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Heng Wang

Publications and source records attributed to Heng Wang.

At least 55 records · Page 3Linked to original sources
arXiv2026

Multi-Turn Agentic Scientific Literature Search via Workflow Induction

Scientific literature search often requires more than retrieving papers from a single query: users' intents are underspecified, preference-dependent, and evolve through interaction. Existing search agents typically rely on fixed pipelines or implicit language-only reasoning, making their search strategies difficult to control, inspect, and refine. We introduce PaperPilot, a multi-turn literature search agent that frames scientific search as workflow induction. Given an anchor paper and a user query, PaperPilot constructs an executable DAG of paper-search operators, including keyword search, citation expansion, filtering, scoring, reranking, and evidence extraction. User feedback is then used to refine both the query and the workflow itself. We train PaperPilot with supervised workflow imitation and preference optimization over controlled workflow corruptions. Experiments show that PaperPilot-9B improves over the base Qwen3.5-9B toolset agent under multi-turn interaction, increasing Hit@5 from 58.0 to 77.0, MRR from 47.5 to 59.4, and nDCG@10 from 26.8 to 32.5, while reducing workflow execution errors from 9.5% to 0%. These results show that explicit, editable search workflows provide an effective and controllable interface for aligning literature search agents with complex scientific intent.

cs.CL↗
arXiv2026

PIGEON: VLM-Driven Object Navigation via Points of Interest Selection

Object navigation in unseen indoor environments requires agents to perform semantic search under partial observability. Vision-language models (VLMs) provide strong semantic-spatial priors for this task, but how to interface them with robot navigation remains challenging: dense VLM inference is expensive, while abstracting environments into symbolic memories often separates high-level reasoning from the raw visual evidence that supports it. We propose we propose PIGEON (Point of Interest Guided Exploration for Object Navigation), a VLM-driven framework that formulates object navigation as raw-observation-grounded sparse decision problem. PIGEON introduces Points of Interest (PoIs) as sparse visual decision units that couple geometrically executable waypoints with raw egocentric observations. Rather than using VLMs as dense controllers or restricting them to frontier ranking, PIGEON enables VLMs to select among task-critical PoIs, including exploration frontiers, suspected target objects, traversable stairs, and floor-level summaries, while low-level planners execute continuous motion between them. This PoI interface further makes high-level navigation decisions verifiable, allowing us to develop an RLVR pipeline that improves local VLMs without manual Chain-of-Thought annotations. Extensive experiments on Habitat ObjectNav benchmarks show that PIGEON achieves state-of-the-art zero-shot performance, scales consistently with foundation model capacity, and transfers to Active Embodied Question Answering with only prompt modifications. Real-world deployments on physical robots further demonstrate its robustness and efficiency.

cs.RO↗
arXiv2026

Agentopia: Long-Term Life Simulation and Learning in Agent Societies

Humans learn from social life. Simulating this process with LLM-powered agents represents a promising research direction, raising a natural question: whether LLMs can learn from such simulated social experience to better understand and replicate human behavior. However, prior agent society simulations typically operate at the scale of days, limiting the depth of social interactions and long-term growth. In this paper, we study long-term life simulation and LLM learning in agent societies, with two goals: (1) investigating social behaviors that emerge from life-long simulation, and (2) developing anthropomorphic capabilities in LLMs, particularly intelligence in social life, through years of simulated social experience. Specifically, we present Agentopia, a comprehensive framework for long-term life simulation in multi-agent societies, where 100 agents autonomously pursue personal growth, develop social relationships, and fulfill their needs and goals over 10 simulated years. We define life reward to mirror human well-being, and leverage this reward to train LLMs via rejection sampling. Extensive experiments show that agents exhibit rich emergent social behaviors. Furthermore, life reward training effectively enhances the underlying LLM, which leads to improved agent well-being in simulation, and generalizes to downstream role-playing benchmarks with +15.6% improvement.

cs.CL↗
arXiv2026

Dream.exe: Can Video Generation Models Dream Executable Robot Manipulation?

Video generation models have made impressive strides in synthesizing visually compelling content, yet their outputs remain confined to the virtual domain. A natural question follows: how well do these models reflect the physical world when their generated videos leave the screen and enter reality? We propose robotic manipulation as a concrete, measurable window onto this question: if a model has truly internalized physical laws, the motion it depicts should translate into executable robot behavior. We introduce Dream$.$exe, an evaluation framework that operationalizes this criterion through a video-to-execution pipeline. Given a scene image and a task description, Dream$.$exe synthesizes a manipulation video, converts the generated motion into robot trajectories, and executes them in a physics simulator, yielding a grounding signal that purely visual metrics cannot offer. Using this pipeline, we evaluate 8 models spanning frontier closed-source generators, open-source generators, and robot-specific models. Our benchmark covers 101 manually curated manipulation tasks at three levels of physical complexity, measured across visual quality, trajectory fidelity, and execution success. Encouragingly, several models achieve measurable execution success, suggesting that generative priors learned from internet-scale data already encode meaningful physical knowledge. Yet visual quality proves a poor predictor of executability, exposing a dimension of model capability that standard visual evaluations do not capture. Dream$.$exe will be open-sourced at https://github.com/showlab/Dream.exe.

cs.CV↗
arXiv2026

Bipolar-doped superconducting infinite-layer cuprates

Distilling the intrinsic physics of the superconducting CuO2 plane from the complexities of charge-reservoir layers is a defining challenge in high-temperature superconductivity. While superconducting electron-doped infinite-layer cuprates have been synthesized, controllable and uniform hole doping has long remained elusive despite exploratory attempts, limiting spectroscopic insights. Here, we realize bipolar doping across infinite-layer (Sr,Eu)CuO2 and (Ca,Li)CuO2+δ single-crystalline thin films, mapping the electronic phase diagram. Both electron- and hole-doped films show pronounced electrical resistance anisotropy, indicating the quasi-two-dimensional nature of the CuO2 planes. Angle-resolved photoemission spectroscopy across electron- and hole-doped regimes reveals persistent antiferromagnetic band folding coexisting with superconductivity. Remarkably, at a hole doping ~0.07 determined by Luttinger volume, the antiferromagnetic folding emerges from Fermi arcs within the film's single Fermi surface, with the onset superconducting transition temperature exceeding 60 K. These findings redefine the interplay between magnetic order and superconductivity and establish a definitive platform to investigate the intrinsic mechanism of high-temperature superconducting cuprates.

cond-mat.supr-con↗
arXiv2026

ChannelAgent-Empowered Electromagnetic Space World Model: A Case Study on Agent-Driven Channel Generation for 6G AI-Native Air Interface

As sixth-generation (6G) wireless networks evolve toward increasingly heterogeneous scenarios, tasks, and service requirements, conventional artificial intelligence (AI) models remain limited in task-aware decision-making and autonomous adaptation. To address this issue, this paper first proposes a ChannelAgent-empowered electromagnetic space world model, in which wireless intelligence is organized into a closed-loop process consisting of multi-modal sensing, ChannelAgent as the intelligent core, and execution with feedback update. As a case study, agent-driven channel generation is instantiated through path loss prediction. Specifically, a task-oriented intelligent feature selection mechanism is designed by integrating reinforcement-learning-inspired policy adaptation with evolutionary search, enabling the agent to iteratively derive compact and task-suitable feature subsets according to the current scenario and performance feedback. Simulation results demonstrate superior performance in both single-scenario and multi-scenario tasks, highlighting the potential of the proposed model for autonomous, adaptive, task-oriented, and closed-loop wireless intelligence.

eess.SP↗
arXiv2026

Magnetic-field-tunable cyclotron hyperbolic polaritons

Hyperbolic polaritons are conventionally associated with structural anisotropy or phononic Reststrahlen bands. Here, we predict a new class of hyperbolic polaritons arising from magnetic-field-induced cyclotron motion of charge carriers. When a perpendicular magnetic field is applied to high-mobility semimetals, the cyclotron response drives the in-plane dielectric function from metallic- to insulating-like below the cyclotron resonance frequency, while the out-of-plane response remains metallic. This anisotropy creates a hyperbolic dielectric environment that supports field-tunable hyperbolic polaritons. We develop a comprehensive theoretical framework incorporating coupling to other collective excitations and show that these modes can be directly visualized in real space via terahertz near-field nanoscopy. Our work identifies cyclotron motion as a new route to hyperbolic polaritons and establishes a versatile platform for magnetically programmable nanophotonics.

cond-mat.mes-hall↗
arXiv2026

Field re-entrant superconductivity in Eu-doped infinite-layer nickelates

Intertwined superconducting and magnetic orders may give rise to exotic quantum phases, including field-induced and re-entrant superconductivity. However, such magnetism-enhanced superconductivity has remained elusive in superconductors with higher transition temperatures. While infinite-layer nickelates represent a new class of unconventional superconductors, the impact of rare-earth magnetism on superconducting properties remains largely unexplored. Here, we show that Eu-doped infinite-layer nickelate Sm$_{0.95-x}$Ca$_{0.05}$Eu$_x$NiO$_2$ exhibits a magnetic-field-induced re-entrant superconducting phase in the Eu-rich over-doped regime. Zero-resistance transport and high-field diamagnetic screening confirm the superconducting nature of this phase, which emerges after the initial suppression of low-field superconductivity and remains robust across a broad range of temperatures, fields and field orientations. In the same doping range, we observe nonlinear Hall transport and hysteretic magnetoresistance, indicating the unconventional nature of the re-entrant behaviour. While partially consistent with a compensation mechanism between the Eu-derived exchange field and the applied field, our data reveal pronounced deviations from this model at the highest-doping levels. Our findings establish infinite-layer nickelates as a fertile platform for exploring magnetically driven high-field superconductivity in strongly correlated oxides.

cond-mat.supr-con↗
arXiv2026

$3d_{z^2}$ orbital delocalization and magnetic collapse in superconducting (La,Pr)$_3$Ni$_2$O$_{7-δ}$ films

The recent discovery of Ruddlesden--Popper (RP) nickelate thin-film superconductors has opened a new frontier in unconventional superconductivity. Its realization requires both compressive epitaxial strain and highly oxidative growth conditions, yet the microscopic pathway from the parent phase to the superconducting phase remains elusive. Here, X-ray absorption spectra and resonant inelastic X-ray scattering are employed to track this evolution by independently tuning strain and oxygen content in (La,Pr)$_3$Ni$_2$O$_{7-δ}$ thin films. We uncover a remarkable two-step narrative. First, signatures of delocalization emerge in the same way upon two independent tunings: Spectral weight transfers from a ''Upper Hubbard''-like peak to the hole-like peak associated with O $2p_z$ state, and in parallel, the initially localized Ni $3d_{z^2}$ orbital becomes more itinerant followed by the broadening and weakening of $dd$ orbital excitations. Second, as itinerancy increases, long-range spin-density-wave (SDW) order is suppressed in both intensity and correlation length, indicating direct competition with superconductivity. Yet, short-range magnons persist: they become damped but their bandwidth stays unchanged. Our results paint a coherent picture that both strain and oxygenation drive the RP bilayer nickelates towards the superconducting instability, where the O $2p_z$ and Ni $3d_{z^2}$ orbitals become delocalized. Concomitantly, the long-range magnetic order loses coherence and gets suppressed. These findings establish an orbital-selective route to RP nickelate superconductivity, in which the delocalization of the $2p_z$ and $3d_{z^2}$ orbitals and the robust short-range magnons upon the melting of SDW order are prerequisites, providing strong constraints for theory and the roadmap for designing nickelate superconductors.

cond-mat.supr-con↗
arXiv2026

Electronic structures across superconductor-insulator transition in Ruddlesden-Popper bilayer nickelate films

High-transition-temperature ($T_{C}$) superconductivity is recently discovered in Ruddlesden-Popper (RP) nickelate films with extraordinarily strong oxidation. While investigating phase diagrams is essential for uncovering the superconducting mechanism, the oxygen-tuned superconductor-insulator transition (SIT) in RP nickelates differs fundamentally from that in cuprates or iron-based systems. Here, we unveil the evolution of electronic structure in RP bilayer nickelate thin films across the SIT, combining angle-resolved photoemission spectroscopy (ARPES) and X-ray absorption spectroscopy (XAS) for both occupied and unoccupied states. In the superconducting state, a coherent quasiparticle band near Fermi level ($E_{F}$) coexists with an incoherent waterfall feature at high energy, paralleling that in cuprates. Approaching the insulating state with oxygen deficiency, the spectral weight of the occupied coherent quasiparticle band is gradually suppressed, accompanied by pronounced density of states redistribution and orbital reconfiguration in unoccupied states. These results reveal the electronic origin of the SIT in the phase diagram, which transcends carrier doping effects and oxygen vacancy states. Our findings point to a decisive role of oxygen in shaping the essential electronic landscape of RP bilayer nickelates, offering crucial insights into the superconducting mechanism.

cond-mat.supr-con↗
arXiv2026

Superconductivity and Electronic Structures of Nickelate Thin Film Superstructures

Ruddlesden-Popper (RP) nickelates have emerged as a crucial platform for exploring the mechanisms of high-temperature superconductivity. However, the Fermi surface topology required for superconductivity remains elusive. Here, beyond the superconducting pure bilayer (2222) phase, we report the thin film growth and ambient-pressure superconductivity of monolayer-bilayer (1212) and bilayer-trilayer (2323) superstructures, together with the absence of superconductivity in monolayer-trilayer (1313) superstructure, under identical compressive epitaxial strain. The onset superconducting transition temperatures range from 46 to 50 K, exceeding the McMillan limit. Angle-resolved photoemission spectroscopy reveals key Fermi surface differences in these atomically-engineered structures. In superconducting 1212 and 2222 films, a dispersive hole-like band ($γ^{\mathrm{II}}$) forms an underlying Fermi pocket, surrounding the Brillouin zone corner. In contrast, the top of the flat band ($γ^{\mathrm{III}}$) is observed ~70 meV below $E_\text{F}$ in the non-superconducting 1313 films. Particularly, the superconducting 2323 films host both $γ^{\mathrm{II}}$ and $γ^{\mathrm{III}}$ bands. The polarization dependence of the $γ$ bands reveals their Ni $d_{z^2}$ origin. Our findings expand the family of ambient-pressure nickelate superconductors and establish a connection between structural configuration, electronic structure, and the emergence of superconductivity in nickelates.

cond-mat.supr-con↗
arXiv2026

Three-Dimensional Electronic Structures in Superconducting Ruddlesden-Popper Bilayer Nickelate Films

Beyond the quasi-two-dimensional (2D) paradigm of cuprates, the role of the third dimension of the Ruddlesden-Popper bilayer nickelates is essential to decoding their superconducting mechanism. Here, using angle-resolved photoemission spectroscopy (ARPES) with varied photon energies, we systematically investigate the electronic band structures in three dimensions for superconducting (La,Pr,Sm)$_3$Ni$_2$O$_7$/SrLaAlO$_4$ thin films (superconducting onset temperature $T_c^{\text{onset}} \sim 48$ K) transferred via a cryogenic ultra-high vacuum suitcase. We reveal an orbital-dependent dimensionality: while the $d{x^2-y^2}$-dominant bands exhibit a quasi-2D character, the $d{z^2}$-dominant band displays a finite $k_z$ dispersion. Finite energy gaps are identified on all observed bands across multiple high-symmetry directions. Systematic temperature-dependent analysis characterizes the superconducting nature of the gap on the $d{z^2}$-derived band, revealing a large gap $Δ\sim 18$ meV and a ratio $2Δ/k_BT_c\sim 8$ exceeding the weak-coupling BCS limit. The suppression of spectral weight near the Fermi level persists above the superconducting transition temperature. Ubiquitous waterfall-like spectral features evidence the presence of electron interactions. These results underscore the role of the $d_{z^2}$ orbital and correlations, placing constraints on theoretical models for nickelate superconductivity.

cond-mat.supr-con↗
arXiv2026

Finding Quasars behind the Galactic Plane. IV. Candidate Selection from Chandra with Random Forest

Quasar samples remain severely incomplete at low Galactic latitudes because of strong extinction and source confusion. We conduct a systematic search for quasars behind the Galactic plane using X-ray sources from the Chandra Source Catalog (CSC 2.1), combined with optical data from Gaia DR3 and mid-infrared data from CatWISE2020. Using spectroscopically confirmed quasars and stellar-type objects from data sets including DESI, SDSS, and LAMOST, we apply a Random Forest classifier to identify quasar candidates, with stellar contaminants suppressed using Gaia proper-motion constraints. Photometric redshifts are estimated for the candidates using a Random Forest regression model. Applying this framework to previously unclassified CSC sources, we identify 7570 quasar candidates, including 1060 Galactic Plane Quasar (GPQ) candidates at |b|<20°, of which 551 are high-confidence candidates. Relative to the previously known GPQ sample, our selected GPQs reach lower optical and X-ray fluxes, improving sensitivity to low-flux GPQs. In addition, both the GPQ candidates and known GPQs display harder X-ray spectra than the all-sky quasar sample, consistent with increased absorption through the Galactic plane. Pilot spectroscopy confirms two high-confidence GPQ candidates as quasars at spectroscopic redshifts of z=1.2582 and z=1.1313, and further spectroscopic follow-up of the GPQ sample is underway. This work substantially improves the census of GPQs and provides a valuable target sample for future spectroscopic follow-up, enabling the use of GPQs to refine the reference frames for astrometry and probe the Milky Way interstellar and circumgalactic media with the absorption features of GPQs.

astro-ph.GA↗
arXiv2026

Superconductivity onset above 60 K in ambient-pressure nickelate films

Ambient-pressure superconductivity in nickelates has been capped at an onset transition temperature ($T_{c}^{onset}$) of ~50 K, a value that remains lower than the cuprate (~133 K) and iron-based (~55 K) counterparts, despite the promise shown under high pressure. Here, we report ambient-pressure superconductivity onset at ~63 K in epitaxial (La,Pr)3Ni2O7 thin films grown under compressive strain on SrLaAlO4 substrates. This $T_{c}$ leap is enabled by pushing our gigantic-oxidative atomic-layer-by-layer epitaxy (GAE) method into an extreme non-equilibrium growth regime. It simultaneously enhances kinetics via higher temperatures and achieves full oxygenation in situ without post-annealing. Synchrotron X-ray diffraction and scanning transmission electron microscopy confirm that this approach yields films of large-scale crystalline purity, overcoming the inherent metastability of the strained superconducting phase. Transport measurements reveal a zero-resistance temperature ($T_{c}^{zero}$) reaching ~37 K, while mutual inductance measurements demonstrate a robust diamagnetic transition starting at ~23 K. These films exhibit a systematic evolution in their normal-state resistivity-temperature curve: the power-law exponent $α$ evolves from Fermi-liquid-like ($α$ ~2) at lower $T_{c}^{onset}$ to strange-metal-like ($α$ ~1) in higher $T_{c}^{onset}$ samples, directly linking the enhanced superconductivity to non-Fermi liquid behavior. Mapping the vortex melting phase diagram by the mutual inductance technique further reveals 2D melting limit suppressed to near zero, which demonstrates significantly stronger interlayer coupling than that of cuprates. These results identify the nickelates as an ambient-pressure strange-metal high-temperature superconductors with strong interlayer coupling.

cond-mat.supr-con↗
arXiv2026

Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills

Large language model (LLM) agents are moving beyond prompting alone. ChatGPT marked the rise of general-purpose LLM assistants, DeepSeek showed that on-policy reinforcement learning with verifiable rewards can improve reasoning and tool use, and OpenClaw highlights a newer direction in which agents accumulate persistent memory and reusable skills. Yet the research landscape remains fragmented across post-training, retrieval, memory, and skill systems. This survey studies these developments under a single notion of \emph{adaptation}: improving an agent, its tools, or their interaction after pretraining. We organize the field with a four-paradigm framework spanning agent adaptation and tool adaptation. On the agent side, A1 (tool-execution-signaled) and A2 (agent-output-signaled) improve the agent itself through supervised fine-tuning, preference optimization, and reinforcement learning with verifiable rewards. On the tool side, T1 (agent-agnostic) provides reusable pre-trained modules any agent can call, while T2 (agent-supervised) uses the agent's outputs to train memory systems, skill libraries, or lightweight subagents. Using this framework, we review post-training methods, adaptive memory architectures, and agent skills; compare their trade-offs in cost, flexibility, and generalization; and summarize evaluation practices across deep research, software development, computer use, and drug discovery. We conclude by outlining open problems in agent-tool co-adaptation, continual learning, safety, and efficient deployment.

cs.AI↗
arXiv2026

MagRobot:An Open Simulator for Magnetically Navigated Robots

Magnetic navigation systems, including magnetic tracking systems and magnetic actuation systems, have shown great potential for occlusion-free localization and remote control of intracorporeal medical devices and robots in minimally invasive medicine, such as capsule endoscopy and cardiovascular intervention. However, the design of magnetically navigated robots remains heavily reliant on experimental prototyping, which is time-consuming and costly. Furthermore, there is a lack of a consistent experimental environment to compare and benchmark the hardware and algorithms across different magnetic navigation systems. To address these challenges, we propose the first universal open-source simulation platform to facilitate research, design and benchmarking of magnetically navigated robots. Our simulator features an intuitive graphical user interface that enables the user to efficiently design, visualize, and analyze magnetic navigation systems for both rigid and soft robots. The proposed simulator is versatile, which can simulate both magnetic actuation and magnetic tracking tasks in diverse medical applications that involve deformable anatomies. The proposed simulator provides an open development environment, where the user can load third-party anatomical models and customize both hardware and algorithms of magnetic navigation systems. The fidelity of the simulator is validated using both phantom and ex vivo experiments of magnetic navigation of a continuum robot and a capsule robot with diverse magnetic actuation setups. Three use cases of the simulator, i.e., bronchoscopy, endovascular intervention, and gastrointestinal endoscopy, are implemented to demonstrate the functionality of the simulator. It is shown that the configuration and algorithms of magnetic navigation systems can be flexibly designed and optimized for better performance using the simulator.

cs.RO↗
arXiv2026

Time-reversal symmetry breaking superconductivity with electronic glass in nickelate (La, Pr, Sm)3Ni2O7 films

The discovery of Ruddlesden-Popper (R-P) nickelate superconductors under high pressure heralds a new chapter of high-transition temperature (high-Tc) superconductivity. Recently, ambient-pressure superconductivity is achieved in R-P bilayer nickelate thin films through epitaxial compressive strain, unlocking the potential for understanding the nature of the unconventional superconductivity. Here, through electrical transport study, we report the discovery of time-reversal symmetry (TRS) breaking superconductivity with electronic glass in bilayer nickelate (La, Pr, Sm)3Ni2O7 films. It emerges in the lower-temperature regime of superconducting transition to the zero-resistance state, and is captured by three remarkable characteristics: 1. Unconventional magnetoresistance hysteresis, the direct evidence of TRS breaking, which is robust under different magnetic field orientations and differs fundamentally from trapped vortices or long-range-ordered magnetism. Successive oxygen reductions simultaneously weaken both the superconductivity and hysteresis, revealing their mutual connections to selective electronic orbitals. 2. Magnetic field history-dependence and zero-field non-reciprocity in the current-voltage responses, further substantiating the intrinsic and spontaneous TRS breaking. 3. Logarithmically slow resistance relaxations upon the removal of magnetic field, the hallmarks of glassy dynamics. Distinguished by the striking magnetic field history- and time-dependent properties, our findings uncover an unprecedented superconducting state in the nickelate superconductors, providing phenomenological and conceptual advances for future research on high-Tc superconductivity.

cond-mat.supr-con↗
arXiv2026

Preparation and optimization of high-temperature superconducting Ruddlesden-Popper nickelate thin films

The discovery of ambient-pressure nickelate high-temperature superconductivity provides a new platform for probing the underlying superconducting mechanisms. However, the thermodynamic metastability of Ruddlesden-Popper nickelates Lnn+1NinO3n+1 (Ln = lanthanide) presents significant challenges in achieving precise control over their structure and oxygen stoichiometry. This study establishes a systematic approach for growing phase-pure, high-quality Ln3Ni2O7 thin films on LaAlO3 and SrLaAlO4 substrates using gigantic-oxidative atomic-layer-by-layer epitaxy. The films grown under an ultrastrong oxidizing ozone atmosphere are superconducting without further post annealing. Specifically, the optimal Ln3Ni2O7/SrLaAlO4 superconducting film exhibits an onset transition temperature (Tc,onset) of 50 K. Four critical factors governing the crystalline quality and superconducting properties of Ln3Ni2O7 films are identified: 1) precise cation stoichiometric control suppresses secondary phase formation; 2) complete atomic layer-by-layer coverage coupled with 3) optimized interface reconstruction minimizes stacking faults; 4) accurate oxygen content regulation is essential for achieving a single superconducting transition and high Tc,onset. These findings provide valuable insights for the layer-by-layer epitaxy growth of diverse oxide high-temperature superconducting films.

cond-mat.supr-con↗