Pore Locations Research Articles

An Insight into the Mechanical Properties of Unidirectional C/C Composites Considering the Effect of Pore Microstructures via Numerical Calculation.

Pores are common defects generated during fabrication, which restrict the application of carbon/carbon (C/C) composites. To quantitatively understand the effects of pores on mechanical strength, this paper proposes a representative volume element model of unidirectional (UD) C/C composites based on the finite element method. The Hashin criterion and exponential degraded rule are used as the failure initiation and evolution of pyrolytic carbon matrices, respectively. Interfacial zones are characterized using the cohesive constitutive. At the same time, periodic boundary conditions are employed to study transverse tensile, compressive, and shear deformations of UD C/C composites. Predicted results are compared with the experimental results, which shows that the proposed model can effectively simulate the transverse mechanical behaviors of UD C/C composites. Based on this model, the effects of microstructural parameters including porosity, pore locations, the distance between two pores, pore clustering, and pore shapes on the mechanical strength are investigated. The results show that porosity markedly reduces the strength as porosity increases. When the porosity increases from 4.59% to 12.5%, the transverse tensile, compressive, and shear strengths decrease by 35.91%, 37.52%, and 30.76%, respectively. Pore locations, the distance between two pores, and pore clustering have little effect on the shear strength of UD C/C composites. For pore shapes, irregular pores more easily lead to stress concentration and matrix failure, which greatly depresses the bearing capacity of UD C/C composites.

A VMD-BP Model to Predict Laser Welding Keyhole-Induced Pore Defect in Al Butt-Lap Joint.

The detection of keyhole-induced pore positions is a critical procedure for assessing laser welding quality. Considering the detection error due to pore migration and noise interference, this research proposes a regional prediction model based on the time-frequency-domain features of the laser plume. The original plume signal was separated into several signal segments to construct the morphological sequences. To suppress the mode mixing caused by environmental noise, variational modal decomposition (VMD) was utilized to process the signals. The time-frequency features extracted from the decomposed signals were acquired as the input of a backpropagation (BP) neural network to predict the pore locations. To reduce the prediction error caused by pore migration, the effect of the length of the signal segments on the prediction accuracy was investigated. The results show that the optimal signal segment length was 0.4 mm, with an accuracy of 97.77%. The 0.2 mm signal segments failed to eliminate the negative effects of pore migration. The signal segments over 0.4 mm resulted in prediction errors of small and dense pores. This work provides more guidance for optimizing the feature extraction of welding signals to improve the accuracy of welding defect identification.

Uncovering acoustic signatures of pore formation in laser powder bed fusion

We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom varvec{k}-means clustering (NMFvarvec{k}) to learn the underlying spectral patterns associated with pore formation. NMFvarvec{k} returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMFvarvec{k} decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMFk, the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

Fabrication and Characterization of Porous Microneedles for Enhanced Fluid Injection and Suction: A Two‐Photon Polymerization Approach

Porous microneedles (MNs) offer broad advantages such as fluid capture and filtration. Compared to hollow MNs, fluid injection through porous MNs causes a broader diffusion spread. Herein, three MN designs with a constant pore size and controlled pore locations are fabricated and compared, using two‐photon polymerization (2PP), by examining factors such as diffusion spread, mixing capabilities, and mechanical resilience. Results show that the porous MN can cover 16 times the injection area than that of the hollow MN. Porous MNs also show good mixing capabilities with two fluids. Mechanical compression results reveal that one porous MN can withstand a load of 0.6 N.

Mechanical properties and deformation behavior of equiatomic CoCrFeMnNi high-entropy alloy foam: A molecular dynamics study

In recent years, the aerospace and mechanical industries have employed metal foams for High Energy Capacity applications. However, the porous nature of such metallic foams results in a drop in tensile properties. High Entropy Alloys (HEAs) have been reported to overcome the strength-ductility trade-off as opposed to conventional metals and their alloys. Based on this, an equiatomic nano porous CoCrFeMnNi HEA is investigated using molecular dynamics simulation to elucidate the deformation behavior and mechanical performance at different atom distributions, percent porosity, and pore locations. The findings indicated that the mechanical properties are independent of atom distributions. However, with an increase in percent porosity, a decline in the ultimate tensile strength was observed. Up to 66% reduction in tensile strength was recorded. A similar trend was observed under temperature variations. By varying pore location, either within or on the structure, the pores within the foam structure led to a significant reduction in properties. The deformation mechanism of the HEA foam was established via analyses of the dislocation distributions, stacking faults, crack nucleation, and propagation. The findings offer new insights for material design to produce high-performance HEA foams and a comprehension of its failure mechanism under loading.

Free-form multi-level porous model design based on truncated hierarchical B-spline functions

Porous structures have been widely applied in aerospace, paramedical, transportation, and other fields owing to their high interconnectivity, low weight, and extensive internal surface areas. Multi-level porous structures with different hole shapes and distributions at varying scales have shown excellent biological and mechanical performances compared with single-level porous structures. However, designing multi-level porous models with complex topological and geometric structures is a challenge. In this work, we propose a multi-level porous model design framework. Given a model represented by a trivariate B-spline solid and porous structures represented by implicit functions, we design the porous model in the parametric domain. We use threshold distribution fields represented by truncated hierarchical B-spline (THB-spline) functions to control the pore shapes, locations, and number of levels. Furthermore, the proposed THB-spline least squares progressive-iterative approximation algorithm can flexibly adjust the porous model. The model meets the expected porosity through the proposed optimization algorithm. The porous structure in the parametric domain is finally mapped to the trivariate B-spline solid to generate the final model. Moreover, we define a new storage space-saving file format to store multi-level porous models. The experimental results demonstrate the effectiveness and efficiency of the method and the superior performance of the new storage format.

Overview of Polyethylene Terephthalate Foils Patterned Using 10 MeV Carbon Ions for Realization of Micromembranes

Polymer membranes are conventionally prepared using high-energy particles from radioactive decay or by the bombardment of hundreds of MeVs energy ions. In both circumstances, tracks of damage are produced by particles/ions passing through the polymer, and successively, the damaged material is removed by chemical etching to create narrow pores. This process ensures nanosized pore diameter but with random placement, leading to non-uniform local pore density and low membrane porosity, which is necessary to reduce the risk of their overlapping. The present study is focused on the use of polyethylene terephthalate (PET) foils irradiated by 10.0 MeV carbon ions, easily achievable with ordinary ion accelerators. The ion irradiation conditions and the chemical etching conditions were monitored to obtain customized pore locations without pore overlapping in PET. The quality, shape, and size of the pores generated in the micromembranes can have a large impact on their applicability. In this view, the Scanning Transmission Ion Microscopy coupled with a computer code created in our laboratory was implemented to acquire new visual and quantitative insights on fabricated membranes.

Ion Lithography of Single Ions Irradiation for Spatially Regular Arrays of Pores in Membranes of Polyethylene Terephthalate.

Routinely, in membrane technology, the decay from radioactive particles or the bombardment of ions with MeV energy per nucleon have been employed for the production of narrow and long pores in membranes. Presently, the ion lithography is proposed to make the fabrication cost more affordable. It is prospective for the use of medium capacity accelerators making more feasible the fabrication of customized membranes. Thin polyethylene terephthalate foils have been patterned using 12 MeV O5+ ions and then processed to obtain good aspect ratio ion track pores in membranes. Pores of micrometric diameter with the following profiles were fabricated in the membranes: truncated cone, double conical, ideal cone, and cylindrical. Monitoring of the shape and size of pores has been attempted with a combination of Scanning Transmission Ion Microscope and a newly designed simulation program. This study is focused on the use of low-energy ions, accomplished in all laboratories, for the fabrication of membranes where the pores are not randomly traced and exhibit higher surface density and negligible overlapping than in membranes commonly manufactured. The good reproducibility and the ordered pore locations can be potentially utilized in applications such as microfluidics and organ-on-chip microsystems, where cells growing over porous substrates are used in simulation of biological barriers and transport processes.

Role of SnO2 Nanoparticles for a Self-Forming Barrier Layer on a Mild Steel Surface in Hydrochloric Acid Medium Containing Piper betle Leaf Extract.

The self-formation of a porous organic thin-film via corrosion inhibitor supports wide applications of carbon steel in industry. Unfortunately, serious damages could be concentrated to the pinhole and/or pore locations in the porous organic film, resulting in the localized corrosion even when an optimal concentration of organic corrosion inhibitors is used. In this work, SnO2 nanoparticles are used for producing the more robust barrier layer via the self-migration of nanoparticles, resulting in a higher corrosion resistance, smooth and uniform protective layer, as well as the existence of SnO2 in the protective layer that could directly affect the high inhibition performance. Therefore, the work suggests a new way to make a more robust thin film that could extend the use of organic corrosion inhibitors.

Sensor fusion of pyrometry and acoustic measurements for localized keyhole pore identification in laser powder bed fusion

In-situ process monitoring as an aid to part qualification for laser powder-bed fusion ( L -PBF) technology is a topic of increasing interest to the additive manufacturing community. In this work, airborne acoustic and inline pyrometry measurements were recorded simultaneously with the laser position. X-ray radiography imaging was used to spatio-temporally register keyhole pore locations to the pyrometry and acoustic signals, enabling binary labeling of data partitions based on pore formation. These labeled partitions were subsequently featurized using a highly comparative time-series analysis toolbox. Acoustic data was found to be much more effective than the pyrometry data for keyhole pore identification. However, when the information contained in both sensing modalities was combined in a sensor fusion strategy, the error rates of the top performing models were significantly reduced.

Effective Elastic Stiffness Tensor and Ultrasonic Velocities for 3D Printed Polycrystals with Pores and Texture

ABSTRACT This paper focuses on the micromechanical modeling of pores and texture in 3D-printed polycrystals. A Gaussian-shape approximation is used to describe the orientation distribution function (ODF) and construct the initial homogenization model of the representative volume element (RVE). Spherical and ellipsoidal pores of varying sizes are added in stages to the RVE for homogenization, utilizing the modified Mori-Tanaka (MT) scheme in conjunction with the stepwise iterative method. Wherein, the mechanical interactions between pores and the spatial distribution of pore locations could be taken into account, when developing a cross-scale model from microstructure to macroelasticity. After obtaining the final elastic stiffness tensor, the Christoffel equation is combined with the Cardano’s formula to derive a closed form solution for ultrasonic velocities depending on microstructure. According to the numerical results, this method can effectively capture the behavior characteristics of pores and texture on the elastic stiffness tensor, average velocity, and velocity distribution.

Detection of keyhole pore formations in laser powder-bed fusion using acoustic process monitoring measurements

In-situ process monitoring of additively manufactured parts has become a topic of increasing interest to the manufacturing community. In this work, acoustic measurements recorded during laser powder-bed fusion (L-PBF) were used to detect the onset of keyhole pores induced by the lasing process. Post-build radiography was used to identify the locations of keyhole pores in the build. The pore locations were spatially and temporally registered with the recorded time-series of laser position and acoustic pressure to identify specific partitions of the acoustic signals which correspond to pore formation. Ensemble empirical mode decomposition, traditional Fourier decomposition, and statistical measures of the time-series and corresponding frequency spectra were used to extract feature vectors which correlate to keyhole pore formation. Sequential feature selection revealed that measures associated with the acoustic spectra were most useful for identifying pore formations in L-PBF. A subset of the most informative data features was used to train a support vector machine model to predict pore formation with up to 97% accuracy.

Hierarchical Pore-Based High-Resolution Fingerprint Indexing

Pore-based fingerprint recognition has become more attractive in recent years because of its uniqueness and difficulty in forgeability. However, most of the existing methods use pore features for fingerprint verification rather than fingerprint indexing, and most of them use only local features of pores to evaluate the similarities between fingerprints. In this article, we present a hierarchical pore-based high-resolution fingerprint indexing system using two kinds of pore features (including pore-based global and local features). Our work consists of two major parts. First, we design a united model named deep pore-based global and local features model (DPGL) to extract pore-based global and local features of fingerprints simultaneously. The most important is the DPGL framework makes full use of pore information. It applies deconvolution module to learn a spatial attention mask that explicitly exploits self-supervision on pore locations. Second, we design a novel hierarchical pore-based fingerprint indexing approach. In the proposed approach, the reference fingerprints are primely selected based on pore-based global features. The fingerprints retained are selected based on pore-based local features subsequently. Finally, the candidate fingerprints are ranked according to pore information matching. Experiments on two datasets show that DPGL not only can accomplish the extraction of pore-based global and local features successfully, but also can achieve self-supervision on pore information. Compared with other state-of-the-art pore-based fingerprint indexing methods, the proposed approach reduces the pre-selection error rate by about 50% at penetration rate 1%, and performs at least 65% reduction in retrieval time.

Influence of Porosity on Fracture Toughness and Fracture Behavior of Antibiotic-Loaded PMMA Bone Cement.

Aseptic loosening is the most common reason for the long-term revision of cemented arthroplasties with fracture of the cement being a postulated cause or contributing factor. In our previous studies we showed that adding an antibiotic to a polymethylmethacrylate (PMMA) bone cement led to detrimental effects on various mechanical properties of the cement such as bending strength, compressive strength and fracture toughness (KIC). This finding implied that the mechanical failure of antibiotic-loaded PMMA bone cement was influenced by its pore volume fraction. Up to now this aspect has not been studied. Hence the purposes of this study were to determine (1) the influence of antibiotic (telavancin) loading on the KIC of a widely used PMMA bone cement brand (Palacos®R) and (2) the influence of pore size and pore distribution on the fracture behavior of the KIC specimens. For (2) both experimental and numerical methods (extended finite element method [XFEM]) were used allowing a comparison between the two sets of results. We found that: (1) KIC decreased with increased porosity with the drop (relative to the value for the control cement) being significant when the telavancin loading was 4.8 wt/wt % (2 g of telavancin added to 40 g of control cement powder); (2) there was a critical pore size above which there was a significant decrease in KIC and is 1 mm; (3) crack propagation was strongly influenced by pore size and pore locations (pore-pore interactions); and, (4) there was good agreement between the experimental and XFEM results. The implications of these findings for the use of a telavancin-loaded PMMA bone cement in cemented total joint arthroplasties are commented upon.

A fractal model of effective mechanical properties of porous composites

In this work, a simple but effective fractal model is proposed to predict the mechanical properties of complex porous composites. By extending the Mori-Tanaka and Double Inclusion models, we develop a computationally efficient algorithm based on the mean-field homogenization, to quickly determine the macroscopic elastic properties of the random porous media by the fractal theory. The random pore sizes and locations are properly characterized by a single fractal dimension, and the fractal model agrees well with the numerical results obtained by the finite element homogenization technique and the existing experimental data from literature. Moreover, the effect of pore size distribution has been investigated, indicating that the elastic properties decrease with the increase in the fractal dimension. In particular, the computation time can be reduced from 4 h for the finite element analysis to 15 s based on the fractal model. Based on the mathematically analogous governing equations, the present fractal modeling has great potential to determine the other significant physical properties such as thermal conductivity and coefficient of thermal expansion.

Effects of embedded spherical pore on the tensile properties of a selective laser melted Ti6Al4V alloy

Selective laser melting (SLM) is one of the most promising additive manufacturing (AM) technologies in recent years. However, some sub-millimeter defects often appear accidently in SLM specimens, resulting in deterioration of mechanical properties. Therefore, the effects of these defects on the mechanical properties of the SLM materials are significantly important. In this study, the effect of a single spherical defect on the tensile properties was investigated by embedding a spherical pore inside the SLM Ti6Al4V specimens. Different combinations of pore diameters (Ф100 μm, Ф300 μm, Ф500 μm, Ф1000 μm) and locations (center, sub-surface, near-surface) were designed to mimic the sub-millimeter printing defects. The results demonstrated that these embedded pores had negligible influence on the elastic modulus and tensile strength but had a noticeable influence on the tensile elongation. With the increase of pore size, the elongation to failure of the specimens tended to be stochastic, stably high and stably low in sequence, which could be related to different fracture modes. The tensile specimens fractured at the embedded pore when the embedded pore size was increased to a critical diameter (approximately Ф1000 μm). Concurrently, the location of the embedded pore started to have an obvious influence on ductility, namely, the elongation to failure decreased as the embedded pore became closer to free surface.

Toward Sub-Surface Pore Prediction Capabilities for Laser Powder Bed Fusion Using Data Science

Abstract Achieving defect-free parts is traditionally challenging in laser powder bed fusion (LPBF). The mechanical properties of additively manufactured parts are highly affected by their density; as such, research in defect detection and pore prediction has gained significant interest. The process parameters, the powder characteristics, and the process environment conditions play an important role in defect occurrence. Moreover, the laser scan path affects density, especially at scan path discontinuities. In this work, the complex interaction between the process parameters and the scan path on the occurrence of subsurface pores is investigated. In the data preparation step, a synthetic data set is generated to model the melt pool morphology along the scan path. A secondary data set containing the pore space of the resulting parts is obtained via X-ray computed tomography (CT) and is registered with the synthetic data set. Machine learning models, namely, a Conditional Variational AutoEncoder (CVAE) and a Convolutional Neural Network (CNN), are then trained based on the input features to predict pore occurrence. The performance evaluation of both CNN and CVAE models on synthetic data indicates that the scan path and process parameters can be utilized in predicting pore locations. Quantitative results show that employing offline CT images a priori in training the CVAE, without the need to have CT information in the test phase, leads the CVAE model to superior performance over the CNN.

Fine-tuning of the surface porosity of micropatterned polyethersulfone membranes prepared by phase separation micromolding

Phase separation micromolding (PSμM) is an effective technique for fabricating porous membranes with micropatterned structures. However, reports on procedures to control the size and number of open pores on the patterned surface are scarce, which often limits the use of the surface-patterned membranes. This work presents a systematic study on tailoring open pores on the patterned surface of polyethersulfone (PES) membranes prepared by the PSμM procedure. The composition of the solvent and the concentration of PES in the casting solution were optimized to tune the size and number of pores on the membrane surfaces formed on a flat substrate during the nonsolvent-induced phase separation (NIPS) process. The surface porosity changed significantly and macrovoids appeared when the flat substrate was replaced by a micropatterned substrate. The vapor-induced phase separation process was applied prior to the NIPS process to prevent the formation of macrovoids. The composition of the casting solution was tuned again to prepare micropatterned porous PES membranes with open pores on the patterned surface. We observed that the size and number of pores were different depending on the pore locations on the patterned surface, which was caused by different solvent/nonsolvent demixing dynamics resulting from the physical discontinuity of micro-patterned membranes. This work presents a method on tailoring open pores on the patterned surface of polyethersulfone membrane prepared by the phase separation micromolding. By modifying both the thermodynamics of the casting solution and the dynamics of solvent/nonsolvent demixing, micropatterned membrane with average surface open pores in the diameter of 1095 nm and porosity as high as 31.4% was achieved. The size and number of pores were different depending on their locations on the patterned surface, which was caused by different solvent/nonsolvent demixing dynamics resulting from the physical discontinuity of micro-patterned membranes.

Effects of process parameters on porosity in laser powder bed fusion revealed by X-ray tomography

This paper reports on X-ray tomography of a series of coupon samples (5 mm cubes) produced under different process parameters, for laser powder bed fusion of Ti6Al4V. Different process parameters result in different pore formation mechanisms, each with characteristic pore sizes, shapes and locations within the 5 mm cube samples. While keyhole pores, lack of fusion pores and metallurgical pores have been previously identified and illustrated using X-ray tomography, this work extends beyond prior work to show how each of these not only exist in extreme situations but how they vary in size and shape in the transition regimes. It is shown how keyhole mode porosity increases gradually with increasing power, and how this depends on the scan speed. Similarly, lack of fusion pores are shown to occur following scan tracks in situations of poor hatch overlap, or a similar but different distribution of lack of fusion porosity due to large layer height spacing, showing respectively vertical and horizontal lack of fusion pore morphologies. Increased spacing between hatch scan tracks and contour scan tracks is demonstrated to form a near-surface porosity similar to that previously reported for slowing at the end of scan tracks which can cause keyhole mode porosity. Insights from 3D images allow improvements in parameter choices for optimized density of parts produced by laser powder bed fusion, and generally allow a better understanding of the porosity present in additively manufactured parts.

Modulation versus Templating: Fine‐Tuning of Hierarchally Porous PCN‐250 Using Fatty Acids To Engineer Guest Adsorption

AbstractModulation and templating are two synthetic techniques that have garnered significant attention over the last several years for the preparation of hierarchically porous metal–organic frameworks (HP‐MOFs). In this study, by using fatty acids with different lengths and concentrations as dual‐functional modulators/templates, we were able to obtain HP‐MOFs with tunable mesopores that exhibit different pore diameters and locations. We found that the length and concentration of the fatty acids can determine if micelle formation occurs, which in turn dictates the porosity of the resulting HP‐MOFs. The HP‐MOFs with different mesopores differed in their performance in gas uptake and dye adsorption, and the structure–performance relationships were ascribed to the pore diameters and locations. This approach could provide a potentially universal method to efficiently introduce hierarchal mesopores into existing microporous MOF adsorbents with tunable properties.