Multi‐Channel Surface Acoustic Wave Sensors Based on Principal Component Analysis (PCA) and Linear Discriminate Analysis (LDA) for Organic Vapors

A multi‐channel surface acoustic wave (SAW) detection system which is employed to detect various organic molecules in a static system was prepared using 315 MHz one‐port quartz resonators and a home‐made computer interface for signal acquisition and data process. The oscillating frequency of the quartz crystal decreases on adsorption of organic molecules on the coating materials. The principal component analysis (PCA) method with SAS software was applied to select the appropriate coating materials onto the SAW crystals for organic vapors, e.g. hexane, 1‐hexene, 1‐hexyne, 1‐propanol, propionaldehyde, propionic acid, and 1‐propylamine. A dataset for a multi‐channel sensor with 19 SAW crystals for 7 analyses was collected after comparing the correlation between the 19 coating materials and the first six principal component (PC) factor. Furthermore, linear discriminate analysis (LDA) with SPSS software and a profile discrimination map were also applied and discussed for the discrimination of these organic vapors. These organic molecules could be clearly distinguished by the six‐channel SAW static sensor. The effect of concentration for various organic vapors was investigated and discussed.     

Multi‐Channel Piezoelectric Quartz Crystal Sensor with Principal Component Analysis and Back‐Propagation Neural Network for Organic Pollutants from Petrochemical Plants

A multi‐channel piezoelectric quartz crystal gas sensor comprising arrays coated with various organic materials and a home‐made computer interface for data processing were prepared and employed to detect six kinds of common organic pollutants from petrochemical plants including benzene, styrene, chloroform, octane, hexene and hexyne. The principal component analysis (PCA) method was employed to select six kinds of appropriate coating materials for these organic pollutants from 22 adsorbents onto piezoelectric crystals. After performing a PCA assay, six representative coating materials, namely Polyisobutylene, Poly(dimethylsiloxane) (SE30), 4‐tert‐Butylcalix[6]arene, Cholesteryl chloroformate, C60‐Polyphenyl acetylene (C60‐PPA) and Ag(I)/cryptand‐2,2/Ethylene diamine/NH₃/Polyvinyl chloride were selected. Moreover, effects of coating load of adsorbents and concentration of pollutants were also investigated. Three kinds of recognition techniques including 2D PCA score map, radar plot and back‐propagation neural network (BPN) were employed for qualitative analysis of these organic pollutants, and a quantitative analysis method could be established by creating calibration curves for each organic pollutant. This homemade multi‐channel piezoelectric quartz crystal gas sensor showed a good detection limit of 0.068‐1.127 mg/L for these organic pollutants. The multi‐channel piezoelectric gas sensor exhibited good reproducibility with a relative standard deviation (RSD) of 1.1‐9.6%. Furthermore, this multi‐channel piezoelectric crystal detection system with BPN recognition technique was also utilized to successfully distinguish and identify each component of the mixture of organic gas samples. Multivariate linear regression (MLR) analysis was employed to quantitatively compute the concentration of species in the organic mixtures.     

Bi‐channel Surface Acoustic Wave Gas Sensor for Carbon Disulfide and Methanol Vapors in Polymer Plants

A C₆₀‐polyphenylacetylene (C₆₀‐PPA) and polyvinylpyrrolidone (PVP) coated two‐channel surface acoustic wave (SAW) crystal gas sensor with a homemade computer interface for data acquisition and data processing was developed and employed to detect carbon disulfide (CS₂) and methanol (CH₃OH) vapors in polymer plants. The frequency of surface acoustic wave oscillator decreases due to the adsorption of gas molecules on the coated materials of the SAW sensor. Six coating materials (C₆₀‐PPA, nafion, PPA, crytand [2,2], polyethene glycol and PVP) were used to adsorb and detect carbon disulfide and methanol gases. Adsorption of all the six coating materials to CS₂ and CH₃OH was found to be physical adsorption. The C₆₀‐PPA coated SAW detector exhibited more sensitive to CS₂ than the other coating materials. In contrast, the PVP coated SAW detector was more sensitive to CH₃OH than the other coating materials. With the two‐channel SAW sensor, the C₆₀‐PPA coated SAW showed a good detection limit of 0.4 ppm and good reproducibility with RSD of 3.37 % (n=10) for CS₂. Similarly, the PVP coated SAW also showed a good detection limit of 0.05 ppm and good reproducibility, with RSD of 0.86 % (n=10) for CH₃OH. The interference effect of other organic molecules on the SAW detection system was negligible, except for the irreversible adsorption of C₆₀‐PPA to propylamine. The frequency signals from the two‐channel SAW sensor array C₆₀‐PPA and PVP coatings were processed by a back‐propagation artificial neural network (BPN) and multiple regression analysis (MRA). Thus a two‐channel SAW sensor array with BPN and MRA has been successfully applied for the qualitative and quantitative analyses of CS₂ and CH₃OH in mixtures.     

Ligand Displacement Reaction Paths in a Diiron Hydrogenase Active Site Model Complex

The mechanism and energetics of CO, 1‐hexene, and 1‐hexyne substitution from the complexes (SBenz)₂[Fe₂(CO)₆] (SBenz=SCH₂Ph) ( 1 ‐CO), (SBenz)₂[Fe₂(CO)₅(η²‐1‐hexene)] ( 1 ‐(η²‐1‐hexene)), and (SBenz)₂[Fe₂(CO)₅(η²‐1‐hexyne)] ( 1 ‐(η²‐1‐hexyne)) were studied by using time‐resolved infrared spectroscopy. Exchange of both CO and 1‐hexyne by P(OEt)₃ and pyridine, respectively, proceeds by a bimolecular mechanism. As similar activation enthalpies are obtained for both reactions, the rate‐determining step in both cases is assumed to be the rotation of the Fe(CO)₂L (L=CO or 1‐hexyne) unit to accommodate the incoming ligand. The kinetic profile for the displacement of 1‐hexene is quite different than that for the alkyne and, in this case, both reaction channels, that is, dissociative (S_N1) and associative (S_N2), were found to be competitive. Because DFT calculations predict similar binding enthalpies of alkene and alkyne to the iron center, the results indicate that the bimolecular pathway in the case of the alkyne is lower in free energy than that of the alkene. In complexes of this type, subtle changes in the departing ligand characteristics and the nature of the mercapto bridge can influence the exchange mechanism, such that more than one reaction pathway is available for ligand substitution. The difference between this and the analogous study of (μ‐pdt)[Fe(CO)₃]₂ (pdt=S(CH₂)₃S) underscores the unique characteristics of a three‐atom S?S linker in the active site of diiron hydrogenases.     

Piezoelectric Crystal Membrane Chemical Sensors Based on Fullerene and Macrocyclic Polyethers

Various reusable and sensitive piezoelectric (PZ) quartz crystal membrane sensors with home‐made computer interfaces for signal acquisition and data processing were developed to detect organic/inorganic vapors and organic/inorganic/biologic species in solutions, respectively. Fullerene(C60), fullerene derivatives and artificial macrocyclic polyethers, e.g., crown ethers and cryptands, were synthesized and applied as coating materials on quartz crystals of the PZ crystal sensors. The oscillating frequency of the quartz crystal decreased due to the adsorption of organic or inorganic species onto coating material molecules on the crystal surface. The crown ether‐coated PZ crystal gas detector exhibited high sensitivity with a frequency shift range of 10–340 Hz/(mg/L) for polar organic gases, a short response time (< 2.0 min.), good selectivity, and good reproducibility. The Ag(I)/crptand22 and Ru(III) / crptand22 coated PZ gas detectors were also prepared for nonpolar organic vapors, e.g., alkynes and alkenes. The frequency shifts of the nonpolar PZ sensors were in the order: alkynes > alkenes > alkanes. A Ti(IV)/Cryptand22‐coated PZ crystal sensor was also developed to detect the inorganic air pollutants, e.g., CO and NO₂. A piezoelectric gas sensor for both polar/nonpolar organic vapors based on C60‐cryptand22 was also prepared. The cryptand22‐coated PZ gas sensor was also employed as a GC detector for organic molecules. The cryptand22‐coated piezoelectric GC detectors compared well with the commercial thermal conductivity detector (TCD). The interaction between fullerene C60 and organic molecules was studied with a fullerene coated PZ gas detector. A multi‐channel PZ organic gas detector with PCA(Principal Component Analysis) and BPN (Back Propagation Neural) analysis methods was developed. Various liquid piezoelectric crystal sensors based on long‐chain macrocyclic polyethers, e.g., C₁₀H₂₁‐dibenzo‐16‐crown‐5, C₁₈H₃₇‐benzo‐15‐crown‐5, (C₁₇CO)₂‐cyptand22 and fullerene derivatives, e.g., C60‐NH‐cryptand22 and dibenzo‐16‐crown‐5‐C60, were also developed as HPLC detectors for metal ions, anions, and various organic compounds in solutions. The sensitive and highly selective PZ bio‐sensors based on enzymes, polyvinylaldehyde, polycinnaldehyde‐C60 and C60‐cryptand22 were developed to detect various biologic species, e.g., proteins, glucose, and urea. A quite sensitive EQCM (Electrochemical Quartz Crystal Micro‐balance) detection system was also developed for detection of trace heavy metal ions.     

Fullerene‐Crown Ether Coated Piezoelectric Crystal Liquid Chromatographic Detector for Metal Ions and Polar/Nonpolar Organic Molecules

Fullerene(C60)‐dibenzo‐16‐crown‐5‐oxyacetic acid (DBI6C5‐OCH₂‐COOC₆₀) was prepared and applied as the coating material on piezoelectric quartz crystals for detection of various metal ions and polar/nonpolar organic molecules. The C60‐crown ether‐coated piezoelectric crystal sensor with a home‐made computer interface for signal acquisition and data processing was applied as an ion chromatographic (IC) detector for various metal ions, e.g., alkali metal, alkaline earth metal and transition‐metal ions. The piezoelectric detector exhibited quite good sensitivity of 10⁴ ～ 10⁶ Hz/M and good detection limit of 10^?3 ～ 10^?4 M for these metal ions. The C60‐crown ether piezoelectric detector compared well with the commercial conductivity detector conventionally used for metal ions. The ionic size and ionic charge seemed to have significant effect on the frequency response of the piezoelectric detector. The C60‐crown ether coated piezoelectric crystal sensor was also employed as a high performance liquid chromatographic (HPLC) detector for various polar organic molecules with frequency responses in the order: amines > carboxylic acids > alcohols > ketones. Furthermore, nonpolar organic molecules, e.g., n‐hexane, 1‐hexene and 1‐hexyne, were also detected with this piezoelectric crystal detector. The frequency responses of the piezoelectric crystal detector for these nonpolar organic molecules were in the following order: alkynes > alkenes > alkanes. The effects of solvents and flow rate on the frequency responses of the piezoelectric crystal detector were investigated. The C60‐crown ether coated piezoelectric crystal detector also showed short response time (< 1 min.) and good reproducibility.     

Preparation and Application of Fullerene C60‐Polymers in Piezoelectric Quartz Crystal Sensors for Hemoglobin and Olefins

The C60—polycinnamaldehyde (C₆₀—PCA) and C60—polyphenylacetylene (C60—PPA) polymers were synthesized by the Friedel—Craft reaction and applied as piezoelectric (PZ) quartz crystal coating materials. A C60—polycinnamaldehyde (PCA) coated piezoelectric quartz crystal liquid sensor with a homemade computer interface was prepared and applied as a PZ hemoglobin sensor. The adsorption of hemoglobin onto the C60—PCA coated crystal resulted in a decreased oscillating frequency. The variations in crystal frequency were converted to voltage with a frequency to voltage converter, followed by amplification with OPA and data acquisition with an analog to digital converter. The PZ hemoglobin sensor exhibited good sensitivity of 6530 Hz/(mg/mL) with a detection limit at the ppm level for hemoglobin. Further, a C60—polyphenylacetylene (C60—PPA) coated piezoelectric quartz crystal gas sensor with an Intell‐8255 data processing system for various olefin vapors was also made. The aromatic hydrocarbons such as toluene seem to have greater adsorption onto C60—PPA membrane than alkynes, alkenes, and alkanes. The adsorption of polycyclic aromatic hydrocarbons (PAHs) onto the C60—PPA membrane was also examined. The C₆₀—PPA coated PZ crystal gas sensor showed much better sensitivity for PAHs than for other olefins such as toluene, 1‐hexyne and 1‐hexene, and a much larger frequency shift for naphthalene than other PAHs was also found.     

A Quantitative Structure–Activity Relationship Study of Calpeptin (Calpain Inhibitor) as an Anticancer Agent

Calpeptin analogs show anticancer properties with inhibition of calpain. In this work, we applied a quantitative structure–activity relationship (QSAR) model on 34 calpeptin derivatives to select the most appropriate compound. QSAR was employed to generate the models and predict the more significant compounds through a series of calpeptin derivatives. The HyperChem, Gaussian 09, and Dragon software programs were used for geometry optimization of the molecules. The 2D and 3D molecular structures were drawn by ChemDraw (Ultra 16.0) and Chem3D (Pro16.0) software. The Unscrambler program was used for the analysis of data. Multiple linear regression (MLR‐MLR), partial least‐squares (MLR‐PLS1), principal component regression (MLR‐PCR), a genetic algorithm‐artificial neural networks (GA‐ANN), and a novel similarity analysis‐artificial neural network (SA‐ANN) method were used to create QSAR models. Among the three MLR models, MLR‐MLR provided better statistical parameters. The R² and RMSE of the prediction were estimated as 0.8248 and 0.26, respectively. Nevertheless, the constructed model using GA‐ANN revealed the best statistical parameters among the studied methods (R² test = 0.9643, RMSE test = 0.0155, R² train = 0.9644, RMSE train = 0.0139). The GA‐ANN model is found to be the most favorable method among the statistical methods and can be employed for designing new calpeptin analogs as potent calpain inhibitors in cancer treatment.     

Quartz crystal microbalance sensor array for the detection of volatile organic compounds

A sensor array system consisting of five quartz crystal microbalance (QCM) sensors (four for measuring and one for reference) and an artificial neural network (ANN) method is presented for on-line detection of volatile organic compounds. Three ionic liquids, 1-butyl-3-methylimidazolium chloride (C₄mimCl), 1-butyl-3-methylimidazolium hexafluorophosphate (C₄mimPF₆), 1-dedocyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (C₄mimNTf₂), and silicone oil II, which is widely used as gas chromatographic stationary phase, have been selected as sensitive coatings on the quartz surface allowing the sensor array effective to identify chemical vapors, such as toluene, ethanol, acetone and dichloromethane. The success rate for the qualitative recognition reached 100%. Quantitative analysis has also been investigated, within the concentration range of 0.6-6.1 mg/L for toluene, 0.9-7.5 mg/L for ethanol, 2.8-117 mg/L for dichloromethane, and 0.7-38 mg/L for acetone, with a prediction error lower than 8%.     

Quantitative Structure Property Relations （QSPR） for Predicting Molar Diamagnetic Susceptibilities,xm, of Inorganic Compounds

For predicting the molar diamagnetic susceptibilities of inorganic compounds, a novel connectivity index ^mG based on adjacency matrix of molecular graphs and ionic parameter gi was proposed. The gi is defined as gi=（ni^0.5-0.91）^4·xi^0.5｜Zi^0.5, where Zi, ni, xi are the valence, the outer electronic shell primary quantum number, and the electronegativity of atom i respectively. The good QSPR models for the molar diamagnetic susceptibilities can be constructed from ^0G and ^1G by using multivariate linear regression （MLR） method and artificial neural network （NN） method. The correlation coefficient r, standard error, and average absolute deviation of the MLR model and NN model are 0.9868, 5.47 cgs, 4.33 cgs, 0.9885, 5.09 cgs and 4.06 cgs, respectively, for the 144 inorganic compounds. The cross-validation by using the leave-one-out method demonstrates that the MLR model is highly reliable from the point of view of statistics. The average absolute deviations of predicted values of the molar diamagnetic susceptibility of other 62 inorganic compounds （test set） are 4.72 cgs and 4.06 cgs for the MLR model and NN model. The results show that the current method is more effective than literature methods for estimating the molar diamagnetic susceptibility of an inorganic compound. Both MLR and NN methods can provide acceptable models for the prediction of the molar diamagnetic susceptibilities. The NN model for the molar diamagnetic susceptibilities appears more reliable than the MLR model.     

Application of an artificial neural network (ANN) and piezoelectric chemical sensor array for identification of volatile organic compounds

A piezoelectric chemical sensor array was developed using four quartz crystals. Gas chromatographic stationary phases were used as sensing materials and the array was connected to an artificial neural network (ANN). The application of the ANN method proved to be particularly advantageous if the measured property (mass, concentration, etc.) should not be connected exactly to the signal of the transducers of the piezoelectric sensor. The optimum structure of neural network was determined by a trial and error method. Different structures were tried with several neurons in the hidden layer and the total error was calculated. The optimum values of primary weight factors, learning rate (η=0.15), momentum term (μ=0.9), and the sigmoid parameter (β=1) were determined. Finally, three hidden neurons and 900 training cycles were applied. After the teaching process the network was used for identification of taught analytes (acetone, benzene, chloroform, pentane). Mixtures of organic compounds were also analysed and the ANN method proved to be a reliable way of differentiating the sensing materials and identifying the volatile compounds.     

吡啶和喹啉类化合物的碳-13核磁共振波谱模拟

运用多元回归分析和人工神经网法对１８个吡啶和喹啉类化合物的１１８个化学位移进行计算机模拟,并应用碳原子的空间和电子结构特征来表征其所处的化学环境,从而获得了比较好的相关模型。波谱模拟技术对辅助有机化合物结构解析和化学位移的确认是十分有用的工具。     

Characterization of N-cyclohexylmethacrylamide LB thin films for room temperature vapor sensor application

This study reports the synthesis, characterization and gas sensing applications of N-cyclohexylmethacrylamide (NCMA) monomer material using FT-IR, ¹H and ¹³C NMR, UV-visible spectroscopy, Quartz Crystal Microbalance (QCM) and Langmuir-Blodgett (LB) thin film deposition techniques. The thin film deposition conditions of NCMA monomer material, which are prepared by LB film technique, are characterized by UV-visible spectroscopy and QCM system. The sensing behaviors of the LB film with respect to volatile organic compounds (VOCs) at room temperature are investigated. Surface pressure change as a function of surface area of NCMA molecule at the water surface shows a well-organized and stable monolayer at 18 mN m^?1 surface pressure value for LB film deposition. Transfer ratio values are found to be ≥ 0.94 for quartz glass and ≥ 0.93 for quartz crystal substrate. The typical frequency shift per layer is obtained 20.10 Hz/layer and the deposited mass onto a quartz crystal is calculated as 824.62 ng/layer. The sensing responses of the LB films against chloroform, dichloromethane, acetone, toluene, benzene and ethanol are measured by QCM system. The sensitivities of the NCMA LB film sensor are determined between 0.085 and 0.029 Hz ppm^?1. Sensitivities with detection limits are between 35.29 and 100.33 ppm against organic vapors. These results can be concluded that the monomer LB film sample is found to be significantly more sensitive to chloroform and dichloromethane vapors than others organic vapors used in this work. This material may find potential applications in the development of room temperature organic vapor sensing.