activity
20142026
most citedHierarchical macro-nanoporous metals for leakage-free high-thermal conductivity shape-stabilized phase change materials

100 citations · 564 across the 24 of their papers we have counts for

collaborators

24 papers

cond-mat.mtrl-sci2026

Structural Chart of Copper-Silver Nanoalloys through machine learning

Manoj Settem, Emanuele Telari, Antonio Tinti +2

Nanoalloys (or alloy nanoparticles) are an important class of materials that are promising for their functional properties. However, designing synthesis protocols to control their…

cond-mat.soft2024

Molecular origin of slippery behaviour in tethered liquid layers

Fabio Rasera, Isaac J. Gresham, Antonio Tinti +2

Slippery covalently attached liquid surfaces (SCALS) are a family of nanothin polymer layers with remarkably low static droplet friction, characterised by a low contact angle hyste…

physics.comp-ph2024★ 1 cited

Inherent structural descriptors via machine learning

Emanuele Telari, Antonio Tinti, Manoj Settem +10

Finding proper collective variables for complex systems and processes is one of the most challenging tasks in simulations, which limits the interpretation of experimental and simul…

cond-mat.soft2024★ 9 cited

The surface tension of Martini 3 water mixtures

Lorenzo Iannetti, Sonia Cambiaso, Fabio Rasera +4

The Martini model, a coarse-grained forcefield for biomolecular simulations, has experienced a vast increase in popularity in the past decade. Its building-block approach balances…

physics.app-ph2024

Tailored Fabrication of 3D Nanopores with Dielectric Oxides for Multiple Nanoscale Applications

German Lanzavecchia, Anastasiia Sapunova, Ali Douaki +6

Nanopore sensing is a key technology for single-molecule detection and analysis. Solid-state nanopores have emerged as a versatile platform, since their fabrication allows to engin…

cond-mat.soft2024★ 5 cited

Chemical Physics of Controlled Wettability and Super Surfaces

Carolina Brito, Hans-Jürgen Butt, Alberto Giacomello

Wetting phenomena are widespread in both natural and technological contexts. Despite the well-established nature of this scientific field and our extensive knowledge of its underly…

cond-mat.mes-hall2023

Voltage controlled iontronic switches: a computational method to predict electrowetting in hydrophobically gated nanopores

Gonçalo Paulo, Alberto Gubbiotti, Giovanni Di Muccio +1

Reliable and controllable switches are crucial in nanofluidics and iontronics. Ion channels in nature serve as a rich source of inspiration due to their intricate mechanisms modula…

cond-mat.soft2023★ 9 cited

Bubbles enable volumetric negative compressibility in metastable elastocapillary systems

Davide Caprini, Francesco Battista, Pawel Zajdel +11

Although coveted in applications, few materials expand when subject to compression or contract under decompression, i.e., exhibit the negative compressibility phenomenon. A key ste…

cond-mat.soft2023★ 13 cited

What keeps nanopores boiling

Alberto Giacomello

The liquid to vapour transition can occur at unexpected conditions in nanopores, opening the door to fundamental questions and new technologies. The physics of boiling in confineme…

cond-mat.mtrl-sci2023★ 24 cited

Structural transformations in Cu, Ag, and Au metal nanoclusters

Manoj Settem, Cesare Roncaglia, Riccardo Ferrando +1

Finite-temperature structures of Cu, Ag, and Au metal nanoclusters are calculated in the entire temperature range from 0 K to melting using a computational methodology that we prop…

cond-mat.mtrl-sci2023

Charting nanocluster structures via convolutional neural networks

Emanuele Telari, Antonio Tinti, Manoj Settem +3

A general method to obtain a representation of the structural landscape of nanoparticles in terms of a limited number of variables is proposed. The method is applied to a large dat…

cond-mat.mes-hall2023★ 70 cited

Hydrophobically gated memristive nanopores for neuromorphic applications

Gonçalo Paulo, Ke Sun, Giovanni di Muccio +6

Brain-inspired computing has the potential to revolutionise the current von Neumann architecture, advancing machine learning applications. Signal transmission in the brain relies o…

cond-mat.soft2023★ 9 cited

An atomistically informed multiscale approach to the intrusion and extrusion of water in hydrophobic nanopores

Gonçalo Paulo, Alberto Gubbiotti, Alberto Giacomello

Understanding intrusion and extrusion in nanoporous materials is a challenging multiscale problem of utmost importance for applications ranging from energy storage and dissipation…

cond-mat.soft2023★ 13 cited

Local grafting heterogeneities control water intrusion and extrusion in nanopores

Sonia Cambiaso, Fabio Rasera, Antonio Tinti +4

Hydrophobic nanoporous materials can be intruded by water only by exerting an external action, typically increasing pressure. For some materials, water extrudes when the pressure i…

physics.atm-clus2021★ 29 cited

Tempering of Au nanoclusters: capturing the temperature-dependent competition among structural motifs

Manoj Settem, Riccardo Ferrando, Alberto Giacomello

A computational approach to determine the equilibrium structures of nanoclusters in the whole temperature range from 0 K to melting is developed. Our approach relies on Parallel Te…

cond-mat.soft2021★ 7 cited

Can one predict a drop contact angle?

Marion Silvestrini, Antonio Tinti, Alberto Giacomello +1

The study of wetting phenomena is of great interest due to the multifaceted technological applications of hydrophobic and hydrophilic surfaces. The theoretical approaches proposed…

cond-mat.soft2020★ 100 cited

Hierarchical macro-nanoporous metals for leakage-free high-thermal conductivity shape-stabilized phase change materials

Yaroslav Grosu, Yanqi Zhao, Alberto Giacomello +6

Impregnation of Phase Change Materials (PCMs) into a porous medium is a promising way to stabilize their shape and improve thermal conductivity which are essential for thermal ener…

cond-mat.stat-mech2018★ 14 cited

Activated wetting of nanostructured surfaces: reaction coordinates, finite size effects, and simulation pitfalls

Matteo Amabili, Simone Meloni, Alberto Giacomello +1

A liquid in contact with a textured surface can be found in two states, Wenzel and Cassie. In the Wenzel state the liquid completely wets the corrugations while in the Cassie state…

cond-mat.soft2017★ 23 cited

Collapse of superhydrophobicity on nanopillared surfaces

Matteo Amabili, Alberto Giacomello, Simone Meloni +1

The mechanism of the collapse of the superhydrophobic state is elucidated for submerged nanoscale textures forming a three-dimensional interconnected vapor domain. This key issue f…

cond-mat.mes-hall2017★ 18 cited

Intrusion and extrusion of a liquid on nanostructured surfaces

Matteo Amabili, Alberto Giacomello, Simone Meloni +1

Superhydrophobicity is connected to the presence of gas pockets within surface asperities. Upon increasing the pressure this "suspended" state may collapse, causing the complete we…

cond-mat.soft2016★ 33 cited

Wetting and cavitation pathways on nanodecorated surfaces

Matteo Amabili, Emanuele Lisi, Alberto Giacomello +1

In this contribution we study wetting and nucleation of vapor bubbles on nanodecorated surfaces via free energy molecular dynamics simulations. The results shed light on the stabil…

cond-mat.soft2016★ 51 cited

Unraveling the Salvinia paradox: design principles for submerged superhydrophobicity

Matteo Amabili, Alberto Giacomello, Simone Meloni +1

The complex structure of the Salvinia molesta is investigated via rare event molecular dynamics simulations. Results show that a hydrophilic/hydrophobic patterning together with a…

cond-mat.soft2016★ 97 cited

Wetting hysteresis induced by nanodefects

Alberto Giacomello, Lothar Schimmele, Siegfried Dietrich

Wetting of actual surfaces involves diverse hysteretic phenomena stemming from ever-present imperfections. Here we clarify the origin of wetting hysteresis for a liquid front advan…

cond-mat.stat-mech2014★ 39 cited

Mechanism of the Cassie-Wenzel transition via the atomistic and continuum string methods

Alberto Giacomello, Simone Meloni, Marcus Mueller +1

The string method is a general and flexible strategy to compute the most probable transition path for an activated process (rare event). We apply here the atomistic string method i…