Microbial Depolymerization of Epoxy Resins: A Novel Approach to a Complex Challenge

The objective of this project is evaluating the potential of microbes (fungi and bacteria) for the depolymerization of epoxy, aiming at the development of a circular management of natural resources for epoxy in a long-term prospective. For depolymerization, epoxy samples were incubated for 1, 3, 6 and 9 months in soil microcosms inoculated with Ganoderma adspersum. Contact angle data revealed a reduction in the hydrophobicity induced by the fungus. Environmental scanning electron microscopy on epoxy samples incubated for more than 3 years in microbiological water revealed abundant microbiota. This comprised microbes of different sizes and shapes. The fungi Trichoderma harzianum and Aspergillus calidoustus, as well as the bacteria Variovorax sp. and Methyloversatilis discipulorum, were isolated from this environment. Altogether, these results suggest that microbes are able to colonize epoxy surfaces and, most probably, also partially depolymerize them. This could open promising opportunities for the study of new metabolisms potentially able depolymerize epoxy materials.

Automated Analysis of Contact Angle Goniometry Data Using DropPy

<p>Despite advances in contact angle data collection and analysis, the opacity inherent to automated options forces most non-expert researchers to rely on manual techniques and limit assessment of available data. In tandem, with the emergence of inexpensive and powerful hardware in increasingly small form-factors, the development of robust and versatile software packages would enable interrogation of wetting phenomena across a range of platforms. Here, we introduce DropPy, an open-source Python implementation of the classic axisymmetric drop shape analysis technique to fit droplet profiles from images automatically while providing an easy interface through which casual users may interpret their findings.</p>

Automated Analysis of Contact Angle Goniometry Data Using DropPy

<p>Despite advances in contact angle data collection and analysis, the opacity inherent to automated options forces most non-expert researchers to rely on manual techniques and limit assessment of available data. In tandem, with the emergence of inexpensive and powerful hardware in increasingly small form-factors, the development of robust and versatile software packages would enable interrogation of wetting phenomena across a range of platforms. Here, we introduce DropPy, an open-source Python implementation of the classic axisymmetric drop shape analysis technique to fit droplet profiles from images automatically while providing an easy interface through which casual users may interpret their findings.</p>