Dynamics and structure of self-generated magnetics fields on solids following high contrast, high intensity laser irradiation

The dynamics of self-generated magnetic B-fields produced following the interaction of a high contrast, high intensity (I > 10¹⁹W cm^-2) laser beam with thin (3 μm thick) solid (Al or Au) targets is investigated experimentally and numerically. Two main sources drive the growth of B-fields on the target surfaces. B-fields are first driven by laser-generated hot electron currents that relax over ∼10-20 ps. Over longer timescales, the hydrodynamic expansion of the bulk of the target into vacuum also generates B-field induced by non-collinear gradients of density and temperature. The laser irradiation of the target front side strongly localizes the energy deposition at the target front, in contrast to the target rear side, which is heated by fast electrons over a much larger area. This induces an asymmetry in the hydrodynamic expansion between the front and rear target surfaces, and consequently the associated B-fields are found strongly asymmetric. The sole long-lasting (>30 ps) B-fields are the ones growing on the target front surface, where they remain of extremely high strength (∼8-10 MG). These B-fields have been recently put by us in practical use for focusing laser-accelerated protons [B. Albertazzi et al., Rev. Sci. Instrum. 86, 043502 (2015)]; here we analyze in detail their dynamics and structure.

Directed self-assembly of nanorod networks: bringing the top down to the bottom up

Self-assembled electrodeposited nanorod materials have been shown to offer an exciting landscape for a wide array of research ranging from nanophotonics through to biosening and magnetics. However, until now, the scope for site-specific preparation of the nanorods on wafers is limited to local area definition. Further there is little or no lateral control of nanorod height. In this work we present a scalable method for controlling the growth of the nanorods in the vertical direction as well as their lateral position. A focused ion beam (FIB) pre-patterns the Au cathode layer prior to the creation of the Anodized Aluminium Oxide (AAO) template on top. When the pre-patterning is of the same dimension to the pore spacing of the AAO template, lines of single nanorods are successfully grown. Further, for sub-200 nm wide features a relationship between the nanorod height and distance from non-patterned cathode can be seen to follow a quadratic growth rate obeying Faradays law of electrodeposition. This facilitates lateral control of nanorod height combined with localised growth of the nanorods.

First report of the use of a saxitoxin-protein conjugate to develop a DNA aptamer to a small molecule toxin

Saxitoxin (STX) is a low molecular weight neurotoxin mainly produced by certain marine dinoflagellates that, along with its family of similarly related paralytic shellfish toxins, may cause the potentially fatal intoxication known as paralytic shellfish poisoning. Illness and fatality rates are low due to the effective monitoring programs that determine when toxins exceed the established regulatory action level and effectuate shellfish harvesting closures accordingly. Such monitoring programs rely on the ability to rapidly screen large volumes of samples. Many of the screening assays currently available employ antibodies or live animals. This research focused on developing an analytical recognition element that would eliminate the challenges associated with the limited availability of antibodies and the use of animals. Here we report the discovery of a DNA aptamer that targets STX. Concentration-dependent and selective binding of the aptamer to STX was determined using a surface plasmon resonance sensor. Not only does this work represent the first reported aptamer to STX, but also the first aptamer to any marine biotoxin. A novel strategy of using a toxin-protein conjugate for DNA aptamer selection was successfully implemented to overcome the challenges associated with aptamer selection to small molecules. Taking advantage of such an approach could lead to increased diversity and accessibility of aptamers to low molecular weight toxins, which could then be incorporated as analytical recognition elements in diagnostic assays for foodborne toxin detection. The selected STX aptamer sequence is provided here, making it available to any investigator for use in assay development for the detection of STX.

MALTS: A Tool to Simulate Lorentz Transmission Electron Microscopy From Micromagnetic Simulations

Here we describe the development of the MALTS software which is a generalized tool that simulates Lorentz Transmission Electron Microscopy (LTEM) contrast of magnetic nanostructures. Complex magnetic nanostructures typically have multiple stable domain structures. MALTS works in conjunction with the open access micromagnetic software Object Oriented Micromagnetic Framework or MuMax. Magnetically stable trial magnetization states of the object of interest are input into MALTS and simulated LTEM images are output. MALTS computes the magnetic and electric phases accrued by the transmitted electrons via the Aharonov-Bohm expressions. Transfer and envelope functions are used to simulate the progression of the electron wave through the microscope lenses. The final contrast image due to these effects is determined by Fourier Optics. Similar approaches have been used previously for simulations of specific cases of LTEM contrast. The novelty here is the integration with micromagnetic codes via a simple user interface enabling the computation of the contrast from any structure. The output from MALTS is in good agreement with both experimental data and published LTEM simulations. A widely-available generalized code for the analysis of Lorentz contrast is a much needed step towards the use of LTEM as a standardized laboratory technique.

Integrating geophysical data and upscaling techniques to support regional groundwater flow modelling: A practical example of the Lagan Valley, Northern Ireland

When studying heterogeneous aquifer systems, especially at regional scale, a degree of generalization is anticipated. This can be due to sparse sampling regimes, complex depositional environments or lack of accessibility to measure the subsurface. This can lead to an inaccurate conceptualization which can be detrimental when applied to groundwater flow models. It is important that numerical models are based on observed and accurate geological information and do not rely on the distribution of artificial aquifer properties. This can still be problematic as data will be modelled at a different scale to which it was collected. It is proposed here that integrating geophysics and upscaling techniques can assist in a more realistic and deterministic groundwater flow model. In this study, the sedimentary aquifer of the Lagan Valley in Northern Ireland is chosen due to intruding sub-vertical dolerite dykes. These dykes are of a lower permeability than the sandstone aquifer. The use of airborne magnetics allows the delineation of heterogeneities, confirmed by field analysis. Permeability measured at the field scale is then upscaled to different levels using a correlation with the geophysical data, creating equivalent parameters that can be directly imported into numerical groundwater flow models. These parameters include directional equivalent permeabilities and anisotropy. Several stages of upscaling are modelled in finite element. Initial modelling is providing promising results, especially at the intermediate scale, suggesting an accurate distribution of aquifer properties. This deterministic based methodology is being expanded to include stochastic methods of obtaining heterogeneity location based on airborne geophysical data. This is through the Direct Sample method of Multiple-Point Statistics (MPS). This method uses the magnetics as a training image to computationally determine a probabilistic occurrence of heterogeneity. There is also a need to apply the method to alternate geological contexts where the heterogeneity is of a higher permeability than the host rock.

Integrating Multiple Point Statistics with Aerial Geophysical Data to assist Groundwater Flow Models

The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively ‘noisy’ magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.

Air pollutant contamination and acidification of surface waters in the North York Moors, UK: Multi-proxy evidence from the sediments of a moorland pool

Despite the extensive geographical range of palaeolimnological studies designed to assess the extent of surface water acidification in the United Kingdom during the 1980s, little attention was paid to the status of surface waters in the North York Moors (NYM). In this paper, we present sediment core data from a moorland pool in the NYM that provide a record of air pollution contamination and surface water acidification. The 41-cm-long core was divided into three lithostratigraphic units. The lower two comprise peaty soils and peats, respectively, that date to between approximately 8080 and 6740 cal. BP. The uppermost unit comprises peaty lake muds dating from between approximately ad 1790 and the present day (ad 2006). The lower two units contain pollen dominated by forest taxa, whereas the uppermost unit contains pollen indicative of open landscape conditions similar to those of the present. Heavy metal, spheroidal carbonaceous particle, mineral magnetics and stable isotope analysis of the upper sediments show clear evidence of contamination by air pollutants derived from fossil-fuel combustion over the last c. 150years, and diatom analysis indicates that the naturally acidic pool became more acidic during the 20th century. We conclude that the exceptionally acidic surface waters of the pool at present (pH=c. 4.1) are the result of a long history of air pollution and not because of naturally acidic local conditions. We argue that the highly acidic surface waters elsewhere in the NYM are similarly acidified and that the lack of evidence of significant recovery from acidification, despite major reductions in the emissions of acidic gases that have taken place over the last c. 30years, indicates the continuing influence of pollutant sulphur stored in catchment peats, a legacy of over 150years of acid deposition.

Compositional data-driven alternatives to single geochemical component maps

Conventional practice in Regional Geochemistry includes as a final step of any geochemical campaign the generation of a series of maps, to show the spatial distribution of each of the components considered. Such maps, though necessary, do not comply with the compositional, relative nature of the data, which unfortunately make any conclusion based on them sensitive
to spurious correlation problems. This is one of the reasons why these maps are never interpreted isolated. This contribution aims at gathering a series of statistical methods to produce individual maps of multiplicative combinations of components (logcontrasts), much in the flavor of equilibrium constants, which are designed on purpose to capture certain aspects of the data.
We distinguish between supervised and unsupervised methods, where the first require an external, non-compositional variable (besides the compositional geochemical information) available in an analogous training set. This external variable can be a quantity (soil density, collocated magnetics, collocated ratio of Th/U spectral gamma counts, proportion of clay particle fraction, etc) or a category (rock type, land use type, etc). In the supervised methods, a regression-like model between the external variable and the geochemical composition is derived in the training set, and then this model is mapped on the whole region. This case is illustrated with the Tellus dataset, covering Northern Ireland at a density of 1 soil sample per 2 square km, where we map the presence of blanket peat and the underlying geology. The unsupervised methods considered include principal components and principal balances
(Pawlowsky-Glahn et al., CoDaWork2013), i.e. logcontrasts of the data that are devised to capture very large variability or else be quasi-constant. Using the Tellus dataset again, it is found that geological features are highlighted by the quasi-constant ratios Hf/Nb and their ratio against SiO2; Rb/K2O and Zr/Na2O and the balance between these two groups of two variables; the balance of Al2O3 and TiO2 vs. MgO; or the balance of Cr, Ni and Co vs. V and Fe2O3. The largest variability appears to be related to the presence/absence of peat.