Arbitrary Shape Research Articles

Conformal Low Temperature Molecular Layer Deposited Coatings as Interface Modifications to Support Ceramic Protective Films on Macroscopic Flexible Devices

Flexible devices often need a protective coating when operating in harmful environments, ranging from mild ambient conditions to a biologically active environment of the human body. The flexibility poses a problem for traditional encapsulation solutions, as those make the device bulky and limit functionality by applying an external casing. Alternatively, fully conformal encapsulation of a device of arbitrary shape can be realized with thin film encapsulation (TFE) without altering device dimensions. Yet TFE is susceptible to fail under mechanical stresses, especially when a hard ceramic coating is applied on a polymer. Reliability of TFE can be enhanced by altering the elasticity of the hard and brittle thin films, by adding softer layers in between sample and barrier. In this work, molecular layer deposited (MLD) metal‐linked trioxysilylheptanoate (M‐TOSH) films are studied for coating of large devices to conformally and uniformly tune the interface between polymer and atomic layer deposited protective film. The results show that M‐TOSH process scales to large chambers, parameter optimization leads to superior film quality and lowers elastic modulus. Conformality, tested with home‐built macroscopic test device, found the process suitable for 3D parts. Final testing revealed that 10 cycles of MLD‐interlayer doubled the crack‐onset‐strain from 0.26% to 0.51%.This article is protected by copyright. All rights reserved.

Three-dimensional flow around and through a porous screen

We investigate the three-dimensional (3-D) flow around and through a porous screen for various porosities at high Reynolds number $Re = {O}(10^4)$ . Historically, the study of this problem has been focused on two-dimensional cases and for screens spanning completely or partially a channel. Since many recent problems have involved a porous object in a 3-D free flow, we present a 3-D model initially based on Koo & James (J. Fluid Mech., vol. 60, 1973, pp. 513–538) and Steiros & Hultmark (J. Fluid Mech., vol. 853, 2018 pp. 1–11) for screens of arbitrary shapes. In addition, we include an empirical viscous correction factor accounting for viscous effects in the vicinity of the screen. We characterize experimentally the aerodynamic drag coefficient for a porous square screen composed of fibres, immersed in a laminar air flow with various solidities and different angles of attack. We test various fibre diameters to explore the effect of the space between the pores on the drag force. Using PIV and hot wire probe measurements, we visualize the flow around and through the screen, and in particular measure the proportion of fluid that is deviated around the screen. The predictions from the model for drag coefficient, flow velocities and streamlines are in good agreement with our experimental results. In particular, we show that local viscous effects are important: at the same solidity and with the same air flow, the drag coefficient and the flow deviations strongly depend on the Reynolds number based on the fibre diameter. The model, taking into account 3-D effects and the shape of the porous screen, and including an empirical viscous correction factor that is valid for fibrous screens may have many applications including the prediction of water collection efficiency for fog harvesters.

Restoration Temperature Control through Glass Transition Temperature Modulation of Shape Memory Polymer for Thermally Switchable Adhesive.

Shape memory polymers (SMPs) undergo changes between arbitrary shapes and programmed shapes upon exposure to specific stimulus, allowing them to restore their original shape. All kinds of external stimuli have a threshold to change the shape of the SMP. Especially, for the thermal type SMP, the critical temperature for shape restoration is typically near the glass transition temperature (Tg). In this study, the controllability of the restoration temperature is analyzed by adjusting the Tg of the polymer using Norland Optical Adhesive 63, which can be cured with UV irradiation. By varying the ambient temperature from 20 to 120°C during UV exposure, Tg changes ranging from 35.84 to 50.50°C are obtained, with corresponding changes in restoration temperature. As a practical application, a thermal-activated SMP dry adhesive is developed with programmable Tg and switchable adhesion. The fabricated SMP dry adhesive exhibited strong adhesion to substrates with various surface roughness. Additionally, the shape memory effect allowed for easy detachment through shape recovery, and different adhesive performances at different temperatures are achieved by programming various Tg values. Moreover, the simple manufacturing process of the SMP dry adhesive is confirmed to be suitable for continuous fabrication processes based on roll-to-roll methods.

K-Space Approach in Optical Coherence Tomography: Rigorous Digital Transformation of Arbitrary-Shape Beams, Aberration Elimination and Super-Refocusing beyond Conventional Phase Correction Procedures.

For the most popular method of scan formation in Optical Coherence Tomography (OCT) based on plane-parallel scanning of the illuminating beam, we present a compact but rigorous K-space description in which the spectral representation is used to describe both the axial and lateral structure of the illuminating/received OCT signals. Along with the majority of descriptions of OCT-image formation, the discussed approach relies on the basic principle of OCT operation, in which ballistic backscattering of the illuminating light is assumed. This single-scattering assumption is the main limitation, whereas in other aspects, the presented approach is rather general. In particular, it is applicable to arbitrary beam shapes without the need for paraxial approximation or the assumption of Gaussian beams. The main result of this study is the use of the proposed K-space description to analytically derive a filtering function that allows one to digitally transform the initial 3D set of complex-valued OCT data into a desired (target) dataset of a rather general form. An essential feature of the proposed filtering procedures is the utilization of both phase and amplitude transformations, unlike conventionally discussed phase-only transformations. To illustrate the efficiency and generality of the proposed filtering function, the latter is applied to the mutual transformation of non-Gaussian beams and to the digital elimination of arbitrary aberrations at the illuminating/receiving aperture. As another example, in addition to the conventionally discussed digital refocusing enabling depth-independent lateral resolution the same as in the physical focus, we use the derived filtering function to perform digital "super-refocusing." The latter does not yet overcome the diffraction limit but readily enables lateral resolution several times better than in the initial physical focus.

The synergy mechanism of CsSnI3 and LiTFSI enhancing the electrochemical performance of PEO‐based solid‐state batteries

AbstractLithium metal solid‐state battery is the first choice of batteries for electromobiles and consumer electronic products because of the specific capacity of 3860 mAh g−1 and high electrochemical potential (−3.04 V) of Li metal. Flexible polymer solid electrolytes have become the optimal solution to produce high energy density lithium batteries with arbitrary size and shape. In this work, we introduce a halide perovskite, CsSnI3, into the polyethylene oxide/lithium bis‐(trifluoromethanesuphone)imide (PEO–LiTFSI) polymer matrix. The CsSnI3 could form a LixSn alloy with Li, leading to homogenization of the electric field and Li+‐flux at the interface, Sn atom also bonds with the TFSI− anion to provide more dissociated Li+. Besides that, the I atom could interact with Li to form an electronic insulation with a strong blocking effect on electron tunneling. As a proof of concept, the synergy mechanism of the PEO–LiTFSI–CsSnI3 electrolyte improves the stable cycle life of the symmetric battery to more than 500 h, and the Li+ conductivity raised to 6.1 × 10−4 S cm−1 at 60°C. The application of the “zwitter ions analog” halide perovskite in PEO–LiTFSI provides a new choice among various methods to improve the electrochemical performance of polymer solid‐state batteries.

Dynamic response of bored piles with gradient defects during low strain integrity test

With the proposal of the gradient ring-soil pile model, the possibility of utilizing the low strain integrity test for identifying gradient defects of the bored piles embedded in unsaturated soil is confirmed. The gradient ring-soil pile model realizes the simulation of soil-pile interaction at the soil-pile interfaces with arbitrary shapes in the horizontal projection. Compared to existing theoretical answers, this paper extends the low strain test theory to the identification of gradient defects. With the adoption of the Laplace transform, differential operator decomposition theory, variable separation method, and impedance function transfer method, a semi-analytical solution is derived. Taking advantage of the semi-analytical solution, a parametric study is conducted to analyze the variation of the defect shapes on the test signal of the bored pile. Based on the findings, a series of methods for identifying gradient defects in engineering applications are summarized. The main findings can be summarized as follows: 1. The soil filled in the gradient necking defects would significantly decrease the magnitudes of reflected signals at these defects, making them more challenging to be identified; 2. If simply modeling the gradient defects as sudden defects, the severity of defects can be underestimated, resulting in the overestimation of pile capacity; 3. The shape of the gradient defect, as well as the length of the gradient defect, has a significant influence on the reflected signal.

Connection density based clustering: A graph-based density clustering method

In this paper, a graph-based density clustering framework is proposed that detects the boundary points of clusters rather than cluster exemplars in high density regions. The framework introduces the connection density to measure the density relationship between points, which depends on both a density metric and a distance metric, and a weighted graph is constructed based on the connection density. By cutting off edges with low connection density, points located at the boundary region become isolated points from the rest of the weighted graph, and each connected subgraph forms an initial cluster. For the generated isolated points, a graph-based label propagation strategy is designed, the stable point in initial clusters with higher connection density with an isolated point preferentially propagate labels. Finally, a novel connection density based clustering algorithm is proposed, called CDBC, which can automatically identify clusters of arbitrary shapes. The experimental results show that the proposed method outperforms other advanced clustering algorithms on several synthetic and real-world datasets.

DPC-DNG: Graph-based label propagation of [formula omitted]-nearest higher-density neighbors for density peaks clustering

Density peaks clustering (DPC) algorithm is a novel density-based clustering approach that effectively determines cluster centers from a decision graph and groups objects by assigning non-center objects to the same cluster as their nearest higher-density neighbor. Although DPC can allocate clusters of arbitrary shapes, its single-chain label propagation mechanism has the risk of “chain error”, where an object assigned an incorrect label causes its subordinates to also be assigned the same incorrect label. Hence, DPC is unable to effectively group objects that are located in overlapping areas between clusters, which leads to unsatisfactory clustering results. To address this issue, this study proposes the graph-based label propagation of k-nearest higher-density neighbor for density peaks clustering (DPC-DNG). DPC-DNG extends the single-chain label propagation of DPC to a graph-based multi-chain label propagation that assigns labels to objects from their k-nearest higher-density neighbors. First, based on k-nearest higher-density neighbors and the selected cluster centers, a symmetric density-based neighbor graph (DNG) is constructed. Second, to assign labels to objects, a classic graph-based label propagation mechanism is utilized in conjunction with DNG. To validate our method, we carry out comprehensive experiments on 6 synthetic and 12 real datasets. Statistically speaking, the results show that our method has improved the clustering performance of DPC and exhibits promising performance over other state-of-the-art DPC-related methods.

OrganL: Dynamic triangulation of biomembranes using curved elements

We describe a method for simulating biomembranes of arbitrary shape. In contrast to other dynamically triangulated surface (DTS) algorithms, our method provides a rich, quasi-tangent-continuous, yet local description of the surface. We use curved Nagata triangles, which we generalize to cubic order to achieve the requisite flexibility. The resulting interpolation can be constructed locally without iterations, at the cost of having only approximate tangent continuity away from the vertices. This allows us to provide a parallelized and fine-tuned Monte Carlo implementation. As a first example of the potential benefits of the enhanced description, our method supports inhomogeneous lipid distributions as well as lipid mixing. It also supports restraints and constraints of various types and is constructed to be as easily extensible as possible. We validate the approach by testing its numerical accuracy, followed by reproducing the known Helfrich solutions for shapes with rotational symmetry. Finally, we present some example applications, including curvature-driven demixing and stylized effects of proteins. Input files for these examples, as well as the implementation itself, are freely available for researchers under the name OrganL.

Propagation and dispersion of Bloch waves in periodic media with soft inclusions

We investigate the behavior of waves in a periodic medium containing small soft inclusions or cavities of arbitrary shape, such that the homogeneous Dirichlet conditions are satisfied at the boundary. The leading terms of Bloch waves, their dispersion relations, and low frequency cutoff are rigorously derived. Our approach reveals the existence of exceptional wave vectors for which Bloch waves are comprised of clusters of perturbed plane waves that propagate in different directions. We demonstrate that for these exceptional wave vectors, no Bloch waves propagate in any one specific direction.

Universal shape replication via self-assembly with signal-passing tiles

AbstractIn this paper, we investigate shape-assembling power of a tile-based model of self-assembly called the Signal-Passing Tile Assembly Model (STAM). In this model, the glues that bind tiles together can be turned on and off by the binding actions of other glues via “signals”. Specifically, the problem we investigate is “shape replication” wherein, given a set of input assemblies of arbitrary shape, a system must construct an arbitrary number of assemblies with the same shapes and, with the exception of size-bounded junk assemblies that result from the process, no others. We provide the first fully universal shape replication result, namely a single tile set capable of performing shape replication on arbitrary sets of any 3-dimensional shapes without requiring any scaling or pre-encoded information in the input assemblies. Our result requires the input assemblies to be composed of signal-passing tiles whose glues can be deactivated to allow deconstruction of those assemblies, which we also prove is necessary by showing that there are shapes whose geometry cannot be replicated without deconstruction. Additionally, we modularize our construction to create systems capable of creating binary encodings of arbitrary shapes, and building arbitrary shapes from their encodings. Because the STAM is capable of universal computation, this then allows for arbitrary programs to be run within an STAM system, using the shape encodings as input, so that any computable transformation can be performed on the shapes. This is the full version, containing all construction and proof details, of a previously published extended abstract version that had most details omitted.

Multivariate time series clustering based on fuzzy cognitive maps and community detection

Most time series clustering methods mainly focus on univariate time series (UTS). Compared with UTS, multivariate time series (MTS) consists of multiple components. Although interest in MTS clustering is increasing, its performance is far from satisfactory. Most traditional MTS clustering methods may have two limitations. First, they do not consider both the temporal features of each component and the relationship between the components. Second, they can only identify the local relationship between adjacent data, but cannot obtain long-distance global relationships and capture clusters of arbitrary shapes. In this paper, we develop a method for MTS clustering based on fuzzy cognitive maps (FCMs) and community detection, termed as MTSC-FCM-CD. To overcome the first limitation, we use FCM to represent MTS; FCM can extract temporal features while preserving the relationship between components in MTS. To overcome the second limitation, we use the community detection algorithm to cluster the global relations, which is different from the traditional nearest neighbor distance-based method. In the calculation process, the similarity between FCMs should be used to build a complex network. Existing methods calculate the similarity between FCMs, only considering the numerical characteristics but ignoring the topological structure. To solve this problem, we design a two-stage similarity measure to build a complex network. In comparison to the existing methods, the experimental results on twenty benchmark datasets demonstrate the effectiveness of MTSC-FCM-CD in MTS clustering.

Phonon transport simulation with an extended VOF scheme for nano-structured thin film

Control of phonon transport in solid devices is important for thermoelectric energy conversion and phononic crystal technology, and much attention has been paid to sub-micrometer or nanometer scale structures for that purpose. In order to investigate how various nano-structures affect the phonon transport, we have developed a numerical simulation code based on the Boltzmann transport equation of phonon distribution function in the reciprocal space. To appropriately treat the phonon transport at interface of an arbitrary shape, we newly introduced a volume of fluid like scheme, which was originally developed for multi-phase flow simulation. As a test of the developed simulation code, we investigated two-dimensional thin silicon films with two types of hole shape and two types of hole arrangement. The results essentially agree with recent experiments.

Prediction of PM2.5 with a piecewise affine model considering spatial-temporal correlation

Over the past several decades, several air pollution prevention measures have been developed in response to the growing concern over air pollution. Using models to anticipate air pollution accurately aids in the timely prevention and management of air pollution. However, the spatial-temporal air quality aspects were not properly taken into account during the prior model construction. In this study, the distance correlation coefficient (DC) between measurements made in various monitoring stations is used to identify appropriate correlated monitoring stations. To derive spatial-temporal correlations for modeling, the causality relationship between measurements made in various monitoring stations is analyzed using Transfer Entropy (TE). This work explores the process of identifying a piecewise affine (PWA) model using a larger dataset and suggests a unique hierarchical clustering-based identification technique with model structure selection. This work improves the BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) by introducing Kullback-Leibler (KL) Divergence as the dissimilarity between clusters for handling clusters with arbitrary shapes. The number of clusters is automatically determined using a cluster validity metric. The task is formulated as a sparse optimization problem, and the model structure is selected using parameter estimations. Beijing air quality data is used to demonstrate the method, and the results show that the proposed strategy may produce acceptable forecast performance.

Programmable photoacoustic patterning of microparticles in air.

Optical and acoustic tweezers, despite operating on different physical principles, offer non-contact manipulation of microscopic and mesoscopic objects, making them essential in fields like cell biology, medicine, and nanotechnology. The advantages and limitations of optical and acoustic manipulation complement each other, particularly in terms of trapping size, force intensity, and flexibility. We use photoacoustic effects to generate localized Lamb wave fields capable of mapping arbitrary laser pattern shapes. By using localized Lamb waves to vibrate the surface of the multilayer membrane, we can pattern tens of thousands of microscopic particles into the desired pattern simultaneously. Moreover, by quickly and successively adjusting the laser shape, microparticles flow dynamically along the corresponding elastic wave fields, creating a frame-by-frame animation. Our approach merges the programmable adaptability of optical tweezers with the potent manipulation capabilities of acoustic waves, paving the way for wave-based manipulation techniques, such as microparticle assembly, biological synthesis, and microsystems.

Alignment Controlled Aramid Nanofiber‐Assembled Films

AbstractAramid nanofibers (ANFs) are a strong and heat‐resistant nanomaterial that can be isolated from commercial para‐aramid fibers, which allow a bottom‐up self‐assembly to form ordered macroscale structures like ANF films. However, the anisotropic nature of high aspect ratio ANFs is not fully exploited when fabricating ANF films for the optimal mechanical properties. In this research, direct ink writing (DIW) is applied to produce ANF‐assembled films with arbitrary shapes, and the shear‐induced alignment of ANFs can follow the printing path direction. Therefore, controlled alignment of ANFs following the computer‐programmed printing pattern is achieved by DIW, which provides a path for the application of topology and nanofiber alignment optimization in nanofiber‐assembled films. In addition, the resulting DIW ANF films exhibit outstanding Young's modulus of 8.39 GPa, tensile strength of 198 MPa, and tensile toughness of 19.4 MJ m−3 in the alignment direction, together with a wide working temperature range up to 440 °C without losing 50% of its room temperature storage modulus. Moreover, the demonstrated self‐joining ability, rollability, and lamination processability of the DIW ANF films expand their potential applications toward high‐temperature ultrathin tubes, substrates for flexible printed circuit boards, and three‐dimensional all‐ANF lightweight structural parts in extreme environments.

Rigorous Accounting for Dependent Scattering in Thick and Concentrated Nanoemulsions.

Concentrated and thick oil-in-water nanoemulsions have been observed to become more transparent with increasing oil volume fraction. This study demonstrates rigorously experimentally and numerically that such unusual behavior is due to dependent scattering including not only far-field but also near-field effects. Indeed, when the droplet concentration is sufficiently large, their interparticle distance becomes small compared to the wavelength of light and scattering by a given droplet may be affected by the proximity of others. This situation is referred to as dependent scattering. Light transfer through nanoemulsions and other colloids has previously been modeled by solving the radiative transfer equation accounting for dependent scattering using the static structure factor based on far-field approximations. Here, oil-in-water nanoemulsions were prepared with oil volume fraction ranging between 1 and 20% and a peak droplet radius of 16 nm. The spectral normal-hemispherical transmittance of the different nanoemulsions in 10 mm thick cuvettes was measured experimentally between 400 and 900 nm. Numerical predictions for nonoverlapping randomly distributed nanoscale oil droplets in water and accounting for dependent scattering including near-field effects-using the recently developed radiative transfer with reciprocal transactions (R2T2) method-were in excellent agreement with experimental measurements. Simulations revealed that assuming independent scattering underestimated the normal-hemispherical transmittance even for a relatively small oil volume fraction. Additionally, simulations using the dense medium radiative transfer (DMRT) and static structure factor predicted that dependent scattering prevailed for oil volume fractions slightly greater than those predicted by the R2T2 method. Interestingly, the DMRT method predicted large increases in transmittance when the oil droplet size and volume fraction were larger than 10 nm and 10%, respectively. Finally, simulations also revealed that dependent scattering enables the design of oil-in-water nanoemulsions to backscatter or absorb light by tuning the oil droplet size and volume fraction. The results validate that the R2T2 method could be used to characterize nanoemulsions or to investigate their formation, composition, and stability for drug delivery, food, and cosmetics applications. Future studies could extend the use of the R2T2 method to colloidal suspensions with particles of arbitrary shapes and to radiation transfer of polarized light in turbid media.

Design of metadevices based on isotropic materials for eigenfrequency recovery in lightened structures

This work presents a novel approach for the design of metadevices conceived to recover a prescribed set of the natural eigenfrequencies of a structure lightened by machining arbitrary shape holes, using classical topology optimization (TO) techniques. This TO metadevice design (TOMD) is performed by minimizing the error of an eigenfrequency recovery task, using the finite element method (FEM) as an analysis tool, ensuring manufacturability via the solid isotropic material with penalization (SIMP) approach with Heaviside filtering to reduce intermediate-density areas. The spatial variation of mechanical properties derives from the macroscopically distinguishable dual material distribution obtained from the TOMD problem. The methodology was first tested on lightened thin steel plates and then extended to a real-world 3D mechanical component with additional mechanical performance testing. In all cases, the optimized metadevice yielded lower error in recovering eigenfrequencies compared to the lightened component without the metadevice. Furthermore, the metadevice generally achieved further mass reduction, demonstrating its potential for lightweight design while restoring its original eigenfrequencies.

Planar technology fabrication of high-density luminescence structure based on NaYF4 microparticles

This study presents a technological capability of producing individual size-defined luminescent centers and high-density arrays of upconversion particles using monosize powder based on NaYF4 matrix doped with rare earth metals such as erbium and ytterbium. The integration of various techniques such as lithography, etching, and deposition has enabled the creation of cavity arrays, or trenches, with arbitrary shapes for localization of luminescent monodisperse microparticles with an average size of 1.65 μm.

Nonlinear transport and kinetics in electrocatalytic thin film of arbitrary shape for non-Michaelis-Menten reaction kinetics

The mathematical model for non-Michael-Menten kinetics, which describes a substrate that produces a complex with the immobilised catalyst, is discussed. This paper analytically solves the nonlinear reaction–diffusion equation in an electrocatalytic thin film of arbitrary shape. We provide a mathematical process that enables a comprehensive analytical solution to the nonlinear boundary value problem. Closed and simple forms of the approximate expression for substrate concentration profiles for general geometry (planar, cylindrical, and spherical) and corresponding steady-state amperometric current response are presented. The results obtained by three analytical methods are then compared with numerical solutions. The comparison has been represented graphically, and the Tabler form shows the effectiveness and advantages of the featured techniques. The effect of the parameters on concentration is also discussed.