The development of next-generation energy technologies is essential for building a sustainable future, supporting advances from electric mobility to renewable energy storage. As the demand for efficient, safe, and scalable energy solutions grows, new battery systems and energy harvesting systems are gaining attention.

At SONG Research Group, we advance energy systems through AI-powered modeling, multiscale simulation, and optimization-driven design.

Our research covers:

• Potassium-ion batteries (K-ion batteries) for cost-effective, resource-abundant storage.

• Sodium-ion batteries (Na-ion batteries) for cost-effective, resource-abundant storage.

• All-solid-state batteries (ASSBs) with enhanced safety and high energy density.

• Energy harvesting systems that convert ambient energy into usable electrical power for self-sustaining devices.

By combining computational engineering with physical insights, we aim to accelerate the design and deployment of advanced storage and harvesting technologies.

Through simulation, AI, and next-generation materials engineering, SONG’S Lab is shaping the future of intelligent, sustainable energy systems.

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Advances in Nano-Bio systems are driving breakthroughs in diagnostics, therapeutics, and personalized medicine. As the need for precise, miniaturized, and intelligent biomedical technologies grows, innovation at the intersection of nanotechnology, biology, and computational engineering becomes critical.

At SONG Research Group, we design Nano-Bio systems through AI-powered modeling, multiscale simulation, and physics-informed optimization.

Our research includes:

• Plasmonic biosensors and biomedical devices for real-time, ultra-sensitive biomolecular detection.

• Organ-on-a-Chip platforms that replicate biological environments for drug development.

• Targeted drug delivery systems to enhance efficacy and minimize side effects.

By combining computational engineering, machine learning, and nanobiotechnology, we aim to create platforms that translate fundamental science into real-world impact.

SONG group is committed to advancing the next generation of smart, scalable biomedical systems.

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Artificial intelligence is reshaping engineering by enabling smarter, faster, and more efficient design, optimization, and deployment across fields from energy systems to biomedical platforms. As real-world applications grow increasingly complex, AI-driven approaches open new pathways for innovation.

At SONG Research Group, we integrate AI and computational techniques to advance simulation, modeling, and optimization processes.

Our research focuses on:

• Deep learning-based optimization for complex system and device design.

• Physics-informed neural networks (PINNs) to enhance simulation accuracy and efficiency.

• Data-driven multiscale modeling linking physical insights with computational methods.

• Bayesian optimization and reinforcement learning for adaptive, real-time design improvements.

By merging physical principles with AI, we aim to accelerate innovation across energy, bio-mechanical, and multiscale systems.

SONG group is committed to developing intelligent, data-driven engineering solutions for next-generation technologies.

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