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Researcher profile

Sanfeng Wu

Sanfeng Wu contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
cond-mat.mtrl-scicond-mat.mes-hallcond-mat.str-elArtificial Intelligencephysics.app-phphysics.data-anRobotics

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Published work

6 published item(s)

preprint2026arXiv

Qumus: Realization of An Embodied AI Quantum Material Experimentalist

While modern Large Language Models (LLMs) and agentic artificial intelligence (AI) have demonstrated transformative capabilities in digital domains, the realization of embodied AI capable of real-world scientific discovery remains a difficult frontier. The advancements are hindered by the inherent complexity of integrating high-level reasoning, multimodal information processing and real-time physical execution. Here we introduce Qumus, the first AI quantum materials experimentalist. Physically embodied within a robotic mini-laboratory, Qumus is an intelligent, multimodal, and multi-agent system designed for the creation and nano-processing of atomically thin two-dimensional (2D) materials and stacked van der Waals (vdW) structures. Qumus autonomously navigates the full scientific cycle, from hypothesis generation and protocol planning to multi-step experimental execution, result analysis and reporting, acting as an experimentalist. Markedly, the system has achieved, for the first time, the AI-creation of graphene, as well as the first AI-fabrication of complex nanodevices including atomically thin field-effect transistors via vdW stacking. Qumus excels at these tasks by demonstrating autonomous error correction and closed-loop experimentation. Our results establish a generalizable framework for self-improving embodied AI systems that learn directly from the quantum world, opening a pathway toward accelerated discovery in quantum materials, electronics and beyond.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Evidence for a Monolayer Excitonic Insulator

The interplay between topology and correlations can generate a variety of quantum phases, many of which remain to be explored. Recent advances have identified monolayer WTe2 as a promising material for doing so in a highly tunable fashion. The ground state of this two-dimensional (2D) crystal can be electrostatically tuned from a quantum spin Hall insulator (QSHI) to a superconductor. However, much remains unknown about the gap-opening mechanism of the insulating state. Here we report evidence that the QSHI is also an excitonic insulator (EI), arising from the spontaneous formation of electron-hole bound states (excitons). We reveal the presence of an intrinsic insulating state at the charge neutrality point (CNP) in clean samples and confirm the correlated nature of this charge-neutral insulator by tunneling spectroscopy. We provide evidence against alternative scenarios of a band insulator or a localized insulator and support the existence of an EI phase in the clean limit. These observations lay the foundation for understanding a new class of correlated insulators with nontrivial topology and identify monolayer WTe2 as a promising candidate for exploring quantum phases of ground-state excitons.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Landau Quantization and Highly Mobile Fermions in an Insulator

In strongly correlated materials, quasiparticle excitations can carry fractional quantum numbers. An intriguing possibility is the formation of fractionalized, charge-neutral fermions, e.g., spinons and fermionic excitons, that result in neutral Fermi surfaces and Landau quantization in an insulator. While previous experiments in quantum spin liquids, topological Kondo insulators, and quantum Hall systems have hinted at charge-neutral Fermi surfaces, evidence for their existence remains far from conclusive. Here we report experimental observation of Landau quantization in a two dimensional (2D) insulator, i.e., monolayer tungsten ditelluride (WTe$_{2}$), a large gap topological insulator. Using a detection scheme that avoids edge contributions, we uncover strikingly large quantum oscillations in the monolayer insulator's magnetoresistance, with an onset field as small as ~ 0.5 tesla. Despite the huge resistance, the oscillation profile, which exhibits many periods, mimics the Shubnikov-de Haas oscillations in metals. Remarkably, at ultralow temperatures the observed oscillations evolve into discrete peaks near 1.6 tesla, above which the Landau quantized regime is fully developed. Such a low onset field of quantization is comparable to high-mobility conventional two-dimensional electron gases. Our experiments call for further investigation of the highly unusual ground state of the WTe$_{2}$ monolayer. This includes the influence of device components and the possible existence of mobile fermions and charge-neutral Fermi surfaces inside its insulating gap.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

One-Dimensional Luttinger Liquids in a Two-Dimensional Moiré Lattice

The Luttinger liquid (LL) model of one-dimensional (1D) electronic systems provides a powerful tool for understanding strongly correlated physics including phenomena such as spin-charge separation. Substantial theoretical efforts have attempted to extend the LL phenomenology to two dimensions (2D), especially in models of closely packed arrays of 1D quantum wires, each being described as a LL. Such coupled-wire models have been successfully used to construct 2D anisotropic non-Fermi liquids, quantum Hall states, topological phases, and quantum spin liquids. However, an experimental demonstration of high-quality arrays of 1D LLs suitable for realizing these models remains absent. Here we report the experimental realization of 2D arrays of 1D LLs with crystalline quality in a moiré superlattice made of twisted bilayer tungsten ditelluride (tWTe$_{2}$). Originating from the anisotropic lattice of the monolayer, the moiré pattern of tWTe$_{2}$ hosts identical, parallel 1D electronic channels, separated by a fixed nanoscale distance, which is tunable by the interlayer twist angle. At a twist angle of ~ 5 degrees, we find that hole-doped tWTe$_{2}$ exhibits exceptionally large transport anisotropy with a resistance ratio of ~ 1000 between two orthogonal in-plane directions. The across-wire conductance exhibits power-law scaling behaviors, consistent with the formation of a 2D anisotropic phase that resembles an array of LLs. Our results open the door for realizing a variety of correlated and topological quantum phases based on coupled-wire models and LL physics.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Deep-Learning-Enabled Fast Optical Identification and Characterization of Two-Dimensional Materials

Advanced microscopy and/or spectroscopy tools play indispensable role in nanoscience and nanotechnology research, as it provides rich information about the growth mechanism, chemical compositions, crystallography, and other important physical and chemical properties. However, the interpretation of imaging data heavily relies on the "intuition" of experienced researchers. As a result, many of the deep graphical features obtained through these tools are often unused because of difficulties in processing the data and finding the correlations. Such challenges can be well addressed by deep learning. In this work, we use the optical characterization of two-dimensional (2D) materials as a case study, and demonstrate a neural-network-based algorithm for the material and thickness identification of exfoliated 2D materials with high prediction accuracy and real-time processing capability. Further analysis shows that the trained network can extract deep graphical features such as contrast, color, edges, shapes, segment sizes and their distributions, based on which we develop an ensemble approach topredict the most relevant physical properties of 2D materials. Finally, a transfer learning technique is applied to adapt the pretrained network to other applications such as identifying layer numbers of a new 2D material, or materials produced by a different synthetic approach. Our artificial-intelligence-based material characterization approach is a powerful tool that would speed up the preparation, initial characterization of 2D materials and other nanomaterials and potentially accelerate new material discoveries.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

High mobility in a van der Waals layered antiferromagnetic metal

Magnetic van der Waals (vdW) materials have been heavily pursued for fundamental physics as well as for device design. Despite the rapid advances, so far magnetic vdW materials are mainly insulating or semiconducting, and none of them possesses a high electronic mobility - a property that is rare in layered vdW materials in general. The realization of a magnetic high-mobility vdW material would open the possibility for novel magnetic twistronic or spintronic devices. Here we report very high carrier mobility in the layered vdW antiferromagnet GdTe3. The electron mobility is beyond 60,000 cm2 V-1 s-1, which is the highest among all known layered magnetic materials, to the best of our knowledge. Among all known vdW materials, the mobility of bulk GdTe3 is comparable to that of black phosphorus, and is only surpassed by graphite. By mechanical exfoliation, we further demonstrate that GdTe3 can be exfoliated to ultrathin flakes of three monolayers, and that the magnetic order and relatively high mobility is retained in approximately 20-nm-thin flakes.

0 citations0 reviewsNo code linkedOpen access