Feature Spacing Research Articles

Programmable adhesion through triangular and hierarchical cuts in metamaterial adhesives.

Metamaterial design approaches, which integrate structural elements into material systems, enable the control of uncommon behaviours by decoupling local and global properties. Leveraging this conceptual framework, metamaterial adhesives incorporate nonlinear cut architectures into adhesive films to achieve unique combinations of adhesion capacity, release, and spatial tunability by controlling how cracks propagate forward and in reverse directions during separation. Here, metamaterial adhesive designs are explored with triangular cut features while integrating hierarchical and secondary cut patterns among primary nonlinear cuts. Both cut geometry and secondary cut features tune adhesive force capacity and energy of separation. Importantly, the size and spacing of cut features must be designed around a critical length scale. When secondary cut features are greater than a critical length, cracks can be steered in multiple directions, going both forward and backwards within a primary attachment element. This control over crack dynamics enhances the work of separation by a factor of 1.5, while maintaining the peel force relative to a primary cut. If hierarchical cut features are too small or too compliant, they interact and do not distinctly modify crack behaviour. This work highlights the importance of adhesive length scales and stiffness for crack control and attachment characteristics in adhesive films.This article is part of the theme issue 'Origami/Kirigami-inspired structures: from fundamentals to applications'.

Unraveling the Geologic History of Miranda’s Inverness Corona

Miranda is the only icy body whose surface is known to contain the enigmatic features called corona—ovoid to trapezoidal areas of deformation. In this work, we seek to constrain potential formation mechanisms for Inverness Corona, the youngest known region on Miranda. To do this, we created the first detailed geologic map of Inverness, enabling the creation of a stratigraphic column of the order of events that formed this region. We employed a previously published Digital Elevation Model of the northern region of Inverness Corona to analyze the spacing of features in the region, which we propose to be extensional in origin. From this, we estimate an approximate brittle ice shell thickness of 2.5–3.8 km at the time of the region’s formation, indicating that Miranda’s brittle ice shell may have been relatively thin in the geologically recent past. We propose that Inverness formed from extension driven by a rising diapir or ice-shell thickening from a recent orbital resonance with Umbriel. The Uranus Orbiter and Probe mission is the highest priority flagship mission recommendation of the 2023–2032 Planetary Science and Astrobiology Decadal Survey. As such, we suggest measurements related to imaging, composition, gravity, and ice-shell thickness to gain an understanding of the geologic and orbital histories of the Uranian satellites, which would have implications for the evolution of the system as a whole.

Enhanced laser-induced damage performance ofall-glass metasurfaces for energetic pulsed laserapplications.

To fabricate optical components with surface layers compatible with high-power laser applications that may operate as antireflective coatings, polarization rotators, or harness physical anisotropy for other uses, metasurfaces are becoming an appealing candidate. In this study, large-beam (1.05cm diameter) 351-nm laser-induced damage testing was performed on an all-glass metasurface structure composed of cone-like features with a subwavelength spacing of adjacent features. These structures were fabricated on untreated fused silica glass and damage tested, as were structures that were fabricated on fused silica glass that experienced a preliminary etching process to remove the surface Beilby layer that is characteristic of polished fused silica. The laser-induced damage onset for structures on untreated fused silica glass was 19.3J⋅c m -2, while the sample that saw an initial pretreatment etch exhibited an improved damage onset of 20.4J⋅c m -2, only 6% short of the reference pretreated glass damage onset of 21.7J⋅c m -2. For perspective, the National Ignition Facility operational average fluence at this wavelength and pulse length is about 10J/c m 2. At a fluence of 25.5J⋅c m -2, the reference (pretreated) fused silica initiated 5.2 damage sites per m m 2, while the antireflective metasurface sample with a preliminary etching process treatment initiated 9.8 damage sites per m m 2. These findings demonstrate that substrate-engraved metasurfaces are compatible with high energy and power laser applications, further broadening their application space.

New estimates of pan-Arctic sea ice–atmosphere neutral drag coefficients from ICESat-2 elevation data

Abstract. The effect that sea ice topography has on the momentum transfer between ice and atmosphere is not fully quantified due to the vast extent of the Arctic and limitations of current measurement techniques. Here we present a method to estimate pan-Arctic momentum transfer via a parameterization that links sea ice–atmosphere form drag coefficients with surface feature height and spacing. We measure these sea ice surface feature parameters using the Ice, Cloud and land Elevation Satellite-2 (ICESat-2). Though ICESat-2 is unable to resolve as well as airborne surveys, it has a higher along-track spatial resolution than other contemporary altimeter satellites. As some narrow obstacles are effectively smoothed out by the ICESat-2 ATL07 spatial resolution, we use near-coincident high-resolution Airborne Topographic Mapper (ATM) elevation data from NASA's Operation IceBridge (OIB) mission to scale up the regional ICESat-2 drag estimates. By also incorporating drag due to open water, floe edges and sea ice skin drag, we produced a time series of average total pan-Arctic neutral atmospheric drag coefficient estimates from November 2018 to May 2022. Here we have observed its temporal evolution to be unique and not directly tied to sea ice extent. By also mapping 3-month aggregates for the years 2019, 2020 and 2021 for better regional analysis, we found the thick multiyear ice area directly north of the Canadian Archipelago and Greenland to be consistently above 2.0×10-3, while most of the multiyear ice portion of the Arctic is typically around ∼1.5×10-3.

The impact of yaw motion on the wake interaction of adjacent floating tidal stream turbines under free surface condition

Several works put emphasis on the maturation of floating tidal stream turbine systems, deemed viable for sites at deep water depths. The objective of this research is to determine, through a CFD model, the yaw effect on the wake and functioning of a floating twin-turbine system under wave-induced motion. The simulation certainty is corroborated against experiments on a 1:7 piled twin-turbine system (Froude similarity). Collectively, the variation and deficiency of the power and thrust coefficients are amplified with the yaw frequency and amplitude. Whereas the individual wakes collide, depending on the yaw feature and turbine cross-current spacing, resembling a smoke-plume-type pattern. The larger cross-current spacing shortens the wakes and reduces near-wake deficit at mid-row due to the greater energy exchange from the ambient flow. Regardless of the yaw feature, the transversal wake deficits turn from double (majority symmetrical) at near wake into triple distributions thenceforth, before flattening at far wake. Importantly, the wake unsteadiness and recovery rate are more obvious with period, as opposed to amplitude effect. As yaw operation is imminent, contributed by flow skewness and platform yaw motion, it will be constructive to implement natural frequency analysis to prevent vortex-induced vibrations and mechanical weariness in the floating system.

On the Fabrication of High-Performance Additively Manufactured Copper Winding Using Laser Powder Bed Fusion

Due to its exceptional electrical and thermal conductivity, pure copper is frequently employed in industry as the base metal for thermal management and electromagnetic applications. The growing need for complicated and efficient motor designs has recently accelerated the development of copper additive manufacturing (AM). The present work aims to improve the power density of the copper laser powder bed fusion (Cu-LPBF) coil by increasing the slot-filling factor (SFF) and the electrical conductivity. Firstly, the dimensional limitation of Cu-LPBF fabricated parts was identified. Sample contouring and adjusting beam offset associated with optimum scan track morphology upgraded the minimum feature spacing to 80 μm. Accordingly, the printed winding’s slot-filling factor increased to 79% for square wire and 63% for round wire. A maximum electrical conductivity of 87% (IACS) was achieved by heat treatment (HT). The electrical impedance of full-size Cu-LPBF coils, newly reported in this study, was measured and compared with solid wire. It can reflect the performance of Cu-LPBF coils (power factor) in high-frequency applications. Furthermore, surface quality benefited from either sample contouring and HT, where the side surface roughness was lowered by 45% and an additional reduction of 25% after HT.

Influence of Surface Texturing on the Dry Tribological Properties of Polymers in Medical Devices.

There is a constant need to improve patient comfort and product performance associated with the use of medical devices. Efforts to optimise the tribological characteristics of medical devices usually involve modifying existing devices without compromising their main design features and functionality. This article constitutes a state-of-the-art review of the influence of dry friction on polymeric components used in medical devices, including those having microscale surface features. Surface tribology and contact interactions are discussed, along with alternative forms of surface texturing. Evident gaps in the literature, and areas warranting future research are highlighted; these include friction involving polymer Vs polymer surfaces, information regarding which topologies and feature spacings provide the best performing textured surfaces, and design guidelines that would assist manufacturers to minimise or maximise friction under non-lubricated conditions.

Recognition of Occluded Goods under Prior Inference Based on Generative Adversarial Network.

Aiming at the recognition of intelligent retail dynamic visual container goods, two problems that lead to low recognition accuracy must be addressed; one is the lack of goods features caused by the occlusion of the hand, and the other is the high similarity of goods. Therefore, this study proposes an approach for occluding goods recognition based on a generative adversarial network combined with prior inference to address the two abovementioned problems. With DarkNet53 as the backbone network, semantic segmentation is used to locate the occluded part in the feature extraction network, and simultaneously, the YOLOX decoupling head is used to obtain the detection frame. Subsequently, a generative adversarial network under prior inference is used to restore and expand the features of the occluded parts, and a multi-scale spatial attention and effective channel attention weighted attention mechanism module is proposed to select fine-grained features of goods. Finally, a metric learning method based on von Mises-Fisher distribution is proposed to increase the class spacing of features to achieve the effect of feature distinction, whilst the distinguished features are utilized to recognize goods at a fine-grained level. The experimental data used in this study were all obtained from the self-made smart retail container dataset, which contains a total of 12 types of goods used for recognition and includes four couples of similar goods. Experimental results reveal that the peak signal-to-noise ratio and structural similarity under improved prior inference are 0.7743 and 0.0183 higher than those of the other models, respectively. Compared with other optimal models, mAP improves the recognition accuracy by 1.2% and the recognition accuracy by 2.82%. This study solves two problems: one is the occlusion caused by hands, and the other is the high similarity of goods, thus meeting the requirements of commodity recognition accuracy in the field of intelligent retail and exhibiting good application prospects.

Microscale Templating of Materials across Electrospray Deposition Regimes

Electrospray deposition (ESD) uses strong electric fields to produce generations of monodisperse droplets from solutions and dispersions that are driven toward grounded substrates. When soft materials are delivered, the behavior of the growing film depends on the film’s ability to dissipate charge, which is strongly tied to its mobility for dielectric materials. Accordingly, there exist three regimes of electrospray: electrowetting, charged melt, and self-limiting. In the self-limiting regime, it has been recently shown that the targeted nature of these sprays allows for corona-free 3D coating. While ESD patterning on the micron-scale has been studied for decades, most typically through the use of insulating masks, there has been no comparative study of this phenomenon across spray regimes. Here, we used test-patterns composed of gratings that range in both feature size (30–240 μm) and spacing (⅓x–9x) to compare materials across regimes. The sprayed patterns were scanned using a profilometer, and the density, average height, and specificity were extracted. From these results, it was demonstrated that material deposited in the self-limiting regime showed the highest uniformity and specificity on small features as compared to electrowetting and charged melt sprays. Self-limiting electrospray deposition is, therefore, the best suited for modification of prefabricated electrode patterns.

A new and versatile template towards vertically oriented nanopillars and nanotubes.

Vertically oriented nanostructures bring unparalleled high surface area, light trapping capability, and high device density to electronic, optoelectronic, and energy storage devices. However, general methods to prepare such structures remain sparse and are typically based on anodized metal oxide templates. Here, we demonstrate a new approach: using vertically oriented tetraaniline nanopillar arrays as templates for creating nanopillars and nanotubes of other materials. The tetraaniline templates are scalable and easy to prepare. Vertical arrays of a variety of materials can be created by directly coating them onto the tetraaniline nanopillars via vapor, solution, or electrodeposition. Since the tetraaniline template is encased within the target material, it does not require post-deposition removal, thus enabling vertical structure formation of sensitive materials. Conversely, removal of the encased tetraaniline template provides vertically oriented nanotube arrays in a lost-wax-type operation. The resulting vertical structures exhibit a high degree of orientation and height uniformity, with tunable feature size, spacing, and array density. Furthermore, the deposition location and shape of the vertical arrays can be patterned at a resolution of 3 μm. Collectively, these attributes should broaden the material repertoire for vertically oriented structures, and lead to advancements in energy storage, electronics, and optoelectronics.

Configural properties of face portraits change between childhood and adulthood

Adult observers are sensitive to the configuration of facial features within a face, able to distinguish between relative differences in feature spacing, and detecting deviations from typical facial appearance. How does the representation of the typical configuration of facial features develop? While there is a great deal of work describing children’s developing abilities to detect differences in feature spacing across face images, there is substantially less work examining what children think constitutes a typical arrangement of facial features. In the current study, we investigated this issue using a production task in which adults and 5- to 10-year-old children created a face “portrait” by arranging the eyes, nose, and mouth of a standard face within an empty outline. Using this simple task, we found differences in face configuration across age groups, such that children of all ages made far larger errors than adult participants, expanding facial features outward from the center of the face more than adults. These results were not affected by face inversion, potentially implying a domain-general rather than face-specific process. We also found that children of all ages endorsed the correct configuration as a best likeness in a perceptual task. We discuss these results in terms of ongoing debate regarding the extent to which configural processing is a meaningful component of face recognition and the conclusions we can draw from production paradigms as compared to purely perceptual tasks.

High-Throughput Biofilm Assay to Investigate Bacterial Interactions with Surface Topographies

The specific topography of biomaterials plays an important role in their biological interactions with cells and thus the safety of medical implants. Antifouling materials can be engineered with topographic features to repel microbes. Meanwhile, undesired topographies of implants can cause complications such as breast implant-associated anaplastic large cell lymphoma (BIA-ALCL). While the cause of BIA-ALCL is not well understood, it is speculated that textured surfaces are prone to bacterial biofilm formation as a contributing factor. To guide the design of safer biomaterials and implants, quantitative screening approaches are needed to assess bacterial adhesion to different topographic surface features. Here we report the development of a high-throughput microplate biofilm assay for such screening. The assay was used to test a library of polydimethylsiloxane (PDMS) textures composed of varying sizes of recessive features and distances between features including those in the range of breast implant textures. Outliers of patterns prone to bacterial adhesion were further studied using real-time confocal fluorescence microscopy. The results from these analyses revealed that surface area itself is a poor predictor for adhesion, while the size and spacing of topographic features play an important role. This high-throughput biofilm assay can be applied to studying bacteria–material interactions and rational development of materials that inhibit bacterial colonization.

Mechanically switchable micro-patterned adhesive for soft material applications

Many switchable adhesives controlled by an external stimulus have been developed for interaction with effectively rigid materials, e.g., in silicon wafer processing and wall climbing robots. However, applications such as medical devices and automated food handling demand switchable adhesives for soft materials. In this work, we apply equibiaxial tensile strain to an elastomeric micro-patterned surface to modulate its adhesion with both rigid and soft materials. First, we measure the geometric changes of frustum-shaped features on the micro-patterned surface under varying applied equibiaxial strains. We then experimentally characterize adhesion of the equibiaxially strained micro-patterned surface in contact with rigid and soft spherical probes. Experimental results show that the applied strain on the micro-patterned surface can substantially influence its adhesion behavior with both the rigid and soft probes. However, the underlying mechanism is different. For the rigid probe, the dominating mechanism is that the applied strain reduces the system compliance by decreasing the backing layer thickness of the micro-patterned surface. For the soft probe, the primary role of the applied strain is to influence the true contact area by changing the shape and spacing of the frustum-shaped features. Finally, we demonstrate the elastomeric micro-patterned surface as a switchable adhesive gripper for both soft and rigid objects.

Initial Fault Diagnosis of Rolling Bearing Based on Second-Order Cyclic Autocorrelation and DCAE Combined With Transfer Learning

Under actual working conditions, the initial faults of rolling bearings are difficult to be predicted effectively because of the lack of prior fault knowledge, weak fault information, and strong noise interference. How to enhance the fault characteristics while removing the vibration signal noise of rolling bearings has become the key challenge to the field of early fault diagnosis of rolling bearings. Based on the above problems, a rolling bearing initial fault diagnosis model based on second-order cyclic autocorrelation (Soca) and deep auto-encoder (AE) combined with transfer learning (TL) was proposed to improve the overall performance of rolling bearing fault identification. First, the Soca is used to estimate the second-order cyclic statistics of the vibration signal, which can better highlight the periodic pulse characteristics of rolling bearings and suppress random noise to a certain extent. After that, the dataset containing the valuable health state information of the rolling bearing is input into the denoising and contraction auto-encoder (DCAE). The advantages of denoising AEs (DAEs) and contraction AEs are fully utilized to extract the initial fault characteristics of rolling bearings. Finally, the balanced distribution adaptation (BDA) is used to reduce the distribution difference and class spacing of the transferable features extracted from the original datasets and the target datasets, and the initial fault diagnosis of the target rolling bearing is diagnosed according to the feature knowledge of the source rolling bearing. In three experimental datasets, six TL experiments were carried out to verify that the Soca-Denoising auto-encoder, Contraction auto-encoder and Transfer learning (DCT) model can effectively enhance the initial fault characteristics of rolling bearings, and has higher diagnostic accuracy and robustness compared with the existing initial fault diagnosis methods of rolling bearings. This method has a good application prospect in the field of early fault diagnosis of rolling bearings.

Flexible Inserts for Injection Molding of Complex Micro‐Structured Polymer Components

AbstractMass production of microfluidic devices commonly relies on injection molding. Injection molding requires a master surface made using micro or nanofabrication. Conventionally, electroplating from a silicon master is used for mold insert production, but this is expensive and cannot be used with masters produced via the Bosch process as interlocking of the scalloping between polymer and metal insert hinders part ejection. Here, an alternative to the electroplating process is developed by adapting a nanoimprint route to produce flexible micro‐structured polymer inserts capable of molding using a Bosch process‐produced master. An optimized fabrication approach using silicon masters with smooth sidewalls (produced using the mixed process) is used to characterize the limits of the process. Aspect ratios of 1 and below are successfully replicated. Feature spacings down to 20 µm are successfully produced with minimal variation between repeated parts. Masters produced using two different Bosch etches exhibiting both coarse and fine nanometer scalloping are also studied. Parts are successfully ejected with retained nanometer scalloping in all samples although inlay damage occurred after >10 replicas. A proof‐of‐concept microfluidic device is successfully produced vindicating the use of this approach as an efficient and cost‐effective approach for the rapid prototyping of complex micro‐structured designs.

Optimization and Control of Large Block Copolymer Self-Assembly via Precision Solvent Vapor Annealing.

The self-assembly of ultra-high molecular weight (UHMW) block copolymers (BCPs) remains a complex and time-consuming endeavor owing to the high kinetic penalties associated with long polymer chain entanglement. In this work, we report a unique strategy of overcoming these kinetic barriers through precision solvent annealing of an UHMW polystyrene-block-poly(2-vinylpyridine) BCP system (Mw: ∼800 kg/mol) by fast swelling to very high levels of solvent concentration (ϕs). Phase separation on timescales of ∼10 min is demonstrated once a thickness-dependent threshold ϕs value of ∼0.80–0.86 is achieved, resulting in lamellar feature spacings of over 190 nm. The threshold ϕs value was found to be greater for films with higher dry thickness (D0) values. Tunability of the domain morphology is achieved through controlled variation of both D0 and ϕs, with the kinetically unstable hexagonal perforated lamellar (HPL) phase observed at ϕs values of ∼0.67 and D0 values of 59–110 nm. This HPL phase can be controllably induced into an order–order transition to a lamellar morphology upon further increase of ϕs to 0.80 or above. As confirmed by grazing-incidence small-angle X-ray scattering, the lateral ordering of the lamellar domains is shown to improve with increasing ϕs up to a maximum value at which the films transition to a disordered state. Thicker films are shown to possess a higher maximum ϕs value before transitioning to a disordered state. The swelling rate is shown to moderately influence the lateral ordering of the phase-separated structures, while the amount of hold time at a particular value of ϕs does not notably enhance the phase separation process. These large period self-assembled lamellar domains are then employed to facilitate pattern transfer using a liquid-phase infiltration method, followed by plasma etching, generating ordered, high aspect ratio Si nanowall structures with spacings of ∼190 nm and heights of up to ∼500 nm. This work underpins the feasibility of a room-temperature, solvent-based annealing approach for the reliable and scalable fabrication of sub-wavelength nanostructures via BCP lithography.

Evolution and applications of polymer brush hypersurface photolithography

Hypersurface photolithography creates arbitrary polymer brush patterns with independent control over feature diameter, height, and spacing between features, while controlling composition along a polymer chain and between features.

Generation of Surfaces With Isotropic and Anisotropic Wetting Properties by Curved Water Jet-Guided Laser Micromachining

Abstract This experimental work utilizes a newly developed method, curved water jet-guided laser micromachining, to generate microfeatures on metallic surfaces. During the process, material is removed by a high-power nanosecond laser beam, which is transmitted through a high-pressure microwater jet via total internal reflection. To achieve intricate texturing patterns, a secondary motion component is superimposed on the XY motion of the workpiece provided by the motion stage. The secondary motion is generated by deflecting the water jet trajectory by a controllable dielectrophoretic force. The induced secondary motion of the water jet cuts the processing time to one half when generating texture patterns for isotropic wetting as compared to processes with only XY motion. The ability to alter the water jet's trajectory by tens of microns at high frequencies, which is beyond the capability of conventional CNC machines, allows a wide range of different micropatterns to be generated, profoundly increasing the flexibility and efficiency of the process as compared to conventional approaches. As a demonstration, surface textures for isotropic and anisotropic behaviors are generated on stainless steel surfaces. The influence of feature spacing, motion speed (frequency), and texturing patterns on surface wettability is studied.

Experimental design for CO2 laser cutting of sub-millimeter features in very large-area carbon nanotube sheets

In this work, laser cutting methodologies have been demonstrated for defining submillimeter features in commercially available carbon nanotube (CNT) sheet materials (24 and 74-µm thick) using a commercial CO2 laser source with a maximum power output of 30 W. Full factorial and central composite designs of experiments were used to investigate the effect of various factors, including the laser power (10–90% of max), speed (10–90% of max), and pulses per inch (100–1000 PPI), on the resulting kerf width and the kerf width variation for 5 mm long single straight-line features. Maximizing the pulses per inch yielded laser cuts with reduced variability, while the power and speed were determined to be the significant factors affecting the kerf width. Fabrication of more complex grid structures, consisting of 100 square openings (0.838 mm wide), revealed that the conditions used for cutting straight lines were insufficient for cutting grids. Thus, for a fixed number of pulses-per-inch, the ratio of the values of power and speed, P/S ratio, was determined to be most significant for affecting the feature quality of these grid structures, as it determines the heat input energy and the delivered energy density. It was determined that, for a fixed PPI of 1000, a percent power value 1.6 × higher than the percent speed value was needed as the input parameter to cut the 24 µm thick CNT sheet, and a percent power value 3.5 × higher than the percent speed value was required to successfully cut the 74 µm thick CNT sheet. Ultimately, refinement in the laser cutting conditions by increasing the energy delivered per pulse and using two passes to account for sheet non-uniformities, enabled patterning of large area (up to 280 mm × 280 mm) CNT sheets with close-packed circles. A structure of this size has over 48,000 openings, and analysis via optical microscopy determined the features have a measured diameter of 0.78 mm ± 0.01 mm, exhibiting reproducibility over the entire CNT sample. Finally, multiple intricate geometries with variable feature spacing were fabricated all on a single CNT sample, demonstrating the utility of laser machining as an alternative technology solution to traditional CNT patterning techniques. These results provide a scalable methodology to determine the laser cutting parameters for use in fabricating very large-area CNT structures with intricate features.

Guess who? Facial identity discrimination training improves face memory in typically developing children.

While vast individual differences in face recognition have been observed in adults, very little work has explored when these differences come online during development, their domain specificity, and their consistency across different aspects of face processing. These issues do not only have important theoretical implications for the cognitive and developmental psychological literatures, but may reveal critical windows of neuroplasticity for optimal remediation of face recognition impairments. Here, we describe the first formal remedial face training program that is suitable for children, modifying the popular game Guess Who. Eighty-one typical children Aged 4-11 years were randomly allocated to an experimental or active control training condition. Over 10 training sessions, experimental participants were required to discriminate between faces that differed in feature size or spacing across 10 levels of difficulty, whereas control participants continuously played the standard version of Guess Who within the same timeframe. Improvements in face memory but not face matching were observed in the experimental compared to the control group, but there were no gains on tests of object matching or memory. Face memory gains were maintained in a 1-month follow up, consistent across age, and larger for poorer perceivers. Thus, this study not only presents a promising means of improving face recognition skills in children, but also indicates a consistent period of plasticity that spans early childhood to preadolescence, implying early segregation of face versus object processing. (PsycInfo Database Record (c) 2020 APA, all rights reserved).