人工智能将重构化工研究范式

Core Viewpoint - The integration of artificial intelligence and big data is essential for advancing the fundamental theories and engineering technologies in the chemical industry, particularly in the context of national goals like carbon neutrality [1][2] Group 1: Advances in Chemical Theory - The chemical industry faces a significant lack of fundamental physical property data necessary for theoretical development and engineering technology updates, necessitating a new paradigm for acquiring chemical properties through AI methods [1] - Experts emphasize the need to deeply integrate theoretical calculations with artificial intelligence, highlighting the importance of traceability and accuracy in chemical big data for future intelligent design [1] - There is a call to accelerate the acquisition of modern chemical foundational data, creating a comprehensive chemical big database based on various dimensions such as chemical industrial processes, experimental research, and literature data [1] Group 2: High-Quality Development in the Chemical Industry - The application of artificial intelligence raises higher demands for the reliability and standardization of industry data, pushing for a shift from experience-driven to data-driven chemical R&D [2] - It is crucial to develop clear and specific data element application scenarios to leverage collaborative advantages and promote data sharing and circulation, thereby unlocking the value of data elements [2] - Establishing a unified regulatory mechanism and a secure technical system is necessary to facilitate sustainable data development, alongside building an ecosystem for data providers, users, and service providers to achieve shared governance [2]