2012
DOI: 10.2172/1055641
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The mechanics of network polymers with thermally reversible linkages.

Abstract: Encapsulated printed circuit boards typically use conventional thermosetting polymers which are difficult to remove without damaging the electronics if upgrades are needed. To improve the efficiency of maintaining printed circuit boards, network polymers with thermally reversible linkages were developed to provide an alternative class of encapsulation thermosets that could be easily and non-destructively removed and later reapplied. These polymers include functionalities that dynamically break and form covalen… Show more

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Cited by 4 publications
(5 citation statements)
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“…In addition, if one takes "phase" as a more general representation of a small collection of material fraction that has distinct deformation history, one would find that many active materials can achieve shape memory effects or its active motion through the phase evolution mechanism, such as light activated polymers developed by Lendlein et al [53] and Scott and coworkers [220,293], covalent adaptable network polymers with bond exchange reaction [294,295], DielsAlder network [296,297], ionic gels [298]. Several constitutive models were developed in the recent years to model these material systems, such as light activate polymers [299][300][301], shape memory elastomeric composites [302] and its triple shape memory behavior [303,304], polymers with temperature-dependent bond exchange reactions [305], and Diels-Alder networks [306]. The concept of employing phase formation to achieve shape memory effect can be easily illustrated by Fig.…”
Section: Phase Evolution Modelsmentioning
confidence: 99%
“…In addition, if one takes "phase" as a more general representation of a small collection of material fraction that has distinct deformation history, one would find that many active materials can achieve shape memory effects or its active motion through the phase evolution mechanism, such as light activated polymers developed by Lendlein et al [53] and Scott and coworkers [220,293], covalent adaptable network polymers with bond exchange reaction [294,295], DielsAlder network [296,297], ionic gels [298]. Several constitutive models were developed in the recent years to model these material systems, such as light activate polymers [299][300][301], shape memory elastomeric composites [302] and its triple shape memory behavior [303,304], polymers with temperature-dependent bond exchange reactions [305], and Diels-Alder networks [306]. The concept of employing phase formation to achieve shape memory effect can be easily illustrated by Fig.…”
Section: Phase Evolution Modelsmentioning
confidence: 99%
“…From non-Gaussian chain statistics, this limiting stretch ratio lim c  is connected to the number of Kuhn segments by lim ck N   [73,74]. In the previous work of Long et al [44], this number of Kuhn segment was determined to be …”
Section: Predictions On the Effective Modulus Of Welded Samplementioning
confidence: 99%
“…Such a modeling scheme exhibits reasonable fidelity but is computationally expensive. Recently, within the scope of continuum mechanics, Long et al [44] studied the mechanics of dynamic covalent networks with thermally induced Diels-Alder reactions. Long et al [45] investigated the stress relaxation of epoxy thermosets with thermally induced BERs.…”
mentioning
confidence: 99%
“…Several scientific articles have reported the ability of thermoset polymers to be repaired in different ways. These include the incorporation of low molecular weight additives in the form of capsules as healing agent after damage events (extrinsic self-repair) [12][13][14][15][16], but also the functionalization of raw non-reworkable polymers that can heal cracks as a consequence of an external stimuli like heat [17][18][19][20] and light [21][22][23][24][25] (intrinsic self-repair). The last approach relies on the chemical modification of the base polymer with functional groups able to undergo a reversible reaction as function of the presence/absence of the external stimulus.…”
Section: Introductionmentioning
confidence: 99%