Polarization-variable emitter for terahertz time-domain spectroscopy

We report on the progress in the development of linear polarization-variable multielectrode emitters for terahertz time-domain spectroscopy. The results on its microfabrication, the finite element method modeling of appropriate bias distribution between electrodes, the finite-difference time-domain simulated spectral output, and actual experimental testing are presented. The rotation of the emitted terahertz field with linear polarization on an angle multiple of 45° can be achieved by synchronized bias and single polarizer rotations

A Semi-deterministic Wear Model Considering the Effect of Zinc Dialkyl Dithiophosphate Tribofilm

Tribochemistry plays a very important role in the behaviour of systems in tribologically loaded contacts under boundary lubrication conditions. Previous works have mainly reported contact mechanics simulations for capturing the boundary lubrication regime, but the real mechanism in which tribofilms reduce wear is still unclear. In this paper, the wear prediction capabilities of a recently published mechanochemical simulation approach (Ghanbarzadeh et al. in Tribol Int, 2014) are tested. The wear model, which involves a time- and spatially dependent coefficient of wear, was tested for two additive concentrations and three temperatures at different times, and the predictions are validated against experimental results. The experiments were conducted using a mini-traction machine in a sliding/rolling condition, and the spacer layer interferometry method was used to measure the tribofilm thickness. Wear measurements have been taken using a white-light interferometry. Good agreement is seen between simulation and experiment in terms of tribofilm thickness and wear depth predictions

Crystal plasticity simulations with representative volume element of as-build laser powder bed fusion materials

Abstract Additive manufacturing of as-build metal materials with laser powder bed fusion typically leads to the formations of various chemical phases and their corresponding microstructure types. Such microstructures have very complex shape and size anisotropic distributions due to the history of the laser heat gradients and scanning patterns. With higher complexity compared to the post-heat-treated materials, the synthetic volume reconstruction of as-build materials for accurate modelling of their mechanical properties is a serious challenge. Here, we present an example of complete workflow pipeline for such nontrivial task. It takes into account the statistical distributions of microstructures: object sizes for each phase, several shape parameters for each microstructure type, and their morphological and crystallographic orientations. In principle, each step in the pipeline, including the parameters in the crystal plasticity model, can be fine-tuned to achieve suitable correspondence between experimental and synthetic microstructures as well as between experimental stress–strain curves and simulated results. To our best knowledge, this work represents an example of the most challenging synthetic volume reconstruction for as-build additive manufacturing materials to date

Non-destructive evaluation by terahertz spectroscopy for penetration of acid solutions into epoxy resin

Epoxy resins are used as high-performance thermosetting linings to protect substrates under corrosive environments. However, in a severe corrosive chemical solution, such protective layers may degrade with long time due to penetrations of solvent and solute molecules into resin network. In this regard, the terahertz time-domain spectroscopy (THz-TDS) is a promising tool for non-destructive evaluation of the penetrant amounts due to high transparency of such plastic materials and high sensitivity to the molecular vibrations in terahertz spectral range. In this work, the complex refractive indexes n and κ of epoxy specimens were measured after immersion into sulfuric acid solutions and compared with penetrated mass fractions of water and acid ions. It was found that n and κ depended linearly with water and sulfuric acid mass fraction in specimens, and κ of sulfuric acid immersed specimens was lager at higher frequency. While the calculated Δκ agreed well with THz-TDS measurement by THz-TDS, the calculated Δn was higher than the measurement. The difference may be attributed to the water and sulfuric states in the specimen

Automatic steel labeling on certain microstructural constituents with image processing and machine learning tools

It is demonstrated that optical microscopy images of steel materials could be effectively categorized into classes on preset ferrite/pearlite-, ferrite/pearlite/bainite-, and bainite/martensite-type microstructures with image pre-processing and statistical analysis including the machine learning techniques. Though several popular classifiers were able to get the reasonable class-labeling accuracy, the random forest was virtually the best choice in terms of overall performance and usability. The present categorizing classifier could assist in choosing the appropriate pattern recognition method from our library for various steel microstructures, which we have recently reported. That is, the combination of the categorizing and pattern-recognizing methods provides a total solution for automatic quantification of a wide range of steel microstructures