Characterizing Key Volatile Pollutants Emitted from Adhesives by Chemical Compositions, Odor Contributions and Health Risks.

As one of the major sources of volatile pollutants in indoor air, gaseous emissions from adhesives during interior decoration have attracted increasing concern. Identifying major volatile pollutants and the risk in adhesive gaseous emissions is of great significance, but remains rarely reported. In the present research, we assessed the major volatile pollutants emitted from white emulsion adhesive and silicone adhesive samples (n = 30) from three aspects: chemical composition, odor and health risk contributions. The results showed that a total of 21 volatile pollutants were detected. Significantly, xylene was the most concentrated compound from white emulsion adhesives, accounting for 45.51% of the total concentrations. Butanone oxime was the most concentrated compound in silicone adhesives, accounting for 69.86% of the total concentrations. The trends in odor concentration (evaluated by the odor activity value method) over time were well correlated with the total chemical concentrations. Xylene (58.00%) and butanone oxime (76.75%) showed the highest odor contribution, respectively. Moreover, from an integrated perspective of chemical emissions, odor and health risk contributions, xylene, ethylbenzene, ethyl acetate and benzene were identified as the key volatile pollutants emitted from the white emulsion adhesives, while butanone oxime, butanone, and ethanol were the key volatile pollutants emitted from the silicone adhesives. This study not only identified the key volatile pollutants but also provided characteristics of odor and health risks of gas emitted from adhesives.

Chemoselective and Highly Sensitive Quantification of Gut Microbiome and Human Metabolites.

The microbiome has a fundamental impact on the human host's physiology through the production of highly reactive compounds that can lead to disease development. One class of such compounds are carbonyl-containing metabolites, which are involved in diverse biochemical processes. Mass spectrometry is the method of choice for analysis of metabolites but carbonyls are analytically challenging. Herein, we have developed a new chemical biology tool using chemoselective modification to overcome analytical limitations. Two isotopic probes allow for the simultaneous and semi-quantitative analysis at the femtomole level as well as qualitative analysis at attomole quantities that allows for detection of more than 200 metabolites in human fecal, urine and plasma samples. This comprehensive mass spectrometric analysis enhances the scope of metabolomics-driven biomarker discovery. We anticipate that our chemical biology tool will be of general use in metabolomics analysis to obtain a better understanding of microbial interactions with the human host and disease development.

High-Performance Cataluminescence Sensor Based on Nanosized V2O5 for 2-Butanone Detection.

The development of high-performance sensors is of great significance for the control of the volatile organic compounds (VOCs) pollution and their potential hazard. In this paper, high crystalline V2O5 nanoparticles were successfully synthesized by a simple hydrothermal method. The structure and morphology of the prepared nanoparticles were characterized by TEM and XRD, and the cataluminescence (CTL) sensing performance was also investigated. Experiments found that the as-prepared V2O5 not only shows sensitive CTL response and good selectivity to 2-butanone, but also exhibits rapid response and recovery speed. The limit of detection was found to be 0.2 mg/m3 (0.07 ppm) at a signal to noise ratio of 3. In addition, the linear range exceeds two orders of magnitude, which points to the promising application of the sensor in monitoring of 2-butanone over a wide concentration range. The mechanism of the sensor exhibiting selectivity to different gas molecules were probed by quantum chemistry calculation. Results showed that the highest partial charge distribution, lowest HOMO-LUMO energy gap and largest dipole moment of 2-butanone among the tested gases result in it having the most sensitive response amongst other VOCs.

UHPLC-QqQ-MS/MS method development and validation with statistical analysis: Determination of raspberry ketone metabolites in mice plasma and brain.

Raspberry ketone (RK) (4-(4-hydroxyphenyl)-2-butanone) is the major compound responsible for the characteristic aroma of red raspberries, and has long been used commercially as a flavoring agent and recently as a weight loss supplement. A targeted UHPLC-QqQ-MS/MS method was developed and validated for analysis of RK and 25 associated metabolites in mouse plasma and brain. Dispersion and projection analysis and central composite design were used for method optimization. Random effect analysis of variance was applied for validation inference and variation partition. Within this framework, repeatability, a broader sense of precision, was calculated as fraction of accuracy variance, reflecting instrumental imprecision, compound degradation and carry-over effects. Multivariate correlation analysis and principle component analysis were conducted, revealing underlying association among the manifold of method traits. R programming was engaged in streamlined statistical analysis and data visualization. Two particular phenomena, the analytes' background existence in the enzyme solution used for phase II metabolites deconjugation, and the noted lability of analytes in pure solvent at 4 ℃ vs. elevated stability in biomatrices, were found critical to method development and validation. The approach for the method development and validation provided a foundation for experiments that examine RK metabolism and bioavailability.

Machine Vision Methods, Natural Language Processing, and Machine Learning Algorithms for Automated Dispersion Plot Analysis and Chemical Identification from Complex Mixtures.

Gas-phase trace chemical detection techniques such as ion mobility spectrometry (IMS) and differential mobility spectrometry (DMS) can be used in many settings, such as evaluating the health condition of patients or detecting explosives at airports. These devices separate chemical compounds in a mixture and provide information to identify specific chemical species of interest. Further, these types of devices operate well in both controlled lab environments and in-field applications. Frequently, the commercial versions of these devices are highly tailored for niche applications (e.g., explosives detection) because of the difficulty involved in reconfiguring instrumentation hardware and data analysis software algorithms. In order for researchers to quickly adapt these tools for new purposes and broader panels of chemical targets, it is critical to develop new algorithms and methods for generating libraries of these sensor responses. Microelectromechanical system (MEMS) technology has been used to fabricate DMS devices that miniaturize the platforms for easier deployment; however, concurrent advances in advanced data analytics are lagging. DMS generates complex three-dimensional dispersion plots for both positive and negative ions in a mixture. Although simple spectra of single chemicals are straightforward to interpret (both visually and via algorithms), it is exceedingly challenging to interpret dispersion plots from complex mixtures with many chemical constituents. This study uses image processing and computer vision steps to automatically identify features from DMS dispersion plots. We used the bag-of-words approach adapted from natural language processing and information retrieval to cluster and organize these features. Finally, a support vector machine (SVM) learning algorithm was trained using these features in order to detect and classify specific compounds in these represented conceptualized data outputs. Using this approach, we successfully maintain a high level of correct chemical identification, even when a gas mixture increases in complexity with interfering chemicals present.

A highly sensitive ultra-high performance liquid chromatography/tandem mass spectrometry method with in-source fragmentation for rapid quantification of raspberry ketone.

Raspberry ketone (RK) is the characteristic aromatic compound in raspberry (Rubus idaeus L.) with wide applications as food additive and anti-obesity agent. However, quantification of RK has presented difficulties in MS detection and reliable LC-MS method for RK analysis in literature is in limit to date. In order to facilitate quality control of raspberry derived products and RK metabolomics study, this study aimed to develop a validated and sensitive UHPLC-MS/MS method. Strong in-source fragmentation was noted and the fragmental ion of 107 m/z produced was selected as the precursor ion for MRM detection, and as such the electrospray ionization performance was optimized by fractional factorial design to accommodate such ion-source dissociation behavior as well as its moderate volatility. A pathway involving the formation of quinone-like structure with strong conjugation was proposed to explain the intense in-source fragmentation. The MRM transition was optimized with product ion of 77 m/z selected as the quantifier ion. The method featured low limit of quantification of ∼2 ng/mL and allowed for rapid detection of RK in fresh raspberries following direct sample preparation. RK contents were found to be higher from locally grown and harvested farm sources compared to commercial products shipped into the state, and higher in those at late-stage compared with early-stage maturity. No correlations in RK content between organic and non-organic labels were noted.

Sources of methacrolein and methyl vinyl ketone and their contributions to methylglyoxal and formaldehyde at a receptor site in Pearl River Delta.

Methacrolein (MACR) and methyl vinyl ketone (MVK) are two major intermediate products from the photochemical oxidation of isoprene, the most important biogenic volatile organic compound. In addition, MACR and MVK have primary emissions. Investigating the sources and evolution of MACR and MVK could provide helpful information for the oxidative capacity of the atmosphere. In this study, hourly measurements of isoprene, MACR, and MVK were conducted at a receptor site in the Pearl River Delta region (PRD), i.e., the Heshan site (HS), from 22 October to 20 November, 2014. The average mixing ratios of isoprene, MACR and MVK were 151 ±â€¯17, 91 ±â€¯6 and 79 ±â€¯6 pptv, respectively. The daily variations and the ratios of MVK/MACR during daytime and nighttime suggested that other sources besides isoprene photooxidation influenced the MACR and MVK abundances at the HS. Positive matrix factorization was utilized to resolve the sources of MACR and MVK. Five sources were identified and quantified, including biogenic emissions, biomass burning, secondary formation, diesel, and gasoline vehicular emissions. Among them, secondary formation made the greatest contribution to observed MACR and MVK with average contributions of ~45% and ~70%, respectively. Through the yields of secondary products from the oxidation of MACR and MVK by the OH radical and the concentrations of MACR and MVK, it was found that methylglyoxal and formaldehyde were the main oxidation products of MACR and MVK at the HS site. Overall, this study evaluated the roles of primary emissions on ambient levels of MACR and MVK and advanced the understanding of photochemical oxidation of MACR and MVK in the PRD.

A comparison between the four Geldart groups on the performance of a gas-phase annular fluidized bed photoreactor for volatile organic compound oxidation.

Heterogeneous photocatalytic oxidation (PCO) is a widely studied alternative for the elimination of volatile organic compounds (VOC) in air. In this context, research on novel photoreactor arrangements to enhance PCO rates is desired. Annular fluidized bed photoreactors (AFBPR) have yielded prominent results when compared to conventional thin film reactors. However, very few works aimed at optimizing AFBPR operation. In this study, TiO2 photocalytic agglomerates were synthesized and segregated in specific size distributions to behave as Geldart groups A, B, C, and D fluidization. The TiO2 agglomerates were characterized by XRD, FTIR spectra, and N2 adsorption. Photocatalyst performances were compared in a 10-mm gapped AFBPR for degrading the model pollutant methyl-ethyl-ketone (MEK), using a 254-nm radiation source. Geldart group C showed to be inadequate for AFBPR operation due to the short operation range between fluidization and elutriation. In all the cases, photocatalytic reaction rates were superior to sole UV photolysis. Group A and group B demonstrated the highest reaction rates. Considerations based on mass transfer suggested that the reasons were enhanced UV distribution within the bed at lower flow rates and superior catalyst surface area at higher flow rates. Results also revealed that groups A, B, and D perform equally per catalyst area within an AFBPR if the fluidization numbers (FN) are high enough.

The individual contribution of starter and non-starter lactic acid bacteria to the volatile organic compound composition of Caciocavallo Palermitano cheese.

The contribution of two starter (Lactobacillus delbrueckii and Streptococcus thermophilus) and nine non-starter (Enterococcus casselliflavus, Enterococcus faecalis, Enterococcus durans, Enterococcus gallinarum, Lactobacillus casei, Lactobacillus paracasei, Lactobacillus rhamnosus, Pediococcus acidilactici and Pediococcus pentosaceus) species of lactic acid bacteria (LAB) to the volatile organic compounds (VOCs) of Caciocavallo Palermitano cheese was investigated. The strains used in this study were isolated during the production/ripening of the stretched cheese and tested in a cheese-based medium (CBM). The fermented substrates were analyzed for the growth of the single strains and subjected to the head space solid phase micro-extraction (HS-SPME) and gas chromatography - mass spectrometry (GC-MS). The 11 strains tested were all able to increase their numbers in CBM, even though the development of the starter LAB was quite limited. GC-MS analysis registered 43 compounds including seven chemical classes. A lower diversity of VOCs was registered for the unfermented curd based medium (CuBM) analyzed for comparison. The class of ketones represented a consistent percentage of the VOCs for almost all LAB, followed by alcohols and esters. The volatile profile of Pediococcus acidilactici and Lactobacillus delbrueckii was mainly characterized by 2-butanol, butanoic acid and hexanoic acid and their esters, while that of Lactobacillus casei and Lactobacillus rhamnosus was characterized by 2,3-butanedione and 2-butanone, 3-hydroxy. In order to correlate the VOCs produced by Caciocavallo Palermitano cheeses with those generated by individual LAB, the 4-month ripened cheeses resulting from the dairy process monitored during the isolation of LAB were also analyzed for the volatile chemical fraction and the compounds in common were subjected to a multivariate statistical analysis. The canonical analysis indicated that the VOCs of the ripened cheeses were mainly influenced by E. gallinarum, L. paracasei, L. delbrueckii, L. rhamnosus and L. casei and that 1-hexanol, o-xylene and m-xylene were the cheese VOCs highly correlated with LAB.

Predicting Air Quality at First Ingress into Vehicles Visiting the International Space Station.

INTRODUCTION: NASA regularly performs ground-based offgas tests (OGTs), which allow prediction of accumulated volatile pollutant concentrations at first entry on orbit, on whole modules and vehicles scheduled to connect to the International Space Station (ISS). These data guide crew safety operations and allow for estimation of ISS air revitalization systems impact from additional pollutant load. Since volatiles released from vehicle, module, and payload materials can affect crew health and performance, prediction of first ingress air quality is important. METHODS: To assess whether toxicological risk is typically over or underpredicted, OGT and first ingress samples from 10 vehicles and modules were compared. Samples were analyzed by gas chromatography and gas chromatography-mass spectrometry. The rate of pollutant accumulation was extrapolated over time. Ratios of analytical values and Spacecraft Maximum Allowable Concentrations were used to predict total toxicity values (T-values) at first entry. Results were also compared by compound. RESULTS: Frequently overpredicted was 2-butanone (9/10), whereas propanal (6/10) and ethanol (8/10) were typically underpredicted, but T-values were not substantially affected. Ingress sample collection delay (estimated by octafluoropropane introduced from ISS atmosphere) and T-value prediction accuracy correlated well (R2 = 0.9008), highlighting the importance of immediate air sample collection and accounting for ISS air dilution. DISCUSSION: Importantly, T-value predictions were conservative 70% of the time. Results also suggest that T-values can be normalized to octafluoropropane levels to adjust for ISS air dilution at first ingress. Finally, OGT and ingress sampling has allowed small leaks in vehicle fluid systems to be recognized and addressed.Romoser AA, Scully RR, Limero TF, De Vera V, Cheng PF, Hand JJ, James JT, Ryder VE. Predicting air quality at first ingress into vehicles visiting the International Space Station. Aerosp Med Hum Perform. 2017; 88(2):104-113.

A new desorption method for removing organic solvents from activated carbon using surfactant.

OBJECTIVES: A new desorption method was investigated, which does not require toxic organic solvents. Efficient desorption of organic solvents from activated carbon was achieved with an ananionic surfactant solution, focusing on its washing and emulsion action. METHODS: Isopropyl alcohol (IPA) and methyl ethyl ketone (MEK) were used as test solvents. Lauryl benzene sulfonic acid sodium salt (LAS) and sodium dodecyl sulfate (SDS) were used as the surfactant. Activated carbon (100 mg) was placed in a vial and a predetermined amount of organic solvent was added. After leaving for about 24 h, a predetermined amount of the surfactant solution was added. After leaving for another 72 h, the vial was heated in an incubator at 60°C for a predetermined time. The organic vapor concentration was then determined with a frame ionization detector (FID)-gas chromatograph and the desorption efficiency was calculated. RESULTS: A high desorption efficiency was obtained with a 10% surfactant solution (LAS 8%, SDS 2%), 5 ml desorption solution, 60°C desorption temperature, and desorption time of over 24 h, and the desorption efficiency was 72% for IPA and 9% for MEK. Under identical conditions, the desorption efficiencies for another five organic solvents were investigated, which were 36%, 3%, 32%, 2%, and 3% for acetone, ethyl acetate, dichloromethane, toluene, and m-xylene, respectively. CONCLUSIONS: A combination of two anionic surfactants exhibited a relatively high desorption efficiency for IPA. For toluene, the desorption efficiency was low due to poor detergency and emulsification power.

Detection of volatile metabolites of moulds isolated from a contaminated library.

The principal fungal species isolated from a contaminated library environment were tested for their microbial volatile organic compound (MVOC) production ability. Aspergillus creber, A. penicillioides, Cladosporium cladosporioides, Eurotium chevalieri, E. halophilicum, Penicillium brevicompactum and P. chrysogenum were cultivated on suitable culture media inside sample bottles specifically designed and created for direct MVOC injection to a GC-MS instrument. The fungal emissions were monitored over several weeks to detect changes with the aging of the colonies, monitored also by respirometric tests. A total of 55 different MVOCs were detected and isopropyl alcohol, 3-methyl-1-butanol and 2-butanone were the principal compounds in common between the selected fungal species. Moreover, 2,4-dimethylheptane, 1,4-pentadiene, styrene, ethanol, 2-methyl-1-butanol, acetone, furan and 2-methylfuran were the most detected compounds. For the first time, the MVOC production for particular fungal species was detected. The species A. creber, which belongs to the recently revised group Aspergillus section Versicolores, was characterized by the production of ethanol, furan and 1,4-pentadiene. For the xerophilic fungus E. halophilicum, specific production of acetone, 2-butanone and 1,4-pentadiene was detected, supported also by respirometric data. The results demonstrated the potential use of this method for the detection of fungal contamination phenomena inside Cultural Heritage's preservation environments.

Mass Spectrometric Approaches to the Identification of Potential Ingredients in Cigarette Smoke Causing Cytotoxicity.

Cigarette smoke contains many harmful chemicals that contribute to the pathogenesis of smoking-related diseases such as chronic obstructive pulmonary disease, cancer, and cardiovascular disease. Many studies have been done to identify cytotoxic chemicals in cigarette smoke and elucidate the onset of the above-mentioned diseases caused by smoking. However, definitive mechanisms for cigarette smoke toxicity remain unknown. As candidates for cytotoxic chemicals, we have recently found methyl vinyl ketone (MVK) and acetic anhydride in nicotine/tar-free cigarette smoke extract (CSE) using L-tyrosine (Tyr), an amino acid with highly reactive hydroxyl group. The presence of MVK and acetic anhydride in CSE was confirmed by gas chromatography-mass spectrometry (GC/MS). We also found new reaction products formed in B16-BL6 mouse melanoma (B16-BL6) cells treated with CSE using LC/MS. These were identified as glutathione (GSH) conjugates of α,ß-unsaturated carbonyl compounds, MVK, crotonaldehyde (CA), and acrolein (ACR), by the mass value and product ion spectra of these new products. ACR and MVK are type-2 alkenes, which are well known as electron acceptors and form Michael-type adducts to nucleophilic side chain of amino acids on peptides. These α,ß-unsaturated carbonyl compounds may have a key role in CSE-induced cell death.

Normalization of Exhaled Carbonyl Compounds After Lung Cancer Resection.

BACKGROUND: Quantitative analysis of specific exhaled carbonyl compounds (ECCs) has shown promise for the detection of lung cancer. The purpose of this study is to demonstrate the normalization of ECCs in patients after lung cancer resection. METHODS: Patients from a single center gave consent and were enrolled in the study from 2011 onward. Breath analysis was performed on lung cancer patients before and after surgical resection of their tumors. One liter of breath from a single exhalation was collected and evacuated over a silicon microchip. Carbonyls were captured by oximation reaction and analyzed by mass spectrometry. Concentrations of four cancer-specific ECCs were measured and compared by using the Wilcoxon test. A given cancer marker was considered elevated at 1.5 or more standard deviations greater than the mean of the control population. RESULTS: There were 34 cancer patients with paired samples and 187 control subjects. The median values after resection were significantly lower for all four ECCs and were equivalent to the control patient values for three of the four ECCs. CONCLUSIONS: The analysis of ECCs demonstrates reduction to the level of control patients after surgical resection for lung cancer. This technology has the potential to be a useful tool to detect disease after lung cancer resection. Continued follow-up will determine whether subsequent elevation of ECCs is indicative of recurrent disease.

Isoprene photochemistry over the Amazon rainforest.

Isoprene photooxidation is a major driver of atmospheric chemistry over forested regions. Isoprene reacts with hydroxyl radicals (OH) and molecular oxygen to produce isoprene peroxy radicals (ISOPOO). These radicals can react with hydroperoxyl radicals (HO2) to dominantly produce hydroxyhydroperoxides (ISOPOOH). They can also react with nitric oxide (NO) to largely produce methyl vinyl ketone (MVK) and methacrolein (MACR). Unimolecular isomerization and bimolecular reactions with organic peroxy radicals are also possible. There is uncertainty about the relative importance of each of these pathways in the atmosphere and possible changes because of anthropogenic pollution. Herein, measurements of ISOPOOH and MVK + MACR concentrations are reported over the central region of the Amazon basin during the wet season. The research site, downwind of an urban region, intercepted both background and polluted air masses during the GoAmazon2014/5 Experiment. Under background conditions, the confidence interval for the ratio of the ISOPOOH concentration to that of MVK + MACR spanned 0.4-0.6. This result implies a ratio of the reaction rate of ISOPOO with HO2 to that with NO of approximately unity. A value of unity is significantly smaller than simulated at present by global chemical transport models for this important, nominally low-NO, forested region of Earth. Under polluted conditions, when the concentrations of reactive nitrogen compounds were high (>1 ppb), ISOPOOH concentrations dropped below the instrumental detection limit (<60 ppt). This abrupt shift in isoprene photooxidation, sparked by human activities, speaks to ongoing and possible future changes in the photochemistry active over the Amazon rainforest.

Azadirachta indica plant-assisted green synthesis of Mn3O4 nanoparticles: Excellent thermal catalytic performance and chemical sensing behavior.

The leaf extract of Azadirachta indica (Neem) plant was utilized as reducing agent for the green synthesis of Mn3O4 nanoparticles (NPs). The crystalline analysis demonstrated the typical tetragonal hausmannite crystal structure of Mn3O4, which confirmed the formation of Mn3O4 NPs without the existence of other oxides. Green synthesized Mn3O4 NPs were applied for the catalytic thermal decomposition of ammonium perchlorate (AP) and as working electrode for fabricating the chemical sensor. The excellent catalytic effect for the thermal decomposition of AP was observed by decreasing the decomposition temperature by 175 °C with single decomposing step. The fabricated chemical sensor based on green synthesized Mn3O4 NPs displayed high, reliable and reproducible sensitivity of ∼569.2 µA mM(-1) cm(-2) with reasonable limit of detection (LOD) of ∼22.1 µM and the response time of ∼10 s toward the detection of 2-butanone chemical. A relatively good linearity in the ranging from ∼20 to 160 µM was detected for Mn3O4 NPs electrode based 2-butanone chemical sensor.

Real-time ultrasensitive VUV-PIMS detection of representative endogenous volatile markers in cancers.

BACKGROUND: Identifying endogenous volatile organic compounds (VOCs) as markers for different cancers currently requires time-consuming procedures and specialized operators. OBJECTIVE: The objective of this study was to develop a rapid and simple method for measuring VOCs at trace levels. METHODS: A simple vacuum ultraviolet photoionization mass spectrometer (VUV-PIMS) was used to detect trace levels of dimethyl trisulfide (DMTS), dimethyl sulfide (DMS), and 2-butanone, which correspond to volatile biomarker candidates present in the exhaled breath of patients with breast, liver, and lung cancers, respectively. The practicality of measuring endogenous VOCs using VUV-PIMS was confirmed by detecting them in cultured cell lines. RESULTS: The abovementioned VOCs were detected with high sensitivity by VUV-PIMS. The limits of detection (LODs) for DMTS, DMS, and 2-butanone were 3.1, 3.9, and 23.2 pptv, respectively, under ambient conditions, which surpass the sensitivity of nearly all other MS-based techniques. Moreover, relatively high concentrations of 2-butanone and DMS were observed in VOCs emitted from the A549 lung cancer cell line and the HepG2 liver cancer cell line, respectively. CONCLUSIONS: Our results show that VUV-PIMS may serve as a reliable method for real-time measurement of endogenous volatile cancer biomarkers.

Determination of 2-alkylcyclobutanones by combining precolumn derivatization with 1-naphthalenyl hydrazine and ultra-performance liquid chromatography with fluorescence detection.

2-Alkylcyclobutanones (2-ACBs) are uniquely formed when triglycerides-containing food products are exposed to ionizing radiation. Thus, 2-ACBs have been used as marker molecules to identify irradiated food. Most methods to determine 2-ACBs involve mass spectrometric detection after chromatographic separation. The spectrofluorometer is rarely used to determine 2-ACBs because these molecules do not fluoresce. In this study, we developed an ultra-performance liquid chromatography (UPLC) method to determine 2-ACBs. 2-ACBs were converted into fluorophores after reacting with 1-naphthalenyl hydrazine to facilitate their sensitive and selective detection using a fluorescence detector (FLD). Analysis of 2-ACBs using our developed UPLC-FLD method allows sensitive determination of 2-ACBs at a detection limit of 2 ng 2-ACBs per g of fat (30 pg/injection), which is significantly lower than that of existing analytical methods. After validation for trueness and precision, the method was applied to γ-irradiated chicken samples to determine their 2-ACB content. Comparative studies employing liquid chromatography-tandem mass spectrometric method revealed no systematic difference between the two methods, thereby demonstrating that the proposed UPLC-FLD method can be suitably used to determine 2-ACBs in irradiated foodstuffs. Graphical Abstract Determination of radiation-induced food-borne 2-dodecylcyclobutanone and 2-tetradecylcyclobutanone by combining 1-naphthalenyl hydrazine derivatization and ultra-performance liquid chromatography with fluorescence detection.

Experimental and theoretical charge-density analysis of 1,4-bis(5-hexyl-2-thienyl)butane-1,4-dione: applications of a virtual-atom model.

The experimental and theoretical charge densities of 1,4-bis(5-hexyl-2-thienyl)butane-1,4-dione, a precursor in the synthesis of thiophene-based semiconductors and organic solar cells, are presented. A dummy bond charges spherical atom model is applied besides the multipolar atom model. The results show that the dummy bond charges model is accurate enough to calculate electrostatic-derived properties which are comparable with those obtained by the multipolar atom model. The refinement statistics and the residual electron density values are found to be intermediate between the independent atom and the multipolar formalisms.

Kinetics studies on the removal of Methyl ethyl ketone using cornstack based biofilter.

The performance of cornstack based biofilter inoculated with a mixed culture was evaluated for gas phase MEK removal under various operating conditions. Experiments were carried out at different flow rates (0.03-0.12m3h-1) and various initial concentrations (0.2-1.2g-3). A maximum elimination capacity (EC) of 35g-3h-1 was achieved at an inlet loading rate of 60g-3h-1 with a removal efficiency of 95%. High elimination capacity reached with this system could have been due to the dominant presence of filamentous fungi among others. The experimental results were compared with the values obtained from the Ottengraf-van den Oever model for zero-order diffusion-controlled region. The critical inlet concentration, critical inlet load and biofilm thickness were estimated using the model predictions.