Search for: All records

In recent decades, more than 100 different mechanophores with a broad range of activation forces have been developed. For various applications of mechanophores in polymer materials, it is crucial to selectively activate the mechanophores with high efficiency, avoiding nonspecific bond scission of the material. In this study, we embedded cyclobutane-based mechanophore cross-linkers (I and II) with varied activation forces (fa) in the first network of the double network hydrogels and quantitively investigated the activation selectivity and efficiency of these mechanophores. Our findings revealed that cross-linker I, with a lower activation force relative to the bonds in the polymer main chain (fa-I/fa-chain = 0.8 nN/3.4 nN), achieved efficient activation with 100% selectivity. Conversely, an increase of the activation force of mechanophore II (fa-II/fa-chain = 2.5 nN/3.4 nN) led to a significant decrease of its activation efficiency, accompanied by a substantial number of nonspecific bond scission events. Furthermore, with the coexistence of two cross-linkers, significantly different activation forces resulted in the almost complete suppression of the higher-force one (i.e., I and III, fa-I/fa-III = 0.8 nN/3.4 nN), while similar activation forces led to simultaneous activations with moderate efficiencies (i.e., I and IV, fa-I/fa-IV = 0.8 nN/1.6 nN). These findings provide insights into the prevention of nonspecific bond rupture during mechanophore activation and enhance our understanding of the damage mechanism within polymer networks when using mechanophores as detectors. Besides, it establishes a principle for combining different mechanophores to design multiple mechanoresponsive functional materials. 

Hydrogen fluoride (HF) is a versatile reagent for material transformation, with applications in self-immolative polymers, remodeled siloxanes, and degradable polymers. The responsive in situ generation of HF in materials therefore holds promise for new classes of adaptive material systems. Here, we report the mechanochemically coupled generation of HF from alkoxy-gem-difluorocyclopropane (gDFC) mechanophores derived from the addition of difluorocarbene to enol ethers. Production of HF involves an initial mechanochemically assisted rearrangement of gDFC mechanophore to α-fluoro allyl ether whose regiochemistry involves preferential migration of fluoride to the alkoxy-substituted carbon, and ab initio steered molecular dynamics simulations reproduce the observed selectivity and offer insights into the mechanism. When the alkoxy gDFC mechanophore is derived from poly(dihydrofuran), the α-fluoro allyl ether undergoes subsequent hydrolysis to generate 1 equiv of HF and cleave the polymer chain. The hydrolysis is accelerated via acid catalysis, leading to self-amplifying HF generation and concomitant polymer degradation. The mechanically generated HF can be used in combination with fluoride indicators to generate an optical response and to degrade polybutadiene with embedded HF-cleavable silyl ethers (11 mol %). The alkoxy-gDFC mechanophore thus provides a mechanically coupled mechanism of releasing HF for polymer remodeling pathways that complements previous thermally driven mechanisms. 

Weak cross-linkers can improve the ultimate strength and tear resistance of polymer networks. 

We introduce a novel approach to describe mesh generation, mesh adaptation, and geometric modeling algorithms relying on changing mesh connectivity using a high-level abstraction. The main motivation is to enable easy customization and development of these algorithms via a declarative specification consisting of a set of per-element invariants, operation scheduling, and attribute transfer for each editing operation. We demonstrate that widely used algorithms editing surfaces and volumes can be compactly expressed with our abstraction, and their implementation within our framework is simple, automatically parallelizable on shared-memory architectures, and with guaranteed satisfaction of the prescribed invariants. These algorithms are readable and easy to customize for specific use cases. We introduce a software library implementing this abstraction and providing automatic shared-memory parallelization. 

The Finite Element Method (FEM) is widely used to solve discrete Partial Differential Equations (PDEs) in engineering and graphics applications. The popularity of FEM led to the development of a large family of variants, most of which require a tetrahedral or hexahedral mesh to construct the basis. While the theoretical properties of FEM basis (such as convergence rate, stability, etc.) are well understood under specific assumptions on the mesh quality, their practical performance, influenced both by the choice of the basis construction and quality of mesh generation, have not been systematically documented for large collections of automatically meshed 3D geometries. We introduce a set of benchmark problems involving most commonly solved elliptic PDEs, starting from simple cases with an analytical solution, moving to commonly used test problem setups, and using manufactured solutions for thousands of real-world, automatically meshed geometries. For all these cases, we use state-of-the-art meshing tools to create both tetrahedral and hexahedral meshes, and compare the performance of different element types for common elliptic PDEs. The goal of this benchmark is to enable comparison of complete FEM pipelines, from mesh generation to algebraic solver, and exploration of relative impact of different factors on the overall system performance. As a specific application of our geometry and benchmark dataset, we explore the question of relative advantages of unstructured (triangular/ tetrahedral) and structured (quadrilateral/hexahedral) discretizations. We observe that for Lagrange-type elements, while linear tetrahedral elements perform poorly, quadratic tetrahedral elements perform equally well or outperform hexahedral elements for our set of problems and currently available mesh generation algorithms. This observation suggests that for common problems in structural analysis, thermal analysis, and low Reynolds number flows, high-quality results can be obtained with unstructured tetrahedral meshes, which can be created robustly and automatically. We release the description of the benchmark problems, meshes, and reference implementation of our testing infrastructure to enable statistically significant comparisons between different FE methods, which we hope will be helpful in the development of new meshing and FEA techniques.