40 citations · 115 across the 8 of their papers we have counts for
8 papers
Auxetic behaviour in crystals of hard polyhedra
Rinske M. Alkemade, Silvana A. Caipa Cure, Alptuğ Ulugöl +8
Auxetic materials - systems that, when subjected to a compression in one direction, also compress in one or more perpendicular directions - have intrigued researchers for decades d…
Determining fluid-crystal phase boundaries for a binary hard-sphere mixture using direct-coexistence simulations
Rinske M. Alkemade, Alessandro Salo, Laura Filion +1
Determining fluid-crystal phase boundaries via direct-coexistence methods can be challenging due to the fact that the simulation box can introduce crystal strain. Recently, a direc…
Characterizing the cage state of glassy systems and its sensitivity to frozen boundaries
Rinske M. Alkemade, Frank Smallenburg, Laura Filion
Understanding the role that structure plays in the dynamical arrest observed in glassy systems remains an open challenge. Over the last decade, machine learning (ML) strategies hav…
Machine learning short-ranged many-body interactions in colloidal systems using descriptors based on Voronoi cells
Rinske M. Alkemade, Rastko Sknepnek, Frank Smallenburg +1
Machine learning (ML) strategies are opening the door to faster computer simulations, allowing us to simulate more realistic colloidal systems. Since the interactions in colloidal…
Roadmap on machine learning glassy dynamics
Gerhard Jung, Rinske M. Alkemade, Victor Bapst +10
Unraveling the connections between microscopic structure, emergent physical properties, and slow dynamics has long been a challenge when studying the glass transition. The absence…
Improving the prediction of glassy dynamics by pinpointing the local cage
Rinske M. Alkemade, Frank Smallenburg, Laura Filion
The relationship between structure and dynamics in glassy fluids remains an intriguing open question. Recent work has shown impressive advances in our ability to predict local dyna…
Comparing machine learning techniques for predicting glassy dynamics
Rinske M. Alkemade, Emanuele Boattini, Laura Filion +1
In the quest to understand how structure and dynamics are connected in glasses, a number of machine learning based methods have been developed that predict dynamics in supercooled…
Point Defects in Crystals of Charged Colloids
Rinske M. Alkemade, Marjolein de Jager, Berend van der Meer +2
Charged colloidal particles - both on the nano and micron scales - have been instrumental in enhancing our understanding of both atomic and colloidal crystals. These systems can be…