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Plastic zone extrusion may be provided. First, a compressor may generate frictional heat in stock to place the stock in a plastic zone of the stock. Then, a conveyer may receive the stock in its plastic zone from the compressor and transport the stock in its plastic zone from the compressor. Next, a die may receive the stock in its plastic zone from the conveyer and extrude the stock to form a wire.
Barely 9% of the 353 million metric tons of plastic waste produced worldwide over the last two decades has been recycled, with the majority of it being either landfilled or incinerated. Recycling and upcycling plastic waste is thus essential in mitigating environmental pollution. Gasification is the thermochemical conversion of solid carbon feedstock at high temperatures using a gasifying agent to produce hydrogen-rich syngas. Existing gasification technologies are energy-intensive and require high operating temperatures (>1000 °C), leaving them uncommercial. Microwave heating has sparked attention in a variety of chemical processes due to its specific advantages over traditional heating technologies, such as rapid and selective heating to improve process efficiency. NETL’s research team recently investigated the synergistic advantages of corn stover and mixed plastics in producing hydrogen-rich syngas via microwave heating. As a continuation of the research, this study provides an outlook over the non-catalytic versus catalytic effects of plastic-corn stover gasification via process electrification to enhance H2 production, minimize undesired tar, and improve process efficiency. Our aim is to provide complete electrification of the existing gasification process by using waste plastics as a starting block to produce valuable fuel and support the nation’s net zero goals.
An extreme extensibility with a true strain of 11.12 has been obtained for continuous columnar-grained (CCG) polycrystalline copper at room temperature, which was cold-drawn from a 10-mm-diameter as-cast rod into a 38.5-μm-diameter ultra-fine wire without any intermediate softening heat treatment. During the extreme plastic deformation, the ultimate tensile stress increased from 140 MPa for as-cast CCG copper to 525 MPa for the deformed sample at a true stain of 11.12, while the relative electrical conductivity maintained a high value of 97.6% IACS. On this basis, CCG copper is an excellent raw material for the fabrication of ultra-fine wires with both high strength and high electrical conductivity. The original columnar grains experienced grain subdivision and formed fibrous grains along the drawing direction with a fibrous longitudinal morphology and curly transverse microstructure at medium to high strain. The subdivision of the fibrous grains then went on as the extreme plastic deformation continued. Large amounts of strain-induced boundaries and microstructural refinement facilitated the storage of abundant glide dislocations created by extreme plastic deformation. Thus, extreme plastic extensibility can be achieved through continuous work hardening of CCG copper.
In this article, we present an energy dissipation analysis framework for granular material that is based on thermodynamics. Theoretical formulations are derived from the second law of thermodynamics, in conjunction with a few plausible assumptions on energy transformation and dissipation. The role of plastic free energy is emphasized by a conceptual experiment showing its physical nature. Theoretical formulation is adapted in order to be applied in elastic–plastic finite element method (FEM) simulations. Developed methodology is verified through comparison of input work, stored energy, and energy dissipation of the system. Lastly, separation of plastic work into plastic free energy and energy dissipation removes a common mistake, made in a number of publications, where energy dissipation can attain negative values (energy production) which is impossible.
The constitutive behavior of a hexagonal close-packed (HCP) polycrystalline ZEK100 magnesium alloy was investigated here using combined high energy X-ray diffraction (HEXRD) from a synchrotron source and crystal plasticity modeling approach. The in-situ tensile test data coupled with the HEXRD enabled the tracking of the lattice strain evolution during deformation. The microscopic behavior represented by lattice strain and the macroscopic behavior represented by stress-strain curves were then used together as objective function to estimate the critical resolved shear stress (CRSS) and hardening parameters of available slip and deformation twin systems in the ZEK100 alloy. An enhanced predominant twinning reorientation (ePTR) scheme was proposed in the current work, and the ePTR parameters were determined for the first time by the use of basal plane peak intensity along loading direction measured from HEXRD. Two crystal plasticity models, the computationally efficient elastic-plastic self-consistent (EPSC) and crystal plasticity finite element (CPFE) models, were developed incorporating the deformation twinning for the HCP-structured metals. The determined constitutive parameters were further validated by comparing the predicted deformation texture with the measured one. The work provides a useful and computationally-efficient modeling scheme to understand the slip/twin induced deformation behaviors of the ZEK100 alloy in micro- and macro-scales.
This work integrates in-situ neutron diffraction and crystal plasticity finite element modeling to study the kinematic stability of retained austenite in high carbon bearing steels. The presence of a kinematically metastable retained austenite in bearing steels can significantly affect the macro-mechanical and micro-mechanical material response. Mechanical characterization of metastable austenite is a critical component in accurately capturing the micro-mechanical behavior under typical application loads. Traditional mechanical characterization techniques are unable to discretely quantify the micro-mechanical response of the austenite, and as a result, the computational predictions rely heavily on trial and error or qualitative descriptions of the austenite phase. In order to overcome this, in the present work, we use in-situ neutron diffraction of a uniaxial tension test of an A485 Grade 1 bearing steel specimen. The mechanical response determined from the neutron diffraction analysis was incorporated into a hybrid crystal plasticity finite element model that accounts for the martensite's crystal plasticity and the stress-assisted transformation from austenite to martensite in bearing steels. Here, the modeling response was used to estimate the single crystal elastic constants of the austenite and martensite phases. Finally, the results show that using in-situ neutron diffraction, coupled with a crystal plasticity model, can successfully predict both the micro-mechanical and macro-mechanical responses of bearing steels while accounting for the martensitic transformation of the retained austenite.
Multi-principal-element alloys (also known as medium and high entropy alloys) offer a much larger and richer design space than conventional alloys, providing opportunities for discovering new functionalities and their governing physics. Some of these alloys exhibit an outstanding combination of high strength and ductility, linked to the activation of various deformation modes triggered by low-energy stacking faults. However, a pressing question remains: Is the plasticity of medium- and high-entropy alloys governed only by stacking fault energy, or does atomic short-range order (SRO) play a role? Here, to answer this, we investigated how SRO affects the deformation in single-crystalline NiCoCr, with previous contradictory findings. First, we established unique experimental evidence for SRO formation in bulk single crystals using high-energy synchrotron transmission X-Ray Diffraction. By tuning the degree of SRO by aging at high temperatures, twinning density and strain-induced martensitic phase transformation can be significantly increased in the [110] and [111] orientations under tension, increasing the tensile ductility; yet, no increase was observed along the [001] orientation due to lack of TWinning-Induced Plasticity (TWIP) or TRansformation-Induced Plasticity (TRIP), indicating a strong crystallographic orientation dependence. Our first-principles thermodynamic calculations unequivocally show SRO exists and governs the observed microstructural evolution and deformation hardening behavior. Here we find direct proof that SRO triggers a simultaneous TWIP and TRIP in NiCoCr, a rare microstructural evolution path. Our findings establish that the interplay of SRO and plasticity could be exploited to alter deformation modes and yield unprecedented mechanical response in medium- and high-entropy alloys.
The accumulation of non-degradable petrochemical plastics imposes a significant threat to the environment and ecosystems. We addressed this challenge by designing a new type of phototunable plastics based on the unique lignin chemistry to enable readily end-life recycling. The advanced material design leveraged the efficient photocatalytic lignin depolymerization by ZnO nanoparticles to build lignin-polymethyl methacrylate (PMMA)-ZnO blends. We first demonstrated the highly effective phototunable lignin depolymerization in the complex polymer blend matrix and explored the molecular mechanisms. The technical barriers of mechanical property and recycling processing were then addressed by a new blend design with lignin core grafted with PMMA polymer. The new process has resulted in a new type of PMMA-g-lignin blend, which significantly improved the mechanical properties, making it comparable to PMMA alone. More importantly, the mechanical properties of the UV-treated blend decreased drastically in the new design, whereas the properties did not reduce in the non-grafted blends upon UV exposure. The results highlighted that the new blend design based on graftization maximized the impact of lignin depolymerization on blend structure and recyclability. Based on the results, we developed a process integrating UV and alkaline treatments to recycle PMMA for plastics and fractionated lignin for bioconversion or other applications in the new phototunable plastics.
Life cycle analysis (LCA) of limonene plasticized poly(lactic acid) (PLA) films containing cellulose nanocrystals (CNC) extracted, by acid hydrolysis, from Phormium tenax leaf fibres, was assessed and compared with the results of acetyl tributyl citrate (ATBC) plasticized PLA films, having equivalent mechanical properties, containing organo-modified montmorillonite (OMMT). Eco-Indicator 99 tool has been adopted as the main method for life cycle assessment. Results indicated that, despite CNC are biobased fillers obtained by natural sources, the related chemical extraction leads to a large environmental footprint and a relatively relevant energy expense. LCA characterization of these films demonstrated that the environmental impact of PLA/limonene film reinforced with 1% in weight of CNC (PLA/CNC/limonene) is comparable to the environmental impact of polylactic acid films reinforced with OMMT and plasticized with a petroleum based plasticizer (ATBC) (PLA/OMTT/ATBC). A “cradle to gate” approach has been considered for both the film typologies.
We pose and solve the problem of the biaxial bending of an isotropic plate with through rectilinear crack by distributed bending moments applied at infinity. The edges of the crack are in contact over the zone of constant width and plastic zones are formed near the crack tips. By using the Tresca plasticity conditions in the form of a surface layer and a plastic hinge, we determine the length of the plastic zone and the crack opening displacements near the tips. The numerical analysis of the problem is performed.
Electrochemical response of Type 304 stainless steel, with different levels of plastic deformation, was investigated in solutions containing different amounts of H{sub 2}SO{sub 4} and KSCN at room temperature. Potentiodynamic polarization and double-loop electrochemical potentiokinetic reactivation (DL-EPR) techniques were used to characterize different levels of plastic deformation. The results have indicated that DL-EPR values and passivation current density increased with increase in plastic deformation. The DL-EPR values were correlated well with hardness and fraction of strain-induced martensite. Attack during DL-EPR tests occurred on strain regions within the matrix such as dislocations in austenite and martensite and/or interface between austenite and martensite. No well-defined correlation was observed between the levels of plastic deformation and potentiodynamic polarization behavior.
Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.
The history-dependent behaviors of classical plasticity models are often driven by internal variables evolved according to phenomenological laws. The difficulty to interpret how these internal variables represent a history of deformation, the lack of direct measurement of these internal variables for calibration and validation, and the weak physical underpinning of those phenomenological laws have long been criticized as barriers to creating realistic models. In this work, geometric machine learning on graph data (e.g. finite element solutions) is used as a means to establish a connection between nonlinear dimensional reduction techniques and plasticity models. Geometric learning-based encoding on graphs allows the embedding of rich time-history data onto a low-dimensional Euclidean space such that the evolution of plastic deformation can be predicted in the embedded feature space. Finally, a corresponding decoder can then convert these low-dimensional internal variables back into a weighted graph such that the dominating topological features of plastic deformation can be observed and analyzed.
In magnesium alloys, deformation twinning and its interactions with dislocation slip are responsible for a sigmoidal shape stress–strain behavior and an asymmetrical tension–compression yield strength in magnesium alloys. The sensitivity of twinning to the underlying microstructure renders the crystal plasticity method the most commonly adopted modeling approach for magnesium-twinning. This paper compares three state-of-the-art crystal plasticity-based twinning models from the literature, namely the elastic-viscoplastic self-consistent twinning-detwinning (EVPSC-TDT) model, crystal plasticity finite element model based on enhanced predominate twin reorientation approach (CPFE-ePTR), and the crystal plasticity finite element model based on “discrete twinning” approach (CPFE-DT). A polycrystalline microstructure is simulated with all three methods to compare the resulting stress–strain curves and lattice strains to those from the experimentally measured data. All three methods showed the capability of capturing the experimental results with different levels of accuracy. Additionally, the EVPSC-TDT method avoids solving the finite element matrices and showed the highest computational efficiency. The CPFE-ePTR model shows a higher accuracy in capturing the lattice strain. The CPFE-DT relies on high-resolution finite element mesh and is much slower than the other two methods, but it captured the local deformation concentration and stress reversal phenomena near the twin band, which was not possible with the other two methods. Based on the comparison, guidance for the selection of the appropriate model based on the specific modeling target is provided in this paper.
We report a recurrent neural network (RNN) based model is developed as a surrogate to predict nonlinear plastic response under multiaxial loading. The RNN-based model is trained and tested on stress versus strain curves generated using a numerical solution based on the classical radial return method. Besides simply learning the basic constitutive relationship, a novel approach is taken to enforce certain physical conditions. Specifically, regularization is employed to maintain non-negative plastic power density throughout the loading history thereby ensuring monotonically increasing plastic work and thermodynamic consistency. Enforcing physics in this manner permits coupling of the data-driven RNN approach with physics-based knowledge and laws. This has the effect of reducing the necessary amount of data and ensuring known physical laws are not violated. Since, once trained, the model need not perform the expensive task of solving nonlinear equations, its efficiency is orders of magnitude greater than its numerical counterpart. The RNN-based model has been trained on varied sets of data and the accuracy on test datasets validated. The developed model is general and robust and has widespread application such as in the simulation of metal forming, large scale plasticity, and part life prediction.
The presence of chemically different and compositionally varying plastics in mixed postconsumer recovered plastic (PCR) presents daunting barriers to recycling and upcycling efforts. This review systematically outlines how different processing techniques and characterization methods can be implemented to improve PCR's mechanical recycling and upcycling processes. The review further addresses the recycling challenges in the processing of mixed plastics from PCR and how their mechanical properties can be enhanced by making use of different types of compatibilizers such as copolymers, Janus nanoparticles as well as different approaches such as solid-state pulverization and microfibrillarization. In addition, the state-of-the-art applications of recycled plastics usage in automotive and construction are reviewed.
An irreversible cohesive zone model was used to understand how plastic strain gradients and yield strength mismatches affect fatigue crack growth across bi-material and multilayer interfaces for a range of interface strengths. Parametric studies identified regimes of penetration through the interface, deflection into the interface, and a transition where cracks extend on both paths. Plastic strain gradients strongly influence the transition regime, and a yield strength mismatch is necessary to cause deflection. For crack growth across an interlayer, interactions between the interfaces occur when the crack-tip plastic zone spans the interlayer. Plastic strain gradients promote penetration through the interlayer.
In this work, the influence of grain boundaries on plastic deformation was studied by carrying out nanoindentation near grain boundaries (GBs). Surface topographies of indentations near grain boundaries were characterized using atomic force microscopy (AFM) and compared to corresponding single crystal indent topographies collected from indentations in grain interiors. Comparison of the single crystal indents to indents adjacent to low-angle boundaries shows that these boundaries have limited effect on the size and shape of the indent topography. Higher angle boundaries result in a decrease in the pile-up topography observed in the receiving grain, and in some cases increases in the topographic height in the indented grain, indicating deformation transfer across these boundaries is more difficult. A crystal plasticity finite element (CPFE) model of the indentation geometry was built to simulate both the single crystal and the near grain boundary indentation (bi-crystal indentation) deformation process. The accuracy of the model is evaluated by comparing the point-wise volumetric differences between simulated and experimentally measured topographies. Good agreement, in both single and bi-crystal cases, suggests that the crystal plasticity kinematics plays a dominant role in single crystal indentation deformation, and is also essential to bi-crystal indentation. Despite the good agreement, some differences between experimental and simulated topographies were observed. These discrepancies have been rationalized in terms of reverse plasticity and the inability of the model to capture the full resistance of the boundary to slip. Lastly, this is discussed in terms of dislocation nucleation versus glide in the model and in the physics of the slip transfer process.