Development and Production of Artificial Test Swarf to Examine Wear Behavior of Running Engine Components-Part 2: Experimentally Derived Designs

In subtractive manufacturing processes, swarf, burrs or other residues are produced, which can impair the function of a tribological system (e.g., journal bearings). To prevent premature engine damage, cleanliness requirements are defined for production processes. Damaging particle tests are an experimental approach for validating these defined cleanliness requirements. This methodical approach is not yet widely used. For one, the test setup must be developed and proven for the respective application. For another, in order to carry out the tests in a systematic manner, defined test particles with properties similar to those of the contaminants encountered in reality are required. In the second part of the paper, the process chain for manufacturing artificial test swarf by micro powder injection molding (MicroPIM) is described. The size and shape of the swarf were derived from real swarf via several abstraction processes. Although certain design guidelines for MicroPIM parts could not be taken into account, the targeted manufacturing tolerances were achieved in most cases. During demolding, it became apparent that the higher ejection forces of the free-formed geometries must be taken more into account in the design of the mold. The experiments on the test setup also revealed that the artificial test swarf was unexpectedly brittle and was therefore ground up in the bearing gap without causing any substantial damage to the bearing. Thus, the artificial test swarf in its current sintered state is not a suitable substitute for micromilled swarf. However, MicroPIM could still be used to manufacture test particles in applications involving lower mechanical forces.

Detecting the Subtle Photo-Responsive Conformational Bistability of Monomeric Azobenzene Functionalized Keggin Polyoxometalates by Using Ion-Mobility Mass Spectrometry

Accurately characterizing the conformational variation of novel molecular assemblies is important but often ignored due to limited characterization methods. Herein, we reported the use of ion-mobility mass spectrometry (IMS/MS) to investigate the conformational changes of four azobenzene covalently functionalized Keggin hybrids (azo-Keggins, compounds 1–4). The as-prepared azo-Keggins showed the general molecular formula of [C₁₆H₃₆N]₄[SiW₁₁O₄₀(Si(CH₂)₃NH–CO(CH₂)_nO–C₆H₄N=NC₆H₄–R)₂] (R = H, n = 0 (1); R = NO₂, n = 0 (2); R = H, n = 5 (3); R = H, n = 10 (4)). The resultant azo-Keggins maintained stable monomeric states in the gas phase with intact molecular structures. Furthermore, the subtle photo-responsive trans-cis conformational variations of azo-Keggins were clearly revealed by the molecular shape-related collision cross-section value difference ranging from 2.44 Ų to 6.91 Ų. The longer the alkyl chains linkers were, the larger the conformational variation was. Moreover, for compounds 1 and 2, higher stability in trans-conformation can be observed, while for compounds 3 and 4, bistability can be achieved for both of them.

A New Measure to Characterize the Degree of Self-Similarity of a Shape and Its Applicability

We propose a new measure (Γ) to quantify the degree of self-similarity of a shape using branch length similarity (BLS) entropy which is defined on a simple network consisting of a single node and its branches. To investigate the properties of this measure, we computed the Γ values for 70 object groups (20 shapes in each group) in the MPEG-7 shape database and performed grouping on the values. With relatively high Γ values, identical groups had visually similar shapes. On the other hand, the identical groups with low Γ values had visually different shapes. However, the aspect of topological similarity of the shapes also warrants consideration. The shapes of statistically different groups exhibited significant visual difference from each other. Also, in order to show that the Γ can have a wide variety of applicability when properly used with other variables, we showed that the finger gestures in the (Γ, Z) space are successfully classified. Here, the Z means a correlation coefficient value between entropy profiles for gesture shapes. As shown in the applications, Γ has a strong advantage over conventional geometric measures in that it captures the geometrical and topological properties of a shape together. If we could define the BLS entropy for color, Γ could be used to characterize images expressed in RGB. We briefly discussed the problems to be solved before the applicability of Γ can be expanded to various fields.

Viscosity of Plasma as a Key Factor in Assessment of Extracellular Vesicles by Light Scattering

Extracellular vesicles (EVs) isolated from biological samples are a promising material for use in medicine and technology. However, the assessment methods that would yield repeatable concentrations, sizes and compositions of the harvested material are missing. A plausible model for the description of EV isolates has not been developed. Furthermore, the identity and genesis of EVs are still obscure and the relevant parameters have not yet been identified. The purpose of this work is to better understand the mechanisms taking place during harvesting of EVs, in particular the role of viscosity of EV suspension. The EVs were harvested from blood plasma by repeated centrifugation and washing of samples. Their size and shape were assessed by using a combination of static and dynamic light scattering. The average shape parameter of the assessed particles was found to be ρ ~ 1 (0.94–1.1 in exosome standards and 0.7–1.2 in blood plasma and EV isolates), pertaining to spherical shells (spherical vesicles). This study has estimated the value of the viscosity coefficient of the medium in blood plasma to be 1.2 mPa/s. It can be concluded that light scattering could be a plausible method for the assessment of EVs upon considering that EVs are a dynamic material with a transient identity.

EuMoBot: replicating euglenoid movement in a soft robot

Swimming is employed as a form of locomotion by many organisms in nature across a wide range of scales. Varied strategies of shape change are employed to achieve fluidic propulsion at different scales due to changes in hydrodynamics. In the case of microorganisms, the small mass, low Reynolds number and dominance of viscous forces in the medium, requires a change in shape that is non-invariant under time reversal to achieve movement. The Euglena family of unicellular flagellates evolved a characteristic type of locomotion called euglenoid movement to overcome this challenge, wherein the body undergoes a giant change in shape. It is believed that these large deformations enable the organism to move through viscous fluids and tiny spaces. The ability to drastically change the shape of the body is particularly attractive in robots designed to move through constrained spaces and cluttered environments such as through the human body for invasive medical procedures or through collapsed rubble in search of survivors. Inspired by the euglenoids, we present the design of EuMoBot, a multi-segment soft robot that replicates large body deformations to achieve locomotion. Two robots have been fabricated at different sizes operating with a constant internal volume, which exploit hyperelasticity of fluid-filled elastomeric chambers to replicate the motion of euglenoids. The smaller robot moves at a speed of body lengths per cycle (20 mm min⁻¹ or 2.2 cycles min⁻¹) while the larger one attains a speed of body lengths per cycle (4.5 mm min⁻¹ or 0.4 cycles min⁻¹). We show the potential for biomimetic soft robots employing shape change to both replicate biological motion and act as a tool for studying it. In addition, we present a quantitative method based on elliptic Fourier descriptors to characterize and compare the shape of the robot with that of its biological counterpart. Our results show a similarity in shape of 85% and indicate that this method can be applied to understand the evolution of shape in other nonlinear, dynamic soft robots where a model for the shape does not exist.

Characterizing the shape patterns of dimorphic yeast pseudohyphae

Pseudohyphal growth of the dimorphic yeast Saccharomyces cerevisiae is analysed using two-dimensional top-down binary images. The colony morphology is characterized using clustered shape primitives (CSPs), which are learned automatically from the data and thus do not require a list of predefined features or a priori knowledge of the shape. The power of CSPs is demonstrated through the classification of pseudohyphal yeast colonies known to produce different morphologies. The classifier categorizes the yeast colonies considered with an accuracy of 0.969 and standard deviation 0.041, demonstrating that CSPs capture differences in morphology, while CSPs are found to provide greater discriminatory power than spatial indices previously used to quantify pseudohyphal growth. The analysis demonstrates that CSPs provide a promising avenue for analysing morphology in high-throughput assays.