What is SciMaster？
SciMaster is a general-purpose scientific research agent jointly developed by Shanghai Jiao Tong University and DP Technology. By integrating a wide range of research tools and intelligent technologies, it offers efficient and user-friendly support for researchers across various domains. SciMaster supports diverse applications such as investigating bottlenecks in quantum computing, analyzing methods and findings in exoplanet detection, running molecular dynamics simulations for drug screening, facilitating multi-agent cooperative learning, and studying the application of 2D materials in electronics. It can generate detailed research reports to help researchers quickly grasp progress and results, significantly boosting research productivity.
Key Features of SciMaster
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Multimodal Search: SciMaster supports three search modes—WebSearch, WebParse, and PaperSearch—to access comprehensive internet data and vast scientific literature, including papers, datasets, news, and patents.
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Expert-Level Reports: Based on the retrieved information, SciMaster can generate in-depth research reports, helping users quickly understand the current landscape and advancements in a given field.
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Scientific Tool Library: SciMaster integrates a variety of scientific tools, offering both “manual invocation” and “automatic recommendation.” Researchers can either select tools on demand or allow SciMaster to choose and use the most suitable ones automatically.
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Chain-of-Thought Editing: Users can pause SciMaster’s reasoning process at any time to inspect its logic, adjust task decomposition, execution order, and focus areas in real time.
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Experimental Ecosystem Integration: SciMaster can directly connect with Uni-Lab’s MCP services, seamlessly integrating laboratory instruments and software to build a complete “dry-wet closed-loop” experimental ecosystem encompassing software, hardware, researchers, and data.
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Detailed Report Generation: It produces comprehensive scientific reports with full citations and direct links to referenced literature, facilitating further exploration.
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Visualization Support: SciMaster uses charts and visual data representations to help users intuitively understand complex information.
Official Website
- Website: https://scimaster.bohrium.com/
Application Scenarios of SciMaster
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Quantum Computing Bottlenecks: Assists researchers in identifying solutions through data analysis and model optimization.
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Exoplanet Detection: Supports astronomical research by analyzing observational data and simulation outcomes.
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Molecular Dynamics in Drug Screening: Accelerates drug development by processing molecular interaction data and optimizing simulations.
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Multi-Agent Cooperative Learning: Helps explore cooperation strategies in AI by simulating and optimizing agent behaviors.
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2D Materials in Electronics: Advances research in electronics by analyzing properties and simulating applications of materials like graphene.
