Rapid discovery of agents for improved chemical agglomeration of fine particles in coal-fired flue gas – A molecular dynamics simulation-based approach and its validation

Abstract

The agglomeration of fine particles, particularly PM2.5, into larger particles, has been a pivotal focus in the battle against atmospheric haze, garnering significant attention in regions addressing this challenge. In this study, a molecular dynamics (MD) simulations-based approach was proposed for the rapid screening of chemical agents and optimal operating conditions for the improved agglomeration of particulate matter in coal-fired power plants. Our findings reveal a distinct hierarchy in agglomeration effectiveness of chemical agents, with the following order: glucose/mannose > carboxylic acid (-COOH-) > nitrate (-ONO2) > hydroxyl (-OH) > ester (-COOC-) > aldehyde (-CHO). Additionally, an exploration delves into fifteen water-soluble polymers, including soluble starch, carboxyl methylcellulose, etc. Remarkably, soluble starch emerges as the most promising agent for the agglomeration of fine particles. Through analyses of interaction energy and the Radial Distribution Function, it is evident that neutral conditions and a temperature at 378 K offer the most conducive environment for chemical agglomeration. Empirical experiments confirmed the outstanding performance of soluble starch in the agglomeration of fine particulate matter, resulting in the excellent fine particles agglomeration performance.