arXiv (All)
open access
Self-assembly Monte Carlo reveals localized entanglement in giant polymer melts
Topological entanglements are central to understanding and predicting the properties of polymer melts. Yet, they make equilibrium sampling computationally challenging, as decorrelation times grow rapidly with chain length. Here, we introduce a Monte Carlo scheme that bypasses typical computational b
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- A route to the thermodynamics of colloid-polymer mixtures from structural information#793947
- A route to the thermodynamics of colloid-polymer mixtures from structural information#789928
- Machine learning for the optimization of porosity-hygroscopy correlations of porous geopolymers in indoor thermal comfort: A hybrid feature selection approach#268537
- Interaction-Dependent Molecular Probing of Heterogeneous Glassy Dynamics in Polymer Melts#1116296
- Probing the microscopic origin of toughness in multiple polymer networks#274372
Record · ID 1215600
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive