arXiv subjects

Roman Gorbachev

Publications and source records attributed to Roman Gorbachev.

At least 19 recordsLinked to original sources

arXiv2026

Moir\'e-induced lattice reconstruction at buried atomic interfaces

Atomic reconstruction at twisted two-dimensional interfaces governs many of their emergent optical, electronic, and mechanical properties, including sliding ferroelectricity. Despite recent progress in understanding lattice reconstruction in suspended twisted bilayers, structural changes at van der Waals heterointerfaces between multilayer crystals remain largely unexplored. Here we use multi-slice electron ptychography to non-invasively recover the three-dimensional atomic structure at marginally twisted rhombohedral interfaces between thick transition-metal dichalcogenide crystals. With a position precision of ~3 pm and a depth resolution ~1 nm, we resolve the twist-induced lattice reconstruction field per layer, and the resulting dislocation network at the buried interface. Despite the bulk nature, we observe markedly strong in-plane interfacial reconstruction due to suppression of the out-of-plane bending by outer layers, exceeding predictions from our three-dimensional modelling. Furthermore, we extract the strain tensor evolution during the decay of the reconstruction into the bulk, providing a structural foundation for understanding multi-layer moir\'e systems.

cond-mat.mes-hall↗

arXiv2026

Predictive Style Matching: Natural and Robust Humanoid Locomotion

Reinforcement learning has become the prevailing approach to humanoid locomotion control: policies transfer reliably from simulation to hardware and recover gracefully from disturbances. Motion quality, however, still lags behind: task-only rewards often converge to stiff, asymmetric gaits, while motion imitation methods improve appearance but become more sensitive to external disturbances because reference signals can oppose the transient poses needed to regain balance. We propose Predictive Style Matching, in which an offline predictor maps the robot's lower-body state history and velocity commands to interpretable upper-body joint and gait targets that shape the rewards during training. Because the targets are state-conditioned rather than time-indexed and the predictor is used only at training time, the deployed controller inherits the proprioceptive interface and inference cost of a task-only RL baseline. On the Unitree G1, in both simulation and hardware, PSM reduces upper-body style error by roughly an order of magnitude over task-only RL while preserving its fall-recovery rate, whereas the motion-imitation baseline attains the lowest style error but fails to recover from disturbances about five times as often.

cs.RO↗

arXiv2026

The Topography Trap: Sifting Interlayer Excitons from Strain-Related Artifacts in Real-World 2D Hetrostructures

Novel excitonic phenomena emerging in transition metal dichalcogenide (TMDC) heterostructures belong to the most exciting topics in contemporary physics of van der Waals materials. Interlayer excitons (IXs) stand out among those due to their long radiative lifetimes and tunability by electric fields, strain, and twist angle. However, many ambiguities persist in the optical identification and manipulation of IXs, highlighting the need for reliable spectroscopic criteria that distinguish interlayer species from spurious signals. Here, we present a decision-tree protocol that evaluates interlayer coupling via intralayer exciton quenching and correlates photoluminescence (PL) with atomic force microscopy (AFM) to correctly assign room-temperature PL features in TMDC-based heterostructures. Applying this protocol, we identify momentum-direct IX between the K valleys of the two layers (KK-IX) in MoS2-MoSe2 and MoS2-WSe2 heterostructures at room temperature. In contrast, our protocol contests the reported bright, momentum-indirect, twist-angle-independent $\Gamma$K-IX in MoS2-WSe2. Comprehensive experimental data, including infrared and tip-enhanced photoluminescence (TEPL) with sub-diffraction-limited resolution, show no compelling evidence for this excitonic species, despite numerous reports. Instead, the spectroscopic features previously assigned to this $\Gamma$K-IX originate from locally strained WSe2 at topographical inhomogeneities of the heterostructure interface, underscoring the need for robust, spatially resolved characterization of real-world samples in this highly accessible field and providing a generally applicable framework for identifying interlayer excitons in 2D semiconductor heterostructures.

cond-mat.mes-hall↗

arXiv2026

Trajectory-based actuator identification via differentiable simulation

Accurate actuation models are critical for bridging the gap between simulation and real robot behavior, yet obtaining high-fidelity actuator dynamics typically requires dedicated test stands and torque sensing. We present a trajectory-based actuator identification method that uses differentiable simulation to fit system-level actuator models from encoder motion alone. Identification is posed as a trajectory-matching problem: given commanded joint positions and measured joint angles and velocities, we optimize actuator and simulator parameters by backpropagating through the simulator, without torque sensors, current/voltage measurements, or access to embedded motor-control internals. The framework supports multiple model classes, ranging from compact structured parameterizations to neural actuator mappings, within a unified optimization pipeline. On held-out real-robot trajectories for a high-gear-ratio actuator with an embedded PD controller, the proposed torque-sensor-free identification achieves much tighter trajectory alignment than a supervised stand-trained baseline dominated by steady-state data, reducing mean absolute position error from 14.20 mrad to as low as 7.54 mrad (1.88 times). Finally, we demonstrate downstream impact for the same actuator class in a real-robot locomotion study: training policies with the refined actuator model increases travel distance by 46% and reduces rotational deviation by 75% relative to the baseline.

cs.RO↗

arXiv2026

Atomic-resolution imaging of gold species at organic liquid-solid interfaces

Understanding solid-liquid interfaces at the atomic-scale is key to improved performance of heterogeneous catalysts, electrodes and membranes. Here we combine unique specimen design, record atomic resolution in situ electron microscopy, and artificial intelligence-enabled analysis to achieve a step change in quantitative understanding of interfacial atomic behaviour. We create the first graphene liquid cells with organic solvents and employ them to track over 106 gold adatoms and clusters at a graphene surface immersed in acetone and cyclohexanone. We reveal dynamic correlated behaviour of gold adatom monomers, dimers, trimers and clusters, strongly influenced by each other, the solvent properties, and the atomic lattice of the substrate, in good agreement with theoretical calculations. We use the results to interpret differences in catalytic activity towards the industrially important acetylene hydrochlorination reaction. This new capability for exploration of atomic scale chemistry could enable rational design of future catalysts, membranes and electrodes with improved functionality.

cond-mat.mtrl-sci↗

arXiv2026

Atomic imaging of 2D transition metal dihalides

Transition metal di-iodides such as FeI2, NiI2 and CoI2 are an emerging class of 2D magnets exhibiting rich and diverse magnetic behaviour, but their study at the monolayer limit has been severely hindered by fabrication challenges due to their air-sensitivity. Here, we introduce a polymer-free method for clean, rapid, and high-yield assembly of hermetically encapsulated suspended samples of air-sensitive monolayers. Applying it to di-iodides enables atomic resolution characterisation of thin samples - down to the monolayer limit - for the first time. Our imaging, combined with complementary first-principles calculations, reveals an unusually small energy barrier between alternate stable stacking polytypes in few-layer films, enabling extrinsic control of the stacking phase. We also observe stable isolated iodine vacancies that do not aggregate to form extended structures, and identify and verify the stability of the various edge configurations of thin samples. These results establish the unique structural characteristics of these materials in the thin limit, and more broadly demonstrate the utility of our transfer platform for creating atomically clean suspended vdW heterostructures.

cond-mat.mtrl-sci↗

arXiv2026

Noise2Void for Denoising Atomic Resolution Scanning Transmission Electron Microscopy Images

The Noise2Void technique is demonstrated for successful denoising of atomic-resolution scanning transmission electron microscopy (STEM) images. The technique is applied to denoising atomic resolution images and videos of gold adatoms on a graphene surface within a graphene liquid cell, with the denoised experimental data qualitatively demonstrating improved visibility of both the Au adatoms and the graphene lattice. The denoising performance is quantified by comparison to similar simulated data and the approach is found to significantly outperform both total variation and simple Gaussian blurring. Compared to other denoising methods, the Noise2Void technique has the combined advantages that it requires no manual intervention during training or denoising, no prior knowledge of the sample and is compatible with real time data acquisition rates of at least 45 frames per second.

cond-mat.mtrl-sci↗

arXiv2025

DecARt Leg: Design and Evaluation of a Novel Humanoid Robot Leg with Decoupled Actuation for Agile Locomotion

In this paper, we propose a novel design of an electrically actuated robotic leg, called the DecARt (Decoupled Actuation Robot) Leg, aimed at performing agile locomotion. This design incorporates several new features, such as the use of a quasi-telescopic kinematic structure with rotational motors for decoupled actuation, a near-anthropomorphic leg appearance with a forward facing knee, and a novel multi-bar system for ankle torque transmission from motors placed above the knee. To analyze the agile locomotion capabilities of the design numerically, we propose a new descriptive metric, called the `Fastest Achievable Swing Time` (FAST), and perform a quantitative evaluation of the proposed design and compare it with other designs. Then we evaluate the performance of the DecARt Leg-based robot via extensive simulation and preliminary hardware experiments.

cs.RO↗

arXiv2025

Heuristic Step Planning for Learning Dynamic Bipedal Locomotion: A Comparative Study of Model-Based and Model-Free Approaches

This work presents an extended framework for learning-based bipedal locomotion that incorporates a heuristic step-planning strategy guided by desired torso velocity tracking. The framework enables precise interaction between a humanoid robot and its environment, supporting tasks such as crossing gaps and accurately approaching target objects. Unlike approaches based on full or simplified dynamics, the proposed method avoids complex step planners and analytical models. Step planning is primarily driven by heuristic commands, while a Raibert-type controller modulates the foot placement length based on the error between desired and actual torso velocity. We compare our method with a model-based step-planning approach -- the Linear Inverted Pendulum Model (LIPM) controller. Experimental results demonstrate that our approach attains comparable or superior accuracy in maintaining target velocity (up to 80%), significantly greater robustness on uneven terrain (over 50% improvement), and improved energy efficiency. These results suggest that incorporating complex analytical, model-based components into the training architecture may be unnecessary for achieving stable and robust bipedal walking, even in unstructured environments.

cs.RO↗

arXiv2025

Achieving Precise and Reliable Locomotion with Differentiable Simulation-Based System Identification

Accurate system identification is crucial for reducing trajectory drift in bipedal locomotion, particularly in reinforcement learning and model-based control. In this paper, we present a novel control framework that integrates system identification into the reinforcement learning training loop using differentiable simulation. Unlike traditional approaches that rely on direct torque measurements, our method estimates system parameters using only trajectory data (positions, velocities) and control inputs. We leverage the differentiable simulator MuJoCo-XLA to optimize system parameters, ensuring that simulated robot behavior closely aligns with real-world motion. This framework enables scalable and flexible parameter optimization. Accurate system identification is crucial for reducing trajectory drift in bipedal locomotion, particularly in reinforcement learning and model-based control. In this paper, we present a novel control framework that integrates system identification into the reinforcement learning training loop using differentiable simulation. Unlike traditional approaches that rely on direct torque measurements, our method estimates system parameters using only trajectory data (positions, velocities) and control inputs. We leverage the differentiable simulator MuJoCo-XLA to optimize system parameters, ensuring that simulated robot behavior closely aligns with real-world motion. This framework enables scalable and flexible parameter optimization. It supports fundamental physical properties such as mass and inertia. Additionally, it handles complex system nonlinear behaviors, including advanced friction models, through neural network approximations. Experimental results show that our framework significantly improves trajectory following.

cs.RO↗

arXiv2025

Exciton-polaritons in a monolayer semiconductor coupled to van der Waals dielectric nanoantennas on a metallic mirror

Polaritons in nanophotonic structures have attracted long-standing interest owing to their fundamental importance and potential for applications in nonlinear and quantum optics. Nanoantennas (NAs) made from high refractive index dielectrics offer a suitable platform for polariton physics thanks to the strongly confined optical Mie resonances and low optical losses in contrast to metallic NAs. However, Mie modes are mainly confined within the NA, making inefficient their coupling with excitons in materials deposited externally. Here, we overcome this limitation by using a high-refractive index van der Waals material WS$_2$, which allows straightforward fabrication of NAs on gold. The combination of a 27 nm tall WS$_2$ NA and a gold substrate enables strong modification of the Mie mode distribution and field enhancement inside and in the vicinity of the NA. This allows observation of room-temperature Mie-polaritons (with a Rabi splitting above 80 meV) arising from the strong coupling between Mie modes and the exciton in a monolayer WSe$_2$ placed on WS$_2$/gold NAs. We demonstrate strong nonlinearity of Mie-polaritons, one order of magnitude higher than for excitons in monolayer WSe$_2$ on gold. Our results highlight applicability of van der Waals materials for the realisation of hybrid dielectric-metallic nanophotonics for the study of the strong light-matter interaction.

physics.optics↗

arXiv2025

Topological Jackiw-Rebbi States in Photonic Van der Waals Heterostructures

Topological phenomena, first studied in solid state physics, have seen increased interest for applications in nanophotonics owing to highly controllable light confinement with inherent robustness to defects. Photonic crystals can be designed to host topologically protected interface states for directional light transport, localization and robust lasing via tuning of the bulk topological invariant. At the same time, van der Waals (vdW) materials, in both their monolayer and quasi-bulk forms, are emerging as exciting additions to the field of nanophotonics, with a range of unique optoelectronic properties and intrinsic adherence to any type of host material, allowing fabrication of complex multi-layer structures. We present here a 1D topological photonic platform made from stacked nanostructured and planar layers of quasi-bulk WS$_2$ to achieve Jackiw-Rebbi (JR) interface states between two topologically distinct gratings in the near-infrared range around 750 nm. Such states are measured in the far-field with angle-resolved reflectance contrast measurements, exhibiting linewidth of 10 meV and highly directional emission with an angular bandwidth of 8.0$^\circ$. Subsequent local mapping of the structure via sub-wavelength resolution scattering-type scanning near-field optical microscopy (s-SNOM) reveals strong spatial confinement of the JR state to the grating interface region. Finally, we couple in the JR state the photoluminescence of monolayer WSe$_2$ incorporated in a five-layer vdW grating heterostructure, giving rise to directional enhancement of the excitonic emission of up to 22 times that of uncoupled monolayer, thus demonstrating the potential of the topological interface states for highly directional light emission in addition to light scattering.

physics.optics↗

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↗

arXiv2024

Electron Channelling Contrast SEM Imaging of Twist Domains in Transition Metal Dichalcogenide Heterostructures

Twisted 2D material heterostructures provide an exciting platform for investigating new fundamental physical phenomena. Many of the most interesting behaviours emerge at small twist angles, where the materials reconstruct to form areas of perfectly stacked crystal separated by partial dislocations. However, understanding the properties of these systems is often impossible without correlative imaging of their local reconstructed domain architecture, which exhibits random variations due to disorder and contamination. Here we demonstrate a simple and widely accessible route to visualise domains in as-produced twisted transition metal dichalcogenide (TMD) heterostructures using electron channelling contrast imaging (ECCI) in the scanning electron microscope (SEM). This non-destructive approach is compatible with conventional substrates and allows domains to be visualised even when sealed beneath an encapsulation layer. Complementary theoretical calculations reveal how a combination of elastic and inelastic scattering leads to contrast inversions at specified detector scattering angles and sample tilts. We demonstrate that optimal domain contrast is therefore achieved by maximising signal collection while avoiding contrast inversion conditions.

cond-mat.mtrl-sci↗

arXiv2024

One-step synthesis of graphene containing topological defects

Chemical vapour deposition enables large-domain growth of ideal graphene, yet many applications of graphene require the controlled inclusion of specific defects. We present a one-step chemical vapour deposition procedure aimed at retaining the precursor topology when incorporated into the grown carbonaceous film. When azupyrene, the molecular analogue of the Stone-Wales defect in graphene, is used as a precursor, carbonaceous monolayers with a range of morphologies are produced as a function of the copper substrate growth temperature. The higher the substrate temperature during deposition, the closer the resulting monolayer is to ideal graphene. Analysis, with a set of complementary materials characterisation techniques, reveals morphological changes closely correlated with changes in the atomic adsorption heights, network topology, and concentration of 5-/7-membered carbon rings. The engineered defective carbon monolayers can be transferred to different substrates, potentially enabling applications in nanoelectronics, sensorics, and catalysis.

cond-mat.mtrl-sci↗

arXiv2024

Tunnel junctions based on interfacial 2D ferroelectrics

Van der Waals (vdW) heterostructures have opened new opportunities to develop atomically thin (opto)electronic devices with a wide range of functionalities. The recent focus on manipulating the interlayer twist angle has led to the observation of out-of-plane room temperature ferroelectricity in twisted rhombohedral (R) bilayers of transition metal dichalcogenides (TMDs). Here we explore the switching behaviour of sliding ferroelectricity using scanning probe microscopy domain mapping and tunnelling transport measurements. We observe well-pronounced ambipolar switching behaviour in ferroelectric tunnelling junctions (FTJ) with composite ferroelectric/non-polar insulator barriers and support our experimental results with complementary theoretical modelling. Furthermore, we show that the switching behaviour is strongly influenced by the underlying domain structure, allowing fabrication of diverse FTJ devices with various functionalities. We show that to observe the polarisation reversal, at least one partial dislocation must be present in the device area. This behaviour is drastically different from that of conventional ferroelectric materials and its understanding is an important milestone for future development of optoelectronic devices based on sliding ferroelectricity.

cond-mat.mes-hall↗

arXiv2023

Benchmarking the Full-Order Model Optimization Based Imitation in the Humanoid Robot Reinforcement Learning Walk

When a gait of a bipedal robot is developed using deep reinforcement learning, reference trajectories may or may not be used. Each approach has its advantages and disadvantages, and the choice of method is up to the control developer. This paper investigates the effect of reference trajectories on locomotion learning and the resulting gaits. We implemented three gaits of a full-order anthropomorphic robot model with different reward imitation ratios, provided sim-to-sim control policy transfer, and compared the gaits in terms of robustness and energy efficiency. In addition, we conducted a qualitative analysis of the gaits by interviewing people, since our task was to create an appealing and natural gait for a humanoid robot. According to the results of the experiments, the most successful approach was the one in which the average value of rewards for imitation and adherence to command velocity per episode remained balanced throughout the training. The gait obtained with this method retains naturalness (median of 3.6 according to the user study) compared to the gait trained with imitation only (median of 4.0), while remaining robust close to the gait trained without reference trajectories.

cs.RO↗

arXiv2023

Ultra-clean assembly of van der Waals heterostructures

Layer-by-layer assembly of van der Waals (vdW) heterostructures underpins new discoveries in solid state physics, material science and chemistry. Despite the successes, all current 2D material (2DM) transfer techniques rely on the use of polymers which limit the cleanliness, ultimate electronic performance, and potential for optoelectronic applications of the heterostructures. In this article, we present a novel polymer-free platform for rapid and facile heterostructure assembly which utilises re-usable flexible silicon nitride membranes. We demonstrate that this allows fast and reproducible production of 2D heterostructures using both exfoliated and CVD-grown materials with perfect interfaces free from interlayer contamination and correspondingly excellent electronic behaviour, limited only by the size and intrinsic quality of the crystals used. Furthermore, removing the need for polymeric carriers allows new possibilities for vdW heterostructure fabrication: assembly at high temperatures up to 600{\deg}C, and in different environments including ultra-high vacuum (UHV) and when the materials are fully submerged in liquids. We demonstrate UHV heterostructure assembly for the first time, and show the reliable creation of graphene moir\'e superlattices with more than an order of magnitude improvement in their structural homogeneity. We believe that broad adaptation of our novel inorganic 2D materials assembly strategy will allow realisation of the full potential of vdW heterostructures as a platform for new physics and advanced optoelectronic technologies.

physics.app-ph↗