Traditional methods to achieve stretchability in electronics often turn to ancient Japanese arts—origami and kirigami. Origami, the art of folding paper, uses carefully engineered hinge patterns to create foldable yet structurally stable configurations. Kirigami, which incorporates strategic cuts along with folds, allows materials to deform more dramatically, enabling extensive stretching and bending. While origami lends itself to the incorporation of rigid, mountable panels, it lacks the range of deformability offered by kirigami. Conversely, kirigami’s expansive slits provide large-area stretchability but impose limitations on mounting rigid electronic components securely. This dichotomy represents a significant engineering bottleneck in stretchable device fabrication.

Addressing this, Professor Eiji Iwase and his collaborator Nagi Nakamura from Waseda University’s Department of Applied Mechanics and Aerospace Engineering have devised an innovative hybrid structure, coined “kiri-origami.” This approach harmoniously blends the folding mechanisms of origami with the cutting strategies of kirigami to craft structures that optimize stretchability without sacrificing the mechanical benefits of rigid components. Their pioneering work was published in the prestigious journal npj Flexible Electronics in June 2025 and stands to set new milestones in stretchable electronics design.

The ingenious kiri-origami framework features a mutually orthogonal cutting line pattern, strategically arranged to synergize deformation with mechanical support. Triangular joint panels, connected by two folding lines acting as hinges, reconcile two adjoining square panels formed by the cuts. Upon stretching from a flat baseline, these square panels elevate and rotate, enabling the formation of slits and culminating in a distinctive Z-shaped configuration around the hinges. This morphing not only facilitates a remarkable degree of stretch but also permits the simultaneous mounting and movement of rigid electronic components—previously a significant limitation in kirigami designs.

Idealized kiri-origami structures, characterized as rigid-origami, assume perfectly rigid panels with frictionless hinge rotation. However, real-world applications encounter panel deformation and the influence of elastic repulsive forces within flexible electronic substrates. To realistically capture these phenomena, the research team developed what they term an “elastic origami model.” Through experimental uniaxial stretching tests on rectangular models of this elastic origami, the researchers observed deviations from the rigid model predictions. Specifically, the fixed clamping edges and non-uniform tension distributions led to distortions, highlighting important mechanical factors that must be addressed for practical device deployment.

To counteract the detrimental effects of fixed edges and inconsistent tension, the researchers introduced a novel buffer structure design. These buffer components are trapezoidal extensions strategically connected to the edges of the kiri-origami structure and its clamps. The smaller edges of these buffers match the original width of the kiri-origami, while their larger edges are tailored to the target stretched configuration. Under tensile load, these buffers elongate akin to mechanical springs, distributing tension uniformly and enabling the entire structure to deform in a controlled, two-dimensional manner. This advancement enhances the fidelity of mechanical response, aligning experimental outcomes with rigid-model predictions and ensuring device reliability.

Demonstrating the practical viability of their approach, the team engineered a stretchable display integrating over 500 hinges and embedding 145 light-emitting diodes (LEDs). Remarkably, every hinge folded simultaneously without compromising the device’s function, underscoring the method’s potential for scalable, complex electronics. This feat not only showcases the robustness of the kiri-origami design but also highlights its promise for future applications extending beyond conventional flexible electronics.

Professor Iwase underscored the wide-reaching implications of this technology, emphasizing that it paves the path for next-generation wearable sensors, curved displays, and dynamic actuators in robotics and human-assistive technologies. The kiri-origami structure negates the historical compromise between flexibility and electronic performance, enabling the integration of traditional high-performance materials into highly deformable frameworks. This could drastically expand the landscape of wearable and implantable devices, enhancing user comfort, device durability, and overall functionality.

One of the standout technical triumphs of this study is the ability of the kiri-origami design to maintain uniform tension during stretching, vital for electronic stability and longevity. Previous methods struggled with uneven strain distributions leading to material fatigue or electrical failure. The buffer structure, by functioning as an adaptive spring, mitigates these issues and embodies an elegant solution fusing structural mechanics with electronic engineering.

By integrating rudimentary mechanical principles from age-old Japanese arts into cutting-edge materials science, this approach redefines the future of electronic device fabrication. It resonates particularly well in the context of expanding fields such as soft robotics and biomedical instrumentation, where devices must conform reliably to complex, dynamic bodily shapes while maintaining sophisticated functionality.

Furthermore, the scalability of the kiri-origami technique marks a crucial advance. The capacity to fabricate devices with large numbers of repeating units suits mass production and broad deployment. This opens avenues for customizable stretchable electronics tailored to user-specific geometries, from flexible displays that seamlessly curve around wrists and fingers to sensors that adapt to unpredictable human body movements.

The breakthrough reported by Iwase and Nakamura offers a compelling paradigm shift, demonstrating that the limitations of material properties can be surmounted through innovative structural engineering. Their contribution stands as a testament to interdisciplinary synergy, where mechanical design principles align with materials science to unlock new technological horizons.

Looking ahead, this innovation holds the promise of transforming not just consumer electronics but also healthcare diagnostics and robotic assistance systems. Stretchable, high-performance electronic platforms energized by kiri-origami structures will likely become foundational enablers of futuristic applications, catalyzing advances in personalized medicine and bio-integrated robotics.

As this research gains traction, it may inspire further explorations into hybrid fold-and-cut geometries, adaptive mechanics, and integrated system design, inspiring a fresh wave of innovations that blend historical artistry with modern scientific tenacity.

Subject of Research: Not applicable

Article Title: Stretch-based kirigami structure with folding lines for stretchable electronics

News Publication Date: 5-Jun-2025

Web References: https://doi.org/10.1038/s41528-025-00409-4

References: Nakamura N, Iwase E. Stretch-based kirigami structure with folding lines for stretchable electronics. npj Flexible Electronics. 2025;9:Article 4. https://doi.org/10.1038/s41528-025-00409-4

Image Credits: Professor Eiji Iwase, Waseda University

Keywords

Electronics; Wearable devices; Applied physics; Applied sciences and engineering; Sensors; Robotics; Mechanical engineering; Materials science

Actuators that respond to optical stimuli, known as photomechanical crystals, represent a cutting-edge class of smart materials capable of converting light energy directly into mechanical work. Unlike conventional actuators that rely on electrical input, these organic crystals offer significant benefits including low energy consumption, contactless operation, and the potential for miniaturization. However, the core challenge limiting their widespread adoption has been the difficulty in achieving high blocking forces—the maximum force these crystals exert when their deformation is restrained—due to the multifaceted interdependencies between molecular structure, crystal lattice arrangement, and environmental factors.

The breakthrough from Waseda University addresses this challenge by employing a data-driven, machine learning–guided strategy that integrates both synthetic chemistry and experimental optimization. Led by Associate Professor Takuya Taniguchi of the Center for Data Science, the research team combined least absolute shrinkage and selection operator (LASSO) regression with Bayesian optimization methods, enabling a refined search across a vast chemical landscape of salicylideneamine derivatives. This approach allowed them to pinpoint molecular designs most conducive to enhanced photomechanical response while simultaneously identifying optimal experimental parameters to fuel efficient and targeted performance testing.

LASSO regression, a technique designed for variable selection and regularization, proved instrumental in distilling a high-dimensional molecular parameter space into a manageable subset of promising candidates. By emphasizing sparsity in the regression model, the team successfully narrowed down complex molecular descriptors that correlate strongly with blocking force output. This computational screening laid the foundation for Bayesian optimization to guide subsequent experimental iterations, wherein the algorithm intelligently predicted the next most informative set of conditions under which force measurements should be conducted—thereby bypassing the inefficiency of traditional trial-and-error experimentation.

The results were striking. The optimized photo-actuated crystals achieved a blocking force 3.7 times greater than previously reported values, with the process demonstrating at least a 73-fold improvement in efficiency compared to conventional methods. This unprecedented advancement not only ramps up the achievable mechanical output of these materials but also provides a scalable framework for accelerating the discovery and fine-tuning of photo-responsive organic crystals, which have historically suffered from slow development cycles due to the complexity of their design space.

Beyond the raw performance metrics, this research exemplifies how machine learning can unify theoretical predictions and experimental validation within a closed-loop system. The iterative synergy between data-driven modeling and hands-on testing cultivates a more nuanced understanding of how molecular-level modifications propagate macroscopic mechanical behavior, unlocking hidden correlations and design principles inaccessible through classical methodologies. This paradigm shift promises to redefine the pace and scope of functional materials research in the decades ahead.

The implications of these findings stretch far beyond the laboratory. Photo-actuated crystals, with their contactless operation enabled by remote light activation, are exceptionally well-suited to applications demanding precise, noninvasive control. Small-scale robotics, where space and weight constraints are paramount, can benefit immensely from lightweight crystal actuators delivering robust mechanical force without the need for bulky electrical components or tethered power supplies. Similarly, in the medical devices sector, these materials offer promising avenues for microsurgical instrumentation or drug delivery systems where remote operation and minimal invasiveness are critical.

The underlying optomechanical mechanism leverages the molecular photoisomerization processes—light-induced changes in molecular geometry—within the crystalline lattice. When these molecular switches actuate cohesively across the ordered crystal matrix, they collectively induce volume changes and shape deformations measurable as mechanical force. The ability to systematically tune the chemistry of these molecular units, guided by machine learning, allows for precise tailoring of actuation dynamics including response speed, force magnitude, and fatigue resistance, which are all vital parameters for practical device integration.

Furthermore, this technology aligns with growing global efforts toward sustainable and energy-efficient engineering. By utilizing light, often from low-energy ambient or focused sources, as an actuation driver, photo-responsive crystals reduce reliance on traditional power-hungry actuators. This inherently cleaner energy input not only diminishes environmental impact but also opens pathways for developing self-powered smart systems operating autonomously in remote or resource-limited settings.

The integration of machine learning in this materials discovery context exemplifies the transformative potential of AI to navigate multidimensional parameter spaces quickly and effectively, often revealing novel chemical architectures and performance optima that might otherwise remain hidden. The Waseda University team’s methodology could therefore serve as a blueprint for other domains where complex structure-function relationships govern material behavior, from energy storage to catalysis.

Associate Professor Taniguchi emphasizes, “Our interdisciplinary approach, bridging data science and synthetic chemistry, paves the way for designing increasingly sophisticated photo-responsive materials. The ability to rapidly iterate and identify optimal molecular structures and experimental settings accelerates innovation and may soon translate to commercial platforms for wearable technology, aerospace actuators, and environmental sensing devices.”

This pioneering research not only demonstrates a substantial leap in the mechanical capabilities of organic photomechanical crystals but also marks a critical step toward their scalable application. The confluence of machine learning–driven molecular design and experimental optimization improves understanding at multiple hierarchical levels—from molecular dynamics to macroscopic force generation—allowing the scientific community to envision a future where smart, light-responsive materials integrate seamlessly into everyday technologies.

Ultimately, the work spearheaded at Waseda University showcases the profound impact of combining artificial intelligence with materials science—a synergy that promises to catalyze next-generation innovations across robotics, medical technology, and sustainable engineering. As these photo-actuated organic crystals move closer to real-world deployment, the ripple effect on designing adaptive, energy-conscious devices could be transformative on a global scale.

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Subject of Research: Not applicable
Article Title: Machine Learning-Driven Optimization of Output Force in Photo-Actuated Organic Crystals
News Publication Date: 20 March 2025
Web References: https://doi.org/10.1039/D4DD00380B
References: Ishizaki, K., Asahi, T., & Taniguchi, T. (2025). Digital Discovery. DOI: 10.1039/D4DD00380B
Image Credits: Takuya Taniguchi from Waseda University

Keywords

Machine learning; Crystals; Chemical engineering; Mechanical engineering; Actuators; Materials science; Applied physics; Robotics