With the rapid growth of retired lithium-ion batteries (LIBs), effective recycling is essential for a sustainable circular economy. Direct recycling is attractive due to its simplicity, low cost, and high efficiency, yet its performance is limited by residual carbon and fluorine in spent cathode powders and by an incomplete understanding of structural rejuvenation. Here, we introduce a low-temperature plasma treatment to efficiently remove carbon and fluorine residues, enabling effective re-lithiation of spent LiNixMnyCozO2 (NMC) cathodes. The regenerated NMC-622 and NMC-811 deliver high capacities of 170 and 202 mAh g-1, respectively, whereas NMC-622 retains 87% capacity after 1,100 cycles in pouch cells, outperforming commercial references. In situ synchrotron X-ray diffraction reveals synchronous recovery of the a axis lattice constant and Li/Ni mixing, linking Ni oxidation to cation ordering. Techno-economic and environmental analyses show similar to 50% reductions in energy use, emissions, and cost, demonstrating the scalability of this direct recycling strategy.

The integration of water-based electrolytes into zinc-ion batteries encounters challenges due to the limited voltage window of water, interfacial side reactions of mobile counterions, and the growth of zinc metal (Zn0) dendrites during charge. In this study, we introduce a nonfluorinated, cation-conducting polyelectrolyte membrane (PEM) designed to alleviate these challenges by suppressing the reactivities of both water and counterions. This PEM forms hydrogen bonds with water molecules through its proton-accepting side chains, thus shifting the lowest unoccupied molecular orbital (LUMO) energy of water from -0.37 to -0.14 eV and inducing a negative shift in the onset potential for hydrogen evolution by 110 mV. Additionally, it immobilizes the counteranions onto the polymer backbones via covalent bonding, hence making the Zn2+ transference number nearly unity (0.96). Meanwhile, the high modulus PEM establishes a solid-state diffusion barrier to homogenize the interfacial Zn2+ flux, leading to 3D in-plane interfacial Zn2+ diffusion and compact Zn0 plating within the (002) plane. Atomic resolution scanning transmission electron microscopy (STEM) reveals corrosion-free Zn0 deposition without electrolyte degradation, while operando transition X-ray microscopy (TXM) further illustrates the real-time dendrite-free Zn0 plating process at 5 mA/cm2. Consequently, the unique properties of this water-binding and anion-tethering PEM enable enhanced electrochemical performance without employing highly fluorinated and expensive anions. This PEM demonstrates a durability of 3800 h in Zn0-Zn0 symmetric cells and a lifetime of 6000 cycles in Zn0-LiV3O8 full cells.

Understanding and overcoming the chemomechanical failures of polycrystalline inorganic solid-state electrolytes (SSEs) are critical for next-generation all-solid-state batteries. Yet, so far, the nanoscale origin of SSEs' chemomechanical failure under operation conditions remains a mystery. Here, by using in situ electron microscopy, we decipher the nanoscale origin of the soft-to-hard short-circuit transition─a conventionally underestimated failure mechanism─caused by electronic leakage-induced Li0 precipitation in SSEs. For the first time, we directly visualize stochastic Li0 interconnection-induced soft short circuits, during which the SSEs undergo the transition from a nominal electronic insulator to a state exhibiting memristor-like nonlinear conduction (electronic leakages), ultimately evolving into hard short circuits. Furthermore, we first capture intragranular cracking caused by Li0 penetration, demonstrating that fully wetted Li0 can fracture polycrystalline oxide SSEs via a liquid-metal embrittlement-like mechanism. Guided by these insights, we show that incorporating an electronically insulating and mechanically resilient 3D polymer network into an inorganic/polymer composite SSE effectively suppresses Li0 precipitation, interconnection, and short circuits, significantly enhancing its electrochemical stability. Our work, by elucidating the soft-to-hard short-circuit transition kinetics of SSEs, offers new insights into their nanoscale failure mechanisms.

Understanding topological defects-controlled structural degradation of layered oxides-a key cathode material for high-performance lithium-ion batteries-plays a critical role in developing next-generation cathode materials. Here, by constructing a nanobattery in an electron microscope enabling atomic-scale monitoring of electrochemcial reactions, we captured the electrochemically driven atomistic dynamics and evolution of dislocations-a most important topological defect in material. We deciphered how dislocations nucleate, move, and annihilate within layered cathodes at the atomic scale. Specifically, we found two types of dislocation configurations, i.e., single dislocations and dislocation dipoles. Both pure dislocation glide/climb and mixed motions were captured, and the dislocation glide and climb velocities were first experimentally measured. Moreover, dislocation activity-mediated structural degradation such as crack nucleation, phase transformation, and lattice reorientation was unraveled. Our work provides deep insights into the atomistic dynamics of electrochemically driven dislocation activities in layered oxides.

Electrochemically converting carbon dioxide (CO 2 ) and nitrate (NO 3 − ) into urea via the C─N coupling route offers a sustainable alternative to the traditional industrial urea production technology, but it is still limited by poor yield rate, low Faradaic efficiency, and insufficient coupling kinetics. Herein, a high‐density Ga─Y dual‐atom catalyst is developed with loading up to 14.1 wt.% of Ga and Y supported on N, P‐co‐doped carbon substrate (Ga/Y‐CNP) for urea electrosynthesis. The catalyst facilitates efficient C─N coupling through co‐reduction of CO 2 and NO 3 − , resulting in a high urea yield rate of 41.9 mmol h −1 g −1 and a Faradaic efficiency of 22.1% at −1.4 V versus the reversible hydrogen electrode. In situ spectroscopy and theoretical calculations reveal that the superior performance is attributed to the cross‐tuning between adjacent pair Ga─Y sites, which can mutually optimize their electronic states for facilitating CO 2 reduction to *CO at Ga sites and promoting NO 3 − conversion to hydroxylamine (*NH 2 OH) at Y sites, followed by spontaneous coupling of *CO and *NH 2 OH intermediates at Ga─Y sites to form C─N bonds. This work offers a pioneering strategy to manipulate C─N coupling pathways by cross‐tuning active sites to produce high‐value‐added chemicals.

Solid polymer electrolytes (SPEs) are widely recognized as promising candidates for enabling solid‐state lithium metal batteries (SSLMBs) with improved safety, high energy density, and extended cycling life. The traditional perspective posits that increasing the mechanical modulus of SPEs enhances their capacity to regulate Li0 deposition and suppress dendrite penetration. However, this study reveals a distinct failure mechanism: a rigid SPE with a high storage modulus suffers from delamination‐induced cell failure due to its inability to accommodate the volumetric changes of the Li0 anode. To address these limitations, we developed a hierarchical SPE incorporating an adhesive adaptation layer (AAL) positioned between the Li0 anode and the rigid SPE. The AAL combines strong adhesive strength, effectively mitigating delamination, with flowability, allowing it to eliminate interfacial voids and defects. Structural characterization via Cryo‐TEM and SEM demonstrates that this hierarchical design facilitates uniform, dense, and whisker‐free Li0 deposition, in sharp contrast to the uneven and porous morphology observed with the rigid SPE alone. Furthermore, the enhanced interfacial stability promotes the formation of an inorganic‐enriched SEI layer, contributing to long‐term cycling stability. As a result, the H‐SPE exhibits superior electrochemical performance, achieving 87% capacity over 960 cycles when paired with high‐loading (1.6 mAh/cm2) NMC622 cathode.

Our recent work, published in Nature (610, 67–73, 2022) and Nature Energy (695–702, 2023), demonstrates the effectiveness of high-entropy doping (HE) in tackling the stability-capacity challenge of zero-cobalt layered cathode active materials (CAMs). While the HE Ni-80% (HE-N80) CAM exhibits competitive discharge capacity, it slightly lags behind NMC-811. This presentation delves into the broader applicability of the HE strategy and highlights the crucial role of pre-CAM microstructure optimization. Through pre-CAM microstructure optimization, we significantly reduce layered CAMs' anti-site defects, leading to a notable enhancement in discharge capacity. This optimization strategy increases the discharge capacity of the HE-N80 cathode from 210 mAh/g to 220 mAh/g under 0.1C charging and 2.5-4.4V voltage window. Moreover, cycling stability sees a substantial improvement, with a 99.5% capacity retention at 0.5C after 100 cycles. The effectiveness of this methodology extends to CAMs with higher nickel content, as demonstrated by discharge capacities of 225 mAh/g for zero-cobalt HE-N85 and 235 mAh/g for zero-cobalt HE-N90 under the same conditions. References: Nature 610, 67–73 (2022). Nature Energy, 695–702 (2023).

Lithium metal (Li0) solid-state batteries encounter implementation challenges due to dendrite formation, side reactions, and movement of the electrode-electrolyte interface in cycling. Notably, voids and cracks formed during battery fabrication/operation are hot spots for failure. Here, a self-healing, flowable yet solid electrolyte composed of mobile ceramic crystals embedded in a reconfigurable polymer network is reported. This electrolyte can auto-repair voids and cracks through a two-step self-healing process that occurs at a fast rate of 5.6 µm h-1. A dynamical phase diagram is generated, showing the material can switch between liquid and solid forms in response to external strain rates. The flowability of the electrolyte allows it to accommodate the electrode volume change during Li0 stripping. Simultaneously, the electrolyte maintains a solid form with high tensile strength (0.28 MPa), facilitating the regulation of mossy Li0 deposition. The chemistries and kinetics are studied by operando synchrotron X-ray and in situ transmission electron microscopy (TEM). Solid-state NMR reveals a dual-phase ion conduction pathway and rapid Li+ diffusion through the stable polymer-ceramic interphase. This designed electrolyte exhibits extended cycling life in Li0-Li0 cells, reaching 12 000 h at 0.2 mA cm-2 and 5000 h at 0.5 mA cm-2. Furthermore, owing to its high critical current density of 9 mA cm-2, the Li0-LiNi0.8Mn0.1Co0.1O2 (NMC811) full cell demonstrates stable cycling at 5 mA cm-2 for 1100 cycles, retaining 88% of its capacity, even under near-zero stack pressure conditions.

High-Ni-content layered materials are promising cathodes for next-generation lithium-ion batteries. However, investigating the atomic configurations of the delithiation-induced complex phase boundaries and their transitions remains challenging. Here, by using deep-learning-aided super-resolution electron microscopy, we resolve the intralayer transition motifs at complex phase boundaries in high-Ni cathodes. We reveal that an O3 → O1 transformation driven by delithiation leads to the formation of two types of O1–O3 interface, the continuous- and abrupt-transition interfaces. The interfacial misfit is accommodated by a continuous shear-transition zone and an abrupt structural unit, respectively. Atomic-scale simulations show that uneven in-plane Li+ distribution contributes to the formation of both types of interface, and the abrupt transition is energetically more favourable in a delithiated state where O1 is dominant, or when there is an uneven in-plane Li+ distribution in a delithiated O3 lattice. Moreover, a twin-like motif that introduces structural units analogous to the abrupt-type O1–O3 interface is also uncovered. The structural transition motifs resolved in this study provide further understanding of shear-induced phase transformations and phase boundaries in high-Ni layered cathodes. High-Ni-content layered cathodes are promising for lithium-ion batteries, but investigating their delithiation-induced phase boundaries is challenging. Intralayer transition motifs at complex phase boundaries in these high-Ni electrodes are now resolved using deep-learning-aided super-resolution electron microscopy.

High-nickel-content layered oxides are one of the most promising lithium-ion battery (LIB) cathode materials for electric vehicle applications.A fundamental understanding of the working/failure modes as well as the structure-performance relationship of current high-nickel layered oxide cathodes will provide theoretical guidance [1, 2] and foster the design and development of nextgeneration cathode materials for high energy-density and long-life lithium-ion batteries.In the past few years, by coupling in-situ atomic-resolution imaging, electron diffraction, electron tomography and artificial-intelligence-enhanced TEM, we systematically elucidated the lattice-shear induced O3→O1 phase transition, O3-O1 phase boundary structure and the degradation pathway of O1 phase.We first captured the atomic structures of delithiation-induced O1 phase and related misfit defect/crack nucleation at O1-O3 interface in LiNiO 2 [3].Also, we first reported the existence of O1 phase in commercial NMC-811 cathode and elucidated the intra-layer structural transition motifs at O1-O3 interfaces aided by deep-learning-based super-resolution TEM [4].By using in-situ TEM, the stability and evolution of O1 phase were investigated and a new phase transformation mechanism, that is O1→rock salt transformation was discovered [5].We demonstrated for the first time that O1 phase provides a highway for oxygen loss (meaning lower energy barrier for cation mixingtransition metal migration from transition metal layers to Li layers) and deactivation of layered cathodes.Later on, we extended our study to both single-crystalline and polycrystal NMC-811 and ultrahigh-Ni cathodes and demonstrated how O1 phase transformation and evolution could influence the battery's electrochemical performance [6,7].Most recently, we discover that severe chemomechanical deformation during battery operation triggers O3→O1 phase transformation as well as the formation of bending bands and kinks in layered cathodes [8].Distinct from conventional O3→O1 phase transformation which is driven by delithiation-induced self-destabilization, the deformation-induced O3→O1 phase transformation is driven by delithiation coupled with local stress concentration.The new failure mechanism uncovers the connection between mechanical degradation and phase transformation in layered oxides for the first time.With the fundamental insights gained from the systematic TEM study, we successfully designed a zero-strain high-Ni and cobalt-free cathode through compositionally complex doping strategy [9].The new knowledge is expected to applicable to layered oxide cathodes in general and will offer important guidance for optimization of current layered cathodes as well as for the design of new cathode materials in the future [10].

Electrochemical CO 2 reduction reaction (CO 2 RR) to high-value product, CO, not only provides a key feedstock for the well-established Fischer—Tropsch process but also mitigates the greenhouse effect. However, it suffers from sluggish reaction kinetics, competitive hydrogen evolution reaction, and low selectivity. Herein, we report non-precious Cu-Sn diatomic sites anchored on nitrogen-doped porous carbon (CuSn/NPC) as an efficient catalyst for CO 2 RR to CO. The catalyst exhibits outstanding selectivity with CO Faradaic efficiency (FE) up to 99.1%, much higher than those of individual Cu (66.2%) and Sn (51.3%) single-atom catalysts. Moreover, high stability is confirmed by consecutive 24 h electrolysis with high selectivity from CO 2 to CO. Theoretical calculations reveal an obvious activation of CO 2 with weakened C—O bonds and distorted CO 2 configuration upon chemisorption on the CuSn/NPC catalyst. It is also suggested CuSn/NPC is more selective for the CO 2 RR with dominant CO production during the electrolysis, rather than the competing hydrogen evolution reaction.

Solid polymer electrolytes (SPEs) offer potential advantages over liquid electrolytes, including flexibility, safety, and processability. However, they suffer from low room-temperature ionic conductivity. Recently, it has been reported a poly(ethyl acrylate) based (polyEA) SPE, by incorporating 50 wt% of succinonitrile (SN) solid plasticizer, 30 wt% of lithium salt and 5 wt% of fluoroethylene carbonate additive, which achieves a high room-temperature ionic conductivity of 1.01 × 10 −3 S cm −1 (Nat. Nanotechnol, 2022, 17, 768-776). This novel SPE exhibits stability against Li 0 and anodic stability up to 4.9 V vs Li + /Li. However, the specific mechanism responsible for its high ionic conductivity remains elusive. In this work, by adjusting the weight ratio of SN in the SPE, a transition from Vogel-Fulcher-Tammann to Arrhenius ion-conducting behavior is observed. It is demonstrated that the addition of SN leads to the gradual decoupling of Li-ion from the polymer backbone and its coordination with SN, as revealed by 6 Li solid-state nuclear magnetic resonance spectroscopy. As a result, Li-ion migration primarily occurs through SN rather than the segmental motion of the polymer backbone. Performances of the SPE in Cu||Li, Li||Li and a LiFePO 4 ||Li pouch cells are shown to demonstrate the commercial viability of this SPE in Li 0 -anode solid-state batteries.

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.

Phase transformation─a universal phenomenon in materials─plays a key role in determining their properties. Resolving complex phase domains in materials is critical to fostering a new fundamental understanding that facilitates new material development. So far, although conventional classification strategies such as order-parameter methods have been developed to distinguish remarkably disparate phases, highly accurate and efficient phase segmentation for material systems composed of multiphases remains unavailable. Here, by coupling hard-attention-enhanced U-Net network and geometry simulation with atomic-resolution transmission electron microscopy, we successfully developed a deep-learning tool enabling automated atom-by-atom phase segmentation of intertwined phase domains in technologically important cathode materials for lithium-ion batteries. The new strategy outperforms traditional methods and quantitatively elucidates the correlation between the multiple phases formed during battery operation. Our work demonstrates how deep learning can be employed to foster an in-depth understanding of phase transformation-related key issues in complex materials.

Decoding spatial symmetry in TEM images and fine structure in EELS spectra using deep learning is a challenging task that requires addressing several key issues.One of the main challenges is the lack of labeled data for training deep learning models to detect, classify, and regress different types of spatial symmetry and near-edge fine structures of different bonding environments.This can make it difficult to develop accurate and robust models that can generalize well to new data.Another challenge is selecting the correct network architecture for the specific task at hand.In this talk, I will discuss methods for generating high-quality labeled data and leveraging the latest advances in natural language processing for spatial and spectral data.I will review recent research in this area [1][2][3] and offer insights into how to overcome these challenges to develop accurate and robust deep learning models for decoding spatial symmetry and fine structure in EELS spectra [4].

Lithium metal anodes are the "Holy Grail" of next generation high-energy-density Li batteries, yet the nucleation and growth kinetics of Li metal at the nanoscale still remain a myth. Here, by combining in situ electron microscopy and atomistic simulations, we decipher the nanoscale nucleation and growth mechanisms of Li metal on carbon. We find that upon nucleation, Li atoms rapidly aggregate to form droplet-shaped nanoparticles that incline to coalesce through diffusion mediated fusion. Statistical observation shows that the Li nucleation follows a mixed nucleation mode different from conventional instantaneous or progressive nucleation model. With increased particle size, the droplet-like Li particles transform into faceted crystals driven by surface energy minimization. Atomistic calculations reveal that the size -dependent Li diffusivity facilitates the coalescence and morphological evolution of the Li particles. This liquid-to-solid-like transformation during deposition is completely reversible upon stripping. This work, by unraveling the fundamental nano-and atomic-scale pathways dominating Li metal nucleation and growth behaviors, offers new insights into the deposition/stripping mechanism of Li metal.

The pronounced compositional inhomogeneity observed in refractory high-entropy alloys (HEAs), as opposed to non-refractory HEAs, has an important influence on their mechanical properties, thereby posing a significant challenge for the development of high-performance refractory HEAs. In this work, by combining transmission electron microscopy imaging, chemical analysis, and nano-hardness tests, we investigate the compositional inhomogeneities in a series of sintered nanostructured HEAs and elucidate their influence on the material's hardness. We reveal that the compositional inhomogeneity of the sintered nanostructured HEAs is temperature- and component-dependent. By correlating the hardness of nanostructured HEAs to the evolving compositional inhomogeneity, our work demonstrates that the compositional inhomogeneity in nanostructured HEAs can be tuned by sintering temperature or alloying towards optimized microstructure and hardness.

Understanding chemomechanical degradations of layered oxide cathodes is critical to developing next-generation cathodes for lithium-ion batteries. So far, although the multimodal phase degradations in layered cathodes have been extensively studied, current understanding of their mechanical failure is only limited to cracking. Here, by using deep-learning-aided super-resolution imaging, we uncover a stress-driven phase degradation mechanism distinct from a conventional pathway driven by delithiation-induced self-destabilization in a technologically important layered cathode. We show that severe lattice bending caused by chemomechanical stress concentration could directly lead to phase transformation through interlayer shear. The O3→O1 transformation forms not only in bending bands but also in bending-induced kink structures, suggesting that the stress-driven phase transformation is a typical degradation modality widely existing in the material. Density functional theory (DFT) calculations confirm that the bending-induced O3→O1 phase transformation in delithiated lattice is energetically favorable. Our work offers new understanding of the mechanical deformation-induced phase transformation in layered oxide cathodes.