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Interview with Tim Jones
No full textTim Jones, Personal Accounts Delivery Authority and NEST CEO (2007-2015) talks about the creation of a national pensions savings scheme (currently known as National Employment Savings Trust) and challenges facing the implementation
DFT Dataset for "Mechanistic Origin of Superionic Lithium Diffusion in Anion-Disordered Li6PS5X Argyrodites"
No full textThis dataset contains inputs and outputs for AIMD simulations of Li6PS5X (X=I, Cl) argyrodites, as described in the article "Mechanistic Origin of Superionic Lithium Diffusion in Anion-Disordered Li6PS5X Argyrodites" DOI:10.1021/acs.chemmater.0c03738
The dataset includes VASP (https://www.vasp.at) inputs and outputs for the full set of AIMD simulations, and for the calculation of "inherent structure trajectories" from the raw simulation trajectories.
Every `runN` directory contains:
- `INCAR`: VASP calculation settings.
- `KPOINTS`: VASP k-points settings.
- `POSCAR`: Starting structure for this MD run. For runN with N>1, this is the final structure from the preceding run, i.e. runN-1.
- `CONTCAR`: The final structure from this MD run.
- `POTCAR.spec`: Specifies the pseudopotentials used.
- `vasprun.xml.gz`: Gzipped VASP `vasprun.xml` output file.
- `XDATCAR.gz`: Gzipped VASP MD trajectory, in `XDATCAR` format.
and a `quench` subdirectory.
The `quench` subdirectories contain a series of `config_XXXX` directories. Each of these uses the corresponding timestep from the parent MD run as a starting structure for a single point geometry optimisation to obtain the corresponding intrinsic structure. Every `quench` directory also contains:
- `actual_XDATCAR.gz`: Geometries from the actual MD simulation, in VASP XDATCAR format.
- `inherent_XDATCAR.gz`: Sequence of inherent structures obtained by optimising the structures in `actual_XDATCAR.gz`, in VASP XDATCAR format.
- `frame_numbers.gz`: A list of timestep, or "frame" numbers for the configurations in `actual_XDATCAR.gz` and `inherent_XDATCAR.gz`.All data included in this dataset has been generated using the VASP DFT code
Dataset for "Continuous Production of Metal Oxide Nanoparticles via Membrane Emulsification−Precipitation"
No full textThis dataset contains for the manuscript Continuous Production of Metal Oxide Nanoparticles via Membrane Emulsification−Precipitation, including XPS and photocatalytic data.TEM (JEOL-JEM-2100 Plus) was used to characterize the TiO2 NPs. ImageJ was used to perform statistical image analysis of TEM micrographs to calculate average particle size. XRD diffraction patterns were obtained using a Bruker D8-Advance. A Raman spectrometer was used to characterize the samples (InVia, Reinshaw). The droplet size distribution of the emulsions was analysed by DLS with a detection angle of 173° (Zetasizer Nano-ZS, Malvern Instruments). The interfacial tension of the dispersed phase/continuous phase were measured using a goniometer (Dataphysics OCA20) based on the pendant drop method.30 The band gap of the TiO2 NPs was obtained by measuring the reflection spectra using a UV-vis spectrophotometer (Cary 100). X-ray photoelectron spectroscopy (XPS) was performed on a Thermo Fisher Scientific K-alpha+ spectrometer. Samples were analysed using a micro-focused monochromatic Al x-ray source (72 W) over an area of approximately 400 micrometres. Data was recorded at pass energies of 150 eV for survey scans and 40 eV for high resolution scan with 1 eV and 0.1 eV step sizes respectively. Data analysis was performed in CasaXPS using a Shirley type background and Scofield cross sections, with an energy dependence of -0.6. The specific surface area and pore size distribution were characterized by analysing the N2 adsorption and desorption isotherms obtained at 77 K using a micromeritics 3Flex equipment.
The photocatalytic activity (PCA) of TiO2 NPs was investigated using a Peschl Ultraviolet photoreactor (PhotoLAB, B400-700 Basic Batch-L) equipped with either low pressure (novaLIGHT LP30x, 2.7 W emission at 254 nm) or medium pressure (novaLIGHT TQ150 HG, 150 W broad band UV-visible emission spectrum) mercury lamps, both Heraeus Noblelight. Photocatalytic experiments were conducted with 0.1 g (low pressure lamp) and 0.05 g (medium pressure lamp) of TiO2 NPs dispersed in 700 mL (determined by reactor size) ultrapure water (MilliQ), respectively. 10 μM phenol was added as model pollutant. During irradiation the solution was magnetically stirred and maintained at 10 °C. Ten samples at equidistant time intervals were taken for 60 minutes and 120 minutes for low pressure lamp and medium pressure lamp experiments, respectively. HPLC was performed with an Agilent, series 1100 machine with a Poroshell 120 EC-C18, 2.7 μm, 4.5 x 50 mm column. Isocratic conditions used for phenol detection were 15 % acetonitrile and 85 % 5 mM phosphoric acid (pH 2.4), flow rate of 0.5 mL/min and UV detection at 220 nm, at 8 minutes retention time
Dataset for "Scale-up effects in alkali-activated soil blocks"
No full textChemical characterisation, mechanical testing and physical data describing the manufacturing process and properties of alkali-activated soil blocks.The experimental approach and methodology is fully described in the accompanying article "Scale-up effects in alkali-activated soil blocks" .For XRD (Figs. 1, 3, 4):
Powder X-ray diffraction (XRD) patterns were taken with a Bruker D8 Advance diffractometer using Cu Kα (λ = 1.54060 Å) X-radiation using a step size of 0.02 °(2θ). For the precursor soil and act-120h samples, a different Bruker D8 Advance diffractometer was used with monochromatic CuKα (λ = 1.540598 Å) X-radiation and a step size of 0.016 °(2θ). Patterns were corrected for specimen height shift by calibrating to the most intense quartz reflection (101) at 26.6 °(2θ), and normalised to the most intense reflection in each respective pattern. Phase identification was done using Bruker EVA software.
For measuring specimen mass (Fig. 7):
The mass change behaviour of the block specimens was measured after curing, and after 7 days ageing time. Average values and standard deviations were calculated for ≥4 measurements for each series.
For measuring UCS (Fig. 10):
Unconfined compressive strength (UCS) testing was done at 7 ±1 days ageing time, using a TUN600 Universal Testing Machine. At least four block specimens were tested for each series. The frogs on both sides of each block specimen were filled in with a mix of Plaster of Paris and <1.18 mm sieved sand to create a level surface.
For measuring particle density (Fig. 11):
Particle density was measured by He gas displacement using a Micromeritics Accupyc 1330. Before measurement, powder samples were heated at 150°C under vacuum for 1 hour
Dataset for "Raman solitons in waveguides with simultaneous quadratic and Kerr nonlinearities"
No full textThe dataset includes data for predictions and simulations of two-component Raman soliton propagation in Lithium Niobate nano-waveguides. Examples of frequency shift and resulting acceleration of solitons under both anomalous and normal dispersion are given each for both quadratic and cascaded Kerr soliton regimes. We provide similar data for cases of soliton collapse in both anomalous and normal dispersion. Predictions were made by treating the Raman response as a perturbation to the soliton. Simulations were done using the Split-Step Fourier method.
We also include modelled Raman response spectrum data for Lithium Niobate and silica.
Shifts in peak frequency of each soliton component are given as a function inverse soliton velocity and soliton propagation constant, calculated by Newton-Raphson method.
Data for soliton frequency shift as a function of soliton peak power is given for both Kerr and two-component solitons. These data were calculated using the semi-analytical perturbation method.The data collection methods are described in detail in the associated publication.The data is organised into folders for each figure and subfigure panels where applicable. The data is given in ".csv" format with each data column labelled with units where appropriate
Data set for "Creation of regular arrays of faceted AlN nanostructures via a combined top-down, bottom-up approach"
No full textThe original data for parts of all figures in the paper, "Creation of regular arrays of faceted AlN nanostructures via a combined top-down, bottom-up approach", both in the main text and supplementary material, is provided here. Figures 1-5, 7 (all) are all .bmp files corresponding to raw scanning electron microscopy (SEM) images. Figure 6 (all) are JPEG files and correspond to growth mechanism schematics. Figure 8.eps and Figure 8 Raw Data.csv files are the plot presented in the main text, and the raw data file corresponding to this plot respectively. Figures 9-11 Supplementary Material are all atomic force microscopy (AFM) figures before any calibration adjustments. Figure 12 Supplementary Information.eps and Figure 12 Supplementary Information Raw Data.csv are the plot and the corresponding raw data file respectively presented in the supplementary material.AlN nanostructures were fabricated and then MOVPE regrowth experiments were performed upon different regrown nanostructures. The data taken in the main text was in the form of SEM images. Other than figure 5, these were taken with a Hitachi Field-Emission S-4300 SE using a 5 kV electron beam using secondary electron detection. Figure 5 was taken with a FEI Quanta 250 variable pressure SEM, again detecting the secondary electron signal. The AFM images in the supplementary information were taken using a Bruker multimode IIIA AFM, utilising high resolution, high aspect ratio AFM tips.Some of the SEM images were modified to have different contrast and brightness levels compared to the original images taken. Also, the images were cropped to remove the bottom and a scale bar inserted in to make them more aesthetically pleasing. The AFM images in the supplementary material were calibrated to be scaled properly as the raw data was distorted to some extent.All SEM images (Figure 1-4, 7) apart from Figure 5 were taken with a Hitachi Field-Emission S-4300 SE using a 5 kV electron beam using secondary electron detection. Figure 5 was taken with a FEI Quanta 250 variable pressure SEM, detecting the secondary electron signal. Blender 2.83 was used to produce the 3-dimensional growth mechanism schematics in Figure 6. ImageJ 1.52a was used to extract quantitative data from the SEM images - this was presented in the two plots presented in the main text and supplementary information respectively (Figure 8 and Figure 12 supplementary information). The actual plotting of the data itself was performed using the Origin 8.5.1 software package. The AFM images presented in the supplementary material (Figures 9-11 supplementary material) were calibrated and analysed using the Gwyddion 2.55 software package (http://gwyddion.net/).The data is organised in order according to each of the Figures presented in the associated publication and supplementary information
Temporal Climate Impacts
No full textSpreadsheet to facilitate the calculation of time-dependent Absolute Global Warming Potential and Absolute Global Temperature Potential due to a temporally resolved (year by year) emissions inventory (CO2, CH4, other well-mixed forcers, and examples of short-life forcers). Examples and instructions are included within the spreadsheet. The spreadsheet is intended to be a tool for LCA practitioners to quickly assess whether temporal aspects of GHG results are relevant and should be reported upon.Further explanation provided in Cooper, S.J.G., R. Green, L. Hattam, M. Roeder, A. Welfle, M. McManus, "Exploring temporal aspects of climate-change effects due to bioenergy" Biomass and Bioenergy (in press).
Equations, data and parameters referenced in spreadsheet. In particular, these are consistent with IPCC AR5 (Physical science basis):
Myhre, G., D. Shindell, F.-M. Bréon, W. Collins, J. Fuglestvedt, J. Huang, D. Koch, J.-F. Lamarque, D. Lee, B. Mendoza, T. Nakajima, A. Robock, G. Stephens, T. Takemura and H. Zhang, 2013: Anthropogenic and Natural Radiative Forcing. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.The spreadsheet is best viewed in MS Excel
Dataset for "Surface-enhanced Raman Spectroscopy Facilitates the Detection of Microplastics < 1 μm in the Environment"
No full textRaw data text file output from Lumerical of the E-Field strength at 685, 785 and 885 nm modes with incident pulse of light centred at 785 nm with a span of 500 nm. The data is taken from a single plane cutting through a single pyrimidal pit of the Klarite surface structure.Finite difference time domain (FDTD) simulations were performed in Lumerical (a commercially available photonic simulation software) to gain insight into the electric-field distribution within the inverted pyramidal pits of the Klarite substrates. The material properties of the Au Klarite substrate was emulated using a Johnson & Christy model for Gold. Nine pyramidal pits were generated in the design modeller in a 3 x 3 grid with dimensional equality to the experimental Klarite. The Eulerian mesh was a cuboid FDTD simulation domain enclosing the central pit (a single unit cell). The granularity of the mesh was 8.5 nm and was selected based on a mesh sensitivity study to determine convergence and quality of results (see Supplemental section). In the cartesian basis, the z direction is normal to the surface of the Klarite; the x and y directions coincide with the plane of the Klarite surface. Periodic boundary conditions were applied in the x and y directions; simulating an infinite array of pyramidal pits. A perfectly matched layer (PML) boundary condition was applied to the upper and lower boundaries of the domain to model an open boundary.
A linearly polarised plane wave pulse of light was incident directly onto the Klarite from 0.7 µm above the surface. The spectrum of the pulse was nominally centred at 785 nm to match the experimental laser wavelength of this study and had a bandwidth of 500 nm; the amplitude of the pulse was E_0= 0.5 V/m. A planar electric field monitor was placed in the vertical cross-section of the inverted pyramid pit, perpendicular to the direction of polarisation to extract the plasmonic electric field distribution at the wavelength of the incident light. The simulations were repeated for two other wavelengths of incident light (685 nm and 885 nm) to determine the wavelength dependence of the electric field distribution.They were published in python using matplotlibText file data exported from lumerica
Dataset for "An Analytical Heat Wave Definition Based on the Impact on Buildings and Occupants"
No full textThese data support the publication "An Analytical Heat Wave Definition Based on the Impact on Buildings and Occupants". This paper provides novel methods and data for the generation of heat wave signatures for the testing of current and future resilience of buildings to extreme heat events. The main novelty of the work lies in the fact that it generates these events by considering the impact on the internal environment, where most of the heat related morbidities and mortalities occur.
Several data sets are included in this deposit to aid the use of the method in the paper and the data we have produced. This includes some data on the real homes used in the paper as well as the EnergyPlus input data files (IDF) used in the simulation. In addition, example weather files including those for the future, are included. Please see the README file for further information.Full details of the data collection method may be found in the associated manuscript.EnergyPlus input data files (IDF) and weather files (.epw) are plain text documents that may be processed with EnergyPlus (https://energyplus.net/) or EPx (https://bigladdersoftware.com/epx/) software. The formats are documented in the Input Output Reference and Auxiliary Programs documentation accompanying the software, respectively
Dataset for "The Potential for Computational IT Tools in Disaster Relief and Shelter Design"
No full textThe expanding use of IT has brought an increase in productivity to the world of business, industry and commerce. However, this is not mirrored by an equivalent growth in the use of IT by aid agencies in post-disaster situations. This data contains results from a pioneering two-stage study which tested the appetite for the increased use of computational IT tools in this sector, their level of usefulness and whether they can be practically implemented.
The data contains the results of two separate online surveys (pre-use survey and post-use survey).
The first survey was conducted with thirty aid workers across nineteen countries on their use of IT and computational tools in shelter design and provision. The data contains information about the knowledge of the aid workers in relation to building performance situation software package and tools. The key finding was that none of the participants used any building simulation tools or software packages in any of the design stages of shelter construction and the great majority of the participants identified a need for a comprehensive, easy to use and freely available shelter design tool.
The data also contains information for the second survey which involved 48 aid-workers to record their experience of using the new tools and their feedback about the shelter design tools provided to them during the study.Google Forms were used as the data collection instrument. Online surveying was adopted because the participants were in various countries. The first
the survey contained 50 questions, the second eight
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