Optimal Process Research Articles

Explainable machine learning-driven predictive performance and process parameter optimization for caproic acid production

In this study, four machine learning (ML) prediction models were developed to predict and optimize the production performance of caproic acid based on substrates, products, and process parameters. The XGBoost outperformed others, with a high R2 of 0.998 on the training set and 0.885 on the test set. Feature importance analysis revealed hydraulic retention time (HRT) and butyric acid concentration are decisive. The SHAP method offered profound insights into the interplay and cumulative effects of substrate composition, identified the synergistic effects between butyric acid and lactic acid, and emphasized adding glucose can benefit caproic with lactic acid co-fermentation. By integrating the Adaptive Variation Particle Swarm Optimization (AVPSO) algorithm, the optimal process conditions to achieve a maximum caproic acid production of 8.64 g/L was obtained. This study not only advances caproic acid production but contributes a versatile ML-driven strategy applicable to bioprocess optimizations, potentially transformative for sustainable and economically viable bioproduction.

Optimization of measured mechanical characteristics of selective microwave hybrid heating processed Inconel 625/ SS 304 weldments using multi-objective JAYA algorithm coupled with multi-attributes decision making R-method

This work focuses on the joining of Inconel-625/SS-304 using selective microwave hybrid heating (SMHH) technique. Input power, filler powder particle size, separator, and susceptor size are considered for experimentation according to the Definitive Screening Design. The multi-objectives measured are UTS, FS, and microhardness. XRD results show the intermetallic/secondary phases, and FESEM micrographs show the metallurgical bonding occurs between base metal and filler. The joint and interface region had an average microhardness of 204 ± 10 HV and 342 ± 18 HV, respectively. The UTS and FS of the weldments measured to 550 MPa and 805 MPa. MOJAYA technique is utilized for multi-objective optimization, and R-method determined the optimal process parameters. The optimal process parameters found to 2.2 kW, 25 μm powder, 120 grit and 0.804 mm separator. The confirmation test reveals UTS − 566 MPa, FS − 903 MPa, and microhardness − 365 HV, which closely matched with predicted observations.

CFD modeling of spray drying of fresh whey: Influence of inlet air temperature on drying, fluid dynamics, and performance indicators

Whey is a very perishable food and a potent source of protein. It might be more commercialized through the process of spray drying, which would enhance its shelf life. No CFD computational models applied to the drying of fresh sweet whey have been reported in the literature to investigate transport phenomena in spray dryers and to predict crucial design parameters such as deposition, powder recovery, and drying efficiency. Using an Eulerian-Langragean technique, the behavior of multiphase flow as well as heat and mass transfer were investigated. The influence of the inlet air temperature was evaluated in relation to the velocity profiles of the continuous and discrete phases, the residence time distribution, the particle diameter formed, the air temperature near the injection zone, the particle temperature, and the mass fraction of evaporated water. Furthermore, performance parameters such as powder recovery, particle deposition, and drying efficiency were projected for varied air inlet temperatures. The velocity, residence time, and particle size distribution patterns were similar for the different air inlet temperatures. Greater variations might be noticed in the injection zone, especially in the temperature and mass fraction profiles. The lowest drying temperature resulted in the lowest particle deposition and the best thermal efficiency, making it the optimal process condition. This investigation can serve as a benchmark for the design of optimized spray dryers with greater thermal efficiency and yield to produce powdered whey.

Recovery of Li from waste Li-containing Al electrolytes with high F and Na contents by using a CaO roasting–water leaching process

With the increasing demand for Li, the recovery of Li from solid waste, such as Li-containing Al electrolytes, is receiving growing attention. However, Li-containing Al electrolytes often contain large amounts of F, leading to environmental pollution. Herein, a new method for preparing water-soluble Li salt from waste Li-containing Al electrolytes with high F and Na contents is proposed based on CaO roasting and water leaching. The effects of different roasting and leaching conditions on the Li leaching efficiency and reaction pathway were systematically investigated. Under the optimum processing conditions, the Li leaching efficiency reached 98%, while those of Na and F were 98.41% and 0.24%, respectively. Phase evolution analysis showed that the addition of CaO promoted the conversion of LiF and Na2LiAlF6 to Li2O, whereas F entered the slag phase as CaF2, which could be reused as a raw material for steel refinement. Overall, this study proposes an efficient and environmentally friendly method for the treatment and resource utilization of waste Al electrolytes with high F and Na contents.

Proposal of trapezoidal vibration-assisted diamond cutting for ductile-regime machining of brittle crystals: A case study on KDP crystal

Despite various vibration-assisted cutting techniques have been utilized to increase the machining performances of brittle materials, the highly dynamic variations of cutting process quantities lead to the complicated brittle-ductile transition (BDT) mechanism and the formation of undesired vibration marks on the machined surfaces. In this paper, a novel ultra-precision vibration-assisted cutting process, named trapezoidal modulation diamond cutting (TMDC), is firstly proposed for ductile-regime machining of brittle materials with significantly increased BDT cutting depth. By imposing a dedicate trapezoidal locus to the diamond tool, the unique invariable uncut chip thickness and cutting states were achieved for realizing stable vibration-assisted cutting without the formations of vibration marks. Systematic cutting experiments of KDP crystals were carried out to comprehensively investigate the influences of different process parameters on the machining performances of TMDC process. In addition, the underlying mechanisms of machining performance improvements have been discussed under the different combinations of process parameters, based on which the guidelines for optimal process parameter selection are given for increasing the BDT cutting depths. The outcomes of this study contribute to not only improving the ductile machining efficiency and machining quality of KDP crystals, but also help to deepen the understandings of BDT mechanism during vibration-assisted diamond cutting of common brittle materials.

Computational modeling and virtual analysis using a moving heat source to join AZ61A and AA7075 alloys with the application of a titanium alloy interlayer

Laser beam welding (LBW) uses a concentrated laser beam to fuse materials, providing benefits such as a smaller heat-affected zone (HAZ), speed, accuracy, adaptability across multiple materials, and seamless adoption into automation processes. Achieving optimal weld quality with LBW remains difficult due to the need to select the appropriate welding process variables and proper interlayer between dissimilar materials. Due to the high cost and safety risks to operators and equipment in LBW, it is challenging to use the practical experiment. Additionally, welding materials with high thermal conductivity and lower melting temperatures, such as AZ61A and AA7075, is a considerable challenge. Previous research focused on process parameters in laser beam welding of various metals, but not enough consideration has been given to the effect of a titanium interlayer on AA7075 and AZ61A using virtual data. This study aims to fill these gaps by using simulation data to assess the effects of process parameters and the titanium interlayer during LBW of dissimilar materials. A backpropagation neural network with the gradient descent learning rule was used for optimization, and a central composite design was used to predict the optimal process parameter interaction. The result indicates the optimum equivalent strain is obtained at the values of beam radius between 4.5 to 5 mm. The maximum equivalent stress reached during welding speed is between 4 to 4.5 mm/s. The maximum residual stress was obtained at the number of segments of 160. The predicted maximum and average anticipated errors for peak temperature are 0.1655 % and 0.0210 %, while for residual stress it is computed as 0.1766 % and 0.0754 %. The Ti-interlayer in magnesium and aluminum laser welding reduces peak temperatures, allows for uniform energy distribution, minimizes localized heating, and enhances weld quality while lowering residual stress.

ANN modeling of tincal ore dehydration

Abstract Tincal ore is a preferred material in many industrial applications, especially without water. It is important to dehydrate boron ores so that they can be used in materials engineering. For this purpose, some heat treatments must be carried out. Heat treatments are associated with additional costs. It is possible to model heat treatments using artificial intelligence methods, determine optimal process conditions and achieve the desired results with much less processing effort. In this study, a dehydration process was first carried out to dehydrate tincal ore and ANN (artificial neural networks) modeling of this process was investigated using the parameters of temperature, time and amount of ore. The possibility of achieving the desired H2O, B2O3 and Na2O concentration values in the dewatering process in the shortest time and by the shortest route was investigated using the ANN model. In the modeling, a single model was designed for the changes in concentrations and this model was trained separately for each. The result of the modeling was that the R 2 values for all three models were close to each other and were approximately 0.98. It was thus shown that the ANN method can be successfully modeled for dewatering processes.

Preparation of Complex Polysaccharide Gels with Zanthoxylum bungeanum Essential Oil and Their Application in Fish Preservation.

In this study, novel functional ZEO-complex gels were prepared using sodium alginate, inulin, grape seed extract (GSE), and Zanthoxylum bungeanum essential oil (ZEO) as the primary raw materials. The effect of the addition of inulin, GSE, and ZEO on water vapor permeability (WVP), tensile strength (TS), and elongation at break (EAB) of ZEO-complex polysaccharide gels was investigated. A comprehensive score (Y) for evaluating the characteristics of ZEO-complex polysaccharide gels was established by principal component analysis. MATLAB analysis and box-Behnken design describe each factor's four-dimensional and three-dimensional interactions. It was found that Y could reach the maximum value when the ZEO addition was at a moderate level (C = 2%). The optimum preparation process of ZEO-complex polysaccharide gels was as follows: the addition of inulin was at 0.84%, the addition of GSE was at 0.04%, and the addition of ZEO was at 2.0785%; in this way, the Y of ZEO-complex polysaccharide gels reached the maximum (0.82276). Optical scanning and X-ray diffraction tests confirmed that the prepared ZEO-complex gels have a smooth and continuous microstructure, good water insulation, and mechanical properties. The storage test results show that ZEO-complex polysaccharide gels could play a significant role in the storage and fresh-keeping of grass carp, and the physicochemical properties of complex polysaccharide gels were improved by adding ZEO. In addition, according to the correlation of fish index changes during storage, adding ZEO in complex polysaccharide gels was closely correlated with the changes in fish TBARS and TVB-N oxidation decay indices. In conclusion, the ZEO-complex polysaccharide gels prepared in this study had excellent water insulation, mechanical properties, and outstanding fresh-keeping effects on grass carp.

Comprehensive study of microstructural evolution and strengthening mechanism of high-performance pure copper prepared by blue laser metal deposition (B-LMD)

The high absorption of the copper to the blue laser provides an alternative method to circumvent the laser reflection of laser metal deposition (LMD) of pure copper. In this work, blue laser metal deposition (B-LMD) was used to prepare pure copper parts. The B-LMD pure copper tracks fabricated using the optimum processing parameter have well bonding with the substrate, consisting of fine equiaxed grains with an average size of 2.8 μm, and exhibit the highest microhardness of 133.21 HV0.2. The pure copper deposit fabricated by the optimum processing parameter exhibited the highest relative density (97.9 % ± 0.2 %) and microhardness (103.05 ± 4.37 HV0.2). Additionally, the microstructure of the B-LMD pure copper deposit is showing a bimodal grain structure with columnar grains at the melt pool boundary and fine equiaxed grains at the center. The B-LMD pure copper deposit exhibits excellent mechanical properties, with an ultimate tensile strength of 244 ± 9 MPa, yield strength of 158 ± 6 MPa, and a fracture elongation of 14.7 ± 0.8 %. The superior mechanical properties are primarily attributed to grain refinement strengthening and dislocation strengthening. The high performance of B-LMD pure copper demonstrate the potential of the blue laser as an effective alternative energy source for fabricating high-performance pure copper components.

Reaction Characteristics of Calcination and Decomposition of Phosphogypsum in a Bubbling Fluidized Bed.

A bubbling fluidized bed reactor is designed to investigate the high-temperature calcination and decomposition characteristics of phosphogypsum (PG). The reactor employs electric heating, and a lifting discharge tube is installed in the middle of the air distributor to allow flexible switching between batch and continuous feeding modes. The batch test results show that the solid-phase bed materials with a PG particle size of 0.27-0.55 mm and a coal particle size of 0.55-0.83 mm are found to have uniformly mixed at a PG/coal mass ratio of 5:1 and calcined at a high temperature of 1100 °C for 30 min. PG completely decomposes to yield mainly CaS and a small amount of Ca2(SiO4) as the solid-phase products. For the above-mentioned optimal process parameters, a 120 min thermal-state continuous test is conducted. Feeding and discharging are performed at intervals of 30 min to maintain the stability of the static bed height inside the reactor. The results indicate that the PG decomposition rate is higher than 92% in the batch and continuous tests. However, the continuous decomposition of PG has significant process advantages, such as a higher CaS yield (71.20%) compared to that in the batch mode (64.49%). Furthermore, PG undergoes agglomeration and bonding within the particles when heated, intensifying the formation of a Ca2(SiO4) eutectic.

Tailoring the vibration characteristics of carbon fiber-reinforced polylactic acid in fused filament fabrication process

The Fused Filament Fabrication (FFF) process has gained significant attention for its ability to manufacture parts using advanced polymeric materials, such as carbon fiber-reinforced polylactic acid (CF-PLA). By adjusting the printing process parameters of the CF-PLA, the optimized mechanical properties can be achieved with less chances of flaws. Structural integrity of the components plays an important role in analyzing the durability of the product which can be analyzed using modal analysis. This research study focuses on analyzing the effect of process parameters on the vibration damping characteristics of CF-PLA components produced by the FFF process. The Taguchi method is used to model the relationship between process parameters and vibration performance metrics. Based on the vibration study, the optimal process parameters were determined as 60% infill density, 0.08 mm slice thickness, and hexagonal pattern. This study shows that the natural frequency and damping increases with increase in infill percent but decreases with increase in slice thickness. The closely aligned values between the predicted and experimental results suggest that the developed model is effective in predicting the vibration characteristics of CF-PLA composites. By accurately adjusting the process parameters, the study’s findings—such as frequencies and damping ratio—provide manufacturers with important and dependable CF-PLA Fused Deposition Modeling components.

Fabrication of Silica–Titanium Composite Film on Wood Surface and Optimization of Its Structure and Properties

In this thesis, wood loaded with a silica–titanium (Si-Ti) composite film was prepared using the sol–gel method in order to achieve improved wood with high hydrophobicity and photocatalytic activity under visible light. The factors affecting the structure and properties of the composite film, as well as the optimization process, were discussed. Infrared analysis revealed that the vibrational intensity of Si-O-Si, Ti-O-Ti, and Ti-O-Si telescopic vibration peaks increased with an increase in vinyltriethoxysilane (VETS). Additionally, the number of Ti-O-Ti telescopic vibration peaks also increased with an increase in VETS. Furthermore, the intensity of -NO3, Si-O-Si, and Ti-O-Ti telescopic vibrational peaks was enhanced with a higher dosage of nitric acid. Conversely, the intensity of -OH telescopic vibrational peaks decreased with an increase in drying temperature. XRD analysis showed that nitric acid could promote the transformation of TiO2 from amorphous to anatase, while SiO2 would reduce the grain size of anatase TiO2 and promote the growth of rutile TiO2. Additionally, wood surfaces loaded with Si-Ti composite film changed from hydrophilic to hydrophobic, with significant differences observed between different levels of each factor. The photocatalytic activity of surface-loaded Si-Ti composite films on wood was most affected by the amount of nitric acid, which influenced crystallinity of TiO2 and thus impacted the photocatalytic activity. Furthermore, changes in VTES dosage not only affected the crystalline phase of TiO2 and the grain size of Si-Ti composite film but also influenced the crystallinity of TiO2 through generating SiO2. Finally, based on optimal preparation process (titanium–alcohol ratio of 1:5, titanium–silicon ratio of 1:0.2, titanium–acid ratio of 1:0.5, and drying temperature of 100 °C), wood surfaces loaded with Si-Ti composite film achieved a contact angle up to 125.9° and exhibited a decolorization rate for rhodamine B under UV light reaching 94% within 180 min.

Ultrasound-assisted deep eutectic solvents extraction of podophyllotoxins from Juniperus sabina L: Optimization, enrichment, and anti-drug resistant bacteria activity

Podophyllotoxin, along with its congeners and derivatives exhibit strong biological activity mainly as antitumor drugs and antiviral agents. Here, the ultrasound-assisted extraction of podophyllotoxins including α-peltatin, podophyllotoxin, podophyllotoxinone and deoxypodophyllotoxin from Juniperus sabina L. leaves using deep eutectic solvents (DESs) were developed first time. To simultaneously and effectively extract four target podophyllotoxins, 19 DESs were screened to determine the best solvent to extract podophyllotoxins. Choline chloride-lactic acid (1:1) with 30 % water content was proved to have the best extraction effect. The optimal extraction process with DES were DES/solid ratio 30 mL/g, reaction temperature 44℃, time 53 min and ultrasound power 495 W. Under optimized extraction conditions, the total podophyllotoxins extraction yield was 27.520 mg/g, 196.84 % higher than that using traditional methanol solvent. The yield of α-peltatin, podophyllotoxin, deoxypodophyllotoxin and podophyllotoxinone were 13.567, 9.548, 2.021, 2.204 mg/g, respectively. Subsequently, the podophyllotoxins were effectively isolated from the deep eutectic solvent using D101 macroporous resin. The optimal process for enriching target podophyllotoxins by D101 macroporous resin were as follows: 30 mg/mL of crude extract solution, five bed volumes feed volume for adsorption; six bed volumes of 80 % ethanol for desorption. Moreover, a scale-up enrichment experiment of podophyllotoxins was performed under optimum procedure, and the results showed that the target podophyllotoxins yield was increased by 8.92 times, with recoveries in the range of 75.86–85.69 %. Additionally, the enriched podophyllotoxins effectively restored the antibacterial efficacy of cefazolin against methicillin-resistant Staphylococcus aureus and colistin-resistant Escherichia coli, resulting in 16–64-fold reduction in MIC. Therefore, the method developed in this study could be an eco-friendly, efficient and sustainable alternative for the selective extraction and enrichment of active compounds from plant material.

Laser-induced protruded bioinspired texturing of Ti-6Al-4V for controlled wettability in biomedical application

Bioinspired protruded textures with variable surface morphology and characteristics are getting worldwide popularity due to their wider applications. Among them controlled wettability for different materials through bioinspired textures is very essential to reduce the adhesion, bacterial contamination and growth, and drug delivery application. Even, identification and efficient fabrication of favorable bioinspired protrusions with optimum parameters are comparatively complex from normal textures through any material processing methods due to their complex shapes, form accuracy and dimensions. Therefore, this work targets the fabrication of four different types of protruded bioinspired textures namely, fish scale, protruded square, protruded circular, Python scale (snake) textured surface on biomedical grade Ti-6Al-4V titanium alloy for controlling the wettability using femtosecond laser surface texturing (LST). The optimum process parameters for the machining of Ti-6Al-4V were set as a temporal width of 350 fs, output power of 5.5 W, wavelength of 1030 nm, scanning speed of 100 mm/s and pulse rate of 500 KHz and three repetitions for all the texture types. To examine the effect of texture type, perimeter of all the fabricated textures was kept constant. Further, effect of varying perimeters was also analyzed for perimeter ranges from 300 to 500 µm. Surface morphology and characteristics were also analyzed for the measurement of texture consistency, dimensions and composition which was also related to the wettability results examined by static contact angle of the sessile drop method. Wetting of fish scale texture is decreased with increasing perimeter whereas of all other textures, wettability is going to be improved significantly.

Tungsten-needle intensifies microwave-sustained plasma accelerating direct H2S conversion to H2

Direct sustainable conversion of hydrogen sulfide (H2S) enables collaborative recovery of H and S resources via a metal-enhanced microwave plasma strategy, avoiding the hydrogen waste in the traditional Claus process. However, the metal size effect on microwave plasma property, the optimal process parameters, and the enhancement mechanism remain unclear in H2S conversion. Herein, the optimal tungsten needle (diameter: 1 mm, length: 60 mm, and tip angle: 10°) is experimentally proven for intensifying microwave discharge in multi-mode cavities. Theoretical calculations and plasma distribution reveal that the optimized tungsten needle achieves the ideal coupling with the microwave field, exhibiting extreme electric field augmentation around the needle tip. Tungsten-needle intensifies microwave-sustained plasma, realizing 40.2 % (90.1 %) conversion of 100 % (10 %) concentration H2S to H2 at a low microwave power of 300 W with a good stability of 30 hrs. Low power, large flow rate, and high H2S concentration are beneficial for improving energy efficiency. The excitation of microwave plasma is accompanied by a massive generation of highly energetic electrons. The direct high-energy electron-H2S collision contributes a lot to H2S splitting, especially for high-concentration H2S. In-situ optical emission spectroscopy confirms the vital S and H radicals in the plasma. The free radical reactions triggered by electron collisions are responsible for the production of H2 and S. This work opens an avenue to sustainable and low-carbon hydrogen production from the direct conversion and utilization of H2S.

Manufacture of the Invar Film Using a Continuous Electrodeposition Technique for the OLED FMM

In the manufacturing processes of red-green-blue (RGB)-type organic light emitting diode (OLED) displays, Invar is used as a material for the fine metal mask (FMM), which guides the evaporated diode materials through its small holes onto the correct positions of the substrate glass. The electroforming of Invar is an immediate hot issue in the RGB-type OLED display industries. Contrary to the conventional top-down method of pyrometallurgically producing Invar, a bottom-up approach of electroforming is a promising technology for producing very thin FMMs to achieve high-quality images in such displays. The present authors have recently presented that the electroformed Invar via sophisticated heat treatment exhibits the coefficient of thermal expansion (CTE) as low as that of the conventional Invar. The current work has been aimed at investigating the effect of the microstructure evolution on the CTE during heat treatment of the electroformed Invar. Finally, we propose optimal process conditions to manufacture the Invar FMM applied for an ultra high definition (UHD) grade of the OLED display.

Enhanced cold plasma hydrogenation with glycerol as hydrogen source for production of trans-fat-free margarine

The quest for better nutritious foods has encouraged novel scientific investigations to find trans-fat reduction methods. This research proposes an innovative approach for the production of healthier trans-fat-free margarine from palm oil by the use of dielectric barrier discharge (DBD) plasma technology with glycerol serving as the principal source of hydrogen. The effectiveness of DBD plasma in hydrogenating palm olein was investigated. By employing a methodical series of experiments and thorough analytical approaches, examination of the saturated fatty acid conversion experienced its iodine value (IV) reduction from 67.16 ± 0.70 to 31.61 ± 1.10 under the optimal process parameters of 1 L min−1 He flow rate, 35 W plasma discharge power, 10 mm gap size, ambient initial temperature, and 12 h reaction time with solid texture. According to the method for producing trans-fat-free margarine in the absence of a catalyst and H2 gas, the hydrogenation rate of the prepared mixture of palm olein-glycerol was remarkably improved; the trans-fat content in the produced product was zero; the efficacy of incorporating cis- and trans-isomerization was lowered, and the method has a promising industrial application prospect.

A prediction method for the backlash error of robot precision reducers based on optimal assembly

Abstract The kinematic accuracy and service life of robot precision reducers are directly affected by their assembly accuracy, and the backlash error is one of the most important performance indicators for evaluating the assembly accuracy. A prediction method for the backlash error of robot precision reducers is proposed, which can quickly and accurately calculate the backlash error of the optimal assembly reducers. Based on the optimal assembly process, the sensitive relationship between the errors of the crucial components and the assembly accuracy of the reducer is analysed, and the crucial errors affecting the backlash error are identified. The cumulative backlash of the crucial error along the dimensional chain is clarified, and the corresponding relationship between the backlash and the backlash error is determined. On this basis, backlash prediction models are established for the involute planetary gear and cycloidal-pin gear transmission parts, respectively. The mapping relationship between dimensional errors and backlash is also derived. Furthermore, the backlash error of the reducer is obtained by calculating the backlash error caused by each error term of the high-speed stage and low-speed stage transmission parts. Finally, the effectiveness and correctness of the prediction method are verified by the optimal assembly of RV reducers and the measurement of the backlash error. The theory and method proposed in this paper can quickly and accurately predict the backlash error of the reducer for robots, effectively predict the assembly accuracy of the selective reducers, significantly improve the assembly efficiency of the reducers, and then provide theoretical guidance and technical support for enhancing the assembly quality and kinematic accuracy of robot reducers.

Multi-Objectives Optimization of Plastic Injection Molding Process Parameters Based on Numerical DNN-GA-MCS Strategy.

An intelligent optimization technique has been presented to enhance the multiple structural performance of PA6-20CF carbon fiber-reinforced polymer (CFRP) plastic injection molding (PIM) products. This approach integrates a deep neural network (DNN), Non-dominated Sorting Genetic Algorithm II (NSGA-II), and Monte Carlo simulation (MCS), collectively referred to as the DNN-GA-MCS strategy. The main objective is to ascertain complex process parameters while elucidating the intrinsic relationships between processing methods and material properties. To realize this, a numerical study on the PIM structural performance of an automotive front engine hood panel was conducted, considering fiber orientation tensor (FOT), warpage, and equivalent plastic strain (PEEQ). The mold temperature, melt temperature, packing pressure, packing time, injection time, cooling temperature, and cooling time were employed as design variables. Subsequently, multiple objective optimizations of the molding process parameters were employed by GA. The utilization of Z-score normalization metrics provided a robust framework for evaluating the comprehensive objective function. The numerical target response in PIM is extremely intricate, but the stability offered by the DNN-GA-MCS strategy ensures precision for accurate results. The enhancement effect of global and local multi-objectives on the molded polymer-metal hybrid (PMH) front hood panel was verified, and the numerical results showed that this strategy can quickly and accurately select the optimal process parameter settings. Compared with the training set mean value, the objectives were increased by 8.63%, 6.61%, and 9.75%, respectively. Compared to the full AA 5083 hood panel scenario, our design reduces weight by 16.67%, and achievements of 92.54%, 93.75%, and 106.85% were obtained in lateral, longitudinal, and torsional strain energy, respectively. In summary, our proposed methodology demonstrates considerable potential in improving the, highlighting its significant impact on the optimization of structural performance.

Utilization of RESOLV with polymer to produce prazosin hydrochloride nanoparticles and optimization of the process parameters

In this study, rapid expansion of a supercritical solution into a Liquid Solvent (RESOLV) was used for the first time to produce pharmaceutical nanoparticles of Prazosin hydrochloride (PRH). The Taguchi method (robust design) was utilized to design the experiments and ensure obtaining the optimal process conditions. The pressure (15–25 MPa), temperature (308–328 K) and nozzle diameter (300–700 μm) effects on the morphology and size distribution of the resulting particles were also examined. The size of the particles decreased from about 40 μm to the range of (252–418 nm). FTIR, DLS, FESEM, XRD, DSC were used to characterize the primary and processed PRH particles. According to DSC investigations, RESOLV-produced PRH showed lower crystallinity than original PRH.