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Reynolds, William

Publications and source records attributed to Reynolds, William.

Enhanced Softwood Cellulose Accessibility by H 3 PO 4 Pretreatment: High Sugar Yield without Compromising Lignin Integrity

Softwood lignocellulose is a potential feedstock for the production of biofuels and bioproducts. However, the highly cross-linked nature of softwood lignocellulose restricts enzyme access to its sugars. Thus, harsh pretreatment conditions (180–280 °C) and/or high enzyme loading are required to unlock sugars. These requirements negatively affect the economic viability of softwoods in biorefineries. Here we show that H 3 PO 4 pretreatment of pine and Douglas fir under a mild reaction temperature (50 °C) and atmospheric pressure enabled a high (~80%) glucan digestibility with low enzyme loading (5 filter paper units (FPU)/g glucan). The dissolution and regeneration of softwoods disrupted the hydrogen bonding between cellulose chains, thereby increasing the cellulose accessibility to cellulase (CAC) values by ~38-fold (from ~0.4 to 15 m 2 /g biomass). Examination of H 3 PO 4 -pretreated softwoods by cross-polarization/magic angle spin (CP/MAS), 13 C- nuclear magnetic resonance (NMR), and Fourier-transform infrared spectroscopy (FTIR) revealed that breaking of the orderly hydrogen bonding of crystalline cellulose caused the increase in CAC (higher than 11 m 2 /g biomass), which, in turn, was responsible for the high glucan digestibility of pretreated softwoods. The H 3 PO 4 pretreatment process was feedstock independent. Finally, 2D 13 C– 1 H heteronuclear single quantum coherence (HSQC) NMR showed that the lignin was depolymerized but not condensed; thus, the lignin can be available for producing high-value products.

09 BIOMASS FUELS↗

Jargon and Graph Modularity on Twitter

The language of conversation is just as dependent upon word choice as it is on who is taking part. Twitter provides an excellent test-bed in which to conduct experiments not only on language usage but on who is using what language with whom. To this end, we combine large scale graph analytical techniques with known socio-linguistic methods. In this article we leverage both expert curated vocabularies and naive mathematical graph analyses to determine if network behavior on Twitter corroborates with the current understanding of language usage. The results reported indicate that, based on networks constructed from user to user communication and communities identified using the Clauset- Newman greedy modularity algorithm we find that more prolific users of these curated vocabularies are concentrated in distinct network communities.

Dowling, Chase P.↗