arXiv subjects

Antonio Rossi

Publications and source records attributed to Antonio Rossi.

At least 19 recordsLinked to original sources

arXiv2026

Direct observation of flat bands in near-magic-angle twisted bilayer CVD graphene

Advances in chemical vapor deposition (CVD) growth have driven graphene crystal quality to unprecedented levels, yet it is still unknown whether this route can realize the fragile flat-band and correlated states of the magic-angle (MA) twisted bilayer graphene (TBG). Here, we report on the experimental observation by room-temperature nano-angle-resolved photoemission spectroscopy (nano-ARPES) of flat bands in a TBG sample close to the MA, assembled via a grow-and-stack protocol based on low-pressure CVD of graphene on copper. Our study indicates electronic bands fully comparable to those measured in exfoliation-based samples and determines the size of the largest near-MA domain to be compatible with electronic transport experiments, motivating further experiments on flat band physics in CVD-graphene.

cond-mat.mes-hall↗

arXiv2026

Lifshitz transitions and isospin polarization in twist-decoupled monolayer-bilayer graphene

Bernal-stacked bilayer graphene (BLG) hosts correlated electronic phases tied to low-energy Lifshitz transitions at saddle points in its valence band. To access this regime, ultralow charge disorder and control over a vertical electric field are simultaneously required. Here, we employ a twist-decoupled monolayer (MLG) to bias a proximal BLG in the absence of an external displacement field (D). We thereby reveal three-fold degenerate quantum Hall states at D = 0, with multiple transitions driven by doping, magnetic and electric field. Spontaneous broken symmetry in the vicinity of the valence band edge is signaled by the emergence of quantum oscillations with anomalous frequencies and large quasiparticle mass. These results indicate that electronic interactions in BLG are preserved in presence of an atomically close MLG, while showcasing the potential of CVD-grown graphene multilayers for the exploration of correlated phases of matter.

cond-mat.mes-hall↗

arXiv2026

Nickel intercalation in epitaxial graphene on SiC(0001): a novel platform for engineering two-dimensional heterostructures

Two-dimensional (2D) magnetic materials integrated with graphene offer a compelling platform for next-generation spintronic devices, yet nickel in its 2D form remains largely unexplored, due to fundamental synthesis limitations. Here, we report the controlled intercalation of Ni beneath epitaxial graphene on the Si-face of SiC(0001), achieved through a scalable colloidal nanoparticle deposition route. Chemically synthesized Ni nanoparticles (~10 nm diameter) are uniformly deposited onto graphene via immersion in colloidal solution at room temperature; subsequent thermal annealing at 650 °C drives intercalation, yielding well-ordered Ni islands at the graphene/buffer-layer interface with morphology dictated by annealing conditions. Scanning tunneling microscopy (STM) and angle-resolved photoemission spectroscopy (ARPES), supported by density functional theory (DFT) calculations, elucidate the atomic and electronic structure of the intercalated layers. DFT simulations further confirm the thermodynamic stability of the 2D nanostructures as a function of shape and lateral size, predicting a robust average magnetic moment of 0.9 $μ_B$ per atom. The resulting Ni-intercalated graphene on SiC constitutes a well-defined 2D heterostructure combining preserved graphene band structure with robust interfacial magnetism, stable under ambient conditions. These findings establish a reproducible, scalable pathway to engineer magnetic graphene-based heterostructures and open new avenues for their integration into spintronic architectures.

cond-mat.mtrl-sci↗

arXiv2026

SpectraFormer: an Attention-Based Raman Unmixing Tool for Accessing the Graphene Buffer-Layer Signature on SiC

Raman spectroscopy is a key tool for graphene characterization, yet its application to graphene grown on silicon carbide (SiC) is strongly limited by the intense and variable second-order Raman response of the substrate. This limitation is critical for buffer layer graphene, a semiconducting interfacial phase, whose vibrational signatures are overlapped with the SiC background and challenging to be reliably accessed using conventional reference-based subtraction, due to strong spatial and experimental variability of the substrate signal. Here we present SpectraFormer, a transformer-based deep learning model that reconstructs the SiC Raman substrate contribution directly from post-growth partially masked spectroscopic data without relying on explicit reference measurements. By learning global correlations across the entire Raman shift range, the model captures the statistical structure of the SiC background and enables accurate reconstruction of its contribution in mixed spectra. Subtraction of the reconstructed substrate signal reveals weak vibrational features associated with ZLG that are inaccessible through conventional analysis methods. The extracted spectra are validated by ab initio vibrational calculations, allowing assignment of the resolved features to specific modes and confirming their physical consistency. By leveraging a state-of-the-art attention-based deep learning architecture, this approach establishes a robust, reference-free framework for Raman analysis of graphene on SiC and provides a foundation, compatible with real-time data acquisition, to its integration into automated, closed-loop AI-assisted growth optimization.

cond-mat.mtrl-sci↗

arXiv2025

Phason-driven temperature-dependent transport in moiré graphene

The electronic and vibrational properties of 2D materials are dramatically altered by the formation of a moiré superlattice. The lowest-energy phonon modes of the superlattice are two acoustic branches (called phasons) that describe the sliding motion of one layer with respect to the other. Considering their low-energy dispersion and damping, these modes may act as a significant source of scattering for electrons in moiré materials. Here, we investigate temperature-dependent electrical transport in minimally twisted bilayer graphene, a moiré system developing multiple weakly-dispersive electronic bands and a reconstructed lattice structure. We measure a linear-in-temperature resistivity across the band manyfold above $T\sim{10}$ K, preceded by a quadratic temperature dependence. While the linear-in-temperature resistivity is up to two orders of magnitude larger than in monolayer graphene, it is reduced (approximately by a factor of three) with respect to magic-angle twisted bilayer graphene. Moreover, it is modulated by the recursive band filling, with minima located close to the full filling of each band. Comparing our results with a semiclassical transport calculation, we show that the experimental trends are compatible with scattering processes mediated by longitudinal phasons, which dominate the resistivity over the contribution from conventional acoustic phonons of the monolayer. Our findings highlight the close relation between vibrational modes unique to moiré materials and carrier transport therein.

cond-mat.mes-hall↗

arXiv2025

Vortex Pinning in Niobium covered by a thin polycrystalline Gold

Owing to its superconducting properties, Niobium (Nb) is an excellent candidate material for superconducting electronics and applications in quantum technology. Here we perform scanning tunneling microscopy and spectroscopy experiments on Nb films covered by a thin gold (Au) film. We investigate the minigap structure of the proximitized region and provide evidence for a highly transparent interface between Nb and Au, beneficial for device applications. Imaging of Abrikosov vortices in presence of a perpendicular magnetic field is reported. The data show vortex pinning by the granular structure of the polycrystalline Au film. Our results show robust and homogeneous superconducting properties of thin Nb film in the presence of a gold capping layer. The Au film not only protects the Nb from surface oxidation but also preserves its excellent superconducting properties.

cond-mat.supr-con↗

arXiv2025

Graphene-driven correlated electronic states in one dimensional defects within WS$_2$

Tomonaga-Luttinger liquid (TLL) behavior in one-dimensional systems has been predicted and shown to occur at semiconductor-to-metal transitions within two-dimensional materials. Reports of one-dimensional defects hosting a Fermi liquid or a TLL have suggested a dependence on the underlying substrate, however, unveiling the physical details of electronic contributions from the substrate require cross-correlative investigation. Here, we study TLL formation within defectively engineered WS$_2$ atop graphene, where band structure and the atomic environment is visualized with nano angle-resolved photoelectron spectroscopy, scanning tunneling microscopy and spectroscopy, and non-contact atomic force microscopy. Correlations between the local density of states and electronic band dispersion elucidated the electron transfer from graphene into a TLL hosted by one-dimensional metal (1DM) defects. It appears that the vertical heterostructure with graphene and the induced charge transfer from graphene into the 1DM is critical for the formation of a TLL.

cond-mat.mtrl-sci↗

arXiv2025

Novel structures of Gallenene intercalated in epitaxial Graphene

The creation of atomically thin layers of non-exfoliable materials remains a crucial challenge, requiring the development of innovative techniques. Here, confinement epitaxy is exploited to realize two-dimensional gallium via intercalation in epitaxial graphene grown on silicon carbide. Novel superstructures arising from the interaction of gallenene (a monolayer of gallium) with graphene and the silicon carbide substrate are investigated. The coexistence of different gallenene phases, including b010-gallenene and the elusive high-pressure Ga(III) phase, is identified. This work sheds new light on the formation of two-dimensional gallium and provides a platform for investigating the exotic electronic and optical properties of confined gallenene.

cond-mat.mtrl-sci↗

arXiv2025

Intercalated structures formed by platinum on epitaxial graphene on SiC(0001)

Graphene on SiC intercalated with two-dimensional metal layers, such as Pt, offers a versatile platform for applications in spintronics, catalysis, and beyond. Recent studies have demonstrated that Pt atoms can intercalate at the heterointerface between SiC(0001) and the C-rich $(6\sqrt{3}\times6\sqrt{3})$R30° reconstructed surface (hereafter referred as the buffer layer). However, key aspects such as intercalated phase structure and intercalation mechanisms remain unclear. In this work, we investigate changes in morphology, chemistry, and electronic structure for both buffer layer and monolayer graphene grown on SiC(0001) following Pt deposition and annealing cycles, which eventually led to Pt intercalation at temperatures above 500°C. Atomic-resolution imaging of the buffer layer reveals a single intercalated Pt layer that removes the periodic corrugation of the buffer layer, arising from partial bonding of C-atoms with Si-atoms of the substrate. In monolayer graphene, the Pt-intercalated regions exhibit a two-level structure: the first level corresponds to a Pt layer intercalated below the buffer layer, while the second level contains a second Pt layer, giving rise to a $(12\times12)$ superstructure relative to graphene. Upon intercalation, Pt atoms appear as silicides, indicating a reaction with Si atoms from the substrate. Additionally, charge neutral $π$-bands corresponding to quasi-free-standing monolayer and bilayer graphene emerge. Analysis of multiple samples, coupled with a temperature-dependent study of the intercalation rate, demonstrates the pivotal role of buffer layer regions in facilitating the Pt intercalation in monolayer graphene. These findings provide valuable insight into Pt intercalation, advancing the potential for applications.

cond-mat.mtrl-sci↗

arXiv2025

Rubidium intercalation in epitaxial monolayer graphene

Alkali metal intercalation of graphene layers has been of particular interest due to potential applications in electronics, energy storage, and catalysis. Rubidium (Rb) is one of the largest alkali metals and the one less investigated as intercalant. Here, we report a systematic investigation, with a multi-technique approach, of the phase formation of Rb under epitaxial monolayer graphene on SiC(0001). We explore a wide phase space with two control parameters: the Rb density (i.e., deposition time) and sample temperature (i.e., room- and low-temperature). We reveal the emergence of $(2 \times 2)$ and $(\sqrt{3} \times \sqrt{3})$R30° structures formed by a single alkali metal layer intercalated between monolayer graphene and the interfacial C-rich reconstructed surface, also known as buffer layer. Rb intercalation also results in a strong n-type doping of the graphene layer. Progressively annealing to high temperatures, we first reveal diffusion of Rb atoms which results in the enlargement of intercalated areas. As desorption sets in, intercalated regions progressively shrink and fragment. Eventually, at approximately 600°C the initial surface is retrieved, indicating the reversibility of the intercalation process.

cond-mat.mtrl-sci↗

arXiv2024

Built-in Bernal gap in large-angle-twisted monolayer-bilayer graphene

Atomically thin materials offer multiple opportunities for layer-by-layer control of their electronic properties. While monolayer graphene (MLG) is a zero-gap system, Bernal-stacked bilayer graphene (BLG) acquires a finite band gap when the symmetry between the layers' potential energy is broken, usually, via a displacement electric field applied in double-gate devices. Here, we introduce a twistronic stack comprising both MLG and BLG, synthesized via chemical vapor deposition, showing a Bernal gap in the absence of external fields. Although a large ($\sim30^{\circ}$) twist angle decouples the MLG and BLG electronic bands near Fermi level, proximity-induced energy shifts in the outermost layers result in a built-in asymmetry, which requires a displacement field of $0.14$ V/nm to be compensated. The latter corresponds to a $\sim10$ meV intrinsic BLG gap, a value confirmed by our thermal-activation measurements. The present results highlight the role of structural asymmetry and encapsulating environment, expanding the engineering toolbox for monolithically-grown graphene multilayers.

cond-mat.mes-hall↗

arXiv2024

A substitutional quantum defect in WS$_2$ discovered by high-throughput computational screening and fabricated by site-selective STM manipulation

Point defects in two-dimensional materials are of key interest for quantum information science. However, the space of possible defects is immense, making the identification of high-performance quantum defects extremely challenging. Here, we perform high-throughput (HT) first-principles computational screening to search for promising quantum defects within WS$_2$, which present localized levels in the band gap that can lead to bright optical transitions in the visible or telecom regime. Our computed database spans more than 700 charged defects formed through substitution on the tungsten or sulfur site. We found that sulfur substitutions enable the most promising quantum defects. We computationally identify the neutral cobalt substitution to sulfur (Co$_{\rm S}^{0}$) as very promising and fabricate it with scanning tunneling microscopy (STM). The Co$_{\rm S}^{0}$ electronic structure measured by STM agrees with first principles and showcases an attractive new quantum defect. Our work shows how HT computational screening and novel defect synthesis routes can be combined to design new quantum defects.

cond-mat.mtrl-sci↗

arXiv2024

Adaptive AI-Driven Material Synthesis: Towards Autonomous 2D Materials Growth

Two-dimensional (2D) materials are poised to revolutionize current solid-state technology with their extraordinary properties. Yet, the primary challenge remains their scalable production. While there have been significant advancements, much of the scientific progress has depended on the exfoliation of materials, a method that poses severe challenges for large-scale applications. With the advent of artificial intelligence (AI) in materials science, innovative synthesis methodologies are now on the horizon. This study explores the forefront of autonomous materials synthesis using an artificial neural network (ANN) trained by evolutionary methods, focusing on the efficient production of graphene. Our approach demonstrates that a neural network can iteratively and autonomously learn a time-dependent protocol for the efficient growth of graphene, without requiring pretraining on what constitutes an effective recipe. Evaluation criteria are based on the proximity of the Raman signature to that of monolayer graphene: higher scores are granted to outcomes whose spectrum more closely resembles that of an ideal continuous monolayer structure. This feedback mechanism allows for iterative refinement of the ANN's time-dependent synthesis protocols, progressively improving sample quality. Through the advancement and application of AI methodologies, this work makes a substantial contribution to the field of materials engineering, fostering a new era of innovation and efficiency in the synthesis process.

cond-mat.mes-hall↗

arXiv2024

Rapid synthesis of uniformly small nickel nanoparticles for the surface functionalization of epitaxial graphene

Nickel nanoparticles (Ni NPs), thanks to their peculiar properties, are interesting materials for many applications including catalysis, hydrogen storage, and sensors. In this work, Ni NPs are synthesized in aqueous solution by a simple and rapid procedure with cetyltrimethylammonium bromide (CTAB) as a capping agent, and are extensively characterized by dynamic light scattering (DLS), scanning electron microscopy (SEM), and atomic force microscopy (AFM). We investigated their shape, dimension, and their distribution on the surfaces of SiO2 and epitaxial graphene (EG) samples. Ni NPs have an average diameter of ~11 nm, with a narrow size dispersion, and their arrangement on the surface is strongly dependent on the substrate. EG samples functionalized with Ni NPs are further characterized by X-ray photoelectron spectroscopy (XPS), as made and after thermal annealing above 350°C to confirm the degradation of CTAB and the presence of metallic Ni(0). Moreover, high resolution scanning tunneling microscopy (STM) topographies reveal the structural stability of the NPs up to 550 °C.

cond-mat.mtrl-sci↗

arXiv2023

Platinum-Decorated Graphene: Experimental Insight into Growth Mechanisms and Hydrogen Adsorption Properties

The potential of graphene for hydrogen storage, coupled with the established role of Platinum as a catalyst for the hydrogen evolution reaction and the spillover effect, makes Pt-functionalized graphene a promising candidate for near-ambient hydrogen storage. This paper focuses on examining the process of Pt cluster formation on epitaxial graphene and assesses the suitability of the system as hydrogen storage material. Scanning tunneling microscopy unveils two primary pathways for Pt cluster growth. In the initial phase, up to ~1 ML of Pt coverage, Pt tends to randomly disperse and cover the graphene surface, while the cluster height remains essentially unchanged. Beyond a coverage of 3 ML, the nucleation of new layers on existing clusters becomes predominant. Then, the clusters mainly grow in height. Thermal desorption spectroscopy on hydrogenated Pt-decorated graphene reveals the presence of multiple hydrogen adsorption mechanisms, manifested as two Gaussian peaks superimposed on a linearly increasing background. We attribute the first peak at 150°C to hydrogen physisorbed on the surface of Pt clusters. The second peak at 430°C is attributed to chemisorption of hydrogen on the surface of the clusters, while the linearly increasing background is assigned to hydrogen bonded in the bulk of the Pt clusters. These measurements demonstrate the ability of Pt-functionalized graphene to store molecular hydrogen at temperatures that are high enough for stable hydrogen binding at room temperature.

cond-mat.mtrl-sci↗

arXiv2023

Direct visualization of the charge transfer in Graphene/$α$-RuCl$_3$ heterostructure

We investigate the electronic properties of a graphene and $α$-ruthenium trichloride (hereafter RuCl$_3$) heterostructure, using a combination of experimental and theoretical techniques. RuCl$_3$ is a Mott insulator and a Kitaev material, and its combination with graphene has gained increasing attention due to its potential applicability in novel electronic and optoelectronic devices. By using a combination of spatially resolved photoemission spectroscopy, low energy electron microscopy, and density functional theory (DFT) calculations we are able to provide a first direct visualization of the massive charge transfer from graphene to RuCl$_3$, which can modify the electronic properties of both materials, leading to novel electronic phenomena at their interface. The electronic band structure is compared to DFT calculations that confirm the occurrence of a Mott transition for RuCl$_3$. Finally, a measurement of spatially resolved work function allows for a direct estimate of the interface dipole between graphene and RuCl$_3$. The strong coupling between graphene and RuCl$_3$ could lead to new ways of manipulating electronic properties of two-dimensional lateral heterojunction. Understanding the electronic properties of this structure is pivotal for designing next generation low-power opto-electronics devices.

cond-mat.mtrl-sci↗

arXiv2023

Phason-mediated interlayer exciton diffusion in WS2/WSe2 moiré heterostructure

Moiré potentials in two-dimensional materials have been proven to be of fundamental importance to fully understand the electronic structure of van der Waals heterostructures, from superconductivity to correlated excitonic states. However, understanding how the moiré phonons, so-called phasons, affect the properties of the system still remains an uncharted territory. In this work, we demonstrate how phasons are integral to properly describing and understanding low-temperature interlayer exciton diffusion in WS2/WSe2 heterostructure. We perform photoluminescence (PL) spectroscopy to understand how the coupling between the layers, affected by their relative orientation, impacts the excitonic properties of the system. Samples fabricated with stacking angles of 0° and 60° are investigated taking into account the stacking angle dependence of the two common moiré potential profiles. Additionally, we present spatially and time-resolved exciton diffusion measurements, looking at the photoluminescence emission in a temperature range from 30 K to 250 K. An accurate potential for the two configurations are computed via density functional theory (DFT) calculations. Finally, we perform molecular dynamics simulation in order to visualize the phasons motion, estimating the phason speed at different temperatures, providing novel insights into the mechanics of exciton propagation at low temperatures that cannot be explained within the frame of classical exciton diffusion alone.

cond-mat.mtrl-sci↗

arXiv2022

Autonomous Investigations over WS$_2$ and Au{111} with Scanning Probe Microscopy

Individual atomic defects in 2D materials impact their macroscopic functionality. Correlating the interplay is challenging, however, intelligent hyperspectral scanning tunneling spectroscopy (STS) mapping provides a feasible solution to this technically difficult and time consuming problem. Here, dense spectroscopic volume is collected autonomously via Gaussian process regression, where convolutional neural networks are used in tandem for spectral identification. Acquired data enable defect segmentation, and a workflow is provided for machine-driven decision making during experimentation with capability for user customization. We provide a means towards autonomous experimentation for the benefit of both enhanced reproducibility and user-accessibility. Hyperspectral investigations on WS$_2$ sulfur vacancy sites are explored, which is combined with local density of states confirmation on the Au{111} herringbone reconstruction. Chalcogen vacancies, pristine WS$_2$, Au face-centered cubic, and Au hexagonal close packed regions are examined and detected by machine learning methods to demonstrate the potential of artificial intelligence for hyperspectral STS mapping.

cond-mat.mtrl-sci↗