Optimal Processing Window Research Articles

Impact of solar radiation on chemical structure and micromechanical properties of cellulose-based humidity-sensing material Cottonid

Renewable and environmentally responsive materials are an energy- and resource-efficient approach in terms of civil engineering applications, e.g. as so-called smart building skins. To evaluate the influence of different environmental stimuli, like humidity or solar radiation, on the long-term actuation behavior and mechanical robustness of these materials, it is necessary to precisely characterize the magnitude and range of stimuli that trigger reactions and the resulting kinetics of a material, respectively, with suitable testing equipment and techniques. The overall aim is to correlate actuation potential and mechanical properties with process- or application-oriented parameters in terms of demand-oriented stimuli-responsive element production. In this study, the impact of solar radiation as environmental trigger on the cellulose-based humidity-sensing material Cottonid, which is a promising candidate for adaptive and autonomously moving elements, was investigated. For simulating solar radiation in the lab, specimens were exposed to short-wavelength blue light as well as a standardized artificial solar irradiation (CIE Solar ID65) in long-term aging experiments. Photodegradation behavior was analyzed by Fourier-transform infrared as well as electron paramagnetic resonance spectroscopy measurements to assess changes in Cottonid’s chemical composition. Subsequently, changes in micromechanical properties on the respective specimens’ surface were investigated with roughness measurements and ultra-micro-hardness tests to characterize variations in stiffness distribution in comparison to the initial condition. Also, thermal effects during long-term aging were considered and contrasted to pure radiative effects. In addition, to investigate the influence of process-related parameters on Cottonid’s humidity-driven deformation behavior, actuation tests were performed in an alternating climate chamber using a customized specimen holder, instrumented with digital image correlation (DIC). DIC was used for precise actuation strain measurements to comparatively evaluate different influences on the material’s sorption behavior. The infrared absorbance spectra of different aging states of irradiated Cottonid indicate oxidative stress on the surface compared to unaged samples. These findings differ under pure thermal loads. EPR spectra could corroborate these findings as radicals were detected, which were attributed to oxidation processes. Instrumented actuation experiments revealed the influence of processing-related parameters on the sorption behavior of the tested and structurally optimized Cottonid variant. Experimental data supports the definition of an optimal process window for stimuli-responsive element production. Based on these results, tailor-made functional materials shall be generated in the future where stimuli-responsiveness can be adjusted through the manufacturing process.

Evaluation of mechanical property predictions of refill Friction Stir Spot Welding joints via machine learning regression analyses on DoE data

The high-potential of lightweight components consisting of similar or dissimilar materials can be exploited by Solid-State Joining techniques. Whereas defects such as pores and hot cracking are often an issue in fusion-based joining processes, via solid-state joining processes they can be avoided to enable high-quality welds. To define an optimal process window for obtaining anticipated joint properties, numerous time and cost consuming experiments are usually required. Building a predictive model based on regression analysis enables the identification and quantification of process-property relationships. On the one hand, mechanical property and performance predictions based on specific process parameters are needed, on the other hand, inverse determination of required process parameters for reaching desired properties or performances are demanded. If these relations are obtained, optimized process parameter sets can be identified while vast numbers of required experiments can be reduced, as underlying physical mechanisms are utilized. In this study, different regression analysis algorithms, such as linear regression, decision trees and random forests, are applied to the refill Friction Stir Spot Welding process for establishing correlations between process parameters and joint properties. Experimental data sets used for training and testing are based on a Box-Behnken Design of Experiments (DoE) and additional test experiments, respectively. The machine-learning based regression analyses are benchmarked against linear regression and DoE statistics. The results illustrate a decryption of relationships along the process-property chain and its deployment to predict mechanical properties governed by process parameters.

Deformation Behavior and Processing Maps of 42CrMo Alloy Casting Blank Subjected to Double-Pass Isothermal Compression

The hot deformation behavior of 42CrMo alloy casting blank was studied using a double-pass isothermal compression. The effects of strain allocation in different passes on the stress softening degree and processing maps were analyzed. It is found that the stresses at the double-pass strains of 0.45 + 0.45 and 0.3 + 0.6 decrease with increasing temperature and decreasing strain rate. The softening fraction of recrystallization in deformation interval increases with increasing strain rate and temperature. The deformation behavior in the second-pass is significantly affected by the first-pass. The stress softening models considering partitioned strain at the double-pass compression are established, respectively. The deformation intervals exert an obvious effect on the efficiency of power dissipation (EPD) and optimum parameters. The main mechanism of microstructure evolution is dominated by dynamic recovery accompanied by a slight DRX. By combining the developed processing maps and microstructures, the optimum processing windows in the double-pass strain of 045 + 0.45 are found to be at a strain of 0.8, temperatures of 1000-1200 °C and strain rates of 0.45-1 s−1 with EPD of 38-49%, and for the double-pass strains of 0.3 + 0.6, the optimum windows at a strain of 0.8, temperatures of 1050-1200 °C and strain rates of 0.4-1 s−1 with EPD of 40-48% are recommended.

Computational thermodynamic study of SiC chemical vapor deposition from MTS‐H2*

AbstractThis study focuses on the computational thermodynamic analysis of the chemical vapor deposition (CVD) of SiC from the methyltrichlorosilane‐hydrogen (MTS‐H2) using up‐to‐date thermodynamic databases. High‐resolution computation has been performed with the fine intervals of temperature and pressure at the various H2/MTS ratios of interest to systematically investigate the deposition condition range (800 to 1600°C, 0 to 26 664 Pa, and H2/MTS ratios of 0.1 to 100) to guide experimental exploration. The influence of deposition parameters on the compositions and phase stabilities of the deposit and gas phase pertinent to vapor processing is elucidated. Low pressure and medium temperatures (1000 to 1400°C) are beneficial to reaching a higher SiC deposition efficiency and provide an optimal window for preparing a high‐purity (>99 wt.% SiC) deposit. This optimal processing window expands significantly with an increasing H2/MTS ratio (<20). These results are supported by a number of previous theoretical and experimental observations. The mass fraction of SiC in deposit is proposed as an additional perspective to understand the discrepancy between thermodynamic calculation and experimental observation of pure CVD SiC at low H2/MTS ratios.

Fracture prediction of powder metallurgical Fe–Cu–C steel at elevated temperatures via finite element-aided hot tensile tests

Surface cracking induced by damage accumulation is a common quality problem during the hot processing of powder metallurgical (P/M) products. This study aims to clarify the damage and fracture of P/M Fe–Cu–C steel at elevated temperatures to propose its fracture criterion by combining hot tensile tests with finite element (FE) calculations. The results reveal that the FE-aided test accurately corrected the true stress and strain of the P/M steel during the Gleeble hot tensile testing. In addition, the flow behaviors and cracking tendency of the P/M steel strongly depended on the hot deformation parameters. The optimum hot processing window of P/M steel was proposed after determining the quantitative relationships between the damage and hot deformation parameters. Finally, a novel elevated temperature fracture strain model of the P/M steel was proposed based on the Zener–Hollomon parameter to construct its Cockroft and Latham fracture criterion coupling hot processing parameters. The constructed fracture criterion was further normalized and modified, and achieved an acceptable fracture predictive capability with a relative error of less than 5%, which was validated by powder forging experiments. This work provides essential information and a useful model for the fracture prediction of P/M Fe–Cu–C steel at elevated temperatures, helping to manage the surface cracking problems of P/M steel during hot processing.

Feasibility Analysis of GNSS-Reflectometry for Monitoring Coastal Hazards

Coastal hazards, such as a tsunamis and storm surges, are a critical threat to coastal communities that lead to significant loss of lives and properties. To mitigate their impact, event-driven water level changes should be properly monitored. A tide gauge is one of the conventional water level measurement sensors. Still, alternative measurement systems can be needed to compensate for the role of tide gauge for contingency (e.g., broken and absence, etc.). Global Navigation Satellite System (GNSS) is an emerging water level measurement sensor that processes multipath signals reflected by the water surface that is referred to as GNSS-Reflectometry (GNSS-R). In this study, we adopted the GNSS-R technique to monitor tsunamis and storm surges by analyzing event-driven water level changes. To detect the extreme change of water level, enhanced GNSS-R data processing methods were applied which included the utilization of multi-band GNSS signals, determination of optimal processing window, and Kalman filtering for height rate determination. The impact of coastal hazards on water level retrievals was assessed by computing the confidence level of retrieval (CLR) that was computed based on probability of dominant peak representing the roughness of the water surface. The proposed approach was validated by two tsunami events, induced by 2012 Haida Gwaii earthquake and 2015 Chile earthquake, and two storm surge events, induced by 2017 Hurricane Harvey and occurred in Alaska in 2019. The proposed method successfully retrieved the water levels during the storm surge in both cases with the high correlation coefficients with the nearby tide gauge, 0.944, 0.933, 0.987, and 0.957, respectively. In addition, CLRs of four events are distinctive to the type of coastal events. It is confirmed that the tsunami causes the CLR deduction, while for the storm surges, GNSS-R keep high CLR during the event. These results are possibly used as an indicator of each event in terms of storm surge level and tsunami arrival time. This study shows that the proposed approach of GNSS-R based water level retrieval is feasible to monitor coastal hazards that are tsunamis and storm surges, and it can be a promising tool for investigating the coastal hazards to mitigate their impact and for a better decision making.

Ultrasonic Deposition of Carbon Nanotubes on Polycrystalline Cubic Boron Nitride Composites.

Polycrystalline cubic boron nitride (PcBN) are super-hard materials with high hardness and excellent abrasive resistance, widely used in cutting tools for precision machining of automotive and aerospace parts; however, their brittle properties make them prone to premature failure. Coatings are often applied to PcBN to extend their range of applicability and durability. Conventional coating methods are limited to the thickness range of a few hundred nanometres, poor adhesion to the substrate, and limited stability under ambient conditions. To further the properties of PcBN composites, in this paper, we explore the use of ultrasonic bonding to apply thick coatings (30–80 μm) on PcBN cutting tools. For the first time, a multi-walled carbon nanotube (MWCNT) powder is preplaced on a PcBN substrate to allow an unconventional coating technique to take place. The effects of ultrasonic bonding parameters on the change of mechanical properties of the coated tools are investigated through scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), micro-hardness analyses, and white light interferometry. The structure of the carbon nanotubes is investigated through transmission electron microscopy (pre coating) and cross-section of the bonded MWCNTs is studied via focused ion beam milling and SEM to evaluate the bonding between the multi-walled nanotubes. Optimum processing windows (i.e., bonding speed, energy, and pressure) are discovered for coating MWCNTs on PcBN. Focus ion beam milling analyses revealed a relationship between consolidation parameters and porosity of MW(pCNT) bonds. The proposed method paves the way for the novel design of functional coatings with attunable properties (i.e., thickness and hardness) and therefore improved productivity in the machining of aerospace and automotive parts.

Nanotwins-containing microstructure and superior mechanical strength of a Cu‒9Al‒5Fe‒5Ni alloy additively manufactured by laser metal deposition

Abstract Laser metal deposition (LMD) additive manufacturing was utilized to fabricate a Cu‒9Al‒5Fe‒5Ni alloy with a hierarchical microstructure and superior mechanical strength. An optimized processing window of LMD was established for printing the alloy with a relative density greater than 99% using laser power of 1000–1500 W, scanning speed of 0.5–1.5 m/min and hatch space of 1.5–2 mm. The LMD-printed alloy exhibited a microstructure consisting of a martensite β* phase, a Widmanstatten α phase, Fe3Al and NiAl nanoprecipitates, and nanotwins. The hierarchical microstructure comprising microscale cellular structures, sub-microscale grains, and nanoscale precipitates and twins was achieved. The cellular structures were formed by the martensite β* and α phases. The nanotwins were formed at the interface of the plate-like β* phase, which was induced by the low stacking fault energy of the alloy and high cooling rate of LMD. The Fe3Al precipitates were formed within the β* and α phases, while the NiAl precipitates were distributed in the β* phase. The yield strength, ultimate strength, and elongation of the LMD-printed alloy were 593–713 MPa, 769–949 MPa, and 10–12%, respectively. The yield strength of the LMD-printed alloy was 160% and 76% higher than that of the counterparts fabricated by casting and wire arc additive manufacturing, respectively, which was attributed to the synergistic effects of the underlying mechanisms including the Hall-Petch type strengthening, dislocation strengthening, precipitation strengthening, and solid solution strengthening. These findings validated the applicability of LMD for printing the Cu‒9Al‒5Fe‒5Ni alloy and facilitated the potential applications in marine and offshore industries.

Determination of Critical Dynamic Recrystallization Conditions and Mechanism Analysis of Ti600 High-Temperature Titanium Alloy

The dynamic recrystallization behavior of a high-temperature titanium alloy Ti600 has been investigated by hot compression tests at the strain rates of 0.001-10 s−1 and temperatures of 950-1010 °C. The grain boundary migration during deformation has been analyzed, and a critical DRX dislocation density associated with material essence and grain boundary mobility has been proposed to identify the main softening mechanism of Ti600. Additionally, JMAK model has been employed to describe the dynamic recrystallization behavior, which is essential to concerned dynamic recrystallization with material and deformation parameters to investigate the dynamic recrystallization behavior of Ti600. The activation energy QSRX has been calculated as 91.18 kJ. Finally, processing map has been established, and the optimal process window has been present. And EBSD experiments at different temperatures and strain rates have been conducted to deeply study the grain boundary distribution and crystal orientation.

Process Variation Analysis of Device Performance Using Virtual Fabrication: Methodology Demonstrated on a CMOS 14-nm FinFET Vehicle

A new methodology is demonstrated to assess the impact of fabrication inherent process variability on 14-nm fin field effect transistor (FinFET) device performance. A model of a FinFET device was built using virtual device fabrication and testing. The model was subsequently calibrated on Design of Experiment corner case data that had been collected on a limited number of processed fab wafers. We then performed 400 virtual experiments comprising seven sources of process variation. Using this virtual fabrication technique, we were able to identify a minimum gate-to-source/drain spacer thickness for a high-temperature post-EPI rapid thermal anneal (RTA) anneal process that avoided device subthreshold slope penalties. The model allowed us to determine the optimal Si recess depth target and process window prior to source/drain epitaxy. We obtained these results by reviewing device performance as a function of statistical process sensitivity and highlighting key process parameters requiring variation control. These experiments would have been impractical to perform in an actual fab, due to the time, cost, and equipment requirements of running 400 fab-based process variation experiments for each process parameter. This methodology can be used to avoid wafer-based testing during early technology development.

Impurity removal from Si by Si-Ca-Mg ternary alloying-leaching system

In this work, Si-Ca-Mg alloys were made with different compositions and solidification conditions to investigate the impurity segregation and separation performance from Si, especially for the crucial P impurity at several ppmw levels. Varying acid leaching parameters were also employed to investigate the optimized process window. Results indicate that the novel Si-Ca-Mg alloying-leaching system is valid for high P extraction. The ternary intermetallic phase Ca7Mg7.5±δSi14 appears as the main precipitate in all alloys to gather other minor impurities. Rapid cooling significantly reduced the size of precipitates and Si grain, the impurity segregation was also limited. In the acid leaching experiments, HCl is found as the most economical leaching agents among the studied combinations. Smaller particle size promotes the leaching efficiency, but the increment narrows with increasing Ca/Mg ratio. Leaching kinetics of the studied alloys was found following the modified Kröger-Ziegler model based on a cracking-shrinking mechanism. The impurity purification efficiency increases with increasing Ca/Mg mixing ratio, but significantly reduced by rapid cooling. An analytical model was developed for ternary alloy system to predict the P segregation and its removal with varying alloy concentration through the thermodynamic approach, which shows good agreements of the experimental results.

Intensive processing optimization for achieving strong and ductile Al-Mn-Mg-Sc-Zr alloy produced by selective laser melting

The Sc-containing AlMn alloy system produced by additive manufacturing (AM) has recently presented exciting new opportunities to achieve a step-change in mechanical properties, but its processability remains unclear. In this work, the optimum processing window for the Al-Mn-Mg-Sc-Zr alloy fabricated by selective laser melting (SLM) has been established for the first time. The window covers the range of processing parameters that can lead to a good combination of part density, strength, ductility, and processability. The alloys fabricated within this optimized processing window of SLM have the material relative density more than 99.8% with less porosity. Moreover, all these alloys have the yield strength exceeding 430 MPa and the ductility of over 17%. Further microstructural examinations suggest that such excellent mechanical properties are associated with a bimodal grain architecture. Also, a high number density of intermetallic particles has been detected in these two-grain regions. They are confirmed to be Al3Sc and Mn(Fe)-rich quasicrystal. Most of these particles distributing along grain boundaries are expected to pin the grain boundaries and contribute to the high strength of this alloy. The findings will provide an essential basis for achieving exceptional mechanical performance and intricate geometry designs of the alloy using AM.

Machine-learning assisted laser powder bed fusion process optimization for AlSi10Mg: New microstructure description indices and fracture mechanisms

In this study, a machine-learning approach based on Gaussian process regression was developed to identify the optimized processing window for laser powder bed fusion (LPBF). Using this method, we found a new and much larger optimized LPBF processing window than was known before for manufacturing fully dense AlSi10Mg samples (i.e., relative density ≥ 99%). The newly determined optimized processing parameters (e.g., laser power and scan speed) made it possible to achieve previously unattainable combinations of high strength and ductility. The results showed that although the AlSi10Mg specimens exhibited similar Al-Si eutectic microstructures (e.g., cell structures in fine and coarse grains), they displayed large difference in their mechanical properties including hardness (118 - 137 HV 10), ultimate tensile strength (297 - 389 MPa), elongation to failure (6.3 - 10.3%), and fracture toughness (9.9 - 12.7 kJ/m2). The underlying reason was attributed to the subtle microstructural differences that were further revealed using two newly defined morphology indices (i.e., dimensional-scale index Id and shape index Is) based on several key microstructural features obtained from scanning electron microscopy images. It was found that in addition to grain structure, the sub-grain cell size and cell boundary morphology of the LPBF fabricated AlSi10Mg also strongly affected the mechanical properties of the material. The method established in this study can be readily applied to the LPBF process optimization and mechanical properties manipulation of other widely used metals and alloys or newly designed materials.

Hybrid subtractive\u2013additive manufacturing processes for high value-added metal components

Hybrid process chains lack structured decision-making tools to support advanced manufacturing strategies, consisting of a simulation-enhanced sequencing and planning of additive and subtractive processes. The paper sets out a method aiming at identifying an optimal process window for additive manufacturing, while considering its integration with conventional technologies, starting from part inspection as a built-in functionality, quantifying geometrical and dimensional part deviations, and triggering an effective hybrid process recipe. The method is demonstrated on a hybrid manufacturing scenario, by dynamically sequencing laser deposition (DLM) and subtraction (milling), triggered by intermediate inspection steps to ensure consistent growth of a part.

Machine-Learning Assisted Laser Powder Bed Fusion Process Optimization for AlSi10mg: New Microstructure Description Indices and Fracture Mechanisms

In this study, a machine-learning approach based on Gaussian process regression was developed to identify the optimized processing window for laser powder bed fusion (LPBF). Using this method, we found a new and much larger optimized LPBF processing window than was known before for manufacturing fully dense AlSi10Mg samples (i.e., relative density ≥ 99%). The newly determined optimized processing parameters (e.g., laser power and scan speed) made it possible to achieve previously unattainable combinations of high strength and ductility. The results showed that although the AlSi10Mg specimens exhibited similar Al-Si eutectic microstructures (e.g., cell structures in fine and coarse grains), they displayed large difference in their mechanical properties including hardness (118 - 137 HV 10), ultimate tensile strength (297 - 389 MPa), elongation to failure (6.3 - 10.3%), and fracture toughness (9.9 - 12.7 kJ/m 2 ). The underlying reason was attributed to the subtle microstructural differences that were further revealed using two newly defined morphology indices (i.e., dimensional-scale index I d and shape index I s ) based on several key microstructural features obtained from scanning electron microscopy images. It was found that in addition to grain structure, the sub-grain cell size and cell boundary morphology of the LPBF fabricated AlSi10Mg also strongly affected the mechanical properties of the material. The method established in this study can be readily applied to the LPBF process optimization and mechanical properties manipulation of other widely used metals and alloys or newly designed materials.

Melting Curves of Triolein Polymorphs

AbstractHigh‐pressure treatment is a promising option for improving mechanical properties and processing parameters of fat‐containing products. To identify optimum processing windows, melting curves, crystallization kinetics, and pathways for transferring the optimized structures to atmospheric pressure need to be known. Here, we provide melting curves of different polymorphic forms of triolein in the industrially relevant pressure range. The melting points of different polymorphic forms are detected optically in thin samples during stepwise changes of pressure or temperature. For cross‐nucleated spherulites, this method allows determining the respective melting points of nuclei and overgrown structures. Tracing the melting curves to atmospheric pressure confirms previous identification of the polymorphic forms at high pressure and enables identifying a previously reported but undefined structure as the β2‐form. Employing Raman spectroscopy, it is confirmed that the polymorph remained unaltered during the pressure release. With increasing pressure, the melting curves of the different polymorphic forms approach each other until they successively merge at the highest pressure levels studied.

The Metal Gate Cut Process Development

The technology of FinFET has led to the continuity of device scaling and enabled the prolongation of Moore’s Law towards the 7 nm and beyond nodes. The gate cut last has been widely adopted since it can provide better SiP/SiGe growth environment, hence yielding the better electrical performance. However, this approach requires more complex process engineering at 3D structure. Both perfect physical structure and good electronic performance are challenging for gate cut last process.As is well known, the metal gate cut process is the only choice of 5nm FinFET and GAA FinFET, which directly determines the performance of FinFET. At present, the metal gate cut process has suffer the following difficulties: the Critical Dimension of the metal gate is only about 20nm, the height is over 100nm, and the aspect ratio has exceeded the limit of the most advanced etching tool; the metal gate complex composition, including more than 10 kinds of metal and insulation materials; the cut CD is very small, but the profile requirement is very challenging, all the metal layers are vertical, and the same CD is maintained from top to bottom. The bigger challenge is that the line end of metal gate cut is very close to germanium silicon or phosphor silicon. On the other hand, the metal's easy collection of charge and conduction will greatly increase the plasma induce damage risk, which needs to be controlled by properly selecting photo and etching conditions.We will start a study on the above issues and discuss the development direction and research ideas in each aspect. This manuscript will focus on plasma etching development during metal gate cut process. The CD shrinkage is very critical process in the soft mask etching process so as to break through the exposure limit of the immersion lithography. In general, immersion lithography with negative photoresist can not complete less than 40 nm CD, but gate cut, especially metal gate cut CD need as small as 20 nm. This puts forward very high requirements for soft mask etching. On the one hand, etch stop or defect cannot be caused with the large CD shrinkage; on the other hand, the CD should meet the design requirements and the patterning should be complete. We use the CxHyFz as etching gas with the advanced coupled plasma etching tool.We found the high/low bias pulsing scheme can reach balance on all sides, as the CD shrinkage, defect control, pattern transfer, line width roughness, the optimum process window. Another part will focus on metal cut etching process, cycle model is benefit to so many kinks of materials. Vertical profile show trade-off and ILD loss, we found the different design and requirement need to adopt different ILD remaining approach. At the same time, low Te etch process is key to avoid plasma induce damage.

Optimization of pulsed electric field assisted drying process of black soldier fly (Hermetia illucens) larvae

Optimization of important drying parameters with PEF pretreatment was carried out using Hermetia illucens larvae tissue. Three level factorial design of response surface methodology was used for the study varying specific PEF energy input 10–20 kJ/kg and drying temperature of 50–90 °C. Important average H. illucens larvae temperature during the drying process was obtained by numerical simulation from Luikov drying model. Consumption of drying energy was affected more by the drying temperature, than by the PEF energy. This indicated that range between 81 and 84 °C drying temperature and range from 11.2 to 13.1 kJ/kg of specific PEF energy input may be considered as optimal processing window for larvae drying.

Flow characterization of magnesium alloy ZK61 during hot deformation with improved constitutive equations and using activation energy maps

The present study aimed at characterizing the flow characteristics and workability of an as-extruded magnesium alloy ZK61 by isothermal compression tests performed at temperatures of 523–673 K and strain rates of 0.001–1s−1. The flow stress curves were analysed via considering the mechanism of microstructure evolution. Using the obtained flow stress data, both of the conventional and improved Arrhenius constitutive equations were developed to predict the flow characteristics, and the 3D activation energy maps were constructed to propose the optimal deformation conditions and reveal the effects of deformation parameters on microstructure evolution. It can be found that the strain factor plays an important role in determining the shapes of the flow stress curves, which exhibit three types of variation tendencies due to the flow softening and hardening behaviour as the strain increases. The improved constitutive equations resulted in excellent predictability of the peak flow stress within all the deformation conditions. Combining with the activation energy maps, the dominant deformation mechanisms, i.e., dynamic recrystallization and flow localization in different deformation regions were identified, and the optimal processing window of the alloy can be obtained at strain rate and temperature range of 0.001–0.01s−1 and 623 ~ 673 K under a strain of 0.9.

Laser sealing of PLA-based compostable coffee capsules

The aim of the present work is to examine the possibility of using laser technology to make welded joints to hermetically seal bioplastic containers with aluminum or bioplastic foils. Specifically, the focus is on the laser sealing process of compostable coffee capsules with toplids in aluminum and in paper coated with compostable plastic (mainly based on polylactic acid, PLA). The aluminum toplid does not allow obtaining a compostable package, but represents the currently most used standard on the coffee capsule market. The welded joints made with laser technology were characterized by peel-off tests to evaluate the adhesion strength of the toplid to the capsule with the laser operational parameters, namely processing and pre-heating laser power, scanning speed of the laser beam. The results of the peel-off test allowed optimizing the choice of the operational parameters of the laser sealing process for the various scenarios examined. Based on the experimental findings, 3D process maps have therefore been built in which the adhesion strength between the toplid and the capsule has been plotted by varying the laser operational parameters process, making it possible to identify the optimal processing windows.