Assessment of the Alga Cladophora glomerata as a Source for Cellulose Nanocrystals

Nanocellulose is isolated from cellulosic fibers and exhibits many properties that macroscale cellulose lacks. Cellulose nanocrystals (CNCs) are a subcategory of nanocellulose made of stiff, rodlike, and highly crystalline nanoparticles. Algae of the order Cladophorales are the source of the longest cellulosic nanocrystals, but manufacturing these CNCs is not well-studied. So far, most publications have focused on the applications of this material, with the basic manufacturing parameters and material properties receiving little attention. In this article, we investigate the entirety of the current manufacturing process from raw algal biomass (Cladophora glomerata) to the isolation of algal cellulose nanocrystals. Yields and cellulose purities are investigated for algal cellulose and the relevant process intermediates. Furthermore, the effect of sulfuric acid hydrolysis, which is used to convert cellulose into CNCs and ultimately determines the material properties and some of the sustainability aspects, is examined and compared to literature results on wood cellulose nanocrystals. Long (>4 μm) CNCs form a small fraction of the overall number of CNCs but are still present in measurable amounts. The results define essential material properties for algal CNCs, simplifying their future use in functional cellulosic materials.


Additional Experimental Details
Preparation of algal cellulose from the raw algal biomass The algal cellulose used in the article was prepared using 100 g batches of air-dried Cladophora glomerata biomass.Each batch was subjected to the process stages detailed in Table S1.The eluent volumes were set to the levels specified here to ensure good mixing during the reactions, as smaller eluent usage resulted in only wetting the biomass and did not produce an aqueous media that could be mixed.Supporting Table S1

Preparation of TiO 2 -coated submonolayers
For measuring the size distribution samples were prepared by spin coating submonolayers of CNCs on a polished silica wafer.The exact procedure used here is described, as proper preparation S3 of submonolayer films of cellulose for AFM-imaging is not trivial, especially for large AFMimages where local surface imperfections may cause damage to the tip and corrupt the data collection for the entire image.The following preparation protocol allowed for consistent production 40 μm × 40 μm AFM-images with good quality and was seen as a valuable addition to the work.The following procedure is expected to work for all negatively charged CNCs, as the adhesion between the CNCs and the TiO2 surface is electrostatic in nature.
The preparation of the silica wafer coating deviated slightly from the method used by Kontturi et.al. 1 Instead of spin coating TALH (titanium(IV)-bis-(ammonium-lactato)-dihydroxide) solution directly on a polished silica wafer.a layer-by-layer coating inspired by Shi et.al. 2 proved better at providing a smooth background for the subsequent AFM-imaging.To prepare the surface for spin coating with CNCs, polished silicon wafers were first treated with the RCA-1 cleaning protocol 3 and rinsed with water.After this, they were placed into a 0.5 M NaCl.1g/l PEI-solution (Branched, Mw 70,000) for 15 minutes and rinsed with water, and finally immersed into a 5% TALH-solution for 15 minutes and rinsed with water.After preparing the surface, the wafers were held overnight in an oven at 450 o C to convert the TALH into TiO2.Then, the wafers were cut to approximately 5 mm × 5 mm squares (to fit the spin coating and AFM-imaging apparatus) and these squares were cleaned with pressurized air to remove any residual wafer dust resulting from the cutting.Prior to spin coating, the TiO2 surface of the wafer was exposed to a UV-Ozone cleaner (Biofore nanosciences) for 10 min.The CNC solutions were diluted to 60 mg/l prior to coating and spin coated at 4000 rpm.

ANOVA-analysis
In ANOVA, each variable was analysed in respect to each parameter variable pair, which is presented in Supporting Table S2.
Supporting Table S2 Then, the ANOVA-table was filled according to the template presented in Supporting Table S3.
The example of yield analysis for temperature can be seen in Supporting Table S4.

Sum of Squares Mean
The F.DIST.RT-function is a Microsoft Excel function that returns the (right-tailed) F probability distribution (degree of diversity) for two data sets.
Supporting Table S4.Anova analysis of the Yield-Temperature pair

N
Figure S1.Length distribution of CNCs with a bin width of 100 nm.
. Detailed reaction conditions of each stage . Results from the sample points Yields of the hemicellulosic sugars in manufacturing of algal celluloseSupporting TableS6.Yields of the hemicellulosic sugars in manufacturing of algal cellulose