Daniel J. Preston

We present a strain-engineering strategy for oxygen-modified nickel telluride/nickel oxide heterostructures capable of enabling bifunctional alkaline water electrolysis with performance surpassing Pt and IrO x benchmarks. The heterostructures are synthesized via electrochemical Te dissolution and mild oxidation of mechanically exfoliated NiTe 2, followed by controlled strain induction through substrate buckling. Atomic-scale simulations and spectroscopic analyses indicate that Te-vacancy/O-substituted NiTe 2 domains promote oxygen-intermediate spillover between adjacent active sites, reducing OER overpotentials. In parallel, strained NiTe 2 domains facilitate hydrogen-intermediate transfer to NiO containing Ni vacancies, leading to accelerated HER kinetics and near-thermoneutral hydrogen adsorption. Strain modulation adjusts the electronic structure and increases active-site density, enabling stable operation at industrial-level current densities (>1 A cm –2 ). These findings illustrate how defect chemistry coupled with strain engineering can be utilized to develop high-performance, earth-abundant bifunctional electrocatalysts.

A design methodology is presented here for MoTe x /Ni(OH) 2 heterostructured catalysts that enhance the oxygen evolution reaction (OER) in water electrolysis. This approach relies on the transfer of mechanically exfoliated MoTe 2 nanosheets to Au/Si substrates followed by electrochemical Te dissolution to induce defect-mediated, partial semiconducting (2H) to metallic (1T’) phase transitions. Immersing the resulting MoTe x into a nickel nitrate hydrate solution results in a heterostructure consisting of 2H-MoTe x /Ni(OH) 2 and 1T’-MoTe x /Ni(OH) 2 domains, which enables high stability and improved efficiency for the OER compared to IrO x . Both machine-learning potential and density functional theory calculations searched and evaluated all atomic sites for this materials system, thus revealing the enhancement mechanisms of OER via four-electron transfer processes with lowered free energy barriers in the rate-determining steps.

Silicone elastomers are widely used in biomedical devices and soft machines because of their compliance, inertness, and biocompatibility. Their sol-gel transition during curing enables mold casting and layer-by-layer manufacturing, allowing the fabrication of fully elastomeric and hybrid soft-rigid devices. However, controlling adhesion at material interfaces remains elusive, especially under diverse temperature conditions. This study introduces a framework that relates adhesion strength to a dimensionless reaction coordinate coupling time and temperature. This reaction coordinate can be used to predict the transition from bulk fracture to adhesive failure, which is crucial to create robust devices with strong interfaces. Using this framework, we fabricated elastomeric robotic actuators and demonstrated 3D printing with direct ink writing. The actuators achieved 50% higher curvature with the same design, and the 3D-printed parts exhibited over 200% improvement in interlayer adhesion. This work serves as a tool for optimizing interfacial adhesion for soft materials across different fabrication approaches.

Achieving carbon neutrality requires effective strategies to reduce CO 2 emissions, and geological sequestration of CO 2 is considered among the most promising and economically viable options. The interfacial tension (IFT) between the CO 2 and the surrounding liquid (underground salt water or brine, NaCl) is a key parameter that affects the storage capacity of CO 2 in saline aquifers; however, the experimental measurement of IFT is often time-consuming, labor-intensive, and reliant on expensive equipment, and empirical correlations demonstrate a low level of accuracy. Machine learning (ML) techniques have been suggested as an alternative approach, and the current literature related to interfacial phenomena utilizes a wide array of basic and advanced ML models for predicting IFT, though often without a comparative analysis, raising the question of which model is most appropriate for this specific application. In this work, multiple machine learning models, including linear regression (LR), support vector machine (SVM), decision tree regressor (DTR), random forest regressor (RFR), and multilayer perceptron (MLP), are used to predict the IFT of the CO 2 and aqueous solution of NaCl. Models are trained using an experimental dataset that covers a wide range of temperature, pressure, and salinity (NaCl) conditions for CO 2 -brine IFT. Hyperparameter tuning algorithms are utilized to optimize each model, and the performance is evaluated using metrics such as mean absolute error (MAE) and mean absolute percentage error (MAPE). The best-performing algorithms are found to be SVM and MLP, with a MAPE of 0.97% and 0.99% and a MAE of 0.39 mN/m and 0.40 mN/m, respectively. The linear regression model demonstrated the worst performance with a MAPE of 4.25% and an MAE of 1.7 mN/m. The feature importance analysis reveals that pressure is the main parameter affecting the IFT. Our findings indicate a notable enhancement in prediction accuracy over previous ML studies in this area. Moreover, the results from this study suggest that even the basic ML models that were investigated, when properly tuned and optimized, are sufficient for accurate IFT predictions. This demonstrates that ML models offer a cost-effective and efficient alternative to experimental methods, potentially optimizing designs for CO 2 sequestration.

Haptic devices enable communication via touch, augmenting visual and auditory displays, or by offering alternative channels of communication when vision and hearing are unavailable. Because of the different types of haptic stimuli that are perceivable by users — vibration, skin stretch, pressure and temperature, among others — devices can be designed to communicate complex information by delivering multiple types of haptic stimuli simultaneously. These multi-sensory haptic devices are often designed to be wearable and have been developed for use in a wide variety of applications, including communication, entertainment and rehabilitation. Multi-sensory haptic devices present unique challenges to designers because human perceptual acuity can vary widely depending on the wearable location on the body and/or the heterogeneity in human perceptual performance, particularly when multiple cues are presented simultaneously. Additionally, packaging haptic systems in a wearable form factor presents its own engineering challenges such as cue masking, device mounting and actuator capabilities, among others. Thus, in this Review, we discuss the state-of-the-art and specific obstacles present in the field to produce multi-sensory devices that enhance the human capacity for haptic interaction and information transmission. Haptic devices enable communication via touch, augmenting visual and auditory displays, or by offering alternative channels of communication when vision and hearing are unavailable. This Review discusses multi-sensory wearable haptics, focusing on body-worn devices that convey multiple types of cutaneous haptic feedback. The translation of wearable multi-sensory haptic devices relies on a robust understanding of human haptic perception so that feedback modalities can be combined to optimally enhance user performance in a given application domain. The contact mechanics at the haptic interface between device and skin varies between users with an unknown effect on haptic perception. In addition to traditional electromechanical actuation, new methods, such as polymeric, fluidic and thermal actuation, now exist. When designing wearable haptic devices, body location, the device interface to the body, user comfort and preserving the integrity of the haptic feedback must be considered. The translation of wearable multi-sensory haptic devices relies on a robust understanding of human haptic perception so that feedback modalities can be combined to optimally enhance user performance in a given application domain. The contact mechanics at the haptic interface between device and skin varies between users with an unknown effect on haptic perception. In addition to traditional electromechanical actuation, new methods, such as polymeric, fluidic and thermal actuation, now exist. When designing wearable haptic devices, body location, the device interface to the body, user comfort and preserving the integrity of the haptic feedback must be considered.

This paper describes a simple design methodology to develop layered PtSe 2 catalysts for hydrogen evolution reaction (HER) in water electrolysis operating under ultralow overpotentials. This approach relies on the transfer of mechanically exfoliated PtSe 2 flakes to gold thin films on prestrained thermoplastic substrates. By relieving the prestrain, a tunable level of uniaxial internal compressive and tensile strain is developed in the flakes as a result of spontaneously formed surface wrinkles, giving rise to band structure modulations with overlapped values of the valence band maximum and conduction band minimum. This strain-engineered PtSe 2 with an optimized level of internal tensile strain amplifies the HER performance of the PtSe 2, with performance far greater than that of pure platinum due to significantly reduced charge transfer resistance. Density functional theory calculations provide fundamental insight into how strain-induced band structure engineering correlates with the promoted HER activity, especially at the atomic edge sites of the materials.

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 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 written by Guest Editors Kon-Well Wang (aka K W Wang) and Suyi Li.)

Thin, flexible sheets can be patterned and bonded to form internal fluidic networks, which enable actuation, sensing, and control, but failure of these sheet-based systems—and how to take advantage of this failure—remains relatively unexplored. Here, we examine this concept using heat-sealable textiles as a material platform. We determine the effects of geometry and material processing on bond strength and burst pressure; these findings can ensure a sheet-based fluidic system is sufficiently robust for a given use case. Building on this framework, we introduce a fuse-like component into which failure is deliberately programmed. In addition to limiting damage in the case of overpressurization, we leverage this programmed failure to enable distinct capabilities including (1) the binary selection of operating modes and (2) the sequencing of a series of tasks with a single pressure input. These findings will facilitate the development of more intelligent sheet-based fluidic systems.

Patterned solid surfaces with wettability contrast can enhance liquid transport for applications such as electronics thermal management, self-cleaning, and anti-icing. However, prior work has not explored easy and scalable blade-cut masking to impart topography patterned wettability contrast on aluminum (Al), even though Al surfaces are widely used for thermal applications. Here, we demonstrate mask-enabled topography contrast patterning and quantify the resulting accuracy of the topographic pattern resolution, spatial variations in surface roughness, wettability, drop size distribution during dropwise condensation, and thermal emissivity of patterned Al surfaces. The method uses blade-cut vinyl mask templates and a commercially available lacquer resin that serves as a polymer resist against etching. Programmable mask templates enable complex patterning of wettability and emissivity contrast with feature sizes down to ∼1.5 mm. As-fabricated patterned samples show a water contact angle (θ) contrast from <5° to 80° between etched and smooth zones, while patterned samples that are further coated with a hydrophobic promoter show θ contrast between 150° and 120° on etched and smooth zones, respectively. In addition to measuring this wettability contrast via contact angle goniometry, we use condensation visualization experiments to study the spatially controlled condensate morphologies and drop size distributions. These condensation studies demonstrate enhanced droplet shedding on the superhydrophobic regions of striped patterned surfaces compared to homogeneous superhydrophobic surfaces. Motivated by the role of thermal radiation in many phase change processes, we use infrared thermography to map topography-mediated thermal emissivity (ε) contrast between etched (ε ≈ 0.65) and smooth (ε ≈ 0.26) regions. Thus, our study provides a route for researchers to readily create complex and scalable topography-patterned Al surfaces for potential applications in vapor chamber thermal rectification, radiative cooling condensation heat transfer, and high-temperature Leidenfrost or film boiling processes.

Additive manufacturing (AM) has opened a new pathway to create customized wicking materials. With lower manufacturing costs and a larger design space than many alternatives for wicking, AM is of particular value in fields such as thermal management and microfluidics. Fluid propagation during wicking in porous media, however, has largely remained limited to Washburnian ( t ) behavior, and optimizing these materials for wicking in a variety of use cases presents a challenge. In this work, we present a method of tailoring wicking behavior to an arbitrary target function of propagation distance versus time, achieved through the use of AM to create nonuniform porous materials. Layers of parallel lines, each successive layer rotated 90° from the last, form a gridded structure with a spatially varying unit cell size for which analytical models for the capillary pressure and solid fraction and a semianalytical model for permeability were found. These models were validated with capillary rise experiments for spatially uniform porous materials over a range of solid fractions from 0.4 to 0.9. Leveraging these models and representing a nonuniform porous material as a series of Ohmic fluidic resistors, we created an inverse design algorithm that generates a wicking material with spatially varying parameters to achieve a specified target function for fluid propagation as a function of time. These materials can exhibit atypical wicking behavior, including fluid propagation displaying simple linear and piecewise linear relationships with time rather than the conventional Washburn relationship.

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 10 9 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.

Flexible Sheet-Based Fluidic Diodes In article number 2300785, Vi T. Vo, Daniel J. Preston, and co-workers introduce a soft fluidic diode made from flexible thermoplastic and textile sheets using a layered fabrication approach. This cover image illustrates the diode as a foundational component in the development of sheet-based fluidic logic systems—as both modular and integrated circuits—to enable electronics-free control of soft devices and robots. Fluidic circuits incorporating the diode provide capabilities including Boolean operations, encoding, and rectification.

Multiscale Haptic Interactions Most wearable haptic devices (top left) deliver haptic notifications to the body; perception of haptics is depicted as brain activity (pink region). In the multiscale paradigm (bottom right), a user actively interacts with the wearable device to perceive a greater amount of information, both via passive receipt of haptic notifications through the band (pink region) and via active exploration of the textile haptic band with fingertips (yellow region). Background letters and numbers represent information transmission to the user via the device. For more information on multiscale haptics, see article number 2300897 by Marcia K. O’Malley and co-workers.

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.

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.

Abstract Electrocatalytic water splitting is crucial to generate clean hydrogen fuel, but implementation at an industrial scale remains limited due to dependence on expensive platinum (Pt)‐based electrocatalysts. Here, an all‐dry process to transform electrochemically inert bulk WS 2 into a multidomain electrochemical catalyst that enables scalable and cost‐effective implementation of the hydrogen evolution reaction (HER) in water electrolysis is reported. Direct dry transfer of WS 2 flakes to a gold thin film deposited on a silicon substrate provides a general platform to produce the working electrodes for HER with tunable charge transfer resistance. By treating the mechanically exfoliated WS 2 with sequential Ar‐O 2 plasma, mixed domains of WS 2 , WO 3 , and tungsten oxysulfide form on the surfaces of the flakes, which gives rise to a superior HER with much greater long‐term stability and steady‐state activity compared to Pt. Using density functional theory, ultraefficient atomic sites formed on the constituent nanodomains are identified, and the quantification of atomic‐scale reactivities and resulting HER activities fully support the experimental observations.

Abstract Jumping droplet thermal diodes (JDTDs) are promising candidates to achieve thermal rectification for next‐generation thermal control. However, most prior demonstrations of JDTDs have relied on monolayer‐coated copper‐based superhydrophobic (SHPB) surfaces, while lower‐cost aluminum JDTDs with more durable thin polymeric coatings have not been explored. In this work, a JDTD is constructed that employs SHPB aluminum surfaces coated with protective thin films of Teflon AF (amorphous fluoropolymer) 1601. Measurements for different heating orientations, gap heights ( H ), and fill ratios (ϕ) show that a maximum thermal rectification ratio of 7 can be achieved for H = 2.4 mm and ϕ = 10%. A thermal circuit is demonstrated that uses the JDTD to rectify time‐periodic temperature profiles, achieving thermal circuit effectiveness values up to 30% of the ideal‐diode limit. Coupon‐level durability tests and device‐level cycling show that dip coated Teflon AF enables stable operation of Al JDTDs over &gt;20 cycles, improving on the performance of a monolayer‐coated surface that fails after 5 cycles. The findings of this work signify that Teflon AF coated Al SHPB surfaces can be used for thermal rectification and motivate future research into Al JDTDs for advanced thermal management applications.

Silicone elastomers exhibit extraordinary compliance, positioning them as a material of choice for soft robots and devices. To accelerate curing times of platinum-catalyzed silicone elastomers, researchers have employed elevated temperatures; however, knowledge of the requisite duration for curing at a given temperature has remained limited to specific elastomers and has relied primarily on empirical trends. This work presents an analytical model based on an Arrhenius framework coupled with data from thermo-rheological experiments to provide guidelines for suitable curing conditions for commercially available addition-cured platinum-catalyzed silicone elastomers. The curing reaction exhibits self-similarity upon normalizing to a dimensionless reaction coordinate, allowing quantification of the extent of curing under arbitrary time-varying thermal conditions. Mechanical testing revealed no significant changes in properties or performance as a result of thermally accelerated curing. With this framework, higher throughput of elastomeric components can be achieved, and the design space for elastomer-based manufacturing can be developed beyond conventional casting.

Fine airborne particles (<10 µm) pose challenges for engineered systems, human health, and environmental pollution. This work investigates the relative influences of van der Waals and capillary adhesion forces during filtration to guide the design of multiplexed inertial coalescence filters, which are constructed with a parallel series of helical passageways designed for low pressure drop (<150 Pa) and capture of fine particulate matter (5–50 μm). Specifically, we experimentally quantified the influence of particle adhesion forces on filtration efficiency for capture of 6.1 µm activated carbon particle clusters. Filtration efficiency for dry filters, where van der Waals adhesion forces dominate, is significantly diminished beyond a threshold flowrate due to the Saffman lift force, which causes wall-bound particle clusters to detach from the interior filter surfaces. For wetted filters, the capillary adhesion force is orders of magnitude greater than the Saffman lift force, and consequently the filtration efficiency is not adversely affected. We developed models for filter pressure drop and filtration efficiency accounting for the influence of particle adhesion forces; these models showed good agreement with experimental results. Filter quality factor (QF) was determined for varying particle sizes and flowrates and can be used as a design guideline for use-case-specific filter optimization, which is enabled by the customizable additive manufacturing approach used to fabricate the filters. Due to its versatility and low-pressure-drop nature, this filtration approach could find use in heating, ventilation, and air conditioning (HVAC), large particle and dust filtration in industrial processes, cleanroom pre-filtration, and beyond.Copyright © 2024 American Association for Aerosol Research

A consensus was built in the first half of the 20th century, which was further debated more than 3 decades ago, that the wettability and condensation mechanisms on smooth solid surfaces are modified by the adsorption of organic contaminants present in the environment. Recently, disagreement has formed about this topic once again, as many researchers have overlooked contamination due to its difficulty to eliminate. For example, the intrinsic wettability of rare earth oxides has been reported to be hydrophobic and non-wetting to water. These materials were subsequently shown to display dropwise condensation with steam. Nonetheless, follow on research has demonstrated that the intrinsic wettability of rare earth oxides is hydrophilic and wetting to water, and that a transition to hydrophobicity occurs in a matter of hours-to-days as a consequence of the adsorption of volatile organic compounds from the ambient environment. The adsorption mechanisms, kinetics, and selectivity, of these volatile organic compounds are empirically known to be functions of the substrate material and structure. However, these mechanisms, which govern the surface wettability, remain poorly understood. In this contribution, we introduce current research demonstrating the different intrinsic wettability of metals, rare earth oxides, and other smooth materials, showing that they are intrinsically hydrophilic. Then we provide details on research focusing on the transition from wetting (hydrophilicity) to non-wetting (hydrophobicity) on somooth surfaces due to adsorption of volatile organic compounds. A state-of-the-art figure of merit mapping the wettability of different smooth solid surfaces to ambient exposure as a function of the surface carbon content has also been developed. In addition, we analyse recent works that address these wetting transitions so to shed light on how such processes affect droplet pinning and lateral adhesion. We then conclude with objective perspectives about research on wetting to non-wetting transitions on smooth solid surfaces in an attempt to raise awareness regarding this surface contamination phenomenon within the engineering, interfacial science, and physical chemistry domains.

Electrocatalytic water splitting produces hydrogen fuel, but its dependence on expensive platinum-based electrocatalysts has limited industrial-scale implementation. Here, we report an approach for the activation of electrochemically inert layered MoTe 2 that results in a low-cost, scalable, and readily available hydrogen evolution reaction (HER) catalyst for water splitting. This approach relies on the transfer of mechanically exfoliated MoTe 2 flakes to gold thin films on prestrained thermoplastic substrates. By relieving the prestrain, a tunable level of internal tensile strain is developed in the flakes as a result of spontaneously formed surface wrinkles, resulting in a local semiconductor-to-metal phase transition to form phase boundaries. This strain engineering enhances the HER performance of the MoTe 2 with reduced charge transfer resistance, and in operando activation of the flakes further amplifies the electrochemical activity, rivaling that of platinum. Density functional theory calculations provide fundamental insight into how strain-induced heterophase boundaries promoted HER activity.

Pandemics stress supply lines and generate shortages of personal protective equipment (PPE), in part because most PPE is single-use and disposable, resulting in a need for constant replenishment to cope with high-volume usage. To better prepare for the next pandemic and to reduce waste associated with disposable PPE, we present a composite textile material capable of thermally decontaminating its surface via Joule heating. This material can achieve high surface temperatures (>100 °C) and inactivate viruses quickly (<5 s of heating), as evidenced experimentally with the surrogate virus HCoV-OC43 and in agreement with analytical modeling for both HCoV-OC43 and SARS-CoV-2. Furthermore, it does not require doffing because it remains relatively cool near the skin (<40 °C). The material can be easily integrated into clothing and provides a rapid, reusable, in situ decontamination method capable of reducing PPE waste and mitigating the risk of supply line disruptions in times of need.

Haptic feedback offers a useful mode of communication in visually or auditorily noisy environments. The adoption of haptic devices in our everyday lives, however, remains limited, motivating research on haptic wearables constructed from materials that enable comfortable and lightweight form factors. Textiles, a material class fitting these needs and already ubiquitous in clothing, have begun to be used in haptics, but reliance on arrays of electromechanical controllers detracts from the benefits that textiles offer. Here, we mitigate the requirement for bulky hardware by developing a class of wearable haptic textiles capable of delivering high-resolution information on the basis of embedded fluidic programming. The designs of these haptic textiles enable tailorable amplitudinal, spatial, and temporal control. Combining these capabilities, we demonstrate wearables that deliver spatiotemporal cues in four directions with an average user accuracy of 87%. Subsequent demonstrations of washability, repairability, and utility for navigational tasks exemplify the capabilities of our approach.

Airborne hydrocarbon contamination hinders nanomanufacturing, limits characterization techniques, and generates controversies regarding fundamental studies of advanced materials; consequently, we urgently need effective and scalable clean storage techniques. In this work, we propose an approach to clean storage using an ultraclean nanotextured storage medium as a getter. Experiments show that our proposed approach can maintain surface cleanliness for more than 1 week and can even passively clean initially contaminated samples during storage. We theoretically analyzed the contaminant adsorption-desorption process with different values of storage medium surface roughness, and our model predictions showed good agreement with experiments for smooth, nanotextured, and hierarchically textured surfaces, providing guidelines for the design of future clean storage systems. The proposed strategy offers a promising approach for portable and cost-effective storage systems that minimize hydrocarbon contamination in applications requiring clean surfaces, including nanofabrication, device storage and transportation, and advanced metrology.

Vibration is a widely used mode of haptic communication, as vibrotactile cues provide salient haptic notifications to users and are easily integrated into wearable or handheld devices. Fluidic textile-based devices offer an appealing platform for the incorporation of vibrotactile haptic feedback, as they can be integrated into clothing and other conforming and compliant wearables. Fluidically driven vibrotactile feedback has primarily relied on valves to regulate actuating frequencies in wearable devices. The mechanical bandwidth of such valves limits the range of frequencies that can be achieved, particularly in attempting to reach the higher frequencies realized with electromechanical vibration actuators ( 100 Hz). In this paper, we introduce a soft vibrotactile wearable device constructed entirely of textiles and capable of rendering vibration frequencies between 183 and 233 Hz with amplitudes ranging from 23 to 114 g. We describe our methods of design and fabrication and the mechanism of vibration, which is realized by controlling inlet pressure and harnessing a mechanofluidic instability. Our design allows for controllable vibrotactile feedback that is comparable in frequency and greater in amplitude relative to state-of-the-art electromechanical actuators while offering the compliance and conformity of fully soft wearable devices.

Vibration is ubiquitous as a mode of haptic communication, and is used widely in handheld devices to convey events and notifications. The miniaturization of electromechanical actuators that are used to generate these vibrations has enabled designers to embed such actuators in wearable devices, conveying vibration at the wrist and other locations on the body. However, the rigid housings of these actuators mean that such wearables cannot be fully soft and compliant at the interface with the user. Fluidic textile-based wearables offer an alternative mechanism for haptic feedback in a fabric-like form factor. To our knowledge, fluidically driven vibrotactile feedback has not been demonstrated in a wearable device without the use of valves, which can only enable low-frequency vibration cues and detract from wearability due to their rigid structure. We introduce a soft vibrotactile wearable, made of textile and elastomer, capable of rendering high-frequency vibration. We describe our design and fabrication methods and the mechanism of vibration, which is realized by controlling inlet pressure and harnessing a mechanical hysteresis. We demonstrate that the frequency and amplitude of vibration produced by our device can be varied based on changes in the input pressure, with 0.3 to 1.4 bar producing vibrations that range between 160 and 260 Hz at 13 to 38 g, the acceleration due to gravity. Our design allows for controllable vibrotactile feedback that is comparable in frequency and outperforms in amplitude relative to electromechanical actuators, yet has the compliance and conformity of fully soft wearable devices.