Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Boattini, Emanuele"'
Autor:
Ciarella, Simone, Chiappini, Massimiliano, Boattini, Emanuele, Dijkstra, Marjolein, Janssen, Liesbeth M. C.
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 particle propensity, our method is built upon a theoretical framework that
Externí odkaz:
http://arxiv.org/abs/2212.09338
Autor:
Chintha, Dinesh, Veesam, Shivanand Kumar, Boattini, Emanuele, Filion, Laura, Punnathanam, Sudeep N
Publikováno v:
The Journal of Chemical Physics 155, 244901 (2021)
Ligand coated nanoparticles are complex objects consisting of a metallic or semiconductor core with organic ligands grafted on their surface. These organic ligands provide stability to a nanoparticle suspension. In solutions, the effective interactio
Externí odkaz:
http://arxiv.org/abs/2202.13012
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 liquids. These methods include both increasingly complex machine learn
Externí odkaz:
http://arxiv.org/abs/2202.09173
Simulations of colloidal suspensions consisting of mesoscopic particles and smaller species such as ions or depletants are computationally challenging as different length and time scales are involved. Here, we introduce a machine learning (ML) approa
Externí odkaz:
http://arxiv.org/abs/2111.14910
Colloidal self-assembly -- the spontaneous organization of colloids into ordered structures -- has been considered key to produce next-generation materials. However, the present-day staggering variety of colloidal building blocks and the limitless nu
Externí odkaz:
http://arxiv.org/abs/2106.14615
Publikováno v:
Phys. Rev. Lett. 127, 088007 (2021)
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 explosion of methods for making such a prediction, often via the applic
Externí odkaz:
http://arxiv.org/abs/2105.05921
Publikováno v:
J. Chem. Phys. 153, 064902 (2020)
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 a simple pairwise interaction, which is usually a valid approximation
Externí odkaz:
http://arxiv.org/abs/2005.14580
Autor:
Boattini, Emanuele, Marín-Aguilar, Susana, Mitra, Saheli, Foffi, Giuseppe, Smallenburg, Frank, Filion, Laura
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: close to the glass transition, the dynamics slow down dramatically and be
Externí odkaz:
http://arxiv.org/abs/2003.00586
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 this algorithm, we use a vector of standard bond-orientational order par
Externí odkaz:
http://arxiv.org/abs/1907.02420
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