2D Array Research Articles

Event Based Cameras: A Comparative Study For Fluid Event Detection

A feasibility study using an event-based camera for the detection of plane-wise motion of a 2D array of bio-inspired sensing pillars to detect generated flow events. EBCs show potential for future applications where PIV may have been classically used. They have the benefit of only generating data when an event happens and with comparatively cheaper setups, they hold great potential for flow monitoring. EBCs collect pixel x and y locations, as well as pixel contrast change data at each time there is an event and can be trained on regions of interest. Comparative experiments were carried out in the labs at City, University of London, to investigate the feasibility of using EBCs for the detection of generated large flow structures in both air and water. The disturbances were produced by a gust generator, an upstream cylinder and an air gun for a variety of controlled situations, such as disturbances caused by gusts, crossflows and wake downstream oscillations. Some results were also compared to known PIV results from our lab to see how EBCs can detect a known flow structure over the sensing pillars. The results presented demonstrate the capability of the pillars and EBC to detect large flow structures. These initial results show promise for future applications of flow monitoring, such as real-time flow monitoring via a machine learning algorithm that is trained to detect certain flow patterns over the sensing pillars. This would be an intermediate step into a fully automated flow control loop.

High-resolution 3D ultrasonic imaging using high-frequency piezoelectric transmitter and ultra-multiple laser 2D scanning

In this paper, we extend a piezoelectric and laser ultrasonic system (PLUS) to a high-frequency version for high-sensitivity three-dimensional (3D) ultrasonic imaging by utilizing a unique characteristic of PLUS. PLUS combines a piezoelectric transmitter and a two-dimensional (2D) scan of a laser Doppler vibrometer (LDV). A high frequency can be used simply by adopting a high-frequency piezoelectric transmitter with a center frequency, such as 15 MHz, since the LDV has a broad bandwidth reception of 0–25 MHz. Furthermore, a 2D array receiver with a small interelement pitch can be achieved by precisely scanning a small laser irradiation spot. We experimentally demonstrate its 3D imaging capability for flat-bottom-hole and fatigue-crack specimens.

Multi‐Scale Seismic Imaging of the Ridgecrest, CA, Region With Waveform Inversion of Regional and Dense Array Data

AbstractWe develop an inversion procedure for deriving multi‐scale velocity models with waveform inversions of earthquake and ambient noise data at multi‐frequency bands recorded by regional and dense sensor configurations. The method is applied for the area around the 2019 Ridgecrest earthquake rupture zones, utilizing data recorded by regional stations and dense 2D and 1D arrays with station spacings of ∼5 km and ∼100 m, respectively. Starting with regional Vp, Vs models and locations of Ridgecrest aftershocks, the velocity models and event locations are improved iteratively by inversions of waveforms recorded by regional stations and the 2D array, using a minimum spectral element size of ∼600 m. Waveforms from local events recorded by dense 1D arrays across the M7.1 rupture zone with frequencies of up to 10 Hz are used to resolve small‐scale features of the rupture zone and shallow crust with a local spectral element size of 80 m. The refined models provide self‐consistent descriptions of the rupture zone and the shallow crust embedded in the regional structures. The results reveal pronounced low Vs and high Vp/Vs in the M6.4 and M7.1 rupture zones coinciding with concentrations of seismicity, and also around the Garlock fault and in several local basins. We also observe clear velocity contrasts across the Garlock fault with polarity reversals along strike and with depth. The obtained multi‐scale velocity models can be used to improve derivations of earthquake source properties, simulations of dynamic ruptures and ground motions, and the understanding of fault and tectonic processes in the region.

Integration of buried nanomagnet and silicon spin qubits in a one-dimensional fin structure

We adopt a buried nanomagnet (BNM) technology on a one-dimensional (1D) array of silicon spin qubits, and its availability was investigated using numerical simulations. The qubit array is formed in the center of the Si fin and the nanomagnet is buried in the lower lateral part of the qubits. The nanomagnet placed near the qubit generates a strong slanting magnetic field in the qubit, enabling X-gate operation approximately 15 times faster than in conventional cases. Furthermore, the formation of a BNM using a self-aligned process suppresses the dimensional variation of the nanomagnet caused by process variation, thereby mitigating the slanting field fluctuation and fidelity degradation. In addition, even for multiple qubits formed in the Si fin, the BNM with excess length generated a uniform slanting field, mitigating fidelity degradation and enabling all qubits to operate using a single-frequency microwave. Therefore, the proposed structure is useful for 1D integrated structures.

3D Surface-Enhanced Raman Scattering Substrate Based on an Array of Self-Assembled Au@SiO2 Microspheres

A quasi-periodic array of 3D gold-nanoparticle-capped SiO2 microspheres (Au@SiO2) was designed and prepared with a facile approach to enhance the Raman signal intensity of adsorbed biomolecules. Through adjusting the thickness and annealing of Au thin films initially deposited on arrays of self-assembled SiO2 microspheres, we were able to control the diameter of Au nanoparticles and their interparticle spacing to produce two types of plasmonic near-field hot spots, locating at the gaps of such densely arranged Au nanoparticles on individual SiO2 microspheres and in the gap regions of neighboring SiO2 microspheres, respectively. Such double near-field enhancement mechanism leads to a surface-enhanced Raman scattering (SERS) enhancement factor up to 3 × 106 for Rhodamine 6G molecules. The SERS signal intensity was highly uniform with a relative standard deviation of 4.5%. This 3D SERS substrate has significant potential for various applications in the field of SERS detection of analytes and wearable biosensing.

Template-assisted growth of Ga-based nanoparticle clusters on Si: effect of post-annealing process on the Ga ion beam exposed 2D arrays fabricated by focused ion beam nanolithography

We demonstrate template-assisted growth of gallium-based nanoparticle clusters on silicon substrate using a focused ion beam (FIB) nanolithography technique. The nanolithography counterpart of the technique steers a focussed 30 kV accelerated gallium ion beam on the surface of Si to create template patterns of two-dimensional dot arrays. Growth of the nanoparticles is governed by two vital steps namely implantation of gallium into the substrate via gallium beam exposure and formation of the stable nanoparticles on the surface of the substrate by subsequent annealing at elevated temperature in ammonia atmosphere. The growth primarily depends on the dose of implanted gallium which is in the order of 107 atoms per spot and it is also critically influenced by the temperature and duration of the post-annealing treatment. By controlling the growth parameters, it is possible to obtain one particle per spot and particle densities as high as 109 particles per square centimetre could be achieved in this case. The demonstrated growth process, utilizing the advantages of FIB nanolithography, is categorized under the guided organization approach as it combines both the classical top-down and bottom-up approaches. Patterned growth of the particles could be utilized as templates or nucleation sites for the growth of an organized array of nanostructures or quantum dot structures.

Denoising of Dense Spatial Array Data Using the Curvelet Transform

ABSTRACT To remove background noise from seismic data recorded by spatially dense arrays, we have developed a space-based denoising procedure using the discrete curvelet transform. Based on a detailed statistical characterization of noise coefficients through the empirical cumulative distribution function method within a pre-event time window, signal and noise can be separated effectively by nonlinear thresholding. After synthetic test, we applied this method on data from an industry 3D seismic experiment recorded at an array deployed near Utica, Ohio. The denoising results show good waveform consistency with a significantly enhanced signal-to-noise ratio. Our curvelet approach allows a more computationally efficient spatial–temporal localization analysis of seismic data than conventional curvelet techniques by avoiding the assumption of stationary Gaussian-distributed noise and can be implemented as a complement of time-domain wavelet methods with fewer frequency losses after denoising. This new method provides a fast and convenient way to recover signals from noisy recordings with dense 2D arrays, leading to a considerable improvement in data quality compared with conventional Fourier, wavelet, and curvelet methods. The partitioned seismic signals and noise would yield advanced earth structure imaging, small-event detection, ambient noise tomography, and others.

Exploring Disturb Characteristics in 2D and 3D Ferroelectric NAND Memory Arrays for Next-Generation Memory Technology.

Ferroelectric transistors are considered promising for next-generation 3D NAND technology due to their lower power consumption and faster operation compared to conventional charge-trap flash memories. However, ensuring their suitability for such applications requires a thorough investigation of array-scale reliability. This study specifically examines the suitability of hafnia-based ferroelectric transistors for advanced 3D NAND applications, with a specific focus on establishing a disturb-free voltage scheme to ensure the reliability of ferroelectric transistors within the array. Our key finding highlights the crucial role of optimal pass voltage in achieving disturb-free operation in both 2D and 3D ferroelectric NAND arrays. Additionally, the study indicates that read disturb remains negligible when an appropriate read voltage is applied. These insights provide a practical strategy for achieving reliable operation in 2D and 3D ferroelectric NAND, highlighting the potential of hafnia-based ferroelectric materials to meet the evolving requirements of high-density and reliable NAND flash memory applications.

Cobalt nanoparticles confined nitrogen–doped carbon integrated bimetallic Co2P–VP heterostructured composite: A MOF integrated 3D arrays for catalytic water splitting

A robust electrode material with outstanding stability at high current density is crucial for the practical application of water splitting. We present an intertwined heterostructure composed of in-situ confined cobalt nanoparticles (Conp) in nitrogen-doped carbon (N–C), derived from functionalized zeolitic imidazolate framework–67 (ZIF−67), and composited with the hetero phase bimetallic cobalt vanadium phosphide (Co2P−VP) through a hydrothermal reaction, room temperature aging, and chemical vapor deposition (CVD) for simultaneous phosphidation, graphitization, and reduction. The synergistic effect generated across the multiple heterointerfaces of Co2P, VP, and Conp in the N−doped carbon on nickel foam, as the Co2P–VP@N–C/Co heterostructure, exhibits outstanding electrocatalytic performance for the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and electrochemical water splitting. The Co2P–VP@N–C/Co (+,−) alkaline electrolyzer demonstrates a low potential of 1.49 and 1.71 V to achieve current densities of 10 and 100 mA cm−2, respectively. It exhibits outstanding stability during continuous operation for 100 h at 100 mA cm−2, with 98.02 % retention. The outstanding performance is credited to the synergistic interaction and d-electronic modulation of the metallic hetero phasic Co2P–VP moiety and confined Conp in a functionalized N−doped porous carbonaceous heterostructure. Density Functional Theory (DFT) validates the regulation of electronic structure for efficient redistribution of local charges and electron transfer.

Ultrasensitive composite electrochemical sensor with printed wrinkled CNTs nanostructure for simultaneous detection

Combining biomimetic and 3D printing has created new opportunities for the manufacture of electrochemical sensors. Dopamine (DA) and Uric acid (UA) are common body electroactive substances, and their detection is important for diagnosing metabolic diseases. Metal electrochemical sensors have limitations in sensitivity and selectivity due to their smooth 2D structures, which make it challenging to capture comprehensive electrochemical information. Here, inspired by taste buds, an ultrasensitive CNT-Pt composite electrochemical sensor, including a printed biomimetic wrinkled CNTs film, was prepared for simultaneous detection of DA and UA. Nanoscale Pt electrode was prepared by UV-LIGA process and the wrinkled CNTs nanofilm was fabricated by thermally assisted electrohydrodynamic jet (E-Jet) printing. CNT lines of 3∼58 μm, droplets of 4 μm and 2D array structures have been printed. The enhanced sensing mechanism of wrinkled CNTs nanofilm was analyzed theoretically. The nanoscale wrinkled morphology (nanofolds∼50 nm) and hydrophilicity (CÃ20°) of printed wrinkled CNTs nanofilm were analyzed. The anodic peak potential for UA was observed to range from 0.429 V to 0.489 V for the conventional Pt electrochemical sensor, whereas it ranged from 0.205 V to 0.276 V for the CNT-Pt composite electrochemical sensor. The detection performance of CNT-Pt composite electrochemical sensor was improved by ∼40 % contrast with Pt electrochemical sensor. The prepared composite electrochemical sensor can effectively recognize DA, UA and AA. From analysis, the peak value of AA was not obvious, the peak values of DA and UA were 0.096 V and 0.265 V. The composite electrochemical sensor successfully eliminated the detection interference caused by AA in detecting DA and UA. The nanoscale composite electrochemical sensor and its hybrid manufacturing method provide great potential for electrochemical testing applications.

Inequality relations for NMR-based polymer homoblock analysis and extended application: Reanalysis of historical data on alginates, chitosans, homogalacturonans, and galactomannans

There has been a long-standing bottleneck in the quantitative analysis of the frequencies of homoblock polyads beyond triads using 1H and 13C NMR for linear polysaccharides, primarily because monosaccharides within a long homoblock share similar chemical environments due to identical neighboring units, resulting in indistinct NMR peaks. In this study, through rigorous mathematical induction, inequality relations were established that enabled the calculation of frequency ranges of homoblock polyads from historically reported NMR-derived frequency values of diads and/or triads of alginates, chitosans, homogalacturonans, and galactomannans. The calculated homoblock frequency ranges were then applied to evaluate three chain growth statistical models, including the Bernoulli chain, first-order Markov chain, and second-order Markov chain, for predicting homoblock frequencies in these polysaccharides. Furthermore, based on the mathematically derived inequality relations, a novel 2D array was constructed, enabling the graphical visualization of homoblock features in polysaccharides. It was demonstrated, as a proof of concept, that the novel 2D array, along with a 1D code generated from it, could serve as an effective feature engineering tool for polymer classification using machine learning algorithms.

A Prediction‐Traversal Approach for Compressing Scientific Data on Unstructured Meshes with Bounded Error

AbstractWe explore an error‐bounded lossy compression approach for reducing scientific data associated with 2D/3D unstructured meshes. While existing lossy compressors offer a high compression ratio with bounded error for regular grid data, methodologies tailored for unstructured mesh data are lacking; for example, one can compress nodal data as 1D arrays, neglecting the spatial coherency of the mesh nodes. Inspired by the SZ compressor, which predicts and quantizes values in a multidimensional array, we dynamically reorganize nodal data into sequences. Each sequence starts with a seed cell; based on a predefined traversal order, the next cell is added to the sequence if the current cell can predict and quantize the nodal data in the next cell with the given error bound. As a result, one can efficiently compress the quantized nodal data in each sequence until all mesh nodes are traversed. This paper also introduces a suite of novel error metrics, namely continuous mean squared error (CMSE) and continuous peak signal‐to‐noise ratio (CPSNR), to assess compression results for unstructured mesh data. The continuous error metrics are defined by integrating the error function on all cells, providing objective statistics across nonuniformly distributed nodes/cells in the mesh. We evaluate our methods with several scientific simulations ranging from ocean‐climate models and computational fluid dynamics simulations with both traditional and continuous error metrics. We demonstrated superior compression ratios and quality than existing lossy compressors.

Stretchable OLEDs based on a hidden active area for high fill factor and resolution compensation

Stretchable organic light-emitting diodes (OLEDs) have emerged as promising optoelectronic devices with exceptional degree of freedom in form factors. However, stretching OLEDs often results in a reduction in the geometrical fill factor (FF), that is the ratio of an active area to the total area, thereby limiting their potential for a broad range of applications. To overcome these challenges, we propose a three-dimensional (3D) architecture adopting a hidden active area that serves a dual role as both an emitting area and an interconnector. For this purpose, an ultrathin OLED is first attached to a 3D rigid island array structure through quadaxial stretching for precise, deformation-free alignment. A portion of the ultrathin OLED is concealed by letting it ‘fold in’ between the adjacent islands in the initial, non-stretched condition and gradually surfaces to the top upon stretching. This design enables the proposed stretchable OLEDs to exhibit a relatively high FF not only in the initial state but also after substantial deformation corresponding to a 30% biaxial system strain. Moreover, passive-matrix OLED displays that utilize this architecture are shown to be configurable for compensation of post-stretch resolution loss, demonstrating the efficacy of the proposed approach in realizing the full potential of stretchable OLEDs.

Mechanistic understanding of nanoparticle interactions to achieve highly-ordered arrays through self-assembly for sensitive surface-enhanced Raman scattering detection of trace thiram

Over the last few decades, there is increasing worldwide concern over human health risks associated with extensive use of pesticides in agriculture. Developing excellent SERS substrate materials to achieve highly sensitive detection of pesticide residues in the food is very necessary owing to their serious threat to human health through food chains. Self-assembled metallic nanoparticles have been demonstrated to be excellent SERS substrate materials. Hence, alkanethiols-protected gold nanoparticles have been successfully prepared for forming larger-scale two-dimensional monolayer films. These films can be disassembled into a fluid state and re-assembled back to crystallized structure by controlling surface pressure. Further investigations reveal that their self-assembled structures are mainly dependent on the diameter of gold nanoparticles and ligand length. These results suggest that the size ratio of nanoparticle diameter/ligand length within the range of 4.45–2.35 facilitates the formation of highly ordered 2D arrays. Furthermore, these arrays present excellent Surface-Enhanced Raman Scattering performances in the detection of trace thiram, which can cause environmental toxicity to the soil, water, animals and result in severe damage to human health. Therefore, the current study provides an effective way for preparing monodispersed hydrophobic gold nanoparticles and forming highly ordered 2D close-packed SERS substrate materials via self-assembly to detect pesticide residues in food. We believe that, our research provides not only advanced SERS substrate materials for excellent detection performance of thiram in food, but also novel fundamental understandings of self-assembly, manipulation of nanoparticle interactions, and controllable synthesis.

2D Vanadium Sulfides: Synthesis, Atomic Structure Engineering, and Charge Density Waves.

Two ultimately thin vanadium-rich 2D materials based on VS2 are created via molecular beam epitaxy and investigated using scanning tunneling microscopy, X-ray photoemission spectroscopy, and density functional theory (DFT) calculations. The controlled synthesis of stoichiometric single-layer VS2 or either of the two vanadium-rich materials is achieved by varying the sample coverage and sulfur pressure during annealing. Through annealing of small stoichiometric single-layer VS2 islands without S pressure, S-vacancies spontaneously order in 1D arrays, giving rise to patterned adsorption. Via the comparison of DFT calculations with scanning tunneling microscopy data, the atomic structure of the S-depleted phase, with a stoichiometry of V4S7, is determined. By depositing larger amounts of vanadium and sulfur, which are subsequently annealed in a S-rich atmosphere, self-intercalated ultimately thin V5S8-derived layers are obtained, which host 2 × 2 V-layers between sheets of VS2. We provide atomic models for the thinnest V5S8-derived structures. Finally, we use scanning tunneling spectroscopy to investigate the charge density wave observed in the 2D V5S8-derived islands.

Engineered 3D Vortex Array with Customized Energy and Topological Charges for Multi‐View Display

AbstractArrays of multiple vortex beams enhance parallel processing capabilities from particle manipulation to information communication. However, the spatial position, topological charge, and energy parameters of the vortex beams within the array have yet to be precisely controlled, posing significant challenges to the realization of multi‐view 3D Orbital Angular Momentum (OAM) display using vortex arrays as information carriers. To address this issue, a method for generating vortex arrays based on a phase‐only hologram, customizing the array by using the energy and OAM spectrum of each vortex beam as the loss function is developed. Experimental results indicate that a 2D array generates 100 vortex beams in the spatial frequency domain, while a 3D array in the Fresnel zone produces 252 vortex beams across 7 planes, each with 36 unprecedentedly controllable energy and topological charge vortex beams. Subsequently, images of 4 views using the 3D vortex arrays and decoded through coordinate transformation to achieve a multi‐view 3D OAM display are encoded. The results demonstrate imaging quality with Mean Peak Signal‐to‐Noise Ratio (MPSNR) of 12.7, 13.0, 13.4, and 12.2 dB in 4 views, respectively, offering promising opportunities for applications in 3D optical manipulation, high‐capacity communication, and 3D OAM holography.

Fully Reprogrammable 2D Array of Multistate Molecular Switching Units.

Integration of molecular switching units into complex electronic circuits is considered to be the next step toward the realization of novel logic and memory devices. This paper reports on an ordered 2D network of neighboring ternary switching units represented by triazatruxene (TAT) molecules organized in a honeycomb lattice on a Ag(111) surface. Using low-temperature scanning tunneling microscopy, the bonding configurations of individual TAT molecules can be controlled, realizing up to 12 distinct states per molecule. The switching between those states shows a strong bias dependence ranging from tens of millivolts to volts. The low-bias switching behavior is explored in active units consisting of two and more interacting TAT molecules that are purposefully defined (programmed) by high-bias switching within the honeycomb lattice. Within such a unit the low-bias switching can be triggered and accessed by single-point measurements on a single TAT molecule, demonstrating up to 9 and 19 distinguishable states in a dyad and a tetrad of coupled molecules, respectively. High experimental control over the desired state, owing to bias-dependent hierarchical switching and pronounced switching directionality, as well as full reversibility, make this system particularly appealing, paving the way to design complex molecule-based memory systems.

3D endoanal ultrasound versus external phased array MRI in detection and evaluation of anal sphincteric lesions

BackgroundThe anal sphincteric complex is formed by internal and external sphincters making two partially overlapping tubes around the anal canal. Anal sphincteric lesions represent a spectrum of entities with different patients’ presentations and surgical managements. Endoanal ultrasound has an increasing role in detection and evaluation of anal sphincteric lesions as compared to MRI of the anal canal. The aim of this work was to compare between the 3D EAUA and external phased array MRI in detection and evaluation of anal sphincteric lesions.ResultsThere is almost perfect agreement of 97.92% (Κw = 0.972) between 3D EAUS and external phased array MRI in the detection of the internal anal sphincter lesions and fair agreement of 66.67% (Κw = 0.37) in the detection of the external anal sphincteric lesions.Conclusions3D EAUS and external phased array MRI are comparable imaging techniques in the detection of the internal anal sphincter lesions, while the MRI could detect more external sphincteric lesions than EAUS.

Filtering After Shading With Stochastic Texture Filtering

2D texture maps and 3D voxel arrays are widely used to add rich detail to the surfaces and volumes of rendered scenes, and filtered texture lookups are integral to producing high-quality imagery. We show that applying the texture filter after evaluating shading generally gives more accurate imagery than filtering textures before BSDF evaluation, as is current practice. These benefits are not merely theoretical, but are apparent in common cases. We demonstrate that practical and efficient filtering after shading is possible through the use of stochastic sampling of texture filters. Stochastic texture filtering offers additional benefits, including efficient implementation of high-quality texture filters and efficient filtering of textures stored in compressed and sparse data structures, including neural representations. We demonstrate applications in both real-time and offline rendering and show that the additional error from stochastic filtering is minimal. We find that this error is handled well by either spatiotemporal denoising or moderate pixel sampling rates.

Magnetotelluric sampling theorem

We consider a general case of a magnetotelluric (MT) study to reveal three-dimensional (3D) distribution of the electrical conductivity within the Earth based on measurements of electromagnetic (EM) fields by a two-dimensional (2D) array. Such an MT array observation can be regarded as a spatially discrete sampling of the MT responses (impedances), and each observation site can be regarded as a sampling point. This means that MT array measurements must follow the Nyquist–Shannon sampling theorem. This paper discusses how the sampling theorem is applied to MT array studies and what kind of consideration is required in the application on the basis of synthetic model calculations, with special attention to spatial resolutions. With an aid of the EM scattering theory and the sampling theorem, we can show that an observation array resolves some features of the MT impedance but does not others. We call the resolvable and unresolvable features the MT signal and noise, respectively. This study introduces the spatial Fourier transform of array MT data (impedances) which helps us investigating sampling effects of lateral heterogeneity from a different angle (in the wavenumber domain). Shallow heterogeneities cause a sharp spatial change of impedance elements near structural boundaries. High wavenumber Fourier components are required to describe such a feature, which means the site spacing must be sufficiently short to be able to resolve such features. Otherwise, a set of array MT data will suffer from aliasing, which is one of the typical causes of MT distortion (MT geologic noise). Conversely, a signal due to a deep-seated conductivity anomaly will have more reduced amplitude at higher wavenumbers, which means focused imaging of such an anomaly is generally difficult. Finally, it is suggested to properly consider the sampling theorem in an observation array design, so as to have best performance in resolving MT signals.Graphical abstract