Batteries & Supercaps最新文献

The anodefree (AF) configuration of lithium batteries represents a low-cost, high energy density alternative to current generation chemistries, and coupling with Ni and Co-free LiMn_xFe_1−xPO₄ (LMFP) cathodes further reinforces these advantages. In this work, this cell type in coin and pouch format is manufactured and evaluated, establishing key performance characteristics and optimized test protocols, while identifying outstanding challenges limiting cell lifetime. The AF LMFP coin cell provides a 35% stack-level energy density advantage over a traditional full cell (with graphite anode) when using a 60:40 Mn:Fe LMFP variant, which improves to a 42% advantage when Mn content was increased to 80% (at the cost of more rapid capacity loss). Cycling over the potential range of 3.0–4.5 V maximizes cell lifetime, while the dominant degradation mechanism is identified as irreversible Li loss associated with a disadvantageous evolution in plated Li morphology. Finally, the AF battery manufacturing is scaled to large-area pouch format to demonstrate commercial viability and compatibility with current industrial processes.

Generative models represent a powerful new paradigm for accelerating the discovery of novel materials across vast chemical space. To evaluate the viability of deploying generalized crystal generative models for application specific discovery tasks, here Li-ion battery (LIB) materials are chosen as a case study. The pretrained MatterGen model is used to generate diverse crystalline structures, conditioned for stability and tested for uniqueness and novelty for promising Li-containing compositions. An unsupervised clustering analysis is performed using atomic neighborhood fingerprints to compare the distribution of generated structures against the training dataset and materials project (MP) data in the chemical space. The multitired workflow for LIB materials combines a universal crystal generative model with foundational machine learning potential to identify the most promising stable (close to convex hull with respect to MP data) candidates for final density functional theory-based stability calculations. Open circuit voltage (OCV) and specific capacity calculations on selected stable materials highlight their potential as LIB materials. Among 91 identified Li-containing stable ($$ eV/atom above MP convex hull) materials, two novel cathode materials are identified useful for LIB, considering average OCV, OCV at highest and lowest state of charge, and the specific capacity.

Lithium-ion batteries, characterized by high energy density, are a promising energy storage device. However, the poorly matched kinetics of the electrochemical reaction between the anode and cathode of lithium-ion batteries make the search for anode materials with high ion-electron transfer efficiency an urgent task. In this work, Fe³⁺ is introduced through the branch-end negative charge of Ti₃C₂ to construct a 3D Fe³⁺/Ti₃C₂ spatial network structure, and then FeP₂@Ti₃C₂ is formed by hydrothermal and low-temperature phosphatization. The 2D nanosheet structure in FeP₂@Ti₃C₂ provides more storage sites for Li⁺ ions, and the Ti₃C₂ contributes to the enhancement of the electrical conductivity of the transition metal phosphide. Because the electronic structure of transition metal phosphides is similar to that of metals, rapid electron transfer and ion diffusion channels are formed in the longitudinal direction between layers. The FeP₂@Ti₃C₂ composite material still has a specific capacity of 1194 mAh g⁻¹ after 1000 cycles at 1000 mA g⁻¹ current density. This article provides guidance for the design of 2D materials, and FeP₂@Ti₃C₂ composites have great potential for next-generation energy storage with their unique structure and excellent electrochemical properties.

Rechargeable Iron-ion batteries (IIBs) are emerging as a sustainable alternative to conventional rechargeable batteries; however, their cathode development is hindered by sluggish Fe-ion diffusion, limited conductivity, and interfacial instability. Addressing these challenges requires designing cathode materials with high conductivity, large surface area, and stable electrochemical interfaces. This work explores carbon aerogel (CA)-based cathodes to overcome these limitations and enhance Fe-ion storage performance. Highly porous CA, used as the cathode material, is synthesized using the sol–gel process and confirmed using transmission electron microscopy, field emission scanning electron microscopy, X-ray diffraction, and Brunauer–Emmett-Teller measurements. Detailed cyclic voltammetry is investigated at different scan rates to understand the characteristics of the Fe-ion storage in CA hosts during cycling. The galvanostatic charging–discharging (GCD) is determined at various current densities, showing a high discharge capacity of ≈150 mAh g⁻¹ and ≈45 mAh g⁻¹ at 35 mA g⁻¹ and 1000 mA g⁻¹ discharge current densities, respectively. The capacity retention is more than ≈60%, with more than 85% Coulombic efficiency (CE) after 750 cycles at 1000 mA g⁻¹, and fast charge–discharge characteristics of ≈18C rate. The galvanostatic intermittent titration technique (GITT) measurements are also performed to check the diffusion characteristics of the Fe-ion during charging and discharging. A digital clock and 5V light-emitting diode are connected to CA-based Fe-ion coin cells to demonstrate the potential of IIBs. A detailed electrochemical impedance spectroscopy and postmortem measurements before and after the GCD cycling suggest a slight degradation of electrochemical performance, which is attributed to the oxidation of the anode during cycling.

The development of flexible energy-storage devices is limited by the poor conductivity, limited cycling stability, and slow electron/ion transport of metal oxides. Optimizing their structure and performance is crucial for advancing these technologies. Herein, a hollow cubic core–shell Co₃O₄@MnO₂ is synthesized via annealing and hydrothermal approaches. This composite enjoys advantages of the high electrical conductivity of Co₃O₄ and the excellent pseudocapacitive properties of MnO₂; in addition, the hollow structure of the composite effectively mitigates the mechanical stress caused by volume changes during charge–discharge cycles. Owing to its large specific surface area and stable framework, Co₃O₄@MnO₂ achieves a high specific capacitance of 670.2 F g⁻¹ and retains 83.18% of its initial capacitance after 10,000 cycles, demonstrating exceptional electrochemical stability and durability. Subsequently, an all-solid-state flexible supercapacitor was assembled using Co₃O₄@MnO₂ positive electrode and a negative electrode made of reduced graphene oxide hydrogel. The device achieves a high energy density of 78.2 W h kg⁻¹ and a power density of 11,500 W kg⁻¹. Further, even after 10,000 charge–discharge cycles, it retained 73.1% of its initial capacitance, demonstrating potential for flexible energy-storage applications. This article highlights the advantages of Co₃O₄@MnO₂ in enhancing supercapacitor performance and offers insights for cost-effective cobalt-based energy-storage systems.

Solid-state sodium-ion batteries (SSIBs) represent an advanced energy storage technology, offering superior safety, thermal stability, and robust long-term cycling performance. However, their practical deployment is critically constrained by the low ionic conductivity of solid electrolytes (SEs) and pronounced interfacial instability—stemming from poor physical contact between the electrode and SE, as well as parasitic reactions involving metallic sodium and liquid electrolyte-based interfacial modifiers. In this work, the development of a composite polymer buffer layer (CPBL) is reported as an interfacial modifier to establish stable and intimate contact at the electrode-SE interface. Integrated into a symmetric full-cell configuration using Fe-doped Na₃V₂(PO₄)₃ electrodes and NASICON-type ceramic electrolyte, the SSIB delivers a discharge capacity of ≈45 mAh g⁻¹ (theoretical capacity ≈58.8 mAh g⁻¹) at C/5, with 89% capacity retention over 200 cycles at 25 °C. Notably, the SSIB assembly is carried out in ambient conditions without the need for an inert atmosphere. The enhanced electrochemical performance is attributed to the synergistic effects of improved ionic conductivity and superior interfacial contact, which collectively facilitate efficient Na⁺ transport across the electrode-SE interface. These findings underscore the potential of CPBL to overcome interfacial challenges in SSIBs and advance the development of safe, high-performance, and sustainable sodium-based energy storage systems.

The development of battery materials presents a complex multiscale challenge, where optimizing the properties of battery systems across various length scales is essential for achieving targeted performance, enhanced safety, lower costs, and resource availability. Traditional methods for solving this complex, multiscale problem rely on time-intensive trial-and-error approaches, which hinder progress. However, integrating advanced machine learning (ML) frameworks significantly changes the landscape of battery materials research by enabling faster discovery, predictive modeling, and optimization of material properties. Among the ML frameworks, generative deep learning (DL) models stand out, as they capture the statistics of real-world scenarios by learning an underlying condensed representation of a higher-dimensional input space to generate information-rich outputs. By merging computational techniques with experimental research, generative DL provides a significant paradigm shift in analyzing battery materials. This review aims to provide valuable insights into generative models, highlighting their potential to accelerate the characterization, screening, and design of battery materials.

Optimizing the manufacturing process of Lithium-Ion Batteries (LIB. Finding efficient approaches that accelerate and replace time-consuming, material scrap-expensive trials-and-error optimization methods is a key area of research. This work presents a comprehensive LIB electrode manufacturing framework that combines physics-based simulations with deep learning. This framework efficiently simulates the manufacturing process of LIB electrodes as a function of their formulation. This framework takes the form of a surrogate manufacturing model able to predict the impact of manufacturing parameters on the electrode microstructure and properties. The model is based on a regressor-inspired variational autoencoder method. The analysis of the data and the predicted electrode functional metrics demonstrates the consistency of the approach with an electrode manufacturing model developed on the basis of physics. The reported framework holds significant promise in paving near real time optimization of LIB electrode manufacturing and supporting the optimization of battery cell design in pilot lines.

This article presents the electrochemical properties of a series of phenothiazine and phenoxazine dimers, by involving an aromatic central core, efficiently synthesized in a single step through a Buckwald–Hartwig coupling reaction. A synergistic approach combining experimental and quantum chemical studies was used in view of providing a thorough characterization of their capabilities as electrodes in the context of electrochemical energy storage applications. A detailed study of the electrochemical activity was then conducted with the aim of optimizing performance, i.e., achieving a specific capacity of around 100 mAh.g⁻¹, close to the theoretical values at a potential of 3.6 V relative to Li metal. The dimerization strategy also emerged as an interesting methodology, since it gives rise to molecular materials having specific solubility properties. This finding opens up the possibility of recovering the active material from the electrode at the end of its life, thus paving the way for improved organic electrodes and batteries, especially with respect to their recyclable character.

The electrochemical performance of LiNi_xMn_yCo_zO₂ (NMC) materials depends strongly on their composition and structure. This study investigates the influence of calcination temperature on the structural, morphological, and electrochemical properties of various NMC materials. For the first time, a conventional powder X-ray diffractometer is used for in situ analysis of NMC calcination, revealing a four-stage transition from precursor to hexagonal structure and composition-dependent transition temperatures. This accessible method offers advantages over synchrotron-based techniques. In situ X-ray diffraction (XRD) enables selection of annealing temperatures for ex situ studies, which are correlated with electrochemical behavior using scanning electron microscopy, XRD, and chronopotentiometry. Raman mapping, which has not previously been applied in this manner, provides novel insight into the local structure and stability of the material. Additionally, the role of calcination atmosphere in Ni-rich NMCs is examined. The results guide further development of advanced NMCs, including core–shell materials, and demonstrate the practicality of laboratory-based structural methods for broader materials research.