Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods.

Availability of and access to wood identification expertise or technology is a critical component for the design and implementation of practical, enforceable strategies for effective promotion, monitoring and incentivisation of sustainable practices and conservation efforts in the forest products value chain. To address this need in the context of the multi-billion-dollar North American wood products industry 22-class, image-based, deep learning models for the macroscopic identification of North American diffuse porous hardwoods were trained for deployment on the open-source, field-deployable XyloTron platform using transverse surface images of specimens from three different xylaria and evaluated on specimens from a fourth xylarium that did not contribute training data. Analysis of the model performance, in the context of the anatomy of the woods considered, demonstrates immediate readiness of the technology developed herein for field testing in a human-in-the-loop monitoring scenario.

Field-Deployable Computer Vision Wood Identification of Peruvian Timbers.

Illegal logging is a major threat to forests in Peru, in the Amazon more broadly, and in the tropics globally. In Peru alone, more than two thirds of logging concessions showed unauthorized tree harvesting in natural protected areas and indigenous territories, and in 2016 more than half of exported lumber was of illegal origin. To help combat illegal logging and support legal timber trade in Peru we trained a convolutional neural network using transfer learning on images obtained from specimens in six xylaria using the open source, field-deployable XyloTron platform, for the classification of 228 Peruvian species into 24 anatomically informed and contextually relevant classes.

Microporous carbon nanoflakes derived from biomass cork waste for CO capture.

Porous structure design is considered to be a promising strategy for the development of effective sorbents for CO capture. Herein, a series of carbon nanoflakes with large surface area (up to 2380 m/g) and high micropore volume (up to 0.896 m/g) were synthesized from a renewable precursor, cork dust waste, to capture CO at atmospheric pressure.

A Study of the Gut Bacterial Community of Exposed to Chitosan Treatment.

A thorough understanding of microbial communities in the gut of lower termites is needed to develop target-specific and environmentally benign wood protection systems. In this study, the bacterial community from was examined by Illumina sequencing of 16S ribosomal RNA (rRNA) spanning the V3 and V4 regions. Prior to library preparation, the termites were subjected to five treatments over an 18-day period: three groups were fed on wood treated with 0.

Effects of Surface Functionalization of Lignin on Synthesis and Properties of Rigid Bio-Based Polyurethanes Foams.

We report the preparation of lignin-based rigid polyurethane (RPU) foams from surface functionalized kraft lignin via a simple and environmentally benign process. Lignin was functionalized with polyisocyanate at 80 °C for 1 h, the resulting lignin-polyisocyanate prepolymer was confirmed by increased viscosity and Fourier-transform infrared spectroscopy (FTIR). The RPU foams containing up to 30% surface functionalized lignin as a substitute for petroleum-based polyols exhibited comparable thermal and mechanical properties to conventional RPU foams.