Actively Programming Battery Chemistry via Pulse Modulation

Area of Science:

• Electrochemistry
• Materials Science
• Energy Storage

Background:

• High-energy electrochemical energy storage is limited by kinetic and thermodynamic bottlenecks during steady-state operation.
• Conventional constant-current charging methods cannot fully control complex battery chemistries.

Purpose of the Study:

• To introduce pulse modulation as a paradigm shift for active, real-time regulation of multiscale battery chemistry.
• To explore the use of nonequilibrium transients for decoupling entangled physicochemical processes.

Main Methods:

• Investigating the chemical physics of pulse modulation, including parameter space analysis (amplitude, frequency, waveform).
• Evaluating the integration of operando diagnostics with physics-informed machine learning.
• Utilizing multiphysics modeling and closed-loop control for adaptive protocols.

Main Results:

• Pulsed excitation allows temporal decoupling of ion solvation, interfacial charge transfer, and mass transport.
• Pulse parameters influence concentration polarization, solid-electrolyte interphase evolution, and metal deposition morphology.
• Adaptive protocols can dynamically compensate for state-of-health drift and thermal fluctuations.

Conclusions:

• Pulse modulation enables active control over battery chemistry, overcoming limitations of steady-state operation.
• The integration of advanced diagnostics and machine learning is key to optimizing pulse protocols.
• This approach paves the way for software-defined chemistry and next-generation closed-loop battery management systems.