The slot nozzle is widely used in industrial applications for its high heat transfer coefficient. Nevertheless, there is still a lack of effective measures to further enhance its heat transfer performance. This study introduces a rotating insert inside the nozzle to achieve both passive (stationary) and active (rotating) heat transfer enhancement. A numerical model is developed to investigate the heat transfer performance of this novel configuration. Numerical results indicate that the heat transfer of the slot nozzle with a rotating insert is significantly superior to that of a traditional nozzle or one with a stationary insert. Moreover, the effects of the insert's configuration parameters, such as its position, diameter, and rotational velocity, are analyzed in detail. Finally, an optimal design of the rotating insert configuration is conducted using a neural network. The average heat transfer of the optimal design increases by 49.25 % as compared to that of the traditional slot nozzle without an insert.

Objective Most domestic holographic plastic processing equipment still relies on embossed holography technology. This traditional technology cannot fabricate reflection volume holograms that possess three-dimensional (3D) effects visible to the naked eye, nor can it meet the high quality printing requirements for holographic optical elements (HOE). To satisfy the urgent demand for advanced processing equipment within the field of holographic plastics manufacturing, a holographic wavefront printing equipment termed HG-I was designed and manufactured. This system demodulated and projected a computer-generated hologram (CGH) through a phase-only spatial light modulator (SLM) onto a photosensitive polymer material, causing the object light carrying information to interfere with a reference beam. The final goal of this research was to print holographic plastics successfully and fabricate reflection volume holograms with naked-eye visible three-dimensional effects.Methods The investigation began with an analysis of the diffracted light field of the object beam from both theoretical and experimental levels. The unfavorable effects and structural characteristics introduced by the discrete pixel structure of the SLM within the object diffraction field were systematically evaluated. To suppress these discrete artifacts, two improvement methods were proposed, utilizing a spatial band-pass filter and a digital blazed grating, respectively. Subsequently, corresponding 4f optical filtering systems were constructed within the optical path. These experimental setups were utilized for quantitative testing and comprehensive comparative analysis, focusing primarily on two core indicators: the spatial spectral distribution and the object light energy utilization. Second, the system was optimized at the optical design level to balance the inherent trade-off between the size of the individual holographic element and the overall viewing angle. A set of exchangeable telecentric lens groups with magnification ratios of 1 and 1/7.5 was designed and manufactured, respectively. This hardware adaptation satisfied the printing requirements across different scenarios. Furthermore, motion planning strategies were optimized and studied. Theoretical analysis was combined with experimental validation to investigate how different scanning paths affected stitching gaps, specifically comparing the differences between the S-shaped path and the unidirectional path. Finally, the overall printing quality of large-scale volume holograms was optimized by introducing an overlap splicing strategy for adjacent holographic elements alongside a cyclic exposure process.Results and Discussions Experimental results indicated that both filtering schemes worked effectively when critical conditions were met. High-order repeated ghost images were effectively eliminated when the filter aperture reached the critical threshold conditions. Quantitative measurements revealed that the aperture size influenced the energy utilization of object light. Under identical aperture conditions, the band-pass filtering method increased the energy utilization of object light by up to 199.4% compared with the digital blazed grating method. Additionally, the band-pass filtering method offered the advantage of a simpler optical path alignment in practical applications, though it simultaneously introduced a loss of low-frequency spectral information. Furthermore, the introduction of the exchangeable telecentric lens groups allowed the equipment to adapt to different application scenarios. This lens system successfully achieved a balance between two modes: the first was the high-efficiency printing of large-scale two-dimensional (2D) holograms corresponding to a small viewing angle (8.15°), and the second was 3D displays requiring a wide viewing angle (64.47°). Regarding mechanical motion planning, the translation stage trajectories were evaluated and analyzed. The results demonstrated that a unidirectional printing path effectively avoided the gap misalignment problem between odd rows and even rows. Finally, implementing a 50% overlap splicing strategy combined with a multi-cycle low-dose exposure process effectively improved the quality of the boundary regions. The row gap width decreased from an initial 355 μm to 231 μm, and the column gap width dropped from 420 μm to 300 μm. Moreover, data analysis confirmed that the average grayscale deviation decreased from 0.413 to 0.030 for row gaps, and from 0.380 to 0.090 for column gaps. These quantitative results indicated that the microscopic stitching seams were significantly weakened, and the overall visual fragmentation degree of the large-scale holograms was markedly reduced.Conclusions The developed reflection volume holographic wavefront printing equipment (HG-I) realized the independent development of the optical system design and the control software system, which together constituted a relatively complete hardware-software integrated equipment system. The equipment possessed the capability for stable, continuous operation over long periods, and it can successfully fabricate reflection volume holograms that reconstruct under white light conditions while preserving complete three-dimensional depth and parallax information. Implementing the overlap splicing and cyclic printing process can effectively optimize the printing quality of large-scale holograms. This research provided a verified hardware and software configuration along with a processing method, establishing a foundation for the development of advanced domestic processing equipment in holographic plastics manufacturing.

The interfacial bonding strength is critical for structural integrity and reliability of overmolded components. While extensive research has focused on optimizing processing parameters and applying surface modifications to enhance interfacial bonding, the fundamental role of interface resin still remains insufficiently understood. This study systematically investigated the effect of interface resin distribution on interfacial performance of overmolded components. Manufactured woven and unidirectional carbon fiber reinforced polyether ether ketone laminates were employed as inserts to represent different surface resin patterns. Results revealed that resin-rich zones at intersections of warp and weft fibers in woven laminates significantly enhanced interfacial bonding compared to resin-deficient surfaces of unidirectional laminates. Furthermore, by introducing resin films onto insert surface, it was demonstrated that an optimal interfacial resin layer acted as an engineered "adhesive," promoting crack deflection from interface into injection part and thereby substantially improving bonding strength. Microscopic analysis confirmed transition of failure mode and associated strengthening mechanism. The interlaminar shear strength of overmolded components with woven and unidirectional laminates increased by 23.8% and 39.3%, respectively. This work elucidates the significant influence of insert's surface microstructure and provides a potential approach for strengthening interfaces through interface resin design, offering a practical guidance for manufacturing high-performance overmolded composites.

Morphotropic phase boundary (MPB) has been demonstrated in various ferroelectric polymers near which piezoelectric coefficient d33 is substantially enhanced. However, all these ferroelectric polymers contain expensive trifluoroethylene while the Curie temperature Tc remains low, limiting their practical applications. Here, MPB is explored in trifluoroethylene-free poly(vinylidene fluoride-co-tetrafluoroethylene) copolymer by grafting design. We find that grafting induces order-to-disorder structural evolution mediated by the formation of MPB reminiscent of composition- and irradiation-induced MPB in trifluoroethylene-contained ferroelectric polymers. Meanwhile, we show that local conformational disorder is pinned by head-head defects inherent to tetrafluoroethylene, which is essential to maintain high Tc. Consequently, markedly improved d33 of -41.6 pC N-1 and high Tc of over 130°C are concurrently achieved in graft poly(vinylidene fluoride-co-tetrafluoroethylene) copolymers, outperforming currently existing ferroelectric polymers with high Tc. These findings add a trifluoroethylene-free member into MPB family, which offers a solution to address the long-standing inverse d33-Tc relationship in ferroelectric materials.

Use of the morphotropic phase boundary (MPB) is a promising approach to enhance the electrocaloric effect in ferroelectric polymers. This is usually achieved by a composition method, and polymer processing near the MPB to tune electrocaloric response has attracted little attention. Here, the relative stability between disordered 3/1-helix and ordered all-trans conformations is leveraged by uniaxial stretching to improve the electrocaloric effect in relaxor ferroelectric polymers under low electric fields. It is found that the stretching technique enables a considerably more enhanced electrocaloric response in polymer composition near the MPB at room temperature, compared with counterparts corresponding to the relaxor phase. The electrocaloric-induced temperature change is found to be 4.5 K under a low electric field of 50 MV m−1 in stretched relaxor ferroelectric polymers at room temperature, corresponding to a 60% enhancement over pristine counterparts. This result highlights the critical role of polymer processing in optimizing electrocaloric properties, especially near the MPB, and this can be extended to improve other functionalities, such as piezoelectric response, in relaxor ferroelectric polymers.

Ferroelectric polymers have been intensively explored for flexible and wearable applications. Most studies concentrate on poly(vinylidene fluoride) and its copolymer poly(vinylidene fluoride-co-trifluoroethylene), and little attention has been given to poly(vinylidene fluoride-co-tetrafluoroethylene) owing to its weak piezoelectricity and pyroelectricity despite its dramatically lower cost. Here, it is reported that both piezoelectricity and pyroelectricity are markedly enhanced in poly(vinylidene fluoride-co-tetrafluoroethylene) via a hot-pressing technique. The long-range ferroelectric phase with improved crystallinity is stabilized via hot pressing, leading to an enhanced piezoelectric coefficient d(33 )of -42.2 pC N(-1 )and a pyroelectric coefficient of 83.8 mu C m(-2) K-1, outperforming the benchmarks poly(vinylidene fluoride) and poly(vinylidene fluoride-co-trifluoroethylene) 80/20 mol. % while preserving a high Curie temperature of more than 160 degrees C. Moreover, this strategy yields outstanding piezoelectric and pyroelectric figures of merit. These findings pave the way toward the scalable fabrication of high-performance ferroelectric polymers for piezoelectric and pyroelectric applications.

To address the challenges of untimely detection and online monitoring lag in injection molding quality anomalies, this study proposes a mixed feature attention-artificial neural network (MFA-ANN) model for high-precision online prediction of product weight. By integrating mechanism-based with data-driven analysis, the proposed architecture decouples time series data (e.g., melt flow dynamics, thermal profiles) from non-time series data (e.g., mold features, pressure settings), enabling hierarchical feature extraction. A self-attention mechanism is strategically embedded during cross-domain feature fusion to dynamically calibrate inter-modality feature weights, thereby emphasizing critical determinants of weight variability. The results demonstrate that the MFA-ANN model achieves a RMSE of 0.0281 with 0.5 g weight fluctuation tolerance, outperforming conventional benchmarks: a 25.1% accuracy improvement over non-time series ANN models, 23.0% over LSTM networks, 25.7% over SVR, and 15.6% over RF models, respectively. Ablation studies quantitatively validate the synergistic enhancement derived from the integration of mixed feature modeling (contributing 22.4%) and the attention mechanism (contributing 11.2%), significantly enhancing the model's adaptability to varying working conditions and its resistance to noise. Moreover, critical sensitivity analyses further reveal that data resolution significantly impacts prediction reliability, low-fidelity sensor inputs degrade performance by 23.8% RMSE compared to high-precision measurements. Overall, this study provides an efficient and reliable solution for the intelligent quality control of injection molding processes.

The automotive front bumper is a critical safety component that must simultaneously achieve a thin-walled, large-scale structure and high impact strength. Fiber-reinforced microcellular injection molding (FR-MIM) is widely used for manufacturing such components; however, increasing demands for environmental sustainability and energy efficiency have made weight reduction a priority. This creates a challenge, as lightweighting often degrades dimensional accuracy and impact strength, both of which are essential for crash safety. Consequently, achieving a balanced optimization of weight reduction, dimensional accuracy, and impact strength within a narrow processing window remains a key issue in FR-MIM. To address this challenge, an RNET-based multi-objective hybrid optimization method (RSM-NSGA-II-Entropy-weighted TOPSIS) is proposed to determine optimal FR-MIM process parameters. Response surface methodology (RSM) is first employed to establish quantitative relationships between key process parameters-melt temperature, mold temperature, injection speed, SCF gas injection rate, and V/P switch-over position-and performance indicators, including weight reduction, warpage, and impact strength. The NSGA-II algorithm is then used to explore trade-offs among these objectives and generate a Pareto-optimal solution set. Finally, the entropy-weighted TOPSIS method objectively determines the optimal parameter combination based on data dispersion. Numerical simulations and molding experiments validate the proposed approach. The optimized parameters achieved a 11.48% increase in weight reduction, a 35.5% decrease in warpage, and a 7.65% improvement in impact strength. The RSM models demonstrate high predictive accuracy, with average relative errors below 5%. Overall, the proposed method effectively balances conflicting performance objectives and provides a practical strategy for automotive lightweight design.

Interfaces in structural composites have long been treated as passive links and weak points to be strengthened. Here, the interface is designed as a programmed layer that directs mechanical and thermal loads into distinct damage pathways. A three-dimensional aramid fiber network is embedded within carbon fiber/polyphenylene sulfide (CF/PPS) laminates, designed to mimic the crack deflection capability of nacre and the heat-induced delamination behavior of Banksia seed pods. The bioinspired composite exhibits a penetration depth 60% lower than that of aluminum under 60 J impact and arrests projectiles at 212 m s-1 through multiscale toughening (crack deflection, fiber bridging, and hierarchical fibrillation). Under flame exposure, in situ thermography and X-ray tomography show that heat becomes localized at the designed interface due to thermal conductivity mismatch, and this localized heating leads to delamination, forming an insulating air gap that acts as a self-sacrificing thermal barrier. This design yields an ultralight (1.62 g cm-3) composite with V-0 flammability and LOI > 50%, which maintains a backside temperature of ∼252 °C under a 1300 °C flame while preserving structural integrity. As a honeycomb sandwich panel, it withstands 150 J impacts, providing excellent impact protection, which highlights its potential as a lightweight material candidate for protective structures such as electric vehicle battery enclosures.

Mechanical performance of the composite structures is dependent on the local fiber orientation. The manufacturing-induced fiber orientation variations should be considered to precisely predict the performances. However, limited simulation studies have addressed the impact of manufacturing-induced fiber orientation variations on composite structure. This paper proposes an equivalent mechanical modeling approach for the variable-thickness composite structures that considers the manufacturing process. Initially, the spatial distribution of fiber orientation variation is determined through draping simulation. Subsequently, the local equivalent mechanical properties of the structure are evaluated using a shell-solid mesh mapping technique combined with a multi-layer equivalent mechanical method. To assess the effectiveness of the proposed method, composite tapered beams are examined, showing close agreement with reference results and a maximum natural-frequency error below 7%. The approach is further applied to the DTMB4119 composite propeller, a representative variable-thickness structure exhibiting fiber shear deformation during lay-up. The predicted mode shapes match the reference solution well, with errors in low-order modal frequencies and displacements under 7% and 2%. Owing to its straightforward implementation and suitability for automated modeling, the method can significantly accelerate the design process while maintaining high accuracy, making it well aligned with engineering applications.

Automated fiber placement (AFP) provides an efficient route for manufacturing thermoplastic composite laminates. However, in-situ consolidation remains constrained by a limited effective thermal history and rapid cooling, thereby limiting interfacial healing, crystallization development, and interlaminar quality. Here, we propose an in-mold annealing (IMA) strategy for AFP-fabricated carbon fiber reinforced low-melt poly(aryl ether ketone) (CF/LM-PAEK) laminates. IMA is a mold-constrained post-AFP thermal treatment designed to extend the effective thermal history of the laminate without demolding. We systematically investigate the effects of tool temperature and subsequent IMA on the consolidation quality and performance of AFP-fabricated laminates. The optimal IMA condition was identified as 250 °C for 3 h. Under this condition, the void content was reduced to 0.387%, and the DSC crystallinity increased to 35.72%. Consequently, the ILSS and flexural strength reached 91.29 MPa and 1355.11 MPa, corresponding to 93.1% and 99.6% of the thermoformed reference, respectively. These results indicate that IMA enables post-AFP interfacial healing, void reduction, and further crystallization, and provides a practical route to improve laminate quality while preserving AFP process continuity.

Dry spots are the most concerned molding defects in Liquid Composite Molding (LCM). Their final size and position are affected by the evolution of entrapped air in the flow field, thus predicting this evolution via simulation is crucial. However, existing macroscale entrapped air prediction models cannot effectively predict both the migration and size evolution of entrapped air simultaneously when the injection pressure is reduced or the vent ports are opened. We developed a macroscale three-dimensional compressible two-phase flow model to predict the evolution of entrapped air and the subsequent formation of dry spots during the LCM filling process. Thereafter, sandwich-panel and flat-panel vacuum infusion experiments were conducted to verify the proposed model. Simulation results indicate that the proposed model can accurately predict evolution of entrapped air regions' size and position in the experiments.

Voids, as the most prevalent defect, can significantly diminish the mechanical properties of composites. Traditional offline methods can only detect porosity after the component has been molded, thus failing to offer data feedback for process parameter optimization. Existing ultrasonic signals are strongly influenced by the internal structure of composites, which makes the signal processing complicated. In this study, we introduce a simple in-situ monitoring method for porosity based on effective permittivity of composites. Among the three prevalent effective permittivity models which can calculate the void volume fraction, volume-average mixing rule was verified by experiment to be more suitable than the Maxwell-Garnett and Bruggeman equations. Based on the volume-average mixing rule and capacitance signals, the porosity can be calculated. Compared to the actual values, the errors in porosity obtained by the in-situ monitoring are less than 10%. This proves the in-situ monitoring method can provide accurate and reliable data support for the real-time regulation of process parameters.

Metallic lithium plating on graphite anodes is a major cell degradation process and triggers the internal short circuit, resulting in the capacity loss and safety risks. However, understanding the interplay of Li plating and reaction uniformity is limited by the coupling of complex electrochemistry and diffusion processes in the electrode. In this study, a mesoscale heterogeneous model is developed to investigate the correlation between the reaction uniformity and Li plating mechanism. Compared with the well-known Li+ concentration gradient, reaction uniformity plays the most important role in the Li plating behavior. The results demonstrate that the spatial distribution of graphite electrodes evolves in a stage-dependent manner, which underlies an intrinsic self-regulation mechanism but breaks down under high C-rate conditions, ultimately leading to localized lithium plating. To address this, we propose a lithium-storage-layer electrode (LSLE) to regulate the reaction uniformity through migrating the exposed reaction surface and Li+ concentration gradient. The combination of simulations and experiments demonstrate that the LSLE benefits the reaction uniformity and suppresses Li plating, thereby improving the capacity retention by similar to 30% after 80 cycles at 2C. Overall, this work offers fundamental understanding of Li plating process and practical guidance for electrode design toward long-cycle and safe batteries.

Accurate estimation of the State of Health (SOH) for lithium-ion batteries is crucial for extending service life and mitigating safety risks. However, the prevailing data-driven approaches for SOH estimation regard the internal degradation mechanisms as a black box, resulting in significant challenges such as high data requirements for complex physical models, limited model transferability, and poor electrochemical interpretability. To address these challenges with precision and comprehensiveness, we propose a hybrid experts-decoupled and physics-informed neural network (HyED-PINN), which decouples the degradation behavior and different physical fields. The HyED-PINN leverages expert models for different physical fields to extract electrochemical quantities, and employs physics-informed loss functions to train and recouple the related quantities for accurate SOH estimation. Notably, the sufficient transferability of HyED-PINN is validated by the combination of diverse datasets (electrode types, charge/discharge protocols, and operating conditions). The proposed model achieves high prediction accuracy, with the lowest RMSE reaching 0.54% on the CALCE dataset and remaining below 1.6% across all evaluated datasets. Compared with conventional neural networks, the HyED-PINN exhibits superior performance in small-sample scenarios, enhanced transfer learning capability, and importantly improved electrochemical interpretability. Overall, this study highlights the promise of physics-informed machine learning for accurate SOH estimation and extends its applicability to real-time risk detection of physical fields during battery operation.

Automated fiber placement (AFP) provides an efficient route for manufacturing thermoplastic composite laminates. However, in-situ consolidation remains constrained by a limited effective thermal history and rapid cooling, thereby limiting interfacial healing, crystallization development, and interlaminar quality. Here, we propose an in-mold annealing (IMA) strategy for AFP-fabricated carbon fiber reinforced low-melt poly (aryl ether ketone) (CF/LM-PAEK) laminates. IMA is a mold-constrained post-AFP thermal treatment designed to extend the effective thermal history of the laminate without demolding. We systematically investigate the effects of tool temperature and subsequent IMA on the consolidation quality and performance of AFP-fabricated laminates. The optimal IMA condition was identified as 250 °C for 3 h. Under this condition, the void content was reduced to 0.387%, and the DSC crystallinity increased to 34.91%. Consequently, the ILSS and flexural strength reached 91.29 MPa and 1355.11 MPa, corresponding to 90.5% and 95.4% of the thermoformed reference, respectively. These results indicate that IMA promotes post-AFP void reduction, further crystallization, and improved interlaminar structural continuity. It provides a practical route to improve laminate quality while keeping the laminate on the same tool after AFP.

Microcellular injection molding process combined with in-mold decoration (MIM/IMD) is a crucial technique for producing lightweight polymer products. However, it faces a significant challenge to achieve strong adhesion between decorative film and polymer substrate. Gas entrapment at the film-substrate interface often results in defects such as bulges and weak interfacial bonding. To address these defects, this study examines the dynamic behavior of gas cells during MIM/IMD processing and proposes a strategy to mitigate bulges by modifying molding conditions. Specifically, we demonstrate that high melt and mold temperatures reduce the melt viscosity and slows the cooling rate. This facilitates the re-dissolution of trapped gas into the melt at the interface before solidification. Numerical simulations and molding experiments are performed to assess melt viscosity, frozen layer fraction, bulge coverage ratio (R), and interfacial peel strength. The results show that re-dissolution of trapped gas is essential for preventing bulges. When the melt temperature is raised from 180 °C to 240 °C and the mold temperature from 35 °C to 80 °C, cell density in the skin layer more than doubled, bulge coverage decreases to nearly zero, and peel strength improves significantly. However, excessive high temperature causes large cell sizes, small cell density, long molding cycles, and weak mechanical properties. This method effectively reduces interfacial bulges and offers a feasible approach for optimizing MIM/IMD manufacturing processes.

High-rise buildings and electric vehicles in high-solar-irradiation regions consume large amounts of energy for climate control, posing a significant challenge to global sustainability. The primary obstacle lies in integrating zero-energy, efficient cooling solutions without compromising comfort. As urbanization intensifies, innovative solutions must balance environmental impact with functionality. We propose a holistic strategy featuring a photoluminescent-assisted hierarchical metafabric sunshade for post-glass spectral regulation. This material leverages to achieve a 95.8% emissivity in the mid-infrared (MIR) band and 94.3% reflectivity in the solar band. These particles efficiently convert absorbed ultraviolet (UV) light into visible light with an absolute quantum yield of 16.4%, significantly boosting cooling performance beyond traditional passive radiative materials. In real-world testing, the metafabric sunshade achieved a temperature reduction of 17.8°C and 14.4°C compared to the vehicles with blank and commercial sunshades, respectively. These results suggest that photoluminescent-enhanced metafabrics represent a sustainable, energy-saving pathway for cooling high-rise infrastructure and transportation, offering a scalable solution to mitigate urban heat islands and advance global sustainability goals.

Ferroelectric polymers exhibit numerous advantages for flexible and wearable electromechanical applications. However, their piezoelectric coefficient d33 remains relatively low while most previous approaches to improve d33 mainly focus on intramolecular engineering. Other than using intramolecular approaches, here we describe an intermolecular crosslinking strategy to achieve markedly enhanced d33 of -95.0 picocoulombs per newton in crosslinked ferroelectric poly(vinylidene fluoride-co-trifluoroethylene) copolymers. First-principles calculations reveal that intermolecular crosslinking creates strong local conformational heterogeneity facilitating ease of bond rotation near the crosslinking sites, which leads to a flattened energy landscape, resulting in substantially improved d33 response. We show that crosslinking enabled by solution casting process enhances piezoelectric properties across a variety of crosslinking agents. Our work offers a facile platform for rational modulation of piezoelectricity of ferroelectric polymers, representing a crucial step towards large-scale manufacturing of lightweight, flexible, and scalable ferroelectric polymers for developing high-performance electromechanical devices.

Thick electrodes are a promising strategy for boosting lithium-ion battery energy density, compounded by significant transport limitations. While tremendous efforts focus on these kinetic issues, the equally critical thermodynamic influence on reaction heterogeneity has been largely overlooked. In this work, an electrochemical-mechanical coupled model is developed to elucidate the regulatory role of the equilibrium potential in thick electrodes. The sloping equilibrium potential creates a potential gradient from the current collector side to the separator side during discharge, partially compensating for kinetic overpotentials and promoting the participation of active materials near the current collector. Inspired by this mechanism, we propose a gradient thermodynamic electrode design, where higher-potential materials are placed on the current collector side to reinforce the local driving force and enhance reaction homogenization. Compared with conventional single-material thick electrodes, this bilayer design promotes greater participation of active materials near the current collector, leading to higher discharge capacity at high rates, reduced lithiation heterogeneity and interfacial damage, and improved cycling stability. The designed bilayer electrode with low-equilibrium-potential LFP on the separator side and high-equilibrium-potential NCM523 on the current collector side exhibits strong thermodynamic regulation, delivering a 62.5% capacity retention at 4C and 98.1% after 100 cycles at 1C. This strategy provides a thermodynamic regulation route for thick electrode design and offers a promising pathway toward next generation high energy density batteries.