Modified Chronoamperometry as an Evaluation Method for Li-Ion Batteries
Authors: Pinilla Sergio , Medina-Santos Jesús Inocente , Garcia - Quismondo Enrique , Marcilla Rebeca , Palma Jesus 
Published: February 2024

In the framework of new materials and next-generation batteries, the acceleration and quantification

of the improvements that these advances pose, have become a priority in the field. In this

regard, rate performance sits in an interesting spot. It is gaining more and more importance due

to the electrification of transportation but its quantitative analysis is usually overlooked.

In this regard, recently, new methodologies have been developed to allow the quantification of

the rate performance. [1] It has been shown that the parameters used for this quantification, can

be linked to intrinsic properties of the electrodes and materials, becoming a tool to further improve

their understanding and optimization.[2]

However, the usefulness of this methodology is damped by the slow acquisition of the rate

data by galvanostatic cycling, which at very low rates can take even weeks. This limitation leads

to reduced data density hampering the building of solid statistics to feed models.

To mitigate this problem, chronoamperometry has been proposed as an accelerated method

to acquire rate-performance data.[3] It has been proved that the low current/rate section of the

chronoamperometry indeed matches the data of the galvanostatic equivalent, and it has been

used as a way to characterize materials and electrodes.[4, 5] However, the high current/rate

section has proved much more challenging, showing inconsistent results across references and

a not well-understood dependence on materials that manifest as another contribution that difficult

the data interpretation. [6]

In this work, we focus on the high-rate behavior of the chronoamperometric response of the

electrodes. We show how this abnormal contribution can distort the fitting of the capacity-rate

curves highly affecting the quantification of the rate performance parameters. To avoid this distortion,

we have investigated the origin of the contribution by electrochemical impedance spectroscopy

and simulations, and developed a methodology to isolate and mitigate it. This leads to

more reliable datasets that permit very accurate fittings that match the galvanostatic data and

works for all the common LIBs materials tested.[7] These advances will surely boost the usefulness

and reliability of the technique as a way to characterize batteries.

(1) Heubner, C.; L¨ammel, C.; Nickol, A.; Liebmann, T.; Schneider, M.; Michaelis, A. Journal of

Power Sources 2018, 397, Publisher: Elsevier, 11–15.

(2) Tian, R.; Park, S.-H. H.; King, P. J.; Cunningham, G.; Coelho, J.; Nicolosi, V.; Coleman, J. N.

Nature Communications 2019, 10, Publisher: Nature Publishing Group, 1933.

(3) Heubner, C.; Seeba, J.; Liebmann, T.; Nickol, A.; B¨ orner, S.; Fritsch, M.; Nikolowski, K.;

Wolter, M.; Schneider, M.; Michaelis, A. Journal of Power Sources 2018, 380, 83–91.

(4) Pinilla, S.; Ryan, S.; McKeon, L.; Lian, M.; Vaesen, S.; Roy, A.; Schmitt, W.; Coleman, J. N.;

Nicolosi, V. Advanced Energy Materials 2023, 2203747.

(5) Tian, R.; Alcala, N.; O’Neill, S. J.; Horvath, D.; Coelho, J.; Griffin, A.; Zhang, Y.; Nicolosi, V.;

O’Dwyer, C.; Coleman, J. N. ACS Applied Energy Materials 2020, DOI: 10.1021/acsaem.

0c00034.

(6) Tian, R.; King, P. J.; Coelho, J.; Park, S. H.; Horvath, D. V.; Nicolosi, V.; O’Dwyer, C.; Coleman,

J. N. Journal of Power Sources 2020, 468, DOI: 10.1016/j.jpowsour.2020.228220.

(7) Manuscript under preparation.