Elucidating the pyrolysis mechanism of lincomycin pharmaceutical waste through thermal analysis

Abstract Based on thermokinetic methods, the pyrolysis behavior was systematically investigated over a defined temperature range. The variations in apparent activation energy during the decomposition process were analyzed, and the most probable reaction model was determined. The optimal pyrolysis performance was observed at a heating rate of 10 K/min, corresponding to a performance index of 9.13 × 10 −4 . The decomposition process was delineated into three distinct stages. The apparent activation energies, evaluated using isoconversional methods (FWO, KAS, Starink, Friedman, and Popescu), exhibited a characteristic trend across these stages: an initial decrease, followed by an increase, and a subsequent final decrease. The respective average activation energies for the three stages were determined to be 75.79, 237.57, and 188.01 kJ/mol. The reaction stages were closely described by the Mamper equation, indicating a nonlinear reaction progression with reaction orders (n‐values) falling within the range of 0.7–1. This observed complexity in the pyrolysis mechanism suggests a multistep or diffusion‐influenced process, thus pointing to the necessity for further investigation to optimize energy recovery from pharmaceutical waste.

Authors

Institutions

Publication Details

Journal
Environmental Progress & Sustainable Energy
Published
2026-03-02
DOI
https://doi.org/10.1002/ep.70404
Primary Topic
Thermochemical Biomass Conversion Processes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Elucidating the pyrolysis mechanism of lincomycin pharmaceutical waste through thermal analysis

Yixin Yang, Aibin Kang, Ming Zhang, Zhongyu Yang et al.
Environmental Progress & Sustainable Energy
Thermochemical Biomass Conversion Processes
article

Elucidating the pyrolysis mechanism of lincomycin pharmaceutical waste through thermal analysis

Yixin Yang, Aibin Kang, Ming Zhang, Zhongyu Yang, Erhong Duan
article en

Abstract

Abstract Based on thermokinetic methods, the pyrolysis behavior was systematically investigated over a defined temperature range. The variations in apparent activation energy during the decomposition process were analyzed, and the most probable reaction model was determined. The optimal pyrolysis performance was observed at a heating rate of 10 K/min, corresponding to a performance index of 9.13 × 10 −4 . The decomposition process was delineated into three distinct stages. The apparent activation energies, evaluated using isoconversional methods (FWO, KAS, Starink, Friedman, and Popescu), exhibited a characteristic trend across these stages: an initial decrease, followed by an increase, and a subsequent final decrease. The respective average activation energies for the three stages were determined to be 75.79, 237.57, and 188.01 kJ/mol. The reaction stages were closely described by the Mamper equation, indicating a nonlinear reaction progression with reaction orders (n‐values) falling within the range of 0.7–1. This observed complexity in the pyrolysis mechanism suggests a multistep or diffusion‐influenced process, thus pointing to the necessity for further investigation to optimize energy recovery from pharmaceutical waste.

Environmental Progress & Sustainable Energy
Hebei University of Science and Technology (CN), Hebei Chemical and Pharmaceutical College (CN), Hebei Food Inspection and Research Institute (CN)
Affordable and clean energy
Openalex Percentile: Top 30%
Thermochemical Biomass Conversion Processes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.