Lignin

Gargulak, Jerry D.; Lebo, Stuart E.; McNally, Timothy J.

doi:10.1002/0471238961.12090714120914.a01.pub3

Cited by 14 publications

(6 citation statements)

References 63 publications

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“…These precursors generally only make up about half of the total plant mass, , meaning that a significant portion of the plants remains unused (10–30% is composed principally of lignin and biopolymers, with the bulk of the remaining mass contributed by water). Biomass therefore represents a large quantity of an inexpensive, green, and renewable resource that has yet to be thoroughly utilized . Biomass is currently almost exclusively used for generating energy through direct combustion, although it could be used for many other purposes should efficient methods of processing it into other compounds be developed.…”

Section: Selected Applications Of Deep Eutectic Solventsmentioning

confidence: 99%

“…Biomass therefore represents a large quantity of an inexpensive, green, and renewable resource that has yet to be thoroughly utilized. 145 Biomass is currently almost exclusively used for generating energy through direct combustion, although it could be used for many other purposes should efficient methods of processing it into other compounds be developed. Many of the difficulties in converting the raw material into useful chemicals lie within the pretreatment options; various separation and reaction pathways exist to convert lignin into biochemical precursors (including physical, physicochemical, biological, and chemical methods), 146−149 but a majority of them are energy intensive, toxic, 144,150 unscalable, 151 and/or expensive processes.…”

Section: Biomass Processingmentioning

confidence: 99%

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Deep Eutectic Solvents: A Review of Fundamentals and Applications

et al. 2020

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Deep eutectic solvents (DESs) are an emerging class of mixtures characterized by significant depressions in melting points compared to those of the neat constituent components. These materials are promising for applications as inexpensive "designer" solvents exhibiting a host of tunable physicochemical properties. A detailed review of the current literature reveals the lack of predictive understanding of the microscopic mechanisms that govern the structure−property relationships in this class of solvents. Complex hydrogen bonding is postulated as the root cause of their melting point depressions and physicochemical properties; to understand these hydrogen bonded networks, it is imperative to study these systems as dynamic entities using both simulations and experiments. This review emphasizes recent research efforts in order to elucidate the next steps needed to develop a fundamental framework needed for a deeper understanding of DESs. It covers recent developments in DES research, frames outstanding scientific questions, and identifies promising research thrusts aligned with the advancement of the field toward predictive models and fundamental understanding of these solvents.

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Section: Selected Applications Of Deep Eutectic Solventsmentioning

confidence: 99%

Section: Biomass Processingmentioning

confidence: 99%

Deep Eutectic Solvents: A Review of Fundamentals and Applications

et al. 2020

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“…Considering the impact of lignin on mechanical and physical properties of lignin-HPU hydrogels, it is important to elucidate the source of interaction between lignin and HPU macromolecules. Lignin has a complex chemical structure that contains carboxylate, sulfonate and hydroxyl groups, which depends on the initial pulping process and the origin of lignin. , Lignin is negatively charged, mainly because of the presence of carboxylate and in some cases sulfonate groups. , It is proposed that the charge interaction was the primary bonding mechanism between lignin (as an anionic polymer) and cationic polymers, such as polydiallyldimethylammonium chloride , and poly(ethylenimine) . On the basis of the chemical structures of lignin and HPU, two mechanisms of interaction between HPU and lignin are suggested.…”

Section: Results and Discussionmentioning

confidence: 99%

Tough and Processable Hydrogels Based on Lignin and Hydrophilic Polyurethane

Oveissi

Naficy

et al. 2018

ACS Appl. Bio Mater.

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Lignin is a low-cost, natural polymer with abundant polar sites on its backbone that can be utilized for physical cross-linking of polymers. Here, we use lignin for additional cross-linking of hydrophilic polyether-based polyurethane (HPU) hydrogels, aiming to improve their mechanical properties and processability. Without reducing the swelling, simple addition of 2.5 wt % lignin increases the fracture energy and Young's modulus of HPU hydrogels from, respectively, 1540 ± 40 to 2050 ± 50 J m −2 and 1.29 ± 0.06 to 2.62 ± 0.84 MPa. Lignin also increases the lap shear adhesiveness of hydrogels and induces an immediate load recovery of 95%. We further confirm that hydrogen bonding is the dominant toughening mechanism and elucidate the toughening mechanism by applying the Lake-Thomas and a recently developed sequential debonding theory. We show that unlike the Lake−Thomas theory, the latter model is able to capture the impact of lignin on toughening of hydrogels. Moreover, the lignin-loaded HPU hydrogels are easily processable by various techniques, such as fiber spinning, casting, and 3D printing and are biocompatible with primary human dermal fibroblasts.

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“…We The structural litter pool (STR C ) consists of lignin and polyphenols, the parts of litter which stabilize the cell wall and are processed by microbes with a low CUE. STR C is assumed to have a carbon content of 65%, representing a lignin-typical C/H/O ratio of 20/23/7 (Gargulak et al, 2015). Through this definition, the structural litter pool is measurable as acid detergent lignin (Van Soest and Wine, 1968) and polyphenols (Anderson and Ingram, 1993), and it does not contain nitrogen.…”

Section: Discussionmentioning

confidence: 99%

SAMM version 1.0: A numerical model for microbial mediated soil aggregate formation

Laub¹,

Blagodatsky²,

Broek³

et al. 2023

Preprint

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Abstract. In light of the large role that soil organic matter (SOM) plays in maintaining healthy and productive agricultural soils, it is crucial to understand the processes of SOM protection including the role of soil aggregate protection. Yet, few numerical process models include aggregate formation and even fewer represent the important connection between microbial growth and aggregate formation. Here, we propose a model of Soil Aggregation through Microbial Mediation (SAMM), which consist of measurable pools and 5 couples soil aggregate formation to microbial growth. The model was evaluated against data from a long term bare-fallow experiment in a tropical sandy soil, subject to plant litter additions of different compositions. The SAMM model effectively represented the microbial growth response after litter addition and the following formation and later disruption of aggregates. Model parameter correlation was low (all r < 0.5; r > 0.4 for only 4 of 22 parameters) showing that SAMM is well parameterized. Differences between treatments resulting from different litter compositions could be captured by SAMM for soil organic carbon (Nash-Sutcliffe modelling efficiency (EF) of 0.68), microbial nitrogen (EF of 0.24) and litter carbon (EF of 0.80). Aggregate-related fractions, i.e., carbon inside aggregates (EF of 0.60) and also carbon in the free silt and clay fraction (EF of 0.24) were simulated very well to satisfactory. Analysis of model parameters led to further noteworthy insights. For example, model results suggested that up to 50 % of carbon in the soil is stabilized through aggregate protection, even in a sandy soil, and that both microbial activity and physical aggregate formation coexist. When aggregate formation was deactivated, the model failed to stabilize soil organic carbon (EF dropped to -3.68) and microbial nitrogen was represented less well (EF of 0.13). By re-calibrating the model version with deactivated aggregates, it was possible to partly correct for removing the aggregate formation, i.e., by reducing the decomposition rate of mineral attached carbon by about 85 % (EF of 0.68, 0.75 and 0.18 for SOC, litter carbon and microbial nitrogen, respectively). Yet, the overall slightly better evaluation statistics (e.g., Akaike information critereon of 5351 vs 5554) show the potential importance of representing aggregate dynamics within SOM models. Our results indicate that current models without aggregate formation partly compensate the missing protection effect by lowering turnover rates of other pools and thus may still be suitable options where data on aggregate associated carbon is not available.

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Lignin

Cited by 14 publications

References 63 publications

Deep Eutectic Solvents: A Review of Fundamentals and Applications

Deep Eutectic Solvents: A Review of Fundamentals and Applications

Tough and Processable Hydrogels Based on Lignin and Hydrophilic Polyurethane

SAMM version 1.0: A numerical model for microbial mediated soil aggregate formation

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