Effect Of Different Process Parameters Research Articles

Enhancing wear resistance of AZ61 alloy through friction stir processing: experimental study and prediction model

Abstract In this study, the friction stir technique is proposed to process AZ61 alloy and artificial neural network is built to predict and compare the experimental wear results. The effects of different processing parameters, including spindle speed (800–1200 rpm), travelling speed (05–15 mm/min), and depth of press (0.8-1.2 mm) on the microstructural evolution, mechanical properties and wear behaviour investigated. The grain size of the FSP1 samples found to be 14 ± 2 µm and shifting of peaks are observed in the X ray diffraction analysis chiefly due to texture development. As the spindle speed, travelling speed increases the surface roughness increases, it is observed that Ra – for FSP1 and FSP9 is found to be 68.4 nm and 116.3 nm respectively. Highest micro-hardness (113.36 Hv) values were observed for FSP1 sample and least is FSP9 sample (79. 51 Hv) and BM sample (65.92 Hv). Due to increased heat input into the processed regime, the hardness decreased as rotational and traveling speed increased, resulting in the development of coarse microstructure and a reduction in hardness. Based on wear results it has been observed that specimen FSP1 sample (0.003 g and 0.28) had the lowest weight loss and COF values compared to other FSP conditions. This is due to the combination of process parameters resulted in sufficient heat generation, grain refinement, and strain hardening of the stir zone, which enhanced the wear resistance of the specimen. Coefficient of friction is reduced to 0.28 from 0.68, and weight loss has been reduced to about 58% as compared to BM sample. This work shows that enhancing the wear resistance of magnesium alloys using friction stir processing is a successful approach.

Investigation of Micropattern Forming Process on Zr‐4 Alloy Surface Considering Plowing Effects

Micropattern forming process is an efficient and low‐cost process for fabricating multifunctional surfaces in electronics, energy, and biomedical products, but this process of creating microdimples on the surface of zirconium alloys has not been investigated. Currently, there are few models describing the micropattern forming process, and these existing models have not considered the effect of roughness on forming. The influence of roughness on micropattern forming process is not to be neglected due to the size effect, especially the plowing effects caused by asperities in surface roughness during sliding process. In this article, a micropattern forming process model is developed by combining a rough plane indentation model and a plowing effects model, and the experimental study of the forming process is conducted, which can quantitatively evaluate the effects of different process parameters and different roughness of forming die on forming process. The applicability range of the developed model is obtained, and the model is capable of predicting the forming process with various process parameters and surface roughness of forming die by comparing the experiment results with the model results, which is of great significance to the design of the forming die and the improvement of the forming process.

Analysis and optimization of stamping and forming process of bearing outer ring

To address the common issues of wrinkling, tearing, and uneven wall thickness in the actual sheet metal stamping process of the outer ring of needle roller bearings, this study analyzes critical technical indicators such as forming limits, thickness distribution, and principal strains in the forming process in detail. Three-dimensional models of the concave and convex dies were constructed. The effects of different process parameters, including stamping speed, edge pressure, sheet metal thickness, and friction coefficient, on the quality of the forming parts were investigated by varying these parameters. Subsequently, the orthogonal experimental method was used to determine an optimal experimental group from multiple sets of experiments. It was found that under the process parameters of a stamping speed of 3000 mm/s, edge pressure of 2000 N, sheet metal thickness of 0.9 mm, and friction coefficient of 0.125, the forming quality of the outer ring of the bearing is ideal.

Investigation of thermal deformation and surface microstructure of wire electrical discharge machining for thin-walled rare-earth gadolinium

Rare-earth gadolinium (Gd) has excellent magnetocaloric properties. High-aspect-ratio arrays of thin-walled parts processed with rare-earth Gd are typical structures for regenerators, which are the core components of magnetic refrigeration. Wire electrical discharge machining (WEDM) offers significant advantages for manufacturing micro-structured parts. However, in WEDM, materials are thermally ablated, which leads to compromised surface quality and significant thermal deformation in thin-walled structures with low stiffness. In this study, the effects of different process parameters on the thermal deformation and surface microstructure of rare-earth Gd thin-walled parts were studied by single-factor experiments. It was found that the pulse-on time, open voltage, and water pressure had prominent effects on thermal deformation. Lowering the pulse energy can effectively reduce the thermal deformation and oxidation of the samples and improve the machined surface quality. Through the SNR analysis of the thermal deformation and surface roughness results for the optimized experimental sample, the optimal processing parameter combination of rare-earth Gd thin-walled structure regenerator with high-aspect-ratio of 38 was determined. It was proved that the thermal deformation of thin-walled parts can be controlled within 20 μm by using the combination of optimal thermal deformation parameters, including a pulse-on time of 0.5 μs, pulse-off time of 25 μs, peak current of 12 A, open voltage of 95 V, and a water pressure of 0.22 MPa.

Comprehensive investigation of capacitive deionization cells by response surface methodology

Freshwater resources are limited; thus, different technologies for desalination of brackish and seawater have been developed. Capacitive deionization (CDI) is one of the most promising desalination technologies owing to its low cost, simplicity, nonmoving parts, and low energy consumption. However, its energy consumption significantly increases with desalination of high-salinity water. In this regard, a good understanding of the effects of different process parameters on CDI energy consumption is crucial for further performance improvement. Therefore, the surface response methodology (RSM) was adopted to systematically study the effects of applying voltage, Stern layer capacity, volume and concentration of feed water, and volume of micropores on energy consumption and desalination time. The results showed that the Stern layer capacity and volume of micropores reduced desalination time by approximately 25% without significant changes in energy consumption. With the design of an improved electrode (improving the micropore structure for ion adsorption), the desalination time (Cycle) was reduced and a slight reduction in energy consumption was achieved. It can be claimed that any improvement in the physical (porosity) and electrical properties of the electrodes, results in an important increase in the performance of the CDI system.

Degradation of Carbamazepine in Water by UV-activated Sulfite Process

In this study, the degradation efficiency and mechanism of carbamazepine (CBZ), a typical emerging contaminant in water, in the UV/sulfite process were investigated. The effects of different concentrations of dissolved oxygen [ρ(DO)] on the degradation of CBZ by UV-activated sulfite were investigated. Additionally, under a simulated natural water environment-controlled initial ρ(DO) of (8.0 ±0.2) mg·L-1, the effects of different process parameters (sulfite dosages and reaction pH) and water environmental factors (the presence of HCO3-, Cl-, and humic acids) on the degradation of CBZ were comprehensively analyzed. The results showed that the UV/sulfite process efficiently degraded CBZ with a degradation rate of 85.3% during the 30 min reaction time and followed the pseudo-first order kinetic model with the constant of 0.055 7 min-1. Using the electron spin resonance detection, reactive species quenching tests, and the competition kinetics, the sulfate radicals (SO4-·) and hydroxyl radicals (·OH) in the UV/sulfite process were determined to be the main reactive species and were responsible for the degradation of CBZ with contribution rates of 43.9% and 56.1%, respectively. In addition, the degradation efficiency of CBZ decreased with the increasing concentration of HCO3-, and the presence of Cl- had little effect on the degradation of CBZ, whereas the presence of humic acids significantly inhibited the degradation of CBZ. Moreover, the accumulation of sulfate during the reaction was significantly lower than the limit of the Standard for Drinking Water (GB5749-2022). Additionally, the sulfite consumption rate constant was 0.004 4 min-1, which was significantly lower than the degradation rate constant of CBZ, indicating that sulfite could be activated efficiently by UV light to degrade CBZ in water.

Parametric study of WEDM of titanium grade 12 using RSM and desirability approach

The present experimental study aims to scrutinize the effect of different process parameters on the material removal rate (MRR) and surface roughness (SR) of titanium grade 12 alloy during wire electro-discharge machining (WEDM) using response surface methodology. Four parameters (pulse-on time, pulse-off time, wire feed and gap voltage) and three levels of each selected variable are considered to conduct the experimental work. Depending on experimental results, a mathematical model is generated for both MRR and SR. An analysis of variance (Anova) study is performed to find significant process parameters. The Anova results show that the developed models for both MRR and SR are significant, and pulse-on time is found to be the most significant parameter. Additionally, the desirability approach is used to scrutinize the single-objective and multi-objective criteria of response variables. The desirability functions for all of the cases are found to be 1. The maximum MRR is observed to be 12.4845 mm3/s, while the minimum value of SR is found to be 1.4911 μm. For multi-objective optimization, the maximum value of MRR and the minimum value of SR are obtained as 12.0942 mm3/min and 1.7167 μm, respectively. Finally, the surface morphology of the machined surfaces is examined using scanning electron microscopy micrographs.

Optimization of ultrasound-assisted extraction of Nigella sativa seed oil for enhancement of yield and antioxidant activity

The seeds of Nigella sativa have been shown to contain a number of constituents that have nutritional and therapeutic characteristics. The oil extracted from the seeds of Nigella sativa has been traditionally used in food systems with reference to its medicinal properties. The different bioactive compounds present in the Nigella sativa seed oil consist of polyphenols which offer a fair amount of antioxidant activity to the oil. Most of these bioactive compounds are generally heat sensitive and prone to oxidation. During the processing and storage, there is loss of antioxidant activity of the oil and the associated bioactivity. This occurs primarily due to the effects of temperature and other environmental factors during processing and storage. Under this background, this study was undertaken with the aim of extracting the Nigella sativa seed oil in order to ensure the improved retention of antioxidant and bioactive characteristics in the essential oil. The extraction of Nigella sativa seed oil was carried out using ultrasound-assisted extraction technique using hexane as solvent. The process was optimized using response surface methodology in order to enhance the yield and antioxidant activity of the extracted Nigella sativa seed oil. The effect of different processing parameters was evaluated on the yield and antioxidant activity. The process variables included the extraction temperature, extraction time and solvent concentration. It was observed that all the factors had significant effect on the yield and antioxidant activity of the extracted Nigella sativa oil. The optimized conditions for maximizing the yield and antioxidant activity obtained were a solvent concentration of 42.82 mL/5 g of sample, the extraction temperature of 69.09 °C and extraction time of 86.60 min, which were validated and found close to the experiment values. Under this set of conditions, the yield was maximized to 34.53% with enhanced antioxidant activity, having IC50 value of 203.56 µg/mL.

Optimization of Pyrolysis Process Parameters for Fuel Oil Production from the Thermal Recycling of Waste Polypropylene Grocery Bags Using the Box–Behnken Design

The impact of dumping plastic waste is realized in different ecosystems of the planet. Several methods have been adopted to dispose of these wastes for energy recovery. This study, for the first time, proposed the Box–Behnken design technique to optimize the pyrolysis process parameters for fuel oil production from waste polypropylene (PP) grocery bags using a semibatch-type pyrolytic reactor. The semibatch-type pyrolytic reactor was developed and employed to produce fuel oil from waste PP grocery bags. The effect of different process parameters on fuel oil production was comprehensively analyzed using the response surface methodology (RSM) with the conjunction of the Box–Behnken design (BBD). The BBD facilitates the prediction of the response variables with respect to changes in the input variables by developing a response model. The BBD was used to optimize the process parameters, such as the reaction temperature (400–550 °C), nitrogen flow rate (5–20 mL min−1), and substrate feed rate (0.25–1.5 kg h−1), and their effect on the responses were observed. The optimum response yields of the fuel oil (89.34 %), solid residue (2.74%), and gas yield (7.92%) were obtained with an optimized temperature (481 °C), a nitrogen flow rate (13 mL min−1), and a feed rate (0.61 kg h−1). The quadratic model obtained for the fuel oil response denotes the greater R2 value (0.99). The specific gravity and calorific value of the fuel oil were found to be 0.787 and 45.42 MJ kg−1, respectively. The fuel oil had higher research octane number (RON) (100.0 min) and motor octane number (MON) (85.1 min) values. These characteristics of the fuel oil were matched with conventional petroleum fuels. Further, Fourier transform infrared spectroscopy (FT-IR) and gas chromatography–mass spectroscopy (GC-MS) were used to analyze the fuel oil, and the results revealed that the fuel oil was enriched with different hydrocarbons, namely, alkane (paraffins) and alkene (olefins), in the carbon range of C4–C20. These results, and also the fractional distillation of the fuel oil, show the presence of petroleum-range hydrocarbons in the waste PP fuel oil.

Influence of atmospheric plasma spraying process parameters on microstructure and properties of yttrium oxide coatings

Y2O3 coatings were fabricated on using atmospheric plasma spraying (APS). The effects of different process parameters on the microstructure and properties of the coating were analyzed. The results show that the overall morphology of Y2O3 coatings are smooth at high spraying power, low spraying distance and low primary gas flow rate, which is consistent with the change trend of porosity and hardness. The minimum porosity of coating is about 1.4%. The roughness of coatings isn’t sensitive to changes in parameters. Y2O3 coatings have excellent corrosion resistance. The smaller the porosity of Y2O3 coating, the better the corrosion resistance.

Parameter and Deposition Strategy Analysis for WAAM Processing of AISI 410 Stainless Steel

Wire + Arc Additive Manufacturing (WAAM®) is an additive manufacturing (AM) process capable of producing near net shape parts while reducing costs and thus gathering increased attention from researchers and manufacturers. Although a significant amount of work has already been published relating to the WAAM processing of stainless steels, it was mainly focused on austenitic stainless steels, with martensitic grades still lacking investigation. AISI 410 is a martensitic stainless steel that, due to its high hardness, demonstrates high wear resistance, being used in parts requiring high resistance to abrasion. Processing this material by WAAM allows for the creation of near net shape parts, leading to a reduction in machining, while at the same time allowing the creation of complex geometries which would be difficult, or outright impossible to obtain otherwise. In this work the effects of different processing parameters on WAAM processed AISI 410 steel, using Cold Metal Transfer (CMT) welding equipment, were investigated, as well as different deposition strategies for the fabrication of a test artifact using an AM software. It was demonstrated that it is possible to process AISI 410 steel by WAAM using an AM software to define deposition strategies and parameters based on the part design and previous experimental trials. The goal to deposit a complex part with high hardness and tensile strength, especially attractive properties to parts requiring high resistance to wear was achieved.

The Analysis of Vibration Resistance of the Shape and Braided Laminated Manufactured Structure Using Taguchi Method

In this study, the L934 orthogonal table of the Taguchi method is used as a systematic parameter analysis. A rapid prototyping machine (RPM, manufactured by the research team) and fused deposition modeling (FDM) are used to make anti-vibration test specimens and to analyze the effect of different process parameters, such as weaving and shaping, on vibration resistance. Hopefully, various application fields will be extended via the deposition method. The impact test is executed by dropping a steel ball onto each test piece which is connected to an accelerometer and a PW700 spectrometer for extracting the frequency response during the impact. The vibration performance under different process parameters is analyzed. Several parameters that may affect anti-vibration performance are selected under the existing process, namely weaving method (A), deposition thickness (B), weaving density (C) and cross weaving per n-layer (D). The policy is to evaluate the required time period to restore to the steady state after impact. Hence, the shorter the convergence time is, the better the specimen resists the vibration. The experimental results show that the build-up layer thickness and the weaving density are the main control factors that affect the anti-vibration ability most. The process parameter A3B1C1D2 obtains the best vibration resistance performance.

Serial artificial neural networks characterized by Gaussian mixture for the modelling of the Consigma25 continuous manufacturing line

In this research, the Consigma25 Continuous Manufacturing (CM) Line is statistically analysed and modelled. First, the main effects plot is employed to examine the effects of different process parameters on the granules size and the tablet strength. Second, a modelling framework based on serial interconnected artificial neural networks is proposed to model the CM line by mapping these parameters to the granules size and the tablet strength. Then, Gaussian mixture models (GMMs) are adopted to characterize the error resulting from these networks in a way that helps in extracting more information and, as a result, improves the performance of the modelling framework. Validated on an experimental data set, the proposed interconnected framework can anticipate the characteristics of the granules and tablets produced using a specific blend of excipients with an absolute error percentage value of less than 12.3%. In addition, the GMMs have improved the predictive performance by 9.7%.

Impact of Fused Deposition Modeling Process Parameters and Heat Treatment on Mechanical Characteristics and Product Quality: A Review

Fused Deposition Modeling (FDM) is indeed one of the most commonly used methods of additive manufacturing, particularly for printing polymers and fiber-reinforced polymer composites. When compared to more conventional production meth ods like injection molding, the key benefits of FDM include producing components with intricate shapes, minimal material wastage, shorter production times, and lower costs because no tooling is needed. However, the strength and surface quality of the product produced using this technique are lower, that can be improved by selecting the optimized design variable and applying heat treatment depending on how the product will be used in an industry. This review paper provides an overview of the effect of different process parameters on mechanical properties, print time, and surface characteristics of the parts made of polymers and fiber-reinforced polymer composites in addition to the challenges encountered during the printing of composites. It also discusses the new material’s development, such as natural fiber-reinforced polymer composites, the impact of heat treatment, and the void formation influence on the mechanical properties, build time, dimensional accuracy, and surface finish of 3D-printed parts.

State-of-the-art on microstructural, mechanical and tribological properties of friction stir processed aluminium 2xxx series alloy

As a noble surface modification technique, friction stir processing (FSP) has been established based on the principle of friction stir welding that refines the microstructure and localized plastic deformation of the material. Nevertheless, despite notable technological progress, challenges persist in utilizing FSP to improve material characteristics. This review paper offers a concise overview, summarizing the influence of process parameters on the microstructure mechanical and tribological properties of aluminium alloy subjected to FSP. In particular, the performance of aluminium alloy is discussed about FSP factors such as tool travel speed, rotating speed, reinforcement particles, multiple passes and tool tilt angle. This paper also reviewed the effect of different process parameters on the wear properties, corrosion and tribological characteristics of the processed alloy, which will facilitate researchers and business organizations in creating the needed upgraded composite.

GLDA and ion exchangers: Unlocking sustainable solutions for recovery of rare earth elements

GLDA (tetrasodium salt of N,N-bis(carboxymethyl)-L-glutamic acid) was proposed as a complexing agent for rare earth elements. The formed complexes Ln(III)-GLDA were subjected to adsorption using twelve commercial ion exchangers of different types. Ion exchangers were characterized by describing their physicochemical properties using sieve analysis, scanning electron microscopy, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy. The stability constants of the Ln(III)-GLDA complexes in the binary systems at different Ln(III):GLDA molar ratios were determined by the potentiometric method. The effects of different process parameters (Ln(III):GLDA molar ratio, initial solution pH, phase contact time, initial solution concentrations, and temperature) on the adsorption of La(III), Nd(III), and Ho(III) ions in the presence of GLDA were investigated by the static method in the single-component systems.Kinetic, equilibrium, and thermodynamic parameters were calculated. The highest adsorption capacities were obtained for the Purolite S957 ion exchanger (139.57 mg/g for the La(III)-GLDA complexes, 152.72 mg/g for the Nd(III)-GLDA complexes, and 151.29 mg/g for the Ho(III)-GLDA complexes), Lewatit Monoplus SP112 ion exchanger (155.49 mg/g for the La(III)-GLDA complexes, 150.23 mg/g for the Nd(III)-GLDA complexes, and 132.77 mg/g for the Ho(III)-GLDA complexes). The desorption process was performed to regenerate the ion exchangers by applying hydrochloric and nitric(V) acids at concentrations of 0.5, 1, and 2 M. In addition, for La(III)-GLDA complexes, experiments were performed in the column systems.

Designer biochar with specific functionalities for the sustainable mining of invaluable metals from sea water: Performance assessment, mechanism insights and cost benefit analysis

Resource efficiency and cleaner production are an integral component of sustainable development. The present research addresses three contemporary issues. Firstly, quest for a greener alterative to land based mining-seawater, secondly, translation of renewable biowastes into carbon negative biochar and thirdly, synthesis of organic salts of metals directly from metal laded biochar. Sea water is an untapped source of invaluable elements leading to rising momentum for various new technologies. Herein, neem cake is tailored specifically for selective recovery of magnesium and strontium ions from simulated sea water in both batch and continuous systems. Magnesium selective biochar is prepared by insitu pyrolysis at 700℃ using sodium bicarbonate and urea as green porogen and nitrogen source whereas strontium selective biochar is prepared by direct pyrolysis at 700℃ followed by encapsulating alginate microspheres within the biochar lattice. Batch studies revealed the maximum adsorption capacities and removal efficiencies of 34.08 mg/g and 95 % for strontium(S-BC) and 40.2 mg/g and 98 % for magnesium(M−BC). The analytics reveals biochars as fine-tuned mesoporous carbon dominant structure with several N and O functionalities suggesting complexation, H-bonding as the adsorption mechanism. The Sips and PNO models surpassed all isotherm and kinetic models and well describes the process kinetics as chemisorption along with film diffusion as main contributors respectively. In column studies, effect of different process parameters is investigated and it is observed that experimental data corelates well with the BDST model. Moreover, scale up approach is employed to predict large scale design parameters. Lastly, citric acid as a green chelating agent is utilized to recover metal ions in the form of citrates and regenerate spent biosorbent along with detailed cost benefit analysis, thereby endorsing the circular economy approach.

Development of Super-Paramagnetic Iron Oxide Nanoparticle-Coated Melt Electrowritten Scaffolds for Biomedical Applications.

Polycaprolactone (PCL) is usually the material chosen for melt electrowriting (MEW) due to its biocompatibility, mechanical strength, and melt processability. This work first investigates the effect of different processing parameters to obtain optimum PCL-MEW scaffolds. Secondly, to increase PCL`s hydrophilicity and cell affinity, and to enable coating with superparamagnetic iron oxide nanoparticles (SPIONs) and silica-coated-SPIONs (Si-SPIONs), the scaffolds are modified with alkaline surface treatment. Finally, SPIONs and Si-SPIONs are successfully coated on MEW scaffolds. Results show that reproducible scaffolds are fabricated. Additionally, the alkaline treatment does not change the three-dimensionalmorphology of scaffolds while reducing fiber diameter. Furthermore, SEM images and ATR-FTIR results confirmed that SPIONs and Si-SPIONs-were coated on scaffolds. A cytocompatibility assay showed a non-toxic effect on MG-63 osteoblast-like cells in all scaffolds. Additionally, higher MC3T3-E1 pre-osteoblastic cell adhesion efficiency and proliferation are achieved for the alkaline-treated scaffolds and SPIONs/Si-SPIONs-coated scaffolds. All samples demonstrated the ability to generate heat, useful for hyperthermia-treatment, when subjected to an alternating magnetic field. Overall, the findings suggest that the strategy of coating PCL-MEW scaffolds with SPIONs/Si-SPIONs has the potential to improve scaffold performance for biomedical applications, especially for producing magnetically responsive MEW scaffolds.

Surface polishing of CoCrMo alloy by magnetorheological polishing

Improving the surface quality of biomedical alloys is of great practical significance to the evolution of orthopaedic implant surgery. In the polishing stage, traditional polishing methods are prone to problems, such as substandard surface roughness values and poor surface morphology, which severely affect the service life of materials. The surface quality of the CoCrMo alloy treated with magnetorheological polishing was studied. First, a polishing tool was designed based on magnetic field simulations of different magnetic pole arrangements and flow field simulations of the shear behaviour of the magnetorheological polishing cluster. Second, to improve the surface quality, an equally spaced pseudo-random path was planned, and the polishing effect for this path was verified using simulations and experiments. Moreover, the effect of different process parameters, i.e., the machining gap, polishing tool rotation speed, and abrasive particle size, on the polishing forces and the surface roughness values was studied. Finally, the wettability of the modified surface of the CoCrMo alloy after polishing was tested. The results confirm the ability of magnetorheological polishing to improve the surface quality of CoCrMo alloys, which has a certain guiding significance for the development of advanced biomedical implants.

Experimental investigation and machine learning modeling using LSTM and special relativity search of friction stir processed AA2024/Al2O3 nanocomposites

In this study, the friction stir technique is proposed to process aluminum nanocomposites reinforced with alumina nanoparticles. The effects of different processing parameters, including spindle speed (900–1800 rpm), feed (10–20 mm/min), and number of passes (1–3) on the mechanical and dynamic properties of the processed samples were investigated. The investigated properties were ultimate tensile strength, yield strength, natural frequency, and damping ratio. An advanced machine learning approach composed of a long short-term memory model optimized by a special relativity search algorithm was developed to predict the properties of the processed samples and different processing conditions. The adequacy of the developed model was tested and compared with three other machine learning models; the predicted properties were in good agreement with the measured properties. The developed model outperformed other tested models and was found to be a powerful prediction tool for predicting processing conditions to obtain high-quality nanocomposite samples. The model succeeded in predicting the ultimate tensile strength, yield strength, natural frequency, and damping ratio with good R2 of 0.912, 0.952, 0.951, and 0.987, respectively. The obtained results showed that the samples' damping ratio and loss factor increase with the number of passes, while the natural frequency, shear modulus, and complex modulus decrease with the number of passes. Thus, friction stir processing can be used to improve the damping properties of materials.