Open Access

The influence of electrode roughness on diffusional cyclic voltammetry (CV) is investigated from a theoretical perspective. For this purpose, the digital-simulation–deconvolution–convolution (DSDC) algorithm, initially developed for the simulation of CV at porous electrodes, is subjected to three substantial modifications. First, by employing adaptive numerical resolution and sample volumina, the computational demand of the digital simulation (DS) step is reduced significantly. Second, by modifying the Douglas–Gunn algorithm of the DS-step to operate on an arbitrarily incremented spatial grid perpendicular to the macroscopically planar electrode surface, the bulk of the fluid can be treated with an exponentially increasing spatial discretization which uses computational power even more efficiently. The third modification is an optimization of the computationally demanding deconvolution step which is used to extract the mass-transfer function from the data computed in the DS-step. This, initially recursive procedure, is replaced by a three-step sequence consisting of (I) a numerical Laplace transformation (NLT) on an exponentially expanding time-grid, (II) a Laplace-domain integration (LDI) and finally (III) a numerical inversion of Laplace transformation (NILT) using the Gaver–Stehfest (GS) inversion formula. Based on this novel strategy for CV simulation, the effects of electrode roughness are thoroughly investigated. It is demonstrated that for an ideally reversible reaction the effects of electrode roughness on the CV response are insignificant at common experimental timescales. In contrast, for scenarios with electrochemically quasi-reversible (or irreversible) kinetics, the apparent rate constants are allegedly upscaled by the area ratio 𝜓 = 𝐴rough∕𝐴planar . This manifests in a lower peak-to-peak separation without a distortion of the shape of the voltammetric profile. This behavior is finally explained in a quantitative manner in terms of convolution-sums and mass-transfer functions which ultimately puts the parameter electrode roughness into the semianalytical framework of convolutive modeling.

Most high capacity anode materials for lithium-ion batteries (LiB) require a carbonaceous matrix. In this context one promising material is reduced graphene oxide (rGO). Herein, we present the influence of different reduction degrees of rGO on its physico-chemical properties, such as crystallinity, specific surface area, electrical conductivity and electrochemical lithiation/delithiation behavior. It is found that a heat treatment under inert and reducing atmospheres increases the long-range order of rGO up to a temperature of 700 °C. At temperatures around 1000 °C, the crystallinity decreases. With decreasing oxygen content, a linear decrease in irreversible capacity during cycle 1 can be observed, along with a significant increase in electrical conductivity. This decrease in irreversible capacity can be observed despite an increase in specific surface area indicating the more significant influence of the oxygen content on the capacity loss. Consequently, the reversible capacity increases continuously up to a carbon content of 84.4 at% due to the thermal reduction. Contrary to expectations, the capacity decreases with further reduction. This can be explained by the loss of functional groups that will be lithiated reversibly, and a simultaneous reduction of long-range order, as concluded from dq/dU analysis in combination with XRD analysis.

The transportation and storage of lithium-ion batteries (LIB) — damaged or in an undefined state — is a major safety concern for regulatory institutions. Damaged LIBs pose the risk of a so-called thermal runaway (TR), a strongly exothermic reaction with the formation of gases, flames or even an explosion of the battery. The relevance of this issue is underlined by the number of fires that have occurred at recycling centers in the recent past. One solution to circumvent a TR is given by thermal passivation (i.e. deep-freezing) of batteries. Practically, this method is already used and temperatures below -60 °C are considered safe. In this talk, the parameter battery safety is revisited under the premise of heat-transfer and activation energies. At first, mechanically initiated TRs are compared for different cell chemistries, cell sizes, and temperatures, revealing that the threshold of thermal passivation is vastly system specific. Combining these results with differential scanning calorimetry underlines that the hazard potential of a battery is not necessarily eliminated by freezing the electrolyte. Instead, the potential for a TR needs to be regarded as a multivariant function of energy content, cell-voltage, chemical stability, and electrokinetic performance. Since the latter parameter is known to be vastly temperature-dependent, it is addressed in detail by a low-temperature electrokinetic study of different types of LIB. In this context, it is demonstrated that batteries are kinetically active even at temperatures well below the freezing point of the electrolyte and that their instantaneous power output is resembled sufficiently via Arrhenius´ law. To get a detailed understanding of cell-specific heat release during and prior to a TR, data from accelerated rate calorimetry will be discussed for various cell types at different state of charge and state of health. This will eventually provide a conclusive picture how a cell-internal TR-propagation takes place and which parameters need to be deliberately tuned under the premise of battery safety.

Electrode roughness is an exceptionally important, yet oftentimes overlooked factor in electrokinetic analysis and catalyst research. Essentially any electroanalytical experiment involving an electrode with a surface which is not perfectly smooth will be subjected to more or less severe effects of roughness. This includes any circumstance where electrodes are decorated with micro- or nanoparticles and is therefore relevant for a plethora of experimental scenarios. Since the roughness-related gain in surface area scales the reaction rate – and thus the current – it is an inherently non-straightforward task to assess intrinsic electrode kinetics from experimental data of rough structures. In other words, a significant overestimation of kinetic constants may arise when rough electrodes are employed and kinetics are analyzed under the assumption of perfectly planar surfaces. For this reason, it is fundamentally interesting to approach electrode roughness from a purely theoretical point of view, since surface roughness and kinetics can be tuned in a deliberate manner for separating their individual contributions. In this study, we propose a strategy for the simulation of the most common electroanalytical technique – cyclic voltammetry – at mesoscopically rough surfaces. For this purpose, our previously introduced digital simulation - deconvolution - convolution (DSDC) algorithm [1] is employed. By modifying, the Douglas--Gunn algorithm, which is used in the digital simulation step to operate on an arbitrarily incremented spatial grid, a high numerical resolution near the electrode/electrolyte boundary and a larger spatial discretization in the bulk of the electrolyte can be used. This provides a fine resolution of artifacts of surface roughness and efficiently utilizes computational power. As a consequence, simulations can be performed on real-space data of rough electrodes which is obtained from atomic force microscopy (AFM). It is demonstrated that for an ideally reversible reaction the effects of electrode roughness on the CV response are insignificant. In contrast, for practically relevant scenarios with electrochemically irreversible or quasi-reversible kinetics, the apparent rate constants are allegedly upscaled by the area-ratio Arough/Aplanar up to a certain threshold. Qualitatively, this manifests in a lower peak-to-peak separation without a distortion of the shape of the voltammetric profile. As soon as the surface profile becomes much deeper than wide, a distortion of the CV response occurs which is associated with an increasingly finite diffusion domain. This behavior is finally explained in terms of convolution-sums and mass-transfer functions and provides a quantitative interpretation of roughness effects.

The transport and storage of lithium-ion (Li-ion) batteries — damaged or in an undefined state — is a major safety concern for regulatory institutions, transportation companies, and manufacturers. Since (electro)chemical reactivity is exponentially temperature-dependent, cooling such batteries is an obvious measure for increasing their safety. The present study explores the effect of cryogenic freezing on the electrochemical and physical stability of Li-ion cells. For this purpose, three different types of cells were repeatedly exposed to liquid nitrogen (LN2). Before and after each cooling cycle, electrical and electrochemical measurements were conducted to assess the impact of the individual freezing steps. While the electrochemical behavior of the cells did not change significantly upon exposure to LN2 , it became apparent that a non-negligible number of cells suffered from physical changes (swelling) and functional failures. The latter defect was found to be caused by the current interrupt device of the cylindrical cells. This safety mechanism is triggered by the overpressure of expanding nitrogen which enters the cells at cryogenic temperatures. This study underlines that the widely accepted reversibility of LN2 -cooling on a material scale does not allow for a direct extrapolation toward the physical integrity of full cells. Since nitrogen enters the cell at cryogenic temperatures and expands upon rethermalization, it can cause an internal overpressure. This can, in turn, lead to mechanical damage to the cell. Consequently, a more appropriate temperature condition — less extreme than direct LN2 exposure — needs to be found