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DOE OSTI2021

Peak states of molybdenum single crystals shock compressed to high stresses

In this work, to determine crystal anisotropy effects at high stresses, peak states behind the plastic shock waves were examined in BCC single crystals. Using plate impact experiments, molybdenum (Mo) single crystals were shock compressed up to 190 GPa elastic impact stress along [100], [110], and [111] orientations. Laser interferometry was used to measure wave velocities and particle velocity profiles at the Mo–LiF window interface. These data were analyzed to obtain in-material quantities in the peak states. The Hugoniots for [100] and [110] orientations were comparable, but the Hugoniot for the [111] orientation was different from the other two orientations. Also, these Mo single crystal Hugoniots display differences from the polycrystalline Mo Hugoniots. Although none of the differences can be considered large, the present results demonstrate that, unlike FCC metal single crystals (Cu, Al), some anisotropy is preserved in Mo single crystal Hugoniots even at high stresses.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Analytic insights into nonlocal energy transport: Steady state Fokker Planck theory in arbitrary Z plasmas

The generation of energetic electrons in laser fusion in an important issue. The electrons may either arise from a laser plasma instability, or from the uncoupled high temperature tail of a Maxwellian distribution. To study these in a laser fusion context, it is important to find a method accurate enough to be useful, and simple enough to be incorporated into a radiation hydrodynamics numerical simulation, the main workhorse for studying the laser fusion target. That is why analytic insights become important, they allow one to simplify the Fokker Planck theory so that a solution of it can be incorporated into a radiation hydrodynamic simulation. This work develops and analyzes a steady state Fokker Planck theory for plasmas of arbitrary Z. It develops a method of solving the simplified Fokker Planck method with a technique called sparse eigenfunction analysis. As a result, this method appears to work reasonably well when compared to the experimental results from the Rochester/NIF on plastic spherical targets with and without a silicon layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Amorphization in extreme deformation of the CrMnFeCoNi high-entropy alloy

Ever-harsher service conditions in the future will call for materials with increasing ability to undergo deformation without sustaining damage while retaining high strength. Prime candidates for these conditions are certain high-entropy alloys (HEAs), which have extraordinary work-hardening ability and toughness. By subjecting the equiatomic CrMnFeCoNi HEA to severe plastic deformation through swaging followed by either quasi-static compression or dynamic deformation in shear, we observe a dense structure comprising stacking faults, twins, transformation from the face-centered cubic to the hexagonal close-packed structure, and, of particular note, amorphization. The coordinated propagation of stacking faults and twins along {111} planes generates high-deformation regions, which can reorganize into hexagonal packets; when the defect density in these regions reaches a critical level, they generate islands of amorphous material. These regions can have outstanding mechanical properties, which provide additional strengthening and/or toughening mechanisms to enhance the capability of these alloys to withstand extreme loading conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Spike-based graph centrality measures

We derive several spike-based routines that compute or establish bounds on radial centrality measures for undirected graphs and trees without the use of matrix multiplication. These spike-based centrality measures utilize a direct embedding of graph nodes and edges into neurons and synapses, can be implemented with static synapses or plastic synapses, and rely on minimal post-processing of spike rasters. This work contributes to the growing set of graphical applications for neuromorphic hardware.

Hamilton, Kathleen↗

DOE OSTI2024

Designing Ti-6Al-4V microstructure for strain delocalization using neural networks

Abstract The deformation behavior of Ti-6Al-4V titanium alloy is significantly influenced by slip localized within crystallographic slip bands. Experimental observations reveal that intense slip bands in Ti-6Al-4V form at strains well below the macroscopic yield strain and may serially propagate across grain boundaries, resulting in long-range localization that percolates through the microstructure. These connected, localized slip bands serve as potential sites for crack initiation. Although slip localization in Ti-6Al-4V is known to be influenced by various factors, an investigation of optimal microstructures that limit localization remains lacking. In this work, we develop a novel strategy that integrates an explicit slip band crystal plasticity technique, graph networks, and neural network models to identify Ti-6Al-4V microstructures that reduce the propensity for strain localization. Simulations are conducted on a dataset of 3D polycrystals, each represented as a graph to account for grain neighborhood and connectivity. The results are then used to train neural network surrogate models that accurately predict localization-based properties of a polycrystal, given its microstructure. These properties include the ratio of slip accumulated in the band to that in the matrix, fraction of total applied strain accommodated by slip bands, and spatial connectivity of slip bands throughout the microstructure. The initial dataset is enriched by synthetic data generated by the surrogate models, and a grid search optimization is subsequently performed to find optimal microstructures. Describing a 3D polycrystal with only a few features and a combination of graph and neural network models offer robustness compared to the alternative approaches without compromising accuracy. We show that while each material property is optimized through a unique microstructure solution, elongated grain shape emerges as a recurring feature among all optimal microstructures. This finding suggests that designing microstructures with elongated grains could potentially mitigate strain localization without compromising strength.

Ahmadikia, Behnam↗

DOE OSTI2023

A Hardware and Software Co-design Framework for Energy Efficient Neuromorphic Systems

Neuromorphic systems can be realized by a variety of algorithms and architectures. A common understanding is that spiking neuromorphic designs, which encode information into spatio-temporal spiking events, are both a biologically-accurate and efficient way of processing information. However, representing the information through timing relationships induces sophisticated circuit designs in traditional CMOS-based implementations. In recent years, high-capacity resistive memory (RRAM, aka, memristor) has demonstrated great potential in mimicking synaptic behaviors. Several RRAM-based spiking neuromorphic designs exist, most of which focus on rate coding schemes. These designs simplify circuit implementations of neuron models and explore challenges such as unsatisfactory speed, resolution, and performance. As an alternative, we will explore temporal coding spiking neuromorphic systems that encode information as the relative timing of neuron activations (spikes), which have been proven to be more adaptive and energy-efficient. Developing a neuromorphic system for spiking neural network (SNN) inference and online training, however, faces some major technical challenges: (1) It lacks circuit implementation support for temporal-coding SNN to achieve satisfying power efficiency and accuracy; (2) Although existing research works have investigated memristive synapse and neuron designs for spike-timing-dependent plasticity, the non-ideal conditions in implementation, such as device variations and signal degradation, degrade online learning accuracy of large scale systems; and (3) Non-optimized, inter-layer data traffic in SNNs, leads to unnecessary data communication costs. In this project, we plan to address these challenges by a hardware and software co-design framework that incorporates solutions at the circuit, architecture, and algorithm levels. At the circuit-level, we will elaborate on the in-situ SNN processing element designs for supporting both inference and online training modes. Variation-aware schemes will be studied to improve reliability. At the architecture level, we propose a pipelined, asynchronous architecture to retain the timing resolution of spikes. At the algorithm level, we will investigate an innovative SNN training algorithm for enabling activation sparsification and reducing unnecessary data communication costs. This neuromorphic system will provide an effective solution to real-life energy-constrained applications and significantly contribute to the exploration of next-generation high-performance computing systems under the DOE context.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Deformation mechanisms of nanotwinned Al and binary Al alloys

The objective of this proposal is to investigate, at a fundamental level, the deformation mechanisms of nanotwinned (NT) Al alloys with high density twin boundaries (TBs) and stacking faults (SFs). Nanotwinned metals with low stacking fault energy (SFE), such as Cu and Ag, have shown outstanding strength and tensile ductility. Twin boundaries play a critical role to enhance the strength and work hardening ability of these metals and alloys, and thus lead to significant plasticity. Al alloys have ultra-high stacking fault energy, and thus are often considered to be nearly free from growth twins and SFs. However, our recent studies show that a significant number of nanotwins and 9R phase can be introduced in Al and certain Al alloys, and lead to high flow stresses.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Mercury Speciation via Diffusive Gradients Thin-Films Technology

Objectives: Develop and test various diffusive gradient in thin films (DGT) samplers for mercury - SRNL is developing reactive DGTS (rDGTs). Test chemistry to differentiate methylmercury from total and/or inorganic mercury in environmental samples. Fabricate and test rDGT samplers for deployment. Deploy the rDGTs in variable settings. Mercury is a persistent-bioaccumulative-toxic environmental pollutant. Mercury exists in different species such as elemental, inorganic, and methyl. Mercury speciation determine mercury behavior and toxicity. For example, methylmercury strongly accumulates in biota such as fish resulting in potential human health impacts. DGTs are innovative samplers to measure water concentration by diffusion and capture. Types of Hg DGTs used: Total Hg, Inorganic Hg, and Methyl Hg. Deployment Sites: Upper Three Runs, Lower Three Runs, Steele Creek, East Fork Poplar Creek (SRNL Sites), Horizons Creek, NOA Creek, Bruners Creek (ORNL Sites). DGT concentration estimates closely matched alternative measurements for soluble mercury at each Oak Ridge site - DGTs did not respond to particulate mercury. DGTs provide a representative measure for biota uptake since they are left out longer which allows for an average exposure concentration. DMA-80 provided an efficient and quick analysis. Variability in site location made a difference in Hg species. DGT preparations and sampling wasn't as quick and simple as microcolumn technology. Copper reagent degraded agarose gel - more work and cleaner data are needed to assess speciation in rDGTs. Future Work: Use cross-linked polyacrylamide for the collection layer for a stronger plastic. Make a copper diffusion layer without agarose. Test copper separation in lab using realistic stream conditions such as high organic carbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Insights into mixing of non-isothermal multi-polymer melts for complex plastics recycling

Catalytic recycling or upcycling of plastics is often limited not by catalyst performance, but by transport, arising from highly viscous, non-Newtonian polymer melts. In this work, we develop a reactor-scale framework that integrates rheological measurements, constitutive modeling, computational fluid dynamics (CFD), and experiments to quantify mixing, heat transfer, and dispersion in surrogate hydrocarbon melts representing mixed plastics systems. Temperature- and shear rate-dependent viscosity of low-density polyethylene (LDPE) and high-density polyethylene (HDPE) is measured to create two surrogate polymers (PLD and PHD) that capture the dominant shear-thinning flow behavior while neglecting strong elastic effects, enabling tractable simulation of non-isothermal, polymer-melt mixing using a Carreau-Arrhenius generalized Newtonian framework. Three-dimensional CFD simulations are employed to evaluate impeller performance in PLD using mixing time, cavern volume, thermal uniformity, and interfacial area for regimes in which viscoelastic effects are not dominant. We show that magnetic stir bars commonly used in lab-scale studies produce large thermal gradients (~60 °C) and poor mixing, even under idealized power delivery and polymer flow conditions. In contrast, close-clearance anchor impellers achieve near-isothermal operation, reduce mixing times by up to 5×, and provide >90% active circulation volume. We further demonstrate that, at low pseudo-Deborah number (De*), motor power requirements can be predicted directly from shear rate-dependent rheology using the Carreau-Arrhenius framework, enabling rational selection of operating conditions. Extension to surrogate immiscible multi-polymer systems based on PLD and PHD shows that interfacial area is highly sensitive to operating conditions and impeller design, with coaxial anchor-turbine configurations enhancing dispersion by up to 4 × .

Close-clearance impellers↗

DOE OSTI2023

Direct comparison between experiments and dislocation dynamics simulations of high rate deformation of single crystal copper

A long standing challenge in computational materials science is to establish a quantitative connection between the macroscopic properties of plastic deformation with the microscopic mechanisms of dislocations in crystalline materials. Although the discrete dislocation dynamics (DDD) simulation method has been developed for several decades with the goal of addressing this challenge, a one-to-one comparison between the DDD predictions on single crystal stress–strain curves and experimental measurements under identical conditions has not been possible to date. Such a comparison is an essential step towards establishing a dislocation-physics based theory of plasticity and a multiscale framework of the plastic behaviors of crystalline materials. Here we provide direct comparisons between the stress–strain curves of Cu single crystals under high strain rate loading in the [0 0 1] and [0 1 1] directions obtained from miniaturized desktop Kolsky bar experiments and those from DDD simulations under identical loading conditions. With an appropriate set of parameters, DDD simulations can produce stress–strain curves that are in reasonable agreement with the experimental results. However, the dislocation mobility values needed to achieve this agreement are an order of magnitude lower than expected based on previous measurements and atomistic simulations. We hypothesize that this discrepancy could be caused by drag forces from jogs and point defects produced during the plastic deformation. Cross-slip of screw dislocations is also found to be necessary to capture the experimental stress–strain behavior, especially for the [0 1 1] loading direction. Finally, this work provides an example of how direct comparisons between DDD simulations and experimental measurements can provide new insight into the fundamental mechanisms of plastic deformation.

36 MATERIALS SCIENCE↗

NASA NTRS1995

Simultaneous cerebrovascular and cardiovascular responses during presyncope

BACKGROUND AND PURPOSE: Presyncope, characterized by symptoms and signs indicative of imminent syncope, can be aborted in many situations before loss of consciousness occurs. The plasticity of cerebral autoregulation in healthy humans and its behavior during this syncopal prodrome are unclear, although systemic hemodynamic instability has been suggested as a key factor in the precipitation of syncope. Using lower body negative pressure (LBNP) to simulate central hypovolemia, we previously observed falling mean flow velocities (MFVs) with maintained mean arterial blood pressure (MABP). These findings, and recent reports suggesting increased vascular tone within the cerebral vasculature at presyncope, cannot be explained by the classic static cerebral autoregulation curve; neither can they be totally explained by a recent suggestion of a rightward shift in this curve. METHODS: Four male and five female healthy volunteers were exposed to presyncopal LBNP to evaluate their cerebrovascular and cardiovascular responses by use of continuous acquisition of MFV from the right middle cerebral artery with transcranial Doppler sonography, MABP (Finapres), and heart rate (ECG). RESULTS: At presyncope, MFV dropped on average by 27.3 +/- 14% of its baseline value (P < .05), while MABP remained at 2.0 +/- 27% above its baseline level. Estimated cerebrovascular resistance increased during LBNP. The percentage change from baseline to presyncope in MFV and MABP revealed consistent decreases in MFV before MABP. CONCLUSIONS: Increased estimated cerebrovascular resistance, falling MFV, and constant MABP are evidence of an increase in cerebral vascular tone with falling flow, suggesting a downward shift in the cerebral autoregulation curve. Cerebral vessels may have a differential sensitivity to sympathetic drive or more than one type of sympathetic innervation. Future work to induce dynamic changes in MABP during LBNP may help in assessing the plasticity of the cerebral autoregulation mechanism.

Non-NASA Center↗

NASA NTRS1993

Elastic-plastic finite element analyses of an unidirectional, 9 vol percent tungsten fiber reinforced copper matrix composite

Micromechanical modeling via elastic-plastic finite element analyses were performed to investigate the effects that the residual stresses and the degree of matrix work hardening (i.e., cold-worked, annealed) have upon the behavior of a 9 vol percent, unidirectional W/Cu composite, undergoing tensile loading. The inclusion of the residual stress-containing state as well as the simulated matrix material conditions proved to be significant since the Cu matrix material exhibited plastic deformation, which affected the subsequent tensile response of the composite system. The stresses generated during cooldown to room temperature from the manufacturing temperature were more of a factor on the annealed-matrix composite, since they induced the softened matrix to plastically flow. This event limited the total load-carrying capacity of this matrix-dominated, ductile-ductile type material system. Plastic deformation of the hardened-matrix composite during the thermal cooldown stage was not considerable, therefore, the composite was able to sustain a higher stress before showing any appreciable matrix plasticity. The predicted room temperature, stress-strain response, and deformation stages under both material conditions represented upper and lower bounds characteristic of the composite's tensile behavior. The initial deformation stage for the hardened material condition showed negligible matrix plastic deformation while for the annealed state, its initial deformation stage showed extensive matrix plasticity. Both material conditions exhibited a final deformation stage where the fiber and matrix were straining plastically. The predicted stress-strain results were compared to the experimental, room temperature, tensile stress-strain curve generated from this particular composite system. The analyses indicated that the actual thermal-mechanical state of the composite's Cu matrix, represented by the experimental data, followed the annealed material condition.

Sanfeliz, Jose G.↗

DOE OSTI2022

Catalytic production of tetrahydropyran (THP): a biomass-derived, economically competitive solvent with demonstrated use in plastic dissolution

Tetrahydropyran (THP) is a five-carbon heterocyclic ether that is non-carcinogenic, non-peroxide forming, biodegradable, and economically competitive with tetrahydrofuran (THF) as a solvent. In this work, THP has been synthesized from renewable biomass at >99.8% selectivity and 98% yield via hydrogenation of furfural-derived 3,4-dihydropyran (DHP) over Ni/SiO 2 in a continuous flow reactor at 150–200 °C. The apparent activation energy of THP formation is 31 kJ mol -1 , and the reaction orders with respect to the partial pressures of H 2 , DHP, and THP are: 2, 1, and -0.3. The kinetic data has been fitted to a Hougen–Watson model where the rate limiting step is the hydrogenation of adsorbed DHP. Ni/SiO 2 is shown to have a low deactivation rate constant of 0.012 h -1 over 100 h time on stream and can be regenerated in situ. As a performance advantage, THP is shown to be resistant to ring opening polymerization under strongly acidic conditions that THF is not, revealing it to be a superior solvent. Further, the minimum selling price of THP is competitive with the market price of THF ($$900 – 1400 per ton ) at a DHP feedstock cost of $1000 per ton. Conductor-like Screening Model for Real Solvents (COSMO-RS) and molecular dynamics (MD) simulations with 1008 solvents and 8 common plastics have demonstrated that THP can serve as an alternative solvent to THF, 2-methyltetrahydrofuran (MeTHF), and cyclopentyl methyl ether (CPME) for plastic dissolution, especially low-density polyethylene (LDPE), polypropylene (PP), polystyrene (PS) and polyvinyl chloride (PVC). This work establishes THP as a green solvent with excellent thermal, chemical and peroxidative stability that can be used for numerous applications, including waste plastic recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Supercritical water co-liquefaction of LLDPE and PP into oil: properties and synergy

The major plastic wastes are always mixtures, which are difficult to separate to treat in practice. Because of some possible cross-reactions, the degradation behaviors of plastics could not be mathematically represented by a simple addition of each polymer according to their proportions. This work examines supercritical water (scH 2 O) to liquefy poly-ethylene and poly-propylene mixtures into an oil with special interest in the oil quality and positive effect. Additionally, linear low-density polyethylene (LLDPE) and polypropylene (PP) were chosen as parent materials because of their high proportions in plastic wastes. The results show that a high conversion rate of around 99.75% was achieved with as high as 90.7 wt% oil yield without additional catalysts or hydrogen. The scH 2 O co-liquefaction of the LLDPE/PP mixture was different from that of the single polymer along with an improvement in the oil yield. Cyclic hydrocarbon ( i.e. , cyclic) generation was promoted while the production of paraffins was hindered in scH 2 O co-liquefaction using a mixture of LLDPE/PP. TGA reveals that the scH 2 O co-liquefaction of LLDPE/PP mixtures generated more diesel and lubricant oils and less gasoline and (jet fuel + light diesel) oils, thus slightly lowering the oil quality. Overall, the supercritical fluid technology was a powerful and promising means to liquefy mixed plastic wastes into oil at a high conversion rate free of catalysts or hydrogen.

42 ENGINEERING↗

DOE OSTI2023

Tailoring material microstructure and property in wire-laser directed energy deposition through a wiggle deposition strategy

Developing effective strategies to directly control material microstructure, property, and anisotropy is an active research area in metal additive manufacturing. This work develops a wiggle deposition pattern for wire-laser directed energy deposition (DED) of 316L stainless steel (SS) to modify the solidification texture, particularly in the building direction, in as-deposited samples. Through multi-physics simulation, operando near-infrared imaging, and synchrotron x-ray characterization, it is found that the wiggle deposition strategy induces highly dynamic melt flow and oscillating thermal gradient in the melt pool, which is responsible for the variation of preferable grain growth direction and crystallographic texture in the sample. The specific texture reduces the anisotropy in the tensile strength of as-printed 316L SS samples cut along different directions. Also, it largely increases the ductility along the build direction. Crystal plasticity simulation is performed to correlate the sample texture with mechanical property. In conclusion, this work offers a unique approach for tailoring local properties through the control of melt pool instability by applying different tool paths.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Analyzing Next-Generation Supply Chains Using the Materials Flows through Industry Tool

The Materials Flows through Industry (MFI) tool is a supply chain modeling tool developed at the National Renewable Energy Laboratory (NREL) with funding from the Department of Energy's Advanced Manufacturing Office. MFI was created to identify and analyze opportunities to reduce the energy and carbon intensities of the U.S. industrial sector (Hanes and Carpenter 2017). In this work, we present an overview of the MFI tool's structure and capabilities, as well as the results of using MFI to analyze a novel NREL-developed process to 'upcycle' PET plastic into higher-value composite materials (Rorrer et al. 2019). This process combines recycled PET (rPET) plastic with inputs that can be derived from biomass, including muconic acid, acrylic acid, and ethylene glycol, to chemically break down the plastic back to its monomers in a process called glycolization. Then, repolymerization and the application of fiberglass yields the valuable glass fiber reinforced plastic (GFRP) composite, a performance material used in the manufacture of wind turbine blades, boat hulls, and other applications. This rPET-derived GFRP was found to have superior strength and fiberglass adhesion compared to conventional GFRP formulations. Our findings indicate that this GFRP production process, were it to be widely commercialized beyond its current lab-scale, could potentially reduce the fossil energy intensity of the GFRP supply chain by between 37% and 58% compared to the conventional method of GFRP manufacture from fossil-derived inputs. We also estimate potential supply chain greenhouse gas (GHG) emissions reductions between 30% and 40% from this process. Scaling these GHG offset estimates up to annual GFRP production in the U.S. would be roughly equivalent to removing between 150,000 and 200,000 vehicles from U.S. roads. These ranges of impact estimates represent the range of differences associated with the various economic allocation methods we have assumed for the intensity contributions from the first life of the PET plastic. Following Shen et al. (2010), we derive economic allocation factors from the current price ratios of clear- and green-colored recycled PET plastic to virgin PET resin ('waste-valuation' approach) or assume them to be zero in a more simplistic allocation ('cutoff' approach). Future work involving the MFI modeling tool will also be discussed, including preliminary results comparing the energy intensity of conventional and bio-based nylons manufacturing. Attendees will also be encouraged to conduct MFI supply chain modeling of their own by requesting a user account on the MFI web application, which is freely available to the public at the following address: https://mfitool.nrel.gov.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Comparison of cracking behavior of nanocrystalline Cu film on substrates of different plastic deformation mechanisms

Nanocrystalline (NC) metallic thin films on metal substrates usually undergo substantial cracking at applied strains of a few percent due to strain concentration at the film/substrate interfaces. In this work, we show that the cracking of a nanocrystalline Cu film can be significantly inhibited by a NiTi substrate. NC Cu films are deposited on 304 stainless steel, Kapton and NiTi substrates, in which plastic deformation occurs via dislocation slip, molecule chain disentanglement and collective lattice shear, respectively. NC Cu film on NiTi substrate starts to show observable cracks at an applied strain of 24%, in contrast to 6% for that on steel and 15% for that on Kapton. Further, the crack density in the film on NiTi substrate is two to three orders lower than the counterparts. The discrepancy is suggested to attribute to the reduced local strain concentration enabled by the uniform lattice shear and high strain hardening of the NiTi substrate.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A Multicopper Oxidase from Paenibacillus Polyethylenelyticus JNU01 Oxidizes Polyethylene

Polyethylene (PE) is a widely used plastic that persists in the environment and resists breakdown via microbial degradation. In this work, we discovered a new bacterium, Paenibacillus polyethylenelyticus JNU01, that grows on a PE-like wax (PELW, 4 kDa) as its sole carbon source, causing chemical modifications to the substrate and releasing small-molecule products. Genomic and transcriptomic analyses identified a multicopper oxidase (PpMmcO) as a key enzyme candidate for this observed activity. PpMmcO promoted surface oxidation, increased hydrophilicity, and the release of small-molecule products such as ketones, alkanes, and alkenoic acids. Scanning electron microscopy confirmed surface damage on both PELW and post-use greenhouse PE films. Weight loss analysis showed mass losses of 5.2% for the PELW powder and 1.6% for the greenhouse PE film after treatment with wild-type PpMmcO. We propose a radical-mediated pathway catalyzed by PpMmcO. These findings identify a new bacterium and enzyme capable of promoting partial PE oxidation and provide insight into biological processes that may act on polyethylene.

36 MATERIALS SCIENCE↗