Electrochemical processes in AZIBs involve complex reaction pathways at both the cathode and the zinc metal anode. At cathode side, energy storage can occur through several mechanisms, including Zn²⁺ intercalation, proton/Zn²⁺ co-insertion, conversion reactions, and dissolution-deposition processes. The dominant pathway depends on the crystal structure of the cathode material (e.g., layered, tunnel or open-framework structures), the physicochemical properties of the electrolyte such as pH and salt concentration, and the operating voltage window.

Performance degradation in AZIBs arises from coupled physicochemical processes occurring at the anode, cathode, and electrolyte interfaces. At the zinc anode, thermodynamic instability in aqueous electrolyte leads to parasitic reactions such as chemical corrosion and HER, accompanied by non-uniform zinc deposition and dendrite growth^[6,28]. Meanwhile, cathode materials suffer from structural degradation and active material dissolution during repeated cycling^[4,6]. In practical applications, temperature fluctuations further accelerate these degradation pathways by intensifying parasitic reactions. To elucidate the fundamental origins of AZIBs degradation, this section systematically discusses critical failure mechanisms, as illustrated in Figure 2, including HER, corrosion and surface passivation, zinc dendrite formation, and cathode material dissolution, as well as dynamic pH fluctuations and thermal instability^[29].

During prolonged cycling, cathode materials, particularly manganese-based oxides, suffer from the dissolution of transition metal ions (e.g., Mn²⁺) into the aqueous electrolyte^[6,26]. This continuous dissolution gradually changes the local electrolyte chemistry. Subsequently, these dissolved species can then migrate to the anode and deposit onto its surface, severely disturbing the normal zinc plating kinetics^[26,31]. This crossover leads to the loss of active cathode material, which macroscopically translates into a continuous and irreversible decline in the battery capacity^[6,26,31]. Similarly, in zinc-iodine systems, the severe dissolution and subsequent shuttle effect of polyiodide intermediates constitute a major cathode degradation pathway^[32].

To address the severe HER and subsequent gas-induced swelling in AZIBs, optical fiber sensing technology has attracted increasing interest, benefiting from its immunity to electromagnetic interference, robust corrosion resistance, and micron-scale footprint. For instance, Ding et al. developed a hybrid optical fiber sensor by combining a Fabry-Pérot interferometer (FPI) with a Fiber Bragg grating (FBG). When embedded directly within the pouch cell, this sensor enables operando monitoring of internal pressure fluctuations driven by HER, with a sensitivity of 137 nm MPa^-1, while simultaneous tracking temperature. By converting the HER-related process into real-time optical signals readable by the BMS, this approach allows direct readout by the BMS and avoids the slow response and limited accuracy of conventional external pressure sensors^[18].

Despite exhibiting rapid response times and high sensitivity, the sensing mechanism of this technology is constrained by the inherent cross-sensitivity between pressure and temperature. Mitigating this interference requires the integration of a FBG to perform complex signal decoupling and compensation. Furthermore, the susceptibility of optical sensors to internal mechanical stress and strain can lead to signal distortion under the complex deformation profiles encountered within a battery^[18]. In terms of practical deployment, while the ultra-slim 140 μm diameter enables excellent non-invasive integration, the associated back-end infrastructure entails significant costs. The dependence on bulky and complex external equipment, including interrogators, laser sources, and spectral readout systems - substantially limits its cost-effective and widespread application in portable electronics or large-scale energy storage facilities^[16]. Consequently, future practical implementations must achieve a strategic balance between sensing precision, system complexity, and the preservation of battery performance.

To probe the chemical drivers of anodic corrosion and dendrite growth, namely electrolyte pH changes and local ion gradients, extended-gate field-effect transistors (EGFETs) and functionalized optical fibers offer practical solutions. For example, Luo et al. developed a miniaturized EGFET-based dual sensor for pH and dissolved oxygen (DO), designed for direct integration into the battery. With a sensitivity of 46 mV pH^-1, the device tracks pH changes at the electrode/electrolyte interface during cycling. This enables early detection of conditions that may trigger the formation of insulating byproducts such as ZHS under local pH increase^[19].

However, since its working mechanism relies on the conversion of potential differences, a stable reference fiber electrode must be introduced inside the battery as a reference. This also takes up more space inside the battery. At the same time, the implantation of the fiber electrodes of the EGFET sensor requires an additional diaphragm layer for mechanical protection and electrical isolation^[17]. This inevitably increases the internal resistance of the battery and may cause subtle interference to the local ion transmission path.

The architectures and working principles of the HER and pH sensing systems are illustrated in Figure 3A and B. Operando measurements in Figure 3C and D reveal the pressure and temperature responses of Zn-MnO₂ and Zn-TiO₂/MnO₂ pouch cells, respectively, highlighting differences in gas evolution behaviour during HER. The EGFET sensor responses (IDS-pH and IDS-DO), together with the corresponding real-time evolution of pH and dissolved oxygen (DO), are shown in Figure 3E under galvanostatic cycling at 2C within 0.80-1.80 V, indicating relatively stable interfacial conditions. When the voltage window is extended to 0.80-2.20 V [Figure 3F], pronounced shifts in pH and DO are observed, suggesting intensified side reactions and electrolyte imbalance. Selected data points are highlighted to mark key stages of these processes.

Zinc dendrite growth remains a major limitation for AZIBs performance. To probe its early-stage dynamics, plasmonic fiber-optic sensors have been employed to monitor ion activity at the electrode interface^[38]. By detecting localized refractive index changes, this method could track the depletion and accumulation of Zn²⁺ in real time, providing direct insight into interfacial ion transport and enabling non-destructive predict potential dendrite growth. Consequently, this real-time monitoring capability facilitates the dynamic optimization of fast-charging protocols, ensures active safety by mitigating catastrophic failures prior to irreversible physical damage, and significantly reduces operation and maintenance costs in large-scale energy storage systems through targeted predictive maintenance. In parallel, acoustic and strain sensing offer complementary routes to capture the mechanical signals associated with dendrite growth and structural evolution. As summarized by Espinoza Ramos et al., acoustic emission (AE) techniques can detect transient elastic waves generated by processes such as gas bubble formation, electrode cracking, and dendrite penetration of the separator^[37]. Analysis of these signals in terms of frequency and amplitude allows early identification of internal failure events, often before measurable changes appear in conventional electrochemical outputs such as voltage. In the specific context of AZIBs, this real-time observability is highly valuable for mitigating dominant failure mechanisms. For instance, AE sensors can acutely capture the acoustic signatures of parasitic HER and localized gas accumulation long before macroscopic cell swelling occurs. Furthermore, the technique provides direct evidence of micro-mechanical degradation, monitoring the structural cracking of cathode materials that accompanies continuous dissolution, as well as the critical moments of separator puncture by growing zinc dendrites. By translating these hidden physical and chemical degradation processes into quantifiable acoustic data, AE sensing effectively transforms the AZIB from a “black box” into a highly observable electrochemical system, paving the way for intrinsically safe battery management and predictive diagnostics.

Although advanced sensing technologies, such as AE and plasmonic fiber-optic sensors, show remarkable non-invasive and high-resolution advantages for operando battery monitoring, they still have inherent limitations regarding their sensing mechanisms and practical deployment. In terms of sensing orientation, the simultaneous occurrence of multiple physicochemical degradation processes and the complex wave propagation paths within the battery make it highly challenging to accurately decouple AE events and pinpoint specific degradation mechanisms^[37]. For the plasmonic fiber-optic sensor, the broad spectral bandwidth of the sensor envelope restricts the accuracy of tracking wavelength shifts, and its inherent cross-sensitivity to mechanical strain, local temperature changes, and light power fluctuations necessitates complex signal calibration and decoupling through core mode referencing^[36]. Regarding practical deployment, both technologies face distinct difficulties: AE sensing currently lacks standardized data acquisition settings, leading to scattered and poorly reproducible results; meanwhile, although the plasmonic fiber-optic sensor probe is miniaturized, its “back-end” operation heavily relies on bulky and expensive benchtop equipment like full-scale optical spectrum analysers, which severely limits its cost-effective and widespread application in routine electric vehicle diagnostics or large-scale energy storage systems. Consequently, future practical implementations must achieve a strategic balance between sensing precision, system complexity, and the preservation of battery performance.

The configurations and operating principles of two sensing strategies for dendrite growth are shown in Figure 4A and B. The operando response of sensor a [Figure 4C] exhibits synchronous changes with the galvanostatic charge-discharge profile, directly reflecting the dynamic evolution of interfacial ion activity during battery operation. In contrast, sensor b captures transient mechanical events: distinct waveforms are detected during bubble rupture [Figure 4D] and during graphite structural failure [Figure 4E], highlighting its sensitivity to localized physical processes. Together, these sensing approaches enable the detection of internal gas pressure, pH variation, ion activity, and acoustic or stress signals. By converting otherwise inaccessible chemical and mechanical processes into real-time, quantifiable outputs, they provide critical inputs for BMS to improve state estimation and safety control.

Significant progress has been made in sensing and monitoring AZIBs. Early approaches relied on external voltage and temperature measurements. Recent work enables operando tracking of internal states, including gas pressure, pH changes, and micro-mechanical signals, using optical fibers, EGFETs, and acoustic emission techniques. Despite these advances, key challenges remain for practical deployment in applications such as grid storage and electric vehicles. Many high-precision sensing approaches still depend on bulky laboratory equipment and lack scalable, low-cost integration. At the same time, existing sensors often show limited response speed and poor signal decoupling. For example, conventional pressure sensors can exhibit hysteresis during HER monitoring, which restricts their use for real-time safety warnings in BMS. To bridge the gap between fundamental understanding and system-level control, next-generation AZIB sensors should address several critical requirements. which, along with their system-level integration pathways, are comprehensively outlined in Figure 5.

Apart from having high-precision hardware sensors, it is crucial that the large amount of in-situ data generated by the sensors be combined with the upper-level algorithms to achieve the maximum value. At the sensing level, future devices will move toward miniaturized, flexible, and distributed architectures. Sensors for key parameters, such as pH, strain, and gas pressure, can be integrated directly onto electrodes or separators, enabling real-time mapping of internal states without compromising energy density. These large-scale operando datasets will support the development of AI-driven analysis and digital twin models. By combining data processing at the device level with cloud-based computation, BMS platforms can interpret complex signals and predict failure modes such as dendrite growth and thermal runaway^[13,22,40]. At the system level, such approaches will support the transition from single-cell studies to large-scale applications. Improved monitoring, consistency management, and dynamic balancing across battery packs can enhance efficiency and reliability, helping to address key challenges in the practical deployment of AZIBs^[1,40].