Porosity Measurements Research Articles

Prediction of in-vitro dissolution and tablet hardness from optical porosity measurements

Advanced manufacturing technologies such as continuous processing require fast information on the quality of intermediates and products. Process analytical technologies (PAT) to monitor many critical quality attributes (CQAs) have been developed and successfully implemented in pharmaceutical industry. However, there are some CQAs, which still have to be measured off-line with significant effort due to the lack of suitable PAT sensors. Two prominent examples are the in-vitro dissolution and the tablet hardness. Both are obtained via destructive measurement, and the dissolution is tedious and time-consuming to determine. In this study, these two CQAs were predicted via correlation with the optical porosity of tablets. The optical porosity was measured via a novel combination of gas in scattering media absorption spectroscopy (GASMAS) and photon time of flight spectroscopy (pTOFS) with a SpectraPore instrument. The approach was tested in a continuous tableting line and showed promising results in predicting the amount of drug released after specific dissolution times as well as the tablet hardness. This indicates that the measurement of optical porosity can support control strategies within the real-time release testing (RTRT) concept.

A rate-dependent damage mechanics model for predicting plasticity and ductile fracture behavior of sheet metals at high strain rates

Uniaxial tensile tests were performed on H340 steel sheets at different strain rates (10-4 to 103s-1) and temperatures (–30 °C and 280 °C). Oscillation-free forces were measured during high-speed tests at strain rates of up to 1000 s-1 using specimens with different stress states. Material hardening curve, strain rate sensitivity, temperature effects, and Taylor-Quinney coefficient for adiabatic temperature calculations were determined in experiments. Digital image correlation (DIC) technique was employed to measure displacement, deformation, and local strain fields. Meanwhile, the temperature fields of specimen gauge section were measured with a high–speed thermal camera in the uniaxial tensile tests at various strain rates. Damage and fracture-related parameters were calibrated and validated using porosity measurements on SEM micrographs and in combination with finite element (FE) simulations. A rate– and temperature–dependent plasticity and damage mechanics model (e2MBW) was proposed and calibrated to predict the plasticity and fracture behavior of H340 under different loading speeds. The study demonstrated good agreement in the overall experimental and simulated force–displacement responses and local strain evolution across all fracture specimens at loading speeds from 0.005 mm/s to 10000 mm/s.

Prototyping and characterisation of 316L stainless steel parts and lattice structures printed via metal fused filament fabrication

PurposeThis study aims to deepen the knowledge concerning the metal fused filament fabrication technology through an analysis of the printing parameters of a commercial 316L stainless steel filament and their influence on the porosity and mechanical properties of the printed parts. It also investigates the feasibility of manufacturing complex geometries, including strut-and-node and triply periodic minimal surface lattices.Design/methodology/approachA three-step experimental campaign was carried out. Firstly, the printing parameters were evaluated by analysing the green parts: porosity and density measurements were used to define the best printing profile. Then, the microstructure and porosity of the sintered parts were investigated using light optical and scanning electron microscopy, while their mechanical properties were obtained through tensile tests. Finally, manufacturability limits were explored with reference samples and cellular structures having different topologies.FindingsThe choice of printing parameters drastically influences the porosity of green parts. A printing profile which enables reaching a relative density above 99% has been identified. However, voids characterise the sintered components in parallel planes at the interfaces between layers, which inevitably affect their mechanical properties. Lattice structures and complex geometries can be effectively printed, debinded, and sintered if properly dimensioned to fulfil printing constraints.Originality/valueThis study provides an extensive analysis of the printing parameters for the 316L filament used and an in-depth investigation of the potential of the metal fused filament fabrication technology in printing lightweight structures.

Green nanoparticles blending with polyacrylonitrile ultrafiltration membrane for antifouling oily wastewater treatment

This work prepares novel polyacrylonitrile (PAN) membranes by incorporating eggplant waste (EGW) as eco-friendly green nanoparticles (NPs) with PAN membranes to enhance the antifouling of PAN membranes to separate oil from oily wastewater (OWW). The modified PAN membranes are characterized by Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscope (FE-SEM), and measurements of the contact angle, porosity, and mechanical properties. The effect of EGW NPs content on membrane properties and morphology, its entire performance, and its antifouling characteristics is investigated. The performance of the PAN-EGW membranes is evaluated by pure water flux and oil rejection. The PAN membrane incorporated with 0.1 wt% EGW NPs enhances a pure water flux to 204.71 L/m2 h, exceeding that of the pristine PAN membrane (136.51 L/m2 h). This can be attributed to the low contact angle (39.66◦), high surface membrane porosity (91%), and good tensile strength (8.2 MPa) for PAN-EGW membranes compared to the contact angle (68.56◦), surface membrane porosity (69%), and tensile strength (5.1 MPa) for the pristine PAN membrane. Another significant improvement noticed is the excellent oil rejection by the modified membranes (about 99.95%, 95.50%, and 90.00% at oil concentrations of 1000, 100, and 10 ppm, respectively, and a transmembrane pressure (TMP) of 2 bar); treated-wastewater oil content that complies with the World Health Organization (WHO) environmental discharge standards (< 5 ppm) is achieved. Also, the antifouling performance is improved; a higher flux recovery ratio (FRR) is obtained (about 94.43%). In addition, the oil separation efficiency remains stable with a minor decrease in permeate flux after four cycles. This study demonstrates that the novel PAN-EGW membranes have great promise and potential for purifying OWW, particularly at low oil concentrations (10 ppm) compared to pristine PAN membranes, attributable to their high separation efficiency, oil-fouling resistance, and excellent environmental durability.

Advanced Support Structures in Metal Additive Manufacturing: A Comparative Analysis of Porous Media for Enhanced Part Quality and Removal Efficiency

In laser powder bed fusion additive manufacturing support, structures are crucial for constructing overhang features and maintaining dimensional accuracy. However, traditional support structures exhibit inherent drawbacks, including compromised surface quality, prolonged post‐processing times, and other challenging requirements. This study investigates innovative approaches to address these issues by analyzing two types of specimens—cuboid and lap shear. The cuboid samples explore the manipulation of process parameters to adjust energy densities, transitioning from powder to porous support structures, with porosity measurement assessment. Subsequently, a shear test specimen objectively evaluates porous support parameters alongside traditional block‐type support, analyzing their impact on removal force, distortion, and surface quality. Results reveal that optimized porous support structures surpass traditional counterparts, showcasing superior surface quality, reduced removal forces, and minimized part distortion. Specifically, the shear test demonstrates a 94.25% reduction in removal forces and a 33.67% decrease in upper part distortion. Moreover, the maximum surface roughness (Rz) improves by 22.8% with the implementation of porous supports. By introducing a methodology for comparative analyses of measurable performance indicators, this research enhances understanding of support structure dynamics in additive manufacturing, facilitating advancements in efficiency and quality within the field.This article is protected by copyright. All rights reserved.

METHODOLOGY AND FEATURES OF RESEARCH OF FILTRATION PROPERTIES OF COMPACTED DEEP-SEATED ROCKS

As a result of the depletion of conventional hydrocarbon reserves, there is a need to explore deposits at great depths and under difficult geological conditions. This requires the improvement of technologies for studying rocks and fluids using computer modeling systems and laboratory equipment. Laboratory modeling of the processes occurring in rocks during drilling, development, stimulation or various chemical treatments plays a significant role in modern hydrocarbon production, as it reduces the number of errors at the design stage of field development or methods of impacting productive formations. There are a number of well-known manufacturers of laboratory equipment that model filtration processes in rocks, but any system has both advantages and disadvantages. To implement the tasks of studying filtration processes in rocks, technologies for the development of compacted and conventional reservoirs, stimulation methods and physical and chemical effects in hydrocarbon production, filtration equipment has been developed that allows for standard and special studies of rock core material. The first low-pressure unit allows for fast and accurate measurements of porosity and permeability at pressures up to 10 MPa and temperatures up to 120℃. In addition to filtration processes, the equipment allows for evaluation studies of the impact of various chemical solutions, drilling and other process fluids on natural and artificial cores in scientific and industrial research. For the study of rocks and fluids in reservoir conditions, a filtration system has been developed that allows for all of the above studies at pressures up to 100 MPa and temperatures up to 200℃. The peculiarity of the developed equipment is high accuracy of measurements, automation of monitoring processes, corrosion-resistant design of the main components and assemblies, which allows conducting research in any aggressive environment. Laboratory studies allow avoiding mistakes in the design of new areas development, reducing drilling accidents and selecting effective technologies for rock impact.

The Effect of Assam Silk Fibroin on the Bacterial Cellulose Cytocompatibility as the Extracellular Matrix

AbstractThe growing interest in natural polymers for biomedical and tissue engineering has fueled the search for materials with superior mechanical and biological properties. Bacterial cellulose (BC) and silk fibroin (SF) emerge as promising candidates meeting these criteria. This study focuses on enhancing BC through high‐pressure homogenization (HPH) and subsequent functionalization with Assam silk fibroin (ASF) using an ex‐situ approach. Analysis via attenuated total reflection–Fourier transform infrared (ATR–FTIR) spectroscopy confirms the successful integration of ASF into the HPH‐treated BC scaffold. The diffractogram of HPH‐BC/ASF indicates the prevalence of type I cellulose crystalline structures, with variations in lamellar and porous architecture based on component ratios. Mechanical testing, particularly the compressive test, reveals that the HPH‐BC/ASF formulation exhibits the highest compressive stress and modulus compared to other samples. Supplementary analyses, including swelling ratio and porosity measurements, support the superior compressive properties of HPH‐BC/ASF. Moreover, the cell viability of chondrocytes demonstrates compatibility with the BC‐based scaffold material. These findings underscore the potential applications of HPH‐BC and ASF in areas such as scaffolding for the development of extracellular matrix.

SEM Image Processing Assisted by Deep Learning to Quantify Mesoporous γ-Alumina Spatial Heterogeneity and Its Predicted Impact on Mass Transfer.

The pore network architecture of porous heterogeneous catalyst supports has a significant effect on the kinetics of mass transfer occurring within them. Therefore, characterizing and understanding structure-transport relationships is essential to guide new designs of heterogeneous catalysts with higher activity and selectivity and superior resistance to deactivation. This study combines classical characterization via N2 adsorption and desorption and mercury porosimetry with advanced scanning electron microscopy (SEM) imaging and processing approaches to quantify the spatial heterogeneity of γ-alumina (γ-Al2O3), a catalyst support of great industrial relevance. Based on this, a model is proposed for the spatial organization of γ-Al2O3, containing alumina inclusions of different porosities with respect to the alumina matrix. Using original, advanced SEM image analysis techniques, including deep learning semantic segmentation and porosity measurement under gray-level calibration, the inclusion volume fraction and interphase porosity difference were identified and quantified as the key parameters that served as input for effective tortuosity factor predictions using effective medium theory (EMT)-based models. For the studied aluminas, spatial porosity heterogeneity impact on the effective tortuosity factor was found to be negligible, yet it was proven to become significant for an inclusion content of at least 30% and an interphase porosity difference of over 20%. The proposed methodology based on machine-learning-supported image analysis, in conjunction with other analytical techniques, is a general platform that should have a broader impact on porous materials characterization.

On improved microstructure properties of slag-based UHPC incorporating calcium formate and calcium chloride

The study aimed to achieve high strength in slag-based cementless ultra-high performance concrete (UHPC) while investigating the role of calcium formate and calcium chloride as accelerators using advanced characterization and microstructural analysis. The UHPC specimens were evaluated using various techniques, including heat of hydration, thermogravimetric analysis, X-ray diffraction, nuclear magnetic resonance, scanning electron microscopy, and porosity measurements. The results showed that both accelerators improved the UHPC properties, with calcium formate being more effective than calcium chloride, as evidenced by higher heat of hydration, improved microstructure, and lower porosity. Furthermore, the thermodynamic modeling revealed insightful information on the reaction mechanisms with C-(N-)A-S-H and hydrotalcite as the primary hydration products formed in the matrix. Notably, the UHPC specimens with calcium chloride exhibited a very low pH value, which could increase the risk of corrosion in reinforced structures. Therefore, the use of calcium formate as an accelerator can lead to the development of cementless UHPC with superior properties.

Regional structure-function relationships of lumbar cartilage endplates

Cartilage endplates (CEPs) act as protective mechanical barriers for intervertebral discs (IVDs), yet their heterogeneous structure–function relationships are poorly understood. This study addressed this gap by characterizing and correlating the regional biphasic mechanical properties and biochemical composition of human lumbar CEPs. Samples from central, lateral, anterior, and posterior portions of the disc (n = 8/region) were mechanically tested under confined compression to quantify swelling pressure, equilibrium aggregate modulus, and hydraulic permeability. These properties were correlated with CEP porosity and glycosaminoglycan (s-GAG) content, which were obtained by biochemical assays of the same specimens. Both swelling pressure (142.79 ± 85.89 kPa) and aggregate modulus (1864.10 ± 1240.99 kPa) were found to be regionally dependent (p = 0.0001 and p = 0.0067, respectively) in the CEP and trended lowest in the central location. No significant regional dependence was observed for CEP permeability (1.35 ± 0.97 * 10−16 m4/Ns). Porosity measurements correlated significantly with swelling pressure (r = −0.40, p = 0.0227), aggregate modulus (r = −0.49, p = 0.0046), and permeability (r = 0.36, p = 0.0421), and appeared to be the primary indicator of CEP biphasic mechanical properties. Second harmonic generation microscopy also revealed regional patterns of collagen fiber anchoring, with fibers inserting the CEP perpendicularly in the central region and at off-axial directions in peripheral regions. These results suggest that CEP tissue has regionally dependent mechanical properties which are likely due to the regional variation in porosity and matrix structure. This work advances our understanding of healthy baseline endplate biomechanics and lays a groundwork for further understanding the role of CEPs in IVD degeneration.

Simulations of absolute porosity measurements by compensated neutron logging tools mounted with stilbene or CLYC scintillators

This paper aims to demonstrate the feasibility of the proposed compensated neutron logging (CNL) tool for the absolute measurement of the porosity of subsurface formation based on the computational simulation study. Conventional CNL tools use 3He gas detectors, but solid-state scintillation detectors such as stilbene and CLYC are explored in this study. Monte Carlo simulations were conducted to investigate the advantages of the proposed CNL tool and the effects of environmental parameters such as pore fluid, borehole radius, and rock type on the absolute porosity measurement. Comparing simulated responses from the stilbene and CLYC detectors with conventional 3He detector, the stilbene-based logging system was expected to exhibit the highest neutron detection efficiency, while the porosity calibration performance was evaluated to be better with the CLYC-based system. Pore fluid makes differences in porosity calibration curves associated with the hydrogen content. Larger borehole radius deteriorates the porosity calibration performance. The shape of porosity calibration curve was altered for a certain rock type. Neutron-induced gamma spectroscopy may reveal the rock type information based on gammas from certain elements. One can identify the rock type from the CLYC results based on photopeaks from silicon, which may be relatively hard to accomplish with the stilbene-based system. The proposed system is expected to allow absolute porosity measurement in a broader environmental configuration compared to the conventional system.

Compaction-induced porosity loss in the Cretaceous Bima Formation around Lakwaime and Dogon Dutsi, Yola Subbasin, Northern Benue Trough, NE Nigeria

The Bima Sandstone is an alluvial fan to braided river sedimentation that represents purely a siliciclastic depositional system. It is the oldest formation and the main reservoir unit in the entire Benue Trough. Porosity loss is an essential component of petroleum reservoirs that needs to be properly investigated for the purpose of hydrocarbon exploitation. Compaction and cementation processes are partly responsible for porosity loss in many known reservoirs around the world. Outcropping units of the formation around Lakwaime and Dogon Dutsi in Yola Sub-basin have been subjected to an integrated approach involving field observations, petrographic analysis and porosity measurements in order to understand the contribution of each of the processes. Modal composition of the samples shows that they are mostly lithic arkose to feldspathic litharenite, with quartz as the most common detrital mineral grain. Grain fracturing has been attributed to mechanical compaction, whereas grain contacts like sutured and concavo-convex are products of chemical compaction. The average values of compactional-porosity loss (COPL), cementational-porosity loss (CEPL), and compaction index (ICOMPACT) in the studied samples stand at 19.51%, 4.18% and 0.82 respectively. The study indicates that the role of compaction in porosity loss is greater than that of cementation as shown by the COPL-CEPL diagram and, as such considered to be generally responsible for the porosity loss in Bima Sandstone.

The Effect of Diagenetic Minerals on the Petrophysical Properties of Sandstone Reservoir: A Case Study of the Upper Shallow Marine Sandstones in the Central Bredasdorp Basin, Offshore South Africa

The upper shallow marine sandstone reservoirs of the Barremian-to-Valanginian formation are the most porous and permeable sandstone reservoirs in the Bredasdorp Basin and an important target for oil and gas exploration. There is a paucity of information on the reservoir characterization and effect of diagenetic mineral studies focusing on the upper shallow marine sandstone reservoirs in the central Bredasdorp Basin; thus, there is a need to investigate the effect of diagenetic minerals and to characterize these reservoirs due to their high porosity and permeability. Datasets, including a suite of geophysical wireline logs, routine core analysis, geological well completion reports, description reports, and core samples, were utilized. A total of 642 core porosity measures, core water saturation, and core permeability data were used for calibration with the log-derived parameters, ranging in depth from 3615 m to 4259 m. Rock samples were prepared for diagenetic mineral analyses, such as thin sections and Scanning electron microscopy, for each well to investigate the presence of diagenetic minerals in the selected reservoir units. The petrophysical analyses showed the results of porosity, volume of clay, water saturation, and permeability, ranging from 9% to 27%, 8.6% to 19.8%, 18.9% to 30.4%, and 0.096 mD to 151.8 mD, respectively, indicating a poor-to-good reservoir quality. Mineralogical analyses revealed that micrite calcite, quartz cement, quartz overgrowth, and authigenic pore-filling and grain-coating clay minerals (illite–smectite and illite) negatively affected intergranular porosity. Porosity-versus-permeability cross plot showed good correlation of 0.86 for ZN1 and 0.83 for ZN3 reservoirs, suggesting that although porosity is the main drive of permeability, there were other geological factors at play, such as diagenetic minerals and compaction.

Enhancing the Green Synthesis of Glycerol Carbonate: Carboxylation of Glycerol with CO2 Catalyzed by Metal Nanoparticles Encapsulated in Cerium Metal-Organic Frameworks.

The reaction of glycerol with CO2 to produce glycerol carbonate was performed successfully in the presence of gold nanoparticles (AuNPs) supported by a metal-organic framework (MOF) constructed from mixed carboxylate (terephthalic acid and 1,3,5-benzenetricarboxylic acid). The most efficient were two AuNPs@MOF catalysts prepared from pre-synthesized MOF impregnated with Au3+ salt and subsequently reduced to AuNPs using H2 (catalyst 4%Au(H2)@MOF1) or reduced with NaBH4 (catalyst 4%Au@PEI-MOF1). Compared to existing catalysts, AuNPs@MOFs require simple preparation and operate under mild and sustainable conditions, i.e., a much lower temperature and the lowest CO2 overpressure ever reported, with MgCO3 having been found to be the optimal dehydrating agent. Although the yield of the process is still not competitive with previously developed systems, the most promising advantage is the highest TOF (78 h-1) ever reported for this reaction. The optimal parameters observed for AuNPs were also tested on AgNPs and CuNPs with promising results, suggesting their great potential for industrial application. The catalysts were characterized by XRD, TEM, SEM-EDS, ICP-MS, XPS, and porosity measurements, confirming that AuNPs are present in low concentration, uniformly distributed, and confined to the cavities of the MOF.

Real-Time Prediction of Petrophysical Properties Using Machine Learning Based on Drilling Parameters.

The prediction of rock porosity and permeability is crucial for assessing reservoir productivity and economic feasibility. However, traditional methods for obtaining these properties are time-consuming and expensive, making them impractical for comprehensive reservoir evaluation. This study introduces a novel approach to efficiently predict rock porosity and permeability for reservoir assessment by leveraging real-time machine learning models. Utilizing readily available drilling parameters, this approach offers a cost-effective alternative to traditional time-consuming methods to predict formation petrophysical parameters in real-time. The data set used in this study was collected from two vertical wells located in the Middle East. It encompasses drilling parameters such as the rate of penetration (ROP), gallons per minute (GPM), revolutions per minute (RPM), strokes per minute (SPP), torque, and weight on bit (WOB), along with the corresponding measurements of porosity (ϕ) and permeability (k) obtained through core analysis. Three machine learning models, namely, decision trees (DTs), random forest (RFs), and support vector machines (SVMs), were employed and evaluated for their effectiveness in predicting porosity and permeability. The results demonstrate promising performance across the different data sets. All three models achieved correlation coefficients (R) higher than 0.91 in predicting porosity. The RF model exhibited accurate predictions of permeability, achieving R values surpassing 0.92 in the various data sets. While the DT model displayed slightly lower performance, with the R-value decreasing to 0.88 in the testing data set, the SVM model suffered from overfitting, with R values dropping to 0.83 in the testing data set. The novelty of this work lies in the successful application of machine learning models to the real-time prediction of reservoir properties, providing a practical and efficient solution for the oil and gas industry. By achieving correlation coefficients exceeding 0.91 and showcasing the models' efficacy in a dynamic testing data set, this study paves the way for improved decision-making processes and enhanced exploration and production activities. The innovative aspect lies in the utilization of drilling parameters for timely and cost-effective estimation, transforming conventional reservoir evaluation methods.

Gradient ionomer designed cathode catalyst layer for proton exchange membrane fuel cells with enhanced performance

The catalyst layer (CL) plays a critical role in the electrochemical reactions that occur in proton exchange membrane fuel cells (PEMFCs). In this study, we employ ionomers with varying equivalent weight (EW) values to create a gradient cathode catalyst layer (CCL) to enhance mass transport and improve water management capability within PEMFC. The best performance is achieved for the membrane electrode assembly (MEA) with gradient CL when the ratio of short side chain (SSC) ionomer near the proton membrane to long side chain (LSC) ionomer near the gas diffusion layer is 3:1. The cell voltage reaches 0.689 V@2.0 A cm−2 (78 °C, 150 kPa, stoic. H2/Air = 2.2/3.2) representing improvements of 55 mV and 14 mV over the MEA with homogeneous CLs containing only LSC ionomer or only SSC ionomer. The porosity measurement indicates that the gradient CL increased the porosity of the MEA. Electrochemical characterization provides evidence that this gradient ionomer design enhances catalyst utilization and reduces mass transfer losses. Furthermore, the durability assessment of the MEAs reveals less performance degradation in the gradient CCL. Therefore, utilizing ionomers with different EW values to construct a gradient CCL is an effective strategy to achieve high power output and long life of PEMFCs.

A comprehensive study on the effects of surface post-processing on fatigue performance of additively manufactured AlSi10Mg: An augmented machine learning perspective on experimental observations

In this study, the efficacy of 21 distinct surface post-processing methods on the fatigue behavior of an additively manufactured (AM) material was investigated. Various treatments, encompassing single-step processes like sand blasting (SB), conventional shot peening (CSP), severe shot peening (SSP), gradient severe shot peening (GSSP), ultrasonic shot peening (USP), severe vibratory peening (SVP), ultrasonic nanocrystal surface modification (UNSM), laser shock peening (LSP), laser polishing (LP), tumble finishing (TF), chemical polishing (CP), electro-chemical polishing (ECP), and machining (M), as well as hybrid treatments, were systematically investigated for their impact on the fatigue behavior of hourglass laser powder based fused (LB-PBF) AlSi10Mg specimens. A comprehensive series of experimental tests were carried out, covering surface texture analyses, microstructural characterizations, porosity measurements, hardness, residual stresses (RS), monotonic tensile tests, and rotating bending fatigue tests at four stress levels. Following the experimental investigations, the acquired data were leveraged to develop a machine learning (ML)-based model to correlate the fatigue life with the influencing factors and conduct parametric and sensitivity analyses. The model utilized a deep learning approach to predict the fatigue response of LB-PBF AlSi10Mg, incorporating various artificial neural networks (ANNs) and considering input parameters such as yield strength, ultimate tensile strength, elongation to fracture, porosity, depth of pore closure, surface hardness, depth of hardness variation, surface RS, maximum compressive residual stresses (CRS), depth of the CRS field, top surface grain size, surface layer mean grain size, surface roughness, and stress amplitude. Depending on the life regime, the factors influencing fatigue behavior can vary significantly. In higher stresses, dominated by plastic strains, surface residual stress emerges as the primary factor. Conversely, in lower stresses, dominated by elastic strains, the significance of surface roughness becomes more pronounced, followed by surface residual stress, surface hardness and other factors. These findings underscore the contextual importance of different influencing factors for enhancing fatigue resistance based on varying loading conditions.

Optimized manufacturing process of homogeneous microwave-sintered blocks of KLS-1 lunar regolith simulant

The use of materials from the Moon's surface based on In-Situ Resource Utilization (ISRU) is gaining considerable attention as a means of constructing infrastructure to sustain a human presence there. In particular, the sintering of lunar regolith appears a promising way to fabricate infrastructure on the lunar surface. This study presents a method to manufacture homogeneous blocks using a lunar regolith simulant. The tested simulant, KLS-1, was sintered under diverse conditions in a multi-mode microwave sintering furnace. Successful sintering requires the sample to be heated throughout, without generating a temperature gradient. This was achieved by testing various heating rates and sample sizes. X-ray computed tomography was used to assess the pore structure of sintered samples. While the optimized sintering conditions resulted in the formation of internal cracks by outgassing, preheating the KLS-1 in a vacuum oven at 250 °C effectively prevented the formation of internal cracks. The homogeneity of the blocks was confirmed by coring and measurements of true density, bulk density, porosity, and unconfined compressive strength. The robust reproducibility and similarity in physical and mechanical properties validate the viability of microwave sintering in manufacturing large and uniform blocks suitable for application as construction materials on the Moon.

Synthesis and characterization of enhanced polysulfone-based mixed matrix membranes containing ZSM-5 zeolite for protein and dye removal

In this paper, polysulfone (PSf)-based ultrafiltration (UF) mixed matrix membranes (MMMs) embedded with ZSM-5 zeolite nanoparticles were synthesized via the NIPS method. The membranes were characterized by FESEM, ATR-FTIR, AFM, and tensile analyses, along with contact angle, porosity, and mean pore size measurements. The FESEM images indicated that the addition of hydrophilic ZSM-5 nanoparticles has led to formation of more and larger finger-like macrovoids. Moreover, hydrophilicity and pure water flux (PWF) values were consequently augmented, which was also approved by water contact angle reduction. The maximum PWF was equal to 394.7 L m-2h−1 at 3 bar for the optimum MMM, containing 1 wt% ZSM-5 which is 125.4 % greater than the value for the bare membrane. In addition, filtration of the bovine serum albumin (BSA) protein and aqueous solutions of two organic dyes were carried out. The highest BSA flux value was obtained 217.9 L m-2h−1 for the optimum membrane, where the BSA rejection values were all greater than 98 %. Furthermore, the optimum MMM displayed the highest flux recovery ratio (FRR%) of 60.1 % as well as the dyes rejection values equal to 95.5 % and 74.1 % for reactive black 5 (RB 5) and reactive yellow 160 (RY 160), respectively, representing its great potential to be applied in various wastewater treatment applications.

Natural based hydrogels promote chondrogenic differentiation of human mesenchymal stem cells.

Background: The cartilage tissue lacks blood vessels, which is composed of chondrocytes and ECM. Due to this vessel-less structure, it is difficult to repair cartilage tissue damages. One of the new methods to repair cartilage damage is to use tissue engineering. In the present study, it was attempted to simulate a three-dimensional environment similar to the natural ECM of cartilage tissue by using hydrogels made of natural materials, including Chitosan and different ratios of Alginate. Material and methods: Chitosan, alginate and Chitosan/Alginate hydrogels were fabricated. Fourier Transform Infrared, XRD, swelling ratio, porosity measurement and degradation tests were applied to scaffolds characterization. After that, human adipose derived-mesenchymal stem cells (hADMSCs) were cultured on the hydrogels and then their viability and chondrogenic differentiation capacity were studied. Safranin O and Alcian blue staining, immunofluorescence staining and real time RT-PCR were used as analytical methods for chondrogenic differentiation potential evaluation of hADMSCs when cultured on the hydrogels. Results: The highest degradation rate was detected in Chitosan/Alginate (1:0.5) group The scaffold biocompatibility results revealed that the viability of the cells cultured on the hydrogels groups was not significantly different with the cells cultured in the control group. Safranin O staining, Alcian blue staining, immunofluorescence staining and real time PCR results revealed that the chondrogenic differentiation potential of the hADMSCs when grown on the Chitosan/Alginate hydrogel (1:0.5) was significantly higher than those cell grown on the other groups. Conclusion: Taken together, these results suggest that Chitosan/Alginate hydrogel (1:0.5) could be a promising candidate for cartilage tissue engineering applications.