An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Microbial spoilage in milk is a crucial concern for healthy consumption. This study aims to apply the electronic nose system (e-nose) comprising an array of different gas sensors as an initial tool for monitoring of food spoilage for maintaining food safety and human health. In this system, nanocomposite gas sensors based on different polymers and functionalized single-walled carbon nanotubes (f-SWCNTs) are employed. By exposure of these gas sensors to the milk's headspace, the gas sensors show responsive signals toward volatile organic compounds (VOCs) contained in the milk. The pasteurized milks under two storage conditions, at 4°C (±1°C) and 25°C (± 1°C), were used to observe development of spoilage for 9 days. To consider the capability of electronic nose for freshness and milk spoilage detection, the odor pattern was analyzed using principal component analysis (PCA). The ability of each sensor to detect the intensity of the odor level was observed by tracking the change of sensing responses. The discrimination results have shown that the odor levels of samples stored at 4°C are not different from the first day to the ninth day, whereas the odor levels of samples stored at room temperature condition are increasing upon the storage time. The exploration in this work can thus provide information about the application of electronic nose with nanocomposite gas sensor array as a beneficial tool for monitoring the food spoilage and quality control.
The coronavirus COVID-19 pandemic have reached almost every country in the world and caused a global health crisis. It is necessary to detect COVID-19 with fast and accurate diagnosis method in order to prevent the rapid spread of Covid-19. This paper presents a preliminary study of using electronic nose (e-nose) technology for detection of COVD-19 infection. In this experiment, the human exhaled breaths of healthy volunteers, asymptomatic and symptomatic COVID-19 patients were collected with commercial face masks for 5 minutes followed by the measurement with an e-nose machine in a closed system. The COVID-19 positivity was confirmed by RT-PCR method. According to the experiment, the odor intensity of human exhaled breath can be described with the total sensing response value. The exhaled breath of COVID-19 infected patients show higher odor intensity than the healthy volunteers (control). The Principal Component Analysis (PCA) shows the classification of three data groups; healthy volunteers, COVID-19 infected patients and unclassified people. For the unclassified cases, the medical record has shown that these people have been subjected either to some respiratory diseases or just recovered from COVID-19 infection. From these preliminary results, e-nose technology and its measurement proto-cols can be considered as a viable tool for COVID-19 rapid detection.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
This paper reveals the development and design of an electronic nose prototype for non-invasive diabetes detection based on measurement of the exhaled breath. This system consists of eight metal oxide gas sensors covering the sensing range for the volatile organic compounds (VOCs) existed in human's exhaled breath. These platforms can be integrated the facemask connected to electronic nose device which used to realtime monitoring. This prototype offers platforms that can be applied to investigate the monitoring exhaled breath human, which have potential to monitoring human health. The experiment obtained the optimizing the condition to detect the exhaled breath. Preliminary results with prototype electronic nose to detect the exhaled breath. It shows an excellent performance to detect an exhaled breath sample. Moreover, it has successfully to discriminate the exhaled breath pattern of diabetes and healthy controls. Soon, this approach may become particularly useful in health application to serve as a noninvasive device for screening patients with diabetes.
Food poisoning is a serious problem that affects thousands of people every year. Contaminated food is usually detectable by odor. The stranger odors of food poisoning are often caused by microorganism that release some gases via its metabolism. Our interest is the improvement of polyaniline and silver nanoparticles composites to achieve developing the off-flavor food gas sensor. PANI and silver nanoparticles (AgNPs)-PANI nanocomposite, including mixing synthesized and core shell synthesized nanocomposite. The AgNPs-PANI nanocomposites successfully synthesized by in-situ chemical polymerization approach. The formation of metallic silver nanoparticles as well as its presence in the nanocomposite were confirmed by UV-Vis spectrometry and SEM analysis. Sensing response of mixing synthesized nanocomposite revealed excellent correlation between sensing response and the various ethanol concentrations at room temperature.
An air stable FeIII complex showing a wide hysteresis near room temperature is described. The origin of the cooperativity is an unprecedented anion conformational change.
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)
'/%3e%3c/defs%3e%3cpath fill='%23012169' d='M0 0h10080v5040H0z'/%3e%3cpath stroke='%23fff' stroke-width='.6' d='m0 0 6 3m0-3L0 3' clip-path='url(%23b)' transform='scale(840)'/%3e%3cpath stroke='%23e4002b' stroke-width='.4' d='m0 0 6 3m0-3L0 3' clip-path='url(%23c)' transform='scale(840)'/%3e%3cpath stroke='%23fff' stroke-width='840' d='M2520 0v2520M0 1260h5040'/%3e%3cpath stroke='%23e4002b' stroke-width='504' d='M2520 0v2520M0 1260h5040'/%3e%3cg fill='%23fff'%3e%3cuse xlink:href='%23d' x='2520' y='3780'/%3e%3cuse xlink:href='%23a' x='7560' y='4200'/%3e%3cuse xlink:href='%23a' x='6300' y='2205'/%3e%3cuse xlink:href='%23a' x='7560' y='840'/%3e%3cuse xlink:href='%23a' x='8680' y='1869'/%3e%3cuse xlink:href='%23e' x='8064' y='2730'/%3e%3c/g%3e%3c/svg%3e)