Carbon nanoparticles as chromophores for photon harvesting and photoconversion

Carbon nanomaterials have generated a tremendous amount of attention in the scientific community. While most of the research and development efforts have been on fullerenes, carbon nanotubes, and graphene sheets, carbon nanoparticles (which are often considered as impurities or unwanted complications in the other carbon nanomaterials) have recently emerged as a unique class of highly fluorescent nano-dots. However, little or no attention has been paid to potential uses of carbon nanoparticles as chromophores in photochemical reactions or for photon harvesting and photoconversion in general. In the study reported herein we demonstrate the chromophore-equivalent functions of aqueous-suspended small carbon nanoparticles in harvesting visible photons for the reductive coating of the nanoparticles with silver and gold and, as a result, the preparation of unique carbon-noble-metal core-shell nanostructures.     

Targeting proteins to liquid-ordered domains in lipid membranes

We demonstrate the construction of novel protein-lipid assemblies through the design of a lipid-like molecule, DPIDA, endowed with tail-driven affinity for specific lipid membrane phases and head-driven affinity for specific proteins. In studies performed on giant unilamellar vesicles (GUVs) with varying mole fractions of dipalymitoylphosphatidylcholine (DPPC), cholesterol, and diphytanoylphosphatidyl choline (DPhPC), DPIDA selectively partitioned into the more ordered phases, either solid or liquid-ordered (L(o)) depending on membrane composition. Fluorescence imaging established the phase behavior of the resulting quaternary lipid system. Fluorescence correlation spectroscopy confirmed the fluidity of the L(o) phase containing DPIDA. In the presence of CuCl(2), the iminodiacetic acid (IDA) headgroup of DPIDA forms the Cu(II)-IDA complex that exhibits a high affinity for histidine residues. His-tagged proteins were bound specifically to domains enriched in DPIDA, demonstrating the capacity to target protein binding selectively to both solid and L(o) phases. Steric pressure from the crowding of surface-bound proteins transformed the domains into tubules with persistence lengths that depended on the phase state of the lipid domains.     

Classification of jet fuels by fuzzy rule-building expert systems applied to three-way data by fast gas chromatography--fast scanning quadrupole ion trap mass spectrometry

A fast method that can be used to classify unknown jet fuel types or detect possible property changes in jet fuel physical properties is of paramount interest to national defense and the airline industries. While fast gas chromatography (GC) has been used with conventional mass spectrometry (MS) to study jet fuels, fast GC was combined with fast scanning MS and used to classify jet fuels into lot numbers or origin for the first time by using fuzzy rule-building expert system (FuRES) classifiers. In the process of building classifiers, the data were pretreated with and without wavelet transformation and evaluated with respect to performance. Principal component transformation was used to compress the two-way data images prior to classification. Jet fuel samples were successfully classified with 99.8 ± 0.5% accuracy for both with and without wavelet compression. Ten bootstrapped Latin partitions were used to validate the generalized prediction accuracy. Optimized partial least squares (o-PLS) regression results were used as positively biased references for comparing the FuRES prediction results. The prediction results for the jet fuel samples obtained with these two methods were compared statistically. The projected difference resolution (PDR) method was also used to evaluate the fast GC and fast MS data. Two batches of aliquots of ten new samples were prepared and run independently 4 days apart to evaluate the robustness of the method. The only change in classification parameters was the use of polynomial retention time alignment to correct for drift that occurred during the 4-day span of the two collections. FuRES achieved perfect classifications for four models of uncompressed three-way data. This fast GC/fast MS method furnishes characteristics of high speed, accuracy, and robustness. This mode of measurement may be useful as a monitoring tool to track changes in the chemical composition of fuels that may also lead to property changes.