RESUMO
The results of an experimental study of micro-jets produced with a gas dynamic virtual nozzle (GDVN) under the influence of an electric field are provided and discussed for the first time. The experimental study is performed with a 50% volume mixture of water and ethanol, and nitrogen focusing gas. The liquid sample and gas Reynolds numbers range from 0.09-5.4 and 0-190, respectively. The external electrode was positioned 400-500 µm downstream of the nozzle tip and an effect of electric potential between the electrode and the sample liquid from 0-7 kV was investigated. The jetting parametric space is examined as a function of operating gas and liquid flow rates, outlet chamber pressure, and an external electric field. The experimentally observed jet diameter, length and velocity ranged from 1-25 µm, 50-500 µm and 0.5-10 m/s, respectively. The jetting shape snapshots were processed automatically using purposely developed computer vision software. The velocity of the jet was calculated from the measured jet diameter and the sample flow rate. It is found that micro-jets accelerate in the direction of the applied electric field in the downstream direction at a constant acceleration as opposed to the standard GDVNs. New jetting modes were observed, where either the focusing gas or the electric forces dominate, encouraging further theoretical and numerical studies towards optimized system design. The study shows the potential to unlock a new generation of low background sample delivery for serial diffraction measurements of weakly scattering objects.
RESUMO
The purpose of the present paper is to predict the grain size of steel during the hot-rolling process. The basis represents a macroscopic simulation system that can cope with temperatures, stresses and strains of steel in a complete continuous rolling mill, including reversible pre-rolling and finishing rolling with several tenths of rolling passes. The grain size models, newly introduced in the present paper, are one-way coupled to the macro-scale calculations performed with the slice model assumption. Macroscale solution is based on a novel radial basis function collocation method. This numerical method is truly meshless by involving the space discretization in arbitrarily distributed nodes without meshing. A new efficient node generation algorithm is implemented in the present paper and demonstrated for irregular domains of the slice as they appear in different rolling passes. Multiple grain size prediction models are considered. Grain size prediction models are based on empirical relations. Austenite grain size at each rolling pass as well as the ferrite grain size at the end of rolling are predicted in this simulation. It is also shown that based on the rolling schedule, it is highly likely that recrystallization takes place at each pass throughout a continuous rolling mill. The simulation system is coded as a user-friendly computer application for industrial use based on programming language C# and an open source developer platform NET and runs on regular personal computers the computational time for a typical rolling simulation is usually less than one hour and can thus be straightforwardly used to optimize the rolling mill design in a reasonable time.
RESUMO
The purpose of this work is to determine, based on the computational model, whether a mixture of a binary liquid is capable of producing longer, thinner and faster gas-focused micro-jets, compared to the mono-constituent liquids of its components. Mixtures of water with two different alcohols, water + ethanol and water + 2-propanol, are considered. The numerical study of pre-mixed liquids is performed in the double flow focusing nozzle geometry used in sample delivery in serial femtosecond crystallography experiments. The study reveals that an optimal mixture for maximizing the jet length exists both in a water + ethanol and in a water + 2-propanol system. Additionally, the use of 2-propanol instead of ethanol results in a 34% jet length increase, while the jet diameters and velocities are similar for both mixtures. Pure ethanol and pure 2-propanol are the optimum liquids to achieve the smallest diameter and the fastest jets. However, the overall aim is to find a mixture with the longest, the smallest and the fastest jet. Based on our simulations, it appears that water + 2-propanol mixture might be slightly better than water + ethanol. This study reveals the dominant effect of liquid viscosity on the jet breakup process in a flow focusing nozzles operated under atmospheric conditions.
RESUMO
Liquid micro-jets are crucial for sample delivery of protein crystals and other macromolecular samples in serial femtosecond crystallography. When combined with MHz repetition rate sources, such as the European X-ray free-electron laser (EuXFEL) facility, it is important that the diffraction patterns are collected before the samples are damaged. This requires extremely thin and very fast jets. In this paper we first explore numerically the influence of different nozzle orifice designs on jet parameters and finally compare our simulations with the experimental data obtained for one particular design. A gas dynamic virtual nozzle (GDVN) model, based on a mixture formulation of Newtonian, compressible, two-phase flow, is numerically solved with the finite volume method and volume of fluid approach to deal with the moving boundary between the gas and liquid phases. The goal is to maximize the jet velocity and its length while minimizing the jet thickness. The design studies incorporate differently shaped nozzle orifices, including an elongated orifice with a constant diameter and an orifice with a diverging angle. These are extensions of the nozzle geometry we investigated in our previous studies. Based on these simulations it is concluded that the extension of the constant diameter channel makes a negligible contribution to the jet's length and its velocity. A change in the angle of the nozzle outlet orifice, however, has a significant effect on jet parameters. We find these kinds of simulation extremely useful for testing and optimizing novel nozzle designs.
RESUMO
Two binary biodegradable Mg-alloys and one ternary biodegradable Mg-alloy (Mg-0.3Ca, Mg-5Zn and Mg-5Zn-0.3Ca, all in wt%) were investigated. Surface-sensitive X-ray photoelectron spectroscopy analyses (XPS) of the alloy surfaces before and after immersion in simulated body fluid (SBF) were performed. The XPS analysis of the samples before the immersion in SBF revealed that the top layer of the alloy might have a non-homogeneous composition relative to the bulk. Degradation during the SBF immersion testing was monitored by measuring the evolution of H2. It was possible to evaluate the thickness of the sample degradation layers after the SBF immersion based on scanning electron microscopy (SEM) of the tilted sample. The thickness was in the order of 10-100 µm. The typical bio-corrosion products of all of the investigated alloys consisted of Mg, Ca, P and O, which suggests the formation of apatite (calcium phosphate hydroxide), magnesium hydrogen phosphate hydrate and magnesium hydroxide. The bioapplicability of the analyzed alloys with regard to surface composition and degradation kinetics is discussed.
RESUMO
This corrects the article DOI: 10.1038/srep44628.
RESUMO
Serial femtosecond crystallography requires reliable and efficient delivery of fresh crystals across the beam of an X-ray free-electron laser over the course of an experiment. We introduce a double-flow focusing nozzle to meet this challenge, with significantly reduced sample consumption, while improving jet stability over previous generations of nozzles. We demonstrate its use to determine the first room-temperature structure of RNA polymerase II at high resolution, revealing new structural details. Moreover, the double-flow focusing nozzles were successfully tested with three other protein samples and the first room temperature structure of an extradiol ring-cleaving dioxygenase was solved by utilizing the improved operation and characteristics of these devices [corrected].
