Energetics and kinetics of Li intercalation in irradiated graphene scaffolds

In the present study we investigate the irradiation-defects hybridized graphene scaffold as one potential building material for the anode of Li-ion batteries. Designating the Wigner V22 defect as a representative, we illustrate the interplay of Li atoms with the irradiation-defects in graphene scaffolds. We examine the adsorption energetics and diffusion kinetics of Li in the vicinity of a Wigner V22 defect using density functional theory calculations. The equilibrium Li adsorption sites at the defect are identified and shown to be energetically preferable to the adsorption sites on pristine (bilayer) graphene. Meanwhile the minimum energy paths and corresponding energy barriers for Li migration at the defect are determined and computed. We find that while the defect is shown to exhibit certain trapping effects on Li motions on the graphene surface, it appears to facilitate the interlayer Li diffusion and enhance the charge capacity within its vicinity because of the reduced interlayer spacing and characteristic symmetry associated with the defect. Our results provide critical assessment for the application of irradiated graphene scaffolds in Li-ion batteries.Comment: 23 pages, 5 figure

Image analysis and statistical modelling for measurement and quality assessment of ornamental horticulture crops in glasshouses

Image analysis for ornamental crops is discussed with examples from the bedding plant industry. Feed-forward artificial neural networks are used to segment top and side view images of three contrasting species of bedding plants. The segmented images provide objective measurements of leaf and flower cover, colour, uniformity and leaf canopy height. On each imaging occasion, each pack was scored for quality by an assessor panel and it is shown that image analysis can explain 88.5%, 81.7% and 70.4% of the panel quality scores for the three species, respectively. Stereoscopy for crop height and uniformity is outlined briefly. The methods discussed here could be used for crop grading at marketing or for monitoring and assessment of growing crops within a glasshouse during all stages of production

Polyoxometalate (POM)-layered double hydroxides (LDH) composite materials: design and catalytic applications

Layered double hydroxides (LDHs) are an important large class of two-dimensional (2D) anionic lamellar materials that possess flexible modular structure, facile exchangeability of inter-lamellar guest anions and uniform distribution of metal cations in the layer. Owing to the modular accessible gallery and unique inter-lamellar chemical environment, polyoxometalates (POMs) intercalated with LDHs has shown a vast array of physical properties with applications in environment, energy, catalysis, etc. Here we describe how polyoxometalate clusters can be used as building components for the construction of systems with important catalytic properties. This review article mainly focuses on the discussion of new synthetic approaches developed recently that allow the incorporation of the element of design in the construction of a fundamentally new class of materials with pre-defined functionalities in catalytic applications. Introducing the element of design and taking control over the finally observed functionality we demonstrate the unique opportunity for engineering materials with modular properties for specific catalytic applications

Reduced hole mobility due to the presence of excited states in poly-(3-hexylthiophene)

Copyright 2007 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. This article appeared in Applied Physics Letters 93, 233306 (2008) and may be found at

Modular polyoxometalate-layered double hydroxide composites as efficient oxidative catalysts

The exploitation of intercalation techniques in the field of two-dimensional layered materials offers unique opportunities for controlling chemical reactions in confined spaces and developing nanocomposites with desired functionality. In this paper, we demonstrate the exploitation of the novel and facile ‘one-pot’ anion-exchange method for the functionalization of layered double hydroxides (LDHs). As a proof of concept, we demonstrate the intercalation of a series of polyoxometalate (POM) clusters, Na3[PW12O40]•15H2O (Na3PW12), K6[P2W18O62]•14H2O (K6P2W18), and Na9LaW10O36•32H2O (Na9LaW10) into tris(hydroxymethyl)amino-methane (Tris) modified layered double hydroxides (LDHs) under ambient conditions without the necessity of degassing CO2. Investigation of the resultant intercalated materials of Tris-LDHs-PW12 (1), Tris-LDH-P2W18 (2), and Tris-LDH-LaW10 (3) for the degradation of methylene blue (MB), rhodamine B (RB) and crystal violet (CV) has been carried out, where Tris-LDH-PW12 reveals the best performance in the presence of H2O2. Additionally, degradation of a mixture of RB, MB and CV by Tris-LDH-PW12 follows the order of CV > MB > RB, which is directly related to the designed accessible area of the interlayer space. Also, the composite can be readily recycled and reused at least ten cycles without measurable decrease of activity

Universality and correlations in individuals wandering through an online extremist space

The 'out of the blue' nature of recent terror attacks and the diversity of apparent motives, highlight the importance of understanding the online trajectories that individuals follow prior to developing high levels of extremist support. Here we show that the physics of stochastic walks, with and without temporal correlation, provides a unifying description of these online trajectories. Our unique dataset comprising all users of a global social media site, reveals universal characteristics in individuals' online lifetimes. Our accompanying theory generates analytical and numerical solutions that describe the characteristics shown by individuals that go on to develop high levels of extremist support, and those that do not. The existence of these temporal and also many-body correlations suggests that existing physics machinery can be used to quantify and perhaps mitigate the risk of future events

Dynamical patterns in individual trajectories toward extremism

Society faces a fundamental global problem of understanding which individuals are currently developing strong support for some extremist entity such as ISIS (Islamic State) -- even if they never end up doing anything in the real world. The importance of online connectivity in developing intent has been confirmed by recent case-studies of already convicted terrorists. Here we identify dynamical patterns in the online trajectories that individuals take toward developing a high level of extremist support -- specifically, for ISIS. Strong memory effects emerge among individuals whose transition is fastest, and hence may become 'out of the blue' threats in the real world. A generalization of diagrammatic expansion theory helps quantify these characteristics, including the impact of changes in geographical location, and can facilitate prediction of future risks. By quantifying the trajectories that individuals follow on their journey toward expressing high levels of pro-ISIS support -- irrespective of whether they then carry out a real-world attack or not -- our findings can help move safety debates beyond reliance on static watch-list identifiers such as ethnic background or immigration status, and/or post-fact interviews with already-convicted individuals. Given the broad commonality of social media platforms, our results likely apply quite generally: for example, even on Telegram where (like Twitter) there is no built-in group feature as in our study, individuals tend to collectively build and pass through so-called super-group accounts