Advanced simulation and modeling techniques: Develop more advanced computational models and algorithms to improve software capabilities for complex systems and high-precision predictions.

Machine Learning and AI Integration: Combine machine learning and AI techniques to improve software intelligence for data analysis and prediction.

Cloud computing and Big Data Analytics: Leverage cloud computing and big data technologies to provide more flexible and scalable thermodynamic analysis services and data management capabilities.

Interdisciplinary Integration: Integrating simulation and analysis techniques from thermodynamics with other subject areas to support the study of complex multi-physics problems.

Green and sustainability: Developing thermodynamic analysis tools that support green and sustainable development, helping to reduce energy consumption and environmental pollution.