Comprehensive comparison of cellulose nanocrystal (CNC) drying using multi-frequency ultrasonic technology with selected conventional drying technologies
Source abstract
Abstract
Cellulose nanocrystals (CNCs) have garnered increased attention due to their renewable nature, abundant feedstock availbility, and good mechanical properties. However, one of the bottlenecks for its commercial production is the drying process. Because of the low CNC concentrations in suspension after isolation, CNC drying requires the removal of a large amount of water to obtain dry products for the following utilization and saving shipping costs. A novel multi-frequency, multimode, modulated ultrasonic drying technology was developed for CNC drying to improve product quality, reduce energy consumption, and increase production rate. CNCs dried with different drying technologies were characterized by Fourier transform infrared (FT-IR) spectra analysis, X-ray diffraction (XRD) analysis, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and redispersibility to measure the quality and property changes. Under the same temperature and airflow rate, ultrasonic drying enhanced drying rates, resulting in at least a 50% reduction in drying time compared to hot air drying. The mean particle sizes of CNC from ultrasonic drying changed little with settling time, indicating good redispersibility. In addition, ultrasonic dried CNCs exhibited good stability in aqueous solutions, with the zeta potentials ranging from –35 to –65 mV. Specific energy consumption and CO2 emissions of various CNC drying technologies were evaluated. Energy consumption of ultrasonic drying is significantly reduced compared to other drying technologies. Moreover, the potential CO2 emissions of the fully electrified ultrasonic drying could be net zero if renewable electricity is used.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Cellulose Research Studies · Lignin and Wood Chemistry · Nanocomposite Films for Food Packaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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