bluuebunny/crossref_metadata_2025_split huggingface dataset:
Solid-Electrolyte Interphase of Molecular Crowding Electrolytes
Authors: Xie Jing , Lu Yi-Chun 
Published: September 2023

Molecular crowding electrolyte was proposed to improve the stability of water at a low concentration of Li salt (2 m LiTFSI )1. Low-cost and safe poly (ethylene glycol) (PEG, Mn=400) is adopted as a crowding agent to confine water molecules through hydrogen bonding and strengthen the covalent bond of H-O (H2O), leading to effective suppression of water decomposition (especially HER). However, the mechanism behind the improved cathodic stability of molecular crowding electrolyte is not yet fully understood. Specifically, the composition of the SEI and the impact of salt on the electrochemical stability of PEG-based electrolyte are still unknown. To gain a deeper insight into the stability mechanism in molecular crowding electrolytes, we investigated the cathodic stability of PEG-based molecular crowding electrolytes with LiTFSI and LiClO4 as the electrolyte salt. We characterized the composition and structure of SEI on Li4Ti5O12 electrode (LTO) derived from LiTFSI- and LiClO4-containing electrolytes, and correlated cathodic stability to the composition of the SEI. Comprehensive characterizations including linear sweep voltammetry (LSV), online electrochemical mass spectroscopy (OEMS), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) are used to study the cathodic stability of water. The enhance mechanism will be discussed.
[1] Xie, J., Liang, Z. & Lu, Y. C. Molecular crowding electrolytes for high-voltage aqueous batteries. Nat. Mater. 2020, 19, 9, 1006-1011
[2] Xie, J., Guan, Y., Huang, Y., & Lu, Y. C. Solid–electrolyte interphase of molecular crowding electrolytes. Chem. Mater. 2022, 34, 11, 5176–5183
Acknowledgement
This work is supported by a grant from the Research Grant Council of Hong Kong Special Administrative Region, China (Project No. RFS2223-4S03) and a grant from the Innovation and Technology Commission of the Hong Kong Special Administrative Region, China (Project No. ITS/219/21FP).
Multifunctional Additive Ethoxy(pentafluoro)Cyclotriphosphazene Enables Safe Carbonate Electrolyte for SiOx-Graphite/NMC811 Batteries
Authors: Liu Sufu , Becker Maximilian , Huang-Joos Yuanye , Lai Huagui , Homann Gerrit , Grissa Rabeb , Egorov Konstantin , Fu Fan , Battaglia Corsin , Kuehnel Ruben-Simon 
Published: September 2023

The silicon or silicon monoxide (SiO
x
)-graphite/nickel-rich (≥80% Ni) LiNi
x
Mn
y
Co
z
O2 (x+y+z = 1, NMC) cell chemistry is widely regarded as one of the most promising chemistries for next-generation electric vehicle batteries for due to its higher energy density compared to state-of-the-art graphite/Ni-rich NMC batteries. However, the drastic volume change during lithiation and delithiation of silicon poses a significant challenge to realize its high capacity with a practical cycle life. Besides performance degradation, it is desirable to address safety risks stemming from, e.g., the high flammability of carbonate solvents and oxygen release from highly delithiated Ni-rich NMC materials.
To address these problems, one of the most effective methods is to develop advanced electrolytes that combine flame-retardant properties and excellent electrochemical performance. Generally, in consideration of the balanced trade-offs between cost, scalability, safety, and electrochemical compatibility, the use of flame retardants is a very promising approach to realize the next-generation nonflammable electrolytes.However, it is still a huge challenge to optimize the electrolyte composition to stabilize Si-based and Ni-rich lithium-ion batteries.
Here, the compatibility of the flame retardant ethoxy(pentafluoro)cyclotriphosphazene (PFPN) as additive for carbonate electrolytes is studied, for the first time, in the SiO
x
-graphite/NMC811 full cells. [1] A synergistic effect is found between PFPN and lithium hexafluorophosphate (LiPF6) for the flame retardancy, and a modified electrolyte (1.35M LiPF6 in ethylene carbonate (EC):ethyl methyl carbonate (EMC) (3:7 by vol.) with 10 wt.% fluoroethylene carbonate (FEC) and 5 wt.% PFPN) displays a very low self-extinguishing time of only 3 s/g while also maintaining a high ionic conductivity of 8.4 mS/cm at 25 °C. Furthermore, the morphology evolution and interphase composition of both anode and cathode are investigated, gaining important insights into the decomposition mechanism of PFPN to stabilize the electrode-electrolyte interfaces. Meanwhile, the wetting properties of the modified electrolyte are also improved due to the excellent wettability of PFPN. As a result, half and full coin cells with SiO
x
-graphite anode and NMC811 cathode display better capacity retention during long-term cycling with the modified electrolyte than with 1M LiPF6 in EC:EMC (3:7 by vol.) with 10 wt.% FEC. In addition, the enhanced cycling performance with the modified PFPN-contained electrolyte is also confirmed for 1 Ah SiO
x
-graphite/NMC811 pouch cells cycled under various pressures. These results open a promising avenue for the development of safe and high-performance electrolytes for silicon-based lithium-ion batteries.

References

[1] S. Liu et al., to be submitted.
Data-Driven Approach to Analyze Interdependencies between Electrode Manufacturing Parameters and Electrochemical Performance of the Lithium-Ion Battery Cell
Authors: Haghi Sajedeh , Daub Rüdiger 
Published: September 2023

The lithium-ion battery cell production is a complex process chain with a high number of process steps and manifold interdependencies. The majority of the properties determining the electrochemical performance of the battery cell are established during electrode manufacturing. An in-depth understanding of electrode manufacturing and its influence on cell performance can pave the way toward high-quality, cost-efficient cell production. Considering the complexity of the process chain and the high share of material costs in battery production, the classic one-factor-at-a-time experimentation is deemed inadequate and expensive.
Machine learning (ML) approaches have been proven suitable for analyzing complex process chains. Design of experiment (DoE) methods can be used to generate a sufficient informative database for ML techniques. This study was based on the joint application of DoE and ML methods in electrode manufacturing. For this purpose, in the first step, the response surface methodology (RSM) was used to conduct experiments and analyze the effect of mass loading, drying temperature, and porosity on cell performance. The study was focused on graphite anodes produced at a pilot scale. The electrochemical performance of electrodes was assessed on coin cells at discharge C-rates from C/10 to 5C. Additionally, symmetric coin cells were used to analyze the electrochemical impedance spectra. Supervised machine learning models were adopted to predict the cell characteristics based on the electrode properties. Additionally, a factor analysis reflecting the contribution and importance of each factor on the final cell properties was conducted. The efficient experiment-based data generation using RSM combined with the applied ML techniques can support practitioners towards smart quality-oriented battery cell production.
Investigating the Electrolyte Degradation of Lithium-Ion Cells with Silicon-Containing Anodes
Authors: Petit Jan , Heugel Philipp , Joos Martin , Klein Franziska , Tübke Jens 
Published: September 2023

Silicon with a high gravimetric capacity of 3579 mAh g-1 of the pure material becomes increasingly common in the anode of lithium-ion batteries to increase energy density on the full cell level. However, silicon changes its volume excessively during (de-)lithiation making it prone to ageing. In commercial cells, it is typically applied as SiOx in small quantities in a composite anode together with graphite.
Gas analytical studies of Gr/SiOx||NMC622 cells with varying silicon content and carbonate-based electrolyte are presented. The electrolyte consists of 1M LiPF6 in EC:DEC (1:1, v/v) + 5 wt-% FEC. The focus of this study is on investigations of ageing processes such as electrolyte decomposition during formation cycling. All measurements were carried out using specially developed multifunctional test setups and accordingly modified test cells. The different cell specifications were examined by operando mass spectrometry (MS) and post-mortem gas chromatography-mass spectrometry (GC-MS).
Strong gas formation leads to a loss of electrolyte, which can cause the cell to dry out and consequently limit the cycle life. Gas analysis is a suitable method to identify decomposition products as well as to illustrate degradation reactions. Operando MS can be used to detect gaseous substances produced by (electro)chemical processes as a function of the state of charge. Furthermore, a post-mortem GC-MS analysis was performed to identify the individual substances qualitatively.
The cyclic formation of several degradation products can be determined. Among others, carbon dioxide, hydrogen as well as ethane are identified as characteristic decomposition products of the electrolyte. In addition, the decomposition path of the conducting salt can be detected. Another main result is the evidence of the presence of silicon-containing gaseous fragments as a function of the Si-content in the composite anode.
These gas analytical studies of silicon graphite composite anodes provide an important contribution to the understanding of the degradation reactions taking place. The results shown help to illustrate them and give information about the influence of the silicon content on electrolyte degradation.

Figure 1
Generalized Inversion of Electrochemical Impedance Data for Battery Systems
Authors: Li Michael L. , Bazant Martin Z. 
Published: September 2023

Electrochemical Impedance Spectroscopy (EIS) is a key technique for taking a snapshot of an electrochemical system near equilibrium conditions. Due to the richness of the complex-valued dataset and its simple experimental operation, it is currently being investigated as a test to diagnosis battery health and degradation details. Nevertheless, challenges with use of EIS is in interpreting the measured impedance. Current methods for analysis involving either fitting simplified equivalent circuit models or inverting distribution of relaxation times with a singular basis function. Because of these methods' simplifications, their results sometime fail to capture both the complex and heterogeneous underlying physics.
Here, we present a novel algorithm for the inversion of EIS data for battery systems, which generalizes the inversion problem to any given linear equivalent circuit model, allowing for the analysis of complicated electrochemical systems. Importantly, this algorithm provides two clear benefits. First, it allows for the analysis of both bounded and unbounded processes, something quite common to battery systems and is vital in understanding non-obvious relationships in degraded batteries. Second, the distribution of independent processes, which can correspond to different physical phenomena, are also inverted by this algorithm. These distributions contain vital features in the identification and prediction of battery state-of-health. Overall, this tool will be indispensable in the analysis of degradation extent over battery aging, and provide an algorithmic framework for interpreting EIS measurements of complicated electrochemical systems.
Mathematical Toolbox for Joint Structural and Electrochemical Analysis of Lithium-Ion Battery Cells
Authors: Karaki Hassan , Kretschmer Katja , Schröder Daniel 
Published: September 2023

Increasing interest in the automotive field for electrification has led to an increased demand for lithium-ion batteries (LIB). LIB remain the most popular and widely applied energy storage technology. The microstructure of the positive electrode of LIBs governs its electrochemical performance. For this reason, it is quite imperative to determine an optimal electrode microstructure design to achieve the best possible energy properties. Mechanistic simulation models can be a powerful tool in analyzing the effect of microstructural parameters on the battery cell performance. Not only do they negate costs for necessary materials, but they also allow analysis and optimization while avoiding time-consuming experiments.
Doyle-Fuller-Newman (DFN) models, being pseudo-2-dimensional (P2D), are computationally less expensive than their higher dimension counterparts; however, they often apply the Bruggeman relation to compute effective parameters such as the electrode conductivity of the electrode. Despite its simple implementation (i. e. a correction factor to reflect effective parameters), the Bruggeman relation delivers inaccurate results. [1, 2]
In this work [1], we coupled a DFN model with the structure surrogate model from [2], excluding the Bruggeman relation. The model predicts the effective transport parameters and thus the battery performance more accurately. With this coupled model, we investigated the effect of the cathode mass loading and density on the achievable volumetric discharge energy density. [1] Furthermore, we developed a numerical optimization tool, which can predict the optimal structural parameters for maximum energy density. Our findings suggested different optimal designs for different current densities; whereas higher mass loading was preferred at lower C-rates, it was less favorable at higher C-rates. The concentration profiles of lithium-ions across the cathode thickness at the end of discharge suggest transport limitations to be the main reason behind this. As a further step, we carried out an uncertainty analysis to determine the robustness of the optimal designs to structural fluctuations with respect to their energy density.
Our findings provide a deeper understanding into the influence of structural parameters on the discharge performance of lithium-ion battery cells, using only simulative methods. Additionally, our methodology of numerical optimization and subsequent uncertainty analysis allows for a quick and simple method for determining optimal structural parameters and their robustness against fluctuations. This approach can assist to produce battery cell electrodes with an optimized design in industry as well as help simulative and experimental researchers to further investigate optimal electrode design.
[1] Karaki et al., Energy Technology 2022

[2] Laue et al., E. Acta 2019

Figure 1
An Electrochemical-Thermal-Mechanical Model for Large Format Lithium Ion Batteries
Authors: Schiffler Marc , Schmidt Adrian , Lindner Adrian , Weber Andre 
Published: September 2023

The intercalation reaction in Lithium-Ion batteries causes significant volume changes in the active material phases during cycling. Due to spatial limitations in common battery applications, this entails mechanical stresses on different length scales and thereby influencing performance and lifetime of the battery[1]. Mechanical effects are closely linked to electrochemical and thermal processes in the cell, giving rise to complex interactions that are difficult to predict. Moreover, large cell dimensions, which become ever so common in today’s battery industry, further increase complexity due to local variations of state variables. Therefore, modeling is essential to enhance understanding of the governing- and limiting processes.
In this contribution we present a fully coupled multi-scale-, multi-physics-model that combines an electrochemical model on the particulate electrode level, namely an extended Newman model featuring a particle size distribution, and a homogenized cell material model, displaying anisotropic electrical-, thermal- and mechanical properties. To include mechanical effects into a multi-physics-model[2] a new approach is considered. We apply the poroelastic theory to describe the mechanical behavior governed by the interaction of the porous electrode matrix and the infiltrated electrolyte. The use of homogenization techniques allows to keep the computational effort in check, while still doing justice to the complexity of a three-dimensional-, multi-scale-, and multi physics problem. The model is parametrized in-house by applying different electrochemical-, mechanical-, and microstructural characterization methods. The model, its parameterization and validation as well as selected simulation results will be presented.

Acknowledgements

This work was funded by the Deutsche Forschungsgemeinschaft (DFG) in the framework of the research training group SiMET (281041241/GRK2218).
[1] Y. Zhao, P. Stein, Y. Bai, M. Al-Siraj, Y. Yang, B.-X. Xu, Journal of Power Sources
2019, 413, 259–283.
[2] A. Schmidt, D. Oehler, A. Weber, T. Wetzel, E. Ivers-Tiffée, Electrochimica Acta
2021, 393, 1–14.
Physics-Based Modelling of Hybrid Cathode Li/CFx-SVO Batteries Under Pulse Discharge
Authors: Liang Qiaohao , Gomadam Partha , Tamirisa Prabhakar , Bazant Martin Z. 
Published: September 2023

Power sources of implantable cardioverter-defibrillators (ICD) require high energy density to ensure longevity and sufficient rate capability to provide high power pulses for treating abnormal heart rhythms. Such demands have led to the design of Li/CFx-SVO battery, which leverages the excellent energy density of carbon monofluoride (CFx) and power density of silver vanadium oxide (SVO) through the use of a CFx-SVO hybrid cathode. A phenomenological model based on porous electrode theory was previously developed for Li/CFx-SVO, but it overlooked phase separation in SVO, Li+ diffusion limitations in particles, and reaction heterogeneity across particles. It was thus unable to accurately predict the voltage over-recovery behavior during transitions from medium to low currents, capture relaxation behavior after high current pulses without the use of unrealistically large capacitance values, or interactions between active materials in the hybrid electrode.
In this work, we present a computational model of Li/CFx-SVO battery based on Multiphase Porous Electrode Theory for hybrid electrodes (Hybrid-MPET). Hybrid-MPET framework allows us to model the phase separation during reduction of SVO, concentration gradients in SVO particles and the evolution of reaction heterogeneities across an ensemble of particles under different current rates. As a result, our Hybrid-MPET model excels at predicting voltage-capacity behavior under constant current or constant load discharge, is capable of providing physical explanation of voltage over-recovery and voltage relaxation, and captures the interactions between SVO and CFx particles during transient currents. The Hybrid-MPET models are validated against experimental data from Li/CFx-SVO batteries of different designs, and show consistent modelling capability across different electrode thickness, particle lengthscales, and discharge timescales. Our work demonstrates how physics-based models can help provide fundamental understanding of experimental phenomenon, and we further discuss how the Hybrid-MPET framework could open up new opportunities to study the performance of hybrid electrode batteries and support their engineering design in a broader range of devices.

Figure 1
(Invited, Digital Presentation) Discovery to Product: A Reflection on the Path from Electrochemical Materials Research to Traction Batteries to the Commercialization of Electric Vehicles
Authors: Verbrugge Mark 
Published: September 2023

We live in an age wherein many industry analysts and surveys indicate that within the not-too-distant future, perhaps within 10 years, battery electric vehicles (BEVs) will outsell vehicles employing internal combustion engines. How did we arrive at this point in history?
In this talk, I will overview some of the key drivers I’ve seen in my nearly four decades of work on the research, development, and commercialization of BEVs. The path I’ve witnessed has been highly nonlinear, making trend predictions along the way difficult. Collaborations, including Public-Private Partnerships, Joint Ventures, and relationships, have been of vital importance. In addition, I’ve found that in attempting to participate in the path of invention to commercialization, having a firm basis on governing foundational principles is an indispensable asset. In my case, learning from predecessors and colleagues about electrochemical materials and characterization and elements of battery cell modeling provided the requisite foundation.
Last, I’ll note that clear and compelling communication within a company and externally is necessary to bring inventions to innovation and commercialization. It is only through such communications that necessary resource allocation emerges.
(Invited) Approaches for Mechanistic Understanding of Electrodeposition Processes for Fabricating Micro/Nano Structures and Devices
Authors: Homma Takayuki , Kunimoto Masahiro , Yanagisawa Masahiro 
Published: September 2023

Electrochemical deposition processes have precise controllability, selectivity and uniformity, and have been widely applied for fabricating various functional micro/nano structures and devices. In order to achieve further higher controllability for developing reliable process for manufacturing, molecular-level understanding of the deposition processes is required. Furthermore, this can be be also utilized to understand various applications such as the electrode processes of secondary batteries using metal anodes and so on. For this, we have attempted to apply theoretical approaches such as density functional theory (DFT) and kinetic Monte Carlo (KMC) calculations[1.2], as well as experimental methods such as surface enhanced Raman microscopy equipped with plasmonic sensors[3-5]. In this paper, these approaches with some of the resent results will be described. The analysis using DFT calculations provided the molecular-level insights for the catalytic activity of the electroless deposition reaction process at the surface, with the effects of the additive species and solvation. Also, in combination with the KMC calculation, multi-scale simulation for the nucleation and growth process at the Zn anode surface for the secondary battery was attempted. While these approaches enable quantitative discussion for the mechanistic understanding of the processes, we also attempted to obtain "real" data from experimental approaches. For this, we applied surface enhanced Raman scattering (SERS) and developed "plasmonic sensors" with controlled nanostructures to obtain high signal enhancement at electrode-electrolyte interface. We have developed two types of the plasmonic sensors which could achieve extremely high sensitivity. Multi-confocal type SERS microscopy was also developed for mapping and imaging analyses of the electrode surface as well as local pH distributions. By using these techniques, various processes at the electrode surfaces and interfaces have been investigated and modelling of the processes has been carried out.
This work was financially supported in part by “Development of Systems and Technology for Advanced Measurement and Analysis” program from Japan Science and Technology Agency, and Grant-in-Aid for Scientific Research, MEXT, Japan.
[1] Y. Onabuta, M. Kunimoto, H. Nakai, T. Homma, Electrochim. Acta, 307, 536 (2019).
[2] Y. Onabuta, M. Kunimoto, S. Wang, Y. Fukunaka, H. Nakai, T. Homma, J. Electrochem. Soc., 169, 092504 (2022).
[3] M. Yanagisawa, M. Saito, M. Kunimoto, T. Homma, Appl. Phys. Express, 9 , 122002 (2016).
[4] M. Kunimoto, F. Yamaguchi, M. Yanagisawa, T. Homma, J. Electrochem. Soc., 166, D212 (2019).
[5] T. Wang, M. Kunimoto, M. Yanagisawa, M. Morita, T. Abe, T. Homma, Energy Env. Mat., in press (2022).