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Natural Additive for Reducing Formaldehyde Emissions in Urea-Formaldehyde Resins

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This work studies the use of soy protein as a natural formaldehyde scavenger in wood particleboard production. The protein is incorporated in two forms: a) as a powder, during the blending process of wood particles with urea-formaldehyde binder resin, and b) as an aqueous solution, added at different times during resin synthesis. Analysis of variance (ANOVA) was used to evaluate the significance level of two effects (amount of added soy and time of addition) on internal bond strength, thickness swelling, and formaldehyde content of the resulting panels. The results showed that soy protein can contribute to decrease the formaldehyde content of particleboard panels. Addition in powder form or in solution during the resin condensation step leads to the highest formaldehyde reduction, without significantly affecting the physical properties of the panels.
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Keywords: FORMALDEHYDE EMISSION; SOY PROTEIN; WOOD ADHESIVES; WOOD-BASED PANELS

Document Type: Research Article

Publication date: 2016-02-01

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  • The Journal of Renewable Materials (JRM) publishes high quality peer reviewed original research on macromolecules and additives obtained from renewable/biobased resources. Utilizing a multidisciplinary approach, JRM introduces cutting-edge research on biobased monomers, polymers, additives (both organic and inorganic), their blends and composites. It showcases both fundamental aspects and new applications for renewable materials. The fundamental theories and topics pertain to chemistry of biobased monomers, macromoners and polymers, their structure-property relationship, processing using sustainable methods, characterization (spectroscopic, morphological, thermal, mechanical, and rheological), bio and environmental degradation, and life cycle analysis. Demonstration of use of renewable materials and composites in applications including adhesives, bio and environmentally degradable structures, biomedicine, construction, electrical & electronics, mechanical, mendable and self-healing systems, optics, packaging, recycling, shape-memory, and stimulus responsive systems will be presented.
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