Lithium-Ion Battery Dendrite Prediction Using Real-Time Simulation
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Solution Overview
Problem
Current methods for analyzing lithium dendrite growth in lithium-ion batteries are limited to post-charging and discharging imaging, lacking real-time simulation capabilities, which hinders the development of lithium metal electrodes due to issues like dendrite formation and corrosion.
Innovation Solution
A dendrite growth prediction method that calculates electronegativity and partial charges of electrode and electrolyte atoms, determines chemical reactions, and predicts dendrite growth based on these interactions, using a lithium secondary battery simulator, with the option to assess the effect of additives on suppressing dendrite growth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If post-charging and discharging imaging is used for dendrite analysis, then experimental analysis can be performed, but real-time simulation capability is lost
Solution Approach 1:
The patent creates a virtual copy of the lithium-ion battery system through a simulator that replicates dendrite growth behavior. The simulation model copies the essential physical and chemical processes of dendrite formation, allowing real-time observation and analysis without requiring actual battery charging/discharging cycles. This virtual replication enables both real-time simulation capability and accurate dendrite analysis simultaneously.
2Quantity of substance
If lithium metal electrode is used to achieve high energy density, then energy density is improved, but dendrite formation and corrosion problems occur
Solution Approach 1:
The simulator performs preliminary analysis of dendrite growth tendencies before actual battery operation. By calculating electronegativity values and partial charges of electrode and electrolyte atoms in advance, the system can predict which configurations are prone to dendrite formation. This preliminary assessment allows researchers to optimize electrode compositions and structures to prevent dendrite issues before they occur in actual high-energy-density lithium metal batteries.
Solution Approach 2:
The patent introduces electronegativity and partial charge calculations as intermediary parameters to assess dendrite formation risk. These intermediate measurements serve as indicators that bridge the gap between material composition and dendrite formation behavior. By monitoring these intermediary properties, the system can predict and prevent dendrite formation without requiring actual dendrite growth to occur, thus enabling the use of lithium metal electrodes while mitigating their inherent reliability problems.
3Measurement precision
If experimental testing on actual batteries is performed to evaluate additive suppression effects, then accurate results are obtained, but time and resource consumption increase
Solution Approach 1:
The simulator creates virtual copies of battery systems with different additive configurations to evaluate suppression effects. Instead of physically testing each additive combination in real batteries, the simulation replicates the electrochemical environment and predicts additive performance. This virtual testing approach maintains measurement precision by accurately modeling the interactions between additives and dendrite growth mechanisms, while dramatically improving productivity by eliminating the need for repeated physical battery assembly, charging, and disassembly cycles.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time simulation and prediction of dendrite growth, allowing for the evaluation of additive suppression effects without experimental testing on actual batteries, thereby improving the understanding and performance of lithium-ion batteries.
Implementation Method 1
calculating an electronegativity of electrode atoms and electrolyte atoms
Implementation Method 2
calculating partial charges of the electrode atoms and the electrolyte atoms from the electronegativity
Implementation Method 3
deriving an interaction between the electrode atoms and the electrolyte atoms on the basis of the partial charges
Data Source
AI summary
Disclosed therein are a dendrite growth prediction method and a computer program for predicting dendrite growth, which have an advantage of being able to simulate dendrite growth in real time like an actual battery using a lithium secondary battery simulator, thereby predicting dendrite growth at a molecular level according to a charging and discharging cycle and being able to shorten a prediction time by changing a calculation method for each electrode section, thereby rapidly predicting dendrite growth in real time. In addition, there is an advantage in which a specific additive is additionally added to the electrolyte, and thus whether dendrite growth is suppressed can be confirmed so that the dendrite suppression effect of a specific additive can be easily checked without an experiment using an actual lithium secondary battery.