Harvesting ubiquitous low-grade waste heat has remained challenging, and ionic thermoelectrics (i-TEs) have shown greater promise than electronic thermoelectrics. The i-TEs are of two types: (1) redox reaction-based i-TEs and (2) Soret effect-driven i-TEs. This work summarizes recent advances in Soret effect-driven i-TEs, which generate a voltage due to differences in the thermophoretic mobilities of electrolyte ions when the i-TE is subjected to a temperature gradient, with the cold end at room temperature. Unlike electronic thermoelectrics, Soret effect-driven i-TEs exhibit a high thermopower of several mV/K. We correlate the thermopower generated by such Soret effect-driven i-TEs to (1) the various entropic contributions of the electrolyte, and (2) electrode porosity. We highlight the role of electrode porosity in driving novel electrochemical voltage oscillations, which can open new avenues for i-TE applications. Notably, we present proof-of-concept demonstrations of Soret effect-driven i-TEs and discuss various schemes employed by researchers to continuously generate power—a hot discussion topic in the field of i-TEs. Lastly, we compare the efficiencies of reported i-TEs and propose future directions to guide the research community in Soret effect-driven i-TEs. In this invited review article, we summarize the (1) developments in electrolyte discovery for Soret effect-driven i-TEs and link them to their entropic contributions, (2) role of electrode porosity in governing thermopower and voltage oscillations, (3) different continuous operation schemes, (4) proof-of-concept demonstrations reported to date, and (5) future research directions.
Performing electrolytic water splitting in acid can enable a step change in electrolyser technology, providing lower overpotential reactions and opportunities for membrane-free electrolysers. Decoupled acid electrolysis exploits H+ intercalation and pseudocapacitive reactions in transition metal oxides to temporally split the hydrogen and oxygen evolution reactions. While the performance of the transition metal oxide is critical to the overall efficiency of the decoupled electrolysis reactions, the role of the carbon support has not been explored. This is surprising as proton battery literature has shown the capacity of these supports to store H+ ions via similar intercalation reactions. Here, bio-derived activated carbons (AC) from Alder charcoal and Birch wood are prepared and compared with commercial conductive carbon additives for decoupled electrolysis in 0.5 M H2SO4. The use of bio-derived activated carbons increases the pseudocapacitive performance by more than 280
The depletion of conventional energy resources, coupled with the growing demand for renewable energy solutions, has intensified the search for efficient energy storage systems capable of addressing the intermittent nature of renewable energy generation. Lithium-ion batteries (LIBs) have dominated the energy storage market due to their high energy density and superior electrochemical performance. However, concerns related to cost, sustainability, resource availability, and safety have highlighted the need for alternative technologies. Sodium-ion batteries (SIBs), benefiting from the natural abundance and low cost of sodium resources, have emerged as a promising alternative for large-scale energy storage applications. Among the various cathode materials investigated for SIBs, iron-phosphate-based compounds have attracted considerable attention owing to the abundance, low cost, environmental benignity, and structural stability of their precursors. This review provides a comprehensive overview of the crystal structures, electrochemical performances, and optimization strategies of selected iron-phosphate cathode materials for cost-effective and sustainable sodium-ion batteries. Furthermore, the current state of the art, existing challenges, critical perspectives, and futurs prospects for the industrial-scale implementation of these cathode materials are discussed. Iron phosphate-based cathode materials were reviewed as sustainable and low-cost candidates for next generation sodium-ion batteries (SIBs). Recent advances in material design, electrochemical performance, and scalable synthesis demonstrate their potential to support affordable and environmentally responsible energy storage technologies.
Two-dimensional (2D) ferroelectrics pair atomic-scale thickness with switchable polarization, but many promising chalcogenides and halides are severely air-sensitive. This review maps the mechanisms (displacive, interlayer sliding, electronic, dipolar, and topological) that govern in-plane and out-of-plane polarization, then examines how oxygen, moisture, and electrothermal stress drive oxidation, hydrolysis, blistering, and morphological failure that destabilize domains in the ultrathin limit. We compare synthesis and handling routes and also highlight encapsulation strategies and their impact on FeFETs, memristors, and vdW heterostructures. Our review shows the requirement for practical 2D ferroelectrics to develop standardized stability metrics, humidity/temperature-controlled testing, interfacial engineering, and scalable, atomically thin encapsulation compatible with wafer-level device integration. This review identifies environmental instability as the principal barrier to deploying 2D ferroelectrics and shows that atomically thin encapsulation and inert-atmosphere handling are essential rather than optional strategies for preserving polarization in the ultrathin limit.
The transition to next-generation energy storage, specifically rechargeable batteries like sodium-ion, polyanionic, and all-solid-state batteries, requires optimizing complex architectures where light mobile ions (Z ≤ 11) migrate through heavy transition-metal frameworks. Although X-ray diffraction and electron microscopy are widely used for structural characterization, they face intrinsic limitations when visualizing light elements (Li, Na, H, O) and buried interfaces in bulk battery devices. As neutrons interact directly with the atomic nuclei via the strong force, neutron-based techniques offer a non-destructive and highly penetrating probe that overcomes many of these barriers. This review focuses on how neutron-based techniques make it possible to directly observe structural features that are often inaccessible to X-ray or electron probes but can critically influence battery performance. We capture how Neutron Powder Diffraction (NPD) locates sodium/lithium vacancies to map diffusion pathways, how neutron reflectivity (NR) quantifies the density and evolution of the in situ solid-electrolyte interphase (SEI), and how small angle neutron scattering (SANS) and neutron imaging (NI) reveal mesoscale porosity and macroscopic electrolyte wetting. By correlating these atomic-to-macroscopic insights with electrochemical data, neutron methodologies are summarized as guiding tools to establish specific material design rules for enhancing the rate capability and thermal stability of sustainable battery chemistries.
Lithium–sulfur (Li–S) batteries offer high theoretical energy density (1,672 mAh g⁻1) and low material cost, yet their practical deployment remains limited by poor scalability under lean-electrolyte and high sulfur-loading conditions. Many reported electrolyte strategies achieve high capacities in coin cells but rely on excess electrolyte and low areal loading, obscuring constraints critical for pouch-cell operation. Here, we present a data-driven benchmarking framework to evaluate Li–S performance across coin and pouch configurations by jointly analyzing sulfur loading, electrolyte-to-sulfur (E/S) ratio, and delivered capacity. Using literature data from 2022 to 2025, we construct ternary performance landscapes and apply principal component analysis (PCA) to identify governing trade-offs. Two orthogonal axes emerge: a practicality-driven axis linking high sulfur loading, low E/S ratio, and high areal capacity, and a stability-driven axis associated with capacity retention and fade rate. Their weak coupling reveals a persistent gap between energy density optimization and durability. Importantly, this work establishes a statistically grounded, data-centric framework that transforms fragmented literature into actionable design space. A feasible operating window— 7–10 mg cm⁻2 sulfur loading and 1.7–2.8 µL mg⁻1 E/S—yields 5.5–7.5 mAh cm⁻2 areal capacity with stable cycling, providing quantitative benchmarks for scalable Li–S systems. We evaluated lithium–sulfur battery performance across realistic conditions and identified critical trade-offs between energy output and durability. The results outline a pathway toward more scalable battery technologies.
The development of efficient, safe, and reversible solid-state hydrogen storage materials is essential for advancing a sustainable hydrogen-based energy economy. In this work, we present a comprehensive first-principles density functional theory investigation of the perovskite hydrides SiMgH3 and GeMgH3, focusing on their structural, dynamical, mechanical, electronic, optical, and hydrogen storage properties. Both compounds are found to be thermodynamically and dynamically stable, as confirmed by negative formation energies and phonon spectra free of imaginary modes. Mechanical analysis reveals that both hydrides are ductile and mechanically robust, with SiMgH3 exhibiting higher stiffness and stronger resistance to deformation compared to GeMgH3. Electronic structure calculations indicate metallic behavior with mixed ionic–covalent H–metal bonding, which enhances charge transport and supports reversible hydrogen mobility within the lattice. Optical properties further demonstrate strong dielectric response and efficient low-energy photon absorption, indicating favorable electronic polarization characteristics. Hydrogen storage analysis shows that SiMgH3 exhibits superior performance, with a gravimetric capacity of 5.46 wt This study shows that SiMgH3 and GeMgH3 are stable hydrogen-storage materials with good mechanical strength and electronic conductivity. SiMgH3 performs better, offering higher hydrogen capacity and a lower hydrogen release temperature, making it more suitable for practical applications.
Biomass-derived carbons show promise as sustainable anode materials for lithium-ion batteries, but there is a lack of understanding of how different biomass molecular and chemical structures influence graphitization processes and electrochemical behavior. Here, we investigate the structural properties and lithium storage behavior of carbons produced via iron-catalyzed pyrolysis of three different biomass precursors (lignin, cellulose, and dextrin). Spectroscopic signatures reveal differences in functional group chemistry and iron binding between the glucose-based polymers and lignin. Iron-catalyzed graphitization was effective for cellulose and dextrin precursors at temperatures as low as 1000°C, whereas lignin exhibited minimal graphitization. Following pyrolysis at 1400°C, cellulose produced the highest degree of graphitic ordering and delivered an average reversible lithium storage capacity of 278 mAh g−1, while lignin showed the lowest (155 mAh g−1). Pre-oxidation of the lignin prior to pyrolysis revealed a strong correlation between enriched carbonyl functionalities and the extent of graphitization, and it enabled improvement of the reversible capacity to 216 mAh g−1. Overall, this work demonstrates that precursor molecular architecture and functional group chemistry dictate graphitization pathways, and it provides design guidelines for engineering biomass-derived precursors for high-performance anode materials. Iron-catalyzed biomass precursors exhibited precursor-dependent graphitization, with cellulose and dextrin exhibiting a greater extent of graphitic ordering compared to lignin under identical conditions. This structural evolution directly translated to enhanced lithium-ion battery performance, highlighting precursor chemistry as a key design parameter for sustainable carbon anodes. The synthetic graphite supply chain is highly centralized and vulnerable to geopolitical disruption, raising the question of whether biomass-derived carbons could play a meaningful role in diversifying critical battery material sourcing. While biomass precursors are often framed as sustainable alternatives, it remains unclear whether their lower-temperature processing and feedstock availability can offset challenges in performance consistency and large-scale manufacturing. The reliance on transition metal catalysts to enable graphitization introduces trade-offs between performance gains and added material, environmental, and economic costs that are not yet fully resolved.
Organic redox-active molecules and solid-state organic materials present a uniquely tunable platform for next-generation energy storage technologies. Their molecular diversity enables precise control over redox energetics, solubility, transport, and long-term stability—yet the breadth of the organic chemical space and the complexity of reactivity have hindered systematic discovery. Recent advances in multi-fidelity quantum chemistry approaches, machine learning, graph neural networks, large language models (LLMs), and agentic autonomous workflows are redefining how we identify and optimize organic materials for both flow and solid-state battery systems. This perspective synthesizes developments across computational chemistry, machine learning, and autonomous science, integrating contributions from our research group and others in computational discovery of organic materials using multiscale modeling, machine learning, and foundation models. By highlighting key challenges, foundational datasets, and emerging opportunities in closed-loop discovery, we outline a forward-looking roadmap for accelerating organic battery innovation through AI-guided materials design. We document recent advances in multi-fidelity quantum chemistry, Physics-based AI, large language models (LLMs), and agentic autonomous workflow-based approaches to accelerate organic battery innovation. Recent computational developments point toward a new era of digitally driven, closed-loop materials discovery, in which computation and AI act not merely as supporting tools, but as the central engines of innovation for organic battery technologies.
The presence and potential leaching of PFAS (Per- and Polyfluoroalkyl Substances) from solar panels are increasingly mentioned in news articles, raising public concerns. Such concerns may slow the adoption of photovoltaic (PV) technology, despite its central role in the renewable energy sector. The limited transparency from manufacturers about fluorinated materials used in PV modules, along with the scarcity of publicly available testing data, contributes to uncertainty and speculation. This perspective aims to clarify the current state of PFAS presence in solar PV. Although certain fluoropolymers are used in PV manufacturing, the scientific consensus on their toxicity indicates they should not be classified as PFAS. Portraying fluoropolymers as toxic PFAS unnecessarily amplifies concerns and unfairly undermines the perceived environmental sustainability of PV technology. This perspective examined claims about PFAS in solar panels using the available scientific evidence. We found that while certain fluoropolymers are used in photovoltaic manufacturing, they are not appropriately classified as toxic PFAS. Mischaracterizing fluoropolymers as hazardous PFAS may unnecessarily undermine public confidence in photovoltaic sustainability. Should manufacturers be encouraged or required to disclose polymer additives used in solar PV components to improve public trust, even when toxicity concerns are low? Could inconsistent media reporting on emerging contaminants inadvertently slow PV adoption by eroding confidence in renewable energy technologies?
The rapid expansion of green hydrogen heightens the need for sustainable water sources, positioning seawater as a compelling feedstock for solar-driven hydrogen production. Photoelectrochemical seawater splitting (PESS) offers an integrated photon-to-fuel approach but remains constrained by seawater’s intrinsic chemical complexity. High chloride concentrations introduce competitive chlorine evolution and accelerate corrosion, while multivalent ions, biofouling, and precipitation impose additional barriers to charge transfer and long-term durability. Recent advances in semiconductors, cocatalysts, and ultrathin protection layers have improved the oxygen evolution reaction (OER) selectivity and chloride tolerance, yet stability remains limited under realistic hydrodynamic and environmental conditions. At the device scale, mass-transport management, flow-cell engineering, and desalination-PEC coupling emerge as critical determinants of performance and scalability. This review focuses on fundamental principles, materials innovations, and system-level strategies, identifies persistent knowledge gaps, and outlines research priorities needed to achieve selective, corrosion-resistant, and deployment-relevant PESS for sustainable hydrogen production from natural seawater. Photoelectrochemical seawater splitting is a promising approach for solar-driven hydrogen production, enabling the direct utilization of Earth-abundant and sustainable seawater resources. This review highlights recent developments, fundamentals, strategies to enhance performance, as well as key challenges for photoelectrochemical seawater splitting.
Efficient energy harvesting for applications such as radioisotope thermoelectric generators and heat-recovery systems require novel thermoelectric materials with exceptional performance. This work demonstrates thermoelectric capabilities of n-type MoS2/MoSe2 heterojunctions fabricated by scalable radiofrequency sputtering. These heterostructures demonstrated an outstanding experimental Seebeck coefficient of − 1.1 mV K−1 (ΔT = 40 K), arising from thermally activated carriers with a low activation energy of 32 meV, and estimated thermoelectric figure-of-merit (ZT) values of 1.0. Furthermore, computational calculations within framework of Density Functional Theory corroborate experimental findings allowing to elucidate a crucial role of atomic-scale in determining anisotropic thermoelectric properties. Lastly, our data indicate MoS2/MoSe2 heterojunctions are a promising material for low-cost and efficient thermoelectric for microelectronic devices. Transition metal dichalcogenides offer a rich platform to exploit overlooked thermoelectric potential for energy-recovery systems and hybrid energy harvesting. This work highlights the potential of MoS2/MoSe2 thin films for thermoelectric applications, featuring a low-cost, scalable, and excellent heterostructure formation that will guide future research in the field of energy and sustainability.
Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies. Conceptual overview of machine learning-driven battery research, illustrating how physics-based constraints, feedback-driven optimization, and predictive forecasting jointly enable adaptive and robust battery systems. The figure was generated with the assistance of generative AI tools (Gemini and ChatGPT) and curated by the authors. As machine learning-driven battery optimization becomes increasingly autonomous, how should responsibility be assigned when algorithmic decisions trade off lifetime, safety, and cost in real-world systems? Physics-informed machine learning promises interpretability, yet overly simplified physical assumptions may encode systematic bias, raising the question of when “less physics” may yield more reliable predictions. Open battery datasets accelerate innovation, but without standards for data provenance and protocol diversity, they may unintentionally narrow the design space explored by the community.
The rapid expansion of electric mobility and energy-storage deployment in India is driving a steep rise in lithium-ion battery (LIB) consumption, projected to exceed 127 GWh by 2030. This surge will generate unprecedented volumes of end-of-life (EOL) waste, increasing from about 50,000 metric tons in 2025 to more than 2 million metric tons per year by 2030. India’s heavy reliance on imported critical elements lithium, cobalt, and nickel, —exposing the domestic ecosystem to over USD 5 billion in import vulnerability—makes large-scale recycling essential for resource security. Although formal systems currently process less than 5 Key pillars of sustainable lithium-ion battery management: recovery, recycling, circular economy, storage, e-waste, and policy Recycling lithium-ion batteries offers India a practical pathway to recover critical materials, cut carbon emissions, and reduce its dependence on imported minerals as battery waste grows rapidly. Strengthening policy enforcement, traceability, and recycling technology will determine how effectively India can build a sustainable and self-reliant battery ecosystem.
High-throughput atomistic simulations were performed to identify novel and sustainable high-performance materials for chemical looping air separation. Nitrogen gas is an important commercial product and intermediate. Conventional methods for the production of pure nitrogen by separating air into its components remain energy-intensive and suffer from a high process complexity. Chemical looping air separation (CLAS) is a promising alternative for large-scale nitrogen gas production due to its high energy efficiency and easy integration with industrial processes. A major obstacle for the large-scale deployment of CLAS remains the lack of available high-performance functional materials needed to carry out the related thermochemical reactions. In this study, high-throughput atomistic simulations were used to identify perovskite oxides consisting of abundant elements with low criticality capable of a reversible absorption of large amounts of oxygen from air. A set of hierarchical filters was applied to pre-select plausible perovskite structures from existing first-principles data. Subsequently, a machine-learned interatomic force field was used to calculate their redox thermodynamics to identify materials with the best CLAS oxygen sorbent properties. The suggested computational workflow as well as the shortlisted materials can serve as starting points for future theoretical and experimental studies of perovskite oxide materials for CLAS as well as chemical looping processes in general.
Electrochemical water splitting for hydrogen production is regarded as an important emerging energy conversion technology due to its broad application prospects, but its industrialization process is limited by the slow kinetics and high reaction energy barrier of the anodic oxygen evolution reaction (OER). Therefore, developing electrocatalytic materials with high activity and stability is crucial for the advancement of electrochemical water splitting technology. This study reported a Ce-doped cobalt sulfide catalyst encapsulated by an ultra-thin carbon layer via a MOFs-derived method. The catalyst achieved a low overpotential of 279 mV for the alkaline OER at 10 mA cm−2 for over 170 h. The high catalytic activity mainly stems from a dual optimization mechanism: (1) the introduction of rare earth element cerium into the lattice effectively optimizes the electronic structure of cobalt sulfide, significantly reducing the OER energy barrier; (2) the ultra-thin carbon layer on the surface constructs a conductive network and greatly improves the lifespan of the catalytic material. This strategy combining electronic structure regulation and surface engineering provides a new idea for the design of high-efficiency electrocatalysts for water splitting. Transition metal sulfides (TMSs) demonstrate exceptional application potential in the oxygen evolution reaction (OER) owing to their unique electronic configurations and superior electrical conductivity. However, the OER activity and stability of TMSs are severely compromised under continuously oxidative potential in alkaline media, which significantly limits their practical implementation. To address these challenges, we modified TMSs via a synergistic combination of ion doping and surface coating strategies, aiming to extend the catalytic lifespan. It also lays a robust foundation for the in-depth investigation of TMSs stability in future research.
The growing deployment of lithium-ion batteries (LIBs) in electric vehicles and energy storage systems has intensified concerns over resource depletion, waste generation, and environmental impacts. Conventional recycling methods—pyrometallurgy and hydrometallurgy—recover valuable elements but are energy-intensive, chemical-heavy, and often yield downgraded products. Direct regeneration of spent cathodes has emerged as a low-energy alternative capable of restoring structural integrity and electrochemical performance without fully breaking down the material. This paper reviews recent advances in direct regeneration, with emphasis on emerging room-temperature pathways alongside established thermal and other non-thermal methods. Key factors affecting energy consumption, including pretreatment, lithium sources, reaction conditions, and reactor design, are critically analyzed. Regenerated cathodes produced through low-energy routes are compared with pristine materials, with evidence showing that room-temperature processes can recover crystal structure, cycling performance, and rate capability to near-virgin levels for selected chemistries. Techno-economic and environmental assessments further indicate substantial reductions in carbon emissions, operating costs, and dependence on critical raw materials. Remaining challenges include mixed cathode waste streams, degradation variability, and industrial-scale implementation. Future directions highlight the need for green chemistry, improved sorting technologies, and supportive policy frameworks to enable a scalable, circular LIB recycling ecosystem.
Rapid growth in lithium-ion batteries is straining lithium supply and exposing the slow, land- and water-intensive nature of conventional extraction (evaporation ponds and ore leaching). Meanwhile, large but dilute and chemically complex resources—salt-lake brines, geothermal fluids, oilfield brines, and seawater—remain underutilized. This review surveys lithium extraction technologies with a focus on electrically driven membrane processes. We first summarize resource chemistries and benchmark classical routes (precipitation, solvent extraction, and solid/porous adsorbents), emphasizing selectivity, robustness, and scalability in brines with high-Mg/Li and Na/Li ratios. We then review pressure-driven membranes, especially nanofiltration and ion-selective composites, highlighting design principles including charge regulation, Donnan exclusion, and coordination-assisted transport for Li+/Mg2+ separation. The core section discusses electrodialysis and solid-electrolyte architectures that use lithium-ion conductors as selective separators to decouple Li+ migration from co-ions and parasitic reactions. Case studies—redox-coupled electrodialysis, hybridization with adsorbents, and laminated solid-electrolyte membranes for seawater—illustrate how cell design and membrane structure govern selectivity, energy use, and process intensification. Finally, we outline challenges (Li+/Na+ discrimination, long-term stability in complex brines, and scale-up of brittle ceramics) and opportunities for low-carbon integration and multi-ion co-recovery. This review examined how lithium can be recovered from salt-lake brines, industrial brines and seawater using both conventional chemistry and newer electrically driven membrane systems. It compared their efficiency, selectivity, and environmental footprint and highlighted what is still needed to turn laboratory-scale devices into practical, low-carbon lithium extraction plants.
Lithium sulfur batteries offer high theoretical energy density and low material cost, but their practical use depends on electrolyte systems that satisfy several fundamental criteria. Solid state electrolytes provide a promising route by removing the liquid phase and improving safety. This review outlines the reaction pathways in lithium sulfur cells and the mechanisms of ion transport in solid electrolytes, followed by a generational comparison of major electrolyte classes, including polymers, oxides, sulfides, halides, garnets and composite systems. Four key criteria for solid state electrolyte use in lithium sulfur batteries are then examined: stability with electrodes, polysulfide behaviour, sulfur utilization and mechanical versatility. Existing strategies are evaluated in terms of how effectively they satisfy each requirement. Finally, two solid state cell designs that meet all identified criteria are proposed, together with quantitative considerations for electrolyte and cathode design. These insights provide a framework for guiding the development of practical solid state lithium sulfur batteries. This work identifies the key requirements that solid electrolytes must meet to enable high-energy lithium–sulfur batteries. It also highlights two practical cell designs that satisfy these requirements and point toward viable solid-state lithium–sulfur technology.
Polymer electrolytes are critical for high-energy-density solid-state batteries (SSBs), yet their X-ray photoelectron spectroscopy (XPS) characterization is plagued by irradiation-induced artifacts, particularly false LiF signals. Herein, we demonstrate that poly(ethylene oxide)-based electrolytes suffer from severe X-ray irradiation-induced decomposition, which is significantly accelerated by the electron flux from the conventional charge neutralization gun, leading to exacerbated Li salt breakdown and artifactual LiF formation. In contrast, poly(vinylidene fluoride)-based electrolytes, while more radiation-resistant, are prone to a different failure mode dominated by inadequate charge compensation, which also results in misleading Li+ migration and LiF signals. In addition, we introduce a simple yet optimized protocol, which replaces the neutralization gun with a microporous copper foil for charge compensation. This approach effectively suppresses the charge-compensation-induced decomposition pathway, thereby excluding the LiF artifacts and yielding highly reliable surface analysis. This facile method requires no equipment modification, offering a robust tool to decouple genuine interfacial reactions from experimental artifacts. By enabling artifact-free characterization, it lays the groundwork for dynamic evolution in polymer SSBs. This work reveals that the electron flux from the conventional charge neutralization gun, rather than X-ray irradiation alone, is the primary driver of artifactual LiF formation during XPS characterization of polymer solid electrolytes. An optimized protocol using microporous copper foil for charge compensation is introduced, effectively suppressing irradiation-induced artifacts without instrument modification or cryogenic conditions. The fundamental mechanisms of irradiation-induced decomposition in polymer electrolytes during XPS characterization, particularly the synergistic effect of X-rays and electron flux, remain insufficiently elucidated. The practical applicability of artifact-mitigation strategies for reliable XPS analysis under real battery operating conditions or during in situ/operando characterization is still largely unexplored. A systematic understanding of the intrinsic irradiation resistance across different polymer hosts and its correlation with material properties is currently lacking.
