Variations in mid-ocean ridge CO2 emissions driven by glacial cycles

The geological record shows links between glacial cycles and volcanic productivity, both subaerially and at mid-ocean ridges. Sea-level-driven pressure changes could also affect chemical properties of mid-ocean ridge volcanism. We consider how changing sea-level could alter the CO2 emissions rate from mid-ocean ridges, on both the segment and global scale. We develop a simplified transport model for a highly incompatible element through a homogenous mantle; variations in the melt concentration the emission rate of the element are created by changes in the depth of first silicate melting. The model predicts an average global mid-ocean ridge CO2 emissions-rate of 53 Mt/yr, in line with other estimates. We show that falling sea level would cause an increase in ridge CO2 emissions with a lag of about 100 kyrs after the causative sea level change. The lag and amplitude of the response are sensitive to mantle permeability and plate spreading rate. For a reconstructed sea-level time series of the past million years, we predict variations of up to 12% (7 Mt/yr) in global mid-ocean ridge CO2 emissions. The magnitude and timing of the predicted variations in CO2 emissions suggests a potential role for ridge carbon emissions in glacial cycles

Reversible DNA micro-patterning using the fluorous effect

We describe a new method for the immobilisation of DNA into defined patterns with sub-micron resolution, using the fluorous effect. The method is fully reversible via a simple solvent wash, allowing the patterning, regeneration and re-patterning of surfaces with no degradation in binding efficiency following multiple removal/attachment cycles of different DNA sequences

Evaluating the effects of processing parameters on budesonide nanocrystals prepared by nanomilling

The aim of this study was to optimise processing parameters in the preparation ofbudesonide nanocrystals by a miniature media milling process performed at labscale. Using Polysorbate 80 as the surfactant choice of stabilizer, the effectof milling bead size, milling time and stabilizer concentration on budesonideparticle size was determined. Particle size decreased with smaller milling beadsize and longer milling time. However, no significant further decrease was seenafter milling past 6 hours. Increasing Polysorbate 80 concentration led to anincrease in budesonide particle size. Future direction will incorporatestability study with the screening of optimal stabilizer choice

Rapid nano-gram scale screening method of micro-arrays to evaluate drug-polymer blends using high-throughput printing technology

A miniaturized, high-throughput assay was optimized to screen polymer-drug solid dispersions using a 2-D Ink-jet printer. By simply printing nanoliter amounts of polymer and drug solutions onto an inert surface, drug:polymer micro-dots of tunable composition were produced in an easily-addressable micro-array format. The amount of material printed for each dried spot ranged from 25 ng to 650 ng. These arrays were used to assess the stability of drug:polymer dispersions with respect to recrystallization, using polarized light microscopy. One array with a panel of 6 drugs formulated at different ratios with Poly (vinylpyrrolidone-vinyl acetate) copolymer (PVPVA) was developed to estimate a possible bulk (gram-scale) approximation threshold from the final printed nano amount of formulation. Another array was printed at a fixed final amount of material to establish a literature comparison of one drug formulated with different commercial polymers for validation. This new approach may offer significant efficiency in pharmaceutical formulation screening, with each experiment in the nano-micro-array format requiring from 3 up to 6 orders of magnitude lower amounts of sample than conventional screening methods

High‐Throughput Miniaturized Screening of Nanoparticle Formation via Inkjet Printing

This is the peer reviewed version of the following article:Ioanna D. Styliari, et al, ‘High‐Throughput Miniaturized Screening of Nanoparticle Formation via Inkjet Printing’, Macromolecular Materials and Engineering, (2018), which has been published in final form at https://doi.org/10.1002/mame.201800146. Under embargo until 27 May 2019. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.The self‐assembly of specific polymers into well‐defined nanoparticles (NPs) is of great interest to the pharmaceutical industry as the resultant materials can act as drug delivery vehicles. In this work, a high‐throughput method to screen the ability of polymers to self‐assemble into NPs using a picoliter inkjet printer is presented. By dispensing polymer solutions in dimethyl sulfoxide (DMSO) from the printer into the wells of a 96‐well plate, containing water as an antisolvent, 50 suspensions are screened for nanoparticle formation rapidly using only nanoliters to microliters. A variety of polymer classes are used and in situ characterization of the submicroliter nanosuspensions shows that the particle size distributions match those of nanoparticles made from bulk suspensions. Dispensing organic polymer solutions into well plates via the printer is thus shown to be a reproducible and fast method for screening nanoparticle formation which uses two to three orders of magnitude less material than conventional techniques. Finally, a pilot study for a high‐throughput pipeline of nanoparticle production, physical property characterization, and cytocompatibility demonstrates the feasibility of the printing approach for screening of nanodrug delivery formulations. Nanoparticles are produced in the well plates, characterized for size and evaluated for effects on metabolic activity of lung cancer cells.Peer reviewe

Analysis and prediction of defects in UV photo-initiated polymer microarrays

Polymer microarrays are a key enabling technology for the discovery of novel materials. This technology can be further enhanced by expanding the combinatorial space represented on an array. However, not all materials are compatible with the microarray format and materials must be screened to assess their suitability with the microarray manufacturing methodology prior to their inclusion in a materials discovery investigation. In this study a library of materials expressed on the microarray format are assessed by light microscopy, atomic force microscopy and time-of-flight secondary ion mass spectrometry to identify compositions with defects that cause a polymer spot to exhibit surface properties significantly different from a smooth, round, chemically homogeneous ‘normal’ spot. It was demonstrated that the presence of these defects could be predicted in 85% of cases using a partial least square regression model based upon molecular descriptors of the monomer components of the polymeric materials. This may allow for potentially defective materials to be identified prior to their formation. Analysis of the PLS regression model highlighted some chemical properties that influenced the formation of defects, and in particular suggested that mixing a methacrylate and an acrylate monomer and/or mixing monomers with long and linear or short and bulky pendant groups will prevent the formation of defects. These results are of interest for the formation of polymer microarrays and may also inform the formulation of printed polymer materials generally.Burroughs Wellcome Fund (grant number 085245)Royal Society (Great Britain) (Wolfson Research Merit Award

Dichloro[(eta(5)-cyclopentadienyl)dimethyl(eta(5)-3-phenylindenyl)silane]hafnium(IV) : a powder study

Peer reviewe

Strategies for MCR image analysis of large hyperspectral data-sets

Polymer microarrays are a key enabling technology for high throughput materials discovery. In this study, multivariate image analysis, specifically multivariate curve resolution (MCR), is applied to the hyperspectral time of flight secondary ion mass spectroscopy (ToF-SIMS) data from eight individual microarray spots. Rather than analysing the data individually, the data-sets are collated and analysed as a single large data-set. Desktop computing is not a practical method for undertaking MCR analysis of such large data-sets due to the constraints of memory and computational overhead. Here, a distributed memory High-Performance Computing facility (HPC) is used. Similar to what is achieved using MCR analysis of individual samples, the results from this consolidated data-set allow clear identification of the substrate material; furthermore, specific chemistries common to different spots are also identified. The application of the HPC facility to the MCR analysis of ToF-SIMS hyperspectral data-sets demonstrates a potential methodology for the analysis of macro-scale data without compromising spatial resolution (data ‘binning’

Strategies for MCR image analysis of large hyperspectral data-sets

Polymer microarrays are a key enabling technology for high throughput materials discovery. In this study, multivariate image analysis, specifically multivariate curve resolution (MCR), is applied to the hyperspectral time of flight secondary ion mass spectroscopy (ToF-SIMS) data from eight individual microarray spots. Rather than analysing the data individually, the data-sets are collated and analysed as a single large data-set. Desktop computing is not a practical method for undertaking MCR analysis of such large data-sets due to the constraints of memory and computational overhead. Here, a distributed memory High-Performance Computing facility (HPC) is used. Similar to what is achieved using MCR analysis of individual samples, the results from this consolidated data-set allow clear identification of the substrate material; furthermore, specific chemistries common to different spots are also identified. The application of the HPC facility to the MCR analysis of ToF-SIMS hyperspectral data-sets demonstrates a potential methodology for the analysis of macro-scale data without compromising spatial resolution (data ‘binning’