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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 55 records · Page 3

Photooxidation of Polyolefins to Produce Materials with In-Chain Ketones and Improved Materials Properties

Herein, we report a selective photooxidation of commodity postconsumer polyolefins to produce polymers with in-chain ketones. The reaction does not involve the use of catalyst, metals, or expensive oxidants, and selectively introduces ketone functional groups. Under mild and operationally simple conditions, yields up to 1.23 mol % of in-chain ketones were achieved. Installation of in-chain ketones resulted in materials with improved adhesion of the materials and miscibility of mixed plastics relative to the unfunctionalized plastics. The introduction of ketone groups into the polymer backbone allows these materials to react with diamines, forming dynamic covalent polyolefin networks. This strategy allows for the upcycling of mixed plastic waste into reprocessable materials with enhanced performance properties compared to polyolefin blends. Mechanistic studies support the involvement of photoexcited nitroaromatics in consecutive hydrogen and oxygen atom transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Compounds and composition for preparation of lithium-loaded plastic scintillators

A scintillator material includes a polymer matrix, a primary dye in the polymer matrix, the primary dye being a fluorescent dye; a secondary dye, and a Li-containing compound in the polymer matrix, where the Li-containing compound is a Li salt of a short-chain aliphatic acid. In addition, the scintillator material exhibits an optical response signature for thermal neutrons that is different than an optical response signature for fast neutrons.

Zaitseva, Natalia P.↗

Biocatalyst discovery and design for plastics deconstruction: A multi‐scale perspective

Plastic waste accumulation poses significant environmental challenges due to a lack of economical solutions for the molecular deconstruction of diverse synthetic polymers. Biological‐based degradation offers promise but is hindered by the crystallinity, hydrophobicity, and additive complexity of plastics, which restrict biocatalyst access and activity. To address these problems, we propose a multi‐scale framework that combines detailed materials characterization, optimization of plastic‐biomolecular interfacial interactions, and enhancement of biocatalytic kinetics to develop effective plastic‐deconstructing enzymes. This approach leverages principles from reaction kinetics, transport and interfacial phenomena, and enzyme engineering to systematically address barriers across diverse plastic types. Our framework aims to accelerate the discovery and optimization of biocatalysts capable of scalable, selective, and efficient deconstruction of plastic waste. These advances hold potential to enable sustainable biological recycling and upcycling pathways, contributing to global efforts in mitigating plastic pollution and promoting circular material economies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lithographic crystallinity regulation in additive fabrication of thermoplastics (CRAFT)

For semicrystalline polyolefin thermoplastics, the balance between interconnected ordered crystalline and disordered amorphous regions is paramount to their performance and processability. However, contemporary manufacturing strategies, from injection molding to three-dimensional (3D) printing, result in monolithic objects, unable to spatially encode crystallinity. We develop a light-based approach for fabricating mechanically robust polyolefin thermoplastics with microscopic control over crystallinity in 3D space. Light dosage governs polymer stereochemistry giving access to a continuum of materials, from strong rigid plastics, such as high-density polyethylene, to more extensible materials akin to low-density polyethylene, all at the flick of a switch. Leveraging this finding in lithographic grayscale 3D printing enables rapid multimaterial fabrication with voxel-level control over optical and mechanical properties, opening avenues in information storage, soft robotics, and energy damping.

36 MATERIALS SCIENCE↗

Changes in dislocation punching behavior due to hydrogen-seeded helium bubble growth in tungsten

The accumulation of gas atoms in tungsten is a topic of long-standing interest to the plasma-facing materials community due the metal's use as a divertor material in some tokamak fusion reactors. The nucleation and growth of He/H gas bubbles (along with their isotopes) can result from impinging fluxes of these gases which give rise to damage at the W divertor surface. The inclusion of He or H in W has been studied extensively by the community, finding that He bubbles modify the surface through periodic dislocation punching and bursting mechanisms while H bubbles impact the metal through plastic-strain induced material failure. However, the mechanisms which are present during the combined flux of both He and H is not well-studied atomistically. Motivated by this, an atomistic modeling study is conducted using molecular dynamics to assess the behavior of mixed concentration He:H bubbles in W. Here we find that the introduction of H into a growing He bubble results in a dramatic change in the nature and presence of dislocation loops which are typically generated via dislocation punching in over-pressurized He bubbles. Most notably, at high H concentrations, there is a switchover in energetic favorability from glissile 1/2<111> dislocations to sessile <100> dislocations. This thermodynamic crossover could imply a significant reduction in W surface morphology changes than with pure He bubbles and, additionally, we show this to have implications on the trapping of H in the bubbles and their associated dislocations.

36 MATERIALS SCIENCE↗

Structure-guided utilization of lignocellulose for catalysis, energy, and biomaterials

As a complex composite of cellulose, hemicellulose, and lignin, plant lignocellulose has long served as a major resource for biomass conversion, materials engineering, and bio-based product development. High-resolution structural insights enabled by solid-state nuclear magnetic resonance (ssNMR) now allow the mapping of polymer interfaces, identification of functional group accessibility, and tracking of molecular organization during processing, all of which are critical factors for optimizing catalytic strategies. These insights could drive transformative progress in lignocellulose-based applications, including selective depolymerization, improved pretreatment design, and efficient upcycling of lignin into resins, plastics, and biomedical materials. In industry-relevant contexts, such as biofuel generation and renewable material manufacturing, understanding the hydration dynamics, cross-linking patterns, and structural heterogeneity is also essential. The ability to visualize these features in native biomass presents a unique opportunity to develop new strategies for sustainability and performance. As the structural toolbox continues to expand, it is becoming a central enabler for innovations in renewable energy, green chemistry, and advanced bioproducts.

bioproduct↗

Strongly nonlinear wave propagation in elasto-plastic metamaterials: Low-order dynamic modeling

Nonlinear elastic metamaterials are known to support a variety of dynamic phenomena that enhance our capacity to manipulate elastic waves. Since these properties stem from complex, subwavelength geometry, full-scale dynamic simulations are often prohibitively expensive at scales of interest. Prior studies have therefore utilized low-order effective medium models, such as discrete mass-spring lattices, to capture essential properties in the long-wavelength limit. While models of this type have been successfully implemented for a wide variety of nonlinear elastic systems, they have predominantly considered dynamics depending only on the instantaneous kinematics of the lattice, neglecting history-dependent effects, such as wear and plasticity. Here, to address this limitation, the present study develops a lattice-based modeling framework for nonlinear elastic metamaterials undergoing plastic deformation. Due to the history- and rate-dependent nature of plasticity, the framework generally yields a system of differential-algebraic equations whose computational cost is significantly greater than an elastic system of comparable size. We demonstrate the method using several models inspired by classical lattice dynamics and continuum plasticity theory and explore means to obtain empirical plasticity models for general geometries, thereby gaining insight into the influence of microstructural plasticity on effective material performance, which can be used to improve the design of nonlinear mechanical metamaterials.

Dynamic simulation↗

Upcycling of Polystyrene Waste to Poly(ionic liquid) Materials

The C–H functionalization of commodity polymers could be a promising approach for upcycling plastic waste into advanced materials, which can alter the properties of the original materials through the introduction of different functionalities onto the existing backbone structures. In this study, waste polystyrene (PS) was modified by Friedel–Crafts acylation using 4-chlorobutyryl chloride (4-CBC) followed by reaction with N-alkylimidazoles to form cationic polyelectrolytes. These methods provide access to what are essentially poly(ionic liquid) (poly(IL)) materials with properties that are distinctly different from those of the PS from which they were formed. In one notable example, the glass transition temperature (T g ) of imidazolium-functionalized PS was ∼16 °C, which is a nearly 90 °C reduction from PS. This is also evidenced by macroscopic mechanical properties where the poly(IL) product is highly elastic in stark contrast to brittle PS. Moreover, the resulting ionomers showed self-healing behaviors in the presence of a “free” IL further contributing to the utility of the materials. Here, the methods in this work can open opportunities to utilize waste PS to obtain a vast array of poly(IL) materials with highly tailored structures and properties.

36 MATERIALS SCIENCE↗

Upcycling Polyethylene Waste into Hybrid Graphitic Porous Carbon Materials Used in High‐Performance Zinc‐Ion Hybrid Capacitors

Polyethylene (PE) waste is a challenge to upcycle into useful materials because this plastic tends to decompose into volatile compounds when heated at relatively low temperatures. In this work, mixtures of PE wastes into a hybrid graphitic porous carbon (HGPC) by a thermal oxidation pretreatment step, with assistance of an inert solid additive (KCl), to functionalize, crosslink, and stabilize the PE waste followed by carbonization and catalytic graphitization steps with a potassium carbonate catalyst, are upcycled. The PE waste‐derived HGPC (PW‐HGPC) has a hybrid structure composed of graphene‐like carbon nanosheets grown on the surface of carbon particles, high porosity with specific surface area, up to 1,763 m 2 g −1 , and good graphitic degree with average Raman I 2D / I G ratios of 0.53. When used as cathode material for zinc‐ion hybrid capacitors, this PW‐HGPC exhibits an excellent specific capacity, up to 126.7 mAh g −1 , at high mass loading of 10 mg cm −2 . Moreover, PW‐HGPC exhibits remarkable cycling stability with capacity retention of >94% after 10 000 cycles. Additionally, the KCl is recycled and reused over five times. This method provides a new solution for upcycling PE wastes into high value‐added carbon materials, not only for zinc‐ion hybrid capacitors but also for other electrochemical energy storage device applications.

hybrid graphitic porous carbon↗

Upcycling Polyethylene Waste Into Hybrid Graphitic Porous Carbon Materials Used in High-Performance Zinc-Ion Hybrid Capacitors

Polyethylene (PE) waste is a challenge to upcycle into useful materials because this plastic tends to decompose into volatile compounds when heated at relatively low temperatures. In this work, we report a chemical process that addresses this challenge by converting mixtures of linear low-density polyethylene (LLDPE), low-density polyethylene (LDPE), and high-density polyethylene (HDPE) waste into a hybrid graphitic porous carbon (HGPC) that can be used as a zinc-ion hybrid capacitor cathode. The process uses a low temperature thermal oxidation pre-treatment step, with assistance of an inert solid additive (KCl) to increase the effective surface area of the PE melt, to functionalize, cross-link, and stabilize the PE waste followed by carbonization and catalytic graphitization steps at higher temperatures with a potassium carbonate (K2CO3) catalyst. The PE waste derived HPGC (PW-HPGC) has a hybrid structure composed of graphene-like carbon nanosheets grown on the surface of carbon particles, high porosity with the Brunauer–Emmett–Teller (BET) specific surface area up to 1,763 m2g-1, and good graphitic degree with average Raman I2D/IG ratios of 0.53. When used as a cathode material for zinc-ion hybrid capacitors, this PW-HGPC exhibits an excellent specific capacity up to 126.7 mAhg-1 at high mass loading of 10 mgcm-2. Moreover, PW-HGPC exhibits remarkable cycling stability with capacity retention of >94% after 10,000 cycles at a current density of 2.0 A g-1.

hybrid graphitic porous carbon↗

Blocky Selective Postpolymerization C–H Functionalization of Polyolefins

C–H functionalization of commodity polyolefins affords functional materials derived from a high-volume, low-cost resource. However, current postpolymerization modification strategies result in randomly distributed functionalization along the length of the polymer backbone, which has a negative impact on the crystallinity of the resultant polymers, and thus the thermomechanical properties. Here, we demonstrate an amidyl radical mediated C–H functionalization of polyolefins to access blocky microstructures, which exhibit a higher crystalline fraction, larger crystallite size, and improved mechanical properties compared to their randomly functionalized analogues. Taking inspiration from the site-selective C–H functionalization of small molecules, we leverage the steric protection provided by crystallites and target polymer functionalization to amorphous domains in a semicrystalline polyolefin gel. The beneficial outcomes of blocky functionalization are independent of the identity of the pendant functional group that is installed through functionalization. Here, the decoupling of functional group incorporation and crystallinity highlights the promise in accessing nonrandom microstructures through selective functionalization to circumvent traditional tradeoffs in postpolymerization modification, with potential impact in advanced materials and upcycling plastic waste.

Neidhart, Eliza K. [The University of North Caroli↗

Compressibility and permeability of particulated non-recyclable municipal solid waste

Biofuels from non-recyclable municipal solid waste (NMSW) stand at the forefront of energy sustainability. However, their widespread adoption is hampered by persistent material handling issues stemming from the variability in NMSW material properties. An enhanced understanding of particulated NMSW properties, particularly compressibility and permeability, is essential to address the feedstock handling challenges and optimize the handling equipment. This study measures the compressibility and gas permeability of five streams of NMSW materials (i.e., rigid plastics, cardboard, thin film, paper, and foam) and their mixtures under different stress conditions. The results highlight the significant variability in compressibility and gas permeability among different streams, as well as the impacts of particle sizes. A semi-empirical model capable of predicting the gas permeability of NMSW mixtures is established and validated. Here, the results also highlight that reduced NMSW particle size helps promote consistency in NMSW feedstock’s physical and mechanical properties, which is favored for handling equipment design in waste-to-energy recovery facilities.

09 BIOMASS FUELS↗

Chain entanglements enable regeneration of high-performance thermosets

Thermoset plastics underpin structural materials, electronics and transportation, yet the permanent covalent networks that prevent flow and provide dimensional stability also make them difficult to recycle without sacrificing performance. In this work we show that high-performance thermosets can be built around dense chain entanglements, the physical interlacing of long polymer strands, rather than dense permanent crosslinks, with only a small number of selectively cleavable junctions preserving connectivity. Long, rigid, entangled polyolefin backbones generated by frontal polymerization form glassy polymers with high stiffness, high toughness and excellent creep suppression yet can be fully deconstructed into soluble, linear oligomers. Varying oligomer length and end-group chemistry enables their reuse as re-entangling building blocks that regenerate thermosets with thermal and mechanical properties that remain unchanged across generations. The strategy further extends to high-temperature fibre-reinforced composite matrices and additively manufactured structures, establishing chain entanglement as a design principle for durable, regenerable thermosets.

36 MATERIALS SCIENCE↗

Accurate and Fast Anomaly Detection in Additive Composite-Based Manufacturing using Thermal Cameras

Today, large-scale additive manufacturing with plastics and composite materials requires continuous monitoring by experienced staff to prevent, detect and correct anomalous events affecting the performance of the printed part. We address the complexity of this demanding task by designing a camera-based anomaly detection system utilizing probabilistic principal component analysis (PPCA). This is a machine learning technique is trained with thermal images collected during normal operation of the large-scale printer (Cincinnati BAAM). This technique is advantageous for practical applications as there is no need to artificially introduce anomalous conditions into model training. During deployment, we challenge this model by introducing deliberate variations of the extruder speed. We reduce extrusion speed to a lower level, between 70 and 95% of the nominal value to collected test images. Our results show that images are easily identified as anomalous for extruder speeds at or below 85% of the nominal speed, meaning that an anomalous reduction of the material deposition rate can be detected within seconds of its onset. We show that our results are robust to (a) camera-to-camera variability and (b) print-to-print variability.

Pike, John [ORNL]↗

Exploring New Applications of Municipal Solid Waste

This study aimed to (i) characterize municipal solid waste (MSW) sourced from Utah and Michigan transfer stations and (ii) upcycle, produce, and evaluate composites derived from this MSW. Composition analysis showed that the MSW was composed of a variety of commodity plastics, paper/cardboard, and inorganic materials. Detailed chemical analysis for lignin, cellulose, hemicellulose, and lipids was performed. The plastics identified were mainly polyethylene, polypropylene, polystyrene, and poly (ethylene terephthalate). The compoundability of the MSW was assessed by torque rheometry. Composites were prepared by compounding the MSW in an extruder. A composite flexural strength of 29 MPa and a modulus of 1.0 GPa was achieved. The thermal properties of the composites were also determined. The melt flow behavior of the MSW composites at 190 °C was comparable to wood plastic composite formulations.

characterization↗

Blending Compostable Plastics for Packaging Applications

Non-sustainable packaging materials (polymers) are a large portion of the increasing amount of plastic waste that become environmental pollutants. While many biodegradable or compostable polymers have been developed in recent years, most fail to compete with the non-sustainable polymers dominating the market, due to lack of certain desired properties, such as thermal (high melt temperature) and mechanical (high ductility) performance. For example, the popular compostable polymer polylactic acid (PLLA) has a high melt temperature but is very brittle. Another polymer, poly(d-valerolactone) (PVL) demonstrates great ductility but has a very low melt temperature. By blending PLLA and PVL, there is an opportunity to create a new biodegradable material with synergistic desired properties for packaging applications. In this study, we produce several (9) physical blends of PVL and PLLA with varying compositions of the two polymers while applying three different materials to make them more compatible (compatibilizers). We test the success of compatibilization by scanning electron microscopy (SEM), mechanic testing (strain at break) and differential scanning calorimetry (melting temperature). Overall, we highlight several promising materials with high compatibility and desired thermomechanical properties for sustainable packaging. Ideally, these materials could help mitigate future plastic pollution in Colorado and beyond.

blending↗

On the Onset of Plasticity: Determination of Strength and Ductility

The analysis of the work hardening variation with stress reveals insight to operative stress-strain mechanisms in material systems. The onset of plasticity can be assessed and related to ensuing plastic deformation up to the structural instability using one constitutive relationship that incorporates both behaviors of rapid work hardening (Stage 3) and the asymptotic leveling of stress (Stage 4). Results are presented for the mechanical behavior analysis of Ti-6Al-4V wherein the work hardening variation of Stages 3 and 4 are found to: be dependent through a constitutive relationship; be useful in a Hall-Petch formulation of yield strength; and provide the basis for a two point-slope fit method to model the experimental work hardening and stress-strain behavior.

36 MATERIALS SCIENCE↗

Active learning of a crystal plasticity flow rule from discrete dislocation dynamics simulations

Continuum-scale material deformation models, such as crystal plasticity (CP), can significantly enhance their predictive accuracy by incorporating input from lower-scale (i.e. mesoscale) models. The procedure to generate and extract the relevant information is however typically complex and ad hoc, involving decision and intervention by domain experts, leading to long development times. In this study, we develop a principled approach for calibration of continuum-scale models using lower scale information by representing a CP flow rule as a Gaussian process model. This representation allows for efficient parameter space exploration, guided by the uncertainty embedded in the model through a process known as Bayesian optimization (BO). We demonstrate a semi-autonomous BO loop which instantiates discrete dislocation dynamics simulations whose initial conditions are automatically chosen to optimize the uncertainty of a model CP flow rule. Our self-guided computational pipeline efficiently generated a dataset and corresponding model whose error, uncertainty, and physical feature sensitivities were validated with comparison to an independent dataset four times larger, demonstrating a valuable and efficient active learning implementation readily transferable to similar material systems.

36 MATERIALS SCIENCE↗