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Unsupervised machine learning for detection of phase transitions in off-lattice systems I. Foundations
R. B. Jadrich, B. A. Lindquist, T. M. Truskett
We demonstrate the utility of an unsupervised machine learning tool for the detection of phase transitions in off-lattice systems. We focus on the application of principal componen…
Unsupervised machine learning for detection of phase transitions in off-lattice systems II. Applications
R. B. Jadrich, B. A. Lindquist, W. D. Pineros +2
We outline how principal component analysis (PCA) can be applied to particle configuration data to detect a variety of phase transitions in off-lattice systems, both in and out of…
From Close-Packed to Topologically Close-Packed: Formation of Laves Phases in Moderately Polydisperse Hard-Sphere Mixtures
Beth A. Lindquist, Ryan B. Jadrich, Thomas M. Truskett
Particle size polydispersity can help to inhibit crystallization of the hard-sphere fluid into close-packed structures at high packing fractions and thus is often employed to creat…
Gelation of Plasmonic Metal Oxide Nanocrystals by Polymer-Induced Depletion-Attractions
Camila A. Saez Cabezas, Gary K. Ong, Ryan B. Jadrich +4
Gelation of colloidal nanocrystals (NCs) emerged as a strategy to preserve inherent nanoscale properties in multiscale architectures. Yet available gelation methods still struggle…
Inverse Design of Multicomponent Assemblies
William D. Piñeros, Beth A. Lindquist, Ryan B. Jadrich +1
Inverse design can be a useful strategy for discovering interactions that drive particles to spontaneously self-assemble into a desired structure. Here, we extend an inverse design…