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1. Solvent Welding and Imprinting Cellulose Nanofiber Films Using Ionic Liquids

Author

Guillermo Reyes, Alistair W. T. King, Orlando J. Rojas, Johanna Lahti, Maryam Borghei, Tampere University, Materials Science, Research group: Paper Converting and Packaging, Department of Chemistry, and Materials Chemistry

Subjects
Polymers and Plastics, 116 Chemical sciences, Nanofibers, Ionic Liquids, 02 engineering and technology, Welding, 01 natural sciences, TOXICITY, law.invention, chemistry.chemical_compound, DISSOLUTION, law, Imidazoles/chemistry, Materials Chemistry, WATER, Dissolution, COATINGS, Cellulose/analogs & derivatives, Imidazoles, Nanofibers/chemistry, NANOCELLULOSE FILMS, MECHANICAL-PROPERTIES, 021001 nanoscience & nanotechnology, Artificial, 0210 nano-technology, BEHAVIOR, Plastic welding, Materials science, Bioengineering, Context (language use), Biodegradable Plastics, 010402 general chemistry, Biomaterials, Elastic Modulus, Fourier transform infrared spectroscopy, Cellulose, ta216, Membranes, Membranes, Artificial, Biodegradable Plastics/chemistry, 0104 chemical sciences, FTIR, chemistry, Chemical engineering, 216 Materials engineering, Nanofiber, Ionic liquid, PAPER, Ionic Liquids/chemistry
Abstract

Cellulose nanofiber films (CNFF) were treated via a welding process using ionic liquids (ILs). Acid-base-conjugated ILs derived from 1,5-diazabicyclo[4.3.0]non-5-ene [DBN] and 1-ethyl-3-methylimidazolium acetate ([emim][OAc]) were utilized. The removal efficiency of ILs from welded CNFF was assessed using liquid-state nuclear magnetic resonance (NMR) spectroscopy and Fourier transform infrared spectroscopy (FTIR). The mechanical and physical properties of CNFF indicated surface plasticization of CNFF, which improved transparency. Upon treatment, the average CNFF toughness increased by 27%, and the films reached a Young's modulus of ∼5.8 GPa. These first attempts for IL "welding" show promise to tune the surfaces of biobased films, expanding the scope of properties for the production of new biobased materials in a green chemistry context. The results of this work are highly relevant to the fabrication of CNFFs using ionic liquids and related solvents. acceptedVersion

Published
2019
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2. Films based on crosslinked TEMPO-oxidized cellulose and predictive analysis via machine learning

Author

Jouni Paltakari, Merve Özkan, Alp Karakoç, Orlando J. Rojas, Maryam Borghei, Paper Converting and Packaging, Department of Bioproducts and Biosystems, Aalto-yliopisto, and Aalto University

Subjects
Materials science, Oxidized cellulose, lcsh:Medicine, 02 engineering and technology, 010402 general chemistry, Machine learning, computer.software_genre, 01 natural sciences, Polyvinyl alcohol, Article, chemistry.chemical_compound, Transmittance, Surface roughness, Cellulose, lcsh:Science, Multidisciplinary, business.industry, lcsh:R, 021001 nanoscience & nanotechnology, Flexible electronics, 0104 chemical sciences, chemistry, Nanofiber, lcsh:Q, Wetting, Artificial intelligence, 0210 nano-technology, business, computer
Abstract

We systematically investigated the effect of film-forming polyvinyl alcohol and crosslinkers, glyoxal and ammonium zirconium carbonate, on the optical and surface properties of films produced from TEMPO-oxidized cellulose nanofibers (TOCNFs). In this regard, UV-light transmittance, surface roughness and wetting behavior of the films were assessed. Optimization was carried out as a function of film composition following the “random forest” machine learning algorithm for regression analysis. As a result, the design of tailor-made TOCNF-based films can be achieved with reduced experimental expenditure. We envision this approach to be useful in facilitating adoption of TOCNF for the design of emerging flexible electronics, and related platforms.

Published
2018
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