Development, modelling and optimization of process parameters on the tensile strength of aluminum, reinforced with pumice and carbonated coal hybrid composites for brake disc application.

This study focuses on optimizing double stir casting process parameters to enhance the tensile strength of hybrid composites comprising aluminum alloy, brown pumice, and coal ash, intended for brake disc applications. Analytical techniques including X-ray fluorescence, X-ray diffraction, thermogravimetric analysis, and scanning electron microscopy were employed to characterize the composite constituents. The Taguchi method was utilized for experimental design and optimization to determine the optimal weight compositions of brown pumice and coal ash, as well as stir casting parameters (stirrer speed, pouring temperature, and stirring duration). Regression analysis was employed to develop a predictive mathematical model for the tensile strength of the hybrid composites and to assess the significance of process parameters. The optimized composite achieved a predicted tensile strength of 186.81 MPa and an experimental strength of 190.67 MPa using 7.5 vol% brown pumice, 2.5 vol% coal ash, a pouring temperature of 700 °C, stirrer speed of 500 rpm, and stirring duration of 10 min. This represents a 52.23% improvement over the as-cast aluminum alloy's tensile strength. Characterization results revealed that brown pumice and coal ash contain robust minerals (SiO2, Fe2O3, Al2O3) suitable for reinforcing metal matrices like aluminum, titanium, and magnesium. Thermogravimetric and differential thermal analyses demonstrated thermal stability up to 614.01 °C for the optimized composite, making it suitable for brake disc applications.

An integrated perspective on measuring cytokines to inform CAR-T bioprocessing.

Chimeric antigen receptor (CAR)-T cells are emerging as a generation-defining therapeutic however their manufacture remains a major barrier to meeting increased market demand. Monitoring critical quality attributes (CQAs) and critical process parameters (CPPs) during manufacture would vastly enrich acquired information related to the process and product, providing feedback to enable real-time decision making. Here we identify specific CAR-T cytokines as value-adding analytes and discuss their roles as plausible CPPs and CQAs. High sensitivity sensing technologies which can be easily integrated into manufacture workflows are essential to implement real-time monitoring of these cytokines. We therefore present biosensors as enabling technologies and evaluate recent advancements in cytokine detection in cell cultures, offering promising translatability to CAR-T biomanufacture. Finally, we outline emerging sensing technologies with future promise, and provide an overall outlook on existing gaps to implementation and the optimal sensing platform to enable cytokine monitoring in CAR-T biomanufacture.

[Extraction process optimization and link evaluation of Reyanning Mixture based on quality by design idea].

Reyanning Mixture is one of the superior Chinese patent medicine varieties of "Qin medicine". Based on the idea of quality by design(QbD), the extraction process of the Reyanning Mixture was optimized. The caffeic acid, polydatin, resveratrol, and emodin were used as critical quality attributes(CQAs). The material-liquid ratio, extraction temperature, and extraction time were taken as critical process parameters(CPPs) by the Plackett-Burman test. The mathematical model was established by the star design-effect surface method, and the design space was constructed and verified. The optimal extraction process of the Reyanning Mixture was obtained as follows: material-liquid ratio of 11.84 g·mL~(-1), extraction temperature at 81 ℃, and two extractions. A partial least-square(PLS) quantitative model for CQAs was established by using near-infrared spectroscopy(NIRS) combined with high-performance liquid chromatography(HPLC) under the optimal extraction process. The results showed that the correlation coefficients of the correction set(R_c) and validation set(R_p) of the quantitative models of four CQAs were more than 0.9. The root mean square error of the correction set(RMSEC) were 0.744, 6.71, 3.95, and 1.53 µg·mL~(-1), respectively, and the root mean square error of the validation set(RMSEP) were 0.709, 5.88, 2.92, and 1.59 µg·mL~(-1), respectively. Therefore, the optimized extraction process of the Reyanning Mixture is reasonable, feasible, stable, and reliable. The NIRS quantitative model has a good prediction, which can be used for the rapid content determination of CQAs during extraction. They can provide an experimental basis for the process research and quality control of Reyanning Mixture.

Determination of Residual Stresses in 3D-Printed Polymer Parts.

This paper presents the results of an investigation of the possibility of the reliable determination of the residual stress-strain state in polymers and composites using a combination of bridge curvature, optical scanning, and finite element methods. A three-factor experiment was conducted to determine the strength of printed PLA plastic products. The effect of the residual stresses on the strength of the printed products was evaluated. By comparing the values of the same strength stresses, a relationship between the nature of the stresses and the strength of the samples was found. A tendency of the negative influence of tensile stresses and the opposite strengthening effect of compressive stresses was obvious, so at the same values of tensile strength, the value of residual stress of 42.9 MPa is lower than that of the fibre compression at the value of 88.9 MPa. The proposed new methods of the residual stress determination allow obtaining a complete picture of the stressed state of the material in the investigated areas of the products. This may be necessary in confirming the calculated models of the residual stress-strain state, clarifying the strength criteria and assessing the quality of the selected technological modes of manufacturing the products.

The Influence of Laser Remelting Parameters on the Surface Quality of Copper.

In order to improve the surface quality of copper after laser remelting, this article took laser frequency, pulse width, and energy density as the research objects and used scanning electron microscopy (SEM), a laser confocal three-dimensional measurement instrument, hardness tester, and friction and wear measurement instrument to study the surface morphology, surface roughness, microhardness, and wear resistance of copper, respectively. The results indicate that the frequency, pulse width, and energy density of laser remelting could directly affect the surface quality of the sample, but the influence of frequency and pulse width was more significant. When the laser remelting frequency was 10 Hz, the pulse width was 10 ms, and the energy density was 132.69 J/mm2, the sample exhibited good surface morphology, roughness, and wear resistance. The relevant research in this article can provide a good reference for the laser surface treatment of copper-based materials.

Analysis of the effect of vibrational stress relief process parameters on 2024Aluminium alloy.

In principle, after all manufacturing processes are performed, a set of residual stresses occur in the product that have their particular distribution given the manufacturing process performed. The residual stresses must be removed to achieve the desired dimensional accuracy and quality. Among stress-relieving processes performed for a piece following the manufacturing process, we can refer to thermal and vibratory stress relief (VSR). Both methods perform the same function as they enter a part or all of a piece into the plastic phase, causing a fracture of residual stresses to be released with local plastic deformations. The process is as follows: The stress induced by thermal or vibratory loads is added to the residual stresses and exceeds the yield stress. This research, which is focused on VSR, aims to evaluate the effect of the main parameters of the VSR method, including load amplitude or amount, load application frequency, and cycle numbers. The general trend of the problem is that the VSR process is performed for a piece with residual stress, and the effect of the abovementioned parameters on reducing its residual stresses is evaluated.

Ultra-early prediction of the process parameters of coal chemical production.

Most accidents in a chemical process are caused by abnormal or deviations of the process parameters, and the existing research is focused on short-term prediction. When the early warning time is advanced, many false and missing alarms will occur in the system, which will cause certain problems for on-site personnel; how to ensure the accuracy of early warning as much as possible while the early warning time is a technical problem requiring an urgent solution. In the present work, a bidirectional long short-term memory network (BiLSTM) model was established according to the temporal variation characteristics of process parameters, and the Whale optimization algorithm (WOA) was used to optimize the model's hyperparameters automatically. The predicted value was further constructed as a Modified Inverted Normal Loss Function (MINLF), and the probability of abnormal fluctuations of process parameters was calculated using the residual time theory. Finally, the WOA-BiLSTM-MINLF process parameter prediction model with inherent risk and trend risk was established, and the fluctuation process of the process parameters was transformed into dynamic risk values. The results show that the prediction model alarms 16 min ahead of distributed control systems (DCS), which can reserve enough time for operators to take safety protection measures in advance and prevent accidents.

Mechanical Properties of Raw Filaments and Printed Specimens: Effects of Fiber Reinforcements and Process Parameters.

Fused Deposition Modeling (FDM) is a well-established manufacturing method for producing both prototype and functional components. This study investigates the mechanical properties of FDM components by material and process-related influencing variables. Tensile tests were conducted on seven different materials in their raw filament form, two of which were fiber-reinforced, to analyze their material-related influence. To cover a wide range from standard to advanced materials relevant for load-carrying components as well as their respective variations, polylactic acid (PLA), 30% wood-fiber-reinforced PLA, acrylonitrile butadiene styrene (ABS), polycarbonate (PC), a blend of ABS and PC, Nylon, and 30% glass-fiber-reinforced Nylon were selected. The process-related influencing variables were studied using the following process parameters: layer thickness, nozzle diameter, build orientation, nozzle temperature, infill density and pattern, and raster angle. The first test series revealed that the addition of wood fibers significantly worsened the mechanical behavior of PLA due to the lack of fiber bonding to the matrix and significant pore formation. The polymer blend of ABS and PC only showed improvements in stiffness. Significant strength and stiffness improvements were found by embedding glass fibers in Nylon, despite partially poor fiber-matrix bonding. The materials with the best properties were selected for the process parameter analysis. When examining the impact of layer thickness on part strength, a clear correlation was evident. Smaller layer thicknesses resulted in higher strength, while stiffness did not appear to be affected. Conversely, larger nozzle diameters and lower nozzle temperatures only positively impacted stiffness, with little effect on strength. The part orientation did alter the fracture behavior of the test specimens. Although an on-edge orientation resulted in higher stiffness, it failed at lower stresses. Higher infill densities and infill patterns aligned with the load direction led to the best mechanical results. The raster angle had a significant impact on the behavior of the printed bodies. An alternating raster angle resulted in lower strengths and stiffness compared to a unidirectional raster angle. However, it also caused significant stretching due to the rotation of the beads.

Optimization of Membrane Condenser Process with PTFE Hollow Fiber Membrane.

A membrane condenser (MC) is a novel membrane separation technology that utilizes the hydrophobic nature of porous membranes to capture water vapor from humid gas. Factors such as temperature, pressure, flow rate, and gas composition entering the membrane condenser play a crucial role in water recovery efficiency. This study utilized hydrophobic polytetrafluoroethylene (PTFE) hollow fiber membranes to create multiple identical membrane modules. This research investigated the impact of temperature, flow rate, pressure on the intake side, gas flow on the cooling side, membrane area, and other variables on the performance of the membrane condenser process. This study compared water extraction efficiency under different conditions, focusing on feed flow temperature and sweeping flow. Results showed that at a temperature of 60 °C, the water recovery rate was 24.7%, while a sweep gas flow rate of 4 L/min resulted in a recovery rate of 22.7%. The efficiency of the membrane condenser decreased with higher feed flow rates but increased with larger membrane areas. A proportional relationship between inlet flow and membrane area was observed, suggesting an optimal range of 0.51-0.67 cm/s for both parameters. These findings offer valuable insights for the practical implementation of hydrophobic membrane-based membrane condenser technology.

Manufacturing process of liposomal Formation: A coarse-grained molecular dynamics simulation.

A method of producing liposomes has been previously developed using a continuous manufacturing technology that involves a co-axial turbulent jet in co-flow. In this study, coarse-grained molecular dynamics (CG-MD) simulations were used to gain a deeper understanding of how the self-assembly process of liposomes is affected by the material attributes (such as the concentration of ethanol) and the process parameters (such as temperature), while also providing detailed information on a nano-scale molecular level. Specifically, the CG-MD simulations yield a comprehensive internal view of the structure and formation mechanisms of liposomes containing DPPC, DPPG, and cholesterol molecules. The importance of this work is that structural details on the molecular level are proposed, and such detail is not possible to obtain through experimental studies alone. The assessment of structural properties, including the area per lipid, diffusion coefficient, and order parameters, indicated that a thicker bilayer was observed at higher ethanol concentrations, while a thinner bilayer was present at higher temperatures. These conditions led to more water penetrating the interior of the bilayer and an unstable structure, as indicated by a larger contact area between lipids and water, and a higher coefficient of lipid lateral diffusion. However, stable liposomes were found through these evaluations at lower ethanol concentrations and/or lower process temperatures. Furthermore, the CG-MD model was further compared and validated with experimental and computational data including liposomal bilayer thickness and area per lipid measurements.

Investigation and Prediction of Nano-Silver Line Quality upon Various Process Parameters in Inkjet Printing Process Based on an Experimental Method.

As an emerging additive manufacturing technology, inkjet printing has been increasingly applied in microelectronics field. However, due to the impacting and rebounding behaviors of conductive ink droplets impinging onto flat substrates, it is challenging to fabricate conductive lines with desired quality, such as suitable line width and line thickness, and matching resistance when it is used for interconnecting multifarious electronic components if there is not a proper configuration of operating parameters. To address this research gap, this article aims to investigate the effect of process parameters on the quality of conductive lines, including the platform temperature, printing speed, number of layers, and delay time (droplet interarrival time), are selected to conduct a full factorial experiment. First, the approximate parameter ranges for ensuring the continuity of conductive lines are determined. Second, this study analyzes the interactive effect among process parameters on line quality. Third, an artificial neural network (ANN) is constructed to predict the quality of printed lines. Results show that the line width does not increase with an increased number of layers, while the line thickness shows an increasing trend. The low resistance and high aspect ratio of printed line are achieved by printing 5 layers with the platform temperature of 70°C, the delay time of 12.2 ms, and the printing speed of 1139.39 mm/min. Moreover, the ANN model can be used to predict line width and line thickness with excellent performance, except for the resistance due to the irregular line edge. This study provides a useful guide for the selection of appropriate printing parameters to realize a diverse range of quality properties for 3D printed conductive lines in integrated circuits.

3D Printing onto Textiles: A Systematic Analysis of the Adhesion Studies.

The article reviews the literature focused on investigating the adhesion strength between the 3D-printed polymers and the textile substrates, and its dependence on different factors related to materials, printing parameters, and fabrics type and structure. 3D printing (3DP) onto textiles is a domain in expansion as it allows developing products with new functionalities by gathering the advantages of design freedom, tailor-fit, comfort, variety, and mass customization provided by both the textiles and the additive manufacturing technology. In this context, it becomes important to document and understand how the adherence of different 3D-printed molten polymer to diverse textiles substrates can be improved for obtaining products more resistant to specific conditions, such as washing, wear, or ironing. Following a systematic search of electronic databases, 28 articles were selected for the full-text read and data extraction. The summarized information was grouped per 3DP material and analyzed factors, and then discussed in terms of variables influencing the adherence, including pretreatments and post-treatments applied to fabrics or 3D-printed onto fabrics specimens and objects. A case study of a customized polylactic acid-cotton-elastane wrist-hand orthosis is also presented to exemplify the modality in which the information synthetized in this review can be used in the development process of a new product.

Response Surface Methodology Optimization of Resistance Welding Process for Unidirectional Carbon Fiber/PPS Composites.

The use of thermoplastic composites (TPCs) as one of the lightweight solutions will inevitably encounter problems in connection. Resistance welding has the characteristics of high strength, simplicity, and high reliability, and is considered a very potential hot-melt connection technology. The resistance welding technology of unidirectional carbon fiber-reinforced polyphenylene sulfide composites (UCF/PPS) was systematically studied. The experimental results show that the 100-mesh brass mesh has the best resin wetting effect and heating efficiency, and the PPS/oxidized 100-mesh brass mesh composite resistance element (Ox-RE/PPS) has the highest welding strength. The welding failure mode changes from interface failure and RE failure to interlayer structure damage and fiber fracture. The single-factor experimental results show that the maximum welding strength is reached at 310 °C, 1.15 MPa, and 120 kW/m2. According to the conclusion of the single-factor experiment, the Box-Behnken method was further used to design a three-factor, three-level experiment, and a quadratic regression model was established according to the test results. The results of variance analysis, fitting curve analysis, and perturbation plot analysis proved that the model had high fitting and prediction abilities. From the 3D surface diagram analysis, the influence of power density is the largest, and the interaction between welding temperature and power density is the most significant. Combined with the analysis of Design Expert 13 software, the optimal range of process parameters was obtained as follows: welding temperature 313-314 °C, welding pressure 1.04-1.2 MPa, and power density 124-128 kW/m2. The average strength of resistance welding joints prepared in the optimal range of process parameters was 13.58 MPa.

QbD Assisted Development of a Compartment and Sequential Drug Delivery System for Periodontotherapy.

Periodontitis, the burgeoning disease, is at an alarming stage. Although this has triggered dedicated research in this area, as the disease itself demands a multi-component therapy, there is an unmet need for a compartment and sequential drug delivery system to ameliorate disease symptoms completely. The hypothesized work consists of multitherapeutic agents such as an antibiotic, a COX-II inhibitor, an MMP inhibitor, and a bone regenerating agent in an insitu gel. However, for the development of the system, as mentioned above, a thorough investigation at each stage is necessary; therefore, the quality-by-design approach was adopted. Furthermore, the current work is a pursuit of studying the quality by design aspects for the fabrication of a compartment system, i.e., in-situ gel for periodontal delivery. The proposed system in-situ gel consists of antibiotic and nano-encapsulating microcapsules. Furthermore, the microcapsules contain a COX-II inhibitor and nanoparticles of MMP inhibitor and bone regenerating agent for complete amelioration of periodontitis. To develop the system as per the QbD approach, the first initial trials and runs were conducted, which helped to decide the quality target product profile (QTPP). However, based on QTPP, critical quality attributes (CQA), critical process parameters (CPP), and critical material attributes (CMAs) were decided for each stage product, i.e., in-situ gel, microcapsules, and nanoparticles. To assess the influence of CPPs and CMAs on CQAs, Pareto charts were constructed, and various risks, along with possible failure modes were studied. In conclusion, the above work will serve as a well-designed scientific mouthpiece for developing a compartment system for periodontotherapy.

Quality by Design Perspective for Designing Foam-based Formulation: Current State of Art.

Foam-based delivery systems contain one or more active ingredients and dispersed solid or liquid components that transform into gaseous form when the valve is actuated. Foams are an attractive and effective delivery approach for medical, cosmetic, and pharmaceutical uses. The foams-based delivery systems are gaining attention due to ease of application as they allow direct application onto the affected area of skin without using any applicator or finger, hence increasing the compliance and satisfaction of the patients. In order to develop foam-based delivery systems with desired qualities, it is vital to understand which type of material and process parameters impact the quality features of foams and which methodologies may be utilized to investigate foams. For this purpose, Quality-by-Design (QbD) approach is used. It aids in achieving quality-based development during the development process by employing the QbD concept. The critical material attributes (CMAs) and critical process parameters (CPPs) were discovered through the first risk assessment to ensure the requisite critical quality attributes (CQAs). During the initial risk assessment, the high-risk CQAs were identified, which affect the foam characteristics. In this review, the authors discussed the various CMAs, CPPs, CQAs, and risk factors associated in order to develop an ideal foam-based formulation with desired characteristics.

Process Parameter Optimization for CO2 Laser Polishing of Fused Silica Using the Taguchi Method.

Fused silica was polished to a high quality by a CO2 laser beam with a rapid scanning rate. The rapid scanning rate produced a line laser heat source, resulting in a "polishing line" during the polishing process. The Taguchi method was used to evaluate the comprehensive influence of polishing process parameters on the polishing qualities. Four factors, namely the length of laser reciprocating scanning (A), laser beam scanning speed (B), feed speed (C), and defocusing amount (D), were investigated in this study. The optimal process parameter combination (A1B1C1D1) was obtained. The surface roughness of fused silica was reduced from Ra = 0.157 µm to 0.005 µm. Through analysis of variance (ANOVA), it was found that laser beam scanning speed (B) had a significant influence on the polishing quality. The interaction of the two factors plays a decisive role in the determination of the best process parameters, and the influence of other multi-factor interaction can be ignored; the interaction between A × B is the largest, with a contribution of 42.69%.

Continuous direct compression of a commercially batch-manufactured tablet formulation with two different processing lines.

The transfer from batch-based to continuous tablet manufacturing increases the quality and efficiency of processes. Nonetheless, as in the development of a batch process, the continuous process design requires optimization studies to ensure a robust process. In this study, processing of a commercially batch-manufactured tablet product was tested with two continuous direct compression lines while keeping the original formulation composition and tablet quality requirements. Tableting runs were conducted with different values of process parameters. Changes in parameter settings were found to cause differences in tablet properties. Most of these quality properties could be controlled and maintained within the set limits effortlessly already at this stage of studies. However, the API content and content uniformity seemed to require more investigation. The observed content uniformity challenges were traced to individual tablets with a high amount of API. This was suspected to be caused by API micro-agglomerates since tablet weight variability did not explain the issue. This could be solved by adding a mill between two blenders in the process line. Overall, this case study produced promising results with both tested manufacturing lines since many tablet properties complied with the test result limits without optimization of process parameter settings.

Sorption capacity of Eichhornia crassipes (Mart.) Solms for zinc removal from electroplating industry wastewater.

Various industrial operations in the dye, fertilizer, pesticide, battery, mining, and chemical industries have been associated with releasing heavy metals in wastewater, such as lead, zinc, copper, arsenic, cadmium, chromium, nickel, and mercury. These metals are dangerous to aquatic life as well as to humans, who may consume them directly or indirectly. Therefore, before being released into open water and land resources, it is necessary to minimize the concentration of toxic ions below the discharge limit. This study used Eichhornia crassipes (Mart.) Solms to remove zinc from wastewater from the electroplating industry in a constructed wetland. Experimental investigations were conducted for removing zinc ions from electroplating industry wastewater using various process parameters such as nutrient dosages, dilution ratios, potential of hydrogen ions, biomasses, and contact times. The outcome of this study revealed that the maximum zinc removal percentage in electroplating industrial wastewater was found for the optimum nutrient dosages of 60 g, dilution ratios of 10, potential hydrogen ion levels of 8, and biomass amounts of 100 g. The maximum zinc removal by Eichhornia crassipes (Mart.) Solms was found to be 88.3 ± 0.6 and 93.4 ± 0.4% at the optimum parameter values for the electroplating industry wastewater and the aqueous solution, respectively, against the optimum contact time of 22 days. This study suggests using this phytoremediation technology to remove all pollutants from industrial wastewater in general, not just wastewater from the electroplating industry.

Surface Roughness of Interior Fine Flow Channels in Selective Laser Melted Ti-6Al-4V Alloy Components.

A challenge remains in achieving adequate surface roughness of SLM fabricated interior channels, which is crucial for fuel delivery in the space industry. This study investigated the surface roughness of interior fine flow channels (1 mm diameter) embedded in SLM fabricated TC4 alloy space components. A machine learning approach identified layer thickness as a significant factor affecting interior channel surface roughness, with an importance score of 1.184, followed by scan speed and laser power with scores of 0.758 and 0.512, respectively. The roughness resulted from thin layer thickness of 20 µm, predominantly formed through powder adherence, while from thicker layer of 50 µm, the roughness was mainly due to the stair step effect. Slow scan speeds increased melt pools solidification time at roof overhangs, causing molten metal to sag under gravity. Higher laser power increased melt pools temperature and led to dross formation at roof overhangs. Smaller hatch spaces increased roughness due to overlapping of melt tracks, while larger hatch spaces reduced surface roughness but led to decreased part density. The surface roughness was recorded at 34 µm for roof areas and 26.15 µm for floor areas. These findings contribute to potential adoption of TC4 alloy components in the space industry.

Process Investigation on Robust Electrospinning of Non-Aligned and Aligned Polyvinylidene Fluoride Nanofiber Mats for Flexible Piezoelectric Sensors.

Polyvinylidene fluoride (PVDF) nanofiber mats have played a significant role in wearable electronic devices that have been in great demand in recent decades. Although manifold PVDFbased freely stacked or well-aligned nanofiber mats created via the electrospinning process have been demonstrated to achieve multisensory capabilities with high sensitivity and long detection range, rarely have any of them proved their ability with a stable process and accurate processing parameters. In this work, we successfully developed freely stacked and well-aligned PVDF nanofiber mats with diameters ranging from micrometers to nanometers, providing stable performance for wearable electronic devices. Through in-depth investigations into material preparation, electrospinning, and fiber collection processes, we revealed the relationship between the nanofiber morphology, ß-phase fraction, and piezoelectric output with various process parameters. Characterized by analytical methods, we have established a mature, reliable nanofiber mat fabrication system capable of mass-producing PVDF nanofibers with the required diameter and consistent properties. At 18 kV voltage and 60% RH humidity, the uniformity of the fiber diameter and ß-phase content was maintained in a favorable range. When the drum speed increased to 2000 r/s, the fiber orientation and ß-phase content increased. We assembled aligned PVDF nanofiber mats with conductive fabric in a flexible piezoelectric sensor that successfully monitored different body movements and produced an output voltage of 0.1 V. This study provides the necessary process parameters for the large-scale production of high-quality PVDF nanofiber mats and provides clear guidance for beginners in the field of nanofiber mat manufacturing.