Leaching of ilmenite to produce titanium based materials: a review

Naturally available ilmenite mineral is being used as a starting material to produce titanium based products that have wide applications. Transformation of ilmenite to different titanium based materials by strong and weak acid, and base digestion, is discussed. Effects of temperature, concentration of acid/base, reaction time on dissolution of ilmenite are extensively reviewed. Characterization of the starting materials, intermediates and the products by x-ray diffraction, thermogravimetry, brunauer–emmett–teller surface area analysis, and scanning electron microscopy are presented. Further, advantages and disadvantages associated with the digestion methods are discussed.

One-bath one-step dyeing of polyester/cotton (PC) blends fabric with disperse dyes after acetylation of cotton

Aiming at the classic problem of dyeing of polyester–cotton blended fabric one-bath one-step dyeing of PC blends with disperse dye after surface modification of cotton were studied. Surface modification of cotton was carried out using fibrous acetylation methods. The optimum value for surface modification was obtained with a concentration of acetylation agent 16% and time of reaction 2.5 h, gave a percent acetylation of 34. Surface chemistry and thermal decomposition were studied by using FTIR spectra and TGA. The tear strength crease recovery, pilling and abrasion resistance were evaluated. The experiment result of dyeing showed that the optimum value was obtained with dye concentration above 1% at a temperature of 120 °C warp tensile strength decreased by 12% and weft tensile strength was decreased by 9% from the control half-bleached fabric. Results of this study showed that one-step one bath dyed modified PC blend with disperse dye fabric presents good fastness property and color strength values compared with conventional two-bath dyed fabric.

Dissolution behaviour and imageability of ternary borate glasses for use in geniculate artery embolization

Sixteen borate glass compositions comprising K2O and SrO were screened, using a design of mixtures approach, to model compositional effects on dissolution, CT imageability, and MRI relaxivity (R2). Based on the characteristics of each network, together with dose determination and toxicological risk, the composition identified as BKSA16 was selected as a preferred composition for pre-clinical evaluations related to geniculate artery embolization (GAE). Accordingly, BKSA16 particles were subjected to a flame spheroidization process and recharacterized, including the evaluation of residual mass at 72 h in physiologically representative media along with clinical determinations of suspension time (ease of use). For both the irregular particles and microspheres residual mass was present at 72 h in physiologically representative media. Additionally, both the microspheres and irregular particles achieved suspension times deemed to be acceptable for clinical use. The collective data confirms that BKSA16 microspheres have a range of beneficial features (specifically both degradable and imageable) suited to GAE.

The effect of different hydration media on magnesia

This paper discusses the rate of hydration of magnesia (CCM1 and CCM2) during the formation of magnesium hydroxide with magnesium acetate and distilled water. The influence of magnesium acetate and the reactivity of the two types of caustic calcined magnesia were studied by thermogravimetric analysis, differential scanning calorimetry, mass spectrometry, particle size detection and pH. Also, both citric acid and acetic acid test were done to measure the reactivity of magnesium oxide powder. The results indicate that the hydration rate of both oxides in magnesium acetate system are vigorously exothermic compared to the water system. The study shows mechanistically that magnesium acetate enhanced the degree of hydration of magnesium oxide due to the presence of acetate ions and Mg2+ ions when it compared to water. Mathematical models confirm the findings.

Autofluorescence of stingray skeletal cartilage: hyperspectral imaging as a tool for histological characterization

Tessellated cartilage is a distinctive composite tissue forming the bulk of the skeleton of cartilaginous fishes (e.g. sharks and rays), built from unmineralized cartilage covered at the surface by a thin layer of mineralized tiles called tesserae. The finescale structure and composition of elasmobranch tessellated cartilage has largely been investigated with electron microscopy, micro-computed tomography and histology, but many aspects of tissue structure and composition remain uncharacterized. In our study, we demonstrate that the tessellated cartilage of a stingray exhibits a strong and diverse autofluorescence, a native property of the tissue which can be harnessed as an effective label-free imaging technique. The autofluorescence signal was excited using a broad range of wavelengths in confocal and light sheet microscopy, comparing several sample preparations (fresh; demineralized and paraffin-embedded; non-demineralized and plastic-embedded) and imaging the tissue at different scales. Autofluorescence varied with sample preparation with the signal in both plastic- and paraffin-embedded samples strong enough to allow visualization of finescale (≥ 1 μm) cellular and matrix structures, such as cell nuclei and current and former mineralization fronts, identifiable by globular mineralized tissue. A defined pericellular matrix (PCM) surrounding chondrocytes was also discernible, described here for the first time in elasmobranchs. The presence of a PCM suggests similarities with mammalian cartilage regarding how chondrocytes interact with their environment, the PCM in mammals acting as a transducer for biomechanical and biochemical signals. A posterior analysis of hyperspectral images by an MCR-ALS unmixing algorithm allowed identification of several distinct fluorescence signatures associated to specific regions in the tissue. Some fluorescence signatures identified could be correlated with collagen type II, the most abundant structural molecule of cartilage. Other fluorescence signatures, however, remained unidentified, spotlighting tissue regions that deserve deeper characterization and suggesting the presence of molecules still unidentified in elasmobranch skeletal cartilage. Our results show that autofluorescence can be a powerful exploratory imaging tool for characterizing less-studied skeletal tissues, such as tessellated cartilage. The images obtained are largely comparable with more commonly used techniques, but without the need for complicated sample preparations or external staining reagents standard in histology and electron microscopy (TEM, SEM).

Simulation study of monolithic MoSe2/CIGS tandem solar cells

This article aims to study MoSe2/CIGS tandem solar cells employing SCAPS-1D computational package based on ant colony algorithm. The simulation of Monolithic MoSe2/CIGS tandem solar cells has been implemented successfully by employing the Matlab/Simulink. The power output of the Monolithic MoSe2/CIGS tandem modules increases by the solar irradiations during the first few days of operation. The J–V characteristic and average daily energy production throughout the year has been calculated. The results show 80.71% FF and 19.29% efficiency of the solar cell. The other parameter for the MoSe2/CIGS tandem solar cell are Voc = 0.62 V; Jsc = 38.69 mA/cm2.

The search for new materials and the role of novel processing routes

Throughout human history, most further developments or new achievements were accompanied by new materials or new processes that enabled the technologic progress. With concrete devices and applications in mind, synthesis and subsequent treatment of materials naturally went along with the progress. The aim of the underlying article is to spot the role of optimization, of discovery, of trial-and-error approaches, of fundamentals and curiosity driven design and development. In a consecutive examination, five missions addressing the challenges facing our world (identified by the European Council) will be cross linked with seven topical areas from materials science defined by the European Materials Research Society. The scope of this examination is to identify approaches and methods to further develop and innovate materials which form the basis of the anticipated solutions.

Comparing electrochemical analysis and particle induced X-ray emission measurements of Prussian Blue Analogue deposits

Prussian Blue Analogues are of major interest for their use in alternative battery technologies due to their charge storing ability with a long life cycle. In this work the Prussian Blue Analogue nickel hexacyanoferrate (Ni-HCF) was produced using an all electrochemical method. Creating charge storing materials with electrochemical processes provides a new approach to the development of battery-like materials. These methods have not been commonly employed because the charge storing material yield is not directly known. The charge storage of the Ni-HCF was characterized with two different methods which provided a measure of the electrochemically active Fe present. These were then compared with the Particle Induced X-ray Emission (PIXE) method which measured the total amount of Fe present. By comparing the electrochemical measurement of active Fe to the total Fe as measured by PIXE, the percentage of material that is active in the charge storage was determined. This enables an independent calculation of the specific charge capacity of the material for comparison to other battery technologies.

Big data and machine learning for materials science

Herein, we review aspects of leading-edge research and innovation in materials science that exploit big data and machine learning (ML), two computer science concepts that combine to yield computational intelligence. ML can accelerate the solution of intricate chemical problems and even solve problems that otherwise would not be tractable. However, the potential benefits of ML come at the cost of big data production; that is, the algorithms demand large volumes of data of various natures and from different sources, from material properties to sensor data. In the survey, we propose a roadmap for future developments with emphasis on computer-aided discovery of new materials and analysis of chemical sensing compounds, both prominent research fields for ML in the context of materials science. In addition to providing an overview of recent advances, we elaborate upon the conceptual and practical limitations of big data and ML applied to materials science, outlining processes, discussing pitfalls, and reviewing cases of success and failure.