Poly(ethylene dioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) has emerged as a promising candidate for renewable, clean, and reliable energy generation from waste heat due to its thermoelectric properties. This largely stems from its tunable and potentially high electrical conductivity. However, the resulting small Seebeck coefficients diminish the thermoelectric efficiency. We employ dedoping methods making use of acido-base and redox dedoping in order to optimize its properties. In order to tune the charge carrier concentration in PEDOT:PSS thin films, aqueous solutions of readily available inorganic salts, namely, sodium hydrogen carbonate (NaHCO3), sodium sulfite (Na2SO3), and sodium borohydride (NaBH4), are introduced in different concentrations into PEDOT:PSS solutions before thin film fabrication. This yields optimized thermoelectric properties in terms of power factors up to 100 μW/K2 m. Changes in the electronic structure are characterized using UV–vis spectroscopy and XPS, while changes in the conformation are investigated using Raman spectroscopy. The thermoelectric quantities are compared for the redox dedopants regarding the absolute number of reducing equivalents.
Two of the main factors influencing the performance of Li-ion battery (LIB) electrodes are the kinetic losses due to the charge transfer resistance of the active material ( R ct ) and the ionic transport resistance in the electrolyte phase within the electrode pores ( R ion ). Seeking to increase the energy density of LIBs, ever higher active material loadings are applied, resulting in thicker electrodes for which R ion becomes dominant. As electrochemical impedance spectroscopy is commonly used to quantify R ct of electrodes, understanding the impact of R ion on the impedance response of thick electrodes is crucial. By use of a simplified transmission line model (TLM), we simulate the impedance response of electrodes as a function of electrode loading. This will be compared to the impedance of graphite anodes (obtained using a micro-reference electrode), demonstrating that their impedance response varies from purely kinetically limited at 0.6 mAh cm−2 to purely transport limited at 7.5 mAh cm−2. We then introduce a simple method with which R ct and R ion can be determined from the electrode impedance, even under transport limited conditions. Finally, we show how the initially homogenous ionic current distribution across porous electrodes under kinetically limited conditions becomes severely inhomogeneous under transport limited conditions.
The influence of calendering and laser structuring on the pore structure and electrochemical performance of electrodes is reported. Graphite anodes of varying bulk porosity were micro structured with pulsed laser radiation. Using scanning electron microscopy and energy-dispersive X-ray spectroscopy, laser structuring was found to release superficial pore clogging caused by calendering and to result in binder agglomerates on the electrode surfaces. Structured electrodes showed higher porosities than their unstructured counterparts due to a thickness increase and material removal, but no significant change in the pore size distribution was detected using mercury intrusion porosimetry. Electrochemical impedance spectra of symmetric battery cells revealed increasing ionic resistances and tortuosities for decreasing electrode porosities. Laser structuring significantly reduced the underlying lithium-ion diffusion limitations at all porosity levels. In a discharge rate test, performance deteriorations at high currents were found to be amplified by calendering and could be diminished by electrode structuring. The performance improvements by laser structuring moved towards lower C-rates for stronger compressed anodes. Despite their growth in thickness and porosity, laser structured graphite anodes showed a higher volumetric energy density at high currents than unstructured electrodes, which demonstrates the potential of electrode structuring for highly compressed anodes.
Highly performing lithium‐ion batteries are essential for the electrification of the transport sector. However, the two performance criteria, high power density and high energy density, inversely correlate with each other via the mass loading of the electrodes. To achieve high charging and discharging rates at high energy densities, structuring of electrodes is a proven method. Currently, structures are mostly realized by laser ablation, which comes along with material loss and low process rates. Herein, a concept for electrode structuring through mechanical embossing in a high‐throughput roll‐to‐roll process is elaborated. Different integration options are described and the challenges are discussed. To provide a proof of concept, a hand‐operated embossing device is built and used to structure graphite anodes. In a rate capability test, an increase in discharge capacity at medium C‐rates by up to 14.3% is observed.
Electrochemical Impedance Spectroscopy (EIS) is a powerful tool, as it is a non-invasive technique that allows to understand and deconvolute internal resistances of electrochemical systems. However, great caution has to be exercised when choosing a proper equivalent circuit for graphite anodes in Li-ion batteries and assigning resistances to specific mechanisms such as solid-electrolyte-interphase (SEI, at the electrolyte-SEI interface) or charge transfer resistance (at the SEI-graphite interface). The ionic resistance in the electrolyte of the porous electrode is hereby often overlooked or assumed negligibly small. Such assumptions lead to improper equivalent circuits and the desired analysis of a specific resistance is questionable. In this study we present a rigorous impedance analysis where the equivalent circuit assigned to the electrode is validated through measurements in multiple configurations. First, we show how the impedance response of a graphite electrode at standard loading (~3mAh/cm2) changes depending on its state of charge (SOC, see Fig. 1) and assign a preliminary equivalent circuit based on the transmission line model, similar to Refs. 1 and 2. We then validate the initial assumptions by changing the graphite loading - a simple but impactful procedure - as all resistances associated with the active material surface area are expected to directly correlate to the change in loading. Both SEI and charge transfer resistance are expected to increase with decreasing surface area, while the pore resistance that depends on electrode thickness, porosity, and tortuosity is expected to decrease. Eventually we will show a full impedance model for the graphite electrode and show how the SEI resistance is dominant compared to the charge transfer resistance, and that pore resistances are a major contribution to the overall resistance for typical battery graphite electrodes. Lastly, we will show the influence of additives on the SEI resistance in low-loaded graphite electrodes and how they affect the impedance spectra for graphite electrodes with a standard loading. Figure 1 Half-cell impedance of a graphite electrode (~3mAh/cm2) at varying state of charge (SOC) measured via a gold-wire µ-reference electrode before and after three formation cycles in 1M LiPF6 in EC:EMC 3:7. Measured at open circuit voltage with a voltage amplitude of 10 mV between 30 kHz and 0.1 Hz. Acknowledgements: This work was supported by the BMBF (Federal Ministry of Education and Research, Germany) under the auspices of the ExZellTUM II project (grant number 03XP0081) and by the BMWI (Federal Ministry for Economic Affairs and Energy) under the auspices of the SurfaLib project (grant number 03ET6103F). References: (1) Landesfeind, J.; Pritzl, D.; Gasteiger, H. A. An Analysis Protocol for Three-Electrode Li-Ion Battery Impedance Spectra: Part I. Analysis of a High-Voltage Positive Electrode. J. Electrochem. Soc. 2017, 164 (7), A1773–A1783. (2) Pritzl, D.; Landesfeind, J.; Solchenbach, S.; Gasteiger, H. A. An Analysis Protocol for Three-Electrode Li-Ion Battery Impedance Spectra: Part II. Analysis of a Graphite Anode Cycled vs. LNMO. J. Electrochem. Soc. 2018, 165 (10), A2145–A2153. Figure 1
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