Solar Thermal Energy Storage in a Photochromic Macrocycle

The conversion and efficient storage of solar energy is recognized to hold significant potential with regard to future energy solutions. Molecular solar thermal batteries based on photochromic systems exemplify one possible technology able to harness and apply this potential. Herein is described the synthesis of a macrocycle based on a dimer of the dihydroazulene/vinylheptafulvene (DHA/VHF) photo/thermal couple. By taking advantage of conformational strain, this DHA–DHA macrocycle presents an improved ability to absorb and store incident light energy in chemical bonds (VHF–VHF). A stepwise energy release over two sequential ring‐closing reactions (VHF→DHA) combines the advantages of an initially fast discharge, hypothetically addressing immediate energy consumption needs, followed by a slow process for consistent, long‐term use. This exemplifies another step forward in the molecular engineering and design of functional organic materials towards solar thermal energy storage and release.     

Facile synthesis of dopa‐functional polycarbonates via thiol‐Ene‐coupling chemistry towards self‐healing gels

Since extraction of the naturally occurring mussel‐foot proteins is expensive and time‐consuming, routes towards synthetic analogues are continuously being explored. Often, these methods involve several protection and deprotection steps, making the synthesis of synthetic analogues time‐consuming and expensive as well. Herein, we show that UV‐initiated thiol‐ene coupling between a thiol‐functional dopamine derivative and an allyl‐functional aliphatic polycarbonate can be used as a fast and facile route to dopa‐functional materials. Different thiol‐to‐allyl ratios and irradiation protocols were used and it was found that nearly 50% of the allyl groups could be functionalized with dopa within short reaction times, without the need of protecting the catechol. It is also demonstrated herein that the dopa‐functional polymers can be used to form self‐healing gels through complexation with Fe³⁺ ions at increased pH. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2016 , 54, 2370–2378     

Validation of a robust and rapid liquid chromatography tandem mass spectrometric method for the quantitative analysis of navitoclax

The Bcl-2 family small molecule inhibitor navitoclax is being clinically evaluated to treat multiple cancers including lymphoid malignancies and small cell lung cancer. A sensitive and reliable method was developed to quantitate navitoclax in human plasma using liquid chromatography with tandem mass spectrometry with which to perform detailed pharmacokinetic studies. Sample preparation involved protein precipitation using acetonitrile. Separation of navitoclax and the internal standard, navitoclax-d8, was achieved with a Waters Acquity UPLC BEH C₁₈ column using isocratic flow over a 3 min total analytical run time. A SCIEX 4500 triple quadrupole mass spectrometer operated in positive electrospray ionization mode was used for the detection of navitoclax. The assay range was 5–5,000 ng/ml and proved to be accurate (89.5–104.9%) and precise (CV ≤ 11%). Long-term frozen plasma stability for navitoclax at −70°C was at least 43 months. The method was applied for the measurement of total plasma concentration of navitoclax in a patient receiving a 250 mg daily oral dose.     

Multivariate analysis of extremely large ToFSIMS imaging datasets by a rapid PCA method

Principal component analysis (PCA) and other multivariate analysis methods have been used increasingly to analyse and understand depth profiles in X‐ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and secondary ion mass spectrometry (SIMS). These methods have proved equally useful in fundamental studies as in applied work where speed of interpretation is very valuable. Until now these methods have been difficult to apply to very large datasets such as spectra associated with 2D images or 3D depth‐profiles. Existing algorithms for computing PCA matrices have been either too slow or demanded more memory than is available on desktop PCs. This often forces analysts to ‘bin’ spectra on much more coarse a grid than they would like, perhaps even to unity mass bins even though much higher resolution is available, or select only part of an image for PCA analysis, even though PCA of the full data would be preferred. We apply the new ‘random vectors’ method of singular value decomposition proposed by Halko and co‐authors to time‐of‐flight (ToF)SIMS data for the first time. This increases the speed of calculation by a factor of several hundred, making PCA of these datasets practical on desktop PCs for the first time. For large images or 3D depth profiles we have implemented a version of this algorithm which minimises memory needs, so that even datasets too large to store in memory can be processed into PCA results on an ordinary PC with a few gigabytes of memory in a few hours. We present results from ToFSIMS imaging of a citrate crystal and a basalt rock sample, the largest of which is 134GB in file size corresponding to 67 111 mass values at each of 512 × 512 pixels. This was processed into 100 PCA components in six hours on a conventional Windows desktop PC. © 2015 The Authors. Surface and Interface Analysis published by John Wiley & Sons Ltd.