Scholarly Works, Mechanical Engineering

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Research articles, presentations, and other scholarship

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Holographic thermal mapping in volumes using acoustic lenses
Cengiz, Ceren; Shahab, Shima (IOP Publishing, 2024-09-13)
Acoustic holographic lenses (AHLs) show great potential as a straightforward, inexpensive, and reliable method of sound manipulation. These lenses store the phase and amplitude profile of the desired wavefront when illuminated by a single acoustic source to reconstruct ultrasound pressure fields, induce localized heating, and achieve temporal and spatial thermal effects in acousto-thermal materials like polymers. The ultrasonic energy is transmitted and focused by AHL from a transducer into a particular focal volume. It is then converted to heat by internal friction in the polymer chains, causing the temperature of the polymer to rise at the focus locations while having little to no effect elsewhere. This one-of-a-kind capability is made possible by the development of AHLs to make use of the translation of attenuated pressure fields into programmable heat patterns. However, the impact of acousto-thermal dynamics on the generation of AHLs is largely unexplored. We use a machine learning-assisted single inverse problem approach for rapid and efficient AHLs' design to generate thermal patterns. The process involves the conversion of thermal information into a holographic representation through the utilization of two latent functions: pressure phase and amplitude. Experimental verification is performed for pressure and thermal measurements. The volumetric acousto-thermal analyses of experimental samples are performed to offer a knowledge of the obtained pattern dynamics, as well as the applicability of holographic thermal mapping for precise volumetric temperature control. Finally, the proposed framework aims to provide a solid foundation for volumetric analysis of acousto-thermal patterns within thick samples and for assessing thermal changes with outer surface measurements.
Simultaneous optimal system and controller design for multibody systems with joint friction using direct sensitivities
Verulkar, Adwait; Sandu, Corina; Sandu, Adrian; Dopico, Daniel (Springer, 2025-05-01)
Real-world multibody systems are often subject to phenomena like friction, joint clearances, and external events. These phenomena can significantly impact the optimal design of the system and its controller. This work addresses the gradient-based optimization methodology for multibody dynamic systems with joint friction using a direct sensitivity approach. The Brown-McPhee model has been used to characterize the joint friction in the system. This model is suitable for the study due to its accuracy for dynamic simulation and its compatibility with sensitivity analysis. This novel methodology supports codesign of the multibody system and its controller, which is especially relevant for applications like robotics and servo-mechanical systems, where the actuation and design are highly dependent on each other. Numerical results are obtained using a software package written in Julia with state-of-the-art libraries for automatic differentiation and differential equations. Three case studies are provided to demonstrate the attractive properties of simultaneous optimal design and control approach for certain applications.
Origami-/kirigami-inspired structures: from fundamentals to applications
Li, Suyi; Daqaq, Mohammed (Royal Society, 2024-10-07)
The Scutulum and the Pre-Auricular Aponeurosis in Bats
Pedersen, Scott C.; Snipes, Chelsie C. G.; Carter, Richard T.; Muller, Rolf (Wiley, 2024-11-01)
The external ear in eutherian mammals is composed of the annular, auricular (pinna), and scutellar cartilages. The latter extends between the pinnae, across the top of the head, and lies at the intersection of numerous auricular muscles and is thought to be a sesamoid element. In bats, this scutulum consists of two distinct regions, (1) a thin squama that is in contact with the underlying temporalis fascia and (2) a lateral bossed portion that is lightly tethered to the medial surface of the pinna. The planar size, shape, and proportions of the squama vary by taxa, as does the relative size and thickness of the boss. The origins, insertions, and relative functions of the auricular muscles are complicated. Here, 30 muscles were tallied as to their primary attachment to the pinnae, scutula, or a pre-auricular musculo-aponeurotic plate that is derived from the epicranius. In contrast to Yangochiroptera, the origins and insertions of many auricular muscles have shifted from the scutulum to this aponeurotic plate, in both the Rhinolophidae and Hipposideridae. We propose that this functional shift is a derived character related primarily to the rapid translations and rotations of the pinna in high-duty-cycle rhinolophid and hipposiderid bats.
Practical Application of Passive Air-Coupled Ultrasonic Acoustic Sensors for Wheel Crack Detection
Shaju, Aashish; Kumar, Nikhil; Mantovani, Giovanni; Southward, Steve; Ahmadian, Mehdi (MDPI, 2025-10-03)
Undetected cracks in railroad wheels pose significant safety and economic risks, while current inspection methods are limited by cost, coverage, or contact requirements. This study explores the use of passive, air-coupled ultrasonic acoustic (UA) sensors for detecting wheel damage on stationary or moving wheels. Two controlled datasets of wheelsets, one with clear damage and another with early, service-induced defects, were tested using hammer impacts. An automated system identified high-energy bursts and extracted features in both time and frequency domains, such as decay rate, spectral centroid, and entropy. The results demonstrate the effectiveness of UAE (ultrasonic acoustic emission) techniques through Kernel Density Estimation (KDE) visualization, hypothesis testing with effect sizes, and Receiver Operating Characteristic (ROC) analysis. The decay rate consistently proved to be the most effective discriminator, achieving near-perfect classification of severely damaged wheels and maintaining meaningful separation for early defects. Spectral features provided additional information but were less decisive. The frequency spectrum characteristics were effective across both axial and radial sensor orientations, with ultrasonic frequencies (20–80 kHz) offering higher spectral fidelity than sonic frequencies (1–20 kHz). This work establishes a validated “ground-truth” signature essential for developing a practical wayside detection system. The findings guide a targeted engineering approach to physically isolate this known signature from ambient noise and develop advanced models for reliable in-motion detection.
High cycle performance of twisted and coiled polymer actuators
Tsai, Samuel; Wang, Qiong; Hur, Ohnyoung; Bartlett, Michael D.; King, William P.; Tawfick, Sameh (Elsevier, 2025-01-01)
Twisted and coiled polymer actuators (TCPA), also known as coiled artificial muscles, are gaining popularity in soft robotics due to their large contractile actuation and work capacity. However, while it has been previously claimed that the stroke of TCPA remains stable after thousands of cycles, their absolute length change has not been rigorously studied. Here, we constructed an isobaric cycling setup that relies on fast heating and cooling by water immersion. This enables testing for 10k cycles in a duration of 56 hours, where the muscle temperature is varied between 15 degrees C and 75 degrees C at a rate of 20 seconds per cycle. Surprisingly, while the stroke usually remains unchanged for the entire 10k cycles as previously claimed, the final muscle loaded length exhibits all the geometrical possibilities of creep behavior as it can remain unchanged, elongate (creep), or contract (reverse creep) at the end of the test. Based on a wide range of experiments, we derived an empirical law which captures the observed relationship between the final muscle length change Delta L, the stroke alpha, and the passive strain 80: 80 + alpha = Delta L. Using this relation, the final length change of the muscle can be predicted from the first 100 cycles only. We show that polyvinylidene fluoride (PVDF), which does not swell in water, and nylon, which swells, follow this empirical law by testing in water with and without a protective coating, respectively. These results offer practical design guidelines for predictive actuation over thousands of cycles.
Enhancing performance of lithium metal batteries through acoustic field application
Zhang, Qipeng; Bo, Luyu; Li, Hao; Li, Jiali; Li, Teng; Tian, Zhenhua; Qiao, Rui (Royal Society Chemistry, 2025-01-14)
Cost-effective strategies for enhancing performance of lithium metal batteries (LMB) are in high demand. Herein, we propose and demonstrate that applying an external acoustic field can significantly enhance LMB performance, offering a novel approach to advancing battery technology. Long-term electrochemical stability tests, along with SEM and XPS characterization, reveal that this enhancement may result from the increased lithium-ion diffusion at slip lines and kinks, which can enable a more uniform solid electrolyte interphase (SEI) layer. Without the acoustic field, lithium ions exhibit slower conduction through thicker SEI regions, influenced by slip lines and kinks. In contrast, the application of an acoustic field facilitates more uniform ion diffusion, thereby enhancing overall performance. This approach provides a valuable pathway for advancing battery technology beyond the traditional focus on material innovation.
Anisotropic and Heterogeneous Thermal Conductivity in Programmed Liquid Metal Composites Through Direct Ink Writing
Hur, Ohnyoung; Markvicka, Eric J.; Bartlett, Michael D. (Wiley-V C H Verlag, 2025-03-01)
Thermal management in electric vehicles, electronics, and robotics requires the systematic ability to dissipate and direct the flow of heat. Thermally conductive soft composites are promising for thermal management due to their high thermal conductivity and mechanical flexibility. However, composites typically have the same microstructure throughout a film, which limits directional and spatial control of thermal management in emerging systems that have distributed heat loads. Herein, directional and spatially tunable thermal properties are programmed into liquid metal (LM) soft composites through a direct ink writing (DIW) process. Through the local control of LM droplet aspect ratio and orientation this programmable LM microstructure has a thermal conductivity in the direction of LM elongation of 9.9 W m-1K-1, which is similar to 40 times higher than the unfilled elastomer (0.24 W m-1K-1). The DIW process enables LM droplets to be oriented in specific directions with tunable aspect ratios at different locations throughout a continuous film. This introduces anisotropic and heterogeneous thermal conductivity in compliant films to control the direction and magnitude of heat transfer. This methodology and resulting materials can provide designed thermal management solutions for rigid and soft devices.
Process parameter optimization in polymer powder bed fusion of final part properties in polyphenylene sulfide through design of experiments
Ho, Ian; Bryant, Jackson; Chatham, Camden; Williams, Christopher (Springernature, 2024-12-17)
The Additive Manufacturing (AM) modality of Laser-Based Powder Bed Fusion of Polymers (PBF-LB/P) is an established method for manufacturing semi-crystalline polymers. Like other AM processes, the selection of PBF-LB/P process parameters is critical as it has direct effect on final part properties. While prior research has been predominantly focused on polyamides (e.g., nylon 12), there exists a gap in exploring how process parameters affect higher performance polymers, such as polyphenylene sulfide (PPS). This work aims to explore the effects of PBF-LB/P process parameters on PPS parts printed via PBF-LB/P. While prior PBF-LB/P parameter research primarily relies on evaluating energy input to the system through a single numerical value of energy density, this study investigates the interplay of the print parameters within the energy density equation. To achieve these goals, an analysis was performed on the influence of the laser power, hatch spacing, and beam velocity on ultimate tensile strength (UTS), modulus, and crystallinity of printed parts. A Taguchi L8 array was used in balancing the print parameter combinations allowing for isolation of variance to the specific factors and interactions. Through this approach, print parameter combinations that improved UTS and modulus were identified. Additionally, the study revealed that numerically equivalent energy densities did not lead to equivalent performance, underscoring the significance for including the constitutive process parameters within the energy density equation when establishing process property relationships in printing with PBF-LB/P.
Electromigration of Aquaporins Controls Water-Driven Electrotaxis
Sáez, Pablo; Kale, Sohan (MDPI, 2025-09-10)
Cell motility is a process central to life and is undoubtedly influenced by mechanical and chemical signals. Even so, other stimuli are also involved in controlling cell migration in vivo and in vitro. Among these, electric fields have been shown to provide a powerful and programmable cue to manipulate cell migration. There is now a clear consensus that the electromigration of membrane components represents the first response to an external electric field, which subsequently activates downstream signals responsible for controlling cell migration. Here, we focus on a specific mode of electrotaxis: frictionless, amoeboid-like migration. We used the Finite Element Method to solve an active gel model coupled with a mathematical model of the electromigration of aquaporins and investigate the effect of electric fields on ameboid migration. We demonstrate that an electric field can polarize aquaporins in a cell and, consequently, that the electromigration of aquaporins can be exploited to regulate water flux across the cell membrane. Our findings indicate that controlling these fluxes allows modulation of cell migration velocity, thereby reducing the cell’s migratory capacity. Our work provides a mechanistic framework to further study the impact of electrotaxis and to add new insights into specific modes by which electric fields modify cell motility.
Modeling Hysteretically Nonlinear Piezoelectric Composite Beams
Alazemi, Abdulaziz H.; Kurdila, Andrew J. (MDPI, 2025-07-06)
This paper presents a modeling framework for hysteretically nonlinear piezoelectric composite beams using functional differential equations (FDEs). While linear piezoelectric models are well established, they fail to capture the complex nonlinear behaviors that emerge at higher electric field strengths, particularly history-dependent hysteresis effects. This paper develops a cascade model that integrates a high-dimensional linear piezoelectric composite beam representation with a nonlinear Krasnosel’skii–Pokrovskii (KP) hysteresis operator. The resulting system is formulated using a state-space model where the input voltage undergoes a history-dependent transformation. Through modal expansion and discretization of the Preisach plane, we derive a tractable numerical implementation that preserves essential nonlinear phenomena. Numerical investigations demonstrate how system parameters, including the input voltage amplitude, and hysteresis parameters significantly influence the dynamic response, particularly the shape and amplitude of limit cycles. The results reveal that while the model accurately captures memory-dependent nonlinearities, it depends on numerous real and distributed parameters, highlighting the need for efficient reduced-order modeling approaches. This work provides a foundation for understanding and predicting the complex behavior of piezoelectric systems with hysteresis, with potential applications in vibration control, energy harvesting, and precision actuation.
Post-Hurricane Debris and Community Flood Damage Assessment Using Aerial Imagery
Aggarwal, Diksha; Gautam, Suyog; Whitehurst, Daniel; Kochersberger, Kevin (MDPI, 2025-09-12)
Natural disasters often result in significant damage to infrastructure, generating vast amounts of debris in towns and water bodies. Timely post-disaster damage assessment is critical for enabling swift cleanup and recovery efforts. This study presents a combination of methods to efficiently estimate and analyze debris on land and on water. Specifically, analyses were conducted at Claytor Lake and Damascus, Virginia where flooding occurred as a result of Hurricane Helene on 27 September 2024. We use the Phoenix U15 motor glider equipped with the GoPro Hero 9 camera to collect aerial imagery. Orthomosaic images and 3D maps are generated using OpenDroneMap (ODM) software, version 3.5.6, providing a detailed view of the affected areas. For lake debris estimation, we employ a hybrid approach integrating machine learning-based tools and traditional techniques. Lake regions are isolated using segmentation methods, and the debris area is estimated through a combination of color thresholding and edge detection. The debris is classified based on the thickness and a volume range of debris is presented based on the data provided by the Virginia Department of Environmental Quality (VDEQ). In Damascus, debris estimation is achieved by comparing pre-disaster LiDAR data (2016) with post-disaster 3D ODM data. Furthermore, we conduct flood modeling using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) to simulate disaster impacts, estimate the flood water depth, and support urban planning efforts. The proposed methodology demonstrates the ability to deliver accurate debris estimates in a time-sensitive manner, providing valuable insights for disaster management and environmental recovery initiatives.
A Framework for an ML-Based Predictive Turbofan Engine Health Model
Jung, Jin-Sol; Son, Changmin; Rimell, Andrew; Clarkson, Rory J. (MDPI, 2025-08-14)
A predictive health modeling framework was developed for a family of turbofan engines, focusing on early detection of performance degradation. Turbine Gas Temperature (TGT) was employed as the primary indicator of engine health within the model, due to its strong correlation with core engine performance and thermal stress. The present research uses engine health monitoring (EHM) data acquired from in-service turbofan family engines. TGT is typically measured downstream of the high-pressure turbine stage and is regarded as the key thermodynamic variable of the gas turbine cycle. Three new training approaches were proposed using data segmentation based on time between major overhauls and compared with the conventional train–test split method. Detrending was employed to effectively remove trends and seasonality, enabling the ML-based model to learn more intrinsic relationships. Large generalized models based on the entire engine family were also investigated. Prediction performance was evaluated using selected machine learning (ML) models, including both linear and nonlinear algorithms, as well as a long short-term memory (LSTM) approach. The models were compared based on accuracy and other relevant performance metrics. The prediction accuracies of ML models depend on the selection of data size and segmentation for training and testing. For individual engines, the proposed training approaches predicted TGT with the accuracy of 4 ^∘C to 6 ^∘C in root mean square error (RMSE) by utilizing 65% less data than the train (80%)–test (20%) split method. Utilizing the data of each family engine, the large generalized model achieved similar prediction accuracy in RMSE with a smaller interquartile range. However, the amount of data required was 45–300 times larger than the proposed approaches. The sensitivity of prediction accuracy to the size of the training dataset offers valuable insights into the framework’s applicability, even for engines with limited data availability. Uncertainty quantification showed a coverage width criterion (CWC) between 29 ^∘C and 40 ^∘C, varying with different family engines.
Self-Propelled Ice on Herringbones
Tapocik, Jack T.; Lolla, Venkata Yashasvi; Propst, Sarah E.; Nath, Saurabh; Boreyko, Jonathan B. (American Chemical Society, 2025-08-14)
In the Leidenfrost regime, droplets or sublimating solids can ratchet across asymmetric surface structures by viscous entrainment with the underlying vapor flow. As an extension to these liquid−vapor or solid−vapor ratchets, here, we investigate the solid−liquid self-propulsion of melting ice disks. On hydrophilic herringbones, ice disks self-propel due to the unidirectional flow of viscous meltwater. This is a more viscous analog to Leidenfrost ratchets, except now a brief start-up time is needed for the underlying channels to get filled. When the herringbone is superhydrophobic using conformal nanostructures, the ice disk partially adheres to the ridge tops such that viscous entrainment cannot induce motion. Instead, after a much longer start-up time, the ice disk suddenly dislodges and slingshots across the surface by virtue of a mismatch in Laplace pressure of the meltwater on either end of the disk.
PECAN: Personalizing Robot Behaviors through a Learned Canonical Space
Nemlekar, Heramb; Ramirez Sanchez, Robert; Losey, Dylan P. (ACM, 2025-05)
Robots should personalize how they perform tasks to match the needs of individual human users. Today’s robots achieve this personalization by asking for the human’s feedback in the task space. For example, an autonomous car might show the human two different ways to decelerate at stoplights, and ask the human which of these motions they prefer. This current approach to personalization is indirect: based on the behaviors the human selects (e.g., decelerating slowly), the robot tries to infer their underlying preference (e.g., defensive driving). By contrast, our paper develops a learning and interface-based approach that enables humans to directly indicate their desired style. We do this by learning an abstract, low-dimensional, and continuous canonical space from human demonstration data. Each point in the canonical space corresponds to a different style (e.g., defensive or aggressive driving), and users can directly personalize the robot’s behavior by simply clicking on a point. Given the human’s selection, the robot then decodes this canonical style across each task in the dataset — e.g., if the human selects a defensive style, the autonomous car personalizes its behavior to drive defensively when decelerating, passing other cars, or merging onto highways. We refer to our resulting approach as PECAN: Personalizing Robot Behaviors through a Learned Canonical Space. Our simulations and user studies suggest that humans prefer using PECAN to directly personalize robot behavior (particularly when those users become familiar with PECAN), and that users find the learned canonical space to be intuitive and consistent. See videos here: https://youtu.be/wRJpyr23PKI
Theoretical modeling of the dynamic range of an elastic nanobeam under tension with a geometric nonlinearity
Welles, Nathan W.; Ma, M.; Ekinci, K. L.; Paul, Mark R. (AIP Publishing, 2025-08-07)
A theoretical description of the weakly nonlinear and mode-dependent dynamics of a nanoscale beam that is under intrinsic tension is developed. A full analysis of the dynamic range of the beam over a wide range of conditions is presented. The dynamic range is bounded from below by the amplitude of vibration due to thermal motion, and it is bounded from above by large amplitude oscillations where the geometric nonlinearity plays a significant role due to stretching induced tension. The dynamics are analyzed using a beam with clamped boundaries, a string model, and a beam with hinged boundaries. The range of validity for the different models is quantified in detail. A hinged-beam model is found to provide an accurate description, with insightful closed-form analytical expressions, over a wide range of conditions. The relative importance of bending and tension in the mode-dependent dynamics of the beam is determined. Bending is shown to be important for the higher modes of oscillation with the onset of its importance dependent upon the amount of intrinsic tension that is present. The theoretical predictions are directly compared with experimental measurements for the first ten modes of two nanoscale beams. We discuss the accuracy of these approaches and their use for the development of emerging micro and nanoscale technologies that exploit the multimodal dynamics of small elastic beams operating in the linear regime.
Quantifying the Influence of Parameters on Heat Release Rate in Electrical Cabinet Fires
Selokar, Umang; Lattimer, Brian Y.; Salvi, Urvin; Sahin, Elvan; Allaf, Mohammad Amer; Duarte, Juliana Pacheco (MDPI, 2025-06-30)
Electrical cabinet fire scenarios constitute a significant risk within nuclear facilities, emphasizing the need to mitigate uncertainties in risk evaluations. Owing to the disparate nature of electrical cabinet parameters, only a few factors have been experimentally explored and statistically analyzed to assess their impact on peak HRR. In this study, we conducted both a cabinet parameter study and a combustible configuration study to systematically evaluate their influence on peak HRR and time-to-peak HRR. A series of 51 simulation matrices were created using statistical experiment design (SED) and ANOVA to quantify the influence of cabinet volume, combustible surface area, vent area, ignition characteristics, and burning behavior (e.g., HRRPUA and duration). A computational fluid dynamics (CFD) model, specifically a Fire Dynamics Simulator (FDS), was used to model the ignition source and flame spread inside of the electrical cabinet that influence peak HRR. The most impactful parameters influencing peak HRR and time-to-peak HRR were identified. The findings revealed that the configuration of combustibles and the placement of the ignition source play a pivotal role in determining the peak HRR. A partition screening analysis was conducted to identify the conditions under which the ventilation area becomes a more significant parameter. Additionally, a comparison between experimental results and numerical simulations demonstrated good agreement, further validating the predictive capability of the model.
Liquid Metal-Vitrimer Conductive Composite for Recyclable and Resilient Electronics
Ho, Dong Hae; Jiang, Meng; Tutika, Ravi; Worch, Joshua C.; Bartlett, Michael D. (Wiley-VCH, 2025-06-01)
Electronic devices are ubiquitous in modern society, yet their poor recycling rates contribute to substantial economic losses and worsening environmental impacts from electronic waste (E-waste) disposal. Here, recyclable and healable electronics are reported through a vitrimer-liquid metal (LM) microdroplet composite. These electrically conductive, yet plastic-like composites display mechanical qualities of rigid thermosets and recyclability through a dynamic covalent polymer network. The composite exhibits a high glass transition temperature, good solvent resistance, high electrical conductivity, and recyclability. The vitrimer synthesis proceeds without the need for a catalyst or a high curing temperature, which enables facile fabrication of the composite materials. The as-synthesized vitrimer exhibits a fast relaxation time with reconfigurability and shape memory. The electrically conductive composite exhibits high electrical conductivity with LM volume loading as low as 5 vol.%. This enables the fabrication of fully vitrimer-based circuit boards consisting of sensors and indicator LEDs integrated with LM-vitrimer conductive wiring. Electrical self-healing and thermally triggered material healing are further demonstrated with the composites. The vitrimer and LM-composite provide a pathway toward fully recyclable, mechanically robust, and reconfigurable electronics, thus advancing the field of electronic materials.
Analytical Investigation of Electromechanical Hierarchical Metamaterials for Vibration Attenuation and Energy Harvesting
Mebrat, Ashenafi Abebe; LeGrande, Joshua; Barry, Oumar (MDPI, 2025-03-21)
This work presents a theoretical study of outward and inward hierarchical metamaterials. Hierarchically configured multiple electromechanical resonators with shunt circuits are implemented, maintaining the same overall mass as that of a comparable single resonator metamaterial. The governing equations of motion for the outward and inward hierarchical configurations are derived. Dispersion relations are determined for each configuration with varying system parameters to identify key design parameters and assess their impact on the system’s dynamic behavior. Furthermore, outer mass displacement transmissibility and normalized total power output of finite chain hierarchical metamaterials are compared to observe vibration attenuation and energy harvesting capacity. The results reveal that the band structure of the hierarchical electromechanical metamaterials depends on the configuration type, the resonator masses, the electromechanical coupling coefficient, and the resistance of the shunt circuit. The first-order hierarchy offers a greater total band gap width, increased bandwidth, and greater flexibility in tuning the band structure. Finite chain transmissibility analysis demonstrates that, compared to the baseline performance of the zero-order hierarchy, the first-order hierarchy exhibits superior abilities in vibration attenuation and energy harvesting for the same total mass. The ideal design requires careful consideration of the resonator masses and their configuration, electromechanical coupling coefficient, and resistance of the shunt circuits. This theoretical work provides a foundation for designing lightweight hierarchical metamaterials for simultaneous vibration attenuation and energy harvesting.
Investigating the effect of heterogeneities across the electrode|multiphase polymer electrolyte interfaces in high-potential lithium batteries
Min, Jungki; Bak, Seong-Min; Zhang, Yuxin; Yuan, Mingyu; Pietra, Nicholas F.; Russell, Joshua A.; Deng, Zhifei; Xia, Dawei; Tao, Lei; Du, Yonghua; Xiong, Hui; Li, Ling; Madsen, Louis A.; Lin, Feng (Nature Portfolio, 2025-04-01)
Polymer electrolytes hold great promise for safe and high-energy batteries comprising solid or semi-solid electrolytes. Multiphase polymer electrolytes, consisting of mobile and rigid phases, exhibit fast ion conduction and desired mechanical properties. However, fundamental challenges exist in understanding and regulating interactions at the electrode|electrolyte interface, especially when using high-potential layered oxide active materials at the positive electrode. Here we demonstrate that depletion of the mobile conductive phase at the interface contributes to battery performance degradation. Molecular ionic composite electrolytes, composed of a rigid-rod ionic polymer with nanometric mobile cations and anions, serve as a multiphase platform to investigate the evolution of ion conductive domains at the interface. Chemical and structural characterizations enable the visualization of concentration heterogeneity and spatially resolve the interfacial chemical states over a statistically significant field of view for buried interfaces. We report that concentration and chemical heterogeneities prevail at electrode|electrolyte interfaces, leading to phase separation in polymer electrolytes. Understanding the hidden roles of interfacial chemomechanics in polymer electrolytes enables us to design an interphase tailoring strategy based on electrolyte additives to mitigate the interfacial heterogeneity and improve battery performance.

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