Browsing by Subject "Secondary batteries"

Now showing 1 - 2 of 2

Open Access
Phenothiazine-based polymer cathode materials with ultrahigh power densities for lithium ion batteries
(American Chemical Society, 2018) Peterson, B. M.; Ren, D.; Shen, L.; Wu, Y. -C. M.; Ülgüt, Burak; Coates, G. W.; Abruna, H. D.; Fors, B. P.
Lithium ion batteries (LIBs) currently deliver the highest energy density of any known secondary electrochemical energy storage system. However, new cathode materials, which can deliver both high energy and power densities, are needed to improve LIBs. Herein, we report on the synthesis of a new organic-based redox-active material centered about phenothiazine and phenylenediamine units. Improved Coulombic efficiencies and greater capacity retention during cycling are observed through the copolymerization of a phenothiazine-based monomer that yields cross-linked materials. With this as the positive electrode in Li-coin cells, high specific capacities (150 mAh/g) are delivered at very positive operating voltages (2.8−4.3 V vs Li+ /Li), yielding high energy densities. The material has low charge transfer resistance as verified by electrochemical impedance spectroscopy, which contributes in delivering previously unseen power densities in coin cells for organic-based cathodes. Excellent retention of capacity (82%) is observed at ultrafast discharge rates (120 C).
Open Access
Zero-free-parameter modeling approach to predict the voltage of batteries of different chemistries and supercapacitors under arbitrary load
(Electrochemical Society, Inc., 2017) Özdemir, E.; Uzundal, C. B.; Ulgut, B.
Performance modeling of electrochemical energy storage systems is gathering increasingly higher attention in recent years. With the ever increasing power demand of mobile applications, predicting voltage behavior under different load profiles is of utmost importance for communications, automotive and consumer electronics. The ideal modelling approach needs not only to accurately predict the response of the battery, but also be robust, easy to implement and have low computational complexity. We will present a new algorithm that is algebraically straightforward, that has no adjustable parameters and that can accurately predict the voltage response of batteries and supercapacitors. The approach works well in a variety of discharge profiles ranging from simple long DC discharge/charge profiles to pulse schemes based on drive schedules published by regulatory bodies. Our approach is based on Electrochemical Impedance Spectroscopy measurements done on the system to be predicted. The spectrum is used in the frequency domain without any further processing to predict the fast moving portion of the voltage in the frequency domain. DC response is added in through a straightforward lookup table. This widely applicable approach can predict the voltage of with less than 1% error, without any adjustable parameters to a large variety of discharge profiles.