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Simkovsky, Ryan

Publications and source records attributed to Simkovsky, Ryan.

Renewable and Biodegradable Polyurethane Foams with Aliphatic Diisocyanates

The transition to renewable plastics will require the development of substitutes with existing industrial standards and manufacturing processes. Polyurethanes (PU), versatile plastics, are traditionally dominated by aromatic diisocyanates, which are challenging to derive from renewable sources. However, for higher biocontent, it is crucial to utilize aliphatic diisocyanates, which can be sourced from renewable plant or algae waste streams. Historically, PU foams relied on aromatic diisocyanates for essential hard segments, resulting in desired physical properties. Here, we report the generation of high-performance renewable and biodegradable PU foams utilizing aliphatic diisocyanates and aromatic polyols, translating hard segments into the polyester polyol component using biosourced furan dicarboxylic acid (FDCA) monomers. We demonstrate that an FDCA-based PU is suitable for foams with performance characteristics that meet commercial tolerances and can biodegrade under backyard compost conditions. Here, this demonstrates steps toward redesigning traditional petrochemical-based polymers to accommodate new biological monomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid biodegradation of microplastics generated from bio-based thermoplastic polyurethane

The accumulation of microplastics in various ecosystems has now been well documented and recent evidence suggests detrimental effects on various biological processes due to this pollution. Accumulation of microplastics in the natural environment is ultimately due to the chemical nature of widely used petroleum-based plastic polymers, which typically are inaccessible to biological processing. One way to mitigate this crisis is adoption of plastics that biodegrade if released into natural environments. In this work, we generated microplastic particles from a bio-based, biodegradable thermoplastic polyurethane (TPU-FC1) and demonstrated their rapid biodegradation via direct visualization and respirometry. Furthermore, we isolated multiple bacterial strains capable of using TPU-FC1 as a sole carbon source and characterized their depolymerization products. Finally, to visualize biodegradation of TPU materials as real-world products, we generated TPU-coated cotton fabric and an injection molded phone case and documented biodegradation by direct visualization and scanning electron microscopy (SEM), both of which indicated clear structural degradation of these materials and significant biofilm formation.

09 BIOMASS FUELS↗

Advanced Algal Biofoundries for the Production of Polyurethane Precursors

The primary goal of the BEEPs project was to develop a process that could accelerate the development of algae as bioproduction platforms, from initial chemical product concept to an economically viable market supply. Under this program we elected to develop strains of algae that could generate polyurethane precursors, while simultaneously developing basic genetic tools to enable improved algal production systems. This program was specifically designed to incorporate National Laboratories as a means to utilize the expertise and facilities for new bio-production platforms. To that end, we designed a program to collaborate with the Agile BioFoundry at Lawrence Berkeley National Laboratory (LBNL) and computational platforms at Pacific Northwest National Laboratory (PNNL). In addition to these National Laboratory partners, we also had academic partners from UC Davis and Georgia Tech, as well as commercial partners Algenesis Materials and BASF. To achieve these goals, we initially focused on developing the genetic tools and high throughput screening technologies necessary to generate and assess production of polymer precursors (succinic acid) in algae and cyanobacteria, including advanced promoters and biosensors. In parallel, we computationally identified potential production bottlenecks and then used the developed genetic tools to increase production rates and yields. Constant feedback of data was used in conjunction with machine learning, high-throughput cell sorting, and synthetic biology, for additional targeted metabolic engineering. Multiple rounds of tool design, building, testing, and learning were supplied to partners at PNNL and LBNL to develop new models and tools that could expedite bioproduction platform development and increase yield performance. We targeted, and achieved, the FOA requirement yield metric of 20 g/L, as a milestone and deliverable from at least one of our engineered strains for the production of succinic acid.

09 BIOMASS FUELS↗