Shape memory polymers (SMPs), as a class of programmable stimuliresponsive shape changing polymers, are attracting increasing attention from the standpoint of both fundamental research and technological innovations. Following a brief introduction of the conventional shape memory effect (SME), progress in new shape memory enabling mechanisms and triggering methods, variations of in shape memory forms (shape memory surfaces, hydrogels, and microparticles), new shape memory behavior (multi-SME and two-way-SME), and novel fabrication methods are reviewed. Progress in thermomechanical modeling of SMPs is also presented. Abbreviations:SCPs shape changing polymers; LCEs liquid crystalline elastomers; SMP shape memory polymer; SME shape memory effect; 2W two-way; 1W oneway; T trans transition temperature; T g glass transition temperature; T m melting temperature; T cl liquid crystal cleaning temperature; T d deformation temperature; T f shape fixing temperature; T c crystallization temperature; R f shape stability ratio; R r shape recovery ratio; T sw switching temperature; ε max maximum recoverable strain; σ max maximum recovery stress; SMC shape memory cycle; ε load strain under load; ε fixed strain; T r recovery Page 2 of 106 A c c e p t e d M a n u s c r i p t 2 temperature; ε rec recovered strain; V r strain recovery rate; T σmax temperature corresponding to σ max ; T sw,app apparent switching temperature; PCL poly(ε-caprolactone); SMPU shape memory polyurethane; EMU elemental memory unit; TME temperature memory effect; PU polyurethane; T i liquid-crystal isotropic transition temperature; T v vitrification temperature; CIE crystallization induced elongation; MIC melting induced contraction

Dynamic covalent polymer networks have long been recognized. With the initial focus on the unintended impact of dynamic covalent linkages on the viscoelasticity of commercial rubbers, efforts in modern times have transitioned into designing dynamic covalent polymer networks with unique adaptive properties. Whereas self-healing and thermoset reprocessing have been the primary motivations for studying dynamic covalent polymer networks, the recent discovery of the vitrimeric rheological behavior and solid-state plasticity for this type of material have opened up new opportunities in material innovations. This, coupled with the revelation of the dynamic characteristics of commercially relevant polymer building blocks such as esters and urethanes, suggests a promising future for this class of materials.

Dynamic covalent polymer networks (DCPN) have historically attracted attention for their unique roles in chemical recycling and self-healing, which are both relevant for sustainable societal development. Efforts in these directions have intensified in the past decade with notable progress in newly discovered dynamic covalent chemistry, fundamental material concepts, and extension toward emerging applications including energy and electronic devices. Beyond that, the values of DCPN in discovering/designing functional properties not offered by classical thermoplastic and thermoset polymers have recently gained traction. In particular, the dynamic bond exchangeability of DCPN has shown unparalleled design versatility in various areas including shape-shifting materials/devices, artificial muscles, and microfabrication. Going beyond this basic bond exchangeability, various molecular mechanisms to manipulate network topologies (topological transformation) have led to opportunities to program polymers, with notable concepts such as living networks and topological isomerization. In this review, we provide an overview of the above progress with particular focuses on molecular design strategies for the exploitation of functional material properties. Based on this, we point out the remaining issues and offer perspectives on how this class of materials can shape the future in ways that are complementary with classical thermoplastic and thermoset polymers.