Sustainable carbon fibres from lignin
Authors
Davis, Alan ; Luik, Juhan
Term
4. semester
Education
Publication year
2021
Submitted on
2021-06-15
Pages
64
Abstract
Formålet med specialet var at fremstille mere miljøvenlige kulfibre af lignin (et plantebaseret polymermateriale) ved hjælp af elektrospinding (en metode, hvor et elektrisk felt trækker meget tynde fibre). Fibrene blev efterfølgende aktiveret for at vurdere deres egnethed til CO2-fangst. Fire af de afprøvede opløsninger gav ensartede fibre uden perler (glatte fibre uden dråbelignende fortykkelser), som kunne stabiliseres og karboniseres uden at smelte sammen. Fibrene blev karakteriseret med scanningelektronmikroskopi (SEM), røntgendiffraktion (XRD) og Raman-spektroskopi, og deres CO2-optag blev undersøgt i en termogravimetrisk analysator (TGA). Effekten af opløsningskoncentration på fibrenes egenskaber blev undersøgt, og der blev fremstillet kulfibre med diametre helt ned til 310 nm. Raman-dataene var lignende for alle prøver. De aktiverede fibre kunne optage 28 mg CO2 per gram, hvilket tyder på, at dette bæredygtige materiale har potentiale til CO2-fangst.
The aim of this thesis was to make more environmentally friendly carbon fibers from lignin (a plant-based polymer) using electrospinning (an electric field draws very fine fibers). The fibers were then activated to assess their potential for CO2 capture. Four of the tested solutions produced uniform, bead-free fibers that could be stabilized and carbonized without fusing together. The fibers were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), and Raman spectroscopy, and their CO2 uptake was measured in a thermogravimetric analyzer (TGA). The effects of solution concentration on fiber properties were studied, and carbon fibers with diameters as low as 310 nm were produced. Raman data were similar across all samples. The activated fibers captured 28 mg of CO2 per gram, indicating that this sustainable material has potential for carbon capture.
[This summary has been rewritten with the help of AI based on the project's original abstract]
Keywords
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