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Todd F. Shupe

Researcher at Louisiana State University Agricultural Center

Publications -  156
Citations -  2785

Todd F. Shupe is an academic researcher from Louisiana State University Agricultural Center. The author has contributed to research in topics: Chromated copper arsenate & Liquefaction. The author has an hindex of 26, co-authored 156 publications receiving 2468 citations. Previous affiliations of Todd F. Shupe include United States Department of Agriculture & Louisiana State University.

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Isolation and characterization of cellulose nanofibers from bamboo using microwave liquefaction combined with chemical treatment and ultrasonication.

TL;DR: The results of wet chemistry analyses, SEM images, and FTIR and X-ray spectra indicated the combination of microwave liquefaction and chemical treatment was significantly efficient in removing non-cellulosic compounds.
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Reducing leaching of boron-based wood preservatives - a review of research.

TL;DR: The key to extending the use of borates to cover the entire spectrum of wood preservation is improving their permanence in wood while retaining efficacy by retaining limited mobility of the borate.
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Renewable chemical feedstocks from integrated liquefaction processing of lignocellulosic materials using microwave energy.

TL;DR: In this article, a method for the production of phenolic rich products and sugar derivatives (biopolyols) via separation of liquefied lingocellulosic materials was proposed.

Chemical changes with maturation of the bamboo species phyllostachys pubescens

TL;DR: The chemical content and specific gravity of bamboo stabilizes at about three years of age, which is an appropriate time for harvesting, and the increases in carbohydrate content with age correlated with increases in specific gravity.
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Multivariate modelling of density, strength and stiffness from near infrared spectra for mature, juvenile and pith wood of longleaf pine ( Pinus palustris )

TL;DR: In this paper, the strength, stiffness and density of mature and juvenile longleaf pine to NIR spectra with MLR and principal component regression (PCR) were compared.