Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Simone Ciarella"'
Autor:
Simone Ciarella, Dmytro Khomenko, Ludovic Berthier, Felix C. Mocanu, David R. Reichman, Camille Scalliet, Francesco Zamponi
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Abstract Structural defects control the kinetic, thermodynamic and mechanical properties of glasses. For instance, rare quantum tunneling two-level systems (TLS) govern the physics of glasses at very low temperature. Due to their extremely low densit
Externí odkaz:
https://doaj.org/article/b5215d3558af4598ba230fbbc3cb69fa
Autor:
Simone Ciarella, Massimiliano Chiappini, Emanuele Boattini, Marjolein Dijkstra, Liesbeth M C Janssen
Publikováno v:
Machine Learning: Science and Technology, Vol 4, Iss 2, p 025010 (2023)
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:
https://doaj.org/article/ef5c796db2bf402780f66b5640baaa0b
Publikováno v:
Machine Learning: Science and Technology, Vol 4, Iss 1, p 010501 (2023)
Several strategies have been recently proposed in order to improve Monte Carlo sampling efficiency using machine learning tools. Here, we challenge these methods by considering a class of problems that are known to be exponentially hard to sample usi
Externí odkaz:
https://doaj.org/article/71a750dff55d470e8916bc459730f1b2
Publikováno v:
SciPost Physics, Vol 12, Iss 4, p 128 (2022)
We implement a three-body potential to model associative bond swaps, and release it as part of the HOOMD-blue software. The use of a three-body potential to model swaps has been proven to be effective and has recently provided useful insights into
Externí odkaz:
https://doaj.org/article/62081ecd02bd4f4eb7fd53c134420ace
Autor:
Simone Ciarella, Massimiliano Chiappini, Emanuele Boattini, Marjolein Dijkstra, Liesbeth M C Janssen
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5d15fede67a75b7423ea68fecf56743
http://arxiv.org/abs/2212.09338
http://arxiv.org/abs/2212.09338
Publikováno v:
Machine Learning: Science and Technology
Machine Learning: Science and Technology, 2023, 4 (1), pp.010501. ⟨10.1088/2632-2153/acbe91⟩
Machine Learning: Science and Technology, 2023, 4 (1), pp.010501. ⟨10.1088/2632-2153/acbe91⟩
Several strategies have been recently proposed in order to improve Monte Carlo sampling efficiency using machine learning tools. Here, we challenge these methods by considering a class of problems that are known to be exponentially hard to sample usi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9db764d7f281e8a91fdff778f3a15fc
http://arxiv.org/abs/2210.11145
http://arxiv.org/abs/2210.11145
Autor:
Felix C. Mocanu, Ludovic Berthier, Simone Ciarella, Dmytro Khomenko, David R. Reichman, Camille Scalliet, Francesco Zamponi
Publikováno v:
Journal of Chemical Physics
Journal of Chemical Physics, 2023, 158 (1), pp.014501. ⟨10.1063/5.0128820⟩
Journal of Chemical Physics, 2023, 158 (1), pp.014501. ⟨10.1063/5.0128820⟩
The low-temperature quasi-universal behavior of amorphous solids has been attributed to the existence of spatially-localized tunneling defects found in the low-energy regions of the potential energy landscape. Computational models of glasses can be s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44ad33fbc226bd39e994b640e89ddf67
http://arxiv.org/abs/2209.09579
http://arxiv.org/abs/2209.09579
Autor:
Jannis Kolker, Simone Ciarella, Johannes Harrer, Hartmut Löwen, Maret Ickler, Liesbeth M. C. Janssen, Marcel Rey, Nicolas Vogel
Publikováno v:
Soft Matter, 17(22), 5581-5589. Royal Society of Chemistry
Thermo-responsive microgel particles can exhibit a drastic volume shrinkage upon increasing the solvent temperature. Recently we found that the spreading of poly(N-isopropylacrylamide) (PNiPAm) microgels at a liquid interface under the influence of s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::116ce80b9b5470ae6070d32984038acd
https://research.tue.nl/en/publications/1978b059-c0eb-4cc0-aac7-df6ef2e0e051
https://research.tue.nl/en/publications/1978b059-c0eb-4cc0-aac7-df6ef2e0e051
Autor:
Nicolas Vogel, Johannes Harrer, Simone Ciarella, Hartmut Löwen, Liesbeth M. C. Janssen, Marcel Rey
Publikováno v:
Soft Matter, 17(17), 4504-4516. Royal Society of Chemistry
Microgels, consisting of a swollen polymer network, exhibit a more complex self-assembly behavior compared to incompressible colloidal particles, because of their ability to deform at a liquid interface or collapse upon compression. Here, we investig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9673fbbe7d580de255dc371e6d93c747
https://doi.org/10.1039/d1sm00318f
https://doi.org/10.1039/d1sm00318f
Publikováno v:
Physical Review E, 104(6):065302. American Physical Society
Generalized mode-coupling theory (GMCT) has recently emerged as a promising first-principles theory to study the poorly understood dynamics of glass-forming materials. Formulated as a hierarchical extension of standard mode-coupling theory (MCT), it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06e6cc9f7659ee25b97acb5a893972fd
https://pubmed.ncbi.nlm.nih.gov/35030832
https://pubmed.ncbi.nlm.nih.gov/35030832