Abstract: In this article we study excitons and trions in fractional dimensional spaces using the model suggested by C. Palmer [ J. Phys. A: Math. Gen. 37 6987 (2004)] through variational quantum Monte Carlo. We present a direct approach for estimating the exciton binding energy and discuss the von Neumann rejection- and Metropolis sampling methods. A simple variational estimate of trions is presented which shows good agreement with previous calculations done within the fractional dimensional model presented by D. R. Herrick and F. H. Stillinger [ Phys. Rev. A 11 42 (1975) and J. Math. Phys. 18 1224 (1977)]. We explain the spatial physics of the positive and negative trions by investigating angular and inter-atomic distances. We then examine the wave function and explain the differences between the positive and negative trions with heavy holes. As applications of the fractional dimensional model we study three systems: First we apply the model to estimate the energy of the hydrogen molecular ion H2+. Then we estimate trion binding energies in GaAs-based quantum wells and we demonstrate a good agreement with other theoretical work as well as experimentally observed binding energies. Finally, we apply the results to carbon nanotubes. We find good agreement with recently observed binding energies of the positively charged trion.

Abstract: Using first-principles calculations and reactive force field molecular dynamics simulations, we study the structural properties and dynamics of a fluorine (F) atom, either adsorbed on the surface of single layer graphene (F/GE) or between the layers of AB stacked bilayer graphene (F@ bilayer graphene). It is found that the diffusion of the F atom is very different in those cases, and that the mobility of the F atom increases by about an order of magnitude when inserted between two graphene layers. The obtained diffusion constant for F/GE is twice larger than that experimentally found for gold adatom and theoretically found for C-60 molecule on graphene. Our study provides important physical insights into the dynamics of fluorine atoms between and on graphene layers and explains the mechanism behind the separation of graphite layers due to intercalation of F atoms.

Abstract: Conventional glass-ionomer cements (GICs) are popular restorative materials, but their use is limited by their relatively low mechanical strength. This paper reports an attempt to improve these materials by incorporation of 10 wt% of three different types of nanoparticles, aluminum oxide, zirconium oxide, and titanium dioxide, into two commercial GICs (ChemFil((R)) Rock and EQUIA (TM) Fil). The results indicate that the nanoparticles readily dispersed into the cement matrix by hand mixing and reduced the porosity of set cements by filling the empty spaces between the glass particles. Both cements showed no significant difference in compressive strength with added alumina, and ChemFil((R)) Rock also showed no significant difference with zirconia. By contrast, ChemFil((R)) Rock showed significantly higher compressive strength with added titania, and EQUIA (TM) Fil showed significantly higher compressive strength with both zirconia and titania. Fewer air voids were observed in all nanoparticle-containing cements and this, in turn, reduced the development of cracks within the matrix of the cements. These changes in microstructure provide a likely reason for the observed increases in compressive strength, and overall the addition of nanoparticles appears to be a promising strategy for improving the physical properties of GICs.

Abstract: Topological insulators are attracting considerable interest due to their potential for technological applications and as platforms for exploring wide-ranging fundamental science questions. In order to exploit, fine-tune, control, and manipulate the topological surface states, spectroscopic tools which can effectively probe their properties are of key importance. Here, we demonstrate that positrons provide a sensitive probe for topological states and that the associated annihilation spectrum provides a technique for characterizing these states. Firm experimental evidence for the existence of a positron surface state near Bi2Te2Se with a binding energy of E-b = 2.7 +/- 0.2 eV is presented and is confirmed by first-principles calculations. Additionally, the simulations predict a significant signal originating from annihilation with the topological surface states and show the feasibility to detect their spin texture through the use of spin-polarized positron beams.

Abstract: Quantum spin Hall (QSH) insulators with a large topologically nontrivial bulk gap are crucial for future applications of the QSH effect. Among these, group III-V monolayers and their halides, which have a chair structure (regular hexagonal framework), have been widely studied. Using first-principles calculations, we formulate a new structure model for the functionalized group III-V monolayers, which consist of rectangular GaBi-X-2 (X = I, Br, Cl) monolayers with a distorted hexagonal framework (DHF). These structures have a far lower energy than the GaBi-X-2 monolayers with a chair structure. Remarkably, the DHF GaBi-X-2 monolayers are all QSH insulators, which exhibit sizeable nontrivial band gaps ranging from 0.17 to 0.39 eV. The band gaps can be widely tuned by applying different spin-orbit coupling strengths, resulting in a distorted Dirac cone.

Abstract: Bilayer graphene can exhibit deformations such that the two graphene sheets are locally detached from each other resulting in a structure consisting of domains with different van der Waals inter-layer coupling. Here we investigate how the presence of these domains affects the transport properties of bilayer graphene. We derive analytical expressions for the transmission probability, and the corresponding conductance, across walls separating different inter-layer coupling domains. We find that the transmission can exhibit a valley-dependent layer asymmetry and that the domain walls have a considerable effect on the chiral tunnelling properties of the charge carriers. We show that transport measurements allow one to obtain the strength with which the two layers are coupled. We perform numerical calculations for systems with two domain walls and find that the availability of multiple transport channels in bilayer graphene significantly modifies the conductance dependence on inter-layer potential asymmetry.

Abstract: Superfluidity has recently been reported in double electron-hole bilayer graphene. The multiband nature of the bilayers is important because of the very small band gaps between conduction and valence bands. The long-range nature of the superfluid pairing interaction means that screening must be fully taken into account. We have carried out a systematic mean-field investigation that includes (i) contributions to screening from both intraband and interband excitations, (ii) the low-energy band structure of bilayer graphene with its small band gap and flattened Mexican-hat-like low-energy bands, (iii) the large density of states at the bottom of the bands, (iv) electron-hole pairing in the multibands, and (v) electron-hole pair transfers between the conduction and valence band condensates. We find that the superfluidity strongly modifies the intraband contributions to the screening, but that the interband contributions are unaffected. Unexpectedly, a net effect of the screening is to suppress Josephson-like pair transfers and to confine the superfluid pairing entirely to the conduction-band condensate even for very small band gaps, making the system behave similarly to a one-band superfluid.

Abstract: The dire previsions of the WHO on the so-called “post-antibiotic era” and the continuous and global rise of anti-microbial resistance, spurs our research community to find better ways to fight these threats. In light of this severe threat to human health many attempts have been made to develop efficient methods to detect antibiotic residues in different streams. The use of electrochemistry seems an inviting approach for on-site and fast monitoring. In this critical review, recent developments in the field of (bio) electro-sensing of 19-lactam antibiotics will be presented, with a focus on aptamers and molecularly imprinted polymers, the two main promises of a new generation of biosensors, yet to be fulfilled.

Abstract: Titania/silica composites with different Ti/Si ratios are synthesized via a nonconventional synthesis route. The synthesis involves non-aqueous reaction of metal alkoxides and formic acid at 75 °C in supercritical carbon dioxide. The as-prepared composite materials contain nanometer-sized anatase crystallites and amorphous silica. Large specific surface areas are obtained. The composites are evaluated in the photocatalytic degradation of phenol in aqueous medium, and in the elimination of acetaldehyde from air. The highest photocatalytic activity in both processes is achieved with a composite containing 40 wt % TiO2.

Abstract: Drought is regarded as a slow-onset natural disaster that causes inevitable damage to water resources and to farm life. Currently, crisis management is the basis of drought mitigation plans, however, thus far studies indicate that effective drought management strategies are based on risk management. As a primary tool in mitigating the impact of drought, vulnerability assessment can be used as a benchmark in drought mitigation plans and to enhance farmers ability to cope with drought. Moreover, literature pertaining to drought has focused extensively on its impact, only awarding limited attention to vulnerability assessment as a tool. Therefore, the main purpose of this paper is to develop a conceptual framework for designing a vulnerability model in order to assess farmers level of vulnerability before, during and after the onset of drought. Use of this developed drought vulnerability model would aid disaster relief workers by enhancing the adaptive capacity of farmers when facing the impacts of drought. The paper starts with the definition of vulnerability and outlines different frameworks on vulnerability developed thus far. It then identifies various approaches of vulnerability assessment and finally offers the most appropriate model. The paper concludes that the introduced model can guide drought mitigation programs in countries that are impacted the most by drought.

Abstract: This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Climate, soil, geography and regional socio-economic variables are matched with farm level data from 41,030 farms across Western Europe. We demonstrate that a median quantile regression outperforms OLS given farm level data. The results suggest that European farms are slightly more sensitive to warming than American farms with impacts from +5 to −32 % by 2100 depending on the climate scenario. Farms in Southern Europe are predicted to be particularly sensitive, suffering losses of −5 to −9 % per degree Celsius.

Abstract: The autoregressive neural networks are emerging as a powerful computational tool to solve relevant problems in classical and quantum mechanics. One of their appealing functionalities is that, after they have learned a probability distribution from a dataset, they allow exact and efficient sampling of typical system configurations. Here we employ a neural autoregressive distribution estimator (NADE) to boost Markov chain Monte Carlo (MCMC) simulations of a paradigmatic classical model of spin-glass theory, namely, the two-dimensional Edwards-Anderson Hamiltonian. We show that a NADE can be trained to accurately mimic the Boltzmann distribution using unsupervised learning from system configurations generated using standard MCMC algorithms. The trained NADE is then employed as smart proposal distribution for the Metropolis-Hastings algorithm. This allows us to perform efficient MCMC simulations, which provide unbiased results even if the expectation value corresponding to the probability distribution learned by the NADE is not exact. Notably, we implement a sequential tempering procedure, whereby a NADE trained at a higher temperature is iteratively employed as proposal distribution in a MCMC simulation run at a slightly lower temperature. This allows one to efficiently simulate the spin-glass model even in the low-temperature regime, avoiding the divergent correlation times that plague MCMC simulations driven by local-update algorithms. Furthermore, we show that the NADE-driven simulations quickly sample ground-state configurations, paving the way to their future utilization to tackle binary optimization problems.