A recent perspective paper published on arXiv explores the transformative impact of artificial intelligence (AI) and machine learning (ML) on chemical engineering. The paper highlights how these technologies are enhancing problem-solving across various applications, from atomic-scale simulations to industrial operations. It emphasizes a shift towards hybrid and physics-informed frameworks that integrate AI/ML with fundamental principles, enabling better accuracy, data scarcity management, and human-AI collaboration. The authors conclude that AI and ML are augmenting, not replacing, core chemical engineering principles, and their thoughtful integration is key to future advancements in autonomous and sustainable systems. AI
IMPACT Enhances predictive accuracy and enables human-AI collaboration in chemical engineering applications.
RANK_REASON The cluster contains a research paper published on arXiv detailing the application of AI/ML in chemical engineering. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- artificial intelligence
- arXiv
- CatalyzeX
- chemical engineering
- CORE Recommender
- DagsHub
- Gotit.pub
- Hugging Face
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- machine learning
- ScienceCast
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