Product introduction
Bohrium is a global AI-powered research cloud platform launched by Deepmodel Technology, designed to establish a future-oriented "AI for Science" workflow for researchers. The platform integrates proprietary scientific large models, over 160 million academic papers, multidisciplinary knowledge bases, and robust computing infrastructure, streamlining the entire research process from literature mining and experimental design to computational simulation and data analysis.
Serving as an exclusive innovation space for scientists, Bohrium significantly enhances knowledge acquisition and application efficiency through intelligent tools. The platform is fully integrated with the CARSI authentication system, serving faculty and students across more than 1,000 universities nationwide, and supports all-chain research activities ranging from basic research to industrial design.
Key Features
- Multimodal Academic Search: Leverages vast databases of papers and patents to support multi-dimensional searches including text, figures, PDFs, and molecular structures, providing semantic relevance ranking and intelligent summary generation.
- Specialized Scientific Large Models: Built-in vertical domain models such as DPA, Uni-Mol, Uni-RNA, and Uni-Fold, covering microscopic research scenarios like molecular dynamics and quantum chemistry.
- Cloud Computing Workbench: Integrates professional toolchains for first-principles calculations and molecular dynamics simulations, equipped with high-performance computing clusters and visual analysis environments to meet complex computational needs.
- AI Research Assistance: Utilizes large language technology for deep literature parsing, intelligent recommendation of experimental protocols, and result visualization, thereby improving research efficiency.
- Team Collaboration Management: Supports multi-role collaboration modes, offering version control, knowledge sharing, and task distribution features to facilitate efficient team workflows.
Application Scenarios
- Cross-disciplinary Literature Review: Quickly aggregates cutting-edge results from multiple fields, automatically generates research status reports, and significantly shortens the literature review cycle.
- Molecular Simulation and Design: Applied in drug discovery and new material development for high-throughput molecular dynamics simulations and property prediction.
- Experimental Parameter Optimization: Combines historical data with AI model recommendations to identify optimal experimental conditions, effectively reducing trial-and-error costs and increasing success rates.
- Teaching and Training: Provides interactive Notebook environments and supporting course systems to assist in teaching courses related to computational chemistry and AI for Science.
- Industrial R&D Validation: Supports full-process computational validation from laboratory exploration to industrial implementation, accelerating new product iteration and development.
