arXiv subjects

A. Marco Saitta

Publications and source records attributed to A. Marco Saitta.

At least 19 recordsLinked to original sources

arXiv2026

Negative Thermal Expansion in Cubic Ice: A Collective Quantum Effect of the hydrogen-bond network

We report neutron powder diffraction measurements and path-integral molecular dynamics simulations of stacking-disorder-free cubic ice I$_c$, produced by topotactic degassing of C2 hydrogen hydrate. Across the cryogenic stability range, ice I$_c$ exhibits a density maximum near 70 K, closely matching that of hexagonal ice I$_h$ despite their different long-range stacking sequences. Negative thermal expansion in ice I is therefore not specific to hexagonal stacking, but arises from the shared open tetrahedral hydrogen-bond network. Simulations with the MB-pol potential quantitatively reproduce the experimental anomaly only when nuclear quantum effects are included. The density maximum coincides, within the temperature resolution, with maximal anisotropy of the proton quantum distribution. Neutron-derived displacement parameters independently reveal a strongly enhanced transverse proton displacement, while phonon calculations identify low-frequency transverse modes with the most negative Grüneisen parameters. Together, these results establish the negative thermal expansion of ice I as a collective quantum effect governed by nuclear statistics and the dynamics of the hydrogen-bond network.

cond-mat.mtrl-sci↗

arXiv2026

Pressure-Temperature Phase Diagram and $λ$-Transition in Liquid Sulfur

Using molecular dynamics simulations driven by a machine-learned interatomic potential, we investigate at low to intermediate pressures the $λ$-transition of sulfur, a temperature-induced polymerization. At ambient pressure, we capture the melting of crystalline cyclo-octasulfur into a liquid of molecular rings. Within this liquid, the concentration of non-S$_8$ rings increases with temperature; we show that these molecules act as reactive centers, which eventually trigger polymerization. We reproduce key experimental signatures of the $λ$-transition, including the sharp increase in heat capacity and the pronounced dependence of the transition temperature on the heating rate. Building on this, we reconstruct a phase diagram of polymerization up to intermediate pressures. Our results reveal a moderate decrease of the polymerization temperature with pressure, culminating with its merging with the melting line at a critical point. Beyond this point, we provide direct evidence of polymerization emerging from the crystalline phase. By analyzing temperature-ramp trajectories, we observe the formation of non-S$_8$ rings, open chains, and extended polymeric structures which retain features of the crystalline arrangement; further heating the system leads to disorder taking over through melting. Polymerization is therefore initiated slightly before melting. Altogether, our findings provide a microscopic picture of the $λ$-transition throughout the sulfur phase diagram.

physics.chem-ph↗

arXiv2026

Interfacial Electric Fields in Water Nanodroplets are Weakly Dependent on Curvature and pH

The origin of enhanced reactivity in aqueous microdroplets remains debated, with interfacial electric fields (IEFs) often invoked as catalytic drivers. Here, we provide a quantum-mechanical, spatially resolved characterization of the electric field at air-water interfaces by combining deep-learning molecular dynamics with \emph{ab initio} re-sampling. Across planar interfaces and nanodroplets of varying curvature and charge state, we find an outward-oriented field of $\sim 1.0$--$1.2$ V/Å along the intrinsic surface normal. Crucially, its magnitude scales linearly with the average number of hydrogen bonds per interfacial molecule, directly tying the field to the local hydrogen-bond network. Despite its large magnitude and contrary to common expectations, we find that curvature and pH exert only a minor influence on the IEF, becoming negligible at experimentally relevant droplet sizes and pH. Consequently, the reactivity differences observed in $μ$m-sized droplets cannot be ascribed to variations in the IEF, which changes by a factor of only $\sim10^{-5}$ between $3$ and $40μ$m-sized droplets. Moreover, the IEF is localized inside the interfacial region and rapidly vanishes within a few Å. This strong spatial confinement renders the IEF strongly tied to the local electronic structure, identifying it as a local property of the air-water boundary rather than an independent physical driver of ``on-water'' catalysis.

physics.chem-ph↗

arXiv2026

Overcoming sampling limitations using machine-learned interatomic potentials: the case of water-in-salt electrolytes

Machine-learned interatomic potentials hold the promise to enable the modeling of highly concentrated liquids over meaningful timescales, far from reach for current ab initio electronic structure methods. Here we evaluate the performances of various MACE potentials in modeling a $21 m$ water-in-salt electrolyte based on lithium bis(trifluoromethanesulfonyl)imide. We test out-of-the-box foundation models, as well as both fine tuning and from scratch training strategies. Our simulations demonstrate that surrogate models allow to overcome sampling limitations of ab initio molecular dynamics, reaching an excellent agreement with experimental observables such as the structure factor. We also demonstrate the benefit of fine tuning a foundation model over training from scratch: in terms of data efficiency, but most importantly as a means to provide information regarding configurations hard to sample, such as short Li$^+$--Li$^+$ distances. Finally, we show that depending on the reference exchange-correlation functional, empirical dispersion correction schemes can be detrimental. All in all, our work shows that machine-learned interatomic potentials are a good fit for the modeling of highly concentrated electrolytes over long timescales.

physics.chem-ph↗

arXiv2025

Dual quantum locking: Dynamic coupling of hydrogen and water sublattices in hydrogen filled ice

Hydrogen hydrates (HH) are a unique class of materials composed of hydrogen molecules confined within crystalline water frameworks. Among their multiple phases, the filled ice structures, particularly the cubic C2 phase, exhibit exceptionally strong host-guest interactions due to ultra-short H2-H2O distances and a 1:1 stoichiometry leading to two interpenetrated identical diamond-like sublattices, one comprised of water molecules, the other of hydrogen molecules. At high pressures, nuclear quantum effects involving both hydrogen molecules and the water lattice become dominant, giving rise to a dual-lattice quantum system. In this work, we explore the sequence of pressure- and temperature-driven phase transitions in HH, focusing on the interplay between molecular rotation, orientational ordering, lattice symmetry breaking and hydrogen bond symmetrization. Using a combination of computational modeling based on classical and path-integral molecular dynamics, quantum embedding, and high pressure experiments, including Raman spectroscopy and synchrotron X-ray diffraction at low temperatures and high pressures, we identify signatures of quantum-induced ordering and structural transformations in the C2 phase. Our findings reveal that orientational ordering in HH occurs at much lower pressures than in solid hydrogen, by inducing structural changes in the water network and enhancing the coupling of water and hydrogen dynamics. This work provides new insights into the quantum behavior of hydrogen under extreme mechanochemical confinement and establishes hydrogen-filled ices as a promising platform for the design of hydrogen-rich quantum materials.

cond-mat.mtrl-sci↗

arXiv2025

Free energy profiles for chemical reactions in solution from high-dimensional neural network potentials: The case of the Strecker synthesis

Machine learning potentials (MLPs) have become a popular tool in chemistry and materials science as they combine the accuracy of electronic structure calculations with the high computational efficiency of analytic potentials. MLPs are particularly useful for computationally demanding simulations such as the determination of free energy profiles governing chemical reactions in solution, but to date such applications are still rare. In this work we show how umbrella sampling simulations can be combined with active learning of high-dimensional neural network potentials (HDNNPs) to construct free energy profiles in a systematic way. For the example of the first step of Strecker synthesis of glycine in aqueous solution we provide a detailed analysis of the improving quality of HDNNPs for datasets of increasing size. We find that next to the typical quantification of energy and force errors with respect to the underlying density functional theory data also the long-term stability of the simulations and the convergence of physical properties should be rigorously monitored to obtain reliable and converged free energy profiles of chemical reactions in solution.

physics.chem-ph↗

arXiv2023

Data-driven path collective variables

Identifying optimal collective variables to model transformations, using atomic-scale simulations, is a long-standing challenge. We propose a new method for the generation, optimization, and comparison of collective variables, which can be thought of as a data-driven generalization of the path collective variable concept. It consists in a kernel ridge regression of the committor probability, which encodes a transformation's progress. The resulting collective variable is one-dimensional, interpretable, and differentiable, making it appropriate for enhanced sampling simulations requiring biasing. We demonstrate the validity of the method on two different applications: a precipitation model, and the association of Li$^+$ and F$^-$ in water. For the former, we show that global descriptors such as the permutation invariant vector allow to reach an accuracy far from the one achieved \textit{via} simpler, more intuitive variables. For the latter, we show that information correlated with the transformation mechanism is contained in the first solvation shell only, and that inertial effects prevent the derivation of optimal collective variables from the atomic positions only.

physics.chem-ph↗

arXiv2018

Navigating at Will on the Water Phase Diagram

Despite the simplicity of its molecular unit, water is a challenging system because of its uniquely rich polymorphism and predicted but yet unconfirmed features. Introducing a novel space of generalized coordinates that capture changes in the topology of the interatomic network, we are able to systematically track transitions among liquid, amorphous and crystalline forms throughout the whole phase diagram of water, including the nucleation of crystals above and below the melting point. Our approach, based on molecular dynamics and enhanced sampling / free energy calculation techniques, is not specific to water and could be applied to very different structural phase transitions, paving the way towards the prediction of kinetic routes connecting polymorphic structures in a range of materials.

cond-mat.mtrl-sci↗

arXiv2013

High Energy Density Mixed Polymeric Phase From Carbon Monoxide and Nitrogen

Carbon monoxide and nitrogen are among the potentially interesting high-energy density materials. However, in spite of the physical similarities of the molecules, they behave very differently at high pressures. Using density functional theory and structural prediction methods, we examine the ability of these systems to combine their respective properties and form novel mixed crystalline phases under pressures of up to 100 GPa. Interestingly, we find that CO catalyzes the molecular dissociation of N2, which means mixed structures are favored at a relatively low pressure (below 18 GPa), and that a three-dimensional framework with Pbam symmetry becomes the most stable phase above 52 GPa, i.e., at much milder conditions than in pure solid nitrogen. This structure is dynamically stable at ambient pressure and has an energy density of approximately 2:2 kJ/g, making it a candidate for a high-energy density material, and one that could be achieved at less prohibitive experimental conditions.

cond-mat.mtrl-sci↗

arXiv2012

Ab initio molecular dynamics study of dissociation of water under an electric field

The behavior of liquid water under an electric field is a crucial phenomenon in science and engineering. However, its detailed description at a microscopic level is difficult to achieve experimentally. Here we report on the first ab initio molecular-dynamics study on water under an electric field. We observe that the hydrogen-bond length and the molecular orientation are significantly modified at low-to-moderate field intensities. Fields beyond a threshold of about 0.35 V/Åare able to dissociate molecules and sustain an ionic current via a series of correlated proton jumps. Upon applying even more intense fields (1.0 V/Å), a 15-20% fraction of molecules are instantaneously dissociated and the resulting ionic flow yields a conductance of about 7.8 $Ω^{-1}cm^{-1}$, in good agreement with experimental values. This result paves the way to quantum-accurate microscopic studies of the effect of electric fields on aqueous solutions and, thus, to massive applications of ab initio molecular dynamics in neurobiology, electrochemistry and hydrogen economy.

cond-mat.soft↗

arXiv2010

Structure and stability of graphene nanoribbons in oxygen, carbon dioxide, water, and ammonia

We determine, by means of density functional theory, the stability and the structure of graphene nanoribbon (GNR) edges in presence of molecules such as oxygen, water, ammonia, and carbon dioxide. As in the case of hydrogen-terminated nanoribbons, we find that the most stable armchair and zigzag configurations are characterized by a non-metallic/non-magnetic nature, and are compatible with Clar's sextet rules, well known in organic chemistry. In particular, we predict that, at thermodynamic equilibrium, neutral GNRs in oxygen-rich atmosphere should preferentially be along the armchair direction, while water-saturated GNRs should present zigzag edges. Our results promise to be particularly useful to GNRs synthesis, since the most recent and advanced experimental routes are most effective in water and/or ammonia-containing solutions.

cond-mat.mes-hall↗

arXiv2010

Clar's Theory, STM Images, and Geometry of Graphene Nanoribbons

We show that Clar's theory of the aromatic sextet is a simple and powerful tool to predict the stability, the π-electron distribution, the geometry, the electronic/magnetic structure of graphene nanoribbons with different hydrogen edge terminations. We use density functional theory to obtain the equilibrium atomic positions, simulated scanning tunneling microscopy (STM) images, edge energies, band gaps, and edge-induced strains of graphene ribbons that we analyze in terms of Clar formulas. Based on their Clar representation, we propose a classification scheme for graphene ribbons that groups configurations with similar bond length alternations, STM patterns, and Raman spectra. Our simulations show how STM images and Raman spectra can be used to identify the type of edge termination.

cond-mat.mtrl-sci↗

arXiv2009

Raman spectra of bilayer graphene to probe the electrostatic environment

The Raman shift, broadening, and relative Raman intensities of bilayer graphene are computed as functions of the electron concentration. We include dynamic effects for the phonon frequencies and we consider the gap induced in the band structure of bilayer graphene by an external electric field. We show that from the analysis of the Raman spectra of gated bilayer graphene it is possible to quantitatively identify the amount of charges coming from the atmosphere and from the substrate. These findings suggest that Raman spectroscopy of bilayer graphene can be used to characterize the electrostatic environment of few-layers graphene.

cond-mat.mtrl-sci↗

arXiv2009

Ab-initio study of gap opening and screening effects in gated bilayer graphene

The electronic properties of doped bilayer graphene in presence of bottom and top gates have been studied and characterized by means of Density Functional Theory calculations. Varying independently the bottom and top gates it is possible to control separately the total doping charge on the sample, and the average external electric field acting on the bilayer. We show that, at fixed doping level, the band gap at the K point in the Brillouin zone depends linearly on the average electric field, whereas the corresponding proportionality coefficient has a non-monotonic dependence on doping. We find that the DFT-calculated band gap at K, for small doping levels, is roughly half of the band gap obtained with standard Tight Binding approach. We show that this discrepancy arises from an underestimate, in the TB model, of the screening of the system to the external electric field. In particular, on the basis of our DFT results we observe that, when the bilayer graphene is in presence of an external electric field, both an interlayer and an intralayer screening occur. Only the interlayer screening is included in TB calculations, while both screenings are fundamental for the description of the band gap opening. We finally provide a general scheme to obtain the full band structure of the gated bilayer graphene, for an arbitrary value of the external electric field and of the doping.

cond-mat.mtrl-sci↗

arXiv2008

Structure, Stability, Edge States and Aromaticity of Graphene Ribbons

We determine the stability, the geometry, the electronic and magnetic structure of hydrogen-terminated graphene-nanoribbons edges as a function of the hydrogen content of the environment by means of density functional theory. Antiferromagnetic zigzag ribbons are stable only at extremely-low ultra-vacuum pressures. Under more standard conditions, the most stable structures are the mono- and di-hydrogenated armchair edges and a zigzag edge reconstruction with one di- and two mono-hydrogenated sites. At high hydrogen-concentration ``bulk'' graphene is not stable and spontaneously breaks to form ribbons, in analogy to the spontaneous breaking of graphene into small-width nanoribbons observed experimentally in solution. The stability and the existence of exotic edge electronic-states and/or magnetism is rationalized in terms of simple concepts from organic chemistry (Clar's rule)

cond-mat.mtrl-sci↗

arXiv2008

Giant non-adiabatic effects in layer metals: Raman spectra of intercalated graphite explained

The occurrence of non-adiabatic effects in the vibrational properties of metals have been predicted since the 60's, but hardly confirmed experimentally. We report the first fully \emph{ab initio} calculations of non-adiabatic frequencies of a number of layer and conventional metals. We suggest that non-adiabatic effects can be a feature of the vibrational Raman spectra of any bulk metal, and show that they are spectacularly large (up to 30% of the phonon frequencies) in the case of layer metals, such as superconducting $MgB_2$, $CaC_6$ and other graphite intercalated compounds. We develop a framework capable to estimate the electron momentum-relaxation time of a given system, and thus its degree of non-adiabaticity, in terms of the experimentally observed frequencies and linewidths.

cond-mat.mtrl-sci↗

arXiv2007

Probing the doping in metallic and semiconducting carbon nanotubes by Raman and transport measurements

In-situ Raman experiments together with transport measurements have been carried out on carbon nanotubes as a function of gate voltage. In metallic tubes, a large increase in the Raman frequency of the $G^-$ band, accompanied by a substantial decrease of its line-width, is observed with electron or hole doping. In addition, we see an increase in Raman frequency of the $G^+$ band in semiconducting tubes. These results are quantitatively explained using ab-initio calculations that take into account effects beyond the adiabatic approximation. Our results imply that Raman spectroscopy can be used as an accurate measure of the doping of both metallic and semiconducting nanotubes.

cond-mat.mes-hall↗

arXiv2007

Kohn anomalies and non-adiabaticity in doped carbon nanotubes

The high-frequency Raman-active phonon modes of metallic single-walled carbon nanotubes (SWNTs) are thought to be characterized by Kohn anomalies (KAs), which are expected to be modified by the doping-induced tuning of the Fermi energy level $ε_F$, obtained through the intercalation of SWNTs with alkali atoms or by the application of a gate potential. We present a Density-Functional Theory (DFT) study of the phonon properties of a (9,9) metallic SWNT as a function of electronic doping. For such study, we use, as in standard DFT calculations of vibrational properties, the Born-Oppenheimer (BO) approximation. We also develop an analytical model capable of reproducing and interpreting our DFT results. Both DFT calculations and this model predict, for increasing doping levels, a series of EPC-induced KAs in the vibrational mode parallel to the tube axis at the $\mathbfΓ$ point of the Brillouin zone, usually indicated in Raman spectroscopy as the $G^-$ peak. Such KAs would arise each time a new conduction band is populated. However, we show that they are an artifact of the BO approximation. The inclusion of non-adiabatic (NA) effects dramatically affects the results, predicting KAs at $\mathbfΓ$ only when $ε_F$ is close to a band crossing $E_{X}$. For each band crossing a double KA occurs for $ε_F=E_{X}\pm \hbarω/2$, where $\hbarω$ is the phonon energy. In particular, for a 1.2 $nm$ metallic nanotube, we predict a KA to occur in the so-called $G^-$ peak at a doping level of about $N_{el}/C=\pm 0.0015$ atom ($ε_F\approx \pm 0.1 ~eV$). Furthermore, we predict that the Raman linewidth of the $G^-$ peak significantly decreases for $|ε_F| \geq \hbarω/2$.

cond-mat.soft↗