Differential capacity analysis (DCA) for battery research with INTELLO

Importance of the Topic

Differential capacity analysis (DCA) offers detailed insight into electrochemical processes, phase transitions, and degradation in batteries. This method enhances understanding of complex chemistries and supports optimization of performance and lifetime.

Objectives and Study Overview

This study presents Application Note AN-BAT-015, detailing the principles and practical uses of dQ/dE plots. Four commercial cells with varying cathode chemistries (NMC, LFP) and Ni-MH are compared. DCA is used to resolve overlapping reactions, detect subtle phase changes, and monitor aging.

Methodology and Instrumentation

The differential capacity is defined as dQ/dE=|Qn+1−Qn|/(En+1−En). Data were collected using the INTELLO battery cycling platform integrated with the VIONIC potentiostat/galvanostat. Sampling was performed at low C‐rates (C/10 to 1C) to ensure equilibrium at each voltage step. Cycling protocols included:

• Coin cell (LIR2450): 1C and 0.1C between 2.8 V and 4.2 V.
• Cylinder cells (INR21700-33J, HTPFPR-18650): CCCV and CC cycling at 0.2C to 0.5C.
• Ni-MH cylinder (BK-3MCDE): 0.1C between 1.0 V and 1.5 V.

Main Results and Discussion

• Coin cell NMC-532: Lower C‐rate (0.1C) resolved four charging peaks and two discharge peaks versus only two at 1C, illustrating enhanced resolution of phase transitions.
• Aging study: After 100 cycles at 1C, decreasing peak heights and voltage shifts indicated lithium inventory loss and possible plating or electrolyte decomposition.
• INR21700-33J cylinder: Charge dQ/dE revealed three distinct peaks similar to NMC coin cell, confirming comparable cathode chemistry.
• HTPFPR-18650 LFP cell: Characteristic four‐peak profile in both charge and discharge cycles, consistent with LFP/graphite intercalation and phase transitions.
• Ni-MH cylinder: Single charge/discharge peaks at 1.4 V and 1.28 V correspond to Ni(OH)₂/NiOOH conversion.

Practical Implications and Benefits

DCA enables:

• Identification of subtle electrochemical events and phase changes.
• Non‐destructive aging diagnostics and loss‐of‐inventory monitoring.
• Quality control and materials screening in R&D and manufacturing.

Future Trends and Applications

Emerging directions include integrating DCA with advanced impedance spectroscopy, in‐situ spectroelectrochemistry, high‐throughput screening, and machine learning for automated feature extraction and predictive modeling.

Conclusion

Differential capacity analysis, especially when implemented on flexible platforms like INTELLO/VIONIC, delivers granular electrochemical insights across various cell formats and chemistries. Its ability to deconvolute overlapping processes makes it invaluable for battery development, diagnostics, and lifetime optimization.

References

• Long B.R. et al. Enabling High-Energy, High-Voltage Lithium-Ion Cells: Standardization of Coin-Cell Assembly, Electrochemical Testing, and Evaluation of Full Cells. J. Electrochem. Soc. 2016, 163, A2999.
• Torai S. et al. State-of-Health Estimation of LiFePO4/Graphite Batteries Based on a Model Using Differential Capacity. J. Power Sources 2016, 306, 62–69.