arXiv subjects

Do-Nyun Kim

Publications and source records attributed to Do-Nyun Kim.

3 recordsLinked to original sources

arXiv2026

Kirigami Meta-Sheet for Enhanced Impact Absorption

Impact absorbers based on mechanical metamaterials often use bulky, vertically stacked architectures, limiting large area deployment and scalable manufacturing. Here, we propose a kirigami meta-sheet as a planar absorber that uses transitions between positive and negative stiffness regimes rather than sacrificial crushing. Guided by an analysis of a simple mass-spring-damper model, we program the stiffness of kirigami meta-sheets through the hinge ratio connecting the unit cells. Quasistatic indentation experiments confirm that the meta-sheet with a low hinge ratio most clearly exhibits the negative stiffness transition. The drop-tower tests show that it reduces rebound, decreases the first impact force, and increases dissipation. Unlike polyethylene mesh and styrofoam, this kirigami meta-sheet is shown to be effective in protecting a falling egg. Its planar geometry enables area scaling by tiling and is compatible with sheet level manufacturing routes such as cutting, molding, and lamination, establishing kirigami meta-sheets as practical impact absorbers.

cs.CE↗

arXiv2026

Explainable quantum neural networks for multi-material topology optimization

We propose an explainable quantum neural network for multi-material topology optimization, XQNN, that determines both load-carrying structural layout and material type assignment for given boundary/loading conditions. Intermediate solution histories are first converted into element-wise strain energy, sensitivity, density, and Sobel boundary descriptors. Then, they are encoded in a ten-qubit circuit and qubit-wise $Z$ observables are mapped onto material type labels. Trained only on two-dimensional topology optimization histories obtained with a fixed mesh resolution, XQNN can be generalized to handle out-of-distribution boundary/loading conditions, progressively refined high-resolution meshes, and voxel-wise three-dimensional problems without additional training. We find that it is important to preserve qubit-wise observables and add boundary information for improving the optimization accuracy, and certain observables have consistent links to load paths, material type regions, and interfaces, demonstrating their usability as auditable mechanics-facing variables.

cs.CE↗

arXiv2010

Conformational Dynamics of Supramolecular Protein Assemblies in the EMDB

The Electron Microscopy Data Bank (EMDB) is a rapidly growing repository for the dissemination of structural data from single-particle reconstructions of supramolecular protein assemblies including motors, chaperones, cytoskeletal assemblies, and viral capsids. While the static structure of these assemblies provides essential insight into their biological function, their conformational dynamics and mechanics provide additional important information regarding the mechanism of their biological function. Here, we present an unsupervised computational framework to analyze and store for public access the conformational dynamics of supramolecular protein assemblies deposited in the EMDB. Conformational dynamics are analyzed using normal mode analysis in the finite element framework, which is used to compute equilibrium thermal fluctuations, cross-correlations in molecular motions, and strain energy distributions for 452 of the 681 entries stored in the EMDB at present. Results for the viral capsid of hepatitis B, ribosome-bound termination factor RF2, and GroEL are presented in detail and validated with all-atom based models. The conformational dynamics of protein assemblies in the EMDB may be useful in the interpretation of their biological function, as well as in the classification and refinement of EM-based structures.

q-bio.BM↗