Experimental and modelling studies of the transient tribological behaviour of a two-phase lubricant under complex loading conditions

The transient tribological phenomenon and premature lubricant breakdown have been widely observed in metal forming, leading to excessive friction at the contact interfaces. In this research, the transient tribological behaviour of a two-phase lubricant were studied under complex loading conditions, featuring abrupt interfacial temperature, contact load, and sliding speed changes, thus representing the severe interfacial conditions observed in warm/hot metal forming applications. The strong experimental evidence indicates that the evolution of friction was attributed to the physical diminution and chemical decomposition effects. As such, a visco-mechanochemical interactive friction model was developed to accurately predict the transient tribological behaviour of the two-phase lubricant under complex loading conditions. The new friction model exhibited close agreements between the modelling and experimental results.

Fluorescence Recognition of Anions Using a Heteroditopic Receptor: Homogenous and Two-Phase Sensing

In contrast to monotopic receptor 3, the anthracene functionalized squaramide dual-host receptor 1 is capable of selectively extracting sulfate salts, as was evidenced unambiguously by DOSY, mass spectrometry, fluorescent and ion chromatography measurements. The receptors were investigated in terms of anion and ion pair binding using the UV–vis and 1H NMR titrations method in acetonitrile. The reference anion receptor 3, lacking a crown ether unit, was found to lose the enhancement in anion binding induced by the presence of cations. Besides the ability to bind anions in an enhanced manner exhibited by ion pair receptors 2 and 4, changing the 1-aminoanthracene substituent resulted in their exhibiting a lower anion affinity than receptor 1. By using receptor 1 and adjusting the water content in organic phase it was possible to selectively detect sulfates both by “turn-off” and “turn-on” fluorescence, and to do so homogenously and under interfacial conditions. Such properties of receptor 1 have allowed the development of a new type of sensor capable of recognizing and extracting potassium sulfate from the aqueous medium across a phase boundary, resulting in an appropriate fluorescent response in the organic solution.

Numerical Study of the Effect of Workpiece Thickness on the Interfacial Behavior of a Molten Aluminum Droplet on a Zinc-coated Steel Sheet

In brazing, the interfacial conditions between the molten filler material and the solid workpiece are important, yet they cannot be observed experimentally. A two-dimensional axisymmetric simulation was conducted to analyze the behavior of a single droplet of molten aluminum on zinc-coated steel sheet as a simplified brazing process. The simulation models were verified through a comparison with experimental results in terms of bead shape, zinc distribution, and molten metal behavior. The results show that Young’s equation was not valid in explaining the wetting behavior because of the instant solidification. In this respect, the effects of the workpiece thickness and wetting angle on the bead width were negligible. Two periods of time, namely the times for the temperature difference and solidification, and their ratio (interface number) were defined to analyze the temperature behavior at the interface over time as well as the effects of workpiece thickness. The interfacial temperature behaviors tended to be divided into three regions: linear (or inversely proportional), singular, and convergence. The interface number converged to a value of one with the increase in the thickness.

Utilizing an Amino Acid Scaffold to Construct Heteroditopic Receptors Capable of Interacting with Salts under Interfacial Conditions

A 4-nitro-L-phenylalanine scaffold was used to construct effective ion pair receptors capable of binding anions in an enhanced manner with the assistance of alkali metal cations. A benzocrown ether was linked to a receptor platform via the amide function so as to support the squaramide function in anion binding and to allow all three NHs to act simultaneously. The binding properties of the receptors were determined using UV-vis, 1H NMR, 2D NMR, and DOSY spectroscopy in MeCN and in the solid state by X-ray measurements. Ion pair receptor 2 was found to interact with the most strongly with salts, and the removal of its key structural elements was shown to hinder the receptor action. The amide proton was recognized to switch from having involvement in an intramolecular hydrogen bond to interacting with anions upon complexation. Apart from carboxylates, which promote deprotonation, and other monovalent salts creating 1:1 complexes with the receptor, more complex equilibria were established upon the complexation of 2 with sulfates. Receptor 2 was shown to be capable of the extraction of ion pairs from the aqueous to organic phase and of the cation-enhanced transport chloride and sulfate anions across a bulk chloroform membrane. These features may open the door for its use in regulating ion concertation under interfacial conditions and acting as a potential drug to treat channelopathies.

Machine Learning Model to Map Tribocorrosion Regimes in Feature Space

Degradation by wear and corrosion are frequently encountered in a variety of tribosystems, including materials and tools in forming operations. The combined effect of wear and corrosion, known as tribocorrosion, can result in accelerated material degradation. Interfacial conditions can affect this degradation. Tribocorrosion maps serve the purpose of identifying operating conditions at the interface for an acceptable rate of degradation. This paper proposes a machine learning-based approach to generate tribocorrosion maps, which can be used to predict tribosystem performance. Two tribocorrosion datasets from the published literature are used. The materials have been chosen based on the wide availability of their tribocorrosion data in the literature. First, unsupervised machine learning is used to identify and label clusters from tribocorrosion data. The identified clusters are then used to train a support vector classification model. The trained support vector machine is used to generate tribocorrosion maps. The generated maps are compared with those from the literature. The general approach can be applied to create tribocorrosion maps of materials widely used in material forming.

Thermodynamic Impact of Mineral Surfaces on Amino Acid Polymerization: Aspartate Dimerization on Two-Line Ferrihydrite, Anatase, and γ-Alumina

The presence of amino acids in diverse extraterrestrial materials has suggested that amino acids are widespread in our solar system, serving as a common class of components for the chemical evolution of life. However, there are a limited number of parameters available for modeling amino acid polymerization at mineral–water interfaces, although the interfacial conditions inevitably exist on astronomical bodies with surface liquid water. Here, we present a set of extended triple-layer model parameters for aspartate (Asp) and aspartyl-aspartate (AspAsp) adsorptions on two-line ferrihydrite, anatase, and γ-alumina determined based on the experimental adsorption data. By combining the parameters with the reported thermodynamic constants for amino acid polymerization in water, we computationally demonstrate how these minerals impact the AspAsp/Asp equilibrium over a wide range of environmental conditions. It was predicted, for example, that two-line ferrihydrite strongly promotes Asp dimerization, leading to the AspAsp/Asp ratio in the adsorbed state up to 41% even from a low Asp concentration (0.1 mM) at pH 4, which is approximately 5 × 107 times higher than that attainable without mineral (8.5 × 10−6%). Our exemplified approach enables us to screen wide environmental settings for abiotic peptide synthesis from a thermodynamic perspective, thereby narrowing down the geochemical situations to be explored for life’s origin on Earth and Earth-like habitable bodies.