Deposition Efficiency Research Articles

Atomistic insights into chemical vapor deposition process of preparing silicon carbide materials using ReaxFF-MD simulation

SiC is a kind of key advanced coating material used widely. The in-depth understanding of the CVD process of preparing SiC materials at the atomic scale is beneficial for studying the CVD mechanism and then optimizing the materials. Here, a CVD model of preparing SiC materials is established based on ReaxFF-MD considering the whole pyrolysis-adsorption-desorption-growth mechanism. The accuracy of the ReaxFF potential and its parameters is verified by DFT at first. Then an energy-based Monte Carlo (EMC)-MD-CVD model is proposed based on the bonding formation energy originating from DFT. It is used to simulate the CVD process of preparing SiC materials. The CVD of MTS is studied by deposition efficiency and deposited film components at different temperatures, and it can be found it in good agreement with experimental results. Finally, the crystallization of SiC film prepared by the CVD of MTS is studied by energy evolution and atomic structure evolution. The results are helpful to understand the CVD mechanism for preparing coatings and it can be used to optimize the CVD parameters of preparing SiC materials in the future.

Investigating the effectiveness of liposome-bacteriophage nanocomplex in killing Staphylococcus aureus using epithelial cell coculture models

Host cell invasion with strong antibiotics evading is a major feature of respiratory Staphylococcus aureus infections with severe recurrence. Bacteriophage (phage) therapy and design of liposomal phage to target intracellular pathogens have been described recently. The practicality for pulmonary delivery of liposomal phage, and how formulation compositions affecting the aerosolization and intracellular bacterial killing remain unexplored. In the present study, three commonly used phospholipids (SPC, EPC, and HSPC) were selected to investigate their ability for phage K nebulization and intracellular therapy in the form of liposome-phage nanocomplexes. The three lipid nanocarriers showed protection on phage K upon mesh nebulization and the pulmonary deposition efficiency was influenced by the lipid used. Moreover, the intracellular bacterial killing was strongly depended on the lipid types, where EPC-phage exhibited the best killing performance with no relapsing. Phage K with the aid of EPC liposomes was also observed to manage the tissue infection in a 3D spheroid model more effectively than other groups. Altogether, this novel EPC liposome-phage nanocomplex can be a promising formulation approach that enables inhalable phage to manage respiratory infections caused by bacteria strongly associated with human epithelial cells.

Cold spray deposition of high density polyethylene composite powders

In this paper, we investigate the use of the cold spray additive manufacturing technique to deposit micron-sized composite particles of high-density polyethylene (HDPE) compounded with either micron or nanometer sized particles of silicon dioxide (SiO2) or copper (Cu). In this study, the mass fraction of the SiO2 and copper particles added into the final composite powders was varied between 0.5 % and 9.1 % and the deposition efficiency of each composite powder was measured. Deposition of the composite powders onto an HDPE substrate was successful even at the highest particle loadings tested. In each case, an optimal mass fraction of silicon dioxide or copper particles was observed with a maximum value of deposition efficiency larger than that of the pure HDPE. For the silicon dioxide composite powders, the deposition efficiency nearly doubled compared to the pure HDPE powders. The improvement of deposition efficiency at moderate particle loadings is likely due to the increase in the impact kinetic energy of the particles resulting from the increase in the density of the composite powders. While the decrease in deposition efficiency at high particle loadings is likely the result of the increased coverage of the silicon dioxide and copper particles on the surface of the HDPE powders limiting the interaction between the HDPE of the composite powder with the HDPE substrate. SEM images show that it is possible to create a smooth, dense, and uniform thin-film polymer composite coating using cold spray.

Study of soot dynamic behavior and catalytic regeneration in diesel particulate filters

Catalytic diesel particulate filters (CDPFs) are key technologies for controlling particulate matter emissions. Nevertheless, it is challenging to experimentally observe the internal working states of the CDPF, which hinders comprehensive research on the flow, capture, and regeneration characteristics. In this study, we utilized quartet structure generation set to generate two-dimensional porous walls, lattice Boltzmann method to simulate CDPF flow and diffusion, cellular automata to simulate soot motion, and global reaction kinetics to simulate soot oxidation. The accuracy of the model is validated through flow, combustion, and pressure drop experiments. We propose a new concept of local porosity, where the porosity of a partially porous wall is used to represent the filtering parameters of that part. These findings indicate that porosity dominates filtering. A higher local porosity results in increased near-wall velocity and greater deposition of soot particles. Similarly, alterations in local porosity and deposition mutually influence each other. The velocity distribution and pressure difference at the inlet and outlet are directly influenced by the upstream velocity. Compared with velocity and porosity, particle diameter has less effect on deposition location, but more effect on deposition efficiency. Active regeneration (800 K) occurs approximately 31.17 times more quickly than passive regeneration (600 K) in the absence of a catalyst. The platinum-based catalyst significantly enhanced the soot oxidation rate by oxidizing NO to NO2, resulting in a 3.62-fold increase in passive regeneration and an estimated 1.17-fold increase in active regeneration. These findings are crucial for developing efficient CDPF systems and for reducing particulate emissions.

Heat-balance control of friction rolling additive manufacturing based on combination of plasma preheating and instant water cooling

Friction rolling additive manufacturing (FRAM) is a solid-state additive manufacturing technology that plasticizes the feed and deposits a material using frictional heat generated by the tool head. The thermal efficiency of FRAM, which depends only on friction to generate heat, is low, and the thermal-accumulation effect of the deposition process must be addressed. An FRAM heat-balance-control method that combines plasma-arc preheating and instant water cooling (PC-FRAM) is devised in this study, and a temperature field featuring rapidly increasing and decreasing temperature is constructed around the tool head. Additionally, 2195-T87 Al-Li alloy is used as the feed material, and the effects of heating and cooling rates on the microstructure and mechanical properties are investigated. The results show that water cooling significantly improves heat accumulation during the deposition process. The cooling rate increases by 11.7 times, and the high-temperature residence time decreases by more than 50 %. The grain size of the PC-FRAM sample is the smallest, i.e., 3.77±1.03 µm, its dislocation density is the highest, and the number density of precipitates is the highest, the size of precipitates is the smallest, which shows the best precipitation-strengthening effect. The hardness test results are consistent with the precipitation distribution. The ultimate tensile strength, yield strength and elongation of the PC-FRAM samples are the highest (351±15.6 MPa, 251.3 ± 15.8 MPa and 16.25 %±1.25 %, respectively) among the samples investigated. The preheating and water-cooling-assisted deposition simultaneously increases the tensile strength and elongation of the deposited samples. The combination of preheating and instant cooling improves the deposition efficiency of FRAM and weakens the thermal-softening effect.

A Review on Wire-Laser Directed Energy Deposition: Parameter Control, Process Stability, and Future Research Paths

Wire-laser directed energy deposition has emerged as a transformative technology in metal additive manufacturing, offering high material deposition efficiency and promoting a cleaner process environment compared to powder processes. This technique has gained attention across diverse industries due to its ability to expedite production and facilitate the repair or replication of valuable components. This work reviews the state-of-the-art in wire-laser directed energy deposition to gain a clear understanding of key process variables and identify challenges affecting process stability. Furthermore, this paper explores modeling and monitoring methods utilized in the literature to enhance the final quality of fabricated parts, thereby minimizing the need for repeated experiments, and reducing material waste. By reviewing existing literature, this paper contributes to advancing the current understanding of wire-laser directed energy deposition technology. It highlights the gaps in the literature while underscoring research needs in wire-laser directed energy deposition.

Modeling of the shape of Taylor cone in EHD printing based on backpropagation neural network and genetic algorithm

Electrohydrodynamic (EHD) printing has been recognized as a promising additive manufacturing technology with superior pattern resolution and economic viability. The shape of Taylor cone is deemed a pivotal element for the amplification of deposition efficiency, and the maintenance of consistent operational steadiness in EHD printing. The correlations between diverse operating parameters and the shape of Taylor cone are presently not well investigated. In this paper, modeling of relationships between operating parameters and the shape of Taylor cone was conducted with a backpropagation neural network (BPNN) and a genetic algorithm optimized backpropagation (GA-BP) neural network. Taylor cone semi-vertical angle and the meniscus height were employed as two indexes to characterize the shape of Taylor cone. The prediction accuracies of BPNN model and GA-BP model were 92.79 % and 95.46 %, respectively. The GA-BP model demonstrated higher precision in forecasting the shape of Taylor cone. A predictive framework for the shape of Taylor cone was proposed, which provided a practical tool for process optimization in EHD printing.

Wear and corrosion properties of Cu–AlN composite coatings deposited by cold spray

Copper and copper alloy are commonly used to fabricate ship propellers and sealing valves that encounter harsh corrosion and wear. To improve their service life, Cu coating and Cu–AlN composite coatings with different volume content of AlN (10%, 20%, 30%) were prepared by cold spraying. The investigation focused on analyzing the coatings’ microstructure, microhardness, resistance to wear, and corrosion. Results show that the composite coatings with AlN have fewer pores and denser microstructure than the Cu coating. The coating demonstrates a relatively low deposition efficiency, resulting in the attainment of only 3.8 vol% of AlN when the feedstock AlN powder content was 30 vol%. The microhardness of Cu-3.8AlN coating is 159.7 HV, about 53.1% higher than that of Cu coating. The specific wear rate of Cu-3.8AlN coating is reduced by about 73.5% compared to that of Cu coating, measuring at 1.69 × 10−3 mm3/(N·m). Compared with other coatings, Cu-3.8AlN has the highest corrosion resistance (Ecorr = −0.199 V, Icorr = 1.2 μA/cm2, Rct = 3200 Ω·cm2). The Cu-3.8AlN coating exhibits superior wear and corrosion resistance among the four coatings, attributed to its highest level of densification and the presence of AlN particles.

Transcriptome analysis of adipose tissue and muscle of Laiwu and Duroc pigs

Fat content is an important trait in pig production. Adipose tissue and muscle are important sites for fat deposition and affect production efficiency and quality. To regulate the fat content in these tissues, we need to understand the mechanisms behind fat deposition. Laiwu pigs, a Chinese indigenous breed, have significantly higher fat content in both adipose tissue and muscle than commercial breeds such as Duroc. In this study, we analyzed the transcriptomes in adipose tissue and muscle of 21-d-old Laiwu and Duroc piglets. Results showed that there were 828 and 671 differentially expressed genes (DEG) in subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT), respectively. Functional enrichment analysis showed that these DEG were enriched in metabolic pathways, especially carbohydrate and lipid metabolism. Additionally, in the longissimus muscle (LM) and psoas muscle (PM), 312 and 335 DEG were identified, demonstrating enrichment in the cell cycle and metabolic pathways. The protein–protein interaction (PPI) networks of these DEG were analyzed and potential hub genes were identified, such as FBP1 and SCD in adipose tissues and RRM2 and GADL1 in muscles. Meanwhile, results showed that there were common DEG between adipose tissue and muscle, such as LDHB, THRSP, and DGAT2. These findings showed that there are significant differences in the transcriptomes of the adipose tissue and muscle between Laiwu and Duroc piglets (P < 0.05), especially in metabolic patterns. This insight serves to advance our comprehensive understanding of metabolic regulation in these tissues and provide targets for fat content regulation.

Behavior of Self‐Disintegrating Microparticles at the Air/Mucus Interface

In recent years, highly specialized nanoscopic drug carriers have been developed, which can, e.g., traverse biological barriers, protect drugs against harsh physiological conditions, and release such drugs in a controlled manner. However, for the delivery of particles via the respiratory pathway, aerodynamic diameters in the range of several micrometers are required to achieve good lung deposition and biodistribution. To combine the favorable properties of inhalable, micron‐sized particles with the advantages of nanosized drug carriers, herein, dry‐powder, hybrid microparticles (h‐μPs), which disintegrate upon contact with moist surfaces (as present in the lung) to release the embedded nanoparticles into the mucosa, are introduced. Furthermore, a microfluidic setup, which mimics the air–gel interface of the mucosal airway epithelium, is presented. With this setup, the interaction of airborne h‐μPs with the mucosal interface on a microscopic level is investigated. In detail, the influence of the h‐μP charge on their deposition efficiency is tested and it is found that this process is governed by a combination of electrostatic interactions between the mucosal surface and the h‐μPs as well as hygroscopic effects. Thus, this approach can help to optimize inhalable drug carriers to increase the efficiency of pulmonary drug administration via the respiratory pathway.

Modification of Cu Oxide and Cu Nitride Films by Energetic Ion Impact

We have investigated lattice disordering of cupper oxide (Cu2O) and copper nitride (Cu3N) films induced by high- and low-energy ion impact, knowing that the effects of electronic excitation and elastic collision play roles by these ions, respectively. For high-energy ion impact, degradation of X-ray diffraction (XRD) intensity per ion fluence or lattice disordering cross-section (YXD) fits to the power-law: YXD = (BXDSe)NXD, with Se and BXD being the electronic stopping power and a constant. For Cu2O and Cu3N, NXD is obtained to be 2.42 and 1.75, and BXD is 0.223 and 0.54 (kev/nm)−1. It appears that for low-energy ion impact, YXD is nearly proportional to the nuclear stopping power (Sn). The efficiency of energy deposition, YXD/Se, as well as Ysp/Se, is compared with YXD/Sn, as well as Ysp/Sn. The efficiency ratio RXD = (YXD/Se)/(YXD/Sn) is evaluated to be ~0.1 and ~0.2 at Se = 15 keV/nm for Cu2O and Cu3N, meaning that the efficiency of electronic energy deposition is smaller than that of nuclear energy deposition. Rsp = (Ysp/Se)/(Ysp/Sn) is evaluated to be 0.46 for Cu2O and 0.7 for Cu3N at Se = 15 keV/nm.

Carotenoid content and deposition efficiency in yolks of laying hens fed with dent corn hybrids differing in grain hardness and processing

Yolk carotenoid profile reflects the hen diet when corn grain is the only source of carotenoids, but corn origin and processing may affect carotenoid utilization. In the present study, 2 commercial dent corn hybrids differing in grain hardness (soft- and hard-type) were dried at low (40°C) and high (85°C) temperature and ground through a 5- and 9-mm sieve to investigate their effects on carotenoid bioavailability in laying hens. With 3 hens per cage, 168 Lohmann Brown laying hens were allocated to 8 dietary treatments (2 hybrids × 2 drying temperatures × 2 grinding sieves) in a completely randomized design (8 treatments × 7 cages). The trial lasted 8 wk, during which eggs were collected for analysis every 3 d until carotenoid content stabilized, and then once a week until the end of the experiment. The carotenoid profile of the experimental diets and yolks was analyzed using an HPLC method and deposition efficiency was calculated based on carotenoid contents, yolk weight, egg production and diet intake. The deposition efficiency for lutein, zeaxanthin, α- and β-cryptoxanthin, and β-carotene averaged 27.37, 18.67, 6.29, 3,32, and 0.94%, respectively. As expected, the tested hybrids highly affected the carotenoid content in egg yolk due to their differences in carotenoid profile. Interestingly, hard- and soft-type hybrids differed in the deposition efficiency for all individual carotenoids but not for the total carotenoids. High grain drying temperature tended to increase the bioavailability of lutein and zeaxanthin in both hybrids. For the hard-type hybrid, the content of β-carotene in egg yolk was higher when grains were dried at a high temperature, while the opposite response was found in the soft-type hybrid. The effect of grinding sieve size was important for the zeaxanthin bioavailability in the soft-type hybrid only. In conclusion, our findings showed that corn hybrid had a primary influence on the carotenoid content in the yolks of laying hens, but grain processing may change the bioavailability of carotenoids.

A Comparative Study of the Life Cycle Inventory of Thermally Sprayed WC-12Co Coatings

In this research, a life cycle inventory (LCI) is developed for tungsten carbide–cobalt (WC-Co) coatings deposited via atmospheric plasma spray (APS), high-velocity oxy-fuel (HVOF), and cold gas spray (CGS) techniques. For the APS process, a mixture of Ar/H2 was used, while the HVOF process was fueled by H2. The carrier gas for CGS was N2. This study aims to determine and quantify the inputs (consumption of inputs and materials) and outputs (emissions to air, soil, water, and waste generation) that could be used in the life cycle analysis (LCA) of these processes. The dataset produced will allow users to estimate the environmental impacts of these processes using WC-Co feedstock powder. To obtain a complete and detailed LCI, measurements of electrical energy, gas, WC-CO powder, and alumina powder consumption were performed (the use of alumina was for sandblasting). Furthermore, emissions like carbon dioxide (CO2), carbon monoxide (CO), and noise were also measured. This practice allowed us to determine the input/output process quantities. For the first time, it was possible to obtain LCI data for the APS, HVOF, and CGS deposition processes using WC-12Co as a feedstock powder, allowing access to the LCI data to a broader audience. Comparisons were made between APS, HVOF, and CGS processes in terms of consumption and emissions. It was determined that the APS process consumes more electrical energy and that its deposition efficiency is higher than the other processes, while the HVOF process consumes a large amount of H2, which makes the process costlier. CGS has comparatively low electricity consumption, high N2 consumption, and low deposition efficiency. The APS, HVOF, and CGS processes analyzed in this study do not emit CO, and CO2 emissions are negligible.

Breaking the limitation of thermodynamic cycle efficiency of the plasma synthetic jet actuator: Noble gases

The low thermodynamic cycle efficiency of the plasma synthetic jet actuator (PSJA) limits its application in flow control of supersonic aircraft. To improve the thermodynamic cycle efficiency of the PSJA, the energy conversion process of the PSJA under single discharge has been investigated by thermodynamic theory analysis and numerical simulation. The relations between thermodynamic cycle efficiency, specific heat ratio of gas medium, non-dimensional energy deposition and heating efficiency are established by theoretical deduction. Employing the three-dimensional nonconstant electrode center energy deposition model, energy conversion processes in the PSJA with six different gas mediums have been investigated. The simulation results show that the thermodynamic cycle efficiency of the PSJA with noble gas medium can exceed 3.2 %, which is 1.92 times of the PSJA with air medium due to their low volume specific heat. The maximum jet x-velocity of helium can reach 493.11 m/s, which is 3.3 times higher than that of air. Consequently, noble gases prove to be effective in improving the thermodynamic cycle efficiency of the PSJA and enhancing the strength of the synthetic jet. The advancement in the performance of the PSJA contributes to their enhanced capabilities in the field of active flow control.

Droplet Morphology-Based Wettability Tuning and Design of Fog Harvesting Mesh to Minimize Mesh-Clogging.

Fog harvesting relies on intercepting atmospheric or industrial fog by placing a porous obstacle, for example, a mesh and collecting the deposited water. In the face of global water scarcity, such fog harvesting has emerged as a viable alternative source of potable water. Typical fog harvesting meshes suffer from poor collection efficiency due to aerodynamic bypassing of the oncoming fog stream and poor collection of the deposited water from the mesh. One pestering challenge in this context is the frequent clogging up of mesh pores by the deposited fog water, which not only yields low drainage efficiency but also generates high aerodynamic resistance to the oncoming fog stream, thereby negatively impacting the fog collection efficiency. Minimizing the clogging is possible by rendering the mesh fibers superhydrophobic, but that entails other detrimental effects like premature dripping and flow-induced re-entrainment of water droplets into the fog stream from the mesh fiber. Herein, we improvise on traditional interweaved metal mesh designs by defining critical parameters, viz., mesh pitch, shade coefficient, and fiber wettability, and deducing their optimal values from numerically and experimentally observed morphology of collected fog water droplets under various operating scenarios. We extend our investigations over a varying range of mesh-wettability, including superhydrophilic and hydrophobic fibers, and go on to find optimal shade coefficients which would theoretically render clog-proof fog harvesting meshes. The aerodynamic, deposition, and overall collection efficiencies are characterized. Hydrophobic meshes with square pores, having fiber diameters smaller than the capillary length scale of water, and an optimal shade coefficient are found to be the most effective design of such clog-proof meshes.

Deep learning assisted fabrication of metallic components using the robotic wire arc additive manufacturing

PurposeBecause of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.Design/methodology/approachInstead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.FindingsThe mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.Originality/valueThe fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.

Spraying performance and deposition characteristics of an improved air-assisted nozzle with induction charging.

Electrostatic spraying technology can improve the efficiency of pesticide deposition on the surface of leaves and reduce the environmental pollution caused by pesticide drift, which has an important prospect in agricultural pesticide application. To improve the deposition and penetration of droplets in the crop canopy, we designed and optimized an air-assisted electrostatic nozzle and conducted the spraying performance experiment. Parameters, such as charge-to-mass ratio (CMR) and particle size, were tested and analyzed to obtain the suitable operating parameters of nozzle. The results proved that the improved air-assisted electrostatic nozzle has good atomization and chargeability. There is a good charging effect with a charging voltage of 3,000-5,000 V, the CMR increased 127.8% from 0.86 to 1.97 mC/kg as the charge voltage increases from 1,000 to 4,000 V, at an air pressure of 1.0bar and liquid flow rate of 200 ml/min. Furthermore, we designed a multi-factor orthogonal experiment, which was conducted using a four-factor, three-level design to investigate the effects of operational parameters and canopy characteristics on droplet deposition and penetration. Analysis of variance (ANOVA) and F-test were performed on the experiment results. The results showed that the factor effect on droplet penetration, in descending order, was as follows: spray distance, leaf area index, air pressure, and air pressure × spray distance. The factor effect on abaxial leaf deposition, in descending order, was as follows: air pressure, spray distance, air pressure × charge voltage, spray distance × charge voltage, and charge voltage. For optimal droplet penetration and abaxial leaf deposition, option A 3 B 1 D 2 (air pressure 1.5bar, spray distance 0.2m, charge voltage 2,500 V) is recommend. The spray nozzle atomization performance and deposition regulation were studied by experimental methods to determine the optimal values of operating parameters to provide a reference for electrostatic spray system development.

Effects of deposited microstructure on wear behaviors of detonation sprayed Fe-based amorphous coatings

Fe-based amorphous coatings (AMCs) were deposited using the detonation spray at varying spraying distances. The study aimed to characterize the deposition morphologies and elemental composition of splats for single shots under different spraying distances. Additionally, the relationship between spraying distance, particle deposition behavior, spreading morphology, and wear behavior of the coatings was comprehensively discussed. The results indicate that modifying the spraying distance affects the melting state of spray particles, thereby influencing the morphology of deposition and determining the coating's microstructure. Larger spraying distances result in reduced deposition efficiency and lead to particles depositing in a manner similar to cold spraying, resulting in an uneven coating structure with higher porosity. Consequently, the coating becomes more susceptible to fatiguedelamination wear. Conversely, a moderate spraying distance leads to full melting and acceleration of powders, results in good spreading and the formation of a uniform and dense laminar structure.

Bead Geometry Control in Wire Arc Additive Manufactured Profile — A Review

Wire arc additive manufacturing (WAAM) is a well-established additive manufacturing method that produces 3D profiles. A better deposition efficiency can be achieved by understanding the parameters that may influence the geometry of the bead. This paper provides a review that focuses on the factors that may influence the formation of the 3D profile. The included factors are the flow pattern of the molten pool after deposition, the built structure and orientation, the heat input and cooling conditions, the welding parameters, and other uncertainties. This review aims to facilitate a better understanding of these factors and achieve the optimum geometry of the 3D parts produced. According to the literature, the behavior of molten pools is identified as one of the major factors that can impact the deposition efficiency of a bead and govern its geometry. The review indicated that the flow behavior of the molten pool and the geometry of the deposited bead are significantly affected by most welding parameters, such as torch angle, wire travel speed, filler feed rate, and cooling conditions. Furthermore, this paper incorporates the technology utilized for comprehending the behaviors of the molten pool, as it constitutes an integral component of the control strategy. It has been concluded that automated planning and strategy are necessary to ensure efficient deposition by controlling those factors. The integration of artificial intelligence could bring benefits in planning to address the variation and complexity of shapes.

Estimating and reducing dissipative losses in thermal spray: A parametrized material flow analysis approach

Thermal spray is a family of surface engineering technologies necessary to meet technical functionalities of components under harsh environmental conditions. Those technologies come at the expense of dissipative losses of coating materials throughout the life cycle of components. Measuring these material losses has so far retained little attention in the field. This research provides a framework to estimate material dissipative losses in surface engineering applications based on specific parameters, mainly deposition efficiencies. We applied material flow analysis to quantify dissipative losses for the main metals used in thermal spray (Cr, Co, Mo, Ni, Si, W, Y and Zr). Results show that the coating process is the most contributing life cycle stage (up to 39% of the losses). Improving the deposition efficiency, recovering the unadhered and stripping the components at their end-of-life are key material efficiency strategies to reduce the material losses (up to 50%).