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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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DOE OSTI2024

Upcycling Low Linear Density Polyethylene Waste into Turbostratic Graphene for High Mass Loading Supercapacitors

In this work, LLDPE was upcycled into a high quality turbostratic graphene using a pre-treatment step to oxidatively crosslink the polymer with the assistance of solid additives (KCl and K2CO3) that improve crosslinking by increasing the effective surface area of the polymer melt during processing. After this pretreatment step, the crosslinked polymer could then be carbonized and catalytically graphenized between 400-950 °C without complete decomposition of the material. The LLDPE derived graphene (LLDPE-G) obtained from this process has a Brunauer–Emmett–Teller (BET) specific surface area, up to 1800 m2g-1 and average Raman ID/IG and I2D/IG ratios of 0.85 and 0.57, respectively, indicating high quality graphene. When used as an electrode material in symmetric supercapacitors, LLDPE-G possesses an outstanding specific capacitance up to 175 Fg-1 at a mass loading of 20 mgcm-2, which is two times the commercial requirement, yielding an excellent areal capacitance of 3.5 Fcm-2. Moreover, LLDPE-G exhibits exceptional cycling stability with a capacitance retention of 95.8% after 100,000 cycles at a current density of 4.0 Ag-1. Additionally, the KCl and K2CO3 were recycled and reused over 3 complete cycles to make new LLDPE-G with the material quality and electrocapacitive performance retained and verified after each cycle. Our approach creates new opportunities for upcycling not only waste LLDPE but also other varieties of PE to high value graphene materials.

Gao, Yuan [NETL Site Support Contractor, National ↗
DOE OSTI2025

Biosynthesis of bioprivileged, linear molecules via novel carboligase reactions

Over the award period, we made progress on the three aims. We screened twenty-five carboligases for activity coupling twenty-one possible -keto acids (Aim 1). The carboligases were selected across a diverse set of protein sequences. Using Q-Exactive UHPLC-MS, we tested a total of 210 coupled products per enzyme and generated a dataset of 5250 enzyme-substrate activity relationships. We identified multiple enzymes that had activity for synthesizing suberic acid and heptanoic acid (Aim 2). We built a random forest model for predicting the activity of each enzyme toward substrates on which it was not tested using the data from Aim 1. Finally, we evaluated growth defects that occurred due to expression of different carboligases in E. coli (Aim 3). We were able to identify specific metabolites and putative pathways that, when supplemented in the media, recovered the growth defect associated with the presence of specific carboligases. We are in the process of publishing two manuscript describing the methods for high-throughput screening of enzyme promiscuity, using machine learning to predict activity on untested substrates, and enzyme activity data we collected. This project has produced enabling data for biosynthesis of a range of new-to-nature compounds to support biomanufacturing.

60 APPLIED LIFE SCIENCES↗