Tuning reaction products by constrained optimisation

We describe an effective means of defining optimisation criteria for self-optimising reactors, applicable to situations where a compromise is sought between several competing objectives. The problem is framed as a constrained optimisation, in which a lead property is optimised subject to constraints on the values that other properties may assume. Compared to conventional methods (using weighted-sum- and weighted-product-based merit functions), the approach described here is more intuitive, easier to implement, and yields an optimised solution that more faithfully reflects user preferences. The method is applied here to the synthesis of o-xylenyl adducts of Buckminsterfullerene, using a cascadic reaction of the form X0 → X1 → X2 → … XN. Specifically, we selectively target the formation of the (technologically useful) first- and second-order adducts X1 and X2, while at the same time suppressing the formation of unwanted higher-order products. More generally, the approach is applicable to any chemical optimisation involving a trade-off between competing criteria. To assist with implementation we provide a self-contained software package for carrying out constrained optimisation, together with detailed tutorial-style instructions

Sub-millisecond control of neuronal firing by organic light-emitting diodes

Optogenetics combines optics and genetics to enable minimally invasive cell-type-specific stimulation in living tissue. For the purposes of bio-implantation, there is a need to develop soft, flexible, transparent and highly biocompatible light sources. Organic semiconducting materials have key advantages over their inorganic counterparts, including low Young's moduli, high strain resistances, and wide color tunability. However, until now it has been unclear whether organic light emitting diodes (OLEDs) are capable of providing sufficient optical power for successful neuronal stimulation, while still remaining within a biologically acceptable temperature range. Here we investigate the use of blue polyfluorene- and orange poly(p-phenylenevinylene)-based OLEDs as stimuli for blue-light-activated Sustained Step Function Opsin (SFFO) and red-light-activated ChrimsonR opsin, respectively. We show that, when biased using high frequency (multi-kHz) drive schemes, the OLEDs permit safe and controlled photostimulation of opsin-expressing neurons and were able to control neuronal firing with high temporal-resolution at operating temperatures lower than previously demonstrated

Pruning neural network for architecture optimization applied to near-infrared reflectance spectroscopic measurements. Determination of the nitrogen content in wheat leaves

The pruning neural network, based on the algorithm called optimum brain surgeon, was used for network architecture optimization. This network pruning procedure was applied for estimating the nitrogen contents in wheat leaves, using near-infrared diffuse reflectance spectroscopy. The results obtained with pruning were compared with those obtained by using ordinary procedures with neural networks, partial least squares, polynomial partial least squares and neural networks/partial least squares methodologies. Comparison of the results with those obtained by the conventional Kjeldahl method showed that the results with pruning neural networks were as good as those with ordinary neural networks and with PLS/neural networks, but better than those with the other methodologies. Although the comparison was performed for one data set, the pruning procedure has the advantage of introducing an automatic architecture optimization, which is cumbersome when performed by the other neural network procedures used in this work, generating a simplified model with better generalization abilities.124111669167

Entanglements in marginal solutions: a means of tuning pre-aggregation of conjugated polymers with positive implications for charge transport

The solution-processing of conjugated polymers, just like commodity polymers, is subject to solvent and molecular weight-dependent solubility, interactions and chain entanglements within the polymer, all of which can influence the crystallization and microstructure development in semi-crystalline polymers and consequently affect charge transport and optoelectronic properties. Disentanglement of polymer chains in marginal solvents was reported to work via ultrasonication, facilitating the formation of photophysically ordered polymer aggregates. In this contribution, we explore how a wide range of technologically relevant solvents and formulations commonly used in organic electronics influence chain entanglement and the aggregation behaviour of P3HT using a combination of rheological and spectrophotometric measurements. The specific viscosity of the solution offers an excellent indication of the degree of entanglements in the solution, which is found to be related to the solubility of P3HT in a given solvent. Moreover, deliberately disentangling the solution in the presence of solvophobic driving forces, leads consistently to formation of photophysically visible aggregates which is indicative of local and perhaps long range order in the solute. We show for a broad range of solvents and molecular weights that disentanglement ultimately leads to significant ordering of the polymer in the solid state and a commensurate increase in charge transport properties. In doing so we demonstrate a remarkable ability to tune the microstructure which has important implications for transport properties. We discuss its potential implications in the context of organic electronics and photovoltaics

Direct dispersion of SWNTs in highly conductive solvent-enhanced PEDOT:PSS films

Poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) is shown to be an effective dispersant for single-wall carbon nanotubes (SWNTs), enabling uniform aqueous suspensions to be obtained at weight loadings of up to 0.23 mg/ml (>1% by weight relative to PEDOT:PSS) without recourse to additional surfactants. Thin films spin-coated from PEDOT:PSS/SWNT suspensions exhibited sheet resistances of 90 Ω/sq. at 80 % transmittance, slightly higher than equivalent films of pure PEDOT:PSS which exhibited sheet resistances of 70 Ω/sq. at the same transmittance

Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments