We present muconic acid, an unsaturated diacid that can be produced from cellulosic sugars and lignin monomers by fermentation, emerges as a promising intermediate for the sustainable manufacture of commodity polyamides and polyesters including Nylon-6,6 and polyethylene terephthalate (PET). Current conversion schemes consist in the biological production of cis,cis-muconic acid using metabolically engineered yeasts and bacteria, and the subsequent diversification to adipic acid, terephthalic acid, and their derivatives using chemical catalysts. In some instances, conventional precious metal catalysts can be advantageously replaced by base metal electrocatalysts. Here, we show the economic relevance of utilizing a hybrid biological-electrochemical conversion scheme to convert glucose to trans-3-hexenedioic acid (t3HDA), a monomer used for the synthesis of bioadvantaged 6. Potential roadblocks to biological and electrochemical integration in a single reactor, including electrocatalyst deactivation due to biogenic impurities and low faradaic efficiency inherent to side reactions in complex media, have been studied and addressed. In this study, t3HDA was produced with 94% yield and 100% faradaic efficiency. With consideration of the high t3HDA yield and faradaic efficiency, a technoeconomic analysis was developed on the basis of the current yield and titer achieved for muconic acid, the figures of merit defined for industrial electrochemical processes, and the separation of the desired product from the medium. On the basis of this analysis, t3HDA could be produced for approximately $2.00 kg -1. The low cost for t3HDA is a primary factor of the electrochemical route being able to cascade biological catalysis and electrocatalysis in one pot without separation of the muconic acid intermediate from the fermentation broth. AbstractMuconic acid, an unsaturated diacid that can be produced from cellulosic sugars and lignin monomers by fermentation, emerges as a promising intermediate for the sustainable manufacture of commodity polyamides and polyesters including Nylon-6,6 and polyethylene terephthalate (PET). Current conversion schemes consist in the biological production of cis,cis-muconic acid using metabolically engineered yeasts and bacteria, and the subsequent diversification to adipic acid, terephthalic acid, and their derivatives using chemical catalysts.In some instances, conventional precious metal catalysts can be advantageously replaced by base metal electrocatalysts. Here, we show the economic relevance of utilizing a hybrid biological-electrochemical conversion scheme to convert glucose to trans-3-hexenedioic acid (t3HDA), a monomer used for the synthesis of bioadvantaged Nylon-6,6. Potential roadblocks to biological and electrochemical integration in a single reactor, including electrocatalyst deactivation due to biogenic impurities and low faradaic efficiency inherent to side reactions in complex media, have been studied and addressed. In this study, t3HDA was produced with 94% yield and 100% farad...

No abstract

No abstract

Technoeconomic analyses using established tools such as SuperPro Designer® require a level of detail that is typically unavailable at the early stage of process evaluation. To facilitate this, members of our group previously created a spreadsheet-based process modeling and technoeconomic platform explicitly aimed at joint fermentative‒catalytic biorefinery processes. In this work, we detail the reorganization and expansion of this model—ESTEA2 (Early State Technoeconomic Analysis, version 2), including detailed design and cost calculations for new unit operations. Furthermore, we describe ESTEA2 validation using ethanol and sorbic acid process. The results were compared with estimates from the literature, SuperPro Designer® (Version 8.5, Intelligen Inc., Scotch Plains, NJ, 2013), and other third-party process models. ESTEA2 can perform a technoeconomic analysis for a joint fermentative‒catalytic process with just 12 user-supplied inputs, which, when modeled in SuperPro Designer®, required approximately eight additional inputs such as equipment design configurations. With a reduced amount of user information, ESTEA2 provides results similar to those in the literature, and more sophisticated models (ca. 7%–11% different).