The nonlinear Hall effect, a member of the Hall effect family, has recently garnered immense scientific interest thanks to its unique ability to generate high-harmonic Hall voltages without necessitating the breaking of time-reversal symmetry. Such characteristics make NLHE a promising phenomenon for numerous technological applications including energy harvesting, wireless communication technologies, and infrared detection devices. Despite its potential, experimentally achieving a pronounced and stable NLHE in two-dimensional transition metal dichalcogenides (TMDs) like MoS2 has proven to be an elusive challenge.

MoS2, as a prototypical 2D TMD, exhibits excellent tunable electronic properties which make it an attractive candidate for next-generation electronics, optoelectronics, and quantum devices. However, the emergence of NLHE demands the precise breaking of inversion symmetry—that is, a symmetry condition that is inherently difficult to maintain or engineer in pristine MoS2 at the device scale. Traditional strategies to induce such symmetry breaking include mechanical strain engineering, twisted bilayer stacking, and external field applications. These methods, however, suffer from issues related to limited scalability, poor reproducibility, and short-term stability, thereby impeding practical implementation.

The innovative solution presented by the Nanjing University team involves the electrochemical intercalation of cetyltrimethylammonium ions (CTA+) directly into the van der Waals gap of the MoS2 thin flakes. This intercalation expands the layer spacing from 0.61 nm to an impressive 1.06 nm, offering unprecedented atomic-layer-level control over the material’s structure while preserving the intrinsic atomic arrangements within the layers. The presence of CTA+ ions within the vdW gap effectively breaks the inversion symmetry, a prerequisite for the emergence of the nonlinear Hall effect.

Beyond the structural transformation, the intercalation process dramatically alters the electronic landscape of MoS2. The infusion of electrons supplied by the CTA+ ions shifts the material’s behavior from a semimetallic regime into a highly conductive metallic state. Quantitatively, the carrier concentration reaches an estimated -6.94 × 10^20 cm^-3, which is a substantial increase that contributes to the robust electrical performance. This carrier density augmentation is crucial for amplifying the nonlinear Hall voltage observed during electrical transport measurements.

At cryogenic temperatures of approximately 10 Kelvin, the researchers recorded a nonlinear Hall voltage perpendicular to the current exceeding 7 microvolts at a current threshold of 100 microamperes. What sets this work apart is that such a nonlinear response remains prominently observable even at room temperature (around 300 Kelvin), signaling a breakthrough in the practical viability of NLHE-based devices. The investigation into the temperature-dependent NLHE signals confirmed that the dominant mechanism underlying this phenomenon is skew scattering—a fundamental scattering process that breaks the symmetry of electron momentum distributions.

This study not only provides a new class of materials demonstrating room-temperature nonlinear Hall effects, but also highlights the potential of electrochemical intercalation as a scalable and controllable route to engineer symmetry and electronic properties in two-dimensional materials. Compared to other reported systems that require complex fabrication or extreme environments, the intercalated MoS2 thin flakes offer chemical stability and established growth processes that favor integration into existing semiconductor technology infrastructures.

The implications of these findings are multifold. NLHE’s inherent rectification properties make it a prime candidate for application in highly efficient photodetectors, energy conversion devices, and spintronic components, where controlling electron spin and charge in low-dimensional systems is key. With further optimization of nonlinear susceptibility particularly at room temperature, new device architectures exploiting the nonlinear transport phenomena could revolutionize sectors ranging from telecommunications to renewable energy technologies.

Future endeavors will logically extend towards exploring a broader range of host and guest materials for intercalation, analyzing how variations in ion species or lattice hosts affect the magnitude and temperature robustness of NLHE. Equally significant is the refinement of electrochemical intercalation parameters—such as electrolyte composition, voltage application, and intercalation duration—to afford fine control over carrier doping levels and symmetry breaking degrees in TMD thin films.

Given the rapid strides in sophisticated thin-film growth technologies, including chemical vapor deposition and molecular beam epitaxy, the scalability challenges for implementing room-temperature NLHE materials at an industrial level appear increasingly surmountable. The merger of precise atomic control via intercalation with mature large-area film growth techniques portends the advent of new classes of highly functional, miniaturized electronic and spintronic devices.

This pioneering research, documented in the international journal Materials Futures, charts a visionary course for the field of nonlinear Hall physics and 2D material engineering. By merging electrochemical methodologies with quantum materials science, it opens unexplored horizons in electronic symmetry manipulation, heralding the next generation of functional nanomaterials with broad technological impact.

Subject of Research:
Article Title: The nonlinear Hall effect induced by electrochemical intercalation in MoS2 thin flake devices
News Publication Date: 2-Feb-2026
Web References: http://dx.doi.org/10.1088/2752-5724/ae31fa
References: Fuwei Zhou, Yu Du, Tianqi Wang, Heng Zhang, Jiajun Li, Wuyi Qi, Yefan Yu, Fucong Fei, Fengqi Song. The nonlinear Hall effect induced by electrochemical intercalation in MoS2 thin flake devices[J]. Materials Futures, 2026, 5(2): 025302. DOI: 10.1088/2752-5724/ae31fa
Image Credits: Fengqi Song, Fucong Fei and Fuwei Zhou from Nanjing University

Keywords
Hall effect, Electrochemistry, Transition metals, Superlattices

Traditional energy harvesting devices have often been hindered by their rigidity and limited adaptability, which restricts their utility in applications requiring flexibility or stretchability. The work by Han and Moon directly addresses these challenges by employing ionic triboelectric nanogenerators that leverage the unique properties of ionic materials. These materials not only provide exceptional mechanical compliance but also maintain high energy conversion efficiencies under deformation, making them ideal candidates for wearable electronics, biomedical devices, and the rapidly expanding Internet of Things (IoT) ecosystems.

The monolithic integration of the I-TENGs described combines multiple functional layers into a single, cohesive structure without the need for external adhesives or complex assembly processes. This integration strategy drastically reduces the risk of delamination or electrical failure during bending, twisting, or stretching, leading to enhanced durability and operational stability over extended periods. Moreover, the compact form factor achieved through monolithic design is crucial for miniaturized electronics that demand both high performance and mechanical resilience.

Central to the operation of these nanogenerators is the ionic mechanism that mimics the natural ion transport seen in biological systems. When mechanical deformation occurs, interfacial charge transfer and ion migration within the ionic layer generate an electrical signal. Unlike conventional electronic-based triboelectric generators that rely on electron transfer alone, the ionic approach benefits from a dual mechanism that boosts the charge density and output power substantially. This duality enables the nanogenerators to function efficiently under a wide range of mechanical stimuli, including low-frequency human motions and biomechanical deformations.

The energy harvesting capabilities demonstrated in the study reveal remarkable efficiency metrics. The devices convert mechanical energy derived from flexing, bending, and compressive forces into electrical energy with minimal loss, thus enabling continuous power supply for low-energy devices. Such capability is particularly transformative for wearable health monitors, smart textiles, and environmental sensors, where conventional batteries are typically bulky and require frequent replacement or recharging.

Beyond energy harvesting, the I-TENGs exhibit impressive self-powered sensing functions. By converting mechanical stimuli directly into readable electrical signals, these devices eliminate the need for external power sources, thus simplifying sensor architecture and extending operational lifespan. This feature is invaluable for remote or implanted sensors, enhancing safety and user convenience.

The fabrication process detailed by the researchers employs scalable techniques compatible with existing semiconductor manufacturing paradigms. Utilizing solution-processed ionic materials and printing methods, the production of these nanogenerators can be efficiently scaled up, paving the way for widespread commercial adoption. The compatibility with flexible substrates further underscores their potential integration into a diverse array of devices, from flexible displays to robotic skins.

In terms of durability, the monolithically integrated I-TENGs exhibit outstanding mechanical robustness. Rigorous cyclic testing demonstrates that device performance remains stable after thousands of deformation cycles. This resilience ensures reliable operation in real-world scenarios where repeated and varied mechanical stress is unavoidable, such as in athletic wear, prosthetics, or interactive electronics.

The implications of this technology extend far beyond individual devices. The ability to harvest ambient mechanical energy and simultaneously sense environmental changes without external power input catalyzes a new paradigm in sustainable and autonomous electronics. Networks of self-sustaining sensors could enable real-time monitoring across smart cities, industrial infrastructure, and environmental systems, significantly reducing energy consumption and maintenance costs.

Furthermore, the researchers’ approach opens avenues for multifunctional devices that combine energy generation, sensing, and even communication capabilities on a single platform. Such integration is critical for the next generation of flexible and wearable electronics that must meet demanding requirements for compactness, performance, and adaptability.

A key insight of this work lies in the demonstration of ionic materials’ compatibility with triboelectric energy conversion—a synergy that had remained underexplored until now. By harnessing the inherent advantages of ionic conduction within soft, deformable matrices, the designed nanogenerators achieve unprecedented operational versatility. This breakthrough challenges traditional concepts of triboelectric materials and encourages new research into hybrid ionic-electronic systems.

The design also incorporates an optimized electrode configuration to maximize the triboelectric effect and facilitate efficient charge transfer. The use of conductive polymers and nanostructured electrodes not only enhances electrical interfacing but also contributes to mechanical compliance, ensuring harmony between electrical performance and physical flexibility.

Beyond healthcare and wearables, the technology promises significant impacts in robotics and human-machine interfaces, where tactile sensing and energy autonomy are vital. Soft robots requiring distributed sensor networks and power supply can benefit immensely from these flexible nanogenerators, enabling more natural and adaptive behaviors.

Despite these breakthroughs, certain challenges remain. Long-term chemical stability of ionic components under varying environmental conditions, such as humidity and temperature fluctuations, needs comprehensive evaluation to ensure reliable field deployment. Nonetheless, the foundational work by Han and Moon sets a robust framework for addressing these issues through material engineering and encapsulation strategies.

In conclusion, the monolithically integrated ionic triboelectric nanogenerators unveiled in this study mark a transformative step toward truly deformable and self-sustained electronic systems. The fusion of ionic conduction with triboelectric energy harvesting and sensing represents a versatile platform with far-reaching implications in flexible electronics, wearable technology, environmental monitoring, and beyond. As research continues to advance, these nanogenerators are poised to become critical components in building a sustainable and interconnected technological future.

The convergence of energy harvesting and self-powered sensing in a mechanically adaptable form factor embodies a new frontier in material science and device engineering. This innovation not only addresses existing limitations in flexible electronics but also unlocks novel functionalities that could drive the next wave of technological evolution, ultimately enhancing human interaction with digital and physical environments.

Subject of Research: Monolithically integrated ionic triboelectric nanogenerators designed for flexible, deformable energy harvesting and self-powered sensing applications.

Article Title: Monolithically integrated ionic triboelectric nanogenerators for deformable energy harvesting and self powered sensing.

Article References:
Han, J.H., Moon, H.C. Monolithically integrated ionic triboelectric nanogenerators for deformable energy harvesting and self powered sensing. npj Flex Electron 9, 114 (2025). https://doi.org/10.1038/s41528-025-00491-8

DOI: https://doi.org/10.1038/s41528-025-00491-8

At the heart of this development is graphene, a two-dimensional material celebrated for its extraordinary electrical, thermal, and mechanical properties. The team exploited graphene’s energy conversion potential to create miniaturized solar cells capable of harvesting ambient energy with remarkable efficiency. These graphene-based solar cells eliminate the need for conventional batteries, often the limiting factor in sensor lifetimes due to their finite charge cycles. As a result, devices powered this way could function autonomously for decades, offering a paradigm shift toward sustainable and maintenance-free sensor networks.

To achieve this feat, researchers tackled two pivotal technical challenges. First, they reduced the power consumption of temperature sensors to the nanowatt scale, a billionth of a watt, which dwarfs the typical power usage of such devices that traditionally operate in the microwatt range. This drastic reduction required designing and optimizing circuits with extraordinarily low power demands. Second, they engineered an energy harvesting system that can directly power the sensor from the local environment’s solar energy, thereby removing the necessity of power management units and batteries.

The research, led by Ph.D. candidate Ashaduzzaman under the guidance of Professor Paul Thibado, demonstrates that multiple graphene-based solar cells can be connected in series to raise the output voltage sufficiently to charge onboard storage capacitors. These capacitors then intermittently power the sensor system, enabling continuous function for more than 24 hours on a single charge cycle. This approach circumvents the traditional reliance on rechargeable batteries while simplifying the energy storage system architecture.

Professor Thibado emphasized the importance of self-contained energy sourcing, stating that power must be drawn entirely from the local environment for true autonomy. The long projected lifespan of the sensors could dramatically reduce maintenance costs and operational disruptions, embodying a ‘set it and forget it’ philosophy that is critical for large-scale IoT deployments in remote or hard-to-access locations.

The collaborative effort with the University of Michigan was crucial to addressing the power consumption hurdle. Professor David Blaauw and his team specialize in ultra-low power circuits and wireless embedded systems; their expertise helped downscale the energy requirements of the sensor electronics. Blaauw’s pioneering work on minuscule sensors, including those small enough to reside on a butterfly’s wing, highlights the significance of precise and efficient low-power design in contemporary sensor applications.

Intriguingly, the research team dispensed with a conventional power management unit entirely. They connected three sets of graphene-based mini solar cells to three corresponding storage capacitors that reliably supply power to the temperature sensor. This streamlined design significantly trims excess energy consumption and improves efficiency by directly converting and storing ambient solar energy.

Looking ahead, the research group aims to enhance the sensor platform by integrating multiple energy harvesting modalities. By combining solar energy harvesting with mechanisms that capture kinetic, thermal, or nonlinear vibrational energy endemic to graphene’s unique properties, future sensors will be multimodal, ensuring continuous power availability even amidst fluctuating environmental energy sources.

Potential applications for this technology span an expansive range of industries and use cases. Agricultural monitoring can profit from long-term climate data collection without battery replacement burdens, and livestock tracking can be improved with minimally invasive, self-sustained devices. Wearable fitness trackers may gain extended lifespans, while building alarm systems, environmental surveillance, and predictive maintenance systems can all benefit from these cost-effective, durable, and autonomous sensors.

A key facet of the research was the fabrication and rigorous characterization of dozens of graphene solar cells, each analyzed via current-voltage profiling under illumination to ensure consistent performance. Connecting these cells in series enabled voltage boosts compatible with sensor requirements. Rapid charging times of mere minutes enable prolonged sensor operation, highlighting the practicality and readiness of the technology for real-world implementation.

This groundbreaking work, published in the Journal of Vacuum Science and Technology B, has been recognized not only for its scientific rigor but also for its innovative approach to solving long-standing problems in energy autonomy. The project received substantial support from the WoodNext Foundation, whose $900,000 grant underpinned the optimization of graphene-based energy-harvesting devices aimed at transforming the commercial sensor market.

Moreover, collaboration with NTS Innovations exemplifies the bridge between laboratory innovation and industry-level commercialization. Specializing in nanotechnology, NTS Innovations holds exclusive licenses to bring graphene energy harvesters into practical, scalable commercial products. Their customer engagement strategy, informed by feedback from over 60 interested parties, ensures that evolving products meet industrial power acceptance criteria and satisfy the demands of diverse application scenarios.

As this technology matures, the integration of kinetic energy harvesting—particularly from graphene’s distinctive vibrational modes—is anticipated to enhance the energy portfolio of future sensors. This traditional multi-modal approach promises a resilient energy supply, ushering in a new era where sensor devices are entirely free from battery dependence and external maintenance.

This pioneering research unlocks unprecedented opportunities within the burgeoning Internet of Things landscape, contributing essential components to untether smart technologies from energy constraints. The fusion of graphene’s material science brilliance and sophisticated low-power circuitry charts a promising trajectory for sensors that seamlessly blend into daily life while continually sensing, monitoring, and transmitting data for years on end.

Subject of Research: Not applicable

Article Title: Array of mini-graphene-silicon solar cells intermittently recharges storage capacitors powering a temperature sensor

News Publication Date: 10-Nov-2025

Web References:

• Official publication: 10.1063/10.0039935
• University of Arkansas graphene research: https://arkansasresearch.uark.edu/scientists-design-novel-nonlinear-circuit-to-harvest-clean-power-using-graphene/
• University of Michigan Blaauw lab: https://blaauw.engin.umich.edu/
• WoodNext Foundation: https://woodnext.org/
• NTS Innovations: https://www.ntsinnovations.com/

References: Journal of Vacuum Science and Technology B, 10-Nov-2025, DOI: 10.1063/10.0039935

Image Credits: Russell Cothren

Keywords

Graphene, energy harvesting, ultra-low power sensors, solar cells, Internet of Things, autonomous sensors, temperature sensors, nanotechnology, energy autonomy, multi-modal energy harvesting, storage capacitors, low-power electronics

At the core of this pioneering work is the integration of physical laws directly into the AI learning algorithm, allowing the model to “understand” the intrinsic governing equations that dictate material behaviors. Conventional methods have long depended on extensive empirical data and complex testing apparatus to infer material properties, often leading to prohibitive costs and time delays. By contrast, the KAIST-led initiative bypasses these obstacles through algorithms that embed conservation laws and thermodynamic principles, rendering neural networks capable of extrapolating reliable material characteristics even when experimental data are scarce or incomplete.

The research team initially concentrated on hyperelastic materials, such as rubbers and elastomers, which exhibit complex, nonlinear deformation under stress. Using a Physics-Informed Neural Network (PINN), the researchers demonstrated the capability to infer constitutive models—mathematical descriptions of material stress-strain relationships—from highly limited experimental data, essentially from a single test. This approach overturns the long-held assumption that large, comprehensive datasets are mandatory for accurate constitutive modeling, illustrating that the interplay of physics and machine learning can compensate for data paucity while maintaining predictive fidelity.

Expanding their frontier, the group then addressed thermoelectric materials, a class critical to sustainable energy technologies due to their ability to convert thermal gradients into electrical energy and vice versa. Through a novel inverse inference technique based on PINNs, the team successfully estimated key temperature-dependent thermoelectric parameters, such as thermal conductivity and the Seebeck coefficient, from just a handful of measurements. This advancement is crucial for accelerating the screening and optimization of thermoelectric materials, which traditionally rely on cumbersome and time-intensive experimental characterization.

Perhaps most impressively, the researchers introduced the concept of Physics-Informed Neural Operators (PINO), an AI architecture that generalizes physical insights across different material systems without requiring re-training on each new material. This means that after training the model on a relatively small set of 20 materials, it was tested on 60 entirely novel materials and achieved exceptionally accurate property predictions. Such scalability and generality herald a transformative platform for large-scale materials discovery, allowing for rapid, high-throughput evaluation that was previously unattainable.

This fusion of physics-based understanding with AI-driven inference marks a paradigm shift. It not only reduces the dependency on expensive and time-consuming experimentation but also ensures that predictions remain physically consistent and interpretable. The approach thus bridges the gap between purely data-driven AI models, which may lack transparency, and mechanistic physical models, which can be intractable for complex materials behavior.

Professor Seunghwa Ryu, who guided these studies, encapsulates the significance of this breakthrough: “This is the first instance where AI embedded with physical laws is employed in real material research. It enables dependable identification of material properties under constrained data conditions, offering vast potential for expansion into multiple engineering domains.” The approach is set to expedite materials innovation pipelines, essential for developing next-generation composites, electronics, and energy devices.

These findings were disseminated across two critical publications. The first study, detailing the discovery of hyperelastic constitutive models from extremely sparse data, appeared in the August 13 issue of Computer Methods in Applied Mechanics and Engineering and was co-first-authored by Ph.D. candidates Hyeonbin Moon and Donggeun Park. The second, focusing on label-free inference of temperature-dependent thermoelectric properties via physics-informed neural operators, was published on August 22 in npj Computational Materials, co-led by Moon, Songho Lee, and Dr. Wabi Demeke.

Financial support for these projects was provided through competitive grants from the Korea Research Foundation and the Ministry of Science and ICT’s INNOCore Program, evidencing governmental commitment to fostering innovation at the nexus of AI and materials science. Collaboration extended beyond KAIST, involving Kyung Hee University and the Korea Electrotechnology Research Institute, reflecting the interdisciplinary and inter-institutional nature of modern scientific advancement.

The impact of these technologies is poised to be far-reaching. By enabling AI models to encode and apply physical laws inherently, researchers can venture beyond empirical limitations, accessing a virtual experimentation environment that accelerates hypothesis testing and material discovery across different length scales and material classes. This capability is particularly valuable as the quest for materials with tailored properties—whether for flexible electronics, sustainable energy solutions, or advanced structural components—becomes increasingly urgent.

Moreover, this scientific milestone addresses one of the longstanding challenges in the application of AI to scientific research: the trade-off between data availability and model reliability. The KAIST team’s success in deploying PIML and PINO frameworks puts forth a robust methodology where the physics-informed constraints act as regularizers, reducing overfitting and enhancing the physical interpretability of the models, a crucial factor for trust in AI-augmented materials engineering.

In practice, the potential extends to developing “digital twins” of materials, virtual counterparts that mirror real material behavior under varying conditions, enabling predictive maintenance and in silico testing. This marriage of physics-informed AI and materials science could thus dramatically lower costs and risks associated with innovation pipelines, catalyzing the creation of novel materials with optimized performance tailored precisely to application needs.

As the landscape of materials research evolves, this research represents a beacon pointing towards a future where AI and physics coexist symbiotically, replacing brute-force experimentation with intelligent, law-abiding computation. The strides achieved by Professor Ryu’s group and collaborators underscore the transformative potential inherent to such integrative approaches, opening avenues that transcend traditional boundaries and herald a new era of accelerated discovery in science and engineering.

Subject of Research: Physics-informed AI methods for material property identification under limited data conditions.

Article Title: “Physics-informed neural operators for generalizable and label-free inference of temperature-dependent thermoelectric properties”

News Publication Date: October 2, 2025

Web References:
– DOI: https://doi.org/10.1038/s41524-025-01769-1

Image Credits: KAIST

Keywords

Applied sciences and engineering, Engineering, Physics-Informed Machine Learning, Material Discovery, Thermoelectric Materials, Hyperelasticity, Neural Networks, Artificial Intelligence, Computational Materials Science, Physics-Informed Neural Operators

The concept of rectifying random motion into directed movement lies at the heart of ratchet systems. These systems have long fascinated scientists, especially in biological contexts where molecular motors convert the seemingly random collisions of molecules into purposeful mechanical work essential for life processes. However, to date, such ratchet systems—especially those engineered at macroscopic scales—have depended on built-in asymmetries like gears, notches, or uneven surfaces to direct the motion in a preferred direction. Breaking away from this paradigm, the team led by Ph.D. student Ms. Miku Hatatani and her colleagues have engineered the first-ever symmetric ratchet motor that exhibits directional rotation purely by the spontaneous breaking of symmetry under vibrational excitation.

Central to their experimental design was a simple circular acrylic disk placed atop a shallow bed of glass beads contained within a vibrating dish. The entire assembly was subjected to random vertical vibrations, causing the beads to endlessly collide and bounce beneath the disk. Remarkably, instead of the disk exhibiting random jitter or stationary behavior, it began to tilt asymmetrically and spin persistently in one direction for several seconds. This directional rotation emerges spontaneously from a system that is, at face value, perfectly symmetric. The researchers’ meticulous observations confirmed that the tilt of the disk was not externally imposed but dynamically generated through interactions with the randomly moving particles underneath.

This spontaneous rotational motion is a direct consequence of a principle known as spontaneous symmetry breaking. Initially, the glass beads beneath the disk were evenly distributed, maintaining symmetry in the system’s configuration. However, as vibrations continued, particles gradually congregated more densely on one side, inducing a tilt in the disk. This tilt altered the collision dynamics, causing more beads to accumulate preferentially on the same side, thus reinforcing the tilt in a self-sustaining feedback loop. Such self-organization transforms chaotic particle motion into a stable macroscopic rotation—a compelling demonstration of how order can spontaneously arise from disorder without external bias or control.

To decode the mechanics underlying this phenomenon, the researchers developed a rigorous mathematical model inspired by the classical physics of spinning tops. The model incorporates the precessional dynamics resulting from torque applied by uneven particle collisions on the disk’s surface, capturing the transition from symmetric initial conditions to sustained rotational motion. Notably, numerical simulations from this model displayed quantitative agreement with experimental data, corroborating that the stochastic collisions alone suffice to maintain the disk’s directional spin. This theoretical framework elevates the understanding of how microscopic randomness links to macroscopic emergent behaviors.

Professor Akihisa Shioi emphasized the fundamental scientific significance of this work by stating that the system “organizes itself,” in which “randomness becomes the very source of order.” This statement encapsulates a profound principle in non-equilibrium statistical physics: open systems can self-organize into ordered structures or motions without explicit external symmetry breaking fields. By demonstrating this principle experimentally, the research transcends mere curiosity and lays the groundwork for novel approaches to manipulating and harnessing energy flows in complex systems.

Beyond its fundamental scientific allure, the discovery offers promising practical implications. Ambient mechanical noise is an abundant energy reservoir present in numerous daily environments, yet it remains largely untapped. The realization of a symmetric ratchet motor suggests that devices capable of extracting regulated mechanical work from omnipresent random vibrations may be feasible. This technology could revolutionize energy harvesting for small-scale applications such as self-powered sensors, wearable devices, or remote monitoring equipment, reducing or eliminating reliance on batteries or external power sources.

Moreover, the research contributes major insights into the burgeoning fields of active matter and non-equilibrium thermodynamics. It challenges preconceived notions about the necessity of geometric or structural asymmetry to induce directed motion, broadening the theoretical landscape for future explorations. This work could inspire the design of novel synthetic active materials or machines that exploit environmental fluctuations to perform useful functions autonomously.

Ms. Hatatani’s team meticulously controlled experimental parameters such as vibration frequency and amplitude to understand the robustness of the spontaneous spinning phenomenon. The experiments consistently revealed that above certain vibrational thresholds, the disk was reliably induced into persistent rotation, highlighting conditions under which symmetry breaking transition occurs. These investigations pave the way for tuning such systems for desired dynamical behaviors, emphasizing potential scalability and engineering adaptability.

In light of these findings, the interdisciplinary nature of the project—combining chemical engineering, materials science, and nonlinear dynamics—showcases an exemplary model for collaborative research tackling complex problems. The team included distinguished researchers like Professors Daigo Yamamoto and Akihisa Shioi, bringing together expertise in theoretical physics, materials engineering, and experimental techniques. Their collective efforts underscore the importance of integrating diverse scientific perspectives to address multifaceted phenomena such as spontaneous symmetry breaking in mechanical ratchets.

The research was supported by prominent Japanese funding agencies including JST SPRING and KAKENHI, underscoring both the national and international interest in advancing fundamental science with tangible technological outcomes. The publication of these findings in a leading physics journal marks a milestone not only for Doshisha University but also for the wider scientific community fascinated by non-equilibrium systems and energy conversion mechanisms.

Although this study concentrated primarily on macroscopic vibrational ratchets, its principles resonate at multiple scales and domains. From microscopic biological motors to potential macroscale machines, the concept that directional, sustainable motion can emerge spontaneously opens exciting questions about how natural and artificial systems exploit fluctuations and noise. Future research might explore various particle types, disk materials, or environmental conditions to optimize or diversify the functionality of symmetric ratchet motors.

In conclusion, this innovative investigation reveals a striking demonstration of how a symmetric system, devoid of any structural or geometric bias, can spontaneously organize under chaotic environmental conditions to perform directional mechanical work. It challenges existing theoretical frameworks and beckons further exploration into harnessing disorder as a resource rather than a hurdle. The experimental and theoretical advances presented by Ms. Hatatani and colleagues thus contribute a vital new chapter to the science of self-organization, statistical physics, and energy harvesting technologies—fields that promise to shape the technological landscape of the future.

Subject of Research: Not applicable

Article Title: Emergence of a ratchet motor by spontaneous symmetry breaking

News Publication Date: 1-Aug-2025

Web References: http://dx.doi.org/10.1063/5.0271467

References: Volume 35, Issue 8 of the journal Chaos

Image Credits: Ms. Miku Hatatani from Doshisha University, Japan

Keywords: Molecular biology, Chemistry

The allure of thermoelectric generators (TEGs) for wearable and soft bioelectronic devices lies in their ability to harvest body heat and convert it directly into electricity, thereby potentially powering implants, sensors, or personal temperature regulators without the need for bulky batteries. Flexibility in these materials aids in conforming to complex curved surfaces, such as skin, but elasticity is what ensures durability and sustained performance under repeated stretches and deformations typical in daily movement. Prior to this work, achieving high thermoelectric performance in materials that are truly elastomeric—capable of recovering from strains exceeding 100%—had remained elusive, primarily due to a trade-off between mechanical compliance and electrical functionality.

The innovation by Liu and colleagues stems from their clever integration of several crucial strategies into a single material system. At its core, their design hinges on a bulk nanophase separation approach, which differentiates distinct domains within the polymer matrix, enabling both robust mechanical properties and enhanced charge transport pathways. This architecture is complemented by thermally activated crosslinking that judiciously stabilizes the polymer network without sacrificing elasticity, maintaining the material’s rubber-like recovery even at large strains of up to 150%. Importantly, the researchers introduced targeted n-type doping, which imparts high electrical conductivity to the semiconducting polymer nanofibrils dispersed within the elastomeric framework.

Conventional wisdom in organic thermoelectrics had held that embedding insulating polymers to induce elasticity would invariably dilute the active semiconducting components, undermining electrical conductivity and therefore device efficiency. This study challenges and overturns that dogma by demonstrating that the choice of elastomer and dopant chemistry can be fine-tuned to not only preserve but actively enhance electrical conductivity. The n-doping process produces heavily doped polymer nanofibrils that are uniformly wrapped by elastomeric chains, creating effective percolation networks for charge transport while simultaneously suppressing phonon-mediated thermal conductivity.

This dual effect—of increased electrical conductivity coupled with decreased thermal conductivity—is pivotal for optimizing the dimensionless figure of merit, ZT, which governs thermoelectric efficiency. Liu et al.’s thermoelectric elastomers achieve ZT values rivalling or even surpassing those of some flexible inorganic materials, marking a significant step forward in the performance limitations that have traditionally held organic thermoelectrics back. These metrics were maintained or even improved under mechanical deformation, a testament to the material’s remarkable stability and resilience.

From a structural perspective, the thermoelectric elastomer’s morphology is characterized by the formation of uniform nanofibrillar networks intimately interfaced with the elastomer matrix. This microscopic ordering ensures that upon stretching, the conductive pathways remain intact or self-recover, preventing loss of electrical performance. The thermally activated crosslinking fortifies the polymer scaffold, providing an elastic backbone that withstands cyclic strains without hysteresis or mechanical fatigue. Such properties open transformative possibilities for wearables where devices must flex, stretch, and compress with body movements over extended periods.

The broader implications of this research touch upon the future of self-powered wearables and soft bioelectronics. With thermoelectric generators rendered truly elastic, devices can better conform to diverse and dynamic surfaces such as skin, joints, or even internal organs. This conformality is critical for intimate thermal contact, maximizing energy harvesting efficiency from subtle temperature gradients between human skin and the surrounding environment. One could envision new generations of personal temperature management systems—garments or patches that generate electricity from body heat while adapting seamlessly to body contours and movements.

Moreover, the ability to harness n-type materials with high performance complements existing p-type thermoelectric elastomers, enabling full thermoelectric modules that produce more efficient power outputs through complementary charge carrier types. Historically, n-type organic thermoelectrics have lagged behind their p-type counterparts, making this breakthrough particularly notable. This balance enhances the practical applicability of thermoelectric devices, especially in scenarios demanding light weight, elasticity, and mechanical robustness.

The approach detailed by Liu et al. not only marks a technological leap but also provides a generalizable materials platform. By elucidating the critical role of dopant distribution, nanophase separation morphology, and thermal crosslinking kinetics, their work paves the way for future materials engineering efforts to tailor mechanical and electrical properties in harmony. This insight is expected to catalyze innovation beyond thermoelectrics alone, influencing fields such as flexible electronics, stretchable sensors, and energy-harvesting textiles.

Yet, the research also points to challenges and questions for subsequent investigation. The long-term stability of dopants under physiological conditions, scalability of synthesis methods, and integration strategies for practical device manufacturing remain areas for further exploration. Control over the interfacial interactions between the elastomeric and semiconducting phases could unlock even higher thermoelectric figures of merit or multifunctional devices that combine sensing and power generation.

In conclusion, the paradigm shift introduced by the development of intrinsically elastic n-type thermoelectric elastomers heralds a new era for wearable energy technologies. By marrying high-performance thermoelectric functionality with true elastomeric mechanical behavior, this advancement sets the stage for innovative self-powered devices capable of stretching, bending, and recovering while delivering reliable electrical output. The work transforms the landscape of organic thermoelectrics and offers promising pathways toward ubiquitous, comfortable, and efficient wearable electronics powered solely by the heat of the human body.

As this technology evolves, the potential impacts span medical monitoring, fitness tracking, environmental sensing, and thermal regulation, all benefiting from materials that feel and behave like skin yet generate power sustainably. The findings underscore the critical value of interdisciplinary materials design in solving grand challenges at the interface of chemistry, physics, and engineering—a testament to the power of inventive molecular architecture in shaping tomorrow’s technologies.

Subject of Research: Elastic n-type thermoelectric materials for wearable energy harvesting devices.

Article Title: n-Type thermoelectric elastomers.

Article References:
Liu, K., Wang, J., Pan, X. et al. n-Type thermoelectric elastomers. Nature (2025). https://doi.org/10.1038/s41586-025-09387-z

Image Credits: AI Generated

The intricate dance of electrons and protons at interfaces has long been recognized as a crucial factor determining the efficiency and selectivity of numerous chemical reactions. By focusing on the interaction between solid surfaces and water, the team led by Chen, Li, Cai, and colleagues meticulously dissected the molecular details of peroxide activation—a key step in oxidative pathways that underlie many biological and industrial processes. Peroxide species, often considered as transient and highly reactive intermediates, play an essential role in oxidation reactions, environmental detoxification, and even cellular signaling. However, the precise mechanisms controlling their formation and reactivity at heterogeneous interfaces have remained elusive until now.

Central to the study is the phenomenon of proton-coupled electron transfer, a process where the transfer of an electron is intimately linked with the movement of a proton. This coupling is not a mere coincidence but a finely tuned mechanism that dictates reaction pathways and energy landscapes. Unlike classical electron transfer that may occur independently, PCET ensures a harmonized transfer that often lowers activation barriers and increases the specificity of chemical transformations. At the boundary where a solid material meets liquid water, these transfers orchestrate complex sequences that culminate in the formation or activation of peroxide species.

The research team employed a combination of advanced spectroscopic methods, electrochemical techniques, and theoretical modeling to unravel the subtle interplay of charges and protons. Their approach highlighted how the solid-water interface acts as more than a passive boundary; it is an active site where electronic states of the solid are dynamically involved in accepting and donating electrons, while the aqueous environment facilitates proton mobility. Such insights clarify how energy is funneled into steps that generate peroxide radicals or convert them into less reactive species, thereby controlling their life span and influence in subsequent reactions.

One of the remarkable findings was the identification of specific sites on the solid surface that serve as hotspots for PCET events. These sites, characterized by their unique electronic structure and coordination environment, enhance the coupling efficiency between electron and proton transfers. The modulation of these sites’ properties by surface defects, hydroxyl groups, or adsorbed species was shown to dramatically influence the rate and outcome of peroxide-related reactions. This discovery opens new avenues for tailoring solid surfaces at the atomic level to optimize their reactivity for targeted applications.

Moreover, the implications of controlling peroxide activation through PCET extend to environmental sciences, where peroxide species act as intermediates in pollutant degradation and water purification processes. A deeper understanding of how to manipulate PCET at interfaces could lead to more efficient catalytic systems that leverage ambient conditions and renewable energy inputs to detoxify contaminants and generate value-added products. This could revolutionize wastewater treatment technologies and pollutant management strategies by making them more sustainable and cost-effective.

In the realm of energy conversion, the study’s insights hold promise for improving the design of photoelectrochemical cells and fuel cells. The selective and controlled activation of peroxide species can be a pivotal factor in the oxygen reduction reaction (ORR) and hydrogen peroxide electrosynthesis, both of which are central to clean energy technologies. The precision afforded by PCET control mechanisms could enhance the efficiency and durability of catalytic electrodes, reducing energy losses and increasing product selectivity.

The researchers also explored how variations in pH, surface composition, and environmental conditions affect PCET-mediated peroxide processes. Their results demonstrated a delicate balance where subtle changes in proton availability or surface electronic states could switch reaction pathways, favoring either beneficial or deleterious outcomes. Such sensitivity underscores the necessity of tailoring reaction environments to harness desirable chemistry while suppressing unwanted side reactions, a fundamental challenge in catalysis and reaction engineering.

Computational modeling provided a molecular-level view of the energetic landscapes involved in PCET. The team used density functional theory (DFT) coupled with molecular dynamics simulations to map out the consecutive steps during peroxide formation and activation. These simulations revealed transition states and intermediate species that were previously unobservable, illuminating how PCET synchronizes electron and proton movements to facilitate smooth reaction progression. The computational insights also predicted how modifying surface properties could tune these energy profiles, offering a predictive framework for designing next-generation catalysts.

The findings contribute to a growing body of evidence emphasizing the universality of PCET in governing redox reactions at interfaces. Previous studies primarily focused on biological systems or homogeneous catalysis, but the current work extends the principles to heterogeneous solid-liquid interfaces with direct technological relevance. This cross-disciplinary relevance reflects the fundamental nature of PCET and underscores its potential as a unifying concept in chemistry and materials science.

Importantly, the study also raises intriguing questions about the role of water molecules themselves in mediating PCET processes. Beyond merely serving as a solvent, water participates actively by shuttling protons through hydrogen-bond networks, effectively bridging electron transfer events with proton dynamics. This insight challenges conventional notions of solvents as inert backgrounds and invites further exploration of solvent engineering as a strategy to optimize interfacial reactions.

The research team foresees numerous practical applications stemming from their discoveries. By exploiting PCET-controlled peroxide activation, it may be possible to develop selective oxidation catalysts that operate under mild conditions, reducing reliance on harsh chemicals and extreme temperatures. Such catalysts would be invaluable in green chemistry, pharmaceuticals, and fine chemical synthesis where precision and environmental compatibility are paramount.

Furthermore, the potential to regulate peroxide behavior at interfaces can impact biomedical technologies, particularly in areas involving reactive oxygen species (ROS). Controlled generation and degradation of ROS are critical in applications ranging from antimicrobial coatings to cancer therapies. Insights into PCET mechanisms could enable the design of surfaces that modulate ROS activity with unprecedented control, enhancing therapeutic outcomes while minimizing side effects.

The study’s methodological framework, combining experimental precision with theoretical rigor, sets a new standard for investigations into interfacial phenomena. By bridging scales from atomic interactions to macroscopic behaviors, this interdisciplinary approach provides a comprehensive understanding essential for rational catalyst design and optimization.

Looking forward, the authors suggest that integrating PCET insights with emerging materials such as two-dimensional semiconductors, metal-organic frameworks, and doped nanostructures could yield novel catalysts with tailored functionalities. Such integration holds the promise of unlocking unprecedented efficiencies in energy conversion and environmental applications.

This transformative research not only deepens our fundamental understanding but also lays the foundation for practical technologies that harness the subtle interplay of protons and electrons at solid-water interfaces. As scientists continue to explore the dynamic complexity of these reactions, the scope for innovation in catalysis, energy, and environmental science will undoubtedly expand, marking a new era in interface chemistry informed by the elegance of proton-coupled electron transfer.

Subject of Research: Proton-coupled Electron Transfer (PCET) mechanisms controlling peroxide activation at solid-water interfaces.

Article Title: Proton-coupled electron transfer controls peroxide activation initiated by a solid-water interface.

Article References:
Chen, JH., Li, WT., Cai, KY. et al. Proton-coupled electron transfer controls peroxide activation initiated by a solid-water interface. Nat Commun 16, 3789 (2025). https://doi.org/10.1038/s41467-025-58917-w

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