Unraveling the mechanism of programmable heating and quenching in enhancing tar yield from PVC pyrolysis: a ReaxFF MD study
Year: 2026
Type: article
Abstract: The conventional continuous heating (CCH) method for recovering polyvinyl chloride (PVC) has limitations that result in a low tar yield. The programmable heating and quenching (PHQ) method can increase the tar yield of PVC, but the underlying mechanism was still unclear. In this study, the Reactive Force Field molecular dynamics (ReaxFF MD) simulations were used to systematically investigate the effect of the PHQ method on the tar yield of PVC. First, the PVC was pyrolyzed using the CCH method to determine the effective temperature range suitable for the PHQ method, which includes the maximum temperature ( T max ) and the minimum temperature ( T min ). Subsequently, within this temperature range, the effects of different heating and cooling time ratios ( t h / t c ) on the product distribution were compared. The results showed that a smaller t h / t c could significantly increase the tar yield. Additionally, when t h / t c was set to 1/9, the effects of changes in T max and T min on the product distribution of the thermal decomposition were studied. Finally, by comparing the product distributions of PVC pyrolysis in the PHQ and CCH modes, it was found that the PHQ method significantly increased the tar yield. Through in-depth analysis of the reaction pathways, the intrinsic mechanism of PHQ in increasing the tar yield was revealed: (1) The cooling process effectively inhibited the condensation reaction of tar, (2) Reducing the generation of organic gas molecules indirectly promoted the accumulation of tar, (3) Pulsed heating promoted the breakage and decomposition of carbon chains.
Source: Fuel
Institutions: North China Electric Power University, Tsinghua University
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,330
Awards: G332329379, G352021586, G7426334526
OpenAlex ID: W7214612223
