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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
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 OSTI2024

Environmental and economic analyses of chemical recycling via dissolution of waste polyethylene terephthalate

Globally, more than 1000 organizations and 175 nations are facing the plastic waste problem and have realized the need to transition from “linear-to-circular” economy of plastics. While the current mechanical recycling technologies for plastics are struggling to increase the U.S. plastic recycling rates beyond 9%, chemical recycling technologies become important complementary technologies to the predominant mechanical recycling that are needed to realize the circular economy in plastics supply chains. Dissolution is one such chemical recycling technology that can recycle waste plastic back into high-quality virgin grade plastic. However, the environmental and economic impacts of chemical recycling of waste polyethylene terephthalate (PET) via dissolution technology using a green solvent are unknown. Our study evaluated environmental metrics such as greenhouse gas (GHG) emissions and cumulative energy demand, and economic metrics such as net present value (NPV), minimum selling price, payback period, return on investment, and discounted internal rate of return for three dissolution processes with polymer recovery via anti-solvent, evaporation, and cooling precipitation techniques. The dissolution process with evaporation technique was the most economically favorable, whereas that with cooling technique was the most environmentally favorable. The anti-solvent approach had low economic performance and the highest environmental impacts. The NPV for all of these technologies ranged from $2.67 MM to $10.93 MM for a capacity of 8,400 MT/year and was found to be the highest for dissolution with evaporation approach and the least for anti-solvent approach. The cradle-to-gate GHG emissions and energy demand for PET dissolution processes ranged from 1.33-3.77 kg CO2-eq/kg of chemically recycled (CR) PET and18.9-56.1 MJ/kg of CR-PET, respectively. These economic and environmental metrics will be helpful in evaluating the sustainability of circular PET supply chains in the U.S.

09 BIOMASS FUELS↗
DOE OSTI2024

Effect of pyrolysis operating conditions on the catalytic co‐pyrolysis of low‐density polyethylene and polyethylene terephthalate with zeolite catalysts

Abstract In this study, the catalytic (co‐)pyrolysis of low‐density polyethylene (LDPE) and polyethylene terephthalate (PET) with HZSM‐5 and HY zeolite catalysts was conducted in a micro‐pyrolysis reactor coupled to a two‐dimensional gas chromatography system. Pyrolysis operating conditions, such as the pyrolysis temperature, the catalyst to feedstock (CF) ratio, and the LDPE:PET ratio, were varied. It was found that for the co‐pyrolysis of LDPE and PET, HZSM‐5 led to higher yields of C2‐C4 olefins and monoaromatic products. Lower CF ratios increased the yield of C2‐C4 olefins for LDPE pyrolysis, but decreased benzene yield for PET pyrolysis, concomitant with an increased yield in benzoic acid. A lower temperature of 400°C which was sufficient for the pyrolysis of LDPE, led to incomplete conversion of PET. Surface response diagrams were used to visualize the impact of the various pyrolysis operating conditions on the yield of C2‐C4 olefins and BTEX, which serve as target products for the circular economy.

Okonsky, Sean Timothy↗
DOE OSTI2022

Catalytic Degradation of Polyethylene Terephthalate Using a Phase‐Transitional Zirconium‐Based Metal–Organic Framework

Abstract Polyethylene terephthalate (PET) is utilized as one of the most popular consumer plastics worldwide, but difficulties associated with recycling PET have generated a severe environmental crisis with most PET ending its lifecycle in landfills. We report that zirconium‐based metal–organic framework (Zr‐MOF) UiO‐66 deconstructs waste PET into the building blocks terephthalic acid (TA) and mono‐methyl terephthalate (MMT) within 24 hours at 260 °C (total yield of 98 % under 1 atm H 2 and 81 % under 1 atm Ar). Extensive structural characterization studies reveal that during the degradation process, UiO‐66 undergoes an intriguing transformation into MIL‐140A, which is another Zr‐MOF that shows good catalytic activity toward PET degradation under similar reaction conditions. These results illustrate the diversity of applications for Zr‐MOFs and establish MOFs as a new class of polymer degradation catalysts with the potential to address long‐standing challenges associated with plastic waste.

Wu, Yufang↗
DOE OSTI2023

Aqueous buffer solution-induced crystallization competes with enzymatic depolymerization of pre-treated post-consumer poly (ethylene terephthalate) waste

In this paper, the complex relationship between kinetics and substrate morphology during enzymatic depolymerization of melt processed poly(ethylene terephthalate) (PET) is explored and the effects of competing transformations are analyzed. Extruded PET substrates from post-consumer recycled PET (RPET) bottles flakes subjected to enzymatic depolymerization are examined to reveal increases in crystallinity from ~10% post-extrusion to >30% after 3 days of depolymerization as well as increases in glass transition temperature (T g ) from ~66°C to > 80°C. Further investigation into this behavior shows that post-extrusion RPET substrates do not exhibit changes in crystallinity when subjected to dry annealing at 65°C in an oven over 7 days, but they do experience annealing in depolymerization buffer solution with no enzymes at 65°C within 3 days. This difference may be attributed to plasticization of PET in the presence of water, also known as solvent induced crystallization. The impact of this plasticized annealing behavior is demonstrated by subjecting RPET substrates to increasing enzyme-to-substrate loads. As enzyme load increases, overall conversion of substrates increases despite crystallinity also increasing to similar levels regardless of the initial enzyme loading. The competition between depolymerization and crystallization suggests that the rate at which PET substrates are depolymerized at the operational temperature is integral to achieving high conversion to monomeric product. This, in turn, also suggests that savings from lowered enzyme loadings may be more detrimental than helpful in pursuing the most cost-effective recycling systems.

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

Multilayer Chitin–Chitosan–Cellulose Barrier Coatings on Poly(ethylene terephthalate)

Currently, effective barrier properties over a wide range of humidity are achieved by layering multiple plastics, resulting in structures that are nearly impossible to recycle through current systems. There is strong interest in developing barriers that are recyclable, biodegradable, or compostable. Chitin and cellulose nanomaterials are promising alternatives because of their high crystallinity, renewable sourcing, strong electrostatic interactions, and potential for biodegradation or composting. In this paper, we explore the potential to create multilayer materials with effective oxygen and water vapor barrier properties at elevated humidity by combining recyclable poly(ethylene terephthalate) (PET) films with single-layer and bilayer coatings of chitin nanowhiskers (ChNWs), chitosan (CS), and cellulose nanocrystals (CNCs). The addition of CS to the ChNW suspension improved the gas barrier properties of ChNW coatings, likely by filling voids, and short ChNWs (SChNW, 114 nm) performed better than long ChNWs (LChNW, 230 nm). At the optimal mass ratio of 1:1 SChNW/CS, the oxygen permeability (OP) of SChNW/CS-coated PET films was 5.1 cm 3 μm m –2 day –1 kPa –1 versus 15.9 cm 3 μm m –2 day –1 kPa –1 for neat PET. To take advantage of electrostatic attraction and hydrogen bonding, CNC was first coated on the PET, followed by coating with ChNW/CS, resulting in an OP as low as 3.6 cm 3 μm m –2 day –1 kPa –1 at 50% relative humidity (RH), and 6.4 cm 3 μm m –2 day –1 kPa –1 at 80% RH. Furthermore, after thermal treatment (120 °C, 2.5 h), the OP dropped to 2.2 cm 3 μm m –2 day –1 kPa –1 (50% RH) and 4.8 cm 3 μm m –2 day –1 kPa –1 (80% RH). The ChNW/CS and CNC coating can be efficiently removed with alkali treatment enabling possible recycling of the coated PET films.

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

Age, vascular disease, and Alzheimer’s disease pathologies in amyloid negative elderly adults

Background: We recently reported that CSF phosphorylated tau (p-Tau 181 ) relative to Aβ 40 (CSF p-Tau/Aβ 40 ratio) was less noisy and increased associations with Alzheimer’s disease (AD) biomarkers compared to CSF p-Tau 181 alone. While elevations of CSF p-Tau/Aβ 40 can occur in amyloid-β (Aβ) negative (Aβ-) individuals, the factors associated with these elevations and their role in neurodegeneration and cognitive decline are unknown. We aim to explore factors associated with elevated tau in CSF, and how these elevated tau are related to neurodegeneration and cognitive decline in the absence of Aβ positivity. Methods: We examined relationships between CSF p-Tau/Aβ 40 , and CSF Aβ 42 /Aβ 40 , Aβ PET, and white matter hyperintensities (WMH) as well as vascular risk factors in 149 cognitively unimpaired and 52 impaired individuals who were presumably not on the Alzheimer’s disease (AD) pathway due to negative Aβ status on both CSF and PET. Subgroups had 18 F-fluorodeoxyglucose (FDG) PET and adjusted hippocampal volume (aHCV), and longitudinal measures of CSF, aHCV, FDG PET, and cognition data, so we examined CSF p-Tau/Aβ 40 associations with these measures as well. Results: Elevated CSF p-Tau/Aβ 40 was associated with older age, male sex, greater WMH, and hypertension as well as a pattern of hippocampal atrophy and temporoparietal hypometabolism characteristic of AD. Lower CSF Aβ 42 /Aβ 40 , higher WMH, and hypertension but not age, sex, Aβ PET, APOE-ε4 status, body mass index, smoking, and hyperlipidemia at baseline predicted CSF p-Tau/Aβ 40 increases over approximately 5 years of follow-up. The relationship between CSF p-Tau/Aβ 40 and subsequent cognitive decline was partially or fully explained by neurodegenerative measurements. Conclusions: These data provide surprising clues as to the etiology and significance of tau pathology in the absence of Aβ. It seems likely that, in addition to age, both cerebrovascular disease and subthreshold levels of Aβ are related to this tau accumulation. Crucially, this phenotype of CSF tau elevation in amyloid-negative individuals share features with AD such as a pattern of metabolic decline and regional brain atrophy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Plastic Parallel Pathways Platform - 4P Model

Global momentum is building towards a circular economy capable of keeping plastics in use and out of waste streams. Given that 79% of all plastic produced since 1950 has accumulated in landfills or the natural environment,rapid implementation of various end-of-life (EoL) management technologies will be needed to reach this target. However, it can be challenging to develop an effective plastic EoL strategy when the available options - chemical or molecular recycling, energy recovery, upcycling, downcycling, closed-loop (plastic-to-plastic) or open-loop (plastic-to-x) recycling, among others - can generate products ranging from low-grade to virgin-quality plastic and from fuels to value-added chemicals. We present a flexible material flow model capable of analyzing the effects of both plastic-to-plastic and plastic-to-x EoL management strategies on the U.S. PET economy. This Plastic Parallel Pathways Platform (4P) assesses the environmental impacts, costs, and circularity of a PET system in which waste is managed through six potential EoL pathways: landfill, incineration with energy recovery, pyrolysis to fuel oil, upcycling to glass fiber reinforced plastic (GFRP), mechanical recycling to low-grade PET, and chemical recycling (glycolysis) to bottle-grade PET. We compare the pathways across multiple metrics using multi-criteria decision analysis (MCDA) and then use a brute force algorithm to predict an optimal combination of EoL pathways to minimize greenhouse gas (GHG) emissions and costs and maximize circularity. This work highlights the need to implement a diverse portfolio of EoL strategies in parallel to enable a PET economy that meets environmental, economic, and circularity requirements simultaneously.

downcycling↗
DOE OSTI2023

Determinants of cognitive and brain resilience to tau pathology: a longitudinal analysis

Mechanisms of resilience against tau pathology in individuals across the Alzheimer’s disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer’s disease dementia with baseline 18 F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβ interaction = -0.062, P = 0.032), higher education level (Stβ interaction = -0.072, P = 0.011) and higher intracranial volume (Stβ interaction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer’s disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Assessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease

Importance: Better understanding is needed of the degree to which individuals tolerate Alzheimer disease (AD)-like pathological tau with respect to brain structure (brain resilience) and cognition (cognitive resilience). Objective: To examine the demographic (age, sex, and educational level), genetic (APOE-ε4 status), and neuroimaging (white matter hyperintensities and cortical thickness) factors associated with interindividual differences in brain and cognitive resilience to tau positron emission tomography (PET) load and to changes in global cognition over time. Design, setting, an participants: In this cross-sectional, longitudinal study, tau PET was performed from June 1, 2014, to November 30, 2017, and global cognition monitored for a mean [SD] interval of 2.0 [1.8] years at 3 dementia centers in South Korea, Sweden, and the United States. The study included amyloid-β-positive participants with mild cognitive impairment or AD dementia. Data analysis was performed from October 26, 2018, to December 11, 2019. Exposures: Standard dementia screening, cognitive testing, brain magnetic resonance imaging, amyloid-β PET and cerebrospinal fluid analysis, and flortaucipir (tau) labeled with fluor-18 (18F) PET. Main outcomes and measures: Separate linear regression models were performed between whole cortex [18F]flortaucipir uptake and cortical thickness, and standardized residuals were used to obtain a measure of brain resilience. The same procedure was performed for whole cortex [18F]flortaucipir uptake vs Mini-Mental State Examination (MMSE) as a measure of cognitive resilience. Bivariate and multivariable linear regression models were conducted with age, sex, educational level, APOE-ε4 status, white matter hyperintensity volumes, and cortical thickness as independent variables and brain and cognitive resilience measures as dependent variables. Linear mixed models were performed to examine whether changes in MMSE scores over time differed as a function of a combined brain and cognitive resilience variable. Results: A total of 260 participants (145 [55.8%] female; mean [SD] age, 69.2 [9.5] years; mean [SD] MMSE score, 21.9 [5.5]) were included in the study. In multivariable models, women (standardized β = -0.15, P = .02) and young patients (standardized β = -0.20, P = .006) had greater brain resilience to pathological tau. Higher educational level (standardized β = 0.23, P < .001) and global cortical thickness (standardized β = 0.23, P < .001) were associated with greater cognitive resilience to pathological tau. Linear mixed models indicated a significant interaction of brain resilience × cognitive resilience × time on MMSE (β [SE] = -0.235 [0.111], P = .03), with steepest slopes for individuals with both low brain and cognitive resilience. Conclusions and relevance: Results of this study suggest that women and young patients with AD have relative preservation of brain structure when exposed to neocortical pathological tau. Interindividual differences in resilience to pathological tau may be important to disease progression because participants with both low brain and cognitive resilience had the most rapid cognitive decline over time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Polyethylene Terephthalate Deconstruction Catalyzed by a Carbon‐Supported Single‐Site Molybdenum‐Dioxo Complex

Abstract Polyethylene terephthalate (PET) is selectively depolymerized by a carbon‐supported single‐site molybdenum‐dioxo catalyst to terephthalic acid (PTA) and ethylene. The solventless reactions are most efficient under 1 atmosphere of H 2 . The catalyst exhibits high stability and can be recycled multiple times without loss of activity. Waste beverage bottle PET or a PET + polypropylene (PP) mixture (simulating the bottle + cap) proceeds at 260 °C with complete PET deconstruction and quantitative PTA isolation. Mechanistic studies with a model diester, 1,2‐ethanediol dibenzoate, suggest the reaction proceeds by initial retro‐hydroalkoxylation/β‐C−O scission and subsequent hydrogenolysis of the vinyl benzoate intermediate.

Kratish, Yosi↗
DOE OSTI2023

Polymer grafted aramid nanofiber reinforces immiscible waste polypropylene/poly(ethylene terephthalate)

Polypropylene (PP) and poly(ethylene terephthalate) (PET) are plastics commonly used for packaging because of their excellent barrier and mechanical properties. The properties of these plastics are often diminished after mechanical recycling, inevitably causing down-cycling. Furthermore, this problem is exacerbated when different kinds of polymers mix. Aramid nanofibers have the potential to improve the mechanical properties of polymers due to their excellent mechanical properties but their poor dispersion in polymers is a challenge. Grafting polymers onto nanofibers can help address this challenge. In this work, different loading levels (1%, 2%, and 5%) of polymer grafted aramid nanofibers (ANFs) are blended with waste PP/PET (90/10), simulating a PP waste stream containing traces of PET contaminants. Scanning electronic microscopy, rheology, and differential scanning calorimetry results show the affinity of PP functionalized aramid nanofibers (PP_ANF) towards the PP matrix. At 1 wt% of the nanofiber, the size of the PET droplets in the PP matrix of the PP_ANF blend range from 0.2 to 2.0 μm while that of unmodified ANF and PET_ANF blends are in the range of 0.1–6.2 and 0.5–7.4 μm, respectively. In summary, polymer grafted ANFs have the tendency of improving properties of its like polymers due to similarity in the grafting polymer and the polymer matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The role of binding modules in enzymatic poly(ethylene terephthalate) hydrolysis at high-solids loadings

In nature, enzymes that deconstruct biological polymers, such as cellulose and chitin, often exhibit multi-domain architectures, comprising a catalytic domain and a non-catalytic binding module; the latter serves to increase the enzyme concentration at the substrate surface. This multi-domain architecture has been shown to improve the hydrolysis of poly(ethylene terephthalate) (PET) using engineered cutinase enzymes. Here, we examine the role of accessory binding modules at industrially relevant PET solids loadings necessary for cost-effective enzymatic recycling. Using a thermostable variant of leaf compost cutinase (LCC), we produced synthetic fusion constructs of LCC with five type A carbohydrate-binding modules (CBMs). At solids loadings below 10 wt%, the CBMs improve aromatic monomer yield from PET, but above this threshold, conversion extents up to 97% are reached with no added benefits from the presence of CBM fusions. This suggests that fusion constructs with the herein studied CBMs are not necessary for industrial enzymatic PET recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Aqueous ionic liquid–mediated depolymerization of textile waste

Textile waste, dominated by polyester-cotton blends, largely evades recycling and ends up in landfills or incinerators. Here, we demonstrate an aqueous ionic liquid–mediated route for selective depolymerization of textile waste, including polyester and polycotton (polyester/cotton blend). Using aqueous cholinium lysinate ([Ch][Lys]), we depolymerized poly(ethylene terephthalate) (PET) textiles with over 95 % terephthalic acid (TPA) yields, comparable to virgin PET resin. Notably, colored fabrics showed no inhibitory effect from dyes. While protic ionic liquids such as ethanolammonium acetate showed limited efficiency, their precursor amine enabled near-complete PET conversion—ethanolamine promoted aminolysis with byproduct formation whereas butylamine achieved higher TPA recovery through combined hydrolysis and aminolysis. Importantly, polycotton blends achieved complete PET depolymerization with TPA yield above 85 % and preserved cotton. These results establish aqueous ionic liquids as efficient, selective agents for deconstructing polyester in blended textiles, offering flexible product and ionic liquid management pathways toward scalable and facile textile recycling.

Amines↗
DOE OSTI2021

Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers.

60 APPLIED LIFE SCIENCES↗