Process Parameters Research Articles

Development, characterization, and assessment of PLAROsomal vesicular system of curcumin for enhanced stability and therapeutic efficacy

Abstract Background Curcumin (CUR) is a natural polyphenol and one of the key phytoconstituents found in the rhizomes of Curcuma Longa. It exhibits various pharmacological properties, encompassing antioxidant, anticancer effects, antiseptic, and anti-inflammatory, among several others. A significant drawback of using CUR is its limited bioavailability, which primarily depends on gut microorganisms responsible for converting it into its bioavailable form. Therefore, the contemporary study intended to formulate a novel PLAROsomal vesicular delivery of CUR, i.e., CUR-PLAROsomes employing a design of experiments approach to examine the influence of various process parameters, such as particle size and drug percentage release. Result The prepared CUR-PLAROsomes were characterized for their physicochemical properties using various hyphenated tools. The CUR-PLAROsomes exhibited sizes ranging from 40 to 300 nm, and the optimized batch demonstrated a drug entrapment of 86.38 ± 0.22%. In-vitro anticancer studies were conducted using human colorectal adenocarcinoma cells (COLO320DM) and human breast adenocarcinoma (MCF-7). CUR-PLAROsomes exhibited significant in-vivo anti-inflammatory potential against carrageenan-induced paw edema. CUR-PLAROsomes were more potent against COLO320DM and MCF-7 cell lines, even at lower concentrations, than pure CUR. Conclusion Furthermore, based on the observations, it exhibits potential as an anti-inflammatory agent, suggesting that PLAROsomes are an effective vesicular drug delivery system. Highlights Newly introduced PLARosome is a next generation of Liposomes which have gain popularity owing to its better adaptability to overcome leakage problem of vesicular drug delivery system. This is the pioneer attempt to prepare Curcumin-loaded PLARosome as an anti-cancer and anti-inflammatory activity. Nano size of the PLAROsomes may contribute to enhance the efficacy of Curcumin as a target specific drug delivery system. Site specific delivery of phytoconstituents is possible by use of PLAROsomes as a novel drug delivery system. Graphical abstract

Damage Development in a Cellular Axisymmetric Tank Additive-Manufactured from Plastic Filament. Part 2. Experimental Studies of Damage to Cellular Shell Systems and the Dependence of Strength Characteristics on Process Parameters

Damage Development in a Cellular Axisymmetric Tank Additive-Manufactured from Plastic Filament. Part 2. Experimental Studies of Damage to Cellular Shell Systems and the Dependence of Strength Characteristics on Process Parameters

Minimization of melt-pool field variables fluctuation during selective laser melting of Ti6Al4V alloy through computational investigation

Abstract The optimization of selective laser melting (SLM) process parameters for a new material through experiments is a time-consuming and challenging process. Computational approaches, on the other hand, offer an economical and relatively faster approach to effectively predict the influences of process factors on the behaviors of the field variables of SLM process. In this work, multiphysics models built using COMSOL software were used to carry out optimization of SLM-Ti6Al4V processes through a single-level setup method followed by a parametric sweep optimization (PSO) approach. The simulated results of the melt pool field variables obtained from both approaches were compared. In the PSO approach, the melt pool velocity was found to have 14.3% higher flow and 78.8% reduction in the transient velocity fluctuation amplitude within the melt pool region. The average transient temperature of the melt pool region was found to have 5.9% increase and 36.4% reduction in the average fluctuation amplitude along the solidus and peak points, respectively. On the other hand, the associated temperature gradient was found to have a fluctuation amplitude reduction of 15.3% at the maximum side of the melt pool region. Finally, the optimal solutions of the melt pool field variables obtained from the PSO were compared with published data to verified the approach. The reductions in temperature and thermal gradient results were found by 18.3% and 28.5% respectively in the melt pool region of the current SLM-Ti6Al4V process and, hence, validating the predictions of the PSO technique.

Optimization of process parameters of catalytic pyrolysis using natural zeolite and synthetic zeolites on yield of plastic oil through response surface methodology

Optimization of process parameters of catalytic pyrolysis using natural zeolite and synthetic zeolites on yield of plastic oil through response surface methodology

Identification of Cause–Effect Relationships between Process Parameters and the Film Formation in the Semidry Electrode Production for Lithium‐Ion Batteries

Conventional electrode production for lithium‐ion batteries has high energy and plant space demand, due to the high solvent content of the slurry to be processed by slot die or doctor blade coating. By using the semidry electrode production, the solvent content is reduced by more than 50% compared to the conventional electrode production, decreasing energy demand and drying length. Regarding technology readiness level, the semidry electrode production is on the pilot scale, as the basic principles have been shown. However, many unknown cause–effect correlations exist between the process parameters and the product properties. This study aims to analyze process parameter variations and their influence on the geometric, electrochemical, and mechanical properties of the electrode. An experimental design is utilized to obtain statistically relevant conclusions. It is found that the first calender gap and the roller speed influence the mass loading and the porosity of the electrode. The roller speed significantly influences the ionic resistance within the electrode, which may be attributed to the used release foil.

Artificial Neural Network for Benchmarking the Dimensional Accuracy of the PLA Fused Flament Fabrication Process

Fused Deposition Modeling (FDM) is an additive manufacturing technique that uses a 3D printer to extrude molten filament through a nozzle, which moves along the X, Y, and Z axes to create parts with the desired geometry. FDM offers numerous advantages, especially for producing parts with complex shapes, due to its ability to enable rapid and cost-effective manufacturing compared to traditional methods. This study implemented an Artificial Neural Network (ANN) to optimize process parameters aimed at minimizing dimensional inaccuracies in the FDM process. Key parameters considered for optimization included the number of shells, infill percentage, and nozzle temperature. The ANN utilized three algorithms: Scaled Conjugate Gradient, Bayesian Regularization, and Levenberg-Marquardt. Model performance was evaluated based on dimensional deviations along the X and Y axes, with a hidden layer of 25 neurons. Among the algorithms, Scaled Conjugate Gradient provided the most accurate results in minimizing dimensional errors.

Physicochemical Investigations of Textile Wastewater and Process Parameter Optimization for Bio-decolorization of Congo Red Dye by Pseudomonas aeruginosa MT-2 Strain

Pollution caused by dyes is a major environmental threat, posing adverse impacts on humans, animals, and plants. Therefore, the remediation of such pollutants is essential to protect the environment. This study aimed to conduct physicochemical and bacteriological analyses of textile wastewater to isolate and identify potential native bacterial strains for the decolorization of Congo red dye. Physical and nutritional process parameters were optimized to achieve maximum decolorization. The biological and chemical oxygen demands of the analyzed textile waste water were found to be above the recommended limits. In this study, 19 Congo red -decolorizing bacteria were isolated, with one bacterial culture capable of growing at a higher dye concentration of 300 mg/L. This bacterium was characterized biochemically and genetically (using 16S rRNA sequencing) and identified as the Pseudomonas aeruginosa MT-2 strain. A maximum decolorization of 94.0% was achieved at an initial dye concentration of 150 mg/L, 35°C, and pH 8.0 under static conditions. The bacterial culture also showed resistance to heavy metals such as arsenic, lead, and chromium. The biodegradation of Congo red dye was confirmed through UV-vis spectral analysis and Fourier transform infrared spectrophotometry. The findings of this study demonstrate the high remediation potential of the MT-2 strain, making it suitable for possible use in dye biodecolorization at contaminated sites.

Advancements in Bamboo-Based Cushioning Material Manufacturing

The study focuses on producing cushioning packaging material from bamboo fibers. The effects of varying the surface treatment duration and the proportions of foaming agents, adhesives, plasticizers, cross-linking agents, and other components were analyzed in terms of foam density, foaming rate, elasticity, and bubble size. The optimal reagents and the ideal ratios for the different components were identified. The parameters for the foaming process were determined based on a high-efficiency, eco-friendly foaming mechanism. Impact testing was conducted to obtain curves for maximum acceleration versus static stress, dynamic stress versus strain, and dynamic buffering factor versus stress. The study examined the dynamic buffering performance as a function of drop height and compared it to other cushioning materials. The findings indicate that at a height of 450 mm, the bamboo pulp product exhibited a lower peak acceleration value than EPE and EPS in the stress range of 2.8-5.4 kPa, indicating superior cushioning performance under these conditions.

Multi-objective optimization in EDM of functionally graded Fe-Al using grey relational analysis

Abstract Functionally Graded Materials (FGMs) are multipurpose materials with a specific goal of managing changes in structural, thermal, or functional qualities. They feature a spatial variation in microstructure and/or composition. The current work prepared three layers of sample with different chemical compositions of Fe-Al FGM (50 Al-50 Fe, 45 Al-55 Fe, and 40 Al-60 Fe) at. % produced by powder metallurgy, then studied the machining behavior of these samples. The literature on the machining behavior of FGM was reviewed, and the influence of electrical discharge machine (EDM) process parameters such as voltage (V), current (I), pulse-on time, and pulse-off time on performance characteristics (material removal rate (MRR), tool wear rate (TWR), and surface roughness (Ra)) was investigated. The optimal machining settings for Fe-Al FGM samples will be ascertained by use of Grey Relational Analysis (GRA), which is based on the Taguchi approach, after an experimental investigation of the L18 orthogonal array design of trials. The GRA findings verify that V 140 volts, Ip10 A, Ton 100 μs, and Toff 75 μs is the optimal combination of process parameters. It has been found that the voltage is more significantly affected than the rest of the input parameters to obtain greater material removal rate (MRR) and lower tool wear rate (EWR) and surface roughness (Ra) through the response table. According to the study, choosing the right process parameters can improve the multi-performance feature.

Optimization strategy of computer numerical control machining process parameters in biomanufacturing mold

With the rapid development of biomanufacturing technology in the medical and pharmaceutical fields, the demand for high-precision and high-quality molds has surged. When Computer numerical control (CNC) machining biomanufacturing molds, the optimization of process parameters becomes the key to improve efficiency and quality. The purpose of this study is to explore the optimization strategy of CNC machining process parameters to achieve the best surface quality, dimensional accuracy and machining efficiency. Through literature review, the spindle speed, feed speed and cutting depth are selected as the key parameters, and the multi-objective optimization model is constructed by response surface method, which is solved by genetic algorithm. The experiment shows that the process parameters of CNC system in mold manufacturing are cutting speed 100 (m/min), feed rate 0.2 (mm/rev) and cutting depth 0.5 (mm), which will effectively reduce the manufacturing cost, and effectively control the alarm times within 35 times in different processing equipment, greatly reduce the risk. The optimization strategy can significantly improve the surface quality and productivity of the mold and reduce the cost. The comparative analysis verifies the effectiveness of the method, which provides new theoretical and technical support for CNC machining in the field of biomanufacturing.

Experimental investigation on in-situ laser-assisted mechanical ruling of single crystal silicon

Abstract In this paper, response surface methodology (RSM) was employed as a robust and convenient predictive tool to establish the correlation between process parameters of in situ laser-assisted mechanical ruling and the ductile-to-brittle transition of single-crystal silicon. The interaction effects among three factors laser power, ruling speed, and negative rake angle on the ductile-to-brittle transition of single-crystal silicon were investigated. The optimal combination of process parameters was determined to be a laser power of 30W, a ruling speed of 0.25 mm s−1, and a negative rake angle of 58°. Utilizing a self-assembled setup and the optimal process parameters, multiple processing experiments were conducted. The average error between the experimental and predicted values was found to be 2.8%.

Recent advances in the AlSi10Mg materials fabrication by selective laser melting: process parameters, optimization, low-velocity and ballistic impact responses

Recent advances in the AlSi10Mg materials fabrication by selective laser melting: process parameters, optimization, low-velocity and ballistic impact responses

Centrifugal Compressor Surge in Innovative Heat Pump: Fluid Dynamic and Vibrational Analysis

Abstract In the current energy scenario, it is necessary to reduce fossil fuel consumption to achieve the far-sighted and stringent decarbonization goals. To date, heat is mainly produced through fossil fuels. Alternatively, electrically driven heat pumps can exploit renewable power to recover environmental and waste heat, offering energy efficient and environmentally friendly heating and cooling for applications ranging from domestic and commercial buildings to process industries. For this reason, they are expected to play a primary role in complementing or displacing natural gas boilers in the residential and industrial sectors in the near future. Centrifugal compressors are already used as prime movers of the working fluid in heat pumps, thanks to their industrial replicability, compact size, affordable costs, and good performance in terms of efficiency and low noise. However, they are subject to instabilities such as surge and stall like any other dynamic compressor and these phenomena develop quite differently than in classic open-loop systems such as gas turbines. In fact, such peculiarity is mainly due to the closed-loop configuration with real gases in two-phase conditions, occurring in typical heat pump cycles. In addition, heat exchangers also contribute to make these phenomena different from what is commonly studied. Compressor surge in closed-loop heat pump systems has received lower attention than other applications by the engineering community, lacking dedicated experimental characterization, and clear exposition of the phenomenon. The aim of this paper is to experimentally investigate the behavior of a centrifugal compressor installed into an innovative close loop heat pump system under stable and unstable conditions from both vibrational and fluid-dynamic points of view. The impact of the main process parameters on the evolution of the instability is shown, highlighting how surge cycles change by varying system operating conditions. The energy contents of surge cycles and pressure fluctuations are highlighted, using data postprocessing techniques such as fast Fourier transform and phase locked average. The vibro-acoustic analysis enrich the comprehension of the phenomena. The experimental results shown in this paper can be a basis for the future development of validated mathematical models of closed-loop heat pumps systems equipped with dynamic compressors operating under stable and unstable operating conditions.

Process Parameters Optimization of Laser Cladding for HT200 with 316L Coating Based on Response Surface Method

Process Parameters Optimization of Laser Cladding for HT200 with 316L Coating Based on Response Surface Method

Analysis and Optimization of Cryogenic Distillation Systems: For Reducing Distillation Energy Consumption

AbstractCarbon capture utilization and storage‐enhanced oil recovery (EOR) is often considered the most promising technology for utilizing CO2. Cryogenic distillation is also viewed as the most reasonable separation option for handling CO2‐EOR gases, despite being an energy‐intensive process. The main challenge for this technology is energy loss. To overcome this challenge, one potential alternative is to optimize the system processes and parameters. This study proposes a new process to reduce distillation energy consumption by refluxing the distillate back to the distillation column. Operational parameter optimization was performed using the commercial simulator Aspen HYSYS for modeling and sensitivity analysis of process parameters using orthogonal experimental methods. The simulation results indicate that after optimization, the energy consumption in the distillation process decreased from 0.207 to 0.196 MJ kg−1, whereas the purity decreased slightly from 94.63 % to 94.52 %. However, the recovery increased from 97.8 % to 97.88 %, and the total energy consumption decreased from 0.772 to 0.761 MJ kg−1.

Optimization of Laser Based-Powder Bed Fusion Parameters for Controlled Porosity in Titanium Alloy Components

Laser based-powder bed fusion (LB-PBF) enables fast, efficient, and cost-effective production of high-performing products. While advanced functionalities are often derived from geometric complexity, the capability to tailor material properties also offers significant opportunities for technical innovation across many fields. This study explores the optimization of the LB-PBF process parameters for producing Ti6Al4V titanium alloy parts with controlled porosity. To this end, cuboid and lamellar samples were fabricated by systematically varying laser power, hatch distance, and layer thickness according to a full factorial Design of Experiments, and the resulting specimens were thoroughly characterized by analyzing envelope porosity, surface roughness and waviness, surface morphology, and surface area. A selection of specimens was further examined using small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS) to investigate the atomic structure and nanometric porosity of the material. The results demonstrated the possibility to finely control the porosity and surface characteristics of Ti6Al4V within specific LB-PBF process ranges. The pores were found to be mostly closed even for thin walls, while the surface roughness was recognized as the primary factor impacting the surface area. The lamellar samples obtained by exposing single scan tracks showed nearly an order-of-magnitude increase in both surface area and pore volume, thereby laying the groundwork for the production of parts with optimized porosity.

Behavior of plasma parameters under mirror and cusp magnetic fields in DC glow discharge – a numerical study

Abstract The plasma parameters in DC glow discharge can easily be controlled by externally applied magnetic field without disturbing internal / built-in process parameters. Though several works have been carried out to study the influence of the magnetic field at different configurations on the plasma parameters, a complete understanding on the behaviour of the plasma discharge under the mirror and cusp fields could not be achieved. Further studies on the same are needed to improve the efficiency of the DC glow discharge system for existing applications and to find the new applications. In this work, a 2D axis-symmetric non-equilibrium plasma model with drift-diffusion approach is developed to study the characteristics of the plasma in DC glow discharge through various plasma parameters under mirror and cusp fields. The effects of current and position of magnetic coils on electric potential, ionization rate, electron temperature and electron number density are predicted and discussed. The distribution of electron number density at various coil currents and positions under both mirror and cusp fields are presented and the operating conditions favorable for applications in surface modification are suggested.

Conformally printed additively manufactured RF demonstrator for circuit compaction

Abstract Recently, there has been interest in applying Additive Manufacturing (AM) to RF and Microwave applications, especially in packaging of microelectronic devices. Additive packaging offers advantages of expanded functionality in restricted volume, through miniature, low-SWaP-C sensors, allowing for non-traditional form factors. In this work, design, fabrication, and characterization of a non-planar multi-material MMIC structure is presented to demonstrate significant footprint reduction and circuit compaction. Performance of a non-planar passive RF device and details of planar to non-planar AM connections for characterization of the transitions will be demonstrated. The work will present details of the design and fabrication of the non-planar structure, optimization of the process parameters for the Optomec 5-axis Aerosol Jet Printer for multi-material printing, and the results of the characterization and testing. RF measurements were conducted to demonstrate the functionality of the developed non-planar circuit and compared with simulations which showed good agreement. The results of this work show that fully additive approach is feasible for non-planar circuits, which will allow for footprint reduction, weight reduction, and achievement of novel form factors that are critical for microwave applications.

Classification-Based Parameter Optimization Approach of the Turning Process

The turning process is a widely used machining process, and its productivity has a significant impact on the cost and profit in industrial enterprises. Currently, it is difficult to effectively determine the optimum process parameters under complex conditions. To address this issue, a classification-based parameter optimization approach of the turning process is proposed in this paper, which aims to provide feasible optimization suggestions of process parameters and consists of a classification model and several optimization strategies. Specifically, the classification model is used to separate the whole complex process into different substages to reduce difficulties of the further optimization, and it achieves high accuracy and strong anti-interference in the identification of substages by integrating the advantages of an encoder-decoder framework, attention mechanism, and major voting. Additionally, during the optimization process of each substage, Dynamic Time Warping (DTW) and K-Nearest Neighbor (KNN) are utilized to eliminate the negative impact of cutting tool wear status on optimization results at first. Then, the envelope curve strategy and boxplot method succeed in the adaptive calculation of a parameter threshold and the detection of optimizable items. According to these optimization strategies, the proposed approach performs well in the provision of effective optimization suggestions. Ultimately, the proposed approach is verified by a bearing production line. Experimental results demonstrate that the proposed approach achieves a significant productivity improvement of 23.43% in the studied production line.

Advanced multi-nozzle electrohydrodynamic printing: mechanism, processing, and diverse applications at micro/nano-scale

Abstract Electrohydrodynamic (EHD) jet printing represents a novel micro/nano-scale additive manufacturing process that utilises a high-voltage induced electric field between the nozzle and the substrate to print micro/nanoscale structures. EHD printing is particularly advantageous for the fabrication on flexible or non-flat substrates and of large aspect ratio micro/nanostructures and composite multi-material structures. Despite this, EHD printing has yet to be fully industrialised due to its low throughput, which is primarily caused by the limitations of serial additive printing technology. The parallel multi-nozzle array-based process has become the most promising option for EHD printing to achieve large-scale printing by increasing the number of nozzles to realise multichannel parallel printing. This paper reviews the recent development of multi-nozzle EHD printing technology, analyses jet motion with multi-nozzle, explains the origins of the electric field crosstalk effect under multi-nozzle and discusses several widely used methods for overcoming it. This work also summarises the impact of different process parameters on multi-nozzle EHD printing and describes the current manufacturing process using multi-nozzle as well as the method by which they can be realised independently. In addition, it presents an additional significant utilisation of multi-nozzle printing aside from enhancing single-nozzle production efficiency, which is the production of composite phase change materials through multi-nozzle. Finally, the future direction of multi-nozzle EHD printing development is discussed and envisioned.