This dataset focuses on the design factors and corresponding properties for the production of cellulose lightweight materials (LMs). These materials, such as foams and aerogels, have distinctive mechanical and thermal properties, making them suitable for cushioning and insulative packaging. The dataset was developed to understand the various "design factors" and their sub-parameters that influence the properties of cellulose LMs, which are vital for packaging applications. Comprising 208 entries of air-dried LMs and 335 entries of freeze-dried LMs, it includes parameters such as the type and concentration of raw materials, method of porosity creation (freeze drying or air drying), drying conditions (temperature, time, surfactants, additives), and measured properties of the materials (apparent density, Young's modulus, yield stress, thermal conductivity). Data was extracted from peer-reviewed publications and patents, standardized for consistency, and processed with specific rules for material classification, concentration, and measurement units. The dataset can be used for machine learning to predict LM properties based on design factors, with a sample Python code provided for demonstration. Limitations include the underrepresentation of non-English publications and potential uncertainties in data estimated from images.

2024