Cross‐Linking Matters: Atomistic Simulations of the Thermal Degradation of Polymethylsiloxanes

Abstract Utilizing an advanced machine‐learning interatomic potential (MLIP) for Si─C─O─H, the thermal breakdown of polysiloxanes covering polymers from linear polydimethylsiloxane (PDMS) to highly networked polymethylsilsesquioxane (PMSQ), is investigated. The reactive simulations reveal that increasing cross‐linking density enhances both thermal stability and ceramic yield after pyrolysis. Multiple pathways for forming siloxane oligomers are uncovered–pathways that depend on the number of unbranched units in the polymer. By simulating the release of gaseous species, the mass‐retention profiles observed in experiments are reproduced: PMSQ exhibits the highest mass retention, while PDMS is prone to substantial mass loss. Non‐isothermal simulations produce thermogravimetric studies and show that higher thermal stability and the peak of mass loss rate align with the degree of cross‐linking. Moreover, these simulations enable a kinetic analysis of TGA data, yielding an activation energy for PDMS degradation that is consistent with literature values. Finally, it is shown that PDMS domains embedded within PMSQ matrices act as sacrificial templates, carving out nanoscale voids that give rise to tailored porosity in the final SiCO ceramics. Overall, the atomistic simulations provide insights into reaction mechanisms and validate experimental trends and offer predictive guidance for tuning preceramic polymers toward tailored ceramic yields and microstructures.

Authors

Institutions

Publication Details

Journal
Advanced Theory and Simulations
Published
2025-10-07
DOI
https://doi.org/10.1002/adts.202501437
Primary Topic
Polymer crystallization and properties
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cross‐Linking Matters: Atomistic Simulations of the Thermal Degradation of Polymethylsiloxanes

Peter Kroll, Mitchell Falgoust
Advanced Theory and Simulations
Polymer crystallization and properties
article

Cross‐Linking Matters: Atomistic Simulations of the Thermal Degradation of Polymethylsiloxanes

Peter Kroll, Mitchell Falgoust
article en

Abstract

Abstract Utilizing an advanced machine‐learning interatomic potential (MLIP) for Si─C─O─H, the thermal breakdown of polysiloxanes covering polymers from linear polydimethylsiloxane (PDMS) to highly networked polymethylsilsesquioxane (PMSQ), is investigated. The reactive simulations reveal that increasing cross‐linking density enhances both thermal stability and ceramic yield after pyrolysis. Multiple pathways for forming siloxane oligomers are uncovered–pathways that depend on the number of unbranched units in the polymer. By simulating the release of gaseous species, the mass‐retention profiles observed in experiments are reproduced: PMSQ exhibits the highest mass retention, while PDMS is prone to substantial mass loss. Non‐isothermal simulations produce thermogravimetric studies and show that higher thermal stability and the peak of mass loss rate align with the degree of cross‐linking. Moreover, these simulations enable a kinetic analysis of TGA data, yielding an activation energy for PDMS degradation that is consistent with literature values. Finally, it is shown that PDMS domains embedded within PMSQ matrices act as sacrificial templates, carving out nanoscale voids that give rise to tailored porosity in the final SiCO ceramics. Overall, the atomistic simulations provide insights into reaction mechanisms and validate experimental trends and offer predictive guidance for tuning preceramic polymers toward tailored ceramic yields and microstructures.

Advanced Theory and SimulationsVol. 9(1)
The University of Texas at Arlington (US)
Openalex Percentile: Top 76%
Polymer crystallization and properties
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.