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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Conversion of plastic waste into high-value lubricants: techno-economic analysis and life cycle assessment

Given the low recycling rate of plastic waste in the United States due to low economic incentives, it is of great interest to develop a technology to upgrade plastic waste with favorable economics. Plastic upcycling to valuable chemicals could ensure a circular economy for plastics and reduce the environmental burden caused by their end use cycle and disposal. A conceptual facility to convert 250 metric ton (MT) per day of plastic waste was modeled; the main product was a high-quality liquid (HQL) with a similar performance to polyalphaolefin (PAO) lubricants. The modeled process had a lubricant yield of up to 90% based on the experimental results at the laboratory scale. Techno-economic analysis (TEA) and life cycle assessment (LCA) were also performed to evaluate the process economics and its environmental impact. By using a mixture of colored and natural high-density polyethylene (HDPE), the production cost was in the range of 0.6–1.98 dollars per kg of lubricant, depending on the operating conditions. The life cycle emissions were in the range of 0.48–1.2 kg CO 2e kg Lub -1 showing, for the best case scenario, a 52% reduction relative to the emissions for petroleum lubricants, and a 74% reduction relative to the emissions for PAO lubricants. Finally, the impacts of the lubricant yield, the catalyst amount, and reaction time were evaluated, and their effect on the final production cost was discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

RB-TnSeq elucidates dicarboxylic-acid-specific catabolism in β-proteobacteria for improved plastic monomer upcycling

Dicarboxylic acids are key components of many polymers and plastics, making them a target for both engineered microbial degradation and sustainable bioproduction. In this study, we generated a comprehensive data set of functional evidence for the genetic basis of dicarboxylic and fatty acid metabolism using randomly barcoded transposon sequencing (RB-TnSeq). We identified four β-proteobacteria that displayed robust growth with dicarboxylic acid sole carbon source and cultured their mutant libraries with dicarboxylic and fatty acids with carbon chain lengths from C3 to C12. The resulting fitness data suggested that dicarboxylic and fatty acid metabolisms are largely distinct, and different sets of β-oxidation genes are required for catabolizing dicarboxylic versus fatty acids of the same carbon chain lengths. In addition, we identified transcriptional regulators and transporters with strong fitness phenotypes related to dicarboxylic acid utilization. In Ralstonia sp. UNC404CL21Col (R. CL21), we deleted two transcriptional repressors to improve its utilization of short-chain dicarboxylic acids. We exploited the diacid-utilizing catabolism of R. CL21 to upcycle a mock mixture of the dicarboxylic acids produced when polyethylene is oxidized. After introducing a heterologous indigoidine production pathway, this engineered Ralstonia produced 0.56 ± 0.02 g/L indigoidine from a mixture of dicarboxylic acids as a carbon source, demonstrating the potential of R. CL21 to upcycle plastic wastes to products derived from tricarboxylic acid (TCA) cycle intermediates. IMPORTANCE: Upcycling the carbon in plastic wastes to value-added products is a promising approach to address the plastic waste and climate crises, and dicarboxylic acid metabolism is an important facet of several approaches. Improving our understanding of the genetic basis of this metabolism has the potential to uncover new enzymes and genetic parts for engineered pathways involving dicarboxylic acids. Our data set is the most comprehensive interrogation of dicarboxylic acid catabolism to date, and this work will be of utility to researchers interested in both plastics bioproduction and upcycling applications.

Pearson, Allison N↗
DOE OSTI2022

The Critical Role of Process Analysis in Chemical Recycling and Upcycling of Waste Plastics

There is an urgent need for new technologies to enable circularity for synthetic polymers, spurred by the accumulation of waste plastics in landfills and the environment and the contributions of plastics manufacturing to climate change. Chemical recycling is a promising means to convert waste plastics into molecular intermediates that can be remanufactured into new products. Given the growing interest in the development of new chemical recycling approaches, it is critical to evaluate the economics, energy use, greenhouse gas emissions, and other life cycle inventory metrics for emerging processes, relative to the incumbent, linear manufacturing practices employed today. Here we offer specific definitions for classes of chemical recycling and upcycling and describe general process concepts for the chemical recycling of mixed plastics waste. We present a framework for techno-economic analysis and life cycle assessment for both closed- and open-loop chemical recycling. Rigorous application of these process analysis tools will be required to enable impactful solutions for the plastics waste problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Selective Plasticization of Poly (ethylene oxide) (PEO) Block in Nanostructured Polystyrene– PEO– Polystyrene Triblock Copolymer Electrolytes

The plasticization of a polymer electrolyte usually promotes its ionic conductivity but decreases its storage modulus due to the increased polymer chain flexibility. Herein, we show that such a tradeoff between the ionic conductivity and the mechanical robustness of the polymer electrolyte can be alleviated by selective plasticization of the ion-conductive block, such as poly(ethylene oxide) (PEO) in a polystyrene (PS)– PEO–PS block copolymer (SEO) electrolyte using an ether type plasticizer, tetraethylene glycol dimethyl ether (TEGDME). In this work, at maximum plasticizer loading, the room temperature ionic conductivity increases by up to 3 orders, whereas the storage modulus, G' reduces to half, is still on the order of 10 2 MPa. At above the melting temperature of the PEO block, the dynamic storage modulus, G' of the plasticized membrane surpasses its dry PS-PEO-PS counterpart. Such a phenomenon results from that, a) TEGDME co-crystallizes with PEO to promote its crystallinity and hence the storage modulus, b) TEGDME swells the amorphous PEO phase to enhance the polymer chain segmental mobility and hence ionic conductivity, and c) the PS phase remains intact from TEGDME to keep the SEO elastic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 304L Stainless Steel Alloy

Numerical simulations of metallic structures undergoing rapid loading into the plastic range require material models that accurately represent the response. In general, the material response can be seen as having four interrelated parts: the baseline response under slow loading, the effect of strain rate, the conversion of plastic work into heat and the effect of temperature. In essence, the material behaves in a thermal-mechanical manner if the loading is fast enough so when heat is generated by plastic deformation it raises the temperature and therefore influences the mechanical response. In these cases, appropriate models that can capture the aspects listed above are necessary. The material of interest here is 304L stainless steel, and the objective of this work is to calibrate thermal-mechanical models: one for the constitutive behavior and another for failure. The work was accomplished by first designing and conducting a material test program to provide data for the calibration of the models. The test program included uniaxial tension tests conducted at room temperature, 150 and 300 C and at strain rates between 10 –4 and 10 3 1/s. It also included notched tension and shear-dominated compression hat tests specifically designed to calibrate the failure model. All test specimens were extracted from a single piece of plate to maintain consistency. The constitutive model adopted was a modular $J_2$ plasticity model with isotropic hardening that included rate and temperature dependence. A criterion for failure initiation based on a critical value of equivalent plastic strain fitted the failure data appropriately and was adopted. Possible ranges of the values of the parameters of the models were determined partially on historical data from calibrations of the same alloy from other lots and are given here. The calibration of the parameters of the models were based on finite element simulations of the various material tests using relatively ne meshes and hexahedral elements. When using the model in structural finite element calculations, however, element formulations and sizes different from those in the calibration are likely to be used. A brief investigation demonstrated that the failure initiation predictions can be particularly sensitive to the element selection and provided an initial guide to compensate for the effect of element size in a specific example.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Co-gasification of Plastic, Coal Waste and Biomass for Hydrogen Rich Syngas Production

Plastic waste has increasingly become one of the most pressing environmental issues. To mitigate plastic emissions, extraordinary efforts are needed for plastic waste recycling and management. This study investigates the co-gasification of plastic, coal refuse, and biomass into hydrogen-rich syngas through steam gasification. The study focuses on the correlations between process parameters and feedstock composition. Coal refuse and biomass are used as co-feedstocks for gasification, aiming to improve the handling of plastic waste and investigating their synergistic effects on product distribution.

Bashir, Muhammad↗
DOE OSTI2025

Chemical Recycling of Plastic Waste to Higher Value Lubricants

The aim of this project was to develop scalable methods to convert plastic waste to petrochemical-equivalent feedstocks and demonstrate their utility in lubricant base oil and wax applications. These objectives were partially accomplished, by scaling up the synthesis of platinum-on-strontium titanate catalysts to twenty gram batches, scaling up the conversion of plastic waste to twenty-five grams of plastic, producing high-melt waxes and characterizing their properties, and demonstrating the purification of high-melt waxes. High-melt waxes are one petrochemical-equivalent feedstock that can be made from plastic waste, consisting of a hard wax with a melt point above 65 C. They are used as ingredients in hot melt adhesives, coatings, and cosmetics. Producing a petrochemical-equivalent feedstock from plastic waste provides an advantage in lower carbon footprint and manufacturing cost, as the waste feedstock costs less than crude oil.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Chemical Recycling of Mixed Plastics in Electronic Waste Using Solvent-Based Processing

Currently, less than 20% of electronic waste (E-waste) produced in the U.S. is recycled. To improve the recycling rate of E-waste, the study aimed to: (1) identify the major plastics found within electronic shredder residue (ESR), (2) design solvents and processing conditions capable of separating out 90% of the plastic in ESR, and (3) estimate the energy efficiency of the solvent-based process developed. Preliminary screening showed 25 wt.% of the ESR was composed of plastics, with two polymers dominating the sorted plastic fraction—polystyrene (PS, 40 wt.%) and acrylonitrile butadiene styrene (ABS, 25 wt.%). Subsequently, solvents and anti-solvents were screened using Hansen Solubility Parameter Theory for PS, ABS, and ESR dissolution. The pre-screening results showed dichloromethane (DCM) and tetrahydrofuran (THF) as the most effective solvents for PS and ABS, with methanol (MeOH) and ethylene glycol (EG) as the most effective anti-solvents. By optimizing the dissolution time and the solvents used, the highest polymer dissolution yield (99 wt.%) was achieved using DCM for 48 h. Both MeOH and EG precipitated 71 wt.% of the polymer fraction of ESR. EG removed more phosphorus containing flame retardants (94 wt.%) than MeOH (69 wt.%). Energy analysis indicated that the solvent-based processes could save 25–60% of the embodied energy for PS and ABS. Characterization showed that the solvent-based processing could preserve the high molecular weight fraction of the polymers while removing flame retardants at the same time. The results from this study prove the potential of solvent-based processing to produce secondary plastic materials from E-waste for cross-industry reuse.

Anderson, Lester↗
DOE OSTI2024

A Step toward Process Electrification: Microwave-Assisted Co-Gasification of Waste Plastics and Biomass to Produce Clean Energy

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.

Abedin, Ashraf↗
DOE OSTI2023

Orientation dependence of the effect of short-range ordering on the plastic deformation of a medium entropy alloy

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.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phototunable Lignin Plastics to Enable Recyclability

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.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of Plastic Deformation on Passivation Characteristics of Type 304 Stainless Steel

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.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identification of crystal plasticity model parameters by multi-objective optimization integrating microstructural evolution and mechanical data

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.

42 ENGINEERING↗
DOE OSTI2022

Geometric learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity

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.

42 ENGINEERING↗
DOE OSTI2022

Comparison of three state-of-the-art crystal plasticity based deformation twinning models for magnesium alloys

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.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recurrent neural network-based multiaxial plasticity model with regularization for physics-informed constraints

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.

42 ENGINEERING↗
DOE OSTI2024

Challenges in the mechanical recycling and upcycling of mixed postconsumer recovered plastics (PCR): A review

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.

Compatibilization↗
DOE OSTI2020

The roles of yield strength mismatch, interface strength, and plastic strain gradients in fatigue crack growth across interfaces

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.

42 ENGINEERING↗