Narrowband Pure Near-Infrared (NIR) Ir(III) Complexes for Solution-Processed Organic Light-Emitting Diode (OLED) with External Quantum Efficiency Over 16 .

Highly efficient near-infrared (NIR) emitters have significant applications in medical and optoelectronic fields, but the development stays a great challenge due to the energy gap law. Here, we report two NIR phosphorescent Ir(III) complexes which display emission peaks around 730 nm with a narrow full width at half maximum of only 43 nm. Therefore, pure NIR luminescence can be obtained without having a very long emission wavelength, thus alleviating the restriction of the energy gap law, and obtaining impressively high photoluminescence quantum yield up to 0.70. More importantly, the pure NIR organic light-emitting diode (OLED) fabricated by the solution-processed mothed shows outstanding device performance with the highest external quantum efficiency of 16.43 %, which sets a new record for solution-processed NIR-OLEDs based on different emitters. This work sheds light on the development of Ir(III) complexes with narrowband emissions as highly efficient pure NIR-emitters.

Parameter Optimization of Support Vector Machine to Improve the Predictive Performance for Determination of Aflatoxin B1 in Peanuts by Olfactory Visualization Technique.

This study proposes a novel method for detection of aflatoxin B1 (AFB1) in peanuts using olfactory visualization technique. First, 12 kinds of chemical dyes were selected to prepare a colorimetric sensor to assemble olfactory visualization system, which was used to collect the odor characteristic information of peanut samples. Then, genetic algorithm (GA) with back propagation neural network (BPNN) as the regressor was used to optimize the color component of the preprocessed sensor feature image. Support vector regression (SVR) quantitative analysis model was constructed by using the optimized combination of characteristic color components to achieve determination of the AFB1 in peanuts. In this process, the optimization performance of grid search (GS) algorithm and sparrow search algorithm (SSA) on SVR parameter was compared. Compared with GS-SVR model, the model performance of SSA-SVR was better. The results showed that the SSA-SVR model with the combination of seven characteristic color components obtained the best prediction effect. Its correlation coefficients of prediction (RP) reached 0.91. The root mean square error of prediction (RMSEP) was 5.7 µg·kg-1, and ratio performance deviation (RPD) value was 2.4. The results indicate that it is reliable to use the colorimetric sensor array with strong specificity for the determination of the AFB1 in peanuts. In addition, it is necessary to properly optimize the parameters of the prediction model, which can obviously improve the generalization performance of the multivariable model.

High Precisive Prediction of Aflatoxin B1 in Pressing Peanut Oil Using Raman Spectra Combined with Multivariate Data Analysis.

This study proposes a label-free rapid detection method for aflatoxin B1 (AFB1) in pressing peanut oil based on Raman spectroscopy technology combined with appropriate chemometric methods. A DXR laser Raman spectrometer was used to acquire the Raman spectra of the pressed peanut oil samples, and the obtained spectra were preprocessed by wavelet transform (WT) combined with adaptive iteratively reweighted penalized least squares (airPLS). The competitive adaptive reweighted sampling (CARS) method was used to optimize the characteristic bands of the Raman spectra pretreated by the WT + airPLS, and a partial least squares (PLS) detection model for the AFB1 content was established based on the features optimized. The results obtained showed that the root mean square error of prediction (RMSEP) and determination coefficient of prediction (RP2) of the optimal CARS-PLS model in the prediction set were 22.6 µg/kg and 0.99, respectively. The results demonstrate that the Raman spectroscopy combined with appropriate chemometrics can be used to quickly detect the safety of edible oil with high precision. The overall results can provide a technical basis and method reference for the design and development of the portable Raman spectroscopy system for the quality and safety detection of edible oil storage, and also provide a green tool for fast on-site analysis for regulatory authorities of edible oil and production enterprises of edible oil.

Rapid determination of process parameters during simultaneous saccharification and fermentation (SSF) of cassava based on molecular spectral fusion (MSF) features.

Simultaneous saccharification and fermentation (SSF) of cassava is one of the key steps in the production of fuel ethanol. In order to improve the monitoring efficiency of the ethanol production process and the product yield, this study puts forward a new idea for monitoring of the cassava SSF process based on the molecular spectroscopy fusion (MSF) technique. Savisky-Golay (SG) combined with standard normal variable (SNV) was used to preprocess the obtained Raman spectra and near-infrared (NIR) spectra. Competitive adaptive reweighted sampling (CARS) was used to optimize the characteristic wavelengths of the preprocessed Raman spectra and the NIR spectra, and the optimized features were fused in the feature layer. The support vector machine (SVM) model of the process parameters during the cassava SSF based on the MSF features was established. The experimental results showed that compared with the best CARS-SVM model based on the single-molecule spectral features, the performance of the best CARS-SVM model based on fusion features has been significantly improved. For detection of the glucose content, the RMSEP, RP2 and RPD of the best CARS-SVM model were 5.398, 0.957 and 4.922, respectively. For detection of the ethanol content, the RMSEP, RP2 and RPD of the best CARS-SVM model were 4.394, 0.977 and 6.758, respectively. The obtained results reveal that the combination of MSF technique and appropriate chemometric methods can achieve high-precision quantitative detection of the process parameters during the cassava SSF. This study can provide technical basis and experimental reference for the development of portable spectrometer equipment for process monitoring of the cassava SSF.

Co-occurrence of functional modules derived from nicotine-degrading gene clusters confers additive effects in Pseudomonas sp. JY-Q.

Pseudomonas sp. JY-Q was isolated from nicotine-rich environment and could degrade and tolerate high-content nicotine. Its specific genetic architecture comprised duplicated homologous nicotine-degrading clusters for different functional modules on the whole pathway. Its adaptive and genomic properties caused our concern whether the duplicated homologous gene clusters confer additive effects on nicotine degradation and result in strain JY-Q strong capability. After deletion of representative genes from duplicated homologous gene clusters of upstream module Nic1, midstream module Spm, and downstream module Nic2, the nicotine degradation efficiency of the wild type and mutant strains were examined. As the first genes of clusters Nic1-1 and Nic1-2, nicA2 and nox are both involved in nicotine degradation, but nox exhibited more contribution to nicotine metabolism due to the higher transcriptional amount of nox than that of nicA2. Likewise, the sub-clusters spm1 and spm2 showed additive effect on nicotine metabolism. As two hpo-like genes of clusters Nic2-1 and Nic2-2, hpo1, and hpo2 also showed additive effect on the nicotine degrading, but hpo1 provided more contribution than hpo2. The third hpo-like gene in cluster NA (nicotinic acid degrading), nicX is not necessary for 2,5-dihydroxypyridine transformation when hpo1 and hpo2 exist. A variety of transposases and integrases observed around Nic1 and Nic2 cluster genes suggests that the duplicated genes could evolve from horizontal gene transfer (HGT)-related dissemination. This study provide an insight into a novel adaptability mechanism of strains in extreme environment such as high nicotine concentration, and potential novel targets to enhance strain synthesis/degradation ability for future applications.

Size-controllable synthesis of NiCoSe2 microspheres as a counter electrode for dye-sensitized solar cells.

NiCoSe2 microspheres have been successfully synthesized by a facile one-step hydrothermal method at different hydrothermal temperatures. The prepared samples are divided according to their reaction temperatures (90, 120, 150 and 180 °C) and named NiCoSe2-90, NiCoSe2-120, NiCoSe2-150 and NiCoSe2-180, respectively. The diameters of the NiCoSe2 microspheres strongly depend on the different hydrothermal temperatures. When the temperature is increased to 150 °C, the size of the resultant NiCoSe2 microspheres changes from 200 to 800 nm, and the interior of NiCoSe2-150 possesses a flocculent structure. However, NiCoSe2-180 displays a cauliflower-like aggregated structure. The prepared NiCoSe2 alloys are used as high-performance Pt-free counter electrodes (CEs) for dye-sensitized solar cells (DSSCs). Cyclic voltammogram measurement indicates that NiCoSe2-150 CE has larger current density than Pt CE. Electrochemical impedance spectroscopy shows that NiCoSe2-150 CE has a low charge-transfer resistance of 1.8 Ω cm2. Due to their unique morphologies and well-defined interior and exterior structures, DSSCs based on NiCoSe2-120 and NiCoSe2-150 CEs achieve high power conversion efficiencies of 8.48% and 8.76%, respectively, which are higher than that of the solar cell based on Pt CE (8.31%).

Comparative Genomics Reveals Specific Genetic Architectures in Nicotine Metabolism of Pseudomonas sp. JY-Q.

Microbial degradation of nicotine is an important process to control nicotine residues in the aqueous environment. In this study, a high active nicotine degradation strain named Pseudomonas sp. JY-Q was isolated from tobacco waste extract (TWE). This strain could completely degrade 5.0 g l-1 nicotine in 24 h under optimal culture conditions, and it showed some tolerance even at higher concentrations (10.0 g l-1) of nicotine. The complete genome of JY-Q was sequenced to understand the mechanism by which JY-Q could degrade nicotine and tolerate such high nicotine concentrations. Comparative genomic analysis indicated that JY-Q degrades nicotine through putative novel mechanisms. Two candidate gene cluster duplications located separately at distant loci were predicted to be responsible for nicotine degradation. These two nicotine (Nic) degradation-related loci (AA098_21325-AA098_21340, AA098_03885-AA098_03900) exhibit nearly completely consistent gene organization and component synteny. The nicotinic acid (NA) degradation gene cluster (AA098_17770-AA098_17790) and Nic-like clusters were both predicted to be flanked by mobile genetic elements (MGE). Furthermore, we analyzed the regions of genomic plasticity (RGP) in the JY-Q strain and found a dynamic genome carrying a type VI secretion system (T6SS) that promotes nicotine metabolism and tolerance based on transcriptomics and used in silico methods to identify the T6SS effector protein. Thus, a novel nicotine degradation mechanism was elucidated for Pseudomonas sp. JY-Q, suggesting its potential application in the bioremediation of nicotine-contaminated environments, such as TWEs.

Exploring the effect of hydrophilic and hydrophobic structure of grafted polymeric micelles on drug loading.

The objective of this paper is to explore the effect of hydrophilic and hydrophobic structure of grafted polymeric micelles on drug loading, and elucidate whether drug-polymer compatibility, as predicted by Hansen solubility parameters (HSPs), can be used as a tool for drug-polymer pairs screening and guide the design of grafted polymeric micelles. HSPs of 27 drugs and three grafted copolymers were calculated according to group contribution method. The drug-polymer compatibilities were evaluated using the approaches of Flory-Huggins interaction parameters (χFH) and polarity difference (△Xp). Two models, model A and B, were put forward for drug-polymer compatibility prediction. In model A, hydrophilic/hydrophobic part as a whole was regarded as one segment. And, in model B, hydrophilic and hydrophobic segments were evaluated individually. First of all, using chitosan (CS)-grafted-glyceryl monooeate (GMO) based micelle as an example, the suitability of model A and model B for predicating drug-polymer compatibility was evaluated theoretically. Thereafter, corresponding experiments were carried out to check the validity of the theoretical prediction. It was demonstrated that Model B, which evaluates drug compatibility with both hydrophilic and hydrophobic segments of the copolymer, is more reliable for drug-polymer compatibility prediction. Moreover, the approach of model B allows for the selection of a defined grafted polymer with for a specific drug and vice versa. Thus, drug compatibility evaluation via HSPs with both hydrophilic and hydrophobic segments is a suitable tool for the rational design of grafted polymeric micelles. The molecular dynamics (MD) simulation study provided further support to the established model and experimental results.

Designing micellar nanocarriers with improved drug loading and stability based on solubility parameter.

The objective of this study is to demonstrate the feasibility of using solubility parameter as guidance for the design and identification of a stable micellar system with a high drug loading capacity for oral drug delivery. Using hydroxycamptothecin (HCPT) as a model drug, the effect of three hydrophobic blocks (fatty glycerides) grafted onto chitosan on the drug loading and stability of HCPT-loaded micellar nanoparticles formed by pH precipitation method were studied systematically. The Flory-Huggins interaction parameter (χFH) calculated by the group contribution method (GCM) and molecular dynamics simulation (MDS) was used to assess the compatibility between HCPT and the copolymers. The predicted order of compatibility between three chitosan derivatives and HCPT was verified experimentally. A high drug loading and remarkably stable micellar system for oral administration based on succinylated glycerol monooleate-chitosan was discovered in this study. Our study suggests that the miscibility between drug and copolymer is crucial to drug loading and stability of the micellar system. Thus, the calculation of χFH using GCM and MDS methods is useful for guiding the design or screening of a suitable copolymer for preparing drug-loaded micellar nanocarrier systems.

Fast analysis of malachite green, leucomalachite green, crystal violet and leucocrystal violet in fish tissue based on a modified QuEChERS procedure.

Triphenylmethane dyes malachite green (MG) and crystal violet (CV) have been used as antimicrobial, antiparasitic and antiseptic agents in aquaculture. However, MG and CV, as well as their metabolites leucomalachite green (LMG) and leucocrystal violet (LCV) are potential mutagens and carcinogens. Thus, the efficient determination of dye residues is of great concern. Considering the complexity of the aquatic products, the sample pretreatment is significant for decreasing matrix interference and improving detection sensitivity. In this study, a simple and rapid QuEChERS procedure was developed and combined with HPLC analysis for the simultaneous determination of the four dyes in fish tissue. An XCharge C18 column was applied in HPLC analysis to achieve good peak shape and selectivity. The pretreatment method involved the extraction of dyes from fish tissue and further clean-up with dispersive solid phase extraction (d-SPE) material. The extraction volume, extraction time as well as d-SPE materials were systematically optimized. The results indicated that reversed-phase/strong anion exchange (C18SAX) adsorbent in the d-SPE procedure could effectively improve the recovery compared with conventional C18 or C18 incorporated with primary secondary amine (PSA) material. Under optimized conditions, good linearity was achieved in the concentration range of 0.5-100 mg/L with R2 greater than 0. 998. The recoveries were 73%-91% and the precisions were 0.66%-5.41%. The results demonstrated the feasibility and efficiency of QuEChERS procedure incorporated with HPLC for dye monitoring.