selectivity towards water formation (4-electron pathway) is unharmed within the first 48 h of storage. MEAs prepared from stored ink reach almost the same current density level after conditioning via potential cycling. The open-circuit voltage (OCV) increases due to increased catalyst availability. Scanning electron microscopy and mercury intrusion porosimetry showed that with increasing acetone content, the pore structure becomes finer, with a higher specific surface area. Electrochemical impedance spectroscopy revealed that this results in a more hindered mass transfer but lowered charge transfer resistance. The MEA with the highest OCV and power output and the lowest overall cell resistance was fabricated from catalyst ink stored for a duration of four weeks.