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Dataset for Enhancing the hydrophobicity of perovskite solar cells using C18 capped CH3NH3PbI3 nanocrystals
No full textThe incorporation of C18 capped CH3NH3PbI3 nanocrystals (MAPI NCs) in perovskite solar cells is investigated. The efficiciency of the devices is measured through JV scans. Both reverse and forward scans are measured. The materials with and without MAPI NCs have been characterised and compared through UV-Vis absorption, XRD, cyclic voltammetry, SEM and AFM imaging. The hydrophobic properties of the films have been investigated using water contact angle measuremnets of the surface. Solar cells with over 10% efficiency are achieved on both standard and inverted architectures. Most importantly, the hydrophobicity of the perovskite surface is highly enhanced leading to a much higher device stability towards moisture.Data have been all collected at the University of Bath. Different techniques have been used: AFM (atomic force microscopy), Contact angles measurements, J-V (density–voltage) scans, PL (polarised light microscopy), UV-Vis, SEM (scanning electron microscopy), XRD (X-ray diffraction). All the data have been collected on multiple samples in order to perform a full conventional error analysis.Data have been processed all in the same experimental conditions and each characterisation setup has been properly calibrated before each measurement.Power conversion efficiency of solar cells has been measured using 1 Sun AM 1.5G reference spectrum
Dataset for "Alcohol induced gelation of TEMPO-oxidized cellulose nanofibril dispersions"
No full textThe data set contains ASCII files (tab delimited) for the following:
- Oscillatory frequency sweeps for OCNF dispersions in water/ethanol dispersions with alcohol content varying from 10 to 60 wt% at 10wt% steps.
- Dependence of shear storage modulus and on the ethanol concentration.
- Shear storage modulus values for OCNF hydrogels at 50 wt% of alcohol.
- Dependence of tan delta with the alcohol content on OCNF dispersions.
- Oscillatory frequency sweeps for OCNF dispersions in water/ethanol with OCNF content varying from 0.4 to 1.2 wt% at 0.2 wt% steps.
- Dependence of tan delta on the OCNF concentration for methanol, ethanol, 1- and 2- propanol.
- Dependence of storage modulus on the OCNF concentration for methanol, ethanol, 1- and 2- propanol.
- Flow curves for OCNF dispersions in water/ethanol with alcohol content varying from 00 to 60 wt% at 10wt% steps.
- SAXS curves and fits for OCNF dispersions in water/ethanol dispersions with alcohol content varying from 10 to 50 wt% at 10wt% steps.
Parameters obtained from SAXS data fitting:
- Dependence of Rmax and Rmin on ethanol concentration.
- Dependence of νRPA on ethanol concentration.
- SEM images of 0.8 wt% OCNF dispersions freeze dried and supercritically dried from methanol and ethanol.Rheological measurements were conducted on a stress-controlled Discovery Hybrid Rheometer, Model HR-3 (TA Instruments, USA) equipped with a crosshatched 20 mm parallel plate geometry over a sandblasted lower plate. Temperature was controlled via a Peltier unit (±0.1 °C). A thin layer of low viscosity silicon-oil was added to the edge of the geometry to prevent evaporation. Oscillatory frequency sweeps were conducted at strain (γ) of 0.5% covering the angular frequency of 50 to 0.01 rad/s (Fig 1 and 2 sets) . Flow curves were measured from shear rates of 0.01 to 10 1/s . All experiments were conducted at 25 °C (Fig 3 sets).
Scanning Electron Microscope (SEM) images of cellulose aqueous and alcoholic dispersions (0.8 wt%) were obtained using a JEOL JSM6480LV SEM (Jeol, USA) at 10 kV. Aqueous dispersions were freeze-dried, mounted on adhesive carbon tape and gold sputter-coated prior to imaging of the fibrils. The alcohol dispersions in methanol (100 %) or ethanol (100 %) were sliced into 2 x 2 cm squares, critical point dried from the alcohol and sputter-coated with gold (Fig 4 set).
Small-angle X-ray scattering (SAXS) measurements were conducted at the Diamond Light Source beamline I22 using a PILATUS 2 M (Dectris, Switzerland) detector. The X-ray wavelength used was 1 Å, corresponding to an energy of 12.4 keV, and the accessible q-range was 0.006 to 0.6 1/Å. Data were reduced, and solvent and capillary contributions were subtracted using the Dawn software. Experiments were conducted at room temperature (Fig 5 sets).The SAXS data (Figure 5 set) were fitted using a model of interacting rigid cylinders with elliptical cross sections and uniform scattering length density.
The fitting parameters for the form factor of the fibrils are the major and minor radii of the cross-section of the cylinders, Rmax and Rmin respectively, and the length of the fibrils, L. Polydispersity of the cross section was not modelled. The effect of interactions on the scattering was calculated using the PRISM model, with the parameter νRPA , proportional to the concentration of cylinders, describing the strength of the interactions between the cylinders (the local excluded volume radius around each site being neglected for weak interactions)
Dataset for "A Computer-Based Incentivized Food Basket Choice Tool: Presentation and Evaluation"
No full textThis study is part of a larger project funded by the European Union and involving leading universities across Europe, which the aim of understanding the drivers of nutritional choices. The project involves scientists from different disciplines such as neuroscience, psychology and economics. This particular study aims at understanding dietary choices and the link between nutrition and health. The data described here contains the variables used to produce the results in “A Computer-Based Incentivized Food Basket Choice Tool: Presentation and Evaluation” published in PLOS ONE.Data was collected at the Behavioural Laboratory at the University of Edinburgh (BLUE). The lab sessions ran from Monday 12th September to Friday 16th September 2016
Data sets for the paper "Topological Ordering and Viscosity in the Glass-Forming Ge-Se System: The Search for a Structural or Dynamical Signature of the Intermediate Phase"
No full textData sets used to prepare Figures 1 – 14 in the article entitled “Topological Ordering and Viscosity in the Glass-Forming Ge-Se System: The Search for a Structural or Dynamical Signature of the Intermediate Phase,” published in Frontiers in Materials: Glass Science. The files are labelled according to the figure numbers. The data sets were created using the methodology described in the manuscript. Each of the plots was created using Origin software (http://www.originlab.com/). The data set corresponding to a plotted curve within an Origin file can be identified by clicking on that curve. The units for each axis are given on the plots. The data sets obtained by other authors are identified in the figure captions.
The data sets correspond to measurements made on glassy samples in the GexSe(1-x) binary system for x in the range from 0 to 0.4. Figures 1 – 5 give the composition dependence of the liquidus temperature, mass density, molar volume, glass transition temperature, and non-reversing heat flow, respectively. Figures 6 – 10 give the composition dependence of the measured neutron diffraction results for the glasses and related parameters. Figure 11 shows fits of the MYEGA model to the measured viscosity data for several Ge-Se liquids. Figure 12 – 14 give the composition dependence of the fragility index, ratio of the glass transition temperature to the liquidus temperature, and viscosity at the liquidus temperature, respectively.The data sets were collected using the methods described in the submitted paper.The data sets were analysed using the methods described in the submitted paper.Figures 1 – 14 were prepared using Origin (http://www.originlab.com/). The data set corresponding to a plotted curve within an Origin file can be identified by clicking on that curve
Dataset for "A mild conditions synthesis route to produce hydrosodalite from kaolinite, compatible with extrusion processing"
No full textChemical characterisation data describing the cured products formed when reacting kaolinite precursor with sodium hydroxide solution at Na:Al ratios of 0-1.5.Fig 2 - Powder X-ray diffraction (PXRD) analysis was done to identify phases with a Bruker D8 Advance instrument using monochromatic CuKalpha1 L3 (λ = 1.540598 Å) X-radiation and a Vantec superspeed detector. A step size of 0.016⁰(2θ) and step duration of 0.3 seconds were used.
Fig 3 - Atterberg plastic limit measurements were taken for kaolinite over a range of sodium hydroxide solution concentrations, based on BS 1377-2:1990. From these data a best fit line was plotted to extrapolate the volume of solution required to reach plastic limit consistency for a given concentration. A correction was made to exclude the mass of the sodium hydroxide from the solids mass in the plastic limit calculations.
Fig 4 - Powder X-ray diffraction (PXRD) analysis was done to identify phases with a Bruker D8 Advance instrument using monochromatic CuKalpha1 L3 (λ = 1.540598 Å) X-radiation and a Vantec superspeed detector. A step size of 0.016⁰(2θ) and step duration of 0.3 seconds were used.
Fig 5 - Powder X-ray diffraction (PXRD) analysis was done to identify phases with a Bruker D8 Advance instrument using monochromatic CuKalpha1 L3 (λ = 1.540598 Å) X-radiation and a Vantec superspeed detector. A step size of 0.016⁰(2θ) and step duration of 0.3 seconds were used.
Fig 7 - Thermogravimetric analysis (TGA) was done to characterise thermal behaviour, using a Setaram Setsys Evolution TGA over a range of 30 to 1000 °C at a heating rate of 10 °C/minute. An air atmosphere was used, with a flow rate of 20 ml/minute. A connected mass spectrometer was used (Pfeiffer Omni) to identify whether evolved gas species contained OH, H2O, CO or CO2.
Fig 8 and Fig 9 - Magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectra were measured for 27Al and 29Si to characterise coordination states, using a Varian VNMRS in direct excitation. Standards used were 1M aq. Al(NO3)3 for 27Al and tetramethylsilane for 29Si. Spin rates used were 12 kHz for 27Al and 6 kHz for 29Si, and frequencies used were 104.199 kHz for 27Al and 79.435 MHz for 29Si. Sample holders were 4mm width for 27Al and 6mm width for 29Si.
Fig 10 - Fourier Transform Infrared Spectroscopy (FTIR) was done to characterise molecular bonding, using a Perkin-Elmer Frontier with a diamond Attenuated Total Reflectance (ATR) head. Spectra were collected over a range of 4000-600 cm-1 using a resolution of 4cm-1 and 5 scans per spectrum.Fig 2 - Phase identification was done using Bruker EVA software.
Fig 5 - Le Bail extractions and Rietveld refinements of the structure were performed using JANA 2006 and the Cheary Coelho fundamental approach for XRD profile parameters.
Fig 10 - Corrections were made for ATR and background using Perkin-Elmer Spectrum software.
Fig 11 - To understand how the Na:Al molar ratio affected the reaction of kaolinite to form a hydrosodalite, the proportion of kaolinite consumed was estimated using PXRD, TGA and 29SI MAS-NMR. For PXRD, Rietveld refinement was used as already described. For TGA, in the dTG spectrum (plotted in %mass loss / minute to normalise between samples), the peak attributed to the dehydroxylation of kaolinite was integrated. This peak area was then expressed as an area fraction of the equivalent peak in the dTG spectrum for the starting kaolinite precursor. The area fraction was then assumed as equivalent to proportion of kaolinite remaining in the sample. For 29Si MAS-NMR, peaks corresponding to kaolinite and hydrosodalite were integrated (deconvoluted as required when overlapping). The area fraction of the kaolinite peak from the total peak area in a given sample’s spectrum was assumed as equivalent to phase proportion, since 29Si is a spin-half nucleus and does not suffer quadrupolar effects. A Lorentzian profile was used for deconvolution as it gave a better fit to the measured curves than a Gaussian profile
Postprandial metabolism and appetite do not differ between lean adults that eat breakfast or morning fast for 6 weeks-dataset
No full textWe present data collected as part of a randomised controlled trial to establish if daily breakfast consumption or fasting until noon modifies the acute metabolic and appetitive responses to a fixed breakfast and ad libitum lunch. The dataset contains measurements of participants' food intake, appetite regulatory hormones and metabolic responses throughout a laboratory testing day before and after a sustained period of either daily breakfast consumption or morning fasting.Data collection methods are outlined in the manuscript and protocol paper (Betts et al, 2011, Trials) with additional information relating to the dataset included in the readme file.
Using a parallel group design, 31 healthy lean men and women (22-56y) were randomly assigned to 6-wk of consuming ≥700 kcal of self-selected items before 1100 or remaining fasted (0 kcal) until 1200 daily. Following 48h of diet and physical activity standardization, we examined metabolic and appetite responses to a standardized breakfast and ad libitum lunch before and after the intervention.Data was analyzed using 3 and 2-way ANCOVA
Dataset for Radio Science "Lower ionosphere effects on narrowband VLF transmission propagation: fast variabilities and frequency dependence"
No full textThe data are processed from electric field recordings from an array network and shows the disturbance on a VLF (very low frequency) transmission attributed to lower ionospheric electrical properties.
The micro-second time resolution received transmission (filtered and frequency shifted to baseband) averaged across the receivers in the network are contained in a MatLab binary (.mat) file. The disturbance on the transmitted signal is obtained by comparing to a simulated transmission. The MatLab scripts to perform this processing are provided.The array network and experiment details are described in the 2013 Journal of Geophysical Research: Atmospheres paper, ‘Mapping the radio sky with an interferometric network of low-frequency radio receivers’, by Mezentsev and Füllekrug (section 3).The processing to obtain the VLF transmission disturbance is described in the 2018 Radio Science paper, ‘Lower ionosphere effects on narrowband VLF transmission propagation: fast variabilities and frequency dependence’, by Koh et al
Dataset for "Understanding heat driven gelation of anionic cellulose nanofibrils: Combining Saturation Transfer Difference (STD) NMR, Small Angle X-ray Scattering (SAXS) and rheology"
No full textThis dataset contains the data underlying the figures in the paper "Understanding heat driven gelation of anionic cellulose nanofibrils: Combining Saturation Transfer Difference (STD) NMR, Small Angle X-ray Scattering (SAXS) and rheology". The data for figure 4 (SAXS) is given as four different data files: Figure 4(a) Oxidised cellulose nanofibrils (OCNF) at 25 °C and OCNF at 25°C after annealing at 80°C and Figure 4(b) cationic cellulose nanofibrils (CCNF) at 25 °C and CCNF at 25°C after annealing at 80°C as explained in the materials and methods of the main manuscript. In a similar fashion, the Fig. ESI3 and Fig. ESI6 files contain the data underlying figures 3 and 6 of the electronic supplementary information.Data collection, materials and methods are listed in the associated manuscript
Quantile Regression Ensemble Summer Year (QRESY)
No full textThe zip file contain 4 datasets in csv format. Each of them correspond to weather files of one hot summer year hourly data based on the weather observed over 40 (basis) years, 1974 - 2013. Two are the so-called probabilistic design summer years (PDSY) for the cities of London (UK) and Joao Pessoa (Brazil). The PDSY uses an overheating metric that is based on the number of hours in which the temperature is above a certain threshold when a building is occupied. Then, PDSY is created by selecting an entire year which contains the third hottest mean based on this overheating metric. PDSY is currently used in the UK as reference of warm summers. However it is the first time that a PDSY is created for Brazil. The other two weather files correspond to the new quantile ensemble regression summer year (QRESY) also aiming to represent hot summers both for London and Joao Pessoa. QRESY is created by combining observed summer extreme temperatures. This is done by endowing higher weights to quantiles away from the median for ensembles within upper quantiles. At the same time, it increases the importance of quantiles near to the median for combining lower quantiles.The Quantile Regression Ensemble Summer Year (QRESY) creation process starts by collecting hourly weather data over a long period. Typically, weather files attempt to be representative of periods around 20-40 years, and here we do the same, however much longer periods could be used. The existence, variables and quality of hourly weather data varies depending on the location. The variables usually include temperature, atmospheric pressure, cloud cover, wind speed and wind direction, precipitation, etc.For the QRESY process, preprocessing of this data is required to ensure it contains no long sequences of missing data. If large amount of data are missing in any of the variables, the whole year is removed from the analysis. At this point it is also necessary to decide the target level of extreme weather to work with. That is, to fix the quantile level for the subsequent construction of the Quantile Regression models depending on the distance to the median (quantile 50, Q50). Running a Quantile Regression model for every year under analysis is an ``embarrassingly parallel'' problem, as it is straightforward to separate the problem into a number of parallel tasks and the code run on a parallel machine. The set of regressions is combined in a unique year of hourly data. This is done by endowing higher weights to quantiles away from Q50 for ensembles within upper quantiles. At the same time, it increases the importance of quantiles near to Q50 for combining lower quantiles. The idea being to focus on explaining critical phases of summer temperatures. Each ensemble is thereby made over the predictors of a number of regression models corresponding to each of the years in the database. The ensemble parameters can be tuned by cross-validation over random partitions of the data into training and test summer periods
Örenäs Research Group: survey for GPs
No full textData from an online questionnaire that investigated the health system factors potentially influencing PCPs’ referral decision-making when consulting with patients who may have cancer, and how these vary between European countries.The survey was conducted using an online form. For full details of the methodology, please see the corresponding manuscript.The spreadsheet is in Microsoft Excel 2016 format
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