Understanding non-linearity in electrochemical systems using multisine-based non-linear characterization

Background: With the development of advanced characterization techniques, lithium-ion battery non-linearities have recently gained increased attention which can benefit battery health diagnosis and ageing mechanism identification. In comparison to conventional single sine wave-based methods, the multisine-based non-linear characterization method has the advantage of capturing the dynamic voltage response within a short testing duration, and therefore has further development potential for on-board applications. However, understanding lithium-ion battery electrochemical processes that contribute to battery non-linearities is still unclear. Methods: In this paper, the sensitivity of the Doyle–Fuller–Newman model parameters are analysed in the frequency domain to investigate the electrochemical processes that contribute to the non-linear dynamics of the voltage response. To begin with, the non-linearities of the Doyle–Fuller–Newman model with validated parameters are characterized and compared to experimental data from a commercial cell. This demonstrated a significant difference between the mathematical model and the non-linearities determined experimentally. Then, a global sensitivity analysis is applied to determine the most sensitive parameter contributing to battery non-linearities. Finally, the appropriate value of the most sensitive parameter which results in the closest non-linear response to the commercial battery is estimated through minimizing the root mean square error. Results: The results show that the charge transfer coefficient is the most sensitive parameter contributing to battery non-linearities among the Doyle–Fuller–Newman model parameters. The non-linear response of the Doyle–Fuller–Newman model is validated with good agreement with the experimental results, when the Butler–Volmer kinetic is asymmetrical due to the unequal anodic and cathodic charge transfer coefficients

Vibrational and vibrational-torsional interactions in the 0–600 cm-1 region of the S1 ← S0 spectrum of p-xylene investigated with resonance-enhanced multiphoton ionization (REMPI) and zero-kinetic-energy (ZEKE) spectroscopy

We assign the 0–600 cm-1 region of the S1 ← S0 transition in p-xylene using resonance-enhanced multiphoton ionization (REMPI) and zero-kinetic-energy (ZEKE) spectroscopy. In the 0–300 cm-1 range, as well as the intense origin band there are a number of torsional and vibration-torsion (vibtor) features. The latter are discussed in more detail in an accompanying paper [Gardner et al. J. Chem. Phys. XXX, xxxxxx (2016)]. Here we focus on the origin and the 300–650 cm-1 region, where vibrational bands and some vibtor activity is observed. From the origin ZEKE spectrum we derive the ionization energy of p-xylene as 68200 ± 5 cm-1. The assignment of the REMPI spectrum is based on the activity observed in the ZEKE spectra coupled with knowledge of the vibrational wavenumbers obtained from quantum chemical calculations. We assign several isolated vibrations, and a complex Fermi resonance that is found to comprise contributions from both vibrations and vibtor levels, and we examine this via a two-dimensional ZEKE (2D-ZEKE) spectrum. A number of the vibrational features in the REMPI and ZEKE spectra of p-xylene that have been reported previously are reassigned and now largely consist of totally-symmetric contributions. We briefly discuss the appearance of non-Franck-Condon allowed transitions. Finally, we find remarkably similar spectral activity to that in the related disubstituted benzenes, para-difluorobenzene and para-fluorotoluene

Microstructural evolution of battery electrodes during calendering

Calendering is a crucial manufacturing process in the optimization of battery performance and lifetime due to its significant effect on the 3D electrode microstructure. By conducting an in situ calendering experiment on lithium-ion battery cathodes using X-ray nano-computed tomography, here we show that the electrodes composed of large particles with a broad size distribution experience heterogeneous microstructural self-arrangement. At high C-rates, the performance is predominantly restricted by sluggish solid-state diffusion, which is exacerbated by calendering due to the increased microstructural and lithiation heterogeneity, leading to active material underutilization. In contrast, electrodes consisting of small particles are structurally stable with more homogeneous deformation and a lower tortuosity, showing a much higher rated capacity that is less sensitive to calendering densification. Finally, the dependence of performance on the dual variation of both porosity and electrode thickness is investigated to provide new insights into the microstructural optimization for different applications in electrode manufacturing

3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling

Driving range and fast charge capability of electric vehicles are heavily dependent on the 3D microstructure of lithium-ion batteries (LiBs) and substantial fundamental research is required to optimise electrode design for specific operating conditions. Here we have developed a full microstructure-resolved 3D model using a novel X-ray nano-computed tomography (CT) dual-scan superimposition technique that captures features of the carbon-binder domain. This elucidates how LiB performance is markedly affected by microstructural heterogeneities, particularly under high rate conditions. The elongated shape and wide size distribution of the active particles not only affect the lithium-ion transport but also lead to a heterogeneous current distribution and non-uniform lithiation between particles and along the through-thickness direction. Building on these insights, we propose and compare potential graded-microstructure designs for next-generation battery electrodes. To guide manufacturing of electrode architectures, in-situ X-ray CT is shown to reliably reveal the porosity and tortuosity changes with incremental calendering steps