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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Degradable Biocomposite Thermoplastic Polyurethanes

In this project, the team developed tough and degradable biocomposite thermoplastic polyurethanes (TPUs) by incorporating bacterial spores into TPUs as a biofunctional living filler. The team screened various bacteria and selected the Bacillus subtilis ATCC 6633 strain as the final candidate, primarily due to its genomic availability, sporulation ability and TPU assimilation activity. The heat-shock tolerance of ATCC 6633 spores was further improved through evolutionary engineering via Adaptive Laboratory Evolution (ALE), demonstrating a 17.7-fold enhanced germination efficiency post heat-shock treatment compared to the wild-type strain (WT). The team fabricated biocomposite TPUs by incorporating lyophilized powder of heat-shock tolerized (HST) spores during the hot melt extrusion (HME) of TPU at 135 °C. The baseline TPU used in this project is a commercially available soft-grade TPU (BCF45) manufactured by BASF. Colony forming unit (CFU) assays quantified that WT and HST spores in the TPU matrix retained approximately 20% and 100% survivability, respectively, after HME. Tensile testing demonstrated that the spores behaved as a polymer-reinforcing filler, positively affecting the overall tensile properties of the biocomposite TPU. For example, biocomposite TPU with WT and HST spores (BC TPU WT and BC TPU HST , respectively) exhibited up to 25% and 37% improved toughness, respectively, compared to TPU without spores. BC TPU HST showed remarkably improved disintegration in autoclaved compost (92% mass loss in 5 months), which simulated a microbially poor environment for TPU degradation. When compared to TPU without spores (44% mass loss in 5 months) the acceleration of degradation is marked. Respirometry confirmed that 72% of BC TPU HST was biomineralized into CO2 within 6 months, indicating that spores in the biocomposite TPU were germinated by utilizing nutrients in the autoclaved compost, facilitating TPU degradation at the end of the material's life. The team demonstrated the scale-up of biocomposite TPU fabrication using continuous extrusion and injection molding techniques. Processing conditions optimized in a lab-scale microcompounder were successfully transferred to a continuous extruder with a 30-fold increased throughput. Biocomposite TPUs prepared using these industry-relevant processes showed comparable toughness improvements to samples prepared in the lab-scale extruder. Excitingly, following compounding in the pilot-extruder the composite material could be injection molded, while retaining high spore viability and similar toughness improvements. The team also found that spores in biocomposite TPU served as antioxidants, preventing toughness decay during the recycled extrusion of BC TPU HST . Long-term storage tests over one year showed that the addition of spores had no negative effect on the longevity of the TPU. Furthermore, the team demonstrated the fabrication of spore-bearing biocomposite polymers with other polyesters such as PBAT, PLA, and PCL. We obtained promising preliminary data that showed overall toughness improvements for all polymers with spore addition. Finally, life cycle assessment (LCA) and techno-economic analysis (TEA) were carried out, which indicated minimal additional cost of fabrication. Overall, a tough and degradable biocomposite thermoplastic was successfully developed through this project, with all tasks completed successfully, achieving >100% of the objectives.

36 MATERIALS SCIENCE↗
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 OSTI2023

Plastic from CO2 and Inedible Biomass (CRADA Final Report)

As part of the Cyclotron Road program, ReSource Chemical Corp. sought to investigate the conversion of inedible biomass and CO₂ to FDCA. FDCA is a performance monomer widely viewed as a green replacement for the petroleum-derived monomer PTA, which is produced at approximately 60 Mt per year with over 100 Mt of annual GHG emissions. The major polyester made from PTA, called PET, is a >$\$$100B industry with applications in bottling, food packaging, and fibers. The FDCA analogue of PET, called PEF, had superior gas barrier, mechanical, and thermal properties that enable increased shelf life of perishable goods while using less plastic.

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

SMC Reinforced by Recycled or Textile Carbon Fiber

There is a significant need to expand material options for SMC that has traditionally used glass fibers for decades. There are several integral issues related to chopping and conveying a range of materials including glass, carbon, basalt, thermoplastic tapes, and recycled fibers. These are in a variety of forms including continuous tows, discontinuous agglomerates such as pyrolyzed carbon fibers that could be used to produce a range of SMC intermediates. Standard/conventional SMC processing is limited to cutting rotors specifically for glass and compounding with thermoset polyesters and some epoxies. The multi-material, multi-format line developed in this project is flexible to enable custom conveying and uses an interchangeable rotor dedicated for specific material types. The overall tasks undertaken in this project included: evaluation of the fiber feed mechanism, effect of textile grade carbon, evaluating servo motor controlling of conveyor, evaluate doctor box resin feed, evaluate compaction unit, evaluation of different formulations, and develop automation such as PLC programming. The new multi-material SMC line Version 2 (SCM-V2) incorporated servo motors over induction motors which gave the overall cutter system precision control and made it quiet. The addition of a 14-roll compaction unit at the end of the line in SMC-V2 enabled higher material wet out which was a limitation in the SMC Version 1 (SMC-V1). The cutters were further updated to reduce the cantilever overhang of the fiber which enabled more uniform cut lengths for glass, carbon, and basalt fibers. The overall instrumentation and system control including a remote control operation was enabled in the SMC-V2. The line speed is capable of 10-20 ft/minute. The cutting modules were designed and engineered for cutting glass, basalt and textile grade carbon in 300k and 450-600k format widths. The cutting trials were established for a range of fiber types. The study also demonstrated the utility of the line to cut and produce basalt fiber SMC. Initial trials were conducted on the properties from recycled carbon fiber (rCF) mats in epoxy resin. Overall, the Covid19 situation constrained the team from accessing the SMC line for over 18 months. Despite this challenge major advancements were made.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Biodegradable Biocomposite Development for Large Scale Additive Manufacturing

Oak Ridge National Laboratory (ORNL) worked with Mitsubishi Chemical America, Inc. to develop a highly biodegradable ~100% biobased feedstock for large format additive manufacturing (AM). Together, they developed an AM feedstock based on the biobased polyester, polybutylene succinate (PBS), that is typically used in agriculture and packaging projects. The motivation for this work was to leverage the high degradability of this polymer in AM to create a new avenue for end-of-life disposal of the product. A composite feedstock was developed from PBS, polylactic acid (PLA), and wood flour (WF). While WF improves printability, reduces feedstock cost, and can improve stiffness, it also often results in a loss in tensile strength which can inhibit/limit applications of the material. To recover the loss in tensile strength suffered by including large quantities, up to 30 wt.% WF in the composite, a chain extender was used to compatibilize the different composite constituents with each other. The feedstock was used to 3D-print a demonstration mold for precast concrete catch basins and was tested by casting 750 lbs of concrete. The mold survived the demonstration. Aerobic degradation testing of the composite feedstock showed that it was highly degradable, 40% biodegradation after 90 days, compared to other incumbent biobased feedstocks.

100% biobased feedstock for large format additive ↗
DOE OSTI2026

Biodegradable Biocomposite Development for Large Scale Additive Manufacturing

Oak Ridge National Laboratory (ORNL) worked with Mitsubishi Chemical America, Inc. to develop a highly biodegradable ~100% biobased feedstock for large format additive manufacturing (AM). Together, they developed a AM feedstock based on the biobased polyester, polybutylene succinate (PBS), that is typically used in agriculture and packaging projects. The motivation for this work was to leverage the high degradability of this polymer in AM to create a new avenue for end-of-life disposal of the product. A composite feedstock was developed from PBS, polylactic acid (PLA), and wood flour (WF). While WF improves printability, reduces feedstock cost, and can improve stiffness, it also often results in a loss in tensile strength which can inhibit/limit application of the material. To recover the loss in tensile strength suffered by including large quantities, up to 30 wt%, WF in the composite a chain extender was used to compatibilze the different composite constituents with each other. The feedstock was used to 3D-print demonstration mold for precast concrete catch basins and was tested by casting 750 lbs of concrete. The mold survived the demonstration. Aerobic degradation testing of the composite feedstock showed that it was highly degradable, 40% biodegradation after 90 days, compared to other incumbent biobased feedstocks.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Biological funneling of phenolics from transgenic plants engineered to express the bacterial 3-dehydroshikimate dehydratase (qsuB) gene

The economic and environmental sustainability of lignocellulosic biomass biorefineries is predicated on generating biofuels and bioproducts from cell-wall polysaccharide and lignin polymers. Historical efforts in plant genetic engineering have focused on the development of strategies that facilitate biomass deconstruction, with more recently efforts including the synthesis of high-value chemicals in planta . One such genetic modification is the expression of the bacterial quinate and shikimate utilization B ( qsuB ) gene that increases the accumulation of protocatechuic acid in lignocellulosic biomass. Herein, we evaluated the effectiveness of an alkaline pretreatment process to extract phenolics directly from wild-type and QsuB-transgenic lines of Arabidopsis, poplar, and sorghum, and then upgrade them to the polyester precursor 2-pyrone-4,6-dicarboxylic acid (PDC) with an engineered strain of Novosphingobium aromaticivorans . Protocatechuic acid extracted from all QsuB transgenic lines was found to be mostly in the glycosylated form. Glycosylated protocatechuic acid and other plant-derived phenolics were effectively metabolized by N. aromaticivorans, and PDC production was greatest using extracts from an Arabidopsis QsuB transgenic line (∼5% w/w), followed by QsuB sorghum (∼1.1% w/w), and QsuB poplar (∼0.4% w/w) lines. The comparison of PDC production from wild-type and QsuB transgenic lines of Arabidopsis, poplar, and sorghum demonstrates the utility of a mild alkaline pretreatment to liberate phenolics from plant biomass that are either naturally present or that accumulate as a consequence of genetic engineering strategies. All QsuB transgenic lines outperformed their wild-type counterparts with respect to observed PDC yields. In addition, microbial funneling to PDC was effective even when most of the protocatechuic acid extracted was in glycosylated form, clearly demonstrating that this bacterium can metabolize these aromatic conjugates. These findings illustrate the benefits of combining plant and microbial engineering for bioproduct formation from phenolics in lignocellulosic biorefineries.

Umana, German E.↗
DOE OSTI2022

The Bacteroidetes Aequorivita sp. and Kaistella jeonii Produce Promiscuous Esterases With PET-Hydrolyzing Activity

Certain members of the Actinobacteria and Proteobacteria are known to degrade polyethylene terephthalate (PET). Here, we describe the first functional PET-active enzymes from the Bacteroidetes phylum. Using a PETase-specific Hidden-Markov-Model- (HMM-) based search algorithm, we identified several PETase candidates from Flavobacteriaceae and Porphyromonadaceae. Among them, two promiscuous and cold-active esterases derived from Aequorivita sp. (PET27) and Kaistella jeonii (PET30) showed depolymerizing activity on polycaprolactone (PCL), amorphous PET foil and on the polyester polyurethane Impranil ® DLN. PET27 is a 37.8 kDa enzyme that released an average of 174.4 nmol terephthalic acid (TPA) after 120 h at 30°C from a 7 mg PET foil platelet in a 200 μl reaction volume, 38-times more than PET30 (37.4 kDa) released under the same conditions. The crystal structure of PET30 without its C-terminal Por-domain (PET30ΔPorC) was solved at 2.1 Å and displays high structural similarity to the Is PETase. PET30 shows a Phe-Met-Tyr substrate binding motif, which seems to be a unique feature, as Is PETase, LCC and PET2 all contain Tyr-Met-Trp binding residues, while PET27 possesses a Phe-Met-Trp motif that is identical to Cut190. Microscopic analyses showed that K. jeonii cells are indeed able to bind on and colonize PET surfaces after a few days of incubation. Homologs of PET27 and PET30 were detected in metagenomes, predominantly aquatic habitats, encompassing a wide range of different global climate zones and suggesting a hitherto unknown influence of this bacterial phylum on man-made polymer degradation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Recent Advances in Biological Recycling of Polyethylene Terephthalate (PET) Plastic Wastes

Polyethylene terephthalate (PET) is one of the most commonly used polyester plastics worldwide but is extremely difficult to be hydrolyzed in a natural environment. PET plastic is an inexpensive, lightweight, and durable material, which can readily be molded into an assortment of products that are used in a broad range of applications. Most PET is used for single-use packaging materials, such as disposable consumer items and packaging. Although PET plastics are a valuable resource in many aspects, the proliferation of plastic products in the last several decades have resulted in a negative environmental footprint. The long-term risk of released PET waste in the environment poses a serious threat to ecosystems, food safety, and even human health in modern society. Recycling is one of the most important actions currently available to reduce these impacts. Current clean-up strategies have attempted to alleviate the adverse impacts of PET pollution but are unable to compete with the increasing quantities of PET waste exposed to the environment. In this review paper, current PET recycling methods to improve life cycle and waste management are discussed, which can be further implemented to reduce plastics pollution and its impacts on health and environment. Compared with conventional mechanical and chemical recycling processes, the biotechnological recycling of PET involves enzymatic degradation of the waste PET and the followed bioconversion of degraded PET monomers into value-added chemicals. This approach creates a circular PET economy by recycling waste PET or upcycling it into more valuable products with minimal environmental footprint.

42 ENGINEERING↗
DOE OSTI2026

A Flexible Quasi-Static Mooring Design Optimization Method for Floating Structures

This paper presents a flexible and efficient design method for optimizing the mooring systems of floating structures. Mooring system optimization is challenging because of the strong nonlinearity of mooring system behavior and the many technical constraints that must be satisfied. Furthermore, different mooring configurations can have very different design spaces. While some successful examples of mooring design optimization exist in the literature, developing an optimization approach that can work across various mooring design problems is a larger challenge. We present such a method based on a flexible parameterization that allows a wide variety of mooring designs to be described by a list of variables, a quasi-static mooring model that provides efficient evaluation of a mooring design without directly considering mooring system dynamics, and an optimization framework that generates, evaluates, and adjusts the mooring design while considering user-specified constraints such as offset limits, strength safety factors, and seabed contact limits. We demonstrate the design optimization framework on four mooring design problems, each for a different type of mooring system. We compare the use of different design modes to simplify the optimization problem, showing that they can reduce the computation time by up to 75%. We also compare different optimization algorithms and find that the resulting computational speed can vary by up to 51 times. We perform a sensitivity study on one design and find that the local sensitivity of anchoring radius to water depth has a positive correlation of 0.29, but the global sensitivity shows large nonlinearities. Lastly, we perform a coupled dynamic analysis on one of the optimized designs and find that the predicted mean platform motions and mooring line tensions are within 1% of dynamic results and the extreme motions and tensions are within 14%. Lastly, we show that a DEA-Chain-Polyester mooring configuration is cost-optimal for the given design problem of the demonstrations, which aligns with general industry practice.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

A Deep Neural Network for Accurate and Robust Prediction of the Glass Transition Temperature of Polyhydroxyalkanoate Homo- and Copolymers

The purpose of this study was to develop a data-driven machine learning model to predict the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced polyesters featuring excellent performance, to guide future design and synthesis experiments. A deep neural network (DNN) machine learning model was built for predicting the glass transition temperature, Tg, of PHA homo- and copolymers. Molecular fingerprints were used to capture the structural and atomic information of PHA monomers. The other input variables included the molecular weight, the polydispersity index, and the percentage of each monomer in the homo- and copolymers. The results indicate that the DNN model achieves high accuracy in estimation of the glass transition temperature of PHAs. In addition, the symmetry of the DNN model is ensured by incorporating symmetry data in the training process. The DNN model achieved better performance than the support vector machine (SVD), a nonlinear ML model and least absolute shrinkage and selection operator (LASSO), a sparse linear regression model. The relative importance of factors affecting the DNN model prediction were analyzed. Sensitivity of the DNN model, including strategies to deal with missing data, were also investigated. Compared with commonly used machine learning models incorporating quantitative structure–property (QSPR) relationships, it does not require an explicit descriptor selection step but shows a comparable performance. The machine learning model framework can be readily extended to predict other properties.

quantitative structure–property relationship (QSPR↗
DOE OSTI2020

Electrocatalytic hydrogenation of muconic acid

Various embodiments disclosed relate to electrocatalytic hydrogenation of muconic acid and polymers formed from the reaction products thereof. In various embodiments, the present invention provides an electrocatalytic method to prepare 3-hexene-1,6-dioic acid, 2-hexene-1,6-dioic acid, adipic acid, or a combination thereof, from muconic acid. The method includes passing current through a catalytic cathode in a reactor including an aqueous acidic solution including muconic acid, a supporting electrolyte, and an anode, so as to generate atomic hydrogen on the cathode surface in an amount effective to hydrogenate the muconic acid to yield a product including 3-hexene-1,6-dioic acid, 2-hexene-1,6-dioic acid, adipic acid, or a mixture thereof. Also disclosed is the polymerization of 3-hexene-1,6-dioic acid, 2-hexene-1,6-dioic acid, or a combination thereof with another compound, such as a diamine or a dialcohol, to form a polymer, such as a polyamide or a polyester.

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

Accelerating Materials Discovery: Artificial Intelligence for Sustainable, High-Performance Polymers

PolyID enables the discovery of polymers with advanced performance and greater sustainability while reducing material development timelines. The material design space is immense and cannot be reasonably probed using an Edisionian approach. High-throughput property prediction, enabled by artificial intelligence provides a hypothesis driven approach for down selection of candidate polymers to pursue experimentally. To aid experimentalists in the down selection of material targets this high-throughput, machine learning-based tool is capable of predicting polymer properties simply from molecular structures. Currently, transport, thermal, and mechanical properties across 7 polymer class (polyamides, polyesters, polycarbonates, polyimides, polyolefins, polyacrylates, and polyurethanes) can be predicted, and the PolyID platform has been flexibly designed so new materials and properties can be added.

artificial intelligence↗
DOE OSTI2022

Performance Advantaged ..beta..-Ketone Containing Polymers - Benefits in Manufacturing, Performance, and End-of-Life

Biomass derived chemicals can possess extended functionality, often in the form of heteroatoms like oxygen and nitrogen, that can enable performance advantaged properties in emergent materials. These performance advantages can manifest in multiple ways such as reduced manufacturing intensity, better performance, or enhanced end-of-life options. One illustrative example of this concept is ..beta..-ketoadipic acid (..beta..KA), a C6 dicarboxylic acid with a ketone in its backbone. ..beta..KA can be obtained via biological cultivation from aromatic compounds, sugars, and even waste plastics. When ..beta..KA is implemented into polymers, namely nylons, in place of adipic acid the overall material properties are increased. Specifically, the glass transition temperature (which is the measurement at which temperature a plastic softens) is increased by 69 degrees C and the water permeability is reduced by 20%. Molecular dynamic (MD) simulations reveal that the ..beta..-ketone in ..beta..KA leads to restricted movement across multiple backbone carbons when compared to adipic acid. Furthermore, MD simulations reveal that the ..beta..-ketone, when compared to no-ketone or an a-ketone, can lead to an increase in hydrogen bonding between neighboring chains. Both phenomena may help explain the molecular origin of the increases in polymer performance. When implemented into polyesters, namely PET, ..beta..KA can maintain the requisite performance while enabling enhanced degradation. Aside from performance advantages in thermomechanical performance, the production of ..beta..KA also is advantaged in its manufacturing. Although estimates for the minimum selling price (MSP) of ..beta..KA exceed adipic acid the manufacture of ..beta..KAwould reduce supply chain energy and GHG emissions by >50% and >30% respectively. Further TEA analysis reveals that the MSP of ..beta..KA is primarily driven by the feedstock cost while the capital expenditures are driven largely by fermentation costs. Overall, the work presented within will be illustrative of how biomass derived molecules, namely ..beta..KA, can manifest performance advantages across multiple benchmarks and may enable a path to market for biomass-derived materials.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS↗
DOE OSTI2023

2.3.4.501 - Synthesis and Analysis of Performance-Advantaged Bioproducts

This project focuses on the synthesis and analysis of performance-advantaged bioproducts (PABPs). We have established collaborations with other BETO-funded projects and academic and industrial collaborators to source new molecules that have promising manufacturing pathways and that could be serve as performance-advantaged biochemicals or biopolymers. We conduct synthesis and characterization of biochemicals and biopolymers alongside techno-economic analysis and life cycle assessment to estimate their cost and environmental impacts relative to incumbent materials. As part of the project, Profs. Linda Broadbelt and Brent Shanks are developing computational pathway prediction tools to identify optimal production pathways for bio-based compounds via biological and chemo-catalytic transformations. When coupled to the polyID tool from the Inverse Design project, these tools will ultimately enable a narrowing of design space for PABPs. From FY21-FY23, we described a framework for benchmarking PAPBs, estimated the energy and GHG emissions for commodity organic chemicals, developed performance-advantaged nylons and polyesters from beta-ketoadipic acid, and produced lignin-based plasticizers. We have shown that aromatic amines can be used in performance thermosets and that polyhydroxyalkanoates with crosslinked side chains can exhibit rubber-like properties, along with repair and degradability. We are working actively with industry partners on scale-up and validation of multiple PABPs.

BIOMASS FUELS↗
DOE OSTI2023

ABF DFO with Technology Holding, Inc.

This Agile BioFoundry Directed Funding Opportunity project with Technology Holding and partners focuses on the development of both a strain of Pseudomonas putida KT2440 and a corresponding bioprocess to convert cellulosic sugars to beta-ketoadipic acid, which can be used in performance nylons and polyesters. Our approach follows the Design-Build-Test-Learn cycle wherein we have transferred learnings from muconic acid production in P. putida to develop a glucose and xylose-utilizing beta-ketoadipic acid production strain. This strain achieves 65 g/L of beta-ketoadipic acid at 0.7 g/L/hr and a C-mol yield of 0.40. We are currently on-boarding arabinose utilization as well. To identify non-intuitive strain modifications as well, we are deploying a beta-ketoadipic acid biosensor and building randomly barcoded transposon insertion sequencing (RB-TnSeq) libraries and gene over-expression libraries in beta-ketoadipic acid production strains. Moreover, we are using global metabolomics and other systems biology tools to identify off-target pathways. Lastly, we are scaling up beta-ketoadipic acid production to kg-scale production for Technology Holding to evaluate in performance polymers with their partners.

beta-ketoadipic acid↗
DOE OSTI2023

Comparing Polymer Recycling Technologies for a Circular Plastic Economy

This presentation summarizes the research article "Technical, Economic, and Environmental Comparison of Closed-Loop Recycling Technologies for Common Plastics" by Uekert et al. (ACS Sustainable Chem. Eng., 2023) for a carpet industry audience. It covers the technical performance, environmental impacts, and costs of existing and emerging plastic recycling technologies, with a focus on those that are applicable to carpet materials such as polypropylene and polyester.

carpet↗
DOE OSTI2023

Developing a Roadmap for Bio-Derivable and Recyclable Composites: Re-Design and Scale-Up Considerations

Composites, often in the form of fiber reinforced plastics, are used in multiple facets of modern life from snowboards to vehicles, to wind turbines and beyond. Despite their prolific, and often renewable energy related uses, they are currently subject to a linear material economy from emission intensive precursors; thus, there is an opportunity to re-design these materials to be both bio-derivable and recyclable. In the present work, we provide a roadmap of what application considerations must be considered for vacuum assisted resin transfer molding (VARTM) processes for large composites materials at scale (e.g. infusible viscosities, moderate cure times, proper fiber adhesion, low cost, and maximum peak exotherm) when implementing bio-derivable and recyclable materials. We also provide illustrative concepts utilizing polyester covalently adaptable networks, from epoxy-anhydride chemistry, to achieve these goals. We further provide considerations when developing recycling process (e.g. maintenance of fiber sizing and orientation) and demonstrate these practices using low temperature methanolysis. Accompanying technoeconomic and life cycle analysis further illustrate the decarbonization benefits to bio-derivable and recyclable thermosets while informing future research and recycling processes. Finally, we provide a brief introduction to synergistic work within our team exploring how to further decarbonize the manufacturing of these materials.

BIOMASS FUELS,ENERGY CONSERVATION, CONSUMPTION, AN↗