3D‐morphology reconstruction of nanoscale phase‐separation in polymer memory blends

In many organic electronic devices functionality is achieved by blending two or more materials, typically polymers or molecules, with distinctly different optical or electrical properties in a single film. The local scale morphology of such blends is vital for the device performance. Here, a simple approach to study the full 3D morphology of phase‐separated blends, taking advantage of the possibility to selectively dissolve the different components is introduced. This method is applied in combination with AFM to investigate a blend of a semiconducting and ferroelectric polymer typically used as active layer in organic ferroelectric resistive switches. It is found that the blend consists of a ferroelectric matrix with three types of embedded semiconductor domains and a thin wetting layer at the bottom electrode. Statistical analysis of the obtained images excludes the presence of a fourth type of domains. The criteria for the applicability of the presented technique are discussed. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2015 , 53, 1231–1237     

Microextraction of metal ions based on solidification of a floating drop: Basics and recent updates

This review provides a comprehensive evaluation of solidified floating organic drop microextraction (SFODME) procedures for metal ions preconcentration and their contributions to green chemistry. In this article we focused on the modifications that have been performed in the recent years to improve this environmentally friendly procedure. Among the most important of these modifications are the inclusion of ultrasonic energy, vortex and air agitation to enhance the dispersion process. The article also discussed new challenges in the procedure by using more ecofriendly solvents as extractants such as ionic liquids, deep eutectic. and supramolecular solvents. The coupling of SFODME with solid phase extraction increases selectivity and efficiency of the preconcentration procedure.     

A Shell-by-Shell Approach for Synthesis of Mesoporous Multi-Shelled Hollow MOFs for Catalytic Applications

Over the past two decades, advanced materials with hollow interiors have received significant attention in materials research owing to their great application potential across a vast number of technological fields. Though with great difficulty, multi-shelled hollow metal–organic frameworks (MSHMs) have also been successfully synthesized in recent years. Herein, a rational shell-by-shell soft-templating protocol has been devised to fabricate highly uniform multi-shelled hollow cobalt-imidazole-based MOF (ZIF-67). For the first time, it has become possible to endow mesoporosity to this new type of functional material (i.e., mesoporous MOFs). When used as carrier materials in catalytic reactions, in principle, these mesoporous MSHMs with high surface area not only improve the dispersity of metal nanoparticles (NPs), but also efficiently facilitate the mass diffusion of the reactions, resulting in enhanced catalyst activity. Moreover, the obtained MSHMs/M nanocomposites serve as base-metal bifunctional catalysts for one-pot oxidation-Knoevenagel condensation cascade reaction, in which the MSHMs itself serves as a pristine active catalyst in addition to its role of catalyst support. The results demonstrate that excellent multifunctional catalysts can be achieved via preparing intrinsically microporous bulk MOFs into extrinsically mesoporous MSHMs which possess many structural merits that conventional bulk MOFs do not have.     

Microwave‐assisted polycondensation of 4‐octylaniline with dibromoarylene

The Pd‐catalyzed polycondensation of 4‐octylaniline with various dibromoarylenes was carried out under microwave heating. Microwave heating led to a decrease in the reaction time and an increase in the molecular weight of the polymers as compared to conventional heating. Microwave heating also allowed the catalyst loading to be reduced to 1 mol %, yielding polymerization results that were comparable to those under conventional heating and 5 mol % catalyst. Investigations regarding field‐effect transistors and organic photovoltaic cells using the obtained poly(arylamine) with azobenzene units revealed that increasing the molecular weight of the polymer led to improved device performance, including hole mobility and power conversion efficiency. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2015 , 53, 536–542     

Buffering effects on the solution behavior and hydrolytic degradation of poly(β-amino ester)s

With a vast, synthetically accessible compositional space and highly tunable hydrolysis rates, poly(β-amino ester)s (PBAEs) are an attractive degradable polymer platform. Leveraging PBAEs in a wide range of applications hinges on the ability to program degradation, which, thus far, has been frustrated by multiple confounding phenomena contributing to the degradation of these charged polyesters. Basic conditions accelerate hydrolysis, yet reduce solubility, limiting water access to amines and esters. Further, the high buffering capacity of PBAEs can render buffers ineffective at controlling solution pH. To unify understanding of PBAE degradation and solution properties, this study examines PBAE hydrolysis as a function of pH and buffer concentration as well as polymer hydrophobicity. At low buffer concentrations, the PBAE amines and the acid produced during hydrolysis control solution pH. Meanwhile, at high buffer concentrations that afford relatively constant pH, hydrolysis rate increases with pH, despite the reduced PBAE solubility. Increasing the hydrophobic content of PBAEs eventually hinders the capacity of the polymer to accept protons from solution, limiting the pH increase and slowing hydrolysis. These studies showcase the role of buffering on the pH-dependent degradation and solution properties of PBAEs, providing guidance for programming degradation in applications ranging from drug delivery to thermosets.     

A volatolomic approach using cerumen as biofluid to diagnose bovine intoxication by Stryphnodendron rotundifolium

An innovative volatolomic approach employs the detection of biomarkers present in cerumen (earwax) to identify cattle intoxication by Stryphnodendron rotundifolium Mart., Fabaceae (popularly known as barbatimão). S. rotundifolium is a poisonous plant with the toxic compound undefined and widely distributed throughout the Brazilian territory. Cerumen samples from cattle of two local Brazilian breeds (‘Curraleiro Pé-Duro’ and ‘Pantaneiro’) were collected during an experimental intoxication protocol and analyzed using headspace (HS)/GC–MS followed by multivariate analysis (genetic algorithm for a partial least squares, cluster analysis, and classification and regression trees). A total of 106 volatile organic metabolites were identified in the cerumen samples of bovines. The intoxication by S. rotundifolium influenced the cerumen volatolomic profile of the bovines throughout the intoxication protocol. In this way, it was possible to detect biomarkers for cattle intoxication. Among the biomarkers, 2-octyldecanol and 9-tetradecen-1-ol were able to discriminate all samples between intoxicated and nonintoxicated bovines. The cattle intoxication diagnosis by S. rotundifolium was accomplished by applying the cerumen analysis using HS/GC–MS, in an easy, accurate, and noninvasive way. Thus, the proposed bioanalytical chromatography protocol is a useful tool in veterinary applications to determine this kind of intoxication.     

Identifying aspirin polymorphs from combined DFT-based crystal structure prediction and solid-state NMR

A combined experimental and computational approach was used to distinguish between different polymorphs of the pharmaceutical drug aspirin. This method involves the use of ab initio random structure searching (AIRSS), a density functional theory (DFT)-based crystal structure prediction method for the high-accuracy prediction of polymorphic structures, with DFT calculations of nuclear magnetic resonance (NMR) parameters and solid-state NMR experiments at natural abundance. AIRSS was used to predict the crystal structures of form-I and form-II of aspirin. The root-mean-square deviation between experimental and calculated ¹H chemical shifts was used to identify form-I as the polymorph present in the experimental sample, the selection being successful despite the large similarities between the molecular environments in the crystals of the two polymorphs.     

A self-penetrating and chemically stable zinc (ii)-organic framework as multi-responsive chemo-sensor to detect pesticide and antibiotics in water

Guided by the self-penetrating features can improve the stability of metal organic frameworks (MOFs), an unprecedented 3D self-penetrated framework, {[Zn (tptc)_0.5(bimb)]·H₂O}_n ( NUC-6 , here NUC corresponding to North University of China), with 3D (4,4)-c {8⁶} net, was designed. Benefit from the high chemical stability and excellent luminescent property, NUC-6 can be act as an efficient multi-response chemo-sensor in detecting dichloronitroaniline pesticide and nitrofuran antibiotics in water with the detection limits are 116 ppb for DCN pesticide, 16 ppb for NFT antibiotic, and 12 ppb for NTZ antibiotic. Besides, the mechanisms of luminescence quenching were revealed from the viewpoint of internal filter effect (IFE) and photo-induced electron transfer (PET), implied by the optical spectroscopy and quantum chemical calculation. This work provides a promising strategy to design stable MOFs by improving the self-penetrating features and to expand their practical applications in the detection of organic pollutants in aqueous medium.     

Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.