A Topic Modeling Approach to Discover the Global and Local Subjects in Membrane Distillation Separation Process

• Published in: Separations Vol. 10; no. 9; p. 482
• Main Authors: Aytaç, Ersin, Khayet, Mohamed
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2023
• Subjects: Algorithms; all-mpnet-base-v2; Aqueous solutions; Artificial intelligence; c-TF-IDF; Computational linguistics; Data mining; Datasets; Distillation; Distilled water; Energy recovery; Heat recovery; Hydrostatic pressure; Language processing; Low temperature; Machine learning; Massive data points; maximal marginal relevance; membrane distillation; Membrane separation; Membranes; Methods; Modelling; Natural language interfaces; Natural language processing; Neural networks; Osmosis; Polyvinylidene fluoride; Polyvinylidene fluorides; Purification; Saline solutions; Separation; Sewage; Wastewater treatment; water treatment; Maryland; Netherlands

Membrane distillation (MD) is proposed as an environmentally friendly technology of emerging interest able to aid in the resolution of the worldwide water issue and brine processing by producing distilled water and treating high-saline solutions up to their saturation with a view toward reaching zer...