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Author Faraji, F.; Neek-Amal, M.; Neyts, E.C.; Peeters, F.M.
Title Cation-controlled permeation of charged polymers through nanocapillaries Type A1 Journal article
Year 2023 Publication Physical review E Abbreviated Journal Phys Rev E
Volume 107 Issue 3 Pages 034501-34510
Keywords A1 Journal article; Condensed Matter Theory (CMT); Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Abstract Molecular dynamics simulations are used to study the effects of different cations on the permeation of charged polymers through flat capillaries with heights below 2 nm. Interestingly, we found that, despite being monovalent, Li+ , Na+ , and K+ cations have different effects on polymer permeation, which consequently affects their transmission speed throughout those capillaries. We attribute this phenomenon to the interplay of the cations' hydration free energies and the hydrodynamic drag in front of the polymer when it enters the capillary. Different alkali cations exhibit different surface versus bulk preferences in small clusters of water under the influence of an external electric field. This paper presents a tool to control the speed of charged polymers in confined spaces using cations.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Wos 000955986000006 Publication Date 2023-03-17
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2470-0053 ISBN Additional Links UA library record; WoS full record; WoS citing articles
Impact Factor 2.4 Times cited Open Access Not_Open_Access
Notes Approved (up) Most recent IF: 2.4; 2023 IF: 2.366
Call Number UA @ admin @ c:irua:196089 Serial 7586
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Author McNaughton, B.; Milošević, M.V.; Perali, A.; Pilati, S.
Title Boosting Monte Carlo simulations of spin glasses using autoregressive neural networks Type A1 Journal article
Year 2020 Publication Physical Review E Abbreviated Journal Phys Rev E
Volume 101 Issue 5 Pages 053312
Keywords A1 Journal article; Condensed Matter Theory (CMT)
Abstract The autoregressive neural networks are emerging as a powerful computational tool to solve relevant problems in classical and quantum mechanics. One of their appealing functionalities is that, after they have learned a probability distribution from a dataset, they allow exact and efficient sampling of typical system configurations. Here we employ a neural autoregressive distribution estimator (NADE) to boost Markov chain Monte Carlo (MCMC) simulations of a paradigmatic classical model of spin-glass theory, namely, the two-dimensional Edwards-Anderson Hamiltonian. We show that a NADE can be trained to accurately mimic the Boltzmann distribution using unsupervised learning from system configurations generated using standard MCMC algorithms. The trained NADE is then employed as smart proposal distribution for the Metropolis-Hastings algorithm. This allows us to perform efficient MCMC simulations, which provide unbiased results even if the expectation value corresponding to the probability distribution learned by the NADE is not exact. Notably, we implement a sequential tempering procedure, whereby a NADE trained at a higher temperature is iteratively employed as proposal distribution in a MCMC simulation run at a slightly lower temperature. This allows one to efficiently simulate the spin-glass model even in the low-temperature regime, avoiding the divergent correlation times that plague MCMC simulations driven by local-update algorithms. Furthermore, we show that the NADE-driven simulations quickly sample ground-state configurations, paving the way to their future utilization to tackle binary optimization problems.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Wos 000535862000014 Publication Date 2020-05-28
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1539-3755; 1550-2376 ISBN Additional Links UA library record; WoS full record; WoS citing articles
Impact Factor 2.366 Times cited 15 Open Access
Notes ; The authors thank I. Murray, G. Carleo, and F. RicciTersenghi for useful discussions. Financial support from the FAR2018 project titled “Supervised machine learning for quantum matter and computational docking” of the University of Camerino and from the Italian MIUR under Project No. PRIN2017 CEnTraL 20172H2SC4 is gratefully acknowledged. S.P. also acknowledges the CINECA award under the ISCRA initiative, for the availability of high performance computing resources and support. M.V.M. gratefully acknowledges the Visiting Professorship program at the University of Camerino that facilitated the collaboration in this work. ; Approved (up) Most recent IF: NA
Call Number UA @ admin @ c:irua:170244 Serial 6463
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Author Jalali, H.; Ghorbanfekr, H.; Hamid, I.; Neek-Amal, M.; Rashidi, R.; Peeters, F.M.
Title Out-of-plane permittivity of confined water Type A1 Journal article
Year 2020 Publication Physical Review E Abbreviated Journal Phys Rev E
Volume 102 Issue 2 Pages 022803
Keywords A1 Journal article; Condensed Matter Theory (CMT); Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Abstract The dielectric properties of confined water is of fundamental interest and is still controversial. For water confined in channels with height smaller than h = 8 angstrom, we found a commensurability effect and an extraordinary decrease in the out-of-plane dielectric constant down to the limit of the dielectric constant of optical water. Spatial resolved polarization density data obtained from molecular dynamics simulations are found to be antisymmetric across the channel and are used as input in a mean-field model for the dielectric constant as a function of the height of the channel for h > 15 angstrom. Our results are in excellent agreement with a recent experiment [L. Fumagalli et al., Science 360, 1339 (2018)].
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Wos 000560660400004 Publication Date 2020-08-11
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1539-3755; 1550-2376 ISBN Additional Links UA library record; WoS full record; WoS citing articles
Impact Factor 2.366 Times cited 25 Open Access
Notes ; This work was supported by the Flemish Science Foundation (FWO-Vl) and the Methusalem program. ; Approved (up) Most recent IF: NA
Call Number UA @ admin @ c:irua:171157 Serial 6574
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