arXiv subjects

Stephan Roche

Publications and source records attributed to Stephan Roche.

At least 19 recordsLinked to original sources

arXiv2026

From Amorphous to Amorphous-Crystalline Mixed-Phase Boron Nitride: Evolution of the Thermal and Elastic Properties

Amorphous boron nitride (aBN) is a promising dielectric and protective coating, yet its nanoscale heat dissipation and elastic response remain poorly quantified. Here we synthesize a variety of BN thin films by borazine-based chemical vapor deposition (800-1000 C) and study the temperature-driven structural transition from fully amorphous networks to mixed amorphous-crystalline films with embedded BN nanocrystallites.Frequency-domain thermoreflectance data show an ultralow, thickness-dependent cross-plane thermal conductivity for aBN (kout < 0.5 W m-1 K-1 for 10-40 nm), which increases systematically with crystalline order up to 1.5 W m-1 K-1. Micro-Brillouin light scattering and finite-element modelling reveal a concomitant stiffening, with Young's modulus rising from 7.5 +/- 0.7 GPa (800 C) to 53 +/- 5 GPa (1000 C). Green-Kubo molecular dynamics simulations rationalize these trends via bonding topology and vibrational transport, and highlight how oxygen, hydrogen and carbon impurities and composition provide practical knobs to further tune the thermal and mechanical responses in BN films for improving nano-electronics, interconnects and coating applications.

cond-mat.mtrl-sci↗

arXiv2026

Excitons in Large Disordered Boron-Nitride Layer using Linear-Scaling Bethe-Salpeter Simulations

We introduce a real-space, linear-scaling Bethe-Salpeter framework that enables excitonic spectroscopy in large and possibly disordered boron-nitride-derived systems. Thanks to the use of a sublattice-resolved perturbative decoupling that maps localized electron-hole pairs onto a sparse tight-binding model, we implement the Kernel Polynomial Method to compute absorption spectra with O(N) cost. To illustrate the capabilities of our method, we apply it to Anderson-disordered monolayer hexagonal boron nitride with up to $10^{5}$ orbitals. The method reveals a disorder-induced asymmetric broadening of bright excitons, a crossover from quadratic to linear redshift of the main absorption peak, and Anderson localization of the exciton center of mass. This approach extends excitonic calculations beyond the reach of conventional ab initio Green's function methods (GW approximation and Bethe-Salpeter equation), opening optical spectroscopy to large-scale, disordered, moir\'e, quasicrystalline, and structurally complex quantum materials.

cond-mat.mtrl-sci↗

arXiv2026

Strain-Mediated Lattice Reconstruction Enhances Ferromagnetism in Cr2Ge2Te6/WTe2 van der Waals Heterobilayers

Van der Waals (vdW) heterostructures enable tailored electronic and magnetic phases by stacking atomically thin layers with pristine interfaces. Here, we investigate fully 2D Cr2Ge2Te6/WTe2 heterostructures and identify a strong enhancement of ferromagnetism in Cr2Ge2Te6 (CGT). Magnetotransport measurements across multiple devices with WTe2 thicknesses ranging from monolayer to bulk reveal a robust anomalous Hall effect together with a more than twofold increase of the Curie temperature and substantially enhanced coercive fields. Interface microscopy confirms chemically abrupt vdW interfaces with no detectable interdiffusion, while control experiments rule out processing- or stray-field-induced artifacts. Our experiments and theoretical calculations demonstrate that interfacial charge transfer renders CGT conductive and that proximity-induced lattice distortions in CGT enhance exchange and magnetocrystalline anisotropy. These results establish strain-mediated lattice reconstruction as a strategy for engineering high-temperature magnetic order in 2D heterostructures and clarify that modifications within the magnetic layer itself can govern proximity effects in vdW stacks.

cond-mat.mtrl-sci↗

arXiv2025

AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions

Artificial intelligence and machine learning are reshaping how we approach scientific discovery, not by replacing established methods but by extending what researchers can probe, predict, and design. In this roadmap we provide a forward-looking view of AI-enabled science across biology, chemistry, climate science, mathematics, materials science, physics, self-driving laboratories and unconventional computing. Several shared themes emerge: the need for diverse and trustworthy data, transferable electronic-structure and interatomic models, AI systems integrated into end-to-end scientific workflows that connect simulations to experiments and generative systems grounded in synthesisability rather than purely idealised phases. Across domains, we highlight how large foundation models, active learning and self-driving laboratories can close loops between prediction and validation while maintaining reproducibility and physical interpretability. Taken together, these perspectives outline where AI-enabled science stands today, identify bottlenecks in data, methods and infrastructure, and chart concrete directions for building AI systems that are not only more powerful but also more transparent and capable of accelerating discovery in complex real-world environments.

physics.soc-ph↗

arXiv2025

Optimal spin-charge interconversion in graphene through spin-pseudospin entanglement control

The electrical generation of spin signals is of central interest for spintronics, where graphene stands as a relevant platform as its spin-orbit coupling (SOC) is tuned by proximity effects. Here, we propose an enhancement of spin-charge interconversion in graphene by controlling the intraparticle entanglement between the spin and pseudospin degrees of freedom. We demonstrate that, although the spin alone is not conserved in Rashba-Dirac systems, a combined spin-pseudospin operator is conserved. This conserved quantity represents the interconversion between pure spin and pseudospin textures to a spin-pseudospin entangled structure, where Kane-Mele SOC tunes this balance. By these means, we achieve spin-charge interconversion of 100\% efficiency via the Rashba-Edelstein effect. Quantum transport simulations in disordered micron-size systems demonstrate the robustness of this effect, and also reveal a disorder resilient spin Hall effect generated by the interplay between Rashba and Kane-Mele SOC. Our findings propose a platform for maximally efficient spin-charge interconversion, and establish spin-pseudospin correlations as a mechanism to tailor spintronic devices.

cond-mat.mes-hall↗

arXiv2025

Atomic-Scale Origins of Oxidation Resistance in Amorphous Boron Nitride

Amorphous boron nitride (\textrm{$\alpha$}-BN) is a promising ultrathin barrier for nanoelectronics, yet the atomistic mechanisms governing its chemical stability remain poorly understood. Here, we investigate the structure-property relationship that dictates the oxidation of \textrm{$\alpha$}-BN using a combination of machine-learning molecular dynamics simulations and angle-resolved X-ray photoelectron spectroscopy. The simulations reveal that the film structure, controlled by synthesis conditions, is the critical factor determining oxidation resistance. Dense, chemically ordered networks with a high fraction of B-N bonds effectively resist oxidation by confining it to the surface, whereas porous, defect-rich structures with abundant homonuclear B-B and N-N bonds permit oxygen penetration and undergo extensive bulk degradation. These computational findings are consistent with experimental trends observed in \textrm{$\alpha$}-BN films grown by chemical vapour deposition. XPS analysis shows that a film grown at a higher temperature develops a more ordered structure with a B/N ratio nearer to stoichiometric and exhibits superior resistance to surface oxidation compared to its more defective, lower-temperature counterpart. Together, these results demonstrate that the oxidation resistance of \textrm{$\alpha$}-BN is a tunable property directly linked to its atomic-scale morphology, providing a clear framework for engineering chemically robust dielectric barriers for future nanoelectronic applications.

cond-mat.mtrl-sci↗

arXiv2025

Anomalous diffusion in multichannel systems without a L\'evy distribution of disorder

We show that multichannel quantum systems with uncorrelated but asymmetric Anderson-type disorder can exhibit anomalous diffusion, even in the absence of heavy-tailed disorder. Using a minimal two-channel model with channel asymmetry, we demonstrate a crossover from normal to anomalous transport tuned by interchannel coupling. Applied to quasi-one-dimensional lattices with edge disorder, this leads to long-tailed transmission statistics characterized by ballistic segments interspersed with localized ones, reminiscent of L\'evy flights. This channel-asymmetric anomalous diffusion (CAAD) emerges from quantum interference between channels with differing disorder strengths. While CAAD governs transport at intermediate lengths, conventional localization prevails asymptotically, violating the Thouless relation. These results highlight a distinct quantum mechanism for anomalous diffusion beyond classical paradigms.

cond-mat.mes-hall↗

arXiv2025

Spin Polarization driven by Itinerant Orbital Angular Momentum in van der Waals Heterostructures

We report on the possibility of manipulating magnetic materials by using itinerant orbital angular momentum to produce out-of-plane spin polarization in van der Waals heterostructures. Employing a real-space formulation of the OAM operator within linear response theory, we demonstrate that in low-symmetry transition-metal dichalcogenide (TMD) monolayers, such as 1$T{}_d$-MoTe2, the current-induced itinerant OAM exceeds the spin response by three orders of magnitude. When TMDs are coupled with ferromagnets with negligible intrinsic orbital responses, the itinerant OAM generated by the orbital Rashba-Edelstein effect transfers across the interface, generating spin densities capable of inducing magnetization dynamics inside the ferromagnet. Our findings highlight the previously overlooked role of itinerant OAM in the generation of out-of-plane spin densities, which serves as an emerging mechanism for efficient electrical control of magnetization in low-power, ultracompact storage devices.

cond-mat.mes-hall↗

arXiv2025

Quantum transport in nitrogen-doped nanoporous graphenes

Bottom-up on-surface synthesized nanoporous graphenes (NPGs), realized as 2D arrays of laterally covalently bonded $\pi$-conjugated graphene nanoribbons (GNRs), are a family of carbon nanomaterials that are receiving increasing attention for nanoelectronics and biosensing. Recently, a so-called hybrid-NPG (hNPG) is synthesized, featuring an alternating sequence of doped and non-doped GNRs, resulting in a band staggering effect in its electronic structure. Such a feature is appealing for photo-catalysis, photovoltaics and even carbon nanocircuitry. However, to date, little is known about the transport properties of hNPG and its derivatives, which is key for most applications. Here, via Green's functions simulations, the quantum transport properties of hNPGs are studied. It is found that injected carriers in hNPG spread laterally through a number of GNRs, though such spreading may take place exclusively through GNRs of one type (doped or non-doped). A simple model is proposed to discern the key parameters determining the electronic propagation in hNPGs and explore alternative hNPG designs to control the spreading/confinement and anisotropy of charge transport in these systems. For one such design, it is found that it is possible to send directed electric signals with sub-nanometer precision for as long as one micrometer - a result first reported for any NPG.

cond-mat.mes-hall↗

arXiv2025

Real-Space Approach to Light-Induced Hall Transport in Disordered Materials

We introduce a linear-scaling real-space methodology to compute time-resolved electrical responses of materials driven far from equilibrium, with energy relaxation and disorder treated on equal footing. Applying this approach to gapped monolayer and AB-stacked (Bernal) bilayer graphene, when driven by a circularly polarized optical pulse, we observe the generation/suppression of a finite Hall conductivity when the system is trivial/topological. This Hall signal oscillates during optical driving and remains sizable after the light is switched off before relaxing toward equilibrium. Remarkably, this dynamical Hall response is robust in the presence of realistic descriptions of disorder, suggesting that disorder and relaxation dynamics can be leveraged as design parameters rather than as limitations. More broadly, our new methodology enables the investigation of electrical responses in driven, complex disordered quantum materials and highlights how engineered energy-transfer pathways can enable ultrafast optoelectronic functionality.

cond-mat.mes-hall↗

arXiv2025

The 2D Materials Roadmap

Over the past two decades, 2D materials have rapidly evolved into a diverse and expanding family of material platforms. Many members of this materials class have demonstrated their potential to deliver transformative impact on fundamental research and technological applications across different fields. In this roadmap, we provide an overview of the key aspects of 2D material research and development, spanning synthesis, properties and commercial applications. We specifically present roadmaps for high impact 2D materials, including graphene and its derivatives, transition metal dichalcogenides, MXenes as well as their heterostructures and moir\'e systems. The discussions are organized into thematic sections covering emerging research areas (e.g., twisted electronics, moir\'e nano-optoelectronics, polaritronics, quantum photonics, and neuromorphic computing), breakthrough applications in key technologies (e.g., 2D transistors, energy storage, electrocatalysis, filtration and separation, thermal management, flexible electronics, sensing, electromagnetic interference shielding, and composites) and other important topics (computational discovery of novel materials, commercialization and standardization). This roadmap focuses on the current research landscape, future challenges and scientific and technological advances required to address, with the intent to provide useful references for promoting the development of 2D materials.

cond-mat.mtrl-sci↗

arXiv2025

Proximity Effects Between the Graphene Quasicrystal and Magic-Angle Twisted Bilayer Graphene

We present a numerical study of three-layer graphene heterostructures in which the layers are twisted by the magic angle ($\sim$1.1$^\circ$) or by $\sim$$30^\circ$ to form a graphene quasicrystal. The heterostacks are described using realistic structural relaxations and tight-binding Hamiltonians, and their transport properties are computed for both pristine and disordered systems containing up to $\sim$8 million atoms. Owing to the weak interlayer coupling, we resolve the hybridization between magic-angle flat bands and quasicrystalline states, which are modified in distinct ways across low- and high-energy windows, revealing a new hybrid electronic regime to explore.

cond-mat.mes-hall↗

arXiv2024

Upper limit of spin relaxation in suspended graphene

We use a combination of molecular dynamics and quantum transport simulations to investigate the upper limit of spin transport in suspended graphene. We find that thermally-induced atomic-scale corrugations are the dominant factor, limiting spin lifetimes to ~10 ns by inducing a strongly-varying local spin-orbit coupling. These extremely short-range corrugations appear even when the height profile appears to be smooth, suggesting they may be present in any graphene device. We discuss our results in the context of experiments, and briefly consider approaches to suppress these short-range corrugations and further enhance spin lifetimes in graphene-based spin devices.

cond-mat.mes-hall↗

arXiv2024

2D Hexagonal Boron Nitride-based Anticorrosion Coatings

The corrosion of metallic surfaces poses significant challenges across industries such as petroleum, energy, and biomedical sectors, leading to structural degradation, safety risks, and substantial maintenance costs. Traditional organic and metallic coatings provide some protection, but their limited durability and susceptibility to harsh environmental conditions necessitate the development of more advanced and efficient solutions. This has driven significant interest in two-dimensional (2D) materials, with graphene extensively studied for its exceptional mechanical strength and impermeability to gases and ions. However, while graphene offers short-term corrosion protection, its high electrical conductivity presents a long-term issue by promoting galvanic corrosion on metal surfaces. In contrast, hexagonal boron nitride (h-BN) has emerged as a promising alternative for anticorrosion coatings. h-BN combines exceptional chemical stability, impermeability, and electrical insulation, making it particularly suited for long-term protection in highly corrosive or high-temperature environments. While h-BN holds promise as anticorrosion material, challenges such as structural defects, agglomeration of nanosheets, and poor dispersion within coatings limit its performance. This review provides a comprehensive analysis of recent advancements in addressing these challenges, including novel functionalization strategies, scalable synthesis methods, and hybrid systems that integrate h-BN with complementary materials. By bridging the gap between fundamental research and industrial applications, this review outlines the potential for h-BN to revolutionize anticorrosion technologies. These obstacles necessitate advanced strategies such as surface functionalization to improve compatibility with polymer matrices and dispersion optimization to minimize agglomeration.

cond-mat.mtrl-sci↗

arXiv2024

Artificial Intelligence-Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

(Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of devices due to its time-intensive nature. To address this, we introduce an analytical workflow for the holistic characterization, modelling, and simulation of device heterostructures. This workflow automates the experimental (S)TEM data analysis, providing an in-depth characterization of crystallographic information, 3D orientation, elemental composition, and strain distribution. It reduces a process that typically takes days for a trained human into an automatic routine solved in minutes. Utilizing a physics-guided artificial intelligence model, it generates representative descriptions of materials and samples. The workflow culminates in creating digital twins, 3D finite element and atomic models of millions of atoms, enabling simulations that provide crucial insights into device behaviour in practical applications. Demonstrated with SiGe planar heterostructures for scalable spin qubits, the workflow links digital twins to theoretical properties, revealing how atomic structure impacts materials and functional properties such as spatially-resolved phononic or electronic characteristics, or (inverse) spin orbit lengths. The versatility of our workflow is demonstrated through its application to a wide array of materials systems, device configurations, and sample morphologies.

cond-mat.mtrl-sci↗

arXiv2024

Topologically Driven Spin-Orbit Torque in Dirac Matter

We unveil novel spin-orbit torque mechanisms driven by topological edge states in magnetic graphene-based devices. Within the energy gap, a damping-like torque plateau emerges within the quantum anomalous Hall phase upon breaking particle-hole symmetry, while for energies at the spin-split Dirac points located within the bands, a large damping-like torque develops as a result of a vanishing Fermi contour. Such torques are tunable by the degree of spin-pseudospin entanglement dictated by proximity-induced spin-orbit coupling terms.

cond-mat.mes-hall↗

arXiv2024

A non-Hermitian loop for a quantum measurement

Here we present a non-Hermitian framework for modeling state-vector collapse under unified dynamics described by Schr\"odinger's equation. Under the premise of non-Hermitian Hamiltonian dynamics, we argue that collapse has to occur when the Hamiltonian completes a closed loop in the parameter space encoding the interaction with the meter. For two-level systems, we put forward the phenomenon of chiral state conversion as a mechanism for effectively eliminating superpositions. This perspective opens a way to simulate quantum measurements in classical systems that up to now were restricted to the Schr\"odinger part of the quantum dynamics.

quant-ph↗

arXiv2024

Real-Time Out-of-Equilibrium Quantum Dynamics in Disordered Materials

We report a linear-scaling numerical method for exploring nonequilibrium electron dynamics in systems of arbitrary complexity. Based on the Chebyshev expansion of the time evolution of the single-particle density matrix, the method gives access to nonperturbative excitation and relaxation phenomena in models of disordered materials with sizes on the experimental scale. After validating the method by applying it to saturable optical absorption in clean graphene, we uncover that disorder can enhance absorption in graphene and that the interplay between light, anisotropy, and disorder in nanoporous graphene might be appealing for sensing applications. Beyond the optical properties of graphene-like materials, the method can be applied to a wide range of large-area materials and systems with arbitrary descriptions of defects and disorder.

cond-mat.mes-hall↗