Determination of phosphate using a highly sensitive paired emitter-detector diode photometric flow detector

The use of a novel inexpensive photometric device, a paired emitter-detector diode (PEDD) has been applied to the colorimetric determination of phosphate using the malachite green spectrophotometric method. The novel miniaturized flow detector applied within this manifold is a highly sensitive, low cost, miniaturized light emitting diode (LED) based detector. The optical flow cell was constructed from two LEDs, whereby one is the light source and the second is the light detector, with the LED light source forward biased and the LED detector reversed biased. The photocurrent generated by the LED light source discharges the junction capacitance of the detector diode from 5 V (logic 1) to 1.7 V (logic 0) and the time taken for this process to occur is measured using a simple timer circuit.The malachite green (MG) method employed for phosphate determination is based on the formation of a green molybdophosphoric acid complex, the intensity of which is directly related to phosphate concentration. Optimum analytical parameters such as reaction kinetics, reagent to sample concentration ratio and emitter wavelength intensity were investigated for the spectrophotometric method. Linear calibration plots that obeyed the Beer-Lambert law were obtained for phosphate in the range of 0.02-2 μM. The dynamic range, sensitivity and limits of detection are reported.     

Universal interpolating function for the dispersion coefficient of DNA fragments in sieving matrices

The separation of DNA fragments by (slab or capillary) gel electrophoresis has been studied extensively. To characterize the separation achieved by such systems, one needs to understand the impact (and their dependency upon the experimental quantities) of two physical parameters: the electrophoretic mobility mu and the diffusion coefficient D. Three different regimes have been shown to exist for both mu and D: the Ogston regime, the reptation regime and the reptation with orientation regime (note that separation is only possible for the first two regimes). In the small electric field limit, both mu and D are apparently well described by theories for all three regimes. Unfortunately this results in disjointed scaling laws and no theory-based general equations can apply to all regimes. Recently, an empirical interpolating formula has been proposed that adequately fits the low electric field mobility mu of dsDNA fragments across all three regimes and is compatible with accepted theories. In this article we review and clarify the current state of knowledge regarding the size dependence of the mobility and the diffusion coefficient and propose an interpolating formula for molecular size dependence of the low field diffusion coefficient D. With formulas for both the mobility and the diffusion coefficient as a function of the experimental conditions one could, in principle, optimize any gel/polymer matrix-based electrophoresis system for a wide range of DNA molecular sizes.     

Structural studies of apatite-type oxide ion conductors doped with cobalt

A series of Co doped lanthanum silicate apatite-type phases, La9.83Si4.5Co1.5O26, La9.66Si5CoO26, La10Si5CoO26.5 and La8BaCoSi6O26, have been synthesised, and neutron diffraction, EXAFS and XANES used to investigate their structures in detail. All compositions were shown to possess the hexagonal apatite structure, and the results confirmed that cobalt can be doped onto both the La and Si sites within the structure depending on the starting composition. The Co doping is shown to cause considerable local distortions within the apatite structure. In the case of Si site doping two compositions showed anisotropic peak broadening, which has been attributed to incommensurate ordering of oxygen within the apatite channels.     

End-labeled free-solution electrophoresis of DNA

DNA is a free-draining polymer. This subtle but "unfortunate" property of highly charged polyelectrolytes makes it impossible to separate nucleic acids by free-flow electrophoresis. This is why one must typically use a sieving matrix, such as a gel or an entangled polymer solution, in order to obtain some electrophoretic size separation. An alternative approach consists of breaking the charge to friction balance of free-draining DNA molecules. This can be achieved by labeling the DNA with a large, uncharged molecule (essentially a hydrodynamic parachute, which we also call a drag-tag) prior to electrophoresis; the resulting methodology is called end-labeled free-solution electrophoresis (ELFSE). In this article, we review the development of ELFSE over the last decade. In particular, we examine the theoretical concepts used to predict the ultimate performance of ELFSE for single-stranded (ssDNA) sequencing, the experimental results showing that ELFSE can indeed overcome the free-draining issue raised above, and the technological advances that are needed to speed the development of competitive ELFSE-based sequencing and separation technologies. Finally, we also review the reverse process, called free-solution conjugate electrophoresis (FSCE), wherein uncharged polymers of different sizes can be analyzed using a short DNA molecule as an electrophoretic engine.     

A modeling concept of a mechanical system having a piecewise linear spring property for its diagnosis

Machine condition monitoring and fault diagnosis of rotating machinery are very important because of the wide use of rotating machinery in industry. Couplings and gears are used in many mechanical systems to connect elements and transmit power. The system is usually modeled as a single-degree-of-freedom system with a piecewise linear spring property, where the mass of main machine is only considered. In the present study, the dynamic behavior of a system with an unsymmetrical nonlinearity and a significant mass of the connecting part was investigated both experimentally and by numerical simulation. In the experiment, a 1/3 sub-harmonic oscillation was observed, but this oscillation was not found in the simulation using a single-degree-of-freedom system, in which the mass of the connecting part was ignored. However, when a two-degrees-of-freedom system was used that considered both the mass of the connecting part and the impact property, the 1/3 sub-harmonic oscillation was observed. Thus it is recognized that an adequate mathematical model for diagnosis in the early stage of abnormality must be selected on the basis of the mass ratio between the connecting part and the main body.     

An Introduction to Closed/Open Neighborhood Sums: Minimax, Maximin, and Spread

For a graph G of order |V(G)| = n and a real-valued mapping f:V(G)?\mathbbR{f:V(G)\rightarrow\mathbb{R}}, if S ì V(G){S\subset V(G)} then f(S)=?_{w ? S} f(w){f(S)=\sum_{w\in S} f(w)} is called the weight of S under f. The closed (respectively, open) neighborhood sum of f is the maximum weight of a closed (respectively, open) neighborhood under f, that is, NS[f]=max{f(N[v])|v ? V(G)}{NS[f]={\rm max}\{f(N[v])|v \in V(G)\}} and NS(f)=max{f(N(v))|v ? V(G)}{NS(f)={\rm max}\{f(N(v))|v \in V(G)\}}. The closed (respectively, open) lower neighborhood sum of f is the minimum weight of a closed (respectively, open) neighborhood under f, that is, NS^-[f]=min{f(N[v])|v ? V(G)}{NS^{-}[f]={\rm min}\{f(N[v])|v\in V(G)\}} and NS^-(f)=min{f(N(v))|v ? V(G)}{NS^{-}(f)={\rm min}\{f(N(v))|v\in V(G)\}}. For W ì \mathbbR{W\subset \mathbb{R}}, the closed and open neighborhood sum parameters are NS_W[G]=min{NS[f]|f:V(G)? W{NS_W[G]={\rm min}\{NS[f]|f:V(G)\rightarrow W} is a bijection} and NS_W(G)=min{NS(f)|f:V(G)? W{NS_W(G)={\rm min}\{NS(f)|f:V(G)\rightarrow W} is a bijection}. The lower neighbor sum parameters are NS^-_W[G]=maxNS^-[f]|f:V(G)? W{NS^{-}_W[G]={\rm max}NS^{-}[f]|f:V(G)\rightarrow W} is a bijection} and NS^-_W(G)=maxNS^-(f)|f:V(G)? W{NS^{-}_W(G)={\rm max}NS^{-}(f)|f:V(G)\rightarrow W} is a bijection}. For bijections f:V(G)? {1,2,?,n}{f:V(G)\rightarrow \{1,2,\ldots,n\}} we consider the parameters NS[G], NS(G), NS ⁻[G] and NS ⁻(G), as well as two parameters minimizing the maximum difference in neighborhood sums.     

Assessing the Importance of Cation Size in the Tetragonal-Cubic Phase Transition in Lithium-Garnet Electrolytes**

Lithium garnets are promising solid-state electrolytes for next-generation lithium-ion batteries. These materials have high ionic conductivity, a wide electrochemical window and stability with Li metal. However, lithium garnets have a maximum limit of seven lithium atoms per formula unit (e.g., La₃Zr₂Li₇O₁₂), before the system transitions from a cubic to a tetragonal phase with poor ionic mobility. This arises from full occupation of the Li sites. Hence, the most conductive lithium garnets have Li between 6–6.55 Li per formula unit, which maintains the cubic symmetry and the disordered Li sub-lattice. The tetragonal phase, however, forms the highly conducting cubic phase at higher temperatures, thought to arise from increased cell volume and entropic stabilisation permitting Li disorder. However, little work has been undertaken in understanding the controlling factors of this phase transition, which could enable enhanced dopant strategies to maintain room temperature cubic garnet at higher Li contents. Here, a series of nine tetragonal garnets were synthesised and analysed by variable temperature XRD to understand the dependence of site substitution on the phase transition temperature. Interestingly the octahedral site cation radius was identified as the key parameter for the transition temperature with larger or smaller dopants altering the transition temperature noticeably. A site substitution was, however, found to make little difference irrespective of significant changes to cell volume.     

Effect of artificial mucus properties on the characteristics of airborne bioaerosol droplets generated during simulated coughing

The effect of viscoelastic properties and surface tension of artificial mucus simulant samples on the size distribution and volume concentration of bioaerosol droplets generated during simulated coughing was investigated through in vitro experiments. The mucus simulant samples had viscoelastic properties in a similar range as those of real human airway mucus. The mucus simulant gels were prepared by mixing various proportions of 0.5–1.7% locust bean gum solution and 0.1 M sodium tetraborate (XLB) solution. Surface tension of one set of samples was varied by adding different amounts of SDS (sodium dodecyl sulfate) surfactant while the measurement of surface tension was performed using ADSA (axisymmetric drop shape analysis) method. The viscoelastic properties of the samples were measured using a Bohlin Gemini 200 HR (Malvern, UK) nano-rheometer with peltier plate assembly. An artificial cough machine was used to simulate human cough, generating aerosol droplets in a model trachea attached to the front of the cough machine. The size distribution and volume concentration of the droplets generated through simulated cough were measured using a laser diffraction particle sizer (SprayTec, Malvern, USA). The surface tension was found to have negligible effect on the characteristic of generated droplets within the range of this investigation. The experimental results showed a decrease in particle size as the samples changed from a viscous fluid type to a viscoelastic to an elastic solid type sample. The volume concentration also changed significantly as the viscoelasticity of the samples was varied.     

Machine learning accelerated high-throughput screening of zeolites for the selective adsorption of xylene isomers

The production of widely used polymers such as polyester currently relies upon the chemical separation of and transformation of xylene isomers. The least valuable but most prevalent isomer is meta-xylene which can be selectively transformed into the more useful and expensive para-xylene isomer using a zeolite catalyst but at a high energy cost. In this work, high-throughput screening of existing and hypothetical zeolite databases containing more than two million structures was performed, using a combination of classical simulation and deep neural network methods to identify promising materials for selective adsorption of meta-xylene. Novel anomaly detection techniques were applied to the heavily biased classification task of identifying structures with a selectivity greater than that of the best performing existing zeolite, ZSM-5 (MFI topology). Eight hypothetical zeolite topologies are found to be several orders of magnitude more selective towards meta-xylene than ZSM-5 which may provide an impetus for synthetic efforts to realise these promising materials. Moreover, the leading hypothetical frameworks identified from the screening procedure require a markedly lower operating temperature to achieve the diffusion seen in existing materials, suggesting significant energetic savings if the frameworks can be realised.

A combination of machine learning and high throughput simulation has identified several potential zeolite structures that appear to outperform the leading commercially used material and explained the key factors for high selectivity.