Advances in nanoporous materials for next-generation battery applications.

In recent years, nanoporous materials, mainly represented by metal-organic frameworks (MOFs) and covalent organic frameworks (COFs), have shown unparalleled potential in critical applications such as energy storage, gas separation and catalysis. The integration of MOFs/COFs into battery technology has garnered substantial research attention since it was found that such materials also play important roles in batteries. The highly controllable nanoporous features of MOFs/COFs enable the regulation of the solvation environment of lithium ions, thereby significantly improving the performance of lithium metal batteries. Moreover, the selective adsorption features of MOFs/COFs make them particularly useful for stabilising high nickel cathodes and sulfur cathodes. This review provides an overview of the application of MOFs/COFs in batteries, and explores potential future directions and challenges in this rapidly evolving interdisciplinary field.

Surface Engineering of Cathode Materials: Enhancing the High Performance of Lithium-Ion Batteries.

The development and application of lithium-ion batteries present a dual global prospect of opportunity and challenge. With conventional energy sources facing reserve shortages and environmental issues, lithium-ion batteries have emerged as a transformative technology over the past decade, owing to their superior properties. They are poised for exponential growth in the realms of electric vehicles and energy storage. The cathode, a vital component of lithium-ion batteries, undergoes chemical and electrochemical reactions at its surface that directly impact the battery's energy density, lifespan, power output, and safety. Despite the increasing energy density of lithium-ion batteries, their cathodes commonly encounter surface-side reactions with the electrolyte and exhibit low conductivity, which hinder their utility in high-power and energy-storage applications. Surface engineering has emerged as a compelling strategy to address these challenges. This paper meticulously examines the principles and progress of surface engineering for cathode materials, providing insights into its potential advancements and charting its development trajectory for practical implementation.

Mechanism and Control Strategies of Lithium-Ion Battery Safety: A Review.

Lithium-ion batteries (LIBs) are extensively used everywhere today due to their prominent advantages. However, the safety issues of LIBs such as fire and explosion have been a serious concern. It is important to focus on the root causes of safety accidents in LIBs and the mechanisms of their development. This will enable the reasonable control of battery risk factors and the minimization of the probability of safety accidents. Especially, the chemical crosstalk between two electrodes and the internal short circuit (ISC) generated by various triggers are the main reasons for the abnormal rise in temperature, which eventually leads to thermal runaway (TR) and safety accidents. Herein, this review paper concentrates on the advances of the mechanism of TR in two main paths: chemical crosstalk and ISC. It analyses the origin of each type of path, illustrates the evolution of TR, and then outlines the progress of safety control strategies in recent years. Moreover, the review offers a forward-looking perspective on the evolution of safety technologies. This work aims to enhance the battery community's comprehension of TR behavior in LIBs by categorizing and examining the pathways induced by TR. This work will contribute to the effective reduction of safety accidents of LIBs.

Mo-Doped Na4Fe3(PO4)2P2O7/C Composites for High-Rate and Long-Life Sodium-Ion Batteries.

Na4Fe3(PO4)2P2O7/C (NFPP) is a promising cathode material for sodium-ion batteries, but its electrochemical performance is heavily impeded by its low electronic conductivity. To address this, pure-phase Mo6+-doped Na4Fe3-xMox(PO4)2P2O7/C (Mox-NFPP, x = 0, 0.05, 0.10, 0.15) with the Pn21a space group is successfully synthesized through spray drying and annealing methods. Density functional theory (DFT) calculations reveal that Mo6+ doping facilitates the transition of electrons from the valence to the conduction band, thus enhancing the intrinsic electron conductivity of Mox-NFPP. With an optimal Mo6+ doping level of x = 0.10, Mo0.10-NFPP exhibits lower charge transfer resistance, higher sodium-ion diffusion coefficients, and superior rate performance. As a result, the Mo0.10-NFPP cathode offers an initial discharge capacity of up to 123.9 mAh g-1 at 0.1 C, nearly reaching its theoretical capacity. Even at a high rate of 10 C, it delivers a high discharge capacity of 86.09 mAh g-1, maintaining 96.18% of its capacity after 500 cycles. This research presents a new and straightforward strategy to enhance the electrochemical performance of NFPP cathode materials for sodium-ion batteries.

Insight into uniform filming of LiF-rich interphase via synergistic adsorption for high-performance lithium metal anode.

Multi-scale simulation is an important basis for constructing digital batteries to improve battery design and application. LiF-rich solid electrolyte interphase (SEI) is experimentally proven to be crucial for the electrochemical performance of lithium metal batteries. However, the LiF-rich SEI is sensitive to various electrolyte formulas and the fundamental mechanism is still unclear. Herein, the structure and formation mechanism of LiF-rich SEI in different electrolyte formulas have been reviewed. On this basis, it further discussed the possible filming mechanism of LiF-rich SEI determined by the initial adsorption of the electrolyte-derived species on the lithium metal anode (LMA). It proposed that individual LiF species follow the Volmer-Weber mode of film growth due to its poor wettability on LMA. Whereas, the synergistic adsorption of additive-derived species with LiF promotes the Frank-Vander Merwe mode of film growth, resulting in uniform LiF deposition on the LMA surface. This perspective provides new insight into the correlation between high LiF content, wettability of LiF, and highperformance of uniform LiF-rich SEI. It disclosed the importance of additive assistant synergistic adsorption on the uniform growth of LiF-rich SEI, contributing to the reasonable design of electrolyte formulas and high-performance LMA, and enlightening the way for multi-scale simulation of SEI.

Microcapsule Modification Strategy Empowering Separator Multifunctionality to Enhance Safety of Lithium-Metal Batteries.

The uncontrollable growth of lithium dendrites and the flammability of electrolytes are the direct impediments to the commercial application of high-energy-density lithium metal batteries (LMBs). Herein, this study presents a novel approach that combines microencapsulation and electrospinning technologies to develop a multifunctional composite separator (P@AS) for improving the electrochemical performance and safety performance of LMBs. The P@AS separator forms a dense charcoal layer through the condensed-phase flame retardant mechanism causing the internal separator to suffocate from lack of oxygen. Furthermore, it incorporates a triple strategy promoting the uniform flow of lithium ions, facilitating the formation of a highly ion-conducting solid electrolyte interface (SEI), and encouraging flattened lithium deposition with active SiO2 seed points, considerably suppressing lithium dendrites growth. The high Coulombic efficiency of 95.27% is achieved in Li-Cu cells with additive-free carbonate electrolyte. Additionally, stable cycling performance is also maintained with a capacity retention rate of 93.56% after 300 cycles in LFP//Li cells. Importantly, utilizing P@AS separator delays the ignition of pouch batteries under continuous external heating by 138 s, causing a remarkable reduction in peak heat release rate and total heat release by 23.85% and 27.61%, respectively, substantially improving the fire safety of LMBs.

Side Reactions/Changes in Lithium-Ion Batteries: Mechanisms and Strategies for Creating Safer and Better Batteries.

Lithium-ion batteries (LIBs), in which lithium ions function as charge carriers, are considered the most competitive energy storage devices due to their high energy and power density. However, battery materials, especially with high capacity undergo side reactions and changes that result in capacity decay and safety issues. A deep understanding of the reactions that cause changes in the battery's internal components and the mechanisms of those reactions is needed to build safer and better batteries. This review focuses on the processes of battery failures, with voltage and temperature as the underlying factors. Voltage-induced failures result from anode interfacial reactions, current collector corrosion, cathode interfacial reactions, overcharge, and over-discharge, while temperature-induced failure mechanisms include SEI decomposition, separator damage, and interfacial reactions between electrodes and electrolytes. The review also presents protective strategies for controlling these reactions. As a result, the reader is offered a comprehensive overview of the safety features and failure mechanisms of various LIB components.

Investigation of the Degradation of LiPF6- in Polar Solvents through Deep Potential Molecular Dynamics.

The nonaqueous electrolyte based on lithium hexafluorophosphate (LiPF6) is the dominant liquid electrolyte in lithium-ion batteries (LIBs). However, trace protic impurities, including H3O+, alcohols, and hydrofluoric acid (HF), can trigger a series of side reactions that lead to rapid capacity fading in high energy density LIBs. It is worth noting that this degradation process is highly dependent on the polarity of the solvents. In this work, a deep potential (DP) model is trained with a certain commercial electrolyte formula through a machine learning method. H3O+ is anchored with polar solvents, making it difficult to approach the PF6-, and suppressing the degradation process quickly at room temperature. Control experiments and simulations at different temperatures or concentrations are also performed to verify it. This work proposes a precise model to describe the solvation structure quantitatively and offers a new perspective on the degradation mechanism of PF6- in polar solvents.

Smart Solid-State Interphases Enable High-Safety and High-Energy Practical Lithium Batteries.

With the electrochemical performance of batteries approaching the bottleneck gradually, it is increasingly urgent to solve the safety issue. Herein, all-in-one strategy is ingeniously developed to design smart, safe, and simple (3S) practical pouch-type LiNi0.8Co0.1Mn0.1O2||Graphite@SiO (NCM811||Gr@SiO) cell, taking full advantage of liquid and solid-state electrolytes. Even under the harsh thermal abuse and high voltage condition (100 °C, 3-4.5 V), the pouch-type 3S NCM811||Gr@SiO cell can present superior capacity retention of 84.6% after 250 cycles (based pouch cell: 47.8% after 250 cycles). More surprisingly, the designed 3S NCM811||Gr@SiO cell can efficiently improve self-generated heat T1 by 45 °C, increase TR triggering temperature T2 by 40 °C, and decrease the TR highest T3 by 118 °C. These superior electrochemical and safety performances of practical 3S pouch-type cells are attributed to the robust and stable anion-induced electrode-electrolyte interphases and local solid-state electrolyte protection layer. All the fundamental findings break the conventional battery design guidelines and open up a new direction to develop practical high-performance batteries.

Machine Learning Applied to Electron Beam Lithography to Accelerate Process Optimization of a Contact Hole Layer.

Determining the lithographic process conditions with high-resolution patterning plays a crucial role in accelerating chip manufacturing. However, lithography imaging is an extremely complex nonlinear system, and obtaining suitable process conditions requires extensive experimental attempts. This severely creates a bottleneck in optimizing and controlling the lithographic process conditions. Herein, we report a process optimization solution for a contact layer of metal oxide nanoparticle photoresists by combining electron beam lithography (EBL) experiments with machine learning. In this solution, a long short-term memory (LSTM) network and a support vector machine (SVM) model are used to establish the contact hole imaging and process condition classification models, respectively. By combining SVM with the LSTM network, the process conditions that simultaneously satisfy the requirements of the contact hole width and local critical dimension uniformity tolerance can be screened. The verification results demonstrate that the horizontal and vertical contact widths predicted by the LSTM network are highly consistent with the EBL experimental results, and the classification model shows good accuracy, providing a reference for process optimization of a contact layer.

Sub-millisecond lithiothermal synthesis of graphitic meso-microporous carbon.

Porous carbons with concurrently high specific surface area and electronic conductivity are desirable by virtue of their desirable electron and ion transport ability, but conventional preparing methods suffer from either low yield or inferior quality carbons. Here we developed a lithiothermal approach to bottom-up synthesize highly meso-microporous graphitized carbon (MGC). The preparation can be finished in a few milliseconds by the self-propagating reaction between polytetrafluoroethylene powder and molten lithium (Li) metal, during which instant ultra-high temperature (>3000 K) was produced. This instantaneous carbon vaporization and condensation at ultra-high temperatures and in ultra-short duration enable the MGC to show a highly graphitized and continuously cross-coupled open pore structure. MGC displays superior electrochemical capacitor performance of exceptional power capability and ultralong-term cyclability. The processes used to make this carbon are readily scalable to industrial levels.

Functional Optical Fiber Sensors Detecting Imperceptible Physical/Chemical Changes for Smart Batteries.

The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist. Now the battery is still a "black box", thus requiring a deep understanding of its internal state. The battery should "sense its internal physical/chemical conditions", which puts strict requirements on embedded sensing parts. This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed, focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition, electrolyte degradation, electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution. The paper contributes to understanding how to use optical fiber sensors to achieve "real" and "embedded" monitoring. Through the inherent advantages of the advanced optical fiber sensor, it helps clarify the battery internal state and reaction mechanism, aiding in the establishment of more detailed models. These advancements can promote the development of smart batteries, with significant importance lying in essentially promoting the improvement of system consistency. Furthermore, with the help of smart batteries in the future, the importance of consistency can be weakened or even eliminated. The application of advanced optical fiber sensors helps comprehensively improve the battery quality, reliability, and life.

Materials descriptors of machine learning to boost development of lithium-ion batteries.

Traditional methods for developing new materials are no longer sufficient to meet the needs of the human energy transition. Machine learning (ML) artificial intelligence (AI) and advancements have caused materials scientists to realize that using AI/ML to accelerate the development of new materials for batteries is a powerful potential tool. Although the use of certain fixed properties of materials as descriptors to act as a bridge between the two separate disciplines of AI and materials chemistry has been widely investigated, many of the descriptors lack universality and accuracy due to a lack of understanding of the mechanisms by which AI/ML operates. Therefore, understanding the underlying operational mechanisms and learning logic of AI/ML has become mandatory for materials scientists to develop more accurate descriptors. To address those challenges, this paper reviews previous work on AI, machine learning and materials descriptors and introduces the basic logic of AI and machine learning to help materials developers understand their operational mechanisms. Meanwhile, the paper also compares the accuracy of different descriptors and their advantages and disadvantages and highlights the great potential value of accurate descriptors in AI/machine learning applications for battery research, as well as the challenges of developing accurate material descriptors.

PDOL-Based Solid Electrolyte Toward Practical Application: Opportunities and Challenges.

Polymer solid-state lithium batteries (SSLB) are regarded as a promising energy storage technology to meet growing demand due to their high energy density and safety. Ion conductivity, interface stability and battery assembly process are still the main challenges to hurdle the commercialization of SSLB. As the main component of SSLB, poly(1,3-dioxolane) (PDOL)-based solid polymer electrolytes polymerized in-situ are becoming a promising candidate solid electrolyte, for their high ion conductivity at room temperature, good battery electrochemical performances, and simple assembly process. This review analyzes opportunities and challenges of PDOL electrolytes toward practical application for polymer SSLB. The focuses include exploring the polymerization mechanism of DOL, the performance of PDOL composite electrolytes, and the application of PDOL. Furthermore, we provide a perspective on future research directions that need to be emphasized for commercialization of PDOL-based electrolytes in SSLB. The exploration of these schemes facilitates a comprehensive and profound understanding of PDOL-based polymer electrolyte and provides new research ideas to boost them toward practical application in solid-state batteries.

Machine learning in electron beam lithography to boost photoresist formulation design for high-resolution patterning.

The reduction of the critical dimension (CD) usually improves the resolution of patterns and performance of chips. In chip manufacturing, electron beam lithography (EBL) is a promising technology for preparing sub-10 nm patterns, and its imaging resolution is primarily determined by the photoresist formulation. However, the smaller CDs are mainly achieved by optimizing process conditions, and little attention has been paid to the photoresist formulation optimization. Screening suitable photoresist formulations remains a significant challenge due to the considerable time and high cost. Herein, we report a formulation optimization technique of a metal oxide nanoparticle photoresist that combines EBL experiments with a machine learning long short-term memory (LSTM) network. Using the LSTM network, a CD photoresist evaluation model is established. Leveraging the CD model, a photoresist formulation optimizer is developed with a line width of 26 nm. The verification results demonstrate that the CDs predicted by the LSTM network are basically consistent with the EBL experimental results, and the photoresist formulations that meet the CD requirements can be screened. This work opens up a novel perspective to boost photoresist formulation design for high-resolution patterning with artificial intelligence and provides guidance for EBL experiments.

Why the Synthesis Affects Performance of Layered Transition Metal Oxide Cathode Materials for Li-Ion Batteries.

The limited cyclability of high-specific-energy layered transition metal oxide (LiTMO2) cathode materials poses a significant challenge to the industrialization of batteries incorporating these materials. This limitation can be attributed to various factors, with the intrinsic behavior of the crystal structure during the cycle process being a key contributor. These factors include phase transition induced cracks, reduced Li active sites due to Li/Ni mixing, and slower Li+ migration. In addition, the presence of synthesis-induced heterogeneous phases and lattice defects cannot be disregarded as they also contribute to the degradation in performance. Therefore, gaining a profound understanding of the intricate relationship among material synthesis, structure, and performance is imperative for the development of LiTMO2. This paper highlights the pivotal role of structural play in LiTMO2 materials and provides a comprehensive overview of how various control factors influence the specific pathways of structural evolution during the synthesis process. In addition, it summarizes the scientific challenges associated with diverse modification approaches currently employed to address the cyclic failure of materials. The overarching goal is to provide readers with profound insights into the study of LiTMO2.

A Promising Solid-State Synthesis of LiMn1- yFeyPO4 Cathode for Lithium-ion Batteries.

LiMn1-yFeyPO4 (LMFP) is a significant and cost-effective cathode material for Li-ion batteries, with a higher working voltage than LiFePO4 (LFP) and improved safety features compared to layered oxide cathodes. However, its commercial application faces challenges due to a need for a synthesis process to overcome the low Li-ion diffusion kinetics and complex phase transitions. Herein, a solid-state synthesis process using LFP and nano LiMn0.7Fe0.3PO4 (MF73) is proposed. The larger LFP acts as a structural framework fused with nano-MF73, preserving the morphology and high performance of LFP. These results demonstrate that the solid-state reaction occurs quickly, even at a low sintering temperature of 500 °C, and completes at 700 °C. However, contrary to the expectations, the larger LFP particles disappeared and fused into the nano-MF73 particles, revealing that Fe ions diffuse more easily than Mn ions in the olivine framework. This discovery provides valuable insights into understanding ion diffusion in LMFP. Notably, the obtained LMFP can still deliver an initial capacity of 142.3 mAh g-1, and the phase separation during the electrochemical process is significantly suppressed, resulting in good cycling stability (91.1% capacity retention after 300 cycles). These findings offer a promising approach for synthesizing LMFP with improved performance and stability.

3D Printing Manufacturing of Lithium Batteries: Prospects and Challenges toward Practical Applications.

The manufacturing and assembly of components within cells have a direct impact on the sample performance. Conventional processes restrict the shapes, dimensions, and structures of the commercially available batteries. 3D printing, a novel manufacturing process for precision and practicality, is expected to revolutionize the lithium battery industry owing to its advantages of customization, mechanization, and intelligence. This technique can be used to effectively construct intricate 3D structures that enhance the designability, integrity, and electrochemical performance of both liquid- and solid-state lithium batteries. In this study, an overview of the development of 3D printing technologies is provided and their suitability for comparison with conventional printing processes is assessed. Various 3D printing technologies applicable to lithium-ion batteries have been systematically introduced, especially more practical composite printing technologies. The practicality, limitations, and optimization of 3D printing are discussed dialectically for various battery modules, including electrodes, electrolytes, and functional architectures. In addition, all-printed batteries are emphatically introduced. Finally, the prospects and challenges of 3D printing in the battery industry are evaluated.

Ultrahigh-printing-speed photoresists for additive manufacturing.

Printing technology for precise additive manufacturing at the nanoscale currently relies on two-photon lithography. Although this methodology can overcome the Rayleigh limit to achieve nanoscale structures, it still operates at too slow of a speed for large-scale practical applications. Here we show an extremely sensitive zirconium oxide hybrid-(2,4-bis(trichloromethyl)-6-(4-methoxystyryl)-1,3,5-triazine) (ZrO2-BTMST) photoresist system that can achieve a printing speed of 7.77 m s-1, which is between three and five orders of magnitude faster than conventional polymer-based photoresists. We build a polygon laser scanner-based two-photon lithography machine with a linear stepping speed approaching 10 m s-1. Using the ZrO2-BTMST photoresist, we fabricate a square raster with an area of 1 cm2 in ~33 min. Furthermore, the extremely small chemical components of the ZrO2-BTMST photoresist enable high-precision patterning, leading to a line width as small as 38 nm. Calculations assisted by characterizations reveal that the unusual sensitivity arises from an efficient light-induced polarity change of the ZrO2 hybrid. We envisage that the exceptional sensitivity of our organic-inorganic hybrid photoresist may lead to a viable large-scale additive manufacturing nanofabrication technology.