arXiv subjects

Zichao Ye

Publications and source records attributed to Zichao Ye.

4 recordsLinked to original sources

arXiv2026

DianShi-RxnDB: A Large-Scale, Fine-Grained Organic Reaction Data Platform Built via a Fully Automated Pipeline for Researchers and AI Agents

High-quality structured organic reaction data are essential for developing artificial intelligence for chemistry (AI4Chem), yet much of this knowledge remains dispersed across patent text, images, and reaction schemes. We present DianShi-RxnDB, a large-scale, fine-grained organic reaction data platform built via a fully automated extraction and normalization pipeline integrating patent text, images, and reaction schemes. Its corpus covers organic synthesis patents from the USPTO and EPO published between 1976 and 2025, yielding approximately 24 million reaction instances, of which approximately 14.8 million (61.7%) pass automated qualification checks. Each instance represents a specific single-step experiment recording participants, roles, quantities, temperatures, reaction times, yields, experimental procedures, and provenance links to source patents. In a manual evaluation of 1,300 sampled qualified instances, the micro-averaged field-level accuracy was 92.95%. A matched comparison with Pistachio further indicated advantages in deduplicated record counts, representation granularity, and field-level exact agreement. The platform provides a Web research workbench for searching, filtering, comparing, and source-verifying records, and a Model Context Protocol (MCP) service offering AI agents composable structured retrieval tools. DianShi-RxnDB is available at https://dianshi.opendatalab.org.cn/ .

cs.CL↗

arXiv2026

AgentPanel: Toward a New Paradigm for Human--AI Collaboration in Exploring Scientific Questions

Identifying promising scientific ideas remains an important challenge in research practice. Researchers commonly rely on small-group discussions or one-to-one interactions with a single large language model, yet these approaches often expose them to only a limited range of perspectives and directions. We present AgentPanel, a multi-agent forum for human--AI collaboration in scientific exploration. Heterogeneous agents asynchronously discuss scientific questions in a forum-style environment, while researchers can submit questions, browse and organize candidate ideas, engage agents in follow-up interactions, and optionally generate post-hoc summary reports. We evaluate AgentPanel in terms of idea quality, exploration breadth, interaction effectiveness, candidate-selection efficiency, and practical utility. Offline experiments show that AgentPanel outperforms a centralized multi-agent debate baseline. A human study with 20 participants further shows that users value AgentPanel for perspective diversity and exploration support. In experience-based comparisons with commonly used LLM tools, 65\% of participants favored AgentPanel for both breadth of research directions and overall suitability for early-stage exploration. The platform is publicly available at https://agentpanel.cc/.

cs.AI↗

arXiv2025

Incorporating Si into Sb2Se3: Tailoring Optical Phase Change Materials via Nanocomposites

Chalcogenide-based optical phase change materials (OPCMs) exhibit a large contrast in refractive index when reversibly switched between their stable amorphous and crystalline states. OPCMs have rapidly gained attention due to their versatility as nonvolatile amplitude or phase modulators in various photonic devices. However, open challenges remain, such as achieving reliable response and transparency spanning into the visible spectrum, a combination of properties in which current broadband OPCMs (e.g., Ge2Sb2Se4Te1, Sb2Se3, or Sb2S3) fall short. Discovering novel materials or engineering existing ones is, therefore, crucial in extending the application scope of OPCMs. Here, we use magnetron co-sputtering to study the effects of Si doping into Sb2Se3. We employ ellipsometry, X-ray diffraction, Raman spectroscopy, and scanning and transmission electron microscopy to investigate the effects of Si doping on the optical properties and crystal structure and compare these results with those from first principles calculations. Moreover, we study the crystallization and melt-quenching of thin films via nano-differential scanning calorimetry (NanoDSC). Our experiments demonstrate that 20% Si doping increases the transparency window in both states, specifically to 800 nm (1.55 eV) in the amorphous phase, while reducing power consumption by lowering the melting temperature. However, this reduction comes at the cost of reducing the refractive index contrast between states and slowing the kinetics of the phase transition.

cond-mat.mtrl-sci↗

arXiv2024

GRUtopia: Dream General Robots in a City at Scale

Recent works have been exploring the scaling laws in the field of Embodied AI. Given the prohibitive costs of collecting real-world data, we believe the Simulation-to-Real (Sim2Real) paradigm is a crucial step for scaling the learning of embodied models. This paper introduces project GRUtopia, the first simulated interactive 3D society designed for various robots. It features several advancements: (a) The scene dataset, GRScenes, includes 100k interactive, finely annotated scenes, which can be freely combined into city-scale environments. In contrast to previous works mainly focusing on home, GRScenes covers 89 diverse scene categories, bridging the gap of service-oriented environments where general robots would be initially deployed. (b) GRResidents, a Large Language Model (LLM) driven Non-Player Character (NPC) system that is responsible for social interaction, task generation, and task assignment, thus simulating social scenarios for embodied AI applications. (c) The benchmark, GRBench, supports various robots but focuses on legged robots as primary agents and poses moderately challenging tasks involving Object Loco-Navigation, Social Loco-Navigation, and Loco-Manipulation. We hope that this work can alleviate the scarcity of high-quality data in this field and provide a more comprehensive assessment of Embodied AI research. The project is available at https://github.com/OpenRobotLab/GRUtopia.

cs.RO↗