Function Of Process Parameters Research Articles

Highly selective Si3N4/SiO2 etching using an NF3/N2/O2/H2 remote plasma. II. Surface reaction mechanism

Developing processes for highly selective etching of silicon nitride (Si3N4) with respect to silicon dioxide (SiO2) is a major priority for semiconductor fabrication processing. In this paper and in Paper I [Volynets et al., J. Vac. Sci. Technol. A 38, 023007 (2020)], mechanisms are discussed for highly selective Si3N4 etching in a remote plasma based on experimental and theoretical investigations. The Si3N4/SiO2 etch selectivity of up to 380 was experimentally produced using a remote plasma sustained in NF3/N2/O2/H2 mixtures. A selectivity strongly depends on the flow rate of H2, an effect attributed to the formation of HF molecules in vibrationally excited states that accelerate etching reactions. Based on experimental measurements and zero-dimensional plasma simulations, an analytical etching model was developed for etch rates as a function of process parameters. Reaction rates and sticking coefficients were provided by quantum chemistry models and also fitted to the experimental results. Etch rates from the analytical model show good agreement with the experimental results and demonstrate why certain etchants accelerate or inhibit the etch process. In particular, the modeling shows the important role of HF molecules in the first vibrationally excited state [HF(v = 1)] in achieving high Si3N4/SiO2 selectivity.

Force-based reliability estimation of remaining cutting tool life in titanium milling

Reliability estimation and prediction of the remaining life of a cutting tool is paramount for ensuring economic and damage proof machining. Monitoring of the status of the cutting tool and especially flank wear disrupts the process and thus avoided. In the present study a novel reliability estimation approach to the cutting tools remaining life based on advanced approximation methods is proposed. An approximation model that is based on response surface and a surrogate model is used for the representation of flank wear as a function of process parameters and cutting forces. For the establishment of this model, the relationship of cutting forces with flank wear is investigated experimentally. The results show that the proposed method is an efficient method for assessing the reliability of the cutting tool based on a minimum number of experimental runs. Experimental verification for the case of titanium milling confirms the findings of the present study.

Investigation on the effect of erodent velocity on the erosion of 3/2 BLARE laminates

Basalt Fibres made from crushed basalt igneous rock by the rapid cooling of lava. Due to their low cost and excellent mechanical properties, basalt fibres used in many applications such as automotive, boat building, civil engineering, wind turbine blades, and sporting goods. Present work deals with the mechanical and erosion response of basalt fiber reinforced epoxy stack Aluminum (AA) fiber metal laminates (BLARE). Fiber metal laminates were fabricated under the hot compression route by alternatively stacking the basalt/epoxy composites with AA foils. Erosion studies were conducted using an air jet erosion test-rig by varying the input process parameters such as jet pressure, Flow rate, and impingement angle. The changes in properties such as mass, density, and roughness of aluminium skin with basalt fibres reinforcements as a function of process parameters were discussed with the aid of electron imaging. Results reveal that increase in abrasive jet velocity significantly erodes mass at the onset, and at a higher velocity rate, the erosion was low due to the surface rolling effects of abrasive particles as understand from the electron imaging.

Femtosecond Laser Lift‐Off with Sub‐Bandgap Excitation for Production of Free‐Standing GaN Light‐Emitting Diode Chips

Laser lift‐off (LLO) is commonly applied to separate functional thin films from the underlying substrate, in particular light‐emitting diodes (LEDs) on a gallium nitride (GaN) basis from sapphire. By transferring the LED layer stack to foreign carriers with tailored characteristics, for example, highly reflective surfaces, the performance of optoelectronic devices can be drastically improved. Conventionally, LLO is conducted with UV laser pulses in the nanosecond regime. When directed to the sapphire side of the wafer, absorption of the pulses in the first GaN layers at the sapphire/GaN interface leads to detachment. In this work, a novel approach towards LLO based on femtosecond pulses at 520 nm wavelength is demonstrated for the first time. Despite relying on two‐photon absorption with sub‐bandgap excitation, the ultrashort pulse widths may reduce structural damage in comparison to conventional LLO. Based on a detailed study of the laser impact as a function of process parameters, a two‐step process scheme is developed to create freestanding InGaN/GaN LED chips with up to 1.2 mm edge length and ≈5 μm thickness. The detached chips are assessed by scanning electron microscopy and cathodoluminescence, revealing similar emission properties before and after LLO.

On the Surface Roughness for the Dry Superfinishing Process of Carbide Inserts

The surface roughness of tool edge and surface can affect the friction, between the rake face and chips and also the cutting force and temperature. For this reasons, in order to assure a good quality, some experimental determinations, from point of view of rake face roughness, are presented in this paper. The results, as capture from a SEM microscope, and, graphically dependencies of roughness as function of process parameters, are presented.

Oxygen gain and aluminum loss during laser metal deposition of intermetallic TiAl

For manufacturing turbine parts for the aeronautical industry, lightweight structural materials like titanium aluminides are used. One well known example is the alloy Ti-43.5Al-4Nb-1Mo-0.1B (atomic percent) with the commercial name TNM™. In previous studies, experiments on laser metal deposition of TiAl were performed to evaluate the potential of the technology to repair defective, damaged, or worn blades. Process conditions including postprocess heat treatment were successfully adjusted. However, oxygen pick-up is still a crucial aspect in laser based additive manufacturing of Ti- and TiAl-based alloys. In this work, approaches were made to analyze the oxygen pick-up as a function of processing parameters and the powder particle size. The results show that the build rate and the powder particle size affect the oxygen content in the consolidated material.

Impact of processing parameters on tensile strength, in-process crystallinity and mesostructure in FDM-fabricated PLA specimens

Purpose This study aims to investigate the impact of layer thickness, extrusion temperature, extrusion speed and build plate temperature on the tensile strength, crystallinity achieved during fabrication (herein, in-process crystallinity) and mesostructure of Poly(lactic acid) specimens. Both tensile strength and in-process crystallinity were optimized and verified as the function of processing parameters, and their relationship was thoroughly examined. Design/methodology/approach The four key technological parameters were systematically varied as factors on three levels, using the statistically designed experiment. Surface response methodology was used to optimize tensile strength and crystallinity for the given ranges of input factors. Optimized factor settings were used in a set of confirmation runs, where the result of optimization was experimentally confirmed. Material characterization was performed using differential scanning calorimetry and X-ray diffraction analysis, while the effect of processing parameters on mesostructure was examined by scanning electron microscopy. Findings Layer thickness and its quadratic effect are dominant contributors to tensile strength. Significant interaction between layer thickness and extrusion speed implies that these parameters should always be varied simultaneously within designed experiment to obtain adequate process model. As regards, the in-process crystallinity, extrusion speed is part of two significant interactions with plate temperature and layer thickness, respectively. Quality of mesostructure is vital contributor to tensile strength during FDM process, while the in-process crystallinity exhibited no impact, remaining below the 20 per cent margin regardless of process parameter settings. Originality/value According to available literature, there have been no previously published investigations which studied the effect of process parameters on tensile strength, mesostructure and in-process crystallinity through systematic variation of four critical processing parameters.

A Hybrid Modeling of the Physics-Driven Evolution of Material Addition and Track Generation in Laser Powder Directed Energy Deposition.

Directed Energy Deposition (DED) is one of the most promising additive manufacturing technologies for the production of large metal components and because of the possibility it offers of adding material to an existing part. Nevertheless, DED is considered premature for industrial production, because the identification of the process parameters may be a very complex task. An original hybrid analytic-numerical model, related to the physics of laser powder DED, is presented in this work in order to evaluate easily and quickly the effects of different sets of process parameters on track deposition outcomes. In the proposed model, the volume of the deposited material is modeled as a function of process parameters using a synergistic interaction between regression-based analytic models and a novel element activation strategy. The model is implemented in a Finite Element (FE) software, and the forecasting capability is assessed by comparing the numerical results with experimental data from the literature. The predicted results show a reasonable correlation with the experimental dimensions of the melt pool and demonstrate that the proposed model may be used for prediction purposes, if a specific set of process parameters that guarantees adequate adhesion of the deposited track to the substrate is introduced.

Correlation of processing parameters and ageing with the phase morphology of styrene-butadiene-styrene block co-polymer modified bitumen

The morphology development of styrene-butadiene-styrene (SBS) block copolymer modified bitumen as a function of processing parameters was investigated using a combination of optical (OM) and confocal laser scanning microscopy (CLSM). The homogeneity of blends of SBS and bitumen increased with increasing mixing time, where the application of higher shear rates enhances the dispersion and distribution of the SBS phase in the bitumen matrix. For higher shear rates, SBS was swollen between 6 and 8 times that of its initial volume and shear rate is more influential than mixing time in achieving a highly dispersed SBS phase in bitumen. The bitumen components having fluorescence properties (i.e. saturates and aromatics) were homogenously dispersed in the bitumen phase, confirmed by highly uniform fluorescence intensity 3D colour maps (CLSM). The fluorescence intensity of the SBS modified bitumen samples was much more variable with regions of high and low intensity due to inhomogeneous dispersion of the polymer in the bitumen and, the absorption of the fluorescence components of the bitumen by the PS and PB phases of SBS. For longer mixing times the SBS modified bitumen aged, observed from a decrease in fluorescence intensity. Long term in-service aging of the SBS modified bitumen blends, simulated using a pressure aging vessel, resulted in a decrease in fluorescence intensity. Only the sample prepared at the lowest shear rate (1000 rpm) and shortest mixing time (15 min) displayed variable intensity in the 3D colour maps as the SBS copolymer was poorly mixed in the bitumen phase.

Adaptive indirect neural network model for roughness in honing processes

Abstract Honing processes provide a crosshatch pattern that allows oil flow, for example in combustion engine cylinders. This paper provides an adaptive neural network model for predicting roughness as a function of process parameters. Input variables are three parameters from the Abbott-Firestone curve, Rk, Rpk and Rvk. Output parameters are grain size, density of abrasive, pressure, linear speed and tangential speed. The model consists of applying a direct and an indirect model consecutively, with one convergence parameter and one error parameter. The indirect model has one network with 48 neurons and the direct model has three networks having 25, 9 and 5 neurons respectively. The adaptive one allows selecting discrete values for some variables like grain size or density.

Surface quality and kerf width prediction in abrasive water jet machining of metal-composite stacks

Machinability of stacked Titanium (Ti6Al4V) and CFRP was evaluated using Abrasive Water Jet (AWJ) machining process. The experimental study was conducted using three pressure levels – 200, 275 and 350 MPa. Traverse speed was varied between 1 and 10 mm/s for two stacking configurations (Ti/CFRP, and CFRP/Ti). The erosion characteristics, kerf width and surface roughness was studied as a function of process parameters. Surface roughness and kerf width variation was high at low jet power conditions, as described by lumped parameters (E˙/u and E˙/hu). The minimum average roughness Ra for Ti and CFRP was less than 3.5 μm and 4.5 μm respectively for both the stacking sequence. The kerf width increased significantly, especially when Ti6Al4V is at top in which case low-energy, turbulent jet diverges at the exit from Ti6Al4V. Mathematical regression models were developed to predict kerf width. An energy based, semi-analytical model was proposed to predict the kerf geometry with R2=92.26%.

An integrative simulation concept for extrusion blow molded plastic bottles

It is well known that the mechanical properties of extrusion blow molded plastic bottles are influenced by the process conditions, which leads to local orthotropic process-dependent material parameters. In this study, these parameters as well as local orientation effects are for the first time considered in the structural analysis of extrusion blow molded products. Furthermore, an integrative simulation concept has been worked out which combines process simulation and structural analysis to take the process history of the plastic bottle into account. The elastic modulus is described as a function of process parameters like the local degrees of stretching and the mold temperature. Because the local degrees of stretching differ considerably, a new algorithm was developed which identifies the local degrees of stretching as well as their orientation using the results of the process simulation. For the data mapping between the process mesh and the structural analysis mesh, the self-developed MpCCI Mapper software was used. In a simulation of a top load test, the integrative simulation model was compared with the conventional model as well as with experimental data. Although in this particular case the influence of the orthotropic material model with respect to the local degrees of stretching is rather low, the general use of process dependent material parameters leads to much better results.

Surface Morphologies in Ultra-short Pulsed Laser Processing of Stainless-Steel at High Repetition Rate

Stainless-steel is ablated with femtosecond laser pulses at high repetition rate. A multi-pass, high spatial overlap laser scanning strategy is applied in order to cope with the requirements for large-scale machining of high aspect ratio structures. Topography of the processed surfaces is analyzed via Shear Force Microscopy scans, with the main aim to investigate morphology changes as a function of process parameters. Quantitative assessment of local height variations enables a detailed investigation of the produced features. Depending on the process parameters, in particular on laser fluence and repetition rate, a transition from small islands to large bumps is observed, explained in terms of feature coalescence.

Study on process technology and surface integrity of 316L cardiovascular stents by fiber laser wet cutting

This paper presents an experiment of fiber laser wet cutting of 316L cardiovascular stents and investigates the relationship between process parameters(pulse width, laser power, frequency, cutting speed) and surface integrity indexes (surface topography, surface roughness, heat-affected zone (HAZ), recast layer, dross, subsurface nano-hardness). Furthermore, single-factor analysis method was performed to find optimal single-factor parameters. The experimental results demonstrate that surface integrity indexes as the function of process parameters and the optimum single-factor parameters could be obtained. In addition, the nano-hardness reflected the variation and nature of the HAZ and recast layer. This study is of great significance to obtain the minimum post-processing of cardiovascular stents.

Analytical temperature predictive modeling and non-linear optimization in machining

Different process parameters can alter the temperature during machining. Consequently, selecting process parameters that lead to a desirable cutting temperature would help to increase the tool life, decrease the tensile residual stress, and controls the microstructure evolution of the workpiece. An inverse computational methodology is proposed to design the process parameters for a specific cutting temperature. A physics-based analytical model is used to predict the temperature induced by cutting forces. The shear deformation and chip formation model is implemented to calculate machining forces as functions of process parameters, material properties, and etc. To calculate the temperature induced by the deformation in the shear zone, a moving point heat source approach is used. The proposed model uses an iterative non-linear regression to predict the cutting process parameters based on the desirable temperature which is assigned by the user. In order to achieve the cutting process parameters, an iterative gradient search is used to adaptively approach the specific temperature by the optimization of process parameters such that an inverse reasoning can be achieved. Experimental data are used to illustrate the implementation and validate the viability of the computational methodology.

Characterization of Au catalytic activity in low-temperature graphene etching

Recent research into Au nanoparticles has revealed some surprising catalytically favorable properties. We apply these properties to the signficant challenge of patterning graphene at low temperatures in a scalable manner. By utilizing these Au nanoparticles, we demonstrate a simple method for low-temperature gold-catalyzed etching of graphite with predictable characteristics using ambient air at 350–375 °C and an ability to etch only the top graphene layer of a graphite piece with suitable choice of processing steps. The naturally occurring water vapor in ambient air is necessary for this reaction to occur. In addition, we characterize the etch characteristics as a function of process parameters. Ar annealing is required to obtain crystallographically straight etches, and 375 °C may be required to obtain single-layer deep etching. The catalytic activity is around ∼1μmolC/gAus and terminates due to catalyst poisoning around ∼0.7mmolC/gAu. We hypothesize that enhanced nanoparticle size control will have the greatest effect on catalytic activity. We anticipate that this work can be adapted by future research to precisely control the shape of the etched areas, allowing for the simple low-temperature creation of nanoscale graphite features, and ultimately can be applied to single-layer graphene sheets for integrated device fabrication.

Multi-droplet splat solidification with re-melting during precision droplet manufacturing

Abstract Precision Droplet Manufacturing (PDM) is an additive manufacturing process to build complex 3D parts one nano-liter molten metal droplet at a time from a CAD file without the need for tooling. Component integrity is explored by simulating the droplet splat solidification process via a finite-difference simulation which utilizes an analytical start valid for short times and also allows for re-melting of previously deposited material. Transformations are used to convert the moving-boundary problem to a fixed-boundary problem. Re-melt depth as a function of process parameters is investigated and an analysis of realistic parameters for building with aluminum indicates that successful inter-droplet splat bonding is feasible. In addition, the computed solidification rates verify PDM’s classification as a rapid solidification process. Furthermore, multi-layer simulations demonstrate that layer stacking is a sustainable process, meaning that it is possible for layers to always solidify fully before the next layer of material arrives on the substrate.

Non-dimensional process maps for normalized dilution limits in laser direct metal deposition

Abstract The quality and integrity of laser direct metal deposition (DMD) processes primarily depend on the substrate dilution and the nature of residual stresses in the deposited layer. An adequate amount of melting of the substrate is required to ensure the formation of sound metallurgical bond between the deposited layer and substrate. Insufficient melting and excessive dilution may lead to adverse effects. Furthermore, the dilution also controls the location of the melt front in substrate where maximum tensile residual stresses occur. The presence of tensile residual stresses in the deposited layer may be detrimental to service life, especially, for components repaired using DMD. These challenges can be overcome by predicting and controlling the dilution and the nature of residual stress as a function of process parameters. To model the direct metal deposition process, a 3D coupled metallo-thermomechanical finite element model is employed to predict the temperature and the residual stress due to thermomechanical interactions and metallurgical transformations and the substrate dilution. Non-dimensional process parameters affecting the dilution in laser DMD have been identified using Buckingham-Π theorem. The metallo-thermomechanical model is used to develop empirical relationships via regression to correlate the dimensionless process parameters with the dilution. These correlations are employed in developing the isopleths in the form of process maps, which could predict regions of inadequate fusion and excessive dilution (unduly large substrate melting). It may be noted that the limiting value of dilution corresponds to the condition where the entire deposited layer (cladding) is under compressive residual stresses. Any dilution higher than this will result in excess substrate melting which is undesirable. The limiting values of normalized dilution are estimated to be 1 and ~1.3 corresponding to complete deposit-substrate fusion and presence of entirely compressive residual stress in deposition, respectively. These process maps are designed to provide a theoretical framework for understanding the influence of process parameters and provide informed decisions on the selection of appropriate process parameters for ensuring the quality and integrity of the deposition.

Flow curve prediction of ZAM100 magnesium alloy sheets using artificial neural network-based models

A multivariable empirical model, based on an artificial neural network (ANN), was developed to predict flow curves of ZAM100 magnesium alloy sheets as a function of process parameters in hot forming conditions. Tensile tests were performed in a wide range of temperature and strain rate to collect the dataset used in the training and testing stages of the network. The generalization ability of the model was tested using both the leave-one-out cross-validation method and flow curves not belonging to the training set. The excellent fitting between experimental and predicted curves was proven the very good predictive capability of the model.

Recovery of Heavy Minerals from Brahmagiri Deposit, Odisha using Gravity Table

Characterization and beneficiation studies are carried out on sand samples collected from Brahmagiri coast of Odisha. Characterization and beneficiation studies are carried out using a lab scale gravity separator. Application of Design expert is also done to find the behavior of gravity table as a function of process parameters. Optimization of response is also done by using Matlab7.1. ANOVA software is applied to compare the predicted and experimental values for grade and recovery, and the results show a good fit.