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On-premise AI agents: a future foundation for education, academia, and industry

The rise of the digital materials ecosystem

Robust global optimization of atomic structures via a learning loss-informed on-the-fly firefly algorithm

An integrated energy system scheduling method considering year-round load variations based on deep reinforcement learning

AI agents: opportunity, hype, and the way through

DIVE-to-design: how a multi-agent workflow converts figure-centric literature into an ai-native hydrogen storage discovery engine

StableOx-Cat agent: an AI agent for exploring stable metal oxide electrocatalysts

AI agents for solid electrolytes: opportunities, challenges, and future directions

AI as a catalyst for transforming scientific research: a perspective

From large language models to AI agents in energy materials research: enabling discovery, design, and automation

Knowledge-extractor: a self-evolving scientific framework for hydrogen energy research driven by AI agents

Exploring structures of nanoclusters combining high-dimensional neural network potentials with unsupervised machine learning algorithms