Treatment of Phaeodactylum tricornutum cells with papain facilitates lipid extraction

Triacylglycerols (TAGs) from microalgae have the potential to be used for biodiesel, but several technical and economic hurdles have to be overcome. A major challenge is efficient extraction of intracellular TAGs from algae. Here we investigate the use of enzymes to deconstruct algal cell walls/membranes. We describe a rapid and simple assay that can assess the efficacy of different enzyme treatments on TAG-containing algae. By this means crude papain and bromelain were found to be effective in releasing TAGs from the diatom Phaeodactylum tricornutum, most likely because of their cysteine protease activity. Pre-treating algal biomass with crude papain enabled complete extraction of TAGs using heptane/isopropyl alcohol. Heptane as a single solvent was also effective, although complete recovery of TAG was not obtained. Economic implications of these findings are discussed, with the aim to reduce the complexity of, and energy needed in, TAG extraction. © 2012 Elsevier B.V.

Analytical field-effect method for extraction of subgap states in thin-film transistors

We present an analytical field-effect method to extract the density of subgap states (subgap DOS) in amorphous semiconductor thin-film transistors (TFTs), using a closed-form relationship between surface potential and gate voltage. By accounting the interface states in the subthreshold characteristics, the subgap DOS is retrieved, leading to a reasonably accurate description of field-effect mobility and its gate voltage dependence. The method proposed here is very useful not only in extracting device performance but also in physically based compact TFT modeling for circuit simulation. © 2012 IEEE.

Multilinear function factorisation for time series feature extraction

This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain specific feature extraction schemes of this type are not necessarily needed for time series classification, as excellent classification results can be obtained by simply applying a number of existing matrix factorisation or linear projection techniques, which are simple and computationally inexpensive. We highlight this using a geometric separability measure and classification accuracies obtained though experiments on four different high dimensional multivariate time series datasets. © 2013 IEEE.

A novel method of extraction of blend component structure from SANS measurements of homopolymer bimodal blends

A new method is presented for the extraction of single-chain form factors and interchain interference functions from a range of small-angle neutron scattering (SANS) experiments on bimodal homopolymer blends. The method requires a minimum of three blends, made up of hydrogenated and deuterated components with matched degree of polymerization at two different chain lengths, but with carefully varying deuteration levels. The method is validated through an experimental study on polystyrene homopolymer bimodal blends with M A≈1/2MB. By fitting Debye functions to the structure factors, it is shown that there is good agreement between the molar mass of the components obtained from SANS and from chromatography. The extraction method also enables, for the first time, interchain scattering functions to be produced for scattering between chains of different lengths. © 2014 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fourier spectrum based extraction of an equivalent trap state density in indium gallium zinc oxide transistors

Segregating the dynamics of gate bias induced threshold voltage shift, and in particular, charge trapping in thin film transistors (TFTs) based on time constants provides insight into the different mechanisms underlying TFTs instability. In this Letter we develop a representation of the time constants and model the magnitude of charge trapped in the form of an equivalent density of created trap states. This representation is extracted from the Fourier spectrum of the dynamics of charge trapping. Using amorphous In-Ga-Zn-O TFTs as an example, the charge trapping was modeled within an energy range of ΔEt 0.3 eV and with a density of state distribution as Dt(Et-j)=Dt0exp(-ΔEt/ kT)with Dt0 = 5.02 × 1011 cm-2 eV-1. Such a model is useful for developing simulation tools for circuit design. © 2014 AIP Publishing LLC.