1,721,043 research outputs found
Dataset for: Semantic segmentation of pollen grain images generated from scattering patterns via deep learning
No full textThis dataset supports the publication: Grant-Jacob, James A., Praeger, Matthew, Eason, Robert W. and Ben Mills (2021). Semantic segmentation of pollen grain images generated from scattering patterns via deep learning. IOP Journal of Physics Communications
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Dataset for: Determination of urban particulates size from occluded scattering patterns using deep learning and data augmentation
No full textThis dataset supports the publication: James A. Grant-Jacob, Matthew Praeger, Matthew Loxham, Robert W. Eason and Ben Mills. Determination of size of urban particulates from occluded scattering patterns using deep learning and data augmentation. IOP Environmental Research Communications. DOI: 10.1088/2515-7620/abed94</span
Development and spatio-spectral mapping of a capillary high harmonic source
Full text linkThis work describes the development and operation of a capillary based High Harmonic Generation (HHG) system. Using this system a coherent beam of soft x-rays is generated, studied and applied. A series of experiments was then undertaken in order to deepen our knowledge of the HHG process and to optimise the performance of the source. Notable contributions made to the field are: A novel laser mode quality measuring device. (Laser mode quality strongly affects the efficiency of the capillary launch). A study of the spectral output of the system as a function of gas pressure, laser power, and laser spectral phase. An analysis technique for recovering spatially-resolved spectral information about a beam by studying the Fresnel diffraction pattern produced at an array of apertures. A study of pulse compression using cascaded quadratic nonlinearity for spectral broadening
Dataset for: The effects of water on the dielectric properties of aluminum based nanocomposites
No full textThis dataset should be used in conjunction with the journal publication;
"The effects of water on the dielectric properties of aluminum based nanocomposites"
Authors: Ian L Hosier, Matthew Praeger, Alun S. Vaughan and Steve G Swingler
in: IEEE Transactions on Nanotechnology, Vol. 16, no. 4, pp. 1-10, July 2017
The excel file contains the raw data used to generate each figure on a separate tab.
Note: The figure ExtraTGAwork.TIF is a graphic of the effects of wet and dry conditioning on water uptake. It is mentioned in the text of the paper but there was insufficient room to include it in the manuscript.
Abstract: A series of polyethylene nanocomposites was prepared utilizing aluminum nitride or alumina nano-powders with comparable morphologies. These were subsequently subjected to different conditioning regimes, namely prolonged storage in vacuum, the ambient laboratory environment or in water. The effect of filler loading and conditioning (i.e. water content) on their morphological and dielectric properties was then examined. Measurements indicated that, in the case of aluminum nitride nanocomposites, none of the conditioning regimes led to significant absorption of water and, as such, neither the dielectric properties nor the DC conductivity varied. Conversely, the alumina nanocomposites were prone to the absorption of an appreciable mass of water, which resulted in them displaying a broad dielectric relaxation, which shifted to higher frequencies, and a higher DC electrical conductivity. We ascribe these different effects to the interfacial surface chemistry present in each system and, in particular, the propensity for hydrogen bonding with water molecules diffusing through the host matrix. Technologically, the use of nanocomposites based upon systems such as aluminum nitride, in place of the commonly used metal oxides (alumina, silica, etc.), eliminates variations in dielectric properties due to absorption of environmental water without resorting to the adoption of techniques such as surface functionalization or calcination in an attempt to render nanoparticle surface chemistry hydrophobic.</span
Microscale deposition of 2D materials via laser induced backwards transfer
No full text2D materials such as graphene have great potential as the basis for novel optoelectronic devices. Typically, 2D materials are produced via chemical vapor deposition and therefore form continuous layers. Here Laser Induced Backwards Transfer (LIBT) is used to deposit pixels of 2D materials with precisely controlled size, shape and position. In LIBT, part of the laser energy that is absorbed in the donor substrate becomes kinetic energy imparted to the 2D material, causing localised transfer of 2D material onto the receiver. The capability to deposit high-quality intact 2D materials, in well-defined microscale pixels will eliminate costly and time-consuming lithographic processing.ABSTRACT (250 words for technical review)Laser Induced Backwards Transfer (LIBT)1 is a candidate for next generation additive manufacturing, especially for materials that are unsuited to more conventional methods. Broadening the range and complexity of materials that can be deposited will enable developments in material functionality e.g. for sensing applications, metamaterials and silicon photonics. Here we demonstrate LIBT as a means of achieving intact transfer of 2D materials (such as graphene and MoS2) onto a receiver substrate (which could be a silicon based electronic or photonic device). Typically, 2D materials are produced via chemical vapor deposition and form featureless, continuous layers. In LIBT, part of the laser pulse energy that is absorbed in the donor substrate becomes kinetic energy imparted to the 2D material, this causes localised detachment and transfer of the 2D material onto the receiver. Here, the transfer region is defined by beam-shaping using a Digital Micromirror Device (DMD)2 allowing precise control over the size, shape and positioning of the 2D material deposition. We use high resolution imaging to observe removal of 2D material from the donor substrate and present Raman analysis of the receiver substrate, verifying both that transfer has occurred and that the 2D materials retain their high quality and viability for end applications.[1] Feinäugle, M. et al., "Laser-induced backward transfer of nanoimprinted polymer elements," Applied Physics A 122(4), 1-5 (2016). [2] Heath, D. J. et al., "Dynamic spatial pulse shaping via a digital micromirror device for patterned laser-induced forward transfer of solid polymer films," Optical Materials Express 5(5), 1129-1136 (2015)
Laser Induced Backwards Transfer (LIBT) of graphene onto glass
No full textGraphene growth is typically optimized for uniformity over relatively large areas; however, this can place undesirable limitations on the design of graphene-based devices and can mandate the use of additional lithographic processing steps. Localized transfer of graphene can therefore offer significant benefits, permitting greater freedom in device design thereby enabling new applications. We present results obtained using a laser transfer method which is capable of localized deposition of graphene onto transparent receiver materials such as glass (using just a single fs laser pulse per deposited structure). In this method (laser induced backwards transfer, LIBT [1-3]) a pulsed laser beam is focussed through the receiving substrate and onto the donor substrate (hence the requirement for the receiver to be transparent). In this case the receiver is a microscope cover glass which is held in close contact with the donor during LIBT. The donor is a nickel coated glass slide upon which large-area monolayer graphene is transferred via the floating film technique with the aid of a PMMA support layer that is subsequently dissolved. The focused laser pulse is absorbed within the metal layer of the donor causing rapid, localized, thermal expansion (a shockwave). This ejects the graphene from the donor surface (only where the laser was focused) and transfers it to the receiver substrate. In this manner, microscale patterning of graphene on the receiver substrate is achieved.Additionally, we present details of spatial beam modulation via a digital micromirror device (DMD, [4, 5]) which allows the shape and size of the deposited graphene to be precisely, computer controlled in the micron range. This innovation could help to facilitate rapid prototyping of graphene-based devices, allowing numerous design variations to be tested quickly and without requiring the purchase of multiple, costly, lithographic masks. This work extends on previous results obtained by the authors at a laser wavelength of 800nm [6] by using an optical parametric amplifier (OPA) to generate laser light at 1650nm and additionally introduces control over laser pulse duration, allowing switching between 200fs and 1200fs pulses.The presence of graphene on a surface creates a slight change in optical reflectance and so it is often possible (although difficult) to observe the presence of localized deposits of graphene via optical microscopy. We have developed image processing methods (with contrast enhancement and image segmentation steps) that greatly simplify the identification of graphene coated regions. These methods have been evaluated using Raman microscopy and have proved to be an accurate and convenient tool (see Figure 1) which we believe may be of interest to other researchers in this field
Vacuum current emission and initiation in an LaB6 hollow cathode
No full textThis paper presents the first investigation of pre-ignition currents and the ignition process in an LaB6 hollow cathode running on krypton propellant. Vacuum and pre-ignition currents are found to be consistent with space charge limited behaviour. A novel, low power ignition strategy with the potential to reduce insert and orifice erosion is also shown
Dataset for: The effects of Hydration on the DC Breakdown Strength of Polyethylene Composites Employing Oxide and Nitride Fillers
No full textThis dataset is intended to be used in conjunction with the journal publication;
"The effects of Hydration on the DC Breakdown Strength of Polyethylene Composites Employing Oxide and Nitride Fillers"
Authors: I. L. Hosier, M. Praeger, A. S. Vaughan and S. G. Swingler
to be published in IEEE Transactions on Dielectrics and Electrical Insulation (accepted for publication 27th April 2017)
The excel file contains the raw data used to generate each figure on a seperate tab.
Abstract: Particle dispersion, water absorption/desorption and electrical breakdown behavior were studied in a range of polyethylene composites having a common matrix morphology. Three different conditioning routes (dry, ambient and wet) were used to vary the absorbed water content. Systems employing oxide fillers (silica and alumina) were found to have poor or intermediate levels of particle dispersion and could absorb/desorb significant amounts of water. Consequently, they required drying to provide breakdown strengths comparable to that of the host matrix. Systems based on calcined silica exhibited reduced water absorption and provided improved breakdown strength after ambient conditioning, despite having an identical dispersion to those utilizing untreated silica. Composites employing nitride fillers (silicon nitride and aluminum nitride) were found to have good or intermediate levels of particle dispersion. These absorbed far less water and hence provided breakdown strength values comparable to that of the host matrix following ambient conditioning. Their breakdown strength was degraded after wet conditioning with both exhibiting similar breakdown strengths despite there being a large difference in the level of particle dispersion between the two fillers. In composites based upon a hydrophobic host matrix, water absorption is largely determined by particle surface chemistry and, although the above results are presented in terms of water absorption, we suggest that changes in this characteristic can be interpreted as a proxy for changed surface chemistry. The results suggest that surface chemistry is at least as important as particle dispersion in determining the electrical breakdown strength.</span
Data supporting the publication "Single-step beam intensity and profile optimization using a 256×256 micromirror array and reinforcement learning"
No full textThe data is collated in 2 main folders. One for Figurative Data and one for Model Data. The schematic representation of the data folder structure is depicted as follows:
1. Figurative data
All figure files referenced in the publication are located in the directory: root/dataset/Figurative data/. Figures labeled in the main text as "Figure 1" through "Figure 7" correspond to the following files: Figure 1.png, Figure 2.png, Figure 3.png, Figure 4.png, Figure 5.png, Figure 6.png, and Figure 7.png. Additionally, the figure cited as "Fig S1" in the supplementary materials is available as Figure Appendix 1.png.
2. Model Data
The models utilized in the publication, labeled "flat" and "UoS," are stored in the directory: root/dataset/Model data/. For detailed instructions on reproducing the results presented in the publication, please consult the README.txt file located at root/dataset/Model data/README.txt.
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Dataset for: In-flight sensing of pollen grains via laser scattering and deep learning
No full textThis dataset supports the publication: 'In-flight sensing of pollen grains via laser scattering and deep learning' in 'IOP Engineering Research Express'.
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