arXiv subjects

Alberto Giacomello

Publications and source records attributed to Alberto Giacomello.

At least 19 recordsLinked to original sources

arXiv2026

Voltage-Controlled Phosphate Precipitation Gating in Solid-State Nanopore Memristors

Nanofluidic memristors preserve a record of electrical activity via ion migration and alterations in conductance that depend on the history of the device s state. These characteristics make them suitable for aqueous, energy efficient, and biologically compatible neuromorphic systems. To establish the viability of fluidic memristors for mimicking the brain s dynamic behavior, a more thorough understanding of the memristive materials and the underlying switching processes is required. In this study, we systematically examined a recently introduced memristive device based on inpore chemical reactions, where the combined influence of electrolyte composition and pore architecture on precipitation gated memory remains poorly understood. To address this, we constructed an asymmetric electrochemical system using CaCl2 and phosphate solutions separated by SiNx solid state nanopores. We explored how variations in pH, phosphate concentration, pore geometry, and voltage pulsing regimens affect the electrical characteristics and memristive performance. Comparison of the single pore and the array showed that parallel pores produced smoother pH and concentration dependent hysteresis and pulse responses, whereas the single pore retained larger, nonmonotonic changes.

physics.app-ph↗

arXiv2026

Structural Chart of Copper-Silver Nanoalloys through machine learning

Nanoalloys (or alloy nanoparticles) are an important class of materials that are promising for their functional properties. However, designing synthesis protocols to control their structure and chemical ordering is rather challenging. Part of this difficulty stems from the lack of information on their metastable and stable structures. Here, we develop a general computational framework to construct a structural chart of nanoalloys using 38-atom AgCu nanoalloys as a model system. Initially, the equilibrium structural distribution is sampled using parallel tempering combined with molecular dynamics (PTMD). Using a machine learning (ML) based approach, the vast number of sampled configurations are classified into various structural classes. This ML approach produces a single three-dimensional map in which all structures and compositions can be visualized and discriminated. Finally, a finite-temperature structural chart is constructed which provides information on the dominant structures across the entire range of compositions and temperatures. In addition, the structural chart reveals significant differences in thermal stability between nanoalloys and bulk alloys. The presented framework provides an effective route to compute and map the vast structural and chemical space of multicomponent nanoparticles, paving the way to the rational design of functional nanoalloys.

cond-mat.mtrl-sci↗

arXiv2025

Electrodrying in nanopores: from fundamentals to iontronic and memristive applications

Iontronics is a burgeoning paradigm that employs ions in solution as information carriers for sensing and computing, e.g., in neuromorphic devices. The fundamentally different working principle as compared to electronics requires novel approaches and concepts to control the impedance of nanoscale fluidic circuit elements, such as nanopores. For instance, previous research has focused on voltage-induced pore wetting as a means to trigger conduction in nanopores. The present study explores the opposite counter-intuitive mechanism: using voltage to dry hydrophobic nanopores and, therefore, to turn off conduction. This "electrodrying" concept affords exquisite, bidirectional control over the conductance of nanopores additionally showing hysteresis in the current-voltage curve that is the fingerprint of memristors. Using an analytical model and free-energy molecular dynamics simulations, we explain the physical mechanism underlying electrodrying and provide clear design criteria for solid-state and biological nanopores with bidirectional control over conductance. The electrical behaviour of electrodrying nanopores shows two unique features: i) the hysteresis loop is shifted from the origin, accounting for the fifth, previously unreported memristor type and ii) negative differential resistance is observed over a broad voltage range in which the non-conductive state is favoured by electrodrying. These properties are demonstrated in a short-term memory task and in an iontronic oscillator circuit to showcase their potential in neuromorphic applications and iontronic devices. Finally, we validate our predictions through experiments on engineered dipolar hydrophobic CytK nanopores, whose voltage-dependent conductance substantiates the electrodrying concept.

physics.chem-ph↗

arXiv2025

Gated MoS2/SiN Nanochannel for Tunable Ion Transport and Protein Translocation

Ionic transport in nanofluidic channels holds great promise for applications such as single-molecule analysis, molecular manipulation, and energy harvesting. However, achieving precise control over ion transport remains a major challenge. In this work, we introduce a MoS2 SiN hybrid nanochannel architecture that enables electrical tuning of ionic transport via external gating, and we examine its potential for osmotic power generation and single molecule detection. To fabricate the channels, we employed a combined focused ion beam (FIB) milling and dry transfer method, producing sub 10 nm thick structures while preserving the structural integrity and electronic properties of MoS2, essential for reliable surface charge modulation. We first investigated how the gate voltage influences ionic conductance, finding evidence of gate dependent modulation of ion selectivity under different bias polarities. Next, by applying a salt concentration gradient across the nanochannels, we demonstrated the feasibility of this platform for osmotic energy harvesting. Finally, we tested the system for single molecule sensing, showing that linearized bovine serum albumin (BSA) produced translocation signals with notably long dwell times. Together, these results highlight gated MoS2 SiN nanochannels as a promising platform for tunable nanofluidics, with potential applications in controlled molecular transport and energy harvesting from osmotic gradients.

physics.app-ph↗

arXiv2024

Molecular origin of slippery behaviour in tethered liquid layers

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 hysteresis (CAH$< 5 \deg$), which makes them ideally suited to self-cleaning, water harvesting, and anti-fouling applications. Recently, a Goldilocks zone of lowest CAH has been identified for polydimethyl siloxane (PDMS) SCALS of intermediate thickness (3.5 nm), yet, molecular-level insights are missing to reveal the underlying physical mechanism of this elusive, slippery optimum. In this work, the agreement between coarse-grained molecular dynamics simulations and atomic force microscopy data shows that nanoscale defects, as well as deformation for thicker layers, are key to explaining the existence of this `just right' regime. At low thickness values, insufficient substrate coverage gives rise to chemical patchiness; at large thickness values, two features appear: 1) a waviness forms on the surface of the liquid layer due to a previously overlooked lateral microphase separation occurring in polydisperse brushes, and 2) layer deformation due to the contact line is larger than in thinner layers. The most pronounced slippery behaviour occurs for smooth PDMS layers that do not exhibit nanoscale waviness. The converging insights from molecular simulations, experiments, and a contact angle hysteresis theory provide design guidelines for tethered polymer layers with ultra-low contact angle hysteresis.

cond-mat.soft↗

arXiv2024

Inherent structural descriptors via machine learning

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 simulated data and the application of enhanced sampling techniques. Here, we propose a machine learning approach able to distill few, physically relevant variables by associating instantaneous configurations of the system to their corresponding inherent structures as defined in liquids theory. We apply this approach to the challenging case of structural transitions in nanoclusters, managing to characterize and explore the structural complexity of an experimentally relevant system constituted by 147 gold atoms. Our inherent-structure variables are shown to be effective at computing complex free-energy landscapes, transition rates, and at describing non-equilibrium melting and freezing processes. The effectiveness of this machine learning strategy guided by the generally-applicable concept of inherent structures shows promise to devise collective variables for a vast range of systems, including liquids, glasses, and proteins.

physics.comp-ph↗

arXiv2024

Local grafting heterogeneities control water intrusion and extrusion in nanopores

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 is lowered again. Controlling intrusion/extrusion hysteresis is central in a number of technological applications, including materials for energy applications and for high performance liquid chromatography, and experimental techniques, as liquid porosimetry, but is still far from being understood. In this work, we consider water intrusion and extrusion in common mesoporous materials grafted with hydrophobic chains, showing that the macroscopic properties of the system are significantly affected by subnanometric heterogeneities in the grafting. For example, intrusion and extrusion pressures can vary more than 20 MPa depending on the chain length and density of the grafting. Coarse-grained molecular dynamics simulations reveal that local changes of radius and contact angle produced by grafting heterogeneities can pin the interface during intrusion or facilitate bubble nucleation in extrusion. These unprecedented microscopic insights can directly impact the design of energy materials and chromatography columns, as well as the interpretation of porosimetry results.

cond-mat.soft↗

arXiv2024

Bubbles enable volumetric negative compressibility in metastable elastocapillary systems

Although coveted in applications, few materials expand when subject to compression or contract under decompression, i.e., exhibit the negative compressibility phenomenon. A key step to achieve such counterintuitive behaviour is the destabilisations of (meta)stable equilibria of the constituents. Here, we propose a simple strategy to obtain negative compressibility exploiting capillary forces both to precompress the elastic material and to release such precompression by a threshold phenomenon -- the reversible formation of a bubble in a lyophobic flexible cavity. We demonstrate that the solid part of such metastable elastocapillary systems displays negative compressibility across different scales: hydrophobic microporous materials, proteins, and millimetre-sized laminae. This concept is applicable to fields such as porous materials, biomolecules, sensors and may be easily extended to create unexpected material susceptibilities.

cond-mat.soft↗

arXiv2024

The surface tension of Martini 3 water mixtures

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 computational efficiency with high chemical specificity, enabling the simulation of various organic and inorganic molecules. The modeling of coarse-grained beads as Lennard-Jones particles poses challenges for the accurate reproduction of liquid-vapour interfacial properties, which are crucial in various applications, especially in the case of water. The latest version of the forcefield introduces refined interaction parameters for water beads, tackling the well-known artefact of Martini water freezing at room temperature. Additionally, multiple sizes of water beads are available for simulating the solvation of small cavities, including the smallest pockets of proteins. This work focuses on studying the interfacial properties of Martini water, including surface tension, surface thickness, and bulk densities for the liquid and vapour phases. Employing the test-area method, we systematically compute the liquid-vapour surface tension across various combinations of water bead sizes and for temperatures in the range from 300 to 350 K. Our findings provide a comprehensive characterization of Martini 3.0 water intefacial properties. These findings are of interest to the Martini community as they allow users to account for the low interfacial tension of Martini water by properly adjusting observables computed via coarse-grained simulations (e.g., capillary forces) to allow for accurate matching against all-atom or experimental results. Surface tension data are also interpreted in terms of local enrichment of the various mixture components at the liquid-vapour interface by means of Gibbs' adsorption formalism

cond-mat.soft↗

arXiv2024

Lipid-mediated hydrophobic gating in the BK potassium channel

The large-conductance, calcium-activated potassium (BK) channel lacks the typical intracellular bundle-crossing gate present in most ion channels of the 6TM family. This observation, initially inferred from Ca$^{2+}$-free-pore accessibility experiments and recently corroborated by a CryoEM structure of the non-conductive state, raises a puzzling question: how can gating occur in absence of steric hindrance? To answer this question, we carried out molecular simulations and accurate free energy calculations to obtain a microscopic picture of the sequence of events that, starting from a Ca$^{2+}$-free state leads to ion conduction upon Ca$^{2+}$ binding. Our results highlight an unexpected role for annular lipids, which turn out to be an integral part of the gating machinery. Due to the presence of fenestrations, the "closed" Ca$^{2+}$-free pore can be occupied by the methyl groups from the lipid alkyl chains. This dynamic occupancy triggers and stabilizes the nucleation of a vapor bubble into the inner pore cavity, thus hindering ion conduction. By contrast, Ca$^{2+}$ binding results into a displacement of these lipids outside the inner cavity, lowering the hydrophobicity of this region and thus allowing for pore hydration and conduction. This lipid-mediated hydrophobic gating rationalizes several seemingly problematic experimental observations, including the state-dependent pore accessibility of blockers.

q-bio.BM↗

arXiv2024

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

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 engineer their properties by controlling size, shape, and chemical functionalization. However, lithography-based fabrication approaches for non-planar nanopores-on-chip rely on polymers that have limits with respect to hard- and robustness, durability, and refractive index. In this respect, nanopores made of metal oxides with high dielectric constant would be much more favourable and have the potential to extend the suitability of solid-state nanopores towards optoelectronic technologies. Here, we present a versatile method to fabricate three-dimensional nanopores of different dielectric oxides with controlled shapes. Our approach uses photoresist only as a template in the focused-ion-beam lithography to define the nanopore shape, which is subsequently coated with different oxides (SiO2, Al2O3, TiO2 and HfO2) by atomic-layer deposition. Then the photoresist is fully removed by chemo-physical treatment, resulting in nanopores entirely made from dielectric oxides on a thin solid-state membrane. Our methodology allows straightforward fabrication of convex, straight, and concave nanopore shapes that can be employed in various technologies and applications. We explored their performance as ionic nanochannels and investigated the dependence of the ionic current rectification on the nanopore geometry. We found hysteresis in the ionic conductance that enables potential applications of the nanopores in memristors. We also investigated the dielectric oxide nanopores for DNA sensing by measuring both cis-trans and trans-cis translocations and support our data with numerical simulations based on the Poisson-Nernst-Planck model.

physics.app-ph↗

arXiv2024

Chemical Physics of Controlled Wettability and Super Surfaces

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 underlying principles, wetting remains a dynamic and vibrant area of study. It continues to pose fundamental questions while offering innovative avenues for controlling these phenomena to develop novel applications. By tailoring the wetting properties of surfaces, researchers and engineers can design materials with specific functionalities, such as self-cleaning surfaces, anti-fog coatings, and enhanced slipperiness. Recent years have witnessed significant advancements in wetting research, owing to the exquisite control achieved in surface topography and chemistry and to the development of novel experimental techniques. Additionally, simulations and theory have played a crucial role in these advancements. They provid the fundamental knowledge and quantitative tools to control wettability and design surfaces with enhanced properties. Given these recent breakthroughs, this special collection Chemical Physics of Controlled Wettability and Super Surfaces becomes particularly timely and significant. It serves as a platform to showcase some of the latest developments in the field of wetting. It highlights the exciting progress and potential applications in controlling wetting properties that are enabled by the synergy between theory, simulations, and experiments.

cond-mat.soft↗

arXiv2023

Hydrophobically gated memristive nanopores for neuromorphic applications

Brain-inspired computing has the potential to revolutionise the current von Neumann architecture, advancing machine learning applications. Signal transmission in the brain relies on voltage-gated ion channels, which exhibit the electrical behaviour of memristors, resistors with memory. State-of-the-art technologies currently employ semiconductor-based neuromorphic approaches, which have already demonstrated their efficacy in machine learning systems. However, these approaches still cannot match performance achieved by biological neurons in terms of energy efficiency and size. In this study, we utilise molecular dynamics simulations, continuum models, and electrophysiological experiments to propose and realise a bioinspired hydrophobically gated memristive nanopore. Our findings indicate that hydrophobic gating enables memory through an electrowetting mechanism, and we establish simple design rules accordingly. Through the engineering of a biological nanopore, we successfully replicate the characteristic hysteresis cycles of a memristor \tr{and construct a synaptic device capable of learning and forgetting}. This advancement offers a promising pathway for the realization of nanoscale, cost- and energy-effective, and adaptable bioinspired memristors.

cond-mat.mes-hall↗

arXiv2023

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

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 modulated by stimuli like pressure, temperature, chemicals, and voltage. The artificial replication of the properties of these channels is challenging due to their complex chemistry, limited stability range, and intricate moving parts, allosterically modulated. Nonetheless, we can harness some of their gating mechanisms for nanofluidic and iontronic purposes. This theoretical and computational study explores the use of electrowetting in hydrophobic nanopores to control their conductance using an external applied voltage. We employ restrained molecular dynamics to calculate the free energy required for wetting a model nanopore under different voltages. Utilizing a simple theory, we generate free energy profiles across a wide voltage range. We also computed transition rates between conductive and non-conductive states, showing their voltage dependence and how this behaviour can impair memory to the system, resembling the memristor behaviour voltage-gated channels in the brain. These findings offer a promising avenue for designing and controlling hydrophobic nanopores via electrowetting, enabling potential applications in neuromorphic iontronics.

cond-mat.mes-hall↗

arXiv2023

What keeps nanopores boiling

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 confinement is progressively introduced, starting from classical nucleation theory, passing through nanoscale effects, and terminating to the material and external parameters which affect the boiling conditions. The relevance of boiling in specific nanoconfined systems is discussed, focusing on heterogeneous lyophobic systems, chromatographic columns, and ion channels. The current level of control of boiling in nanopores enabled by microporous materials, as metal organic frameworks, and biological nanopores paves the way to thrilling theoretical challenges and to new technological opportunities in the fields of energy, neuromorphic computing, and sensing.

cond-mat.soft↗

arXiv2023

Structural transformations in Cu, Ag, and Au metal nanoclusters

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 proposed recently [Settem \emph{et al.}, Nanoscale, 2022, 14, 939]. In this method, Harmonic Superposition Approximation (HSA) and Parallel Tempering Molecular Dynamics (PTMD) are combined in a complementary manner. HSA is accurate at low temperatures and fails at higher temperatures. PTMD, on the other hand, effectively samples the high temperature region and melting. This method is used to study the size- and system-dependent competition between various structural motifs of Cu, Ag, and Au nanoclusters in the size range 1 to 2 nm. Results show that there are mainly three types of structural changes in metal nanoclusters depending on whether a solid-solid transformation occurs. In the first type, global minimum is the dominant motif in the entire temperature range. In contrast, when a solid-solid transformation occurs, the global minimum transforms either completely to a different motif or partially resulting in a co-existence of multiple motifs. Finally, nanocluster structures are analyzed to highlight the system-specific differences across the three metals.

cond-mat.mtrl-sci↗

arXiv2023

Charting nanocluster structures via convolutional neural networks

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 dataset of parallel tempering molecular dynamics simulations of gold clusters of 90 and 147 atoms, silver clusters of 147 atoms, and copper clusters of 147 atoms, covering a plethora of structures and temperatures. The method leverages convolutional neural networks to learn the radial distribution functions of the nanoclusters and to distill a low-dimensional chart of the structural landscape. This strategy is found to give rise to a physically meaningful and differentiable mapping of the atom positions to a low-dimensional manifold, in which the main structural motifs are clearly discriminated and meaningfully ordered. Furthermore, unsupervised clustering on the low-dimensional data proved effective at further splitting the motifs into structural subfamilies characterized by very fine and physically relevant differences, such as the presence of specific punctual or planar defects or of atoms with particular coordination features. Owing to these peculiarities, the chart also enabled tracking of the complex structural evolution in a reactive trajectory. In addition to visualization and analysis of complex structural landscapes, the presented approach offers a general, low-dimensional set of differentiable variables which has the potential to be used for exploration and enhanced sampling purposes.

cond-mat.mtrl-sci↗

arXiv2023

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

Understanding intrusion and extrusion in nanoporous materials is a challenging multiscale problem of utmost importance for applications ranging from energy storage and dissipation to water desalination and hydrophobic gating in ion channels. Including atomistic details in simulations is required to predict the overall behavior of such systems, because the statics and dynamics of these processes depend sensitively on microscopic features of the pore such as the surface hydrophobicity, geometry, and charge distribution and on the composition of the liquid. On the other hand, the transitions between the filled (intruded) and empty (extruded) states are rare events which often require long simulation times difficult to achieve with standard atomistic simulations. In this work, we explored the intrusion and extrusion processes by a multiscale approach in which the atomistic details of the system, extracted from molecular dynamics simulations, inform a simple Langevin model of water intrusion/extrusion in the pore. We then used the Langevin simulations to compute the transition times at different pressures, validating our coarse-grained model by comparing it with nonequilibrium molecular dynamics simulations. The proposed approach reproduces experimentally relevant features such as the time and temperature dependence of the intrusion/extrusion cycles, as well as specific details about the shape of the cycle. This approach also drastically increases the timescales that can be simulated allowing to reduce the gap between simulations and experiments and showing promise for more complex systems.

cond-mat.soft↗