Chemical Composition, Hygroscopic Properties, Particle Size Distribution, and Morphological Characterization of Lignocellulosic Fibres from Virgin and Recycled Sources

This record contains five complementary datasets describing the chemical, hygroscopic, and morphological properties of lignocellulosic fibres produced from virgin wood, recycled fibreboard waste, and mixed raw-material streams. The datasets include measurements of nitrogen content, dynamic vapor sorption behaviour, sieve-based particle size distribution, fibre and fines characterization using fibre tester image analysis, and fibre and fines morphology obtained by QICPIC dynamic image analysis. Together, these datasets enable systematic comparison of fibre composition, moisture–material interactions, particle size characteristics, and morphological descriptors across different industrial processing routes. The data support research in fibreboards, pulp and paper science, bio-based materials, and circular bioeconomy applications and can be used independently or in combination.

Keywords

Lignocellulosic fibres; Nitrogen content; Dynamic Vapor Sorption; Sieve analysis; Particle size distribution; Fibre morphology; Fines content; Fibre tester; QICPIC; Bio-based materials; Circular economy

Dataset 1: Nitrogen Content of Lignocellulosic Fibres

Overview

This dataset compiles nitrogen content–related information for lignocellulosic fibres obtained from different raw materials and fibre-processing technologies. Nitrogen content is relevant for understanding fibre chemistry, emissions, and downstream material performance.

Content

·       Fibre sample identifiers.

·       Raw material origin (virgin, recycled, mixed).

·       Fibre-processing route and process type.

·       Key processing parameters, when available.

·       Measured nitrogen, carbon and dry content.

Dataset 2: Dynamic Vapor Sorption (DVS) Analysis of Lignocellulosic Fibres

Overview

This dataset contains Dynamic Vapor Sorption (DVS) measurements describing the hygroscopic behaviour of lignocellulosic fibres under controlled relative humidity conditions.

Content

·       Fibre sample identifiers and material descriptions.

·       Fibre origin and processing route.

·       DVS experimental parameters.

·       Moisture sorption and desorption data.

Dataset 3: Sieve Analysis and Particle Size Distribution of Lignocellulosic Fibres

Overview

This dataset provides sieve analysis results describing the particle size distribution of lignocellulosic fibres from different production routes.

Content

·       Fibre sample identifiers and material descriptions.

·       Raw material origin and fibre-processing route.

·       Sieve size classes.

·       Percentage retained in each fraction.

Dataset 4: Fibre and Fines Characterization Using Fibre Tester Image Analysis

Overview

This dataset contains quantitative fibre and fines characterization data obtained using a fibre tester image analysis system. The method provides statistically robust morphological descriptors of fibres and fines, enabling systematic comparison of size and shape across processing conditions.

Methods

Fibre and fines measurements were carried out using an automated fibre tester image analysis system combining optical imaging and digital image processing. Measurements were conducted under controlled conditions to ensure reproducibility.

Content

·       Fibre source and processing route information.

·       Quantitative morphological parameters, including:

         o   Fibre length and width indicators.

         o   Kink and shape descriptors.

         o   Fines content metrics.

Dataset 5: Fibre and Fines Morphological Characterization Using QICPIC Dynamic Image Analysis

Overview

This dataset contains fibre and fines morphological data obtained using QICPIC dynamic image analysis. The data provide quantitative descriptors of particle size, shape, and distribution for fibres produced by thermo-mechanical, modified thermo-mechanical, wet, and dry processes.

Methods

Measurements were performed using the QICPIC dynamic image analysis system, which captures high-speed images of particles in motion and extracts morphological parameters through automated image processing. Samples were dispersed to ensure representative particle flow and minimize agglomeration.

Content

·       Sample identifiers and processing route codes.

·       Fibre origin descriptions.

·       Quantitative morphological parameters, including:

          o   Particle and fibre size distributions.

          o   Length and width metrics.

          o   Shape descriptors for fibre and fines classification.