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Abstract This is a roadmap article with multiple contributors on different aspects of embodying intelligence and computing in the mechanical domain of functional materials and structures. Overall, an IOP roadmap article is a broad, multi-author review with leaders in the field discussing the latest developments, commissioned by the editorial board. The intention here is to cover various topics of adaptive structural and material systems with mechano-intelligence in the overall roadmap, with twelve sections in total. These sections cover topics from materials to devices to systems, such as computational metamaterials, neuromorphic materials, mechanical and material logic, mechanical memory, soft matter computing, physical reservoir computing, wave-based computing, morphological computing, mechanical neural networks, plant-inspired intelligence, pneumatic logic circuits, intelligent robotics, and embodying mechano-intelligence for engineering functionalities via physical computing.  In this paper, we view all the 2-page sections with equal contributions to the overall roadmap article and thus list the authorship on the front page via alphabetical order of their last names.  On the other hand, for each individual section, the authors decide on their own the order of authorship.  

Abstract The synthesis of soft matter intelligence with circuit‐driven logic has enabled a new class of robots that perform complex tasks or conform to specialized form factors in unique ways that cannot be realized through conventional designs. Translating this hybrid approach to fluidic systems, the present work addresses the need for sheet‐based circuit materials by leveraging the innate porosity of foam—a soft material—to develop pneumatic components that support digital logic, mixed‐signal control, and analog force sensing in wearables and soft robots. Analytical tools and experimental techniques developed in this work serve to elucidate compressible gas flow through porous sheets, and to inform the design of centimeter‐sized foam resistors with fluidic resistances on the order of 10⁹ Pa s m⁻³. When embedded inside soft robots and wearables, these resistors facilitate diverse functionalities spanning both sensing and control domains, including digital logic using textile logic gates, digital‐to‐analog signal conversion using ladder networks, and analog sensing of forces up to 40 N via compression‐induced changes in resistance. By combining features of both circuit‐based and materials‐based approaches, foam‐enabled fluidic circuits serve as a useful paradigm for future hybrid robotic architectures that fully embody the sensing and computing capabilities of soft fluidic materials. 

The recent development of soft fluidic analogs to electrical components aims to reduce the demand for rigid and bulky electromechanical valves and hard electronic controllers within soft robots. This ongoing effort is advanced in this work by creating sheet‐based fluidic diodes constructed from readily available flexible sheets of polymers and textiles using a layered fabrication approach amenable to manufacturing at scale. These sheet‐based fluidic diodes restrict reverse flow over a wide range of differential pressures—exhibiting a diodicity (the ratio of resistance to reverse vs forward flow) of approximately 100×—to address functional limitations exhibited by prior soft fluidic diodes. By harnessing the diode's highly unidirectional flow, soft devices capable of 1) facilitating the capture and storage of pressurized fluid, 2) performing Boolean operations using diode logic, 3) enabling binary encoding of circuits by preventing interactions between different pressurized input lines, and 4) converting oscillating input pressures to a direct current‐like, positively phased output are realized. This work exemplifies the use of fluidic diodes to achieve complex patterns of actuation and unique capabilities through embedded fluidic circuitry, enabling future development of sheet‐based systems—including wearable and assistive robots made from textiles—as well as other soft robotic devices. 

Wearable haptic devices transmit information via touch receptors in the skin, yet devices located on parts of the body with high densities of receptors, such as fingertips and hands, impede interactions. Other locations that are well‐suited for wearables, such as the wrists and arms, suffer from lower perceptual sensitivity. The emergence of textile‐based wearable devices introduces new techniques of fabrication that can be leveraged to address these constraints and enable new modes of haptic interactions. This article formalizes the concept of “multiscale” interaction, an untapped paradigm for haptic wearables, enabling enhanced delivery of information via textile‐based haptic modules. In this approach, users choose the depth and detail of their haptic experiences by varying their interaction mode. Flexible prototyping methods enable multiscale haptic bands that provide both body‐scale interactions (on the forearm) and hand‐scale interactions (on the fingers and palm). A series of experiments assess participants’ ability to identify pressure states and spatial locations delivered by these bands across these interaction scales. A final experiment demonstrates the encoding of three‐bit information into prototypical multiscale interactions, showcasing the paradigm's efficacy. This research lays the groundwork for versatile haptic communication and wearable design, offering users the ability to select interaction modes for receiving information.