An aerosol flow reactor was used for the first time for high-throughput, high yield synthesis of spherical lignin particles with given inherent hydrophilicity, depending on the precursor biomolecule. In situ fractionation via Berner type impactor afforded populations with characteristic sizes ranging from ∼30 nm to 2 μm. The as-produced, dry lignin particles displayed excellent mechanical integrity, even after redispersion under high shear in either mineral oil or water. They were effective in the stabilization of oil-in-water (O/W) Pickering emulsions with tunable droplet size, depending on the dimension of the lignin particles used for emulsification. The emulsion stability correlated with particle concentration as well as the respective lignin type. For the O/W emulsions stabilized with the more hydrophilic lignin particles, negligible changes in phase separation via Ostwald ripening and coalescence were observed over a period of time of more than two months. Together with the fact that the lignin particle concentrations used in emulsification were as low as 0.1%, our results reveal a remarkable ability to endow emulsified systems with high colloidal stability. Overall, we offer a new, high-yield, scalable nanomanufacturing approach to producing dry spherical lignin particles with size control and high production capacity. A number of emerging applications for these organic particles can be envisioned and, as a proof-of-concept, we illustrate here surfactant-free emulsification.
Recent progress in advanced nanostructures synthesized from biomass resources for the oxygen reduction reaction (ORR) is reviewed. The ORR plays a significant role in the performance of numerous energy-conversion devices, including low-temperature hydrogen and alcohol fuel cells, microbial fuel cells, as well as metal-air batteries. The viability of such fuel cells is strongly related to the cost of the electrodes, especially the cathodic ORR electrocatalyst. Hence, inexpensive and abundant plant and animal biomass have become attractive options to obtain electrocatalysts upon conversion into active carbon. Bioresource selection and processing criteria are discussed in light of their influence on the physicochemical properties of the ORR nanostructures. The resulting electrocatalytic activity and durability are introduced and compared to those from conventional Pt/C-based electrocatalysts. These ORR catalysts are also active for oxygen or hydrogen evolution reactions.
Sugar‐based biorefineries have faced significant economic challenges. Biorefinery lignins are often classified as low‐value products (fuel or low‐cost chemical feedstock) mainly due to low lignin purities in the crude material. However, recent research has shown that biorefinery lignins have a great chance of being successfully used as high‐value products, which in turn should result in an economy renaissance of the whole biorefinery idea. This critical review summarizes recent developments from our groups, along with the state‐of‐the‐art in the valorization of technical lignins, with the focus on biorefinery lignins.
A beneficial synergistic effect of lignin and cellulose mixtures used in different applications (wood adhesives, carbon fiber and nanofibers, thermoplastics) has been demonstrated. This phenomenon causes crude biorefinery lignins, which contain a significant amount of residual crystalline cellulose, to perform superior to high‐purity lignins in certain applications. Where previously specific applications required high‐purity and/or functionalized lignins with narrow molecular weight distributions, simple green processes for upgrading crude biorefinery lignin are suggested here as an alternative. These approaches can be easily combined with lignin micro‐/nanoparticles (LMNP) production. The processes should also be cost‐efficient compared to traditional lignin modifications.
Biorefinery processes allow much greater flexibility in optimizing the lignin characteristics desirable for specific applications than traditional pulping processes. Such lignin engineering, at the same time, requires an efficient strategy capable of handling large datasets to find correlations between process variables, lignin structures and properties and finally their performance in different applications.
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