A Critical Review for an Accurate Electrochemical Stability Window Measurement of Solid Polymer and Composite Electrolytes

All-solid-state lithium batteries (ASSLB) are very promising for the future development of next generation lithium battery systems due to their increased energy density and improved safety. ASSLB employing Solid Polymer Electrolytes (SPE) and Solid Composite Electrolytes (SCE) in particular have attracted significant attention. Among the several expected requirements for a battery system (high ionic conductivity, safety, mechanical stability), increasing the energy density and the cycle life relies on the electrochemical stability window of the SPE or SCE. Most published works target the importance of ionic conductivity (undoubtedly a crucial parameter) and often identify the Electrochemical Stability Window (ESW) of the electrolyte as a secondary parameter. In this review, we first present a summary of recent publications on SPE and SCE with a particular focus on the analysis of their electrochemical stability. The goal of the second part is to propose a review of optimized and improved electrochemical methods, leading to a better understanding and a better evaluation of the ESW of the SPE and the SCE which is, once again, a critical parameter for high stability and high performance ASSLB applications

Assessing the Electrochemical Stability Window of NASICON-Type Solid Electrolytes

All-Solid-State Lithium Batteries (ASSLBs) are promising since they may enable the use of high potential materials as positive electrode and lithium metal as negative electrode. This is only possible through solid electrolytes (SEs) stated large electrochemical stability window (ESW). Nevertheless, reported values for these ESWs are very divergent in the literature. Establishing a robust procedure to accurately determine SEs’ ESWs has therefore become crucial. Our work focuses on bringing together theoretical results and an original experimental set up to assess the electrochemical stability window of the two NASICON-type SEs Li1.3Al0.3Ti1.7(PO4)3 (LATP) and Li1.5Al0.5Ge1.5(PO4)3 (LAGP). Using first principles, we computed thermodynamic ESWs for LATP and LAGP and their decomposition products upon redox potentials. The experimental set-up consists of a sintered stack of a thin SE layer and a SE-Au composite electrode to allow a large contact surface between SE and conductive gold particles, which maximizes the redox currents. Using Potentiostatic Intermittent Titration Technique (PITT) measurements, we were able to accurately determine the ESW of LATP and LAGP solid electrolytes. They are found to be [2.65–4.6 V] and [1.85–4.9 V] for LATP and LAGP respectively. Finally, we attempted to characterize the decomposition products of both materials upon oxidation. The use of an O2 sensor coupled to the electrochemical setup enabled us to observe operando the production of O2 upon LAGP and LATP oxidations, in agreement with first-principles calculations. Transmission Electron Microscopy (TEM) allowed to observe the presence of an amorphous phase at the interface between the gold particles and LAGP after oxidation. Electrochemical Impedance Spectroscopy (EIS) measurements confirmed that the resulting phase increased the total resistance of LAGP. This work aims at providing a method for an accurate determination of ESWs, considered a key parameter to a successful material selection for ASSLBs. © Copyrigh

Limiting Factors Affecting the Ionic Conductivities of LATP/Polymer Hybrid Electrolytes

All-Solid-State Lithium Batteries (ASSLB) are promising candidates for next generation lithium battery systems due to their increased safety, stability, and energy density. Ceramic and solid composite electrolytes (SCE), which consist of dispersed ceramic particles within a polymeric host, are among the preferred technologies for use as electrolytes in ASSLB systems. Synergetic effects between ceramic and polymer electrolyte components are usually reported in SCE. Herein, we report a case study on the lithium conductivity of ceramic and SCE comprised of Li1.4Al0.4Ti1.6(PO4)3 (LATP), a NASICON-type ceramic. An evaluation of the impact of the processing and sintering of the ceramic on the conductive properties of the electrolyte is addressed. The study is then extended to Poly(Ethylene) Oxide (PEO)-LATP SCE. The presence of the ceramic particles conferred limited benefits to the SCE. These findings somewhat contradict commonly held assumptions on the role of ceramic additives in SCE

An electrochemically roughened Cu current collector for Si-based electrode in Li-ion batteries

International audienceAn electrochemically roughened copper foil was evaluated as a current collector for micrometric Si powder (ball-milled) based electrodes prepared by the conventional slurry-coating method. The formation of a bunch of copper nanowires on the current collector provides a rough surface, which enhances the adhesion of the Si composite electrode as confirmed from scratch tests. This produces a major decrease of the irreversible capacity associated with the electrical disconnection of the Si particles with cycling, which results in a great improvement of the electrode cycle life. With such a roughened Cu current collector, the micrometric Si-based electrode is able to maintain a discharge capacity of 1200 mAh g−1 for at least 1000 cycles

Calcium substitution to improve the total ionic conductivity of the Li3/8Sr7/16Ta3/4Hf1/4O3 perovskite-type electrolyte

We report novel calcium-substituted perovskite-type solid state electrolyte with nominal composition Li0.344Sr0.433Ca0.02Ta3/4Hf1/4O3, which we compare with Li3/8Sr7/16Ta3/4Hf1/4O3. The compounds were synthesized via solid-state reaction and studied by X-ray and neutron powder diffraction and electrochemical impedance spectroscopy. Neutron powder diffraction allowed the Li position in the structure to be accurately determined. Calcium-substituted phase showed higher Li-ion conductivity than the analogous calcium-free phase obtained with our synthesis method. High total Li-ion conductivities of 3.6 ± 1.0 × 10−4 S cm−1 (Ea = 431 meV) at 30 °C were reached for calcium-substituted phase, and both bulk and grain-boundary conductivities increased compared to that of the calcium-free phase. The same experiment was conducted on Li0.344Sr0.433Ca0.02Ta3/4Zr1/4O3 and led to the same conclusion compared to Li3/8Sr7/16Ta3/4Zr1/4O3. Elemental analysis by energy-dispersive X-ray (EDX) of Li0.344Sr0.433Ca0.02Ta3/4Hf1/4O3 showed the formation of an intermediary phase at grain boundaries, which contained essentially strontium, calcium, and oxygen. To better understand the increased bulk conductivity, neutron diffraction was performed on Li0.344Sr0.433Ca0.02Ta3/4Hf1/4O3. The results demonstrate the importance of understanding and controlling the grain boundary composition, as much as the bulk composition, to improve the total ionic conductivity of solid electrolytes

Deep Learning Classification of Li-Ion Battery Materials Targeting Accurate Composition Classification from Laser-Induced Breakdown Spectroscopy High-Speed Analyses

Laser-induced breakdown spectroscopy (LIBS) is a valuable tool for the solid-state elemental analysis of battery materials. Key advantages include a high sensitivity for light elements (lithium included), complex emission patterns unique to individual elements through the full periodic table, and record speed analysis reaching 1300 full spectra per second (1.3 kHz acquisition rate). This study investigates deep learning methods as an alternative tool to accurately recognize different compositions of similar battery materials regardless of their physical properties or manufacturer. Such applications are of interest for the real-time digitalization of battery components and identification in automated manufacturing and recycling plant designs

Deep Learning Classification of Li-Ion Battery Materials Targeting Accurate Composition Classification from Laser-Induced Breakdown Spectroscopy High-Speed Analyses

Laser-induced breakdown spectroscopy (LIBS) is a valuable tool for the solid-state elemental analysis of battery materials. Key advantages include a high sensitivity for light elements (lithium included), complex emission patterns unique to individual elements through the full periodic table, and record speed analysis reaching 1300 full spectra per second (1.3 kHz acquisition rate). This study investigates deep learning methods as an alternative tool to accurately recognize different compositions of similar battery materials regardless of their physical properties or manufacturer. Such applications are of interest for the real-time digitalization of battery components and identification in automated manufacturing and recycling plant designs