Application of Amino-acids for Deinking of MOW-type Paper in Flotation Columns

Mixed waste from office paper (MOW) is an excellent source of low-cost, high-quality fiber for the papermaking industry. It is a fast-growing source of materials for recycling and the most difficult raw material to deink. The limitations in conventional deinking such paper are related to the negative environmental impacts that chemical substances can cause, which is why deinking in a neutral medium is receiving increasing attention. This study focuses on investigating the effect of the application of the amino acids Aspartate, Glutamate, and Asparagine in the deinking of office paper using a flotation column on a laboratory scale.

The methodology involves sample preparation, pretreatment, flotation, paper manufacture, microscopy analysis, and optical property evaluation. Here, 9 experimental series were carried out, modifying the amino acid dose from 0.1% to 0.2% on a dry paper basis. In the pretreatment, different doses of each amino acid and a mixture of the three were tested at different temperatures and pH conditions. The quality evaluation of the paper was carried out after the measurement execution of the optical properties of the paper (brightness, tonality, opacity and content of impurities), and the analysis of the scanning electron microscope (SEM). The best optical characteristics were obtained when using the mixture of the three amino acids at 0.6% on a dry weight basis of the paper to be deinked, proposed in this study, with 90.8% whiteness. From scanning electron microscopy analysis, no superficial damage to fiber morphology is observed in any of the fiber samples after deinking. The product of the mixture of the three amino acids, Aspartate, Glutamate and Asparagine, is useful and effective in the deinking of MOW paper, and it is also respectful with the environment, since only with its reactivity in this process, it achieves results of whiteness, cleanliness, color and shine far superior to those obtained by conventional methods.