The advent of miniaturized electronics and wearable technology has precipitated an urgent need for flexible, lightweight power sources compatible with dynamic, irregular surfaces. Existing batteries, predominantly lithium-ion or alkaline chemistries, often suffer from inherent rigidity and bulky form factors that impede seamless integration into next-generation devices. Moreover, their reliance on hazardous chemicals raises environmental and health concerns, exacerbated by the potential for leakage. While energy harvesters provide an alternative by generating power from ambient conditions, their output is frequently insufficient or inconsistent for sustained device operation. The MAB’s design champions a paradigm shift by amalgamating the convenience of an energy harvester with the reliability and capacity associated with traditional batteries.

At the core of this moisture-activated battery lies a novel composite structure featuring a magnesium anode paired with a silver/silver chloride cathode, separated by a cellulose membrane embedded with lithium chloride salts. This unique separator functions not merely as a physical barrier but as an active medium for electrolyte formation. It absorbs moisture from the surrounding environment, dissolving the lithium chloride salt to produce a saltwater electrolyte essential for ionic conduction within the battery. This approach eradicates the need for pre-impregnated or volatile electrolytes, substantially enhancing safety and extending shelf life by maintaining the battery in an inert state until activated by atmospheric humidity.

A remarkable aspect of the MAB’s architecture is its bioinspired stratagem modeled after pangolin skin. This natural design motif, comprising densely overlapping scales, confers exceptional mechanical resilience and adaptability. While conventional stretchable batteries utilize serpentine interconnectors to maintain electrical continuity under strain, they are often susceptible to energy density reduction due to gaps formed during deformation. The pangolin-inspired layering enables the MAB to maintain minimal gaps, redistributing mechanical stresses evenly across the battery surface. This ensures sustained electrochemical performance under diverse mechanical deformations, including stretching, bending, and twisting, without sacrificing energy storage capacity.

The mechanics underlying this stretchability were elucidated through sophisticated computer simulations conducted in tandem with empirical assessments. Rice University’s mechanical engineering team demonstrated that the integrated design could withstand significant mechanical deformation while preserving charge transfer pathways and internal resistance characteristics. The synergy of materials science and biomechanics is clearly evident in the MAB’s stable electrochemical output, with an open-circuit voltage around 1.6 volts and a specific capacity approximating 52 milliampere-hours per gram. The specific energy density reaches a noteworthy 81 milliwatt-hours per gram, competitive with many commercial batteries, thus affirming the device’s viability for practical applications.

One compelling demonstration of the battery’s capabilities involved powering a wireless Bluetooth-enabled pulse oximeter continuously for approximately 30 hours. This performance aligns closely with that of conventional rigid batteries but with the added advantages of reduced weight, flexibility, and non-toxicity. Beyond wearables, the MAB’s design opens avenues for embedding safe, conformal power sources in robotics, environmental sensing devices, and distributed surveillance systems. The biocompatible and biodegradable nature of the constituents significantly mitigates ecological impact, addressing growing concerns about electronic waste proliferation.

Of particular interest is the integration of an innovative “kill switch,” leveraging the core moisture harvesting principle to enhance security and tamper resistance in sensitive monitoring applications. This feature involves a dry mixture of aluminum and iodine powder housed within an isolated compartment enveloped by a moisture-absorbing cellulose membrane. Upon mechanical pressure—such as an attempt to remove or disable the device—the mixture interacts violently with the harvested moisture, triggering a rapid exothermic reaction that incinerates the device. This self-destructive mechanism not only protects valuable and sensitive data but also prevents unauthorized reuse, representing a significant advancement in device security, particularly for covert surveillance missions.

Empirical tests of the kill switch embedded within a MAB-powered wireless gas sensor demonstrated total device obliteration within three minutes of activation. This rapid response underscores the system’s efficacy in safeguarding against tampering and adds a layer of fail-safe protection previously unattainable in miniature power systems. The innovation embodies a functional integration of energy harvesting, power storage, and security features within a single compact architecture, indicative of future trends in smart device design where multifunctionality is paramount.

The MAB’s development is a testament to the interdisciplinary collaboration between materials scientists, electrical engineers, and mechanical engineers. The project is backed by the Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST) Center at NC State, with strategic funding to bridge industrial innovation and academic research. Graduate and postdoctoral researchers played vital roles in advancing the technology from conceptual frameworks to demonstrable prototypes, underscoring the team’s commitment to transitioning laboratory breakthroughs into real-world deployments.

Looking ahead, this moisture-activated battery paradigm has the potential to redefine energy solutions for the exploding IoT ecosystem. Its convergence of sustainability, safety, mechanical flexibility, and energy density positions it uniquely to tackle challenges posed by wearable health monitors, environmental sensors, and smart infrastructure. With further refinement, scalability, and integration, MAB technology could soon supplant toxic, rigid batteries, heralding an era where ubiquitous electronics operate safely, efficiently, and harmoniously with natural environments.

The publication of these findings in the prestigious journal Science Advances marks a significant milestone that invites further exploration and adoption within the scientific and industrial communities. By demonstrating that a battery can be activated purely by environmental moisture and engineered for stretchability without compromising capacity, the research opens new horizons in battery chemistry and device engineering. As IoT devices proliferate, the demand for such novel power sources that merge eco-friendliness with advanced functionality will be more critical than ever, making this development both timely and transformative.

In conclusion, the moisture-activated battery represents a groundbreaking advancement in energy storage technology, unlocking promising avenues for the future of wearable electronics and IoT devices. Its safe, flexible, and environmentally benign profile coupled with an innovative security mechanism reflects a holistic approach to power solution design, reflecting the growing complexity and sophistication of modern electronic ecosystems. As industries pivot towards greener, smarter technologies, the MAB stands out as a beacon of sustainable innovation with broad-reaching implications across multiple technological frontiers.

Subject of Research: Not applicable

Article Title: Safe, high-performance, moisture-activated batteries for powering next-generation Internet-of-Things devices

News Publication Date: 1-Jul-2026

Web References: http://dx.doi.org/10.1126/sciadv.aee2065

Image Credits: Rajaram Kaveti

Keywords

Batteries, Electrical engineering, Energy storage, Moisture-activated battery, Stretchable battery, Internet of Things, Wearable technology, Flexible power source, Biocompatible battery, Kill switch, Energy harvesting, Sustainable energy

At the core of WPT technology is a transmitter coil linked to a power source, which converts electrical energy into an electromagnetic field. This field is then captured by a receiver coil, which channels the energy to power electronic devices. However, one of the major challenges within WPT systems has been achieving load-independent (LI) operation, a vital feature that maintains stable output voltage and zero-voltage switching (ZVS) across fluctuating loads. The conventional means of solving this problem often rely on complex analytical equations with idealized assumptions that fail to address the myriad of real-world irregularities.

To tackle these intricate challenges, a pioneering research team led by Professor Hiroo Sekiya from the Graduate School of Informatics at Chiba University, Japan, has made significant advancements by introducing a machine learning-based design method for LI-WPT systems. Collaborating with experts in electrical engineering and computer science, including Mr. Naoki Fukuda, Dr. Yutaro Komiyama from Chiba University, Dr. Wenqi Zhu from Tokyo University of Science, and Dr. Akihiro Konishi from Sojo University, the team embarked on a journey to enhance the efficiency of power delivery through innovative approaches. Their findings were published in the prestigious journal, IEEE Transactions on Circuits and Systems I.

The novel design process they proposed embraces a fully numerical framework that leverages differential equations to describe the dynamic behavior of voltages and currents within the WPT system. By embracing a numerical approach, the researchers could realistically account for the varying characteristics of physical components, a leap beyond traditional analytical methods. This new approach involves solving equations incrementally, allowing the circuit’s performance to stabilize as it evolves to steady-state conditions.

Central to this design methodology is an evaluation function that measures the system’s effectiveness by focusing on key parameters such as output voltage stability, power-delivery efficiency, and total harmonic distortion. By employing a genetic algorithm, the team could iteratively fine-tune system parameters, enhancing the evaluation score until the goal of load-independent operation was successfully achieved. This integration of machine learning into the design not only showcases the practical utility of artificial intelligence but also signifies a substantial shift in how power electronics research and development could be conducted in the future.

Professor Sekiya emphasizes the transformative implications of this work, asserting, “We established a novel design procedure for a LI-WPT system that achieves a constant output voltage without control against load variations. We believe that load independence is a key technology for the social implementation of WPT systems.” This innovative thinking paints a bright future for WPT technology, indicating that load independence could pave the way for its broader utilization.

In terms of practical applications, the research team applied their method to a specific type of WPT system—the class-EF WPT system. This design combines the benefits of a class-EF inverter with a class-D rectifier, providing a robust solution to the issues faced by conventional systems. While traditional designs typically lose ZVS when the load varies, the LI WPT system developed by Sekiya’s team showcased remarkable resilience, maintaining both ZVS and a stable output voltage, regardless of load fluctuations.

Their evaluations revealed notable discrepancies between conventional and their fully numerical method. In traditional LI inverter systems, the output voltage could vary drastically—up to 18%—as loads changed. In stark contrast, the newly designed system maintained this variation below 5%, illustrating a level of stability that could revolutionize how we utilize WPT technologies. This enhanced performance extends to lighter loads as well, where the new system was able to better manage diode parasitic capacitance effects, further solidifying its advantage.

A thorough analysis of power losses within the system indicated that the newly designed transmission coil was capable of dissipating similar levels of power across varied load conditions. This efficiency stems from the system’s design, which ensures consistent output current, an essential factor for reliable wireless power distribution. At its rated operating point, the LI class-EF WPT system achieved an impressive power delivery efficiency of 86.7% at a frequency of 6.78 MHz, capable of providing more than 23 watts of output power.

With a forward-looking perspective, the researchers envision broader implications for their findings, suggesting that advancements in WPT technology could be a step toward a wholly wireless society. Prof. Sekiya notes that the simplification enabled by LI operation could lead to reduced costs and sizes of WPT systems, helping facilitate more widespread adoption in everyday applications. The ambition is to normalize WPT technology over the next 5 to 10 years, fundamentally altering our interaction with energy transmission and consumption.

In essence, this research not only reveals critical advancements in wireless power transfer technology but also opens up exciting avenues for the integration of machine learning in the field of power electronics. It emphasizes a shift toward automated design processes that are poised to redefine how such systems are conceptualized, developed, and manufactured, highlighting the potential for technology to adapt more fluidly to real-world complexities.

The work undertaken by the team from Chiba University encapsulates a significant milestone in the quest for efficient and reliable wireless energy transfer. The implications for consumer electronics and broader applications could herald a new era in which power becomes truly wireless, paving the way for innovations that will transform everyday life.

As they continue to explore new horizons in WPT technology, the research team’s work stands as a testament to the synergy between advanced engineering methods and artificial intelligence, demonstrating the power of interdisciplinary collaboration in overcoming long-standing challenges within electronic systems.

Subject of Research: Wireless Power Transfer Systems

Article Title: ML-Based Fully-Numerical Design Method for Load-Independent Class-EF WPT Systems

News Publication Date: 18-Jun-2025

Web References: IEEE Transactions on Circuits and Systems

References: Not applicable

Image Credits: Wikimedia Commons via Creative Commons Search Repository

Keywords: Wireless Power Transfer, Load-Independent Operation, Machine Learning, Differential Equations, Circuit Design, Power Delivery Efficiency, Nikola Tesla, Chiba University, Class-EF WPT Systems, Automation in Electronics, Energy Transmission.