Data for: Modelling viscosity of liquid dropout near wellbore region in gas-condensate reservoirs using modern numerical approaches.

This data bank cover viscosity of the light oil known as condensate in gas condensate reservoirs. MATLAB codes are also provided as a results of this study

Code and data supporting the paper "Incremental Material Flow Analysis with Bayesian Inference"

This dataset includes data from the paper "Incremental Material Flow Analysis with Bayesian Inference", derived from real global steel flow data from Cullen et al. (2012). It also includes the code to reproduce the figures, written in Python in the form of Jupyter notebooks. A conda environment file is included to easily set up the necessary Python packages to run the notebooks

Code and data supporting the paper "Incremental Material Flow Analysis with Bayesian Inference"

This dataset includes data from the paper "Incremental Material Flow Analysis with Bayesian Inference", derived from real global steel flow data from Cullen et al. (2012). It also includes the code to reproduce the figures, written in Python in the form of Jupyter notebooks. A conda environment file is included to easily set up the necessary Python packages to run the notebooks

Results for article "Meeting the costs of decarbonising industry – the potential effects on prices and competitiveness (a case study of the UK)"

This spreadsheet contains the results for the article, "Meeting the costs of decarbonising industry – the potential effects on prices and competitiveness (a case study of the UK)". These include projected impacts for industrial process decarbonisation (costs, fuel use, residual emissions), for key years (2030, 2040, 2050), distributed in the following ways: - Directly allocated to industrial sector in which they occur - Shared between sectors in proportion to the share of GVA of each supply chain - Embodied in final products - Embodied in final products, aggregated to consumption patterns The source of the projections and the method to perform the distribution are described in detail in the associated article

Monte Carlo code, input files, and simulation outputs for contact-based collective move simulations of MOF formations (cobalt succinate)

A C++ implementation of a molecular Monte Carlo simulation with a contact-based collective move algorithm (CCMC: Contact Cluster Monte Carlo). This simulation features periodic boundary conditions. Interaction energies are defined by two-body distance/energy potentials of mean force, suitable for implicit-solvent simulations. Input files are provided for simulations of assembly in the cobalt succinate system. Inputs and outputs of production runs are provided, as these are the full datasets underlying our paper reporting the CCMC method and initial results

Dataset for "Continuous Production of Metal Oxide Nanoparticles via Membrane Emulsification−Precipitation"

This dataset contains for the manuscript Continuous Production of Metal Oxide Nanoparticles via Membrane Emulsification−Precipitation, including XPS and photocatalytic data

Dataset for "A simplified model for minor and major loop magnetic hysteresis and its application for inference of temperature in induction heated particle beds"

The dataset contains the background data for recreation or use of the results presented in Figures 2 - 7. The data supports the recent publication that demonstrated how a LangArc model can successfully fit both major and minor hysteresis loops of a bed of magnetic particles in real time using instruments that detect changes in the magnetic field strength, such as in-situ pick-up coils. The data is intelligible when cross-referenced to the respective Figure, its caption and experimental details published in the article. The data presents a full numerical representation of the results published in the article including the direct experimental data and the model fit results for the various cases. The data will support other researchers in developing their own models to fit the results of magnetic hysteresis experiments

Lightweighting of Wishbone Finite Element Analysis

This paper focuses on lightweighting of wishbone structure for ordinary 5-seated commercial vehicle. Typically, the wishbone structure is made of high carbon steel and the aim is to investigate if the composite materials, such as E-Glass/Epoxy, Carbon/Epoxy and Boron/Epoxy, can achieve the lightweighting purpose without compromising material strength. The study is carried out through finite element package (Siemen NX) with the consideration of three different loading conditions, namely, lateral braking force, vertical and longitudinal braking force. Throughout the study, it is found that both Carbon/Epoxy and Boron/Epoxy composites is able to reduce the weight of the component by 46% while maintaining the required strength

Dataset for "Increased Photocorrosion Resistance of ZnO foams Through Transition Metal Doping"

Raw data files for X-ray diffraction (XRD), high-performance liquid chromatography (HPLC), UV-Vis, inductively coupled plasma-mass spectrometry (ICPMS), X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS) and X-ray absorption near edge structure (XANES) associated with the paper "Increased Photocorrosion Resistance of ZnO foams Through Transition Metal Doping." XRD contains raw data of XRD spectra used to analyse crystallinity and crystal phase of ZnO samples. HPLC contains the raw data used to produce degradation profiles of carbamazepine when exposed to the photocatalyst. ICPMS contains the raw data collected to analyse the concentration of metal in the pollutant stream, allowing for analysis of material stability and assess stability to photocorrosion. UV-Vis contains the raw data used to analyse the band gap of the materials. XPS and UPS contains the raw data used to elucidate the band edge positions of the material. XANES includes the raw data used to analyse the near edge extended structure of the material