Structure-property and composition-property relationships for poly(ethylene terephthalate) surfaces modified by helium plasma-based ion implantation

The surfaces of untreated and helium plasma-based ion implantation (He PBII) treated poly(ethylene terephthalate) (PET) samples were characterised by reflectance colorimetry, contact angle studies and measurements of surface electrical resistance. The results were related to the structural and compositional data obtained by the authors earlier on parallel samples by XPS and Raman spectroscopy. Inverse correlations between lightness and ID/IG ratio and between chroma and ID/IG ratio were obtained, suggesting that the PBII-treated PET samples darken and their colourfulness decreases with the increase of the portion of aromatic sp2 carbon rings in the chemical structure of the modified layer. Direct correlation between water contact angle and the ID/IG ratio and inverse correlations between surface energy and ID/IG ratio and between dispersive component of surface energy and ID/IG ratio were found, reflecting that surface wettability, surface energy and its dispersive component decrease with the formation of surface structure, characterised again by enhanced portion of aromatic sp2 carbon rings. The surface electrical resistance decreased with the increase of the surface C-content determined by XPS and also with the increase of the surface concentration of conjugated double bonds, reflected by the increase of the pi-pi* shake-up satellite of the C 1s peak

Bayesian interpretation of periodograms

The usual nonparametric approach to spectral analysis is revisited within the regularization framework. Both usual and windowed periodograms are obtained as the squared modulus of the minimizer of regularized least squares criteria. Then, particular attention is paid to their interpretation within the Bayesian statistical framework. Finally, the question of unsupervised hyperparameter and window selection is addressed. It is shown that maximum likelihood solution is both formally achievable and practically useful

Quantitative three-dimensional local order analysis of nanomaterials through electron diffraction

Structure-property relationships in ordered materials have long been a core principle in materials design. However, the introduction of disorder into materials provides structural flexibility and thus access to material properties that are not attainable in conventional, ordered materials. To understand disorder-property relationships, the disorder – i.e., the local ordering principles – must be quantified. Local order can be probed experimentally by diffuse scattering. The analysis is notoriously difficult, especially if only powder samples are available. Here, we combine the advantages of three-dimensional electron diffraction – a method that allows single crystal diffraction measurements on sub-micron sized crystals – and three-dimensional difference pair distribution function analysis (3D-ΔPDF) to address this problem. In this work, we compare the 3D-ΔPDF from electron diffraction data with those obtained from neutron and x-ray experiments of yttria-stabilized zirconia (Zr0.82Y0.18O1.91) and demonstrate the reliability of the proposed approach

Unsupervised word embeddings capture latent knowledge from materials science literature.

The overwhelming majority of scientific knowledge is published as text, which is difficult to analyse by either traditional statistical analysis or modern machine learning methods. By contrast, the main source of machine-interpretable data for the materials research community has come from structured property databases1,2, which encompass only a small fraction of the knowledge present in the research literature. Beyond property values, publications contain valuable knowledge regarding the connections and relationships between data items as interpreted by the authors. To improve the identification and use of this knowledge, several studies have focused on the retrieval of information from scientific literature using supervised natural language processing3-10, which requires large hand-labelled datasets for training. Here we show that materials science knowledge present in the published literature can be efficiently encoded as information-dense word embeddings11-13 (vector representations of words) without human labelling or supervision. Without any explicit insertion of chemical knowledge, these embeddings capture complex materials science concepts such as the underlying structure of the periodic table and structure-property relationships in materials. Furthermore, we demonstrate that an unsupervised method can recommend materials for functional applications several years before their discovery. This suggests that latent knowledge regarding future discoveries is to a large extent embedded in past publications. Our findings highlight the possibility of extracting knowledge and relationships from the massive body of scientific literature in a collective manner, and point towards a generalized approach to the mining of scientific literature

Structure-Property Relationships of Bismaleimides

The purpose of this research was to control and systematically vary the network topology of bismaleimides through cure temperature and chemistry (addition of various coreactants) and subsequently attempt to determine structure-mechanical property relationships. Characterization of the bismaleimide structures by dielectric, rheological, and thermal analyses, and density measurements was subsequently correlated with mechanical properties such as modulus, yield strength, fracture energy, and stress relaxation. The model material used in this investigation was 4,4'-BismaleiMidodIphenyl methane (BMI). BMI was coreacted with either 4,4'-Methylene Dianiline (MDA), o,o'-diallyl bisphenol A (DABA) from Ciba Geigy, or Diamino Diphenyl Sulfone (DDS). Three cure paths were employed: a low- temperature cure of 140 C where chain extension should predominate, a high-temperature cure of 220 C where both chain extension and crosslinking should occur simultaneously, and a low-temperature (140 C) cure followed immediately by a high-temperature (220 C) cure where the chain extension reaction or amine addition precedes BMI homopolymerization or crosslinking. Samples of cured and postcured PMR-15 were also tested to determine the effects of postcuring on the mechanical properties. The low-temperature cure condition of BMI/MDA exhibited the highest modulus values for a given mole fraction of BMI with the modulus decreasing with decreasing concentration of BMI. The higher elastic modulus is the result of steric hindrance by unreacted BMI molecules in the glassy state. The moduli values for the high- and low/high-temperature cure conditions of BMI/MDA decreased as the amount of diamine increased. All the moduli values mimic the yield strength and density trends. For the high-temperature cure condition, the room- temperature modulus remained constant with decreasing mole fraction of BMT for the BMI/DABA and BMI/DDS systems. Postcuring PMR-15 increases the modulus over that of the cured material even though density values of cured and postcured PMR were essentially the same. Preliminary results of a continuous and intermittent stress relaxation experiment for BMI:MDA in a 2:1 molar ratio indicate that crosslinking is occurring when the sample is in the undeformed state. Computer simulation of properties such as density, glass transition temperature, and modulus for the low- temperature cure conditions of BMI/MDA and BMI/DABA were completed. The computer modeling was used to help further understand and confirm the structure characterization results. The simulations correctly predicted the trends of these properties versus mole fraction BMI and were extended to other BMI/diamine systems

Geoscience after IT: Part F. Familiarization with quantitative analysis

Numbers, measurement and calculation extend our view of the world. Statistical methods describe the properties of sets of quantitative data, and can test models (particularly the model that observed relationships arose by chance) and help us to draw conclusions. Links between spatial and quantitative methods, through coordinate geometry and matrix algebra, lead to graphical representations for visualizing and exploring relationships. Multivariate statistics tie into visualization to look at pattern among many properties

Structure-property relationships in extruded plastics foams

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Physical properties and morphology of extruded semicrystalline polymers can be significantly affected by modification and change in die design and melt viscosity of the molten polymer. Further modifications to physical properties (i.e. density and open cell fraction) of foamed material occur, following the modification of melt viscosity by melt blending of polypropylene and high density polyethylene). The main object of this research project was to carry out a systematic examination of rheological properties of polymer/gas mixture, affect of die design, polymer molecular weight (melt viscosity), and processing conditions on density, open cell fraction, cell morphology (i.e. cell size and cell size distribution) and micromorphology of polyolefin foams. Also attention was given to method of stabilisation of extruded foam, where, it was found support of the extrudated foam (by adding a specially designed die adapter to the end of the die) prior to entering the cooling tank could result not only to a specimen with uniform cross section, but also due to drop in melt temperature, the cell walls are to some extent rigidized, hence, the collapse of bubbles are limited. From commercial point of view control of cell collapse, density and open cell fraction, will make these foamed materials valuable for their filtration characteristics. Microstructural analysis of polypropylene (unfoamed state) by X-ray diffraction and Differential Scanning Calorimetry revealed 13-spherulites are only formed in skin layer, and beneath the thickness of 500 pm from the surface, the crystal structure of this polymer is only consist of B-spherulites. On the other hand, the chemical blowing agent (Hydrocerol CF-20), was found to have nucleating affect on microstructure of polypropylene, where, it has resulted in reduction of size of spherulites together with a drop in recrystallisation temperature and formation of P and a spherulites through the thickness of extrudated foam. The foregoing chemical blowing agent was found to have no significant affect on the crystal structure of the high density polyethylene