Longitudinal spatial charge transfer optimization in composite cathodes enables ultra-stable all-solid-state batteries

Junwei Lianga, Kun Qianb, Caijin Xiaoc, Yuhang Lia, Zhichun Sia, Lin Zengd, Songbai Hane, Yan-Bing Hea, Feiyu Kanga and Ming Liu*a
aShenzhen All-Solid-State Lithium Battery Electrolyte Engineering Research Center, Institute of Materials Research (IMR), Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, P. R. China. E-mail: liuming@sz.tsinghua.edu.cn
bDongguan Key Laboratory of Interdisciplinary Science for Advanced Materials and Large-Scale Scientific Facilities, School of Physical Sciences, Great Bay University, Dongguan 523000, P. R. China
cDepartment of Nuclear Physics, China Institute of Atomic Energy, Beijing 102413, P. R. China
dShenzhen Key Laboratory of Advanced Energy Storage, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen 518055, China
eShenzhen Key Laboratory of Solid-State Batteries, Institute of Major Scientific Facilities for New Materials, Southern University of Science and Technology, Shenzhen, 518055, China

Received 17th June 2025 , Accepted 28th July 2025

First published on 29th July 2025


Abstract

All-solid-state batteries (ASSBs) promise high energy density and inherent safety but face critical challenges in the complex charge transfer process across the longitudinal cathode. Here, through the Multiphysics simulation, it is firstly revealed that charge transfer critically governs electrochemical reaction heterogeneity, dictating where reactions initiate preferentially along the length of cathodes. Building on this insight, a charge-transfer-optimized cathode (CTOC) is proposed to conceptually validate the effectiveness of charge-transfer regulation in homogenizing the longitudinal Li concentration. The CTOC features a double-layer architecture: a carbon-free layer with large-sized catholytes near the separator to enhance Li-ion transfer while reducing electron conduction and a carbon-containing layer near the current collector to ensure efficient electronic conductivity, thus tandemly modulating the spatial ion and electron transfer dynamics along the longitudnal axis. Through graded ionic and electronic conduction to achieve decoupled but synchronized ion and electron transport pathways, the CTOC enables longitudinally homogeneous Li distribution throughout the cathode. As a result, CTOC exhibits excellent cycling performance, retaining 82.7% capacity after 2000 cycles at 2C, a 27.4% durability improvement over conventional single-layer designs. This work establishes electrode-level charge transfer optimization as a design principle for heterogeneous reaction control, offering fundamental insights and practical strategies for high-performance ASSBs.



Broader context

All-solid-state batteries (ASSBs) promise enhanced safety and energy density over conventional Li-ion batteries but face inherent charge transfer challenges. Solid–solid interfacial contacts disrupt ion/electron transport, causing spatially heterogeneous reactions—especially in thick cathodes—that reduce active material utilization, accelerate chemo-mechanical degradation, and compromise energy density/cycling stability. However, direct observation of heterogeneous Li concentration distribution is difficult due to the Li insensitivity of most characterization methods (such as X-rays). Only a few methods such as neutron depth profiling (NDP) and time-of-flight secondary ion mass spectrometry (TOF-SIMS), which use thermal neutron capture reactions with 6Li or mass-to-charge ratio, enable directly obtaining the Li concentration distribution. In this work, the relative charge transfer of ions and electrons is firstly revealed to critically govern electrochemical reaction heterogeneity, dictating where reactions initiate preferentially along longitudinal cathode. Building on this insight, a charge-transfer-optimized cathode (CTOC) is introduced with a double-layer architecture to decouple and synchronize ion/electron transport pathways. The results of NDP and TOF-SIMS collectively highlight the critical role of charge transfer optimization in homogenizing electrochemical reactions and Li distribution. The charge transfer optimization principles provide fundamental insights and actionable strategies for deployment of high-performance ASSBs.

Introduction

ASSBs have emerged as a transformative advancement in energy storage technology, replacing flammable liquid organic electrolytes with solid-state electrolytes (SEs) to achieve high energy density and intrinsic safety.1–6 Unlike conventional Li-ion batteries, where cathodes are immersed in a fluid and continuous ionic conduction medium, ASSBs face inherent challenges rooted in solid–solid interfacial contact limitations, such as complex interfacial transport, contact loss due to volumetric changes and poorly conducting decomposition products.7 These constraints severely disrupt the formation of continuous transport networks within the composite cathodes, particularly leading to localized bottlenecks of Li-ion transfer in thick cathodes that are impeding for high energy density.8,9

To overcome the ionic transfer limitations, strategies of catholyte particle-size reduction have been extensively employed to increase the interfacial contacts between cathode active materials (CAMs) and catholytes.10–13 These approaches effectively reduce the porosity of composite cathodes and create additional ionic contact sites and pathways, thereby significantly elevating the electrochemical performance of ASSBs. Furthermore, the catholytes mixture with a designed ratio between nanoscale and microscale particles has been demonstrated to promote intimate CAMs-catholytes interface contact while reducing Li-ion transport tortuosity through the large micron-sized catholyte, enabling exceptional rate capability.14 Nevertheless, the Li concentration distribution within composite cathodes during charge–discharge processes has not been sufficiently investigated in current studies, despite its potentially profound implications for accessible capacity, rate capability, and cycling durability.

In addition to the particle size optimization of catholytes, electrode geometry design is also crucial to achieve high ionic transport efficiency in thick cathodes. Gradient designs are successfully implemented in lithium-ion batteries,15,16 exploiting porous networks infiltrated by liquid electrolytes. ASSBs require different design principles because pores degrade performance by disrupting ionic and/or electronic contacts. A promising strategy involves gradient composite cathodes,17 where the composite cathode near the separator side is designed for high ionic conductivity, while the composite cathode adjacent to the current collector enhances electronic conductivity. Simulation results demonstrate that the introduction of a double-layer cathode architecture exhibits significant potential to improve ASSBs performance, in which the CAMs content is lower near the separator and higher near the current collector.18 As further proof of concept, a three-layer gradient cathode is experimentally fabricated to improve effective charge transfer, using a low content of CAMs on the separator side and gradually increasing its content toward the current collector, which achieves better rate performance, reducing overpotential at a high current density.19 Such gradient cathode design compensates for longitudinal charge transfer limitations across the cathode, while sacrificing the achievable energy density by reducing the CAM content away from the current collector. Moreover, the mechanism by which such gradient architectures influence electrochemical reaction heterogeneity and subsequently induce heterogeneous Li distribution remains unclear. In particular, how the ionic and electronic charge transfer fundamentally govern nonhomogeneous reactions requires further elucidation, which is of great significance for optimizing CAMs utilization and suppressing localized degradation.

Here, we reveal through the Multiphysics simulation that the relative charge transfer dynamics of ions and electrons fundamentally determine the propagation direction of reaction heterogeneity along the longitudinal axis of the cathode. Experimental validation confirms that single-layer conventional cathodes (CC) naturally form a pronounced depth-dependent Li concentration gradient due to unbalanced charge transfer, even with nanoscale catholytes, which is in good agreement with the simulation results. To address this heterogeneity, a CTOC architecture featuring a carbon-free layer with large-sized catholytes near the separator and a carbon-containing layer near the current collector is engineered. Significantly advancing beyond conventional gradient cathodes, CTOC achieves complete carbon elimination in the SE-adjacent layer and uniform CAM fraction across layers, accelerating charge transfer while preserving energy density without active materials sacrifice. Therefore, the CTOC achieves spatially graded ionic and electronic transport pathways to promote fast charge transfer for mitigating electrochemical heterogeneity, thereby alleviating inhomogeneous Li distribution at the cathode level. Multimodal analyses, such as neutron depth profiling (NDP) and time-of-flight secondary ion mass spectrometry (TOF-SIMS), jointly confirm the effectiveness of CTOC in homogenizing Li distribution along longitudinal axis of the cathode, enabling exceptional durability and rate capability. Our results reveal the critical yet overlooked role of macroscopic electrode-scale charge transfer optimization while providing a general strategy and actionable insights for electrode design in ASSBs.

Results and discussion

Optimized design of composite cathodes

For the purpose of investigating the cathode-scale charge transfer processes, the effective ionic and electronic conductivities of composite cathodes are utilized to precisely quantify the charge transfer dynamics. To this end, the relative electronic transfer capability (te) and relative ionic transfer capability (tion) are defined as te = σe/(σe + σion) and tion = σion/(σe + σion), where σe and σion denote the effective electronic and ionic conductivities of the composite cathode, respectively. In order to systematically explore the intrinsic connections between ionic/electronic charge transfer and electrochemical processes, we employed COMSOL Multiphysics simulation to adjust the te (or tion) values. The simulation results reveal that the relative charge transfer dynamics of electrons and ions intrinsically dictate the electrochemical heterogeneous reaction fronts. As shown in Fig. 1 and Fig. S1, several characteristic scenarios corresponding to specific te values are illustrated. If te → 1 (tion → 0, ion transfer-limited), preferential electrochemical reactions initiate and persist near the separator side, developing obvious heterogeneous reactions along the longitudinal axis of the cathode (Fig. 1a). However, reducing te by merely 0.1 significantly mitigates Li concentration gradients (Fig. 1b), highlighting the critical influence of relative ionic–electronic transfer on heterogeneous Li distribution. Furthermore, for intermediate te values, reaction synchronize from both cathode sides, leaving delayed reactions in the middle of the cathode (Fig. S1a). And te → 0 (tion → 1, electron transfer-limited) drives reaction front propagation from the current collector side (Fig. S1b). This theoretical framework implies intrinsic limitations of CC containing conductive additives shown in Fig. 1b–d, even using nanoscale small-sized catholytes (Fig. S2; σion = 3.4 mS cm−1, Fig. S4), where effective electronic conductivity exceeds ionic conductivity by three orders of magnitude (122.4 vs. 0.18 mS cm−1, te = 0.9985). Considering the Li content in catholytes is constant, the Li concentration gradient caused by the heterogeneous electrochemical reaction can be attributed to the lithiation/delithiation heterogeneity of CAMs along the cathode longitudinal axis, which will inevitably play a role in utilization of CAMs, performance decay and chemical-mechanical degradation, as previously reported.20
image file: d5ee03407h-f1.tif
Fig. 1 Schematic diagram of Multiphysics simulation for te → 1 (a), te = 0.9 (b) and CTOC (c) of charge transfer, determining the direction of heterogeneous reactions (the current collector is at 0 μm and the separator is at 100 μm). (d) Schematic diagram of ASSBs with a conventional single-layer carbon-containing cathode (CC). (e) and (f) DC polarization measurements of CC using ion-blocking (e) and electron-blocking (f) electrodes (the inset is the monitored time–current response). (g) Schematic diagram of ASSBs with CTOC. (h) and (i) DC polarization measurements of CTOC using ion-blocking (h) and electron-blocking (i) electrodes (the inset is the monitored time–current response).

Considering that the relative ionic and electronic transfer capabilities govern cathode electrochemical heterogeneity, regulating the te becomes essential for designing high-performance cathodes. However, it should be noted that achieving an intermediate te value by enhancing the effective ionic conductivity of composite cathodes remains challenging due to the intrinsically limited ionic conductivity of SEs.21 Consequently, the widely researched gradient cathode designs15,16 are adopted to accelerate charge transfer, further mitigating heterogeneous Li distribution along the longitudinal axis. Thus, a proof-of-concept CTOC employing a strategically stacked architecture was proposed. As the ultrahigh electronic conductivity and low ion transfer are responsible for heterogeneous reactions, a carbon-free composite cathode layer with micron large-sized catholytes (Fig. S3; σion = 7.5 mS cm−1, Fig. S4) was added and stacked near the separator to enhance ionic transfer while weakening electronic conduction. Meanwhile, a carbon-containing CC layer was stacked near the current collector to ensure high electronic conductivity, thus synergistically modulating the spatial ionic and electronic transfer dynamics along the longitudinal axis of the cathode, as shown in Fig. 1e. Multiphysics simulation reveal that at identical te values (te = 0.9), the double-layer gradient cathode further mitigates heterogeneous Li concentration gradients compared to CC by reducing ionic resistance at the separator-side interface and lowering electronic resistance at the collector-side interface (Fig. 1c vs. Fig. 1b). DC polarization measurements quantitatively confirmed that the carbon-free layer has a 44% increase in ionic conductivity and a 99% decrease in electronic conductivity compared with CC (Fig. S5). As a result, the designed CTOC has an overall lower electronic conductivity and higher ionic conductivity (Fig. 1f and g), which is ascribed to the reduction of electronic conductivity due to the carbon-free layer and the improvement of ionic transport due to the large micron-sized catholytes.

Adjustments to the cathode architecture will reshape ionic/electronic charge transfer pathways, so it is necessary to confirm its spatial configuration. But conventional morphological characterizations struggle to capture complete cross-sectional profiles of thick cathodes, which often exceed hundreds of micrometers. Plasma-focused ion beam scanning electron microscopy (PFIB-SEM), leveraging a Xe-ion plasma source, enables rapid processing and etching of cross-sections spanning hundreds of micrometers, making it very suitable for observing the continuous cross-sectional morphology and spatial distribution of thick electrodes (Fig. 2a). Consequently, PFIB-SEM was employed to meticulously characterize the longitudnal morphology and architectural integrity of CTOC. As shown in Fig. 2b–e, the hierarchical structure exhibited distinct spatial segregation and intimate contact between nanoscale and microscale catholytes, confirming the successful implementation of the charge transfer optimized architecture. Besides, it can be clearly observed that the composite cathode with small-sized catholytes (SCC) is uniformly distributed near the current collector, showing a typical nanoscale size. While the carbon-free cathode with a large-sized catholytes (LCC) was distributed near the separator, showing a micron size, which is consistent with the SEM results (Fig. S3). Such designed architecture establishes complementary charge transfer pathways: the LCC layer forms fast ionic transfer networks, while the SCC layer ensures efficient electronic conduction.


image file: d5ee03407h-f2.tif
Fig. 2 (a) Schematic diagram of PFIB-SEM and 3D reconstruction. (b) Cross-sectional SEM image of CTOC. (c) and (d) Front view of CAMs (c) and catholytes (d) by 3D reconstruction. (e) 3D reconstructed side view of CTOC. Note: the current collector is at the top side of the image and the separator is at the bottom side of the image.

Enhanced rate capability and cycling performance of ASSBs with CTOC

Given that the heterogeneous reactions directly impact critical electrochemical performance metrics such as rate capability and cycling durability, a systematic evaluation of the rate and cycle performance between CC and CTOC was prioritized under identical test conditions (25 °C). To ensure a fair comparison, three distinct areal loadings (2.4, 3.6, and 4.8 mAh cm−2) were implemented. At the 2.4 mAh cm−2 loading level, both architectures exhibited comparable specific capacities of ∼190 mAh g−1 at a 0.1C low rate. However, under high-rate conditions (5C), the CTOC demonstrated enhanced rate capability, delivering 74 mAh g−1, over 5-fold of the CC counterpart (14 mAh g−1), as shown in Fig. 3a. This advantage of rate performance was confirmed and continued at higher areal loadings of 3.6 and 4.8 mAh cm−2 as shown in Fig. S6. The capacity enhancement at high rates can be attributed to the rapid ion transfer that reduces cathode polarization, implying that heterogeneous reactions are mitigated and CAMs utilization is improved. And it is worth noting that CTOC exhibited higher initial coulombic efficiency (ICE) than that of CC regardless of the areal loading (Fig. S7–S9), which is ascribed to the reduction of side reactions as well as decreased interfacial impedance and polarization due to the introduction of the carbon-free layer.22–24 In addition, the capacity–voltage curves of CTOC at a high rate showed smaller polarization (Fig. S7–S9), which also suggests enhanced charge transfer dynamics. These significant improvements stem from the CTOC's graded ionic and electronic transport pathways, which facilitate the synergistic rapid charge transfer and homogenize electrochemical reactions. Diffusion kinetic analysis via galvanostatic intermittent titration technique (GITT, Fig. 3b) revealed an approximately 1.5-fold increase in Li-ion diffusion coefficient for CTOC compared to CC (Fig. 3c), also quantitatively validating the advantage of architecture design in accelerating Li-ion charge transfer dynamics.
image file: d5ee03407h-f3.tif
Fig. 3 Comparison of electrochemical performance between CC and CTOC. (a) Rate performances. (b) GITT curves. (c) Diffusion coefficient. (d) Cycling performance at 0.5C. (e) Discharge medium voltage decay curves at 0.5C. (f) Cycling performance at 2C. (g) Comparison of areal capacity and cycle performance between CTOC and other reported all-solid-state batteries. The above tests were conducted at the same areal capacity of 2.4 mAh cm−2.

Furthermore, the CTOC design significantly impacts cycling durability through electrode-scale graded charge transfer. After 300 cycles at 0.5C, CTOC maintained 88.1% capacity while that of CC is 62.4% (Fig. 3d). Remarkably, similar advantages of CTOC in cycling stability persist under higher areal loading (3.6 and 4.8 mAh cm−2, Fig. S10), demonstrating the universal applicability of such CTOC architectural strategy. Besides, the voltage polarization is closely related to charge transfer dynamics decay, where CTOC architecture demonstrates 80% lower average voltage decay of the discharge medium voltage at 0.5C compared to CC (0.08 vs. 0.41 mV per cycle, Fig. 3e), suggesting that the intrinsic charge transfer limitation has been broken. The discharge medium voltage decay during 0.5C cycling at high areal capacity shows the same conclusion (Fig. S11 and S12). More importantly, the cycling performance gap amplifies at elevated rates, with CTOC retaining 82.7% capacity after 2000 cycles at 2C, an obvious 27.4% improvement over CC's 55.3% (Fig. 3f). The capacity–voltage curves of CTOC during 2C cycling also shows smaller polarization, indicating the improvement of charge transfer dynamics during the high-rate (dis)charge process (Fig. S13). The CTOC architecture shows 75% lower average voltage decay at a high rate of 2C compared to CC (0.03 vs. 0.12 mV per cycle, Fig. S14), suggesting that the charge transfer dynamics has been improved. The enhanced cycling durability indicates that heterogeneous reaction-induced chem-mechanical degradation has been significantly suppressed, thereby enabling more efficient utilization of the CAMs. Even compared with state-of-the-art studies,25–37 the CTOC strategy delivers obvious advantages in high areal loading and ultra-stable cyclability (Fig. 3g). These results collectively demonstrated that the graded ionic and electronic transport pathways could fundamentally reshape charge transfer dynamics and mitigate the performance decay caused by chemical–mechanical degradation.

Improved reaction homogeneity in CTOC

The enhanced electrochemical performance of CTOC strongly indicates the alleviation of longitudinal reaction heterogeneity in the composite cathodes. To probe the dynamic evolution of this homogeneous reaction, operando XRD was conducted on mold-extracted pressed cell pellets at a low charging rate of 0.1C for CC and CTOC. As illustrated in Fig. 4a and b, the shifting of NCM's (003) diffraction peak in both cathode architectures was tracked, revealing comparable de-lithiation trajectories. They show similar initial low-angle shifts followed by high-angle transitions, a typical phase evolution feature of Ni-rich layered oxides.38 Nevertheless, the details of XRD curves reveal critical temporal and spatial evolution distinctions. Firstly, the CTOC exhibited earlier peak displacement initiation at 43 min (Fig. 4b), which is much earlier than that of CC (68 min as shown in Fig. 4a), indicating accelerated electrochemical reaction dynamics of CAMs enabled by the coordinated rapid charge transfer. Moreover, the extracted XRD patterns from the operando dataset with identical voltages confirmed the same conclusion. CC's (003) peak was almost completely consistent with the pristine after charging to 3.65 V, while that of CTOC exhibited a significant peak shift at the same charging voltage (Fig. S15). This temporal disparity of the electrochemical process strongly indicates enhanced electrochemical dynamics and homogeneity across the cathode longitudinal axis.
image file: d5ee03407h-f4.tif
Fig. 4 (a) and (b) Operando XRD patterns of CC (a) and CTOC (b) at 0.1C with a CAM loading of 2.4 mAh cm−2. (c) Schematic diagram of ex situ XRD measurements for cathode powder. (d) Ex situ XRD patterns of the (003) and (104) peaks of CC and CTOC at 2C full charged.

More importantly, the phase transition process further highlights the impact of charge transfer-determined electrochemical reaction heterogeneity. During the H2 → H3 phase transformation process, CC exhibited pronounced lattice contraction with a 0.74° angular shift in the (003) peak (Fig. 4a), accompanied by obvious peak splitting indicative of spatially heterogeneous de-lithiation among CAM particles. In contrast, CTOC demonstrated mitigated lattice distortion (0.42° shift) with continuous peak displacement migration (Fig. 4b), strongly verifying its superior electrochemical dynamics and reaction homogeneity. The reduction in the peak shift magnitude directly correlates with the architecturally programmed ion–electron transfer in CTOC configurations, establishing a complementary transport pathway that suppresses localized charge transfer barriers while enforcing reaction homogeneity.

However, it must be mentioned that the depth threshold of laboratory XRD detection on the cathode is ∼30 μm,39 thus leaving the Li concentration distribution of the thick cathode (∼100 μm) near the separator regions undiagnosed. To avoid the partial sampling, which may mask potential heterogeneous Li distribution across the cathode longitudinal axis, complementary ex situ XRD analysis for cathode powders was conducted to provide complete depth-dependent insights. To better probe heterogeneous reactions, the high-rate-fully-charged cell pellets of 2C were mechanically disassembled from the mold, followed by cathode scraping and mixing through hand milling (Fig. 4c). Such post-mortem processing protocol ensures comprehensive crystallographic analysis by eliminating spatially heterogeneous reaction separations. As shown in Fig. 4d, CTOC-derived powders maintained peak integrity at both (003) and (104) characteristic peaks, confirming the efficacy of graded ionic and electronic charge transfer pathways in homogenizing electrochemical reactions and Li distribution. Conversely, CC powders displayed distinct peak splitting at both (003) and (104) reflections, evidencing severe inhomogeneous Li concentration distribution along the cathode longitudinal axis. These multifaceted crystallographic observations jointly confirm that charge transfer optimization of spatially graded ionic/electronic transfer dynamics effectively mitigates cathode-scale reaction heterogeneity, thus enabling higher CAMs utilization and electrochemical performance enhancement.

To further quantitatively monitor the extent of heterogeneous Li distribution governed by charge transfer, NDP was employed based on the capture reaction of 6Li isotopes with thermal neutrons, which generates charged particles (3H+ and 4He2+) possessing characteristic initial kinetic energy (as shown in Fig. 5a). The spatial position and density of Li nuclei were reconstructed through precise measurement of particle emission energy and flux intensities.40 But it should be noted that the detectable depth in NDP is inherently constrained by particle penetration limits in dense materials, confining the quantitative profiling to a region of tens of micrometers near the current collector.40,41 Given the invariant Li content within catholytes during the electrochemical process – a well-justified premise considering their ionic delivery nature – the derived depth-Li concentration profiles accurately reflect the longitudinal Li distribution of CAMs, which could intuitively show the degree of heterogeneous reactions. Post-mortem NDP analysis of 0.1C fully charged cells revealed striking architectural dependencies (Fig. 5b). CTOC configuration demonstrated interface-to-bulk Li homogeneity, quantitatively validating its effectiveness in suppressing electrochemical heterogeneity via spatially graded ionic and electronic transfer pathways. Conversely, CC architecture exhibited pronounced anomalous Li accumulation near the current collector side (20% excess relative to bulk phase concentrations) even with nanoscale catholytes, a hallmark of heterogeneous reaction dictated by unbalanced charge transfer, where electronic conduction dominates far over ionic transfer. The pronounced disparities of heterogeneity in Li distribution underscore the decisive role of charge transfer in governing reaction heterogeneity. By optimizing electrode architectures to regulate charge transfer dynamics, heterogeneous reactions can be effectively suppressed.


image file: d5ee03407h-f5.tif
Fig. 5 (a) Schematic diagram of NDP measurements for solid cathodes. (b) Li concentration curves of CC and CTOC at 0.1C full charge. (c) Cross-sectional SEM image and (d) mapping of Li content in CAMs of CTOC by TOF-SIMS.

In order to further comprehensively acquire the Li distribution across the full cathode longitudinal axis, TOF-SIMS was employed for 2D Li mapping of CAMs. Analysis of four longitudinally aligned square regions revealed remarkable homogeneous Li distribution among CAM particles (Fig. 5c and d). More importantly, this depth-independent Li homogeneity persists from the separator side to the current collector boundary (Fig. 5d), validating the CTOC architecture's capability to enforce Li homogeneity by adjusting charge transfer. The multimodal characterization (NDP and TOF-SIMS) jointly demonstrate that spatially graded charge transfer regulation of ions and electrons intrinsically enables cathode-scale homogeneous reaction and Li distribution. These findings propose unique optimization paradigms, demonstrating that charge transfer regulation through architecture design could mitigate the Li concentration gradient caused by heterogeneous reaction inherent in conventional ASSBs system.

Conclusions

This work reveals a critical yet overlooked intrinsic challenge in ASSBs, in which single-layer conventional carbon-containing cathodes inherently develop cathode-scale inhomogeneous Li concentration distribution due to the unbalanced charge transfer, persisting even with optimized nanoscale catholytes. Multiscale characterization studies reveal that such electrochemical heterogeneity induces cumulative chemical–mechanical degradation, accelerating performance fading. The theoretical–experimental framework ultimately demonstrates that cathode-scale charge transfer optimization can break this limitation through spatially graded ionic/electronic transfer dynamics enabled by architecture design. The CTOC introduces complementary transport pathways that promote Li-ions and electron coordinated transfer across the cathode longitudinal axis, achieving homogeneous electrochemical reactions and Li distribution. Besides, the CTOC is obviously distinct from the existing gradient cathodes: a conductive–additive-free layer near the separator and uncompromised CAM content throughout its architecture, which preserves energy density without active materials sacrifice. As a result, the CTOC architecture exhibits excellent durability (82.7% capacity retention after 2000 cycles at 2C) and rate capability (429% capacity improvement at 5C compared to CC). These findings highlight the importance of charge transfer optimization as a universal paradigm, providing implications and practical strategies for high performance ASSBs.

Experimental

Materials preparation

The bare single-crystal Li(Ni0.85Co0.05Mn0.10)O2 (NCM85) and conductive additive Super P were purchased from Guangdong Canrd New Energy Technology Co., Ltd. They were both dried overnight in a vacuum oven at 120 °C and then transferred into an Ar-filled glove box (O2 < 1 ppm, H2O < 0.01 ppm) for storage before use. In addition, both large and small particle size Li5.5PS4.5Cl1.5 (LPSC1.5) solid electrolytes were purchased from Wuhan Tianshi Kefeng New Energy Technology Co., Ltd and transferred into the Ar-filled glove box for direct use.

Multiphysics simulation

Multiphysics simulations were conducted using COMSOL Multiphysics®6.3, with parameters calibrated against experimental data. Electroneutrality was assumed throughout the whole domain. The electrode thickness is set to 100 μm, and the overall diffusion distance of the electrode is 100 μm. To systematically explore the impact of charge transfer dynamics, five scenarios were modelled: (1) an electron-dominated regime (te → 1), where the electronic conductivity (σe) was assigned 120 mS cm−1 and the ionic conductivity (σion) was set to 0.2 mS cm−1; (2) a mitigated electron-dominated regime (te = 0.9), where the electronic conductivity (σe) was assigned 120 mS cm−1 and the ionic conductivity (σion) was set to 13.3 mS cm−1; (3) a balanced charge transfer regime (te → 0.5), with both σe and σion adjusted to 120 mS cm−1; (4) an ion-dominated regime (te → 0), where σe was reduced to 0.2 mS cm−1 while σion was maintained at 120 mS cm−1; and (5) CTOC regime, where σe = 120 mS cm−1 and σion = 0.2 mS cm−1 for the SCC layer, σe = 1.36 mS cm−1 and σion = 0.26 mS cm−1 for the LCC layer. These configurations aimed to elucidate the interplay between electronic and ionic transport in governing reaction heterogeneity across the cathode.

All-solid-state batteries (ASSBs) assembly

Before assembling the full cell, a composite cathode powder was prepared by hand grinding with an agate mortar and pestle for 30 min. For the composite cathode with nanoscale LPSC1.5 (SCC), the formula is a mixture of NCM85, nanoscale LPSC1.5 and carbon with a mass ratio of 65[thin space (1/6-em)]:[thin space (1/6-em)]30[thin space (1/6-em)]:[thin space (1/6-em)]5. While the formula is a mixture of NCM85 and microscale LPSC1.5 in a mass ratio of 65[thin space (1/6-em)]:[thin space (1/6-em)]35 for the carbon-free composite cathode with large LPSC1.5 (LCC).

After the composite cathodes were prepared, the full cells can be fabricated using a homemade mold battery. First, 100 mg microscale LPSC1.5 was pressed into a pellet in a 10 mm PEEK die under 375 MPa with two stainless steel stamps as the separator. Then, 16 mg SCC was spread on one side of the electrolyte pellet and pressed at 375 MPa to form the CC. Alternatively, 8 mg LCC was evenly spread on one side of the electrolyte pellet and pressed at 125 MPa, followed by adding 8 mg SCC onto the LCC and pressed at 375 MPa to form the CTOC. Finally, a disc of 9 mm In foil (0.1 mm thick) and a disc of 6 mm Li foil (0.1 mm thick) were successively attached to the other side of the electrolyte pellet to act as the anode and pressed again at 125 MPa. Finally, the cell is sealed with an O-ring and tightened with three studs for testing. All the above processes were carried out in the Ar-filled glove box.

Electrochemical measurements

Electrochemical impedance spectroscopy (EIS) measurements were conducted to obtain the ionic conductivity of purchased LPSC1.5. 100 mg SE powder was pressed into a pellet in a 10 mm PEEK die under 375 MPa in the glove box. Then the frequency range from 7 MHz to 100 mHz with a perturbation voltage of 10 mV was applied. The electronic and ionic conductivities of the composite cathode were evaluated through DC polarization at different constant voltages on a BioLogic VMP-3 multichannel electrochemical station at room temperature. To obtain the electronic conductivity, 80 mg composite cathode was pressed at 375 MPa between two stainless steel stamps serving as ion-blocking electrodes. For the ionic conductivity measurements, 100 mg electron-blocking LPSC1.5 was compressed onto each side of the pressed 80 mg composite cathode pellet with a pressure of 375 MPa. Then a 9 mm In (0.1 mm thick) and 6 mm Li (0.1 mm thick) discs were added to both sides, serving as a Li reservoir, and finally the entire stack was compressed under 125 MPa. After resting for 6 h, a constant voltage ranging from 10 mV to 30 mV was applied at 5 mV intervals for 2 hours each, and the current response was monitored. Finally, the effective conductivities were calculated using the formula:
image file: d5ee03407h-t1.tif
where L is the thickness of the composite cathode, R is the resistance obtained from DC polarization measurements, and S represents the area of the composite cathode (which is 0.7854 cm2 here).

Electrochemical performance of assembled cells was performed in a Wuhan Land battery test system at 25 °C and galvanostatic (dis)charge were conducted in a voltage range of 2.6–4.3 V vs. Li+/Li. A specific capacity of 180 mAh g−1 (1C = 180 mA g−1) was considered for the NCM85. For the galvanostatic intermittent titration technique (GITT) test, the cells were charged at 0.1C for 30 min, followed by relaxation for 6 h.

Characterization

X-ray diffraction (XRD) was performed on a Rigaku Smartlab with a scanning speed of 2° min−1 from 10° to 80°, using Cu Kα radiation (λ = 1.54 Å). During the testing process, samples were protected with Kapton tape. In particular, for operando XRD tests, a Be window was used to maintain the pressure required for ASSBs, and the scanning range focused at 17.5° to 19.5°. The morphologies of nanoscale and microscale LPSC1.5 were obtained by field emission scanning electron microscopy (SEM, HITACH SU8010). The continuous cross-sectional morphology and spatial distribution were acquired using plasma-focused ion beam scanning electron microscopy (PFIB-SEM) under liquid nitrogen temperature, and each slice was 50 nm thick. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) was used to acquire the Li content and distribution of NCM along the depth of the fully charged cathodes, and the applied positive voltage was 30 kV with a 790 pA current. Both the PFIB-SEM and TOF-SIMS were conducted on Helios G5 in Thermo Fisher Scientific China Customer Experience Center. The quantitative Li concentration along the depth of the fully delithiated cathodes was obtained by neutron depth profiling (NDP). The Li concentration of the catholytes was assumed to be constant, so that the changes in the Li concentration–depth curve could reflect the evolution of the Li concentration of CAMs. More details and working principles about NDP could be found in the previous literature.41

Unless otherwise specified, all fabrications, tests, and characterizations were performed at room temperature (25 °C).

Author contributions

J. Liang and K. Qian contributed equally to this work. M. Liu, F. Kang and Y. B. He conceived and supervised the project. J. Liang, Y. Li, and M. Liu designed the experiments. J. Liang performed the experiments with the help of Y. Li and K. Qian. C. Xiao conducted the NDP tests. L. Zeng conducted the COMSOL Multiphysics simulations. J. Liang, M. Liu, K. Qian, Y. Li, Z. Si and S. Han performed the data analysis and results discussion. J. Liang, K. Qian and M. Liu wrote and revised the manuscript.

Conflicts of interest

There are no conflicts to declare.

Data availability

The data supporting the findings of this study are available from EES online or from the corresponding author upon reasonable request.

Supplementary information is available from EES online. See DOI: https://doi.org/10.1039/d5ee03407h

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 22479087 and 52203298), the National Key R&D Program of China (No. 2021YFA1202802), the Guangdong Province Foundation for Distinguished Young Scholars (No. 2024B1515020092), the Shenzhen Technical Plan Project (No. JCYJ20220818101003007 and JCYJ20220530143012027), the Shenzhen Stable Support Program for Higher Education Institutions (No. WDZC20231124181029002), the Shenzhen All-Solid-State Lithium Battery Electrolyte Engineering Research Center Upgrade Project (No. XMHT20240108008), the Shenzhen Science and Technology Program (No. KQTD20240729102048053), the Guangdong Innovative and Entrepreneurial Research Team Program (2023ZT10L039) and the Scientific Research Startup Funds (No. QD2022003C). Meanwhile, the authors are grateful for the contribution of the Thermo Fisher China Customer Experience Center to the testing of PFIB-SEM and TOF-SIMS. And the authors acknowledge the neutron spectrometer operated by China Institute of Atomic Energy, Southern University of Science and Technologies (https://cstr.cn/31113.02.CSNS.HPND) and China Spallation Neutron Source (CSNS) (https://cstr.cn/31113.02.CSNS).

Notes and references

  1. A. Manthiram, X. Yu and S. Wang, Nat. Rev. Mater., 2017, 2, 16103 CrossRef CAS .
  2. A. Banerjee, X. Wang, C. Fang, E. A. Wu and Y. S. Meng, Chem. Rev., 2020, 120, 6878–6933 CrossRef CAS PubMed .
  3. X. Hu, Z. Zhang, X. Zhang, Y. Wang, X. Yang, X. Wang, M. Fayena-Greenstein, H. A. Yehezkel, S. Langford, D. Zhou, B. Li, G. Wang and D. Aurbach, Nat. Rev. Mater., 2024, 9, 305–320 CrossRef CAS .
  4. T. Yu, Y. Liu, H. Li, Y. Sun, S. Guo and H. Zhou, Chem. Rev., 2025, 125, 3595–3662 CrossRef CAS PubMed .
  5. Y. Li, S. Song, H. Kim, K. Nomoto, H. Kim, X. Sun, S. Hori, K. Suzuki, N. Matsui, M. Hirayama, T. Mizoguchi, T. Saito, T. Kamiyama and R. Kanno, Science, 2023, 381, 50–53 CrossRef CAS PubMed .
  6. N. Kamaya, K. Homma, Y. Yamakawa, M. Hirayama, R. Kanno, M. Yonemura, T. Kamiyama, Y. Kato, S. Hama, K. Kawamoto and A. Mitsui, Nat. Mater., 2011, 10, 682–686 CrossRef CAS PubMed .
  7. M. Liu, C. Wang, C. Zhao, E. Van Der Maas, K. Lin, V. A. Arszelewska, B. Li, S. Ganapathy and M. Wagemaker, Nat. Commun., 2021, 12, 5943 CrossRef CAS PubMed .
  8. Y. Xiao, Y. Wang, S.-H. Bo, J. C. Kim, L. J. Miara and G. Ceder, Nat. Rev. Mater., 2019, 5, 105–126 CrossRef .
  9. R. Chen, Q. Li, X. Yu, L. Chen and H. Li, Chem. Rev., 2020, 120, 6820–6877 CrossRef CAS PubMed .
  10. E. Schlautmann, A. Weiß, O. Maus, L. Ketter, M. Rana, S. Puls, V. Nickel, C. Gabbey, C. Hartnig, A. Bielefeld and W. G. Zeier, Adv. Energy Mater., 2023, 13, 2302309 CrossRef CAS .
  11. L. Peng, C. Yu, Z. Zhang, R. Xu, M. Sun, L. Zhang, S. Cheng and J. Xie, Energy Environ. Mater., 2023, 6, e12308 CrossRef CAS .
  12. T. Shi, Q. Tu, Y. Tian, Y. Xiao, L. J. Miara, O. Kononova and G. Ceder, Adv. Energy Mater., 2020, 10, 1902881 CrossRef CAS .
  13. A. Karuthedath Parameswaran, J. Azadmanjiri, N. Palaniyandy, B. Pal, S. Palaniswami, L. Dekanovsky, B. Wu and Z. Sofer, Nano Energy, 2023, 105, 107994 CrossRef CAS .
  14. Y. Wang and X. Li, Adv. Mater., 2024, 36, 2309306 CrossRef CAS PubMed .
  15. J. Wu, Z. Ju, X. Zhang, A. C. Marschilok, K. J. Takeuchi, H. Wang, E. S. Takeuchi and G. Yu, Adv. Mater., 2022, 34, 2202780 CrossRef CAS PubMed .
  16. F. Maxharraj, K. Voigt, A. Werwein, C. Heubner, K. Nikolowski, M. Partsch and A. Michaelis, Adv. Energy Sustainability Res., 2025, 6, 2400377 CrossRef CAS .
  17. P. Minnmann, F. Strauss, A. Bielefeld, R. Ruess, P. Adelhelm, S. Burkhardt, S. L. Dreyer, E. Trevisanello, H. Ehrenberg, T. Brezesinski, F. H. Richter and J. Janek, Adv. Energy Mater., 2022, 12, 2201425 CrossRef CAS .
  18. M. Clausnitzer, T. Danner, B. Prifling, M. Neumann, V. Schmidt and A. Latz, Batteries Supercaps, 2024, 7, e202300522 CrossRef CAS .
  19. E. Schlautmann, J. Drews, L. Ketter, M. A. Lange, T. Danner, A. Latz and W. G. Zeier, ACS Energy Lett., 2025, 10, 1664–1670 CrossRef CAS .
  20. M. Jeong, K. G. Naik, Y. Zheng, W. J. Suk, B. S. Vishnugopi, L. Lin, D. Puthusseri, A. C. Chuang, J. S. Okasinski, J. Sakamoto, P. P. Mukherjee and K. B. Hatzell, Adv. Energy Mater., 2024, 14, 2304544 CrossRef CAS .
  21. T. Yu, Y. Liu, H. Li, Y. Sun, S. Guo and H. Zhou, Chem. Rev., 2025, 125, 3595–3662 CrossRef CAS PubMed .
  22. D. H. S. Tan, E. A. Wu, H. Nguyen, Z. Chen, M. A. T. Marple, J.-M. Doux, X. Wang, H. Yang, A. Banerjee and Y. S. Meng, ACS Energy Lett., 2019, 4, 2418–2427 CrossRef CAS .
  23. T. Ates, M. Keller, J. Kulisch, T. Adermann and S. Passerini, Energy Storage Mater., 2019, 17, 204–210 CrossRef .
  24. M. Liu, A. Song, X. Zhang, J. Wang, Y. Fan, G. Wang, H. Tian, Z. Ma and G. Shao, Nano Energy, 2025, 136, 110749 CrossRef CAS .
  25. Y. Chen, X. Gao, Z. Zhen, X. Chen, L. Huang, D. Zhou, T. Hu, B. Ren, R. Xu, J. Chen, X. Chen, L. Cui and G. Wang, Energy Environ. Sci., 2024, 17, 9288–9302 RSC .
  26. X. Zhang, X. Li, S. Weng, S. Wu, Q. Liu, M. Cao, Y. Li, Z. Wang, L. Zhu, R. Xiao, D. Su, X. Yu, H. Li, L. Chen, Z. Wang and X. Wang, Energy Environ. Sci., 2023, 16, 1091–1099 RSC .
  27. C. Kim, Y. Li, I. Jang, W. Wu, Y. Su, H. M. Meyer, J. Keum, J. Nanda and G. Yang, Adv. Mater., 2025, 2502300 CrossRef CAS PubMed .
  28. S. Xu, X. Cheng, S. Yang, Y. Yin, X. Wang, Y. Zhang, D. Ren, Y. Sun, X. Sun, H. Yao and Y. Yang, Adv. Mater., 2024, 36, 2310356 CrossRef CAS PubMed .
  29. L. Hu, Y. Ren, C. Wang, J. Li, Z. Wang, F. Sun, J. Ju, J. Ma, P. Han, S. Dong and G. Cui, Adv. Mater., 2024, 36, 2401909 CrossRef CAS PubMed .
  30. S. Lu, Y. Zhang, H. Lv, X. Zhang, T. Yang, Z. Li, M. Ma, X. Xu and D. Mu, Angew. Chem., Int. Ed., 2025, e202500388 CAS .
  31. D. Wang, C. Liu, R. Wang, T. Zhang, B. Chen, T. Wang, Q. Lu, W. Yin and X. Liu, Angew. Chem., 2025, 137, e202501411 CrossRef .
  32. L. Qian, Y. Huang, C. Dean, I. Kochetkov, B. Singh and L. Nazar, Angew. Chem., 2025, 137, e202413591 CrossRef .
  33. A. Bhadra, M. Brunisholz, J. O. Bonsu and D. Kundu, Adv. Energy Mater., 2025, 15, 2403608 CrossRef CAS .
  34. Y. Li, J. Li, Z. Zeng, Y. Zhu, Y. Deng, J. Cheng, J. Li, H. Zhang, J. Lu, L. Ci and D. Li, ACS Energy Lett., 2025, 10, 2203–2211 CrossRef CAS .
  35. W. Zhao, Y. Zhang, N. Sun, Q. Liu, H. An, Y. Song, B. Deng, J. Wang, G. Yin, F. Kong, S. Lou and J. Wang, ACS Energy Lett., 2023, 8, 5050–5060 CrossRef CAS .
  36. J. Li, Y. Li, T. Liu, S. Zhang, X. Li and L. Ci, Adv. Funct. Mater., 2025, 2504546 CrossRef .
  37. Y. Li, G. Wu, X. Fan, D. Li, H. Liu, X. Zhao, W. Ren, P. Lei, X. Zhao, X. Wang, G. Wang, L. Gao, C.-W. Nan and L.-Z. Fan, Energy Storage Mater., 2025, 77, 104221 CrossRef .
  38. C. Xu, P. J. Reeves, Q. Jacquet and C. P. Grey, Adv. Energy Mater., 2021, 11, 2003404 CrossRef CAS .
  39. L. Zhang, C. Zhao, X. Qin, S. Wang, L. He, K. Qian, T. Han, Z. Yang, F. Kang and B. Li, Small, 2021, 17, 2102055 CrossRef CAS PubMed .
  40. X. Zhang, T. W. Verhallen, F. Labohm and M. Wagemaker, Adv. Energy Mater., 2015, 5, 1500498 CrossRef .
  41. M. Liu, Z. Cheng, K. Qian, T. Verhallen, C. Wang and M. Wagemaker, Chem. Mater., 2019, 31, 4564–4574 CrossRef CAS .

This journal is © The Royal Society of Chemistry 2025
Click here to see how this site uses Cookies. View our privacy policy here.