Hierarchical kinetic analysis for development of a reduced-order model of the multi-step thermal decomposition of munitions wastewater

Research output: Contribution to journalArticlepeer-review

Abstract

Kinetic modeling of complex, multi-component decomposition processes is typically challenging, and often requires extensive mechanistic knowledge and data from multiple techniques. This work presents a systematic framework to address these challenges, by employing a hierarchical approach to kinetic analysis, applied to experimental data from a single thermoanalytical technique, and without relying on compositional or mechanistic information, to develop an accurate reduced-order model of the thermal decomposition of munitions wastewater at 5 MPa. Composite heat flow signals obtained at 5–20 °C/min were resolved into seven peaks with an iterative deconvolution procedure by leveraging features in the original signals and subsequent residuals. Kinetic parameters for these peaks were estimated with isoconversional analysis and model fitting, refined through ODE optimization, and combined with independently modeled peak weights to construct the reduced-order model. This model was extended into a multi-step model by assigning semi-global reactions to deconvoluted peaks based on alignment with expected reaction behaviors. Both models reproduce experimental conversion profiles with r2≥0.996, demonstrating the method's effectiveness in analyzing highly overlapped multi-step reactions. The methodology presented here offers a framework that could be adapted for effective kinetic analysis of other similarly challenging systems.

Original languageEnglish
Article number180038
JournalThermochimica Acta
Volume750
DOIs
StatePublished - Aug 2025

ASJC Scopus subject areas

  • Instrumentation
  • Condensed Matter Physics
  • Physical and Theoretical Chemistry

Keywords

  • Ammonium nitrate wastewater
  • Hierarchical kinetic analysis
  • Mathematical deconvolution
  • Multi-step kinetics
  • Reaction mechanisms
  • Reduced-order model

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