142 citations · 431 across the 9 of their papers we have counts for
9 papers
Dynamics of supercooled liquids from static averaged quantities using machine learning
Simone Ciarella, Massimiliano Chiappini, Emanuele Boattini +2
We introduce a machine-learning approach to predict the complex non-Markovian dynamics of supercooled liquids from static averaged quantities. Compared to techniques based on parti…
Modeling of effective interactions between ligand coated nanoparticles through symmetry functions
Dinesh Chintha, Shivanand Kumar Veesam, Emanuele Boattini +2
Ligand coated nanoparticles are complex objects consisting of a metallic or semiconductor core with organic ligands grafted on their surface. These organic ligands provide stabilit…
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…
Machine learning many-body potentials for colloidal systems
Gerardo Campos-Villalobos, Emanuele Boattini, Laura Filion +1
Simulations of colloidal suspensions consisting of mesoscopic particles and smaller species such as ions or depletants are computationally challenging as different length and time…
Inverse design of soft materials via a deep-learning-based evolutionary strategy
Gabriele Maria Coli, Emanuele Boattini, Laura Filion +1
Colloidal self-assembly -- the spontaneous organization of colloids into ordered structures -- has been considered key to produce next-generation materials. However, the present-da…
Averaging local structure to predict the dynamic propensity in supercooled liquids
Emanuele Boattini, Frank Smallenburg, Laura Filion
Predicting the local dynamics of supercooled liquids based purely on local structure is a key challenge in our quest for understanding glassy materials. Recent years have seen an e…
Modeling of many-body interactions between elastic spheres through symmetry functions
Emanuele Boattini, Nina Bezem, Sudeep N. Punnathanam +2
Simple models for spherical particles with a soft shell have been shown to self-assemble into numerous crystal phases and even quasicrystals. However, most of these models rely on…
Autonomously revealing hidden local structures in supercooled liquids
Emanuele Boattini, Susana Marín-Aguilar, Saheli Mitra +3
Few questions in condensed matter science have proven as difficult to unravel as the interplay between structure and dynamics in supercooled liquids and glasses. The conundrum: clo…
Unsupervised learning for local structure detection in colloidal systems
Emanuele Boattini, Marjolein Dijkstra, Laura Filion
We introduce a simple, fast, and easy to implement unsupervised learning algorithm for detecting different local environments on a single-particle level in colloidal systems. In th…