Controlling surface wettability and liquid spreading on patterned surfaces is of significant interest for a broad range of applications, including DNA microarrays, digital lab-on-a-chip, anti-fogging and fog-harvesting, inkjet printing and thin-film lubrication. Advancements in surface engineering, with the fabrication of various micro/nanoscale topographic features, and selective chemical patterning on surfaces, have enhanced surface wettability and enabled control of the liquid film thickness and final wetted shape. In addition, groove geometries and patterned surface chemistries have produced anisotropic wetting, where contact-angle variations in different directions resulted in elongated droplet shapes. In all of these studies, however, the wetting behaviour preserves left-right symmetry. Here, we demonstrate that we can harness the design of asymmetric nanostructured surfaces to achieve uni-directional liquid spreading, where the liquid propagates in a single preferred direction and pins in all others. Through experiments and modelling, we determined that the spreading characteristic is dependent on the degree of nanostructure asymmetry, the height-to-spacing ratio of the nanostructures and the intrinsic contact angle. The theory, based on an energy argument, provides excellent agreement with experimental data. The insights gained from this work offer new opportunities to tailor advanced nanostructures to achieve active control of complex flow patterns and wetting on demand.

Enhancing condensation heat transfer is important for broad applications from power generation to water harvesting systems. Significant efforts have focused on easy removal of the condensate, yet the other desired properties of low contact angles and high nucleation densities for high heat transfer performance have been typically neglected. In this work, we demonstrate immersion condensation on oil-infused micro and nanostructured surfaces with heterogeneous coatings, where water droplets nucleate immersed within the oil. The combination of surface energy heterogeneity, reduced oil-water interfacial energy, and surface structuring enabled drastically increased nucleation densities while maintaining easy condensate removal and low contact angles. Accordingly, on oil-infused heterogeneous nanostructured copper oxide surfaces, we demonstrated approximately 100% increase in heat transfer coefficient compared to state-of-the-art dropwise condensation surfaces in the presence of non-condensable gases. This work offers a distinct approach utilizing surface chemistry and structuring together with liquid-infusion for enhanced condensation heat transfer.

Prediction and optimization of liquid propagation rates in micropillar arrays are important for various lab-on-a-chip, biomedical, and thermal management applications. In this work, a semianalytical model based on the balance between capillary pressure and viscous resistance was developed to predict liquid propagation rates in micropillar arrays with height-to-period ratios greater than 1 and diameter-to-period ratios less than 0.57. These geometries represent the most useful regimes for practical applications requiring large propagation rates. The capillary pressure was obtained using an energy approach where the meniscus shape was predicted using Surface Evolver simulations and experimentally verified by interference microscopy. The combined viscous resistance of the pillars and the substrate was determined using Brinkman's equation with a numerically obtained permeability and corroborated with finite element simulations. The model shows excellent agreement with one-dimensional propagation experiments of deionized water in silicon micropillar arrays, highlighting the importance of accurately capturing the details of the meniscus shape and the viscous losses. Furthermore, an effective propagation coefficient was obtained through dimensionless analysis that is functionally dependent only on the micropillar geometry. The work offers design guidelines to obtain optimal liquid propagation rates on micropillar surfaces.

Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals generated by the human brain and translates them into control signals to control external devices, e.g., wheelchairs. One problem challenging noninvasive BCI technologies is the limited control dimensions from decoding movements of, mainly, large body parts, e.g., upper and lower limbs. It has been reported that complicated dexterous functions, i.e., finger movements, can be decoded in electrocorticography (ECoG) signals, while it remains unclear whether noninvasive electroencephalography (EEG) signals also have sufficient information to decode the same type of movements. Phenomena of broadband power increase and low-frequency-band power decrease were observed in EEG in the present study, when EEG power spectra were decomposed by a principal component analysis (PCA). These movement-related spectral structures and their changes caused by finger movements in EEG are consistent with observations in previous ECoG study, as well as the results from ECoG data in the present study. The average decoding accuracy of 77.11% over all subjects was obtained in classifying each pair of fingers from one hand using movement-related spectral changes as features to be decoded using a support vector machine (SVM) classifier. The average decoding accuracy in three epilepsy patients using ECoG data was 91.28% with the similarly obtained features and same classifier. Both decoding accuracies of EEG and ECoG are significantly higher than the empirical guessing level (51.26%) in all subjects (p<0.05). The present study suggests the similar movement-related spectral changes in EEG as in ECoG, and demonstrates the feasibility of discriminating finger movements from one hand using EEG. These findings are promising to facilitate the development of BCIs with rich control signals using noninvasive technologies.

Responsive actuating surfaces have attracted significant attention as promising materials for liquid transport in microfluidics, cell manipulation in biological systems, and light tuning in optical applications via their dynamic regulation capability. Significant efforts have focused on fabricating static micro and nanostructured surfaces, [1,2,3,4,5] even with asymmetric features to realize passive functionalities such as directional wettability [6,7] and adhesion. [8,9] Only recent advances in utilizing materials that mechanically respond to thermal, [10,11,12,13] chemical [14,15,16,17] or magnetic [18,19,20,21,22,23] stimuli have enabled dynamic regulation.However the challenges with these surface designs are associated with the tuning range, [19,20] accuracy, [19,20,21,22,23] response time [10,11,12,13,15,16,17] and multi-functionality for advanced systems. Here we report dynamically tunable micropillar arrays with uniform, reversible, continuous and extreme tilt angles with precise control for real-time fluid and optical manipulation. Inspired by hair and motile cilia on animal skin and plant leaves for locomotion, [24] liquid transportation [25] and thermal-optical regulation, [26,27] our flexible uniform responsive microstructures (µFUR) consist of a passive thin elastic skin and active ferromagnetic microhair whose orientation is controlled by a magnetic field. We experimentally show uniform tilt angles ranging from 0° to 57°, and developed a model to accurately capture the tilting behavior. Furthermore, we demonstrate that the µFUR can control and change liquid spreading direction on demand, manipulate fluid drag, and tune optical transmittance over a large range. The versatile surface developed in this work enables 2 new opportunities for real-time fluid control, cell manipulation, drag reduction and optical tuning in a variety of important engineering systems, including applications that require manipulation of both fluid and optical functions.Dynamically tunable structured surfaces offer new manipulation capabilities in mechanical, fluidic, and optical systems. Examples from nature have inspired the design of such active systems: bacteria use flagella as propellers [24] and motile cilia in the lining of human respiratory airways move mucus and dirt out of the lungs. [25] These biological systems display well-defined structural patterns and controllable mechanical motion in response to different stimuli. Accordingly, researchers have investigated various approaches to fabricate tunable microstructures including temperature-sensitive liquid crystalline [13] and thermoplastic elastomers, [10] hydrogels that respond to thermal, chemical or optical stimuli, [11,12,14,15,16,17] and polymer-based magnetically actuated structures [18,19,20,21,22,23] over the past decade. However, the response of the thermally actuated elastomer is either irreversible [10] or slow [13] and the hydrogels require a liquid environment and have a long response time, thus limiting their applications.Magnetically actuated surfaces,...

We present a nanoporous membrane-based approach, which decouples the capillary pressure from the viscous resistance, to achieve high driving pressures and efficient liquid delivery for thin film evaporation. By using alumina membranes with ≈150 nm pore diameters, absolute liquid pressures as low as −300 kPa were achieved using isopropyl alcohol, while dissipating maximum interfacial heat fluxes of ≈96 W/cm2. Design guidelines are provided to achieve higher interfacial heat fluxes with reduced membrane thicknesses. This work shows a promising approach to address thermal management needs for next generation electronic devices.

Existing research in infants has correlated electroencephalography (EEG) measures of power and coherence to cognitive development and to locomotor experience, but only in infants older than 5 months of age. Our goal was to explore the relationship between EEG measures of power and coherence and motor skill development in younger infants who are developing reaching skill. Twenty-one infants with typical development between 38 and 203 days of age participated. Longitudinal EEG recording sessions were recorded in monthly increments, with 3–5 sessions acquired for 19 participants and 1 session for 2 participants, resulting in 71 sessions in total. EEG variables of interest were relative power in the 6–9 Hz range and coherence between selected electrode pairs. We describe the development of the peak in relative power in the 6–9 Hz frequency band of EEG; it is not present around 1 month of age and starts to appear across the following months. Coherence generally increased in the bilateral frontal-parietal networks, while the interhemispheric connectivity in motor cortices generally decreased. The results of this relatively small pilot study provide a foundational description of neural function changes observed as motor skills are changing across the first half year of life. This is a first step in understanding experience-dependent plasticity of the infant brain and has the potential to aid in the early detection of atypical brain development.

Liquid dynamics in micropillar arrays have received significant fundamental interest and have offered opportunities for the development of advanced microfluidic, thermal management, and energy-harvesting devices. However, a comprehensive understanding of complex liquid behavior and the effect on macroscopic propagation rates in micropillar arrays is needed. In this work, we investigated the microscopic sweeping behavior of the liquid front along the spreading direction in micropillar arrays where the sweeping distance scales with the one-fifth power of time. We explain the scaling with a simplified model that captures the capillary pressure gradient at the liquid front. Furthermore, we show that such microscopic dynamics is the mechanism that decreases the macroscopic propagation rate. This effect is a result of the reduction in the interfacial energy difference used to generate the capillary pressure, which is explained with an energy-based model and corroborated with experiments. The results indicate the importance of accounting for the microscopic dynamics of the liquid on microstructured surfaces, particularly in sparse geometries.