The Development and Application of NMR Methodologies for the Study of Degradation in Complex Silicones

Lewicki, James P.; Maxwell, Robert S.; Mayer, Brian; Maiti, Amitesh; Harley, Stephen J.

doi:10.1002/9781118938478.ch11

Cited by 6 publications

(11 citation statements)

References 105 publications

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“…Today there is no single suitable spectroscopic method which can differentiate information received relating the network interactions within the resulting spectra due to bulk assessment of the structural markers. 21 Furthermore, many network level functionalities (e.g., free chain ends, chemical cross-link points, and stress-induced chain scissions), which, despite having a significant impact on the dynamics and properties of polysiloxane elastomers, occur at the nano-to picomolar levels with respect to the total network and as such are often beyond the limits of resolution of common spectroscopic techniques. Some knowledge of the original structure and components of engineered silicones can be understood from destructive techniques, such as pyrolysis, which allows for the interpretation of the thermal degradation products of the engineered silicones.…”

Section: ■ Introductionmentioning

confidence: 99%

“…24−33 Polysiloxane networks undergo a range of degradation mechanisms, which include a broad spectrum of temporal and spatial scales ranging from the molecular, meso, and macro scale. 21 Common causes of degradation within polysiloxane materials are environmental influences, such as irradiation, mechanical stresses, and thermal exposure. Degradation reactions within polysiloxane materials involve concurring competing processes of backbone chain breaking (scission, backbiting, and unzipping) and newly formed bonds (via free radical or silanol rearrangement cross-linking) mechanisms.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Previously, nuclear magnetic resonance (NMR) has been used to characterize the structure of polysiloxane networks with respect to age and degradation. 21 However, both pre-and postdegradation, isolation of the specific chemical moieties methyl [−CH 3 ] groups on the backbone and hydrogen atoms attached to the silanol [−Si−OH] ends and silica filler functionality has been beyond the limits of 1 H, 29 Si, or 13 C NMR spectroscopic techniques, making the direct quantitation at molar levels that are relevant to many aging and degradation processes, impossible. 19 F NMR is both highly sensitive and specific within the context of a material such as a polysiloxane where there is no native 19 F bath to present a signal background or interference.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Because of this combination of structural complexity and intractability, polysiloxane elastomers are challenging to characterize by most spectroscopic methods. Today there is no single suitable spectroscopic method which can differentiate information received relating the network interactions within the resulting spectra due to bulk assessment of the structural markers . Furthermore, many network level functionalities (e.g., free chain ends, chemical cross-link points, and stress-induced chain scissions), which, despite having a significant impact on the dynamics and properties of polysiloxane elastomers, occur at the nano- to picomolar levels with respect to the total network and as such are often beyond the limits of resolution of common spectroscopic techniques.…”

Section: Introductionmentioning

confidence: 99%

“…Some knowledge of the original structure and components of engineered silicones can be understood from destructive techniques, such as pyrolysis, which allows for the interpretation of the thermal degradation products of the engineered silicones . Other techniques such as solid state nuclear magnetic resonance (NMR), attenuation total reflectance Fourier transform infrared (ATR-FTIR), and Raman spectroscopy are limited to bulk or surface analysis which generates broadly averaged data , and limited structural resolution.…”

Section: Introductionmentioning

confidence: 99%

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NMR Methodologies for the Detection and Quantification of Nanostructural Defects in Silicone Networks

et al. 2018

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We present and discuss a sensitive spectroscopic means of detecting and quantifying network defects within a series of polysiloxane elastomers through a novel application of 19F solution state nuclear magnetic resonance (NMR). Polysiloxanes are the most utilized non-carbon polymeric material today. Their final network structure is complex, hierarchical, and often ill-defined due to modification. Characterization of these materials with respect to starting and age-dependent network structure is obfuscated by the intractable nature of polysiloxane network elastomers. We report a synthetic strategy for selectively tagging chain-end silanols with an organofluorine compound, which may then be conveniently and quantitatively measured as a function of structure and environment by means of 19F NMR. This study represents a new and sensitive means of directly quantifying aspects of network architecture in polysiloxane materials and has the potential to be a powerful new tool for the spectroscopic assessment of structural dynamic response in polysiloxane networks.

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Section: ■ Introductionmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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NMR Methodologies for the Detection and Quantification of Nanostructural Defects in Silicone Networks

et al. 2018

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Second-order statistical bootstrap for the uncertainty quantification of time-temperature-superposition analysis

Maiti

2019

Rheol Acta

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A Quantum-Based Approach to Predict Primary Radiation Damage in Polymeric Networks

Kroonblawd

Goldman

Maiti

et al. 2020

J. Chem. Theory Comput.

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Initial atomistic-level radiation damage in chemically reactive materials is thought to induce reaction cascades that can result in undesirable degradation of macroscale properties. Ensembles of quantum-based molecular dynamics (QMD) simulations can accurately predict these cascades, but extracting chemical insights from the many underlying trajectories is a labor-intensive process that can require substantial a priori intuition. We develop here a general and automated graph-based approach to extract all chemically distinct structures sampled in QMD simulations and apply our approach to predict primary radiation damage of polydimethylsiloxane (PDMS), the main constituent of silicones. A postprocessing protocol is developed to identify underlying polymer backbone structures as connected components in QMD trajectories. These backbones form a repository of radiation-damaged structures. A scheme for extracting and updating a library of isomorphically distinct structures is proposed to identify the spanning set and aid chemical interpretation of the repository. The analyses are applied to ensembles of cascade QMD simulations in which the four element types in PDMS are selectively excited in primary knock-on atom events. Our approach reveals a much higher degree of combinatorial complexity in this system than was inferred through radiolysis experiments. Probabilities are extracted for radiation-induced network changes including formation of branch points, carbon linkages, cycles, bond scissions, and carbon uptake into the Si−O siloxane backbone network. The general analysis framework presented here is readily extendable to modeling chemical degradation of other polymers and molecular materials and provides a basis for future quantum-informed multiscale modeling of radiation damage.

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The Development and Application of NMR Methodologies for the Study of Degradation in Complex Silicones

Cited by 6 publications

References 105 publications

NMR Methodologies for the Detection and Quantification of Nanostructural Defects in Silicone Networks

NMR Methodologies for the Detection and Quantification of Nanostructural Defects in Silicone Networks

Second-order statistical bootstrap for the uncertainty quantification of time-temperature-superposition analysis

A Quantum-Based Approach to Predict Primary Radiation Damage in Polymeric Networks

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