Green and durable engineered cementitious composites (GD-ECC) with recycled PE fiber, desert sand, and carbonation curing: Mixture design, durability performance, and life-cycle analysis
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Construction & Building Technology↗
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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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A fast computational framework for the design of solvent-based plastic recycling processes
Multicomponent plastics cannot be processed using mechanical recycling technologies, hindering efforts to deal with plastic waste. Multicomponent plastics include multilayer plastic films, which are widely used for food and healthcare packaging. Multilayer films combine several layers (potentially dozens) of different polymers to protect products from external factors (e.g., oxygen, water, temperature, shock, and light). Solvent-based separation processes have emerged as a promising alternative to recycle these complex materials. For instance, the Solvent-Targeted Recovery and Precipitation (STRAP TM ) process uses sequential solvent washes to selectively dissolve and separate constituent polymers from multicomponent plastic waste, including films. STRAP TM process design (separation sequence, type of solvents, and operating conditions) changes significantly depending on the design of the multilayer plastic film (e.g., number, types, and proportions of polymers). The ability to quickly quantify the economic and environmental benefits of diverse STRAP TM process designs is essential to accelerate the development of sustainable recycling processes and more recyclable multilayer film products. In this work, we present a fast computational framework that integrates molecular-scale models, process modeling, and techno-economic and life cycle analysis to quickly evaluate STRAP TM designs. The computational framework is general and can be used to study the processing of complex multilayer plastic waste streams that contain many layers. Furthermore, we highlight the different uses of the framework via targeted case studies.
Computational framework↗
Closed‐Loop Recyclable Vitrimer Plastics from PET Waste: A Design for Circularity
Plastics are essential to modern society, but their low recycling rates and inefficient end-of-life management pose a significant environmental challenge. Herein, the efficient strategy for upcycling postconsumer poly(ethylene terephthalate) (PET) waste into robust, closed-loop recyclable vitrimer plastics and composites is presented to address this issue. The catalyst-free aminolysis utilizes readily available amines to deconstruct diverse PET wastes into macromonomers, which are upcycled into vitrimers, exhibiting superior mechanical properties and exceeding the ultimate tensile stress and Young's Modulus of virgin PET by 80% and 150% respectively. These vitrimers exhibit excellent healability, shape memory, thermal reprocessability, and closed-loop chemical recyclability, enabling quantitative macromonomer recovery even from mixed plastic waste streams and glass/carbon fiber reinforced vitrimer (G/CFRV) composites. Furthermore, the vitrimer resin yields robust GFRV and CFRV composites with tensile strengths exceeding those of traditional epoxy composites by 100% and 80%, respectively, while maintaining complete chemical recyclability of both constituent materials. A preliminary technoeconomic analysis confirms the costeffectiveness and competitiveness of the facile PET deconstruction approach, which is potentially adaptable to other condensation polymers. Further, this study presents a facile approach to upcycling plastic waste into circular plastics and composites, offering a sustainable solution to global plastic waste management and fostering a circular economy.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Enabling Partnership between South Carolina and NREL for Advancing Opportunities in Plastics Recycling Research (EPSCOR for Plastics Recycling)
Proposal Objectives: 1. Utilize depolymerization/fractionation techniques to recover highly processable and reactive feedstocks for polymer synthesis from lignin. 2. Synthesize lignin‐derived non‐isocyanate polyurethane, epoxy, and polyamide using non‐ toxic, biobased route designed for chemical recycling. Characterize resulting materials. 3. Design a high‐yielding chemical recycling process for as‐synthesized materials yielding usable building blocks for many generations of polymer synthesis. 4. Optimize chemical recycling of PET waste for the synthesis of lignin‐based polymers. Compare properties to commercial materials. 5. Optimize reaction conditions and recycling steps to facilitate enhanced sustainability of the synthetic steps and final properties of materials. 6. Complete a lifecycle assessment of lignin utilization and chemical recycling to compare their environmental performance to that of materials produced from virgin material. Identify hot spots and benefits using the chemical recycling process.
36 MATERIALS SCIENCE↗
Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach
Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.
Estela‐García, John E. [Polymer Engineering Center↗
Sustainable bioleaching of lithium-ion batteries for critical metal recovery: Process optimization through design of experiments and thermodynamic modeling
Recycling spent lithium-ion batteries (LIBs) could alleviate supply risks for critical metals and be less harmful to the environment compared to new production of metals from mining. Developing a cost-effective LIB bioleaching process could be a promising alternative to traditional energy-intensive recycling technologies. Here, this study aimed to optimize bioleaching conditions for maximum economic competitiveness through design of experiments using iterative response surface methodology (RSM), assisted by thermodynamic modeling. The optimal condition was identified as 2.5% pulp density in 75 mM gluconic acid biolixiviant at 55°C for 30 h which could recover 57%–84% of nickel, 71%–86% of cobalt, and 100% of lithium and manganese, yielding a 17%–26% net profit margin. The recommended pulp density and acid concentrations, together with the observed metal solubilization, were supported by thermodynamic modeling predictions. Our study demonstrated that combining RSM with thermodynamic simulations could be a powerful tool for optimizing bioleaching conditions.
60 APPLIED LIFE SCIENCES↗
Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels (Final Scientific/Technical Report)
The project, "Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels," represents a significant advancement in nuclear fuel recycling technology. It integrates cutting-edge multimodal sensor fusion, machine learning (ML), and digital twin (DT) technologies to address challenges in material safeguarding, process optimization, and regulatory compliance for pyroprocessing facilities. This research has significantly enhanced the understanding of pyrochemical fuel recycling processes by developing innovative tools and methodologies. The Multimodal Safeguards Monitoring Unit (MSMU) combines electroanalytical techniques, Raman spectroscopy, and differential thermal analysis (DTA) to enable high-fidelity, near-real-time material accountancy measurements. Machine learning techniques, such as Long Short-Term Memory (LSTM) autoencoders, are utilized to detect anomalies in material balances and sensor data, improving the reliability of safeguards monitoring. Additionally, digital twin technology has been established to provide real-time system-level monitoring and diagnostics, integrating physics-based models with sensor data to optimize process safety and efficiency.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Design and Analysis of a Flexible, Reliable Deep Space Life Support System
This report describes a flexible, reliable, deep space life support system design approach that uses either storage or recycling or both together. The design goal is to provide the needed life support performance with the required ultra reliability for the minimum Equivalent System Mass (ESM). Recycling life support systems used with multiple redundancy can have sufficient reliability for deep space missions but they usually do not save mass compared to mixed storage and recycling systems. The best deep space life support system design uses water recycling with sufficient water storage to prevent loss of crew if recycling fails. Since the amount of water needed for crew survival is a small part of the total water requirement, the required amount of stored water is significantly less than the total to be consumed. Water recycling with water, oxygen, and carbon dioxide removal material storage can achieve the high reliability of full storage systems with only half the mass of full storage and with less mass than the highly redundant recycling systems needed to achieve acceptable reliability. Improved recycling systems with lower mass and higher reliability could perform better than systems using storage.
reliability↗
Design of solvent-assisted plastics recycling: Integrated economics and environmental impacts analysis
In 2018, the United States generated over 35. 7 million tons of plastic waste, with only 8.4% being recycled and the other 91.6% incinerated or disposed of in a landfill. The continued growth of the polymer market has raised concerns over the end of life of plastics. Currently, the waste management system is faced with issues of inefficient sorting methods and low-efficiency recycling methods when it comes to plastics recycling. Mechanical recycling is the commonest recycling method but presents a lower-valued recycled material due to the material incompatibilities introduced via the inefficient sorting methods. Chemical recycling offers a promising alternative as it potentially allows for plastics to maintain their original properties. To that end, there is the need to investigate feasible chemical recycling methods to help mitigate the challenging problem posed by plastics at the end-of-life stage. This work proposes a conceptual solvent-assisted plastics recycling framework based on a superstructure optimization approach. This framework is evaluated using a representative case study to recover Polyethylene Terephthalate (PET). In this case study, it is found that polymer recovery is both economically and environmentally favorable when compared to traditional methods of disposal such as incineration.
Lehr, Austin L.↗
An optimization approach for cryogenic distillation-based protium removal systems in magnetic fusion energy fuel cycles
Tritium inventory reduction for fusion power plants is central to the successful adoption of fusion energy. The advent of direct internal recycling in deuterium-tritium fusion fuel cycle design has led to significant reduction in startup tritium inventory estimates for fusion power plants but requires an isotope rebalancing and protium removal (IRPR) system to ensure acceptable isotopic fuel composition. Cryogenic distillation is a potential solution for near-term deployment in an IRPR system due to its demonstrated performance in similar operating regimes. Using protium removal in the fuel cycle as the primary performance metric, this paper presents an optimization methodology for a single-column continuous cryogenic distillation-based IRPR system for a 500 MW fus magnetic fusion device. Distillation column optimization was performed using the CryOgenic Distillation For Isotopic Separation of Hydrogen (CODFISH) code developed at Savannah River National Laboratory. The distillation column design presented maximizes direct recycling of hydrogen isotopes from the fusion chamber exhaust to the fueling system while minimizing IRPR system steady-state tritium inventory. The optimized IRPR distillation column presented achieves direct recycling of 60 % of the hydrogen isotopes in the fusion chamber exhaust with an estimated steady-state system tritium inventory <30 g. In conclusion, the optimized IRPR distillation column operation was then used to estimate the design requirements for a detritation column to treat the IRPR system effluent stream.
CryOgenic distillation↗
Solar Photovoltaic Module Recycling: A Survey of U.S. Policies and Initiatives
Industry stakeholders, regulators, and policymakers in the United States are starting to develop policies for PV module recycling. Well-designed policies could reduce negative environmental impacts and resource constraints while opening new market and employment opportunities. This paper summarizes drivers, barriers, and enablers related to PV module recycling, which might be addressed via policy. It then analyzes existing and proposed U.S. policies that may affect PV module recycling. Among the global and national voluntary industry stewardship standards related to EoL PV management, this paper discusses a Solar Energy Industries Association program encouraging PV recycling among its U.S. membership. The paper concludes with a synthesis of policy-related factors that may encourage effective EoL PV module management.
14 SOLAR ENERGY↗
Polymer Deconstruction and Redesign Strategies for Plastics Recycling
Advancing plastics recycling requires both the selective deconstruction of existing polymers and the design of new materials that enable efficient reuse without loss of performance. This perspective highlights an integrated approach that is rooted in polymer chemistry, catalysis, and process engineering which can enable a circular plastics economy. Here, we outline recent advances in catalytic, solvolytic, and enzymatic pathways for plastic deconstruction, and examine the molecular design principles driving next-generation recyclable-by-design and bio-based polymers. Despite these advances, major knowledge gaps remain in understanding the evolution of polymer morphology and catalyst structure during deconstruction, assessing deconstruction processes with realistic polymers, and offering redesigned polymers with competitive cost and environmental advantage over conventional plastics. United States Department of Energy (U.S. DOE) national laboratories offer unique capabilities to address these challenges through in situ and operando characterization, high-throughput experimentation, environmental studies, technoeconomic and life cycle assessment, scale-up support, and collaboration networks. Advances made in understanding plastic deconstruction mechanisms and structure-property correlations of redesigned polymers inform emerging research directions including autonomous experimentation, real-time feedback-enabled process optimization, and protein engineering for enzymatic depolymerization.
36 MATERIALS SCIENCE↗
Fluoride-Catalyzed Siloxane Exchange as a Robust Dynamic Chemistry for High-Performance Vitrimers
Sustainable development of new technologies requires materials having advanced physical and chemical properties while maintaining reprocessability and recyclability. Vitrimers are designed for this purpose; however, their dynamic covalent chemistries often have drawbacks or are limited to specialized polymers. Here, fluoride-catalyzed siloxane exchange is reported as an exceptionally robust chemistry for scalable production of high-performance vitrimers through industrial processing of commodity polymers such as poly(methyl methacrylate), polyethylene, and polypropylene. The vitrimers show improved resistance to creep, heat, oxidation, and hydrolysis, while maintaining excellent melt flow for processing and recycling. Furthermore, the siloxane exchange between different vitrimers during mechanical blending results in self-compatibilized blends without any compatibilizers. In conclusion, this offers a general, scalable method for producing sustainable high-performance vitrimers and a new strategy for recycling mixed plastic wastes.
36 MATERIALS SCIENCE↗
Mapping structures and dynamics with frequency-correlated diffusion exchange
Understanding molecular motion in diffusion-driven complex environments is critical for designing sustainable materials and improving chemical processes. Here, we introduce a multidimensional nuclear magnetic resonance (NMR) method that captures how molecular populations exchange across different dynamic regimes. By extending the modulated gradient spin-echo technique to include frequency-frequency correlations, our approach reveals diffusion pathways that are otherwise obscured in heterogeneous systems. Implemented on a unilateral NMR magnet, the method eliminates gradient pulsing constraints and accesses dynamics in the kilohertz regime. We apply this technique to swelling and acid-catalyzed deconstruction of cross-linked and linear polymers to observe how structural heterogeneity evolves over time. By linking molecular motion to topology and chemical state, we extract physical metrics such as fractal surface dimensionality and reaction wavefront velocity, properties inaccessible with standard diffusion measurements. This work expands the capabilities of NMR for probing soft matter, with implications for polymer recycling and materials design.
Fricke, Sophia N. [University of California, Berke↗
Superstructure Optimization of Waste Plastic Pyrolysis, Integrating Thermal, Catalytic, and Plasma Technologies with Machine Learning
Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.
Life cycle assessment↗
Stabilization of Preternatural Barium Oxidation States as an Unexpected Byproduct of β-Decay: Discovery of a New Halide Semiconductor Alloy
137 Cs has a wide range of roles in the nuclear industry. The solid material, safely encapsulated in CsCl as 137 CsCl, is stored as fission product waste from nuclear power production and legacy waste from nuclear weapons production; it has also served as a radiation source in food and sewage irradiators as well as medical devices. However, because of the solubility of the chloride salt and the relatively high specific activity of 137 Cs, damaged or broken capsules can lead to severe radiological accidents. Safe capsule design and material recycling are complicated by the unclear structural evolution during β-decay, which remains ambiguous due to the differing oxidation states of Cs (1+) and Ba (2+). Here, in this study, we use first-principles calculations to investigate the evolving structure–property relationships of Cs 1–x Ba x Cl during β-decay. Despite the well-established 2+ formal oxidation state of alkali-earth metals, we find that Ba 1+ can be stabilized in the form of a mixed-valence alloy at low concentrations. Specifically, we identify three regimes for the β-decay of 137 Cs into CsCl: Ba-doped CsCl (Ba ≤ 14%), wherein Ba has the expected 2+ oxidation state; Cs–Ba–Cl alloys, where Ba has a mix of the usual Ba 2+ and highly unusual Ba 1+ oxidation state in the form of a quasi-disordered mixed-valence alloy (Ba = 25%); and phase separation into a CsCl + BaCl 2 + Ba (m) mechanical mixture, where Ba reverts to its expected 2+ oxidation state (Ba > 25%). Surprisingly, the Cs 0.75 Ba 0.25 Cl mixed-valence alloy is a narrow indirect band gap semiconductor (1.05 eV) despite the insulating nature of both CsCl and BaCl 2 . It also exhibits strongly excitonic polarized optical properties, has glass-like ultralow thermal conductivity (directional average of 0.21 W/mK at 300 K), and shows greater resistance to deformation under both tensile and volumetric strengths compared with the original CsCl structure (e.g., shear and Young’s modulus of 9.04 and 31.62 GPa, respectively). These findings imply that transmutation of 137 Cs leads to highly unusual chemical bonding that stabilizes Ba 1+ in local regions of the quasi-disordered Cs 0.25 Ba 0.75 Cl, resulting in anomalous physical properties. Moreover, this discovery provides valuable insight for safe nuclear waste capsule design, which can aid in preventing environmental or human exposure to radioactive materials.
Fuhr, Addis S. [Oak Ridge National Laboratory (ORN↗
PV DMFA [SWR-21-105]
The Photovoltaic Dynamic Material Flow Assessment (PV DMFA) model (also referred to here as “The model”) is a computational framework written in Python based on utility-scale PV electricity generation to quantify time-series stocks and flows of PV materials primarily in crystalline silicon PV technologies. The model evaluates cradle-to-cradle life cycle of utility-scale solar PV systems in the United States in the period 2000-2100. PV DMFA serves as a sustainability analysis tool to assess the impacts of different material circularity practices (i.e., reduce, reuse/refurbish, remanufacture, and recycle), PV module design shifts and sensitivity of material processing and technology related parameters to material installations, waste creation and raw material depletion in PV material supply chains. This tool enables advanced planning for future material needs and informs sustainable pathways for PV material management in the circular economy. This tool could be helpful to a wide range of stakeholders; Particularly, researchers and manufacturers looking for technoeconomic and/or environmental life cycle analysis (LCA) feedback for renewable energy (RE) systems.
Khalifa, SherifA.↗
Advances in additive manufacturing, materials, and applications with AI/ML
There is high interest in making digital manufacturing a central facet of the new manufacturing landscape. However, in the materials science world, there is much work and opportunity to realize the full potential of artificial intelligence/machine learning (AI/ML) with regard to the structure–composition–processing–property (SCPP) relationship. For polymers (thermoplastics, thermosets, elastomers) and composites (nanocomposites), the origin of their high performance and even recyclability starts with design and formulation. Processing methods enable more property development based on curing, shape-factor forming, and anisotropic directionality. In subtractive manufacturing, high-performance and engineering polymers can be shaped and milled to very high tolerance and specifications and used as replacements for metals and alloys. In conclusion, this typically relies on digital manufacturing methods but tends to be wasteful in materials.
Lara-Ceniceros, Tania E. [Centro de Investigación ↗