Polaron pattern recognition
in correlated oxide surfaces

@article{Zhu_2026a,

title = {Emergent ferroelectric order in strained KTaO_{3} by anharmonic and machine learned force fields methods},

author = {Yu Zhu and Luigi Ranalli and Taikang Chen and Wei Ren and Cesare Franchini},

doi = {10.1103/8jph-2w9q},

year  = {2026},

date = {2026-07-06},

journal = {Physical Review Materials},

volume = {10},

pages = {074403},

abstract = {Ferroelectric materials are a class of dielectrics that exhibit spontaneous polarization which can be reversed under an external electric field. The emergence of ferroelectric order in incipient ferroelectrics is a topic of considerable interest from both fundamental and applied perspectives. Despite evidence from first-principles calculations that strain triggers ferroelectricity in KTaO_{3}, conventional methods cannot reliably characterize the soft-mode dynamics that govern its ferroelectric behavior. In this study, we investigate the impact of in-plane uniaxial and biaxial strain, ranging from 0 to 1%, on pristine KTaO_{3} to explore its potential for ferroelectricity induction via inversion symmetry breaking. By integrating density-functional theory calculations with the stochastic self-consistent harmonic approximation assisted by on-the-fly machine learned force fields, we obtain accurate structural information and dynamical properties under varying strain conditions while incorporating higher-order anharmonic effects. Employing the Berry-phase method, we obtained the ferroelectric polarization of the strained structures over the entire temperature range up to 300 K. Our findings provide valuable insights into the role of strain in stabilizing ferroelectricity in KTaO_{3}, offering guidance for future experimental and theoretical studies on strain-engineered ferroelectric materials.},

keywords = {P07},

pubstate = {published},

tppubtype = {article}

}

@article{Corrias_2026a,

title = {Total Variation-Based Image Decomposition and Denoising for Microscopy Images},

author = {Marco Corrias and Giada Franceschi and Michele Riva and Alberto Tampieri and Karin Föttinger and Ulrike Diebold and Thomas Pock and Cesare Franchini},

doi = {10.1093/mam/ozag031},

year  = {2026},

date = {2026-05-12},

urldate = {2026-05-12},

journal = {Microscopy and Microanalysis},

volume = {32},

issue = {3},

pages = {ozag031},

abstract = {Experimentally acquired microscopy images are unavoidably affected by the presence of noise and other unwanted signals, which degrade their quality and might hide relevant features. With the recent increase in image acquisition rate, modern denoising and restoration solutions become necessary. This study focuses on image decomposition and denoising of microscopy images through a workflow based on total variation (TV), addressing images obtained from various microscopy techniques, including atomic force microscopy (AFM), scanning tunneling microscopy (STM), and scanning electron microscopy (SEM). Our approach consists in restoring an image by extracting its unwanted signal components and subtracting them from the raw one, or by denoising it. We evaluate the performance of TV-\textit{L}^{1}⁠, Huber-ROF, and TGV-\textit{L}^{1} in achieving this goal in distinct study cases. Huber-ROF proved to be the most flexible one, while TGV-\textit{L}^{1} is the most suitable for denoising. Our results suggest a wider applicability of this method in microscopy, restricted not only to STM, AFM, and SEM images. The Python code used for this study is publicly available as part of AiSurf. It is designed to be integrated into experimental workflows for image acquisition or can be used to denoise previously acquired images.},

keywords = {P02, P07, P10},

pubstate = {published},

tppubtype = {article}

}

@article{Celiberti_2026a,

title = {Machine Learning the order-disorder Jahn-Teller transition in LaMnO_{3}},

author = {Lorenzo Celiberti and Alexander Ehrentraut and Luca Leoni and Cesare Franchini},

doi = {10.1063/5.0328174},

year  = {2026},

date = {2026-05-04},

urldate = {2026-04-09},

journal = {The Journal of Chemical Physics},

volume = {164},

pages = {174703},

abstract = {We investigate the Jahn-Teller structural phase transition in LaMnO_{3} at \emph{T_{JT}=~750} K using molecular dynamics simulations based on machine-learning force fields trained on ab initio data. Analysis of the site-site correlation function of the distortions reveals that the transition is driven by the ordering of the \emph{Q_{2}} Jahn-Teller distortion of the MnO_{6} octahedra, which acts as the order parameter and establishes the order-disorder nature of the transition. Dynamical local distortions are found to persist above \emph{T_{JT}}. Our results reproduce the experimental temperature dependence of both structural and phonon properties and highlight the presence of anharmonic effects at finite temperature. More broadly, the combined use of machine-learning molecular dynamics and velocity autocorrelation function analysis provides a robust framework for uncovering the microscopic mechanisms of structural phase transitions in correlated materials. In particular, this approach enables a clear distinction between order-disorder transitions and alternative mechanisms, such as displacive behavior, through the temperature evolution of vibrational properties.},

note = {Festschrift in honor of Christoph Dellago},

keywords = {P07},

pubstate = {published},

tppubtype = {article}

}

@article{Wang_2026a,

title = {Hydrogen Activation via Dihydride Formation on a Rh_{1}/Fe_{3}O_{4}(001) Single-Atom Catalyst},

author = {Chunlei Wang and Panukorn Sombut and Lena Puntscher and Nail Barama and Maosheng Hao and Florian Kraushofer and Jiri Pavelec and Matthias Meier and Florian Libisch and Michael Schmid and Ulrike Diebold and Cesare Franchini and Gareth S. Parkinson},

doi = {10.1002/anie.202525745},

year  = {2026},

date = {2026-02-18},

urldate = {2026-02-18},

journal = {Angewandte Chemie International Edition},

pages = {e25745},

abstract = {Hydrogen activation is a key elementary step in catalytic hydrogenation. In heterogeneous catalysis, it usually proceeds through dissociative adsorption on metal nanoparticles followed by surface diffusion or spillover, whereas homogeneous catalysts activate H_{2} through dihydride or dihydrogen intermediates at a single metal center. Here, we show that isolated Rh adatoms supported on Fe_{3}O_{4}(001) activate hydrogen through formation of a stable dihydride species without atomic H spillover. Temperature-programmed desorption, x-ray photoelectron spectroscopy, and scanning tunneling microscopy collectively reveal strong (≈1 eV) hydrogen adsorption exclusively at isolated Rh_{1} sites, while isotope-exchange experiments further demonstrate that hydrogen remains localized. Density-functional theory-based calculations indicate a barrierless conversion from molecular H_{2} to the dihydride, and random-phase approximation calculations further confirm the relative stability of the dihydride. Together, these results show that single-atom Rh sites cleave hydrogen through a dihydride pathway analogous to homogeneous complexes, establishing a mechanistic bridge between homogeneous and heterogeneous catalysis.},

keywords = {P02, P04, P07},

pubstate = {published},

tppubtype = {article}

}

@article{Eder_2025a,

title = {Multi-technique characterization of rhodium gem-dicarbonyls on TiO_{2}(110)},

author = {Moritz Eder and Faith J. Lewis and Johanna I. Hütner and Panukorn Sombut and Maosheng Hao and David Rath and Paul Ryan and Jan Balajka and Margareta Wagner and Matthias Meier and Cesare Franchini and Gianfranco Pacchioni and Ulrike Diebold and Michael Schmid and Florian Libisch and Jiři Pavelec and Gareth S. Parkinson},

doi = {10.1039/D5SC04889C},

year  = {2025},

date = {2025-10-16},

journal = {Chemical Science},

abstract = {Gem-dicarbonyls of transition metals supported on metal (oxide) surfaces are common intermediates in heterogeneous catalysis. While infrared (IR) spectroscopy is a standard tool for detecting these species on powder catalysts, the ill-defined crystallographic environment renders data interpretation challenging. In this work, we apply a multi-technique surface science approach to investigate rhodium gem-dicarbonyls on a single-crystalline rutile TiO_{2}(110) surface. We combine spectroscopy, scanning probe microscopy, and density functional theory (DFT) to determine their location and coordination on the surface. IR spectroscopy shows the successful creation of gem-dicarbonyls on a titania single crystal by exposing deposited Rh atoms to CO gas, followed by annealing to 200–250 K. Low-temperature scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM) data reveal that these complexes are mostly aligned along the [001] crystallographic direction, corroborating theoretical predictions. Notably, X-ray photoelectron spectroscopy (XPS) data reveal multiple rhodium species on the surface, even when the IR spectra show only the signature of rhodium gem-dicarbonyls. As such, our results highlight the complex behavior of carbonyls on metal oxide surfaces, and demonstrate the necessity of multi-technique approaches for the adequate characterization of single-atom catalysts.},

keywords = {P02, P04, P07},

pubstate = {published},

tppubtype = {article}

}

@article{Joseph_2025a,

title = {Coupling between small polarons and ferroelectricity in BaTiO_{3}},

author = {Darin Joseph and Cesare Franchini},

doi = {10.1103/5z43-rm34},

year  = {2025},

date = {2025-09-30},

urldate = {2025-09-30},

journal = {Physical Review Materials},

volume = {9},

pages = {094415},

abstract = {In this study, we investigate the formation of electron and hole small polarons in the prototypical ferroelectric material BaTiO_{3}, with a focus on their interaction with ferroelectric distortive fields. To accurately describe the ferroelectric phase in electronically correlated BaTiO_{3}, we employ the HSE06 hybrid density functional, which addresses the limitations of conventional density-functional theory (DFT) and Hubbard-corrected DFT+U models, providing a more precise depiction of both ferroelectric and polaronic behaviors. Our analysis spans three structural phases of BaTiO_{3}: cubic, tetragonal, and rhombohedral. We uncover a unique phase-dependent trend in electron-polaron stability, which progressively increases across the structural phases, peaking in the rhombohedral phase due to the constructive coupling between the polaron and ferroelectric phonon fields. In contrast, hole polarons exhibit a stability pattern largely unaffected by the phase transitions. Furthermore, we observe that polaron self-trapping significantly alters the local ferroelectric distortive pattern, which propagates to neighboring sites but has a minimal effect on the long-range macroscopic spontaneous polarization. Charge trapping is also associated with localized spin formation, opening new possibilities for enhanced functionalities in multiferroic materials.},

keywords = {P07},

pubstate = {published},

tppubtype = {article}

}

@article{Franchini_2025a,

title = {Spin Matters: A Multidisciplinary Roadmap to Understanding Spin Effects in Oxygen Evolution Reaction During Water Electrolysis},

author = {Emma van der Minne and Priscila Vensaus and Vadim Ratovskii and Seenivasan Hariharan and Jan Behrends and Cesare Franchini and Jonas Fransson and Sarnjeet S. Dhesi and Felix Gunkel and Florian Gossing and Georgios Katsoukis and Ulrike I. Kramm and Magalí Lingenfelde and Qianqian Lan and Yury V. Kolen’ko and Yang Li and Ramsundar Rani Mohan and Jeffrey McCord and Lingmei Ni and Eva Pavarini and Rossitza Pentcheva and David H. Waldeck and Michael Verhage and Anke Yu and Zhichuan J. Xu and Piero Torelli and Silvia Mauri and Narcis Avarvari and Anja Bieberle-Hütter and Christoph Baeumer},

doi = {10.1002/aenm.202503556},

year  = {2025},

date = {2025-09-01},

journal = {Advanced Energy Materials},

pages = {e03556},

abstract = {A central challenge in water electrolysis lies with the oxygen evolution reaction (OER) where the formation of molecular oxygen (O_{2}) is hindered by the constraint of angular momentum conservation. While the reactants OH^{-} or H_{2}O are diamagnetic (DM), the O_{2} product has a paramagnetic (PM) triplet ground state, requiring a change in spin configuration when being formed. This constraint has prompted interest in spin-selective catalysts as a means to facilitate OER. In this context, the roles of magnetism and chirality-induced spin selectivity (CISS) in promoting the OER reaction have recently been investigated through both theoretical and experimental studies. However, pinpointing the key principles and their relative contribution in mediating spin-enhancement remains a significant challenge. This roadmap offers a forward-looking perspective on current experimental trends and theoretical developments in spin-enhanced OER electrocatalysis and outlines strategic directions for integrating incisive experiments and operando approaches with computational modeling to disentangle key mechanisms. By providing a conceptual framework and identifying critical knowledge gaps, this perspective aims to guide researchers toward dedicated experimental and computational studies that will deepen the understanding of spin-induced OER enhancement and accelerate the development of next-generation catalysts.},

keywords = {P07},

pubstate = {published},

tppubtype = {article}

}

@article{Kender_2025a,

title = {Automatic Determination of Quasicrystalline Patterns from Microscopy Images},

author = {Tano Kim Kender and Marco Corrias and Cesare Franchini},

doi = {10.1002/aidi.202500043},

year  = {2025},

date = {2025-07-09},

journal = {Advanced Intelligent Discovery},

pages = {202500043},

abstract = {Quasicrystals are aperiodically ordered solids that exhibit long-range order without translational periodicity, bridging the gap between crystalline and amorphous materials. Due to their lack of translational periodicity, information on atomic arrangements in quasicrystals cannot be extracted by current crystalline lattice recognition softwares. This work introduces a method to automatically detect quasicrystalline atomic arrangements and tiling using image feature recognition coupled with machine learning, tailored toward quasiperiodic tilings with 8-, 10-, and 12-fold rotational symmetry. Atom positions are identified using clustering of feature descriptors. Subsequent nearest-neighbor analysis and border following on the interatomic connections deliver the tiling. Support vector machines further increase the quality of the results, reaching an accuracy consistent with those reported in the literature. A statistical analysis of the results is performed. The code is now part of the open-source package AiSurf.},

keywords = {P07},

pubstate = {published},

tppubtype = {article}

}

@article{Birschitzky_2024b,

title = {Machine Learning Small Polaron Dynamics},

author = {Viktor C. Birschitzky and Luca Leoni and Michele Reticcioli and Cesare Franchini},

url = {https://doi.org/10.1103/PhysRevLett.134.216301},

year  = {2025},

date = {2025-05-27},

urldate = {2024-09-24},

journal = {Physical Review Letters},

volume = {134},

issue = {21},

pages = {216301},

abstract = {Polarons are crucial for charge transport in semiconductors, significantly impacting material properties and device performance. The dynamics of small polarons can be investigated using first-principles molecular dynamics. However, the limited timescale of these simulations presents a challenge for adequately sampling infrequent polaron hopping events. Here, we introduce a message-passing neural network combined with first-principles molecular dynamics within the Born-Oppenheimer approximation that learns the polaronic potential energy surface by encoding the polaronic state, allowing for simulations of polaron hopping dynamics at the nanosecond scale. By leveraging the statistical significance of the long timescale, our framework can accurately estimate polaron (anisotropic) mobilities and activation barriers in prototypical polaronic oxides across different scenarios (hole polarons in rocksalt MgO and electron polarons in pristine and F-doped rutile TiO_{2}) within experimentally measured ranges.},

keywords = {P07},

pubstate = {published},

tppubtype = {article}

}

@article{Cao_2025a,

title = {Quantum Delocalization Enables Water Dissociation on Ru(0001)},

author = {Yu Cao and Jiantao Wang and Mingfeng Liu and Yan Liu and Hui Ma and Cesare Franchini and Yan Sun and Georg Kresse and Xing-Qiu Chen and Peitao Liu},

doi = {10.1103/PhysRevLett.134.178001},

year  = {2025},

date = {2025-04-30},

journal = {Physical Review Letters},

volume = {134},

issue = {17},

pages = {178001},

abstract = {We revisit the long-standing question of whether water molecules dissociate on the Ru(0001) surface through nanosecond-scale path-integral molecular dynamics simulations on a sizable supercell. This is made possible through the development of an efficient and reliable machine-learning potential with near first-principles accuracy, overcoming the limitations of previous ab initio studies. We show that the quantum delocalization associated with nuclear quantum effects enables rapid and frequent proton transfers between water molecules, thereby facilitating the water dissociation on Ru(0001). This work provides the direct theoretical evidence of water dissociation on Ru(0001), resolving the enduring issue in surface sciences and offering crucial atomistic insights into water-metal interfaces.},

keywords = {P03, P07},

pubstate = {published},

tppubtype = {article}

}