Interconnect Layers Research Articles

MnO2 Nanowire Thin Mesh With Enhanced Mass Transfer as Hydroxide Exchange Membrane Fuel Cell Cathode

AbstractHydroxide exchange membrane fuel cells (HEMFCs) are promising due to the potential use of nonprecious metal catalysts. However, the performance of HEMFCs based on nonprecious catalysts is still unsatisfactory, and one reason for this is hindered mass transfer in the catalyst layer. In this study, we employ a hydrothermal method to grow in situ a MnO2 nanowire thin mesh (NTM) catalytic layer on the gas diffusion electrode. The HEMFC prepared with MnO2 NTM cathode achieves a peak power density of 425 mW cm−2, surpassing the performance of the HEMFC prepared using the traditional powder catalyst spraying method by four times. High‐frequency resistance and limiting current tests indicate that the MnO2 NTM reduces ohmic resistance and improves mass transfer, thereby enhancing the HEMFC performance. Furthermore, the peak power density of the HEMFC is increased to 626 mW cm−2 by depositing additional active Co3O4 nanoparticles on the MnO2 NTM. These findings demonstrate that an interconnected and porous catalyst layer structure is beneficial for improving mass transfer properties, which in turn enhances HEMFC performance.

Gameplay 2.0: Toward a New Theory

The aim of this article is to present an updated version of our previous theory of gameplay. “Gameplay” is a term often used without a clear definition or consistent application. In this article, we propose categorizing gameplay into three distinct yet interconnected layers: the first emphasizing temporality, the second highlighting spatiality, and the third pinpointing emotion as anchor point. Our model and understanding are influenced by the philosophy of phenomenology, particularly Husserl's objective examination of the first-person perspective in perceptual experience—a commendable approach for blending formalism with real-time experience without resorting to subjectivism or psychologism. We offer an analytical and methodological framework for understanding gameplay, relying on micro-tensions to elucidate gameplay as a structural entity as well as an experiential phenomenon. As we shall demonstrate, micro-tensions are present within each of the three layers, paving the way for the entirety of gameplay—referred to by gamers as “great gameplay.”

Boosting Carrier Transport in Quasi-2D/3D Perovskite Heterojunction for High-Performance Perovskite/Organic Tandems.

Wide-bandgap (WBG) perovskites are continuously in the limelight owing to their applicability in tandem solar cells. The main bottlenecks of WBG perovskites are interfacial non-radiative recombination and carrier transport loss caused by interfacial defects and large energy-level offsets, which induce additional energy losses when WBG perovskites are stacked with organic solar cells in series because of unbalanced carrier recombination in interconnecting layer (ICL). To solve these issues, 1,3-propanediammonium iodide (PDADI) is incorporated to form Dion-Jacobson -phase quasi-2D perovskites with mixed high-n-values in WBG perovskites. PDADI simultaneously repairs the shallow/deep defects and establishes a Type-II energy-level alignment between quasi-2D/3D and 3D perovskites for rapid carrier extraction. More importantly, the short-chain diammonium cation in quasi-2D perovskite with high n-values results in a short Pb-I inorganic layer spacing, which enhances the interlayer electronic coupling and weakens the quantum-well confinement effect that restricts carrier transport. The suppressed transport loss increases the electron concentration in the ICL for balanced carrier recombination. The 0.0628 and 1.004 cm2 perovskite/organic tandems achieve remarkable efficiencies of 25.92% and 24.63%, respectively. The quasi-2D capping layer can inhibit ion migration, allowing perovskite/organic tandems to show excellent operational stability (T85 >1000h).

Progress and prospects for all-perovskite tandem solar cells

All-perovskite tandem solar cells (TSCs) consist of a wide-bandgap (WBG, 1.75-1.8 eV) top subcell and a low-bandgap (LBG, 1.2-1.3 eV) bottom subcell, exhibit superior power conversion efficiencies (PCEs) compared to single-junction perovskite solar cells (PSCs). In addition, the advantages of low-temperature solution preparation and low manufacturing cost make the all-perovskite tandem solar cells widely concerned, and are considered to be one of the most potential next-generation high-performance thin film photovoltaic technologies. In this perspective, we briefly summarize the state-of-the-art advances in monolithic all-perovskite TSCs focusing on the following aspects: LBG perovskite bottom subcells, WBG perovskite top subcells, and interconnecting layers (ICLs). We then discuss the primary strategies to improve their performance and finally highlight the perspective regarding the achievement of efficient and stable all-perovskite tandems.

Penerapan Jaringan Syaraf Tiruan untuk Pengenalan Pola Huruf Menggunakan Metode Bidirectional Associative Memory (BAM)

The process in artificial intelligence is similar to the process that occurs in the human brain. The pattern recognition process is to determine whether the input and output values ​​are the same so that the system can detect the pattern. A reciprocal relationship between the input and output levels is made possible by the two interconnected layers of the Bidirectional Associative Memory (BAM) technique. As a result, this technique can serve as an associative memory, meaning that some of the data stored in it can be called upon.. The load signal is transmitted from the input layer X to the output layer Y in this procedure. The weight value will be modified by computing the outcomes between the ranks [1,0]. In this work, the active sigmoid function is employed. Three input characters—the letters S, O, and X—are used in this study's 5x5 order matrix. A pattern [27 4] that matches the target is produced by the target letter S [1,-1], a pattern [27 -3] that does not match the target is produced by the target letter O [1.1], and a pattern [-37 21] that matches the target is produced by the target letter X [-1,1]. Consequently, not all patterns are able to meet the established objectives.

Implementing Lattice and Energy Level Matching to Optimize Buried Interfaces for High-Performance Perovskite Solar Cells.

In n-i-p type perovskite solar cells (PSCs), mismatches in energy level and lattice at the buried interface is highly detrimental to device performance. Here, thin PbS interconnect layer in situ coating on the SnO2 surface is grown. The function of PbS at the interface is different from the commonly used function of crystalline seeds in perovskite bulk. The theoretical calculation show that it helps construct an interconnect structure of SnO2/PbS/Perovskite with matched energy level and lattice. This not only increases conductivity of SnO2, but also upshifts Fermi energy levels (EF) of both SnO2 and buried perovskite due to charge transfer and perovskite's internal defect changes. Such a suitable energy level arrangement ensures a better energy level match at the interface, favoring efficient charge transfer and less open circuit voltage (Voc) loss. Additionally, in situ PL reveals that the template effect of PbS enable perovskite grain to grow bottom-up because of their highly matched lattice parameters. This growth mode optimizes buried interface contact and crystallinity of perovskite. Ultimately, after PbS modification, a remarkable power conversion efficiency (PCE) exceeding 24% and better device stability are obtained. This work demonstrates an effective interconnect layers strategy to realize ideal interface contact toward high-performance PSCs.

High efficiency homojunction tandem organic solar cells with all solution processable interconnect layer

In the field of organic photovoltaics, the power conversion efficiency of single junction solar cells continues to improve. However, tandem organic solar cells are poised to push the efficiency limits even further and offer a promising avenue for improving the performance of organic photovoltaic devices. This study reports the development of an all-solution processed interconnecting layer (ICL) based on ZnO NPs:PEI/PEI/PEDOT:PSS/2PACz for tandem solar cells. The PM6:BTP-eC9 active layer material was adjusted for its donor-to-acceptor (D/A) ratio and film thickness as the front and back sub-cells. The ICL exhibits favorable mechanical, electrical and optical properties. Through multidimensional modulation, the front and rear sub-cells have been optimized to obtain highly efficient homojunction tandem solar cells. The tandem solar cell has a structure of indium tin oxide (ITO)/PEDOT:PSS/2PACz/active layer/ICL/active layer/PNDIT-F3N/Ag. This optimization resulted in a power conversion efficiency (PCE) of 19.9 %, which is the highest reported efficiency for homojunction tandem organic solar cells to date. Our research demonstrates that the PCE of homojunction tandem cells can be significantly improved by careful design of the interconnecting layers and optimization of the donor-to-acceptor (D/A) ratio. This strategy may provide guidance for further improvements in homojunction tandem cells.

Optimization of Charge Extraction and Interconnecting Layers for Highly Efficient Perovskite/Organic Tandem Solar Cells with High Fill Factor.

Perovskite/organic tandem solar cells (POTSCs) have garnered significant attention due to their potential for achieving high photovoltaic (PV) performance. However, the reported power conversion efficiencies (PCEs) and fill factors (FFs) are still subpar due to the challenges associated with charge extraction in the organic bulk-heterojunction (BHJ) and significant energy losses in the interconnecting layers (ICLs). Here, a quaternary organic BHJ blend is developed to enhance the charge extraction in the organic subcell, contributing to an increased FF of ≥78% under 1 sun illumination and even more under lower illumination intensities. Meanwhile, energy losses in the ICLs are reduced via the incorporation of a self-assembly monolayer (SAM), (4-(3,6-Dimethyl-9H-carbazol-9-yl)butyl)phosphonic acid (Me-4PACz), in organic BHJ to form a MoOx/SAM interface and the thorough control of the MoOx thickness to suppress parasitic absorption. The resultant POTSCs achieve a remarkable PCE of 25.56% (certified: 24.65%), with a record FF of 83.62%, which is among the highest PCEs of POTSCs and the highest FF of all types of perovskite-based tandem solar cells (TSCs) till now. This work proves the optimization of charge extraction and ICLs are effective strategies to promote the performance of POTSCs to surpass other solution-processed perovskite-based TSCs in the near future.

Rotation-invariant image recognition using interconnected floating-gate phototransistor

Rotational invariance is fundamental for robust image recognition systems, ensuring accurate analysis irrespective of image orientation. However, existing systems predominantly reliant on software often encounter challenges such as increased computational demands and compromises between processing speed and accuracy. In this study, we propose leveraging the interconnected floating-gate (FG) structure as an effective hardware-level solution to achieve rotational invariance in image recognition. Our design features a reconfigurable two-dimensional material FG phototransistor array, where each processing unit integrates four sensory devices sharing a common FG. This configuration facilitates uniform distribution of stored charges across the interconnected FG layer, which is typically made of metal, enabling consistent application of a single weight matrix to images across varied rotational conditions. The photoactive material, tungsten diselenide (WSe2), possesses a distinctive bipolar property that facilitates both hole and electron tunneling into the FG layer. This property directly contributes to the efficiency of state transition within the setup and improves its overall adaptability. In this manner, our design achieves stable and predictable outputs in recognizing identical digital numbers regardless of their rotation, while also demonstrating variable performance essential for accurately distinguishing between different digital numbers. This dual capability guarantees both the adaptability and precision required for rotation-invariant image recognition, suggesting that our work may open up a promising venue for exploring advanced hardware designs, such as optimized interconnected FG architectures, tailored for enhancing recognition accuracy and efficiency in the field of intelligent visual systems.

Navigating Complex Process and Design Challenges in Hybrid Bonding for Advanced Semiconductor Integration: A Comprehensive Analysis

Abstract In advanced electronic systems, achieving top-tier interconnect interfaces with fine-pitch integration is of paramount importance. Among interconnect options, hybrid bonding is the preeminent choice given its exceptional capacity for accommodating a high input/output (I/O) count, which facilitates high-density memory integration, increased power delivery, and enhanced signal speed. One key technique for ensuring utmost quality in hybrid bonding involves embedding Cu interconnects within the dielectric layer. Equally pivotal is surface planarization, accomplished through chemical mechanical polishing (CMP), which encompasses a meticulous two-step procedure, commencing with copper bulk CMP and culminating in barrier CMP. The latter step is particularly critical, yielding the indispensable surface finish required for a successful hybrid bonding process. Several crucial surface properties significantly influence overall bond yield, including a copper recess (“dishing”) in the vias, erosion and roughness of the dielectric layer, and surface topography changes from high-density to low-density copper vias. To optimize these parameters, a comprehensive understanding of the interconnect layer's design is essential. Here, we delve into the ramifications of via scaling, ranging from 5 to 1 µm, on dishing and roll-off, and the effects of copper via density variation, spanning from 16% to 13%, on topography. Furthermore, we explore how incorporation of dummy vias impacts the final surface finish, potentially leading to improved bond yie

Remote sensing framework for geological mapping via stacked autoencoders and clustering

Supervised machine learning methods for geological mapping via remote sensing face limitations due to the scarcity of accurately labelled training data that can be addressed by unsupervised learning, such as dimensionality reduction and clustering. Dimensionality reduction methods have the potential to play a crucial role in improving the accuracy of geological maps. Although conventional dimensionality reduction methods may struggle with nonlinear data, unsupervised deep learning models such as autoencoders can model non-linear relationships. Stacked autoencoders feature multiple interconnected layers to capture hierarchical data representations useful for remote sensing data. We present an unsupervised machine learning-based framework for processing remote sensing data using stacked autoencoders for dimensionality reduction and k-means clustering for mapping geological units. We use Landsat 8, ASTER, and Sentinel-2 datasets to evaluate the framework for geological mapping of the Mutawintji region in Western New South Wales, Australia. We also compare stacked autoencoders with principal component analysis (PCA) and canonical autoencoders. Our results reveal that the framework produces accurate and interpretable geological maps, efficiently discriminating rock units. The results reveal that the combination of stacked autoencoders with Sentinel-2 data yields the best performance accuracy when compared to other combinations. We find that stacked autoencoders enable better extraction of complex and hierarchical representation of the input data when compared to canonical autoencoders and PCA. We also find that the generated maps align with prior geological knowledge of the study area while providing novel insights into geological structures.

Pluralism and the Design of Autonomous Vehicles

This paper advocates for an ethical analysis of autonomous vehicle systems (AVSs) based on a moral epistemic pluralism. This paper contends that approaching the design of intricate social technologies, such as AVSs, is most effective when acknowledging a diverse range of values. Additionally, a comprehensive ethical framework for autonomous vehicles should be applied across two interconnected layers. The first layer centers on the individual level, where each autonomous vehicle becomes a unit of moral consideration. The second layer focuses on the system level, directing moral attention toward the intricate autonomous vehicle system as a whole. Distinguishing the approach from metaphysical pluralism, the paper responds to counterarguments from a moral relativist and value monist perspectives. It concludes by emphasizing the necessity of embracing epistemic pluralism to navigate the complex ethical landscape of AVSs, urging a holistic understanding that transcends individual events and integrates system-level considerations.

Skin Cancer Classification Using Fine-Tuned Transfer Learning of DENSENET-121

Skin cancer diagnosis greatly benefits from advanced machine learning techniques, particularly fine-tuned deep learning models. In our research, we explored the impact of traditional machine learning and fine-tuned deep learning approaches on prediction accuracy. Our findings reveal significant improvements in predictability and accuracy with fine-tuning, particularly evident in deep learning models. The CNN, SVM, and Random Forest Classifier achieved high accuracy. However, fine-tuned deep learning models such as EfficientNetB0, ResNet34, VGG16, Inception _v3, and DenseNet121 demonstrated superior performance. To ensure comparability, we fine-tuned these models by incorporating additional layers, including one flatten layer and three densely interconnected layers. These layers play a crucial role in enhancing model efficiency and performance. The flatten layer preprocesses multidimensional feature maps, facilitating efficient information flow, while subsequent dense layers refine feature representations, capturing intricate patterns and relationships within the data. Leveraging LeakyReLU activation functions in the dense layers mitigates the vanishing gradient problem and promotes stable training. Finally, the output dense layer with a sigmoid activation function simplifies decision making for healthcare professionals by providing binary classification output. Our study underscores the significance of incorporating additional layers in fine-tuned neural network models for skin cancer classification, offering improved accuracy and reliability in diagnosis.

The Guardian Node Slow DoS Detection Model for Real-Time Application in IoT Networks.

The pernicious impact of malicious Slow DoS (Denial of Service) attacks on the application layer and web-based Open Systems Interconnection model services like Hypertext Transfer Protocol (HTTP) has given impetus to a range of novel detection strategies, many of which use machine learning (ML) for computationally intensive full packet capture and post-event processing. In contrast, existing detection mechanisms, such as those found in various approaches including ML, artificial intelligence, and neural networks neither facilitate real-time detection nor consider the computational overhead within resource-constrained Internet of Things (IoT) networks. Slow DoS attacks are notoriously difficult to reliably identify, as they masquerade as legitimate application layer traffic, often resembling nodes with slow or intermittent connectivity. This means they often evade detection mechanisms because they appear as genuine node activity, which increases the likelihood of mistakenly being granted access by intrusion-detection systems. The original contribution of this paper is an innovative Guardian Node (GN) Slow DoS detection model, which analyses the two key network attributes of packet length and packet delta time in real time within a live IoT network. By designing the GN to operate within a narrow window of packet length and delta time values, accurate detection of all three main Slow DoS variants is achieved, even under the stealthiest malicious attack conditions. A unique feature of the GN model is its ability to reliably discriminate Slow DoS attack traffic from both genuine and slow nodes experiencing high latency or poor connectivity. A rigorous critical evaluation has consistently validated high, real-time detection accuracies of more than 98% for the GN model across a range of demanding traffic profiles. This performance is analogous to existing ML approaches, whilst being significantly more resource efficient, with computational and storage overheads being over 96% lower than full packet capture techniques, so it represents a very attractive alternative for deployment in resource-scarce IoT environments.

Kei te moe te tinana, kei te oho te wairua – As the body sleeps, the spirit awakens: exploring the spiritual experiences of contemporary Māori associated with sleep

ABSTRACT For Aotearoa New Zealand Māori, sleep and wairua (spirit) are closely intertwined. During sleep the wairua awakens and journeys across multiple dimensions of time and space to attain the tools and knowledge the individual needs to navigate waking life. While this function of sleep is understood within Mātauranga Māori (bodies of knowledge regarding everything within the universe) (Hikuroa 2017), it has yet to be explored within psychological sleep research. This qualitative study contributes to addressing this gap by exploring nine Māori participants’ personal experiences of wairua during sleep. A whakapapa thematic analysis identified two interconnected layers. The first layer contributed to a spiritual explanatory framework for sleep, developed to encompass participants’ beliefs regarding wairua, which were utilised to interpret their sleep experiences. The second layer describes these interpretations, comprised of three central themes: (1) Tohu/Guidance; (2) Ako/Space and time for learning; and (3) Tau/Attaining a state of stability, peace, and purpose. These findings suggest that the spiritual experience of sleep supported participants in navigating their waking lives safely, purposefully, and meaningfully, contributing to Indigenous and Māori scholarship regarding the spiritual and cultural purpose of sleep, and with important implications for clinical, social, and academic approaches to understanding and supporting sleep.

Atomic-Scale Investigation of Electromigration Behavior in Cu-to-Cu Joints at High Current Density

Three-dimensional integrated circuit (3D IC) packaging offers significant advantages, such as enhanced computational efficiency through greater integration and shorter interconnection distances. The effective interconnection of layers, particularly through redistribution layer (RDL) technology, is crucial for the successful operation of 3D ICs. While copper remains the preferred material for interconnections, often in conjunction with through-silicon via (TSV) technology for chip-to-chip links, the shrinking dimensions of components present challenges. In particular, the reduction in size may lead to elevated current densities in individual joints, giving rise to issues like electromigration (EM) and potential failure. EM-induced atomic migration may lead to the formation of voids in the interconnection. The accumulation of voids to a critical point may result in an open circuit in the joints, significantly impacting the conductor's reliability. This work delves into the micro-scale aspects of these challenges, complementing previous macroscopic investigations. We aim to elucidate the behavioral mechanisms through atomic-scale observations, employing an in-situ high-resolution transmission electron microscope (in-situ HRTEM) to observe atomic-scale images of EM. The insights gained from this work not only contribute to the academic understanding of industry challenges but hold potential applications in real-world manufacturing processes. Fig. 1. (a) Schematic diagram of TEM sample preparation. (b) Cross-sectional HRTEM image of copper bonding. (c, d) TEM images showing voids expansion at bonding interface. Figure 1

Melamine foam scaffolded 3D porous polyaniline/reduced graphene oxide composite electrode for flexible supercapacitor

Graphene composite foam with enhanced mechanical and electrochemical properties holds great promise for flexible supercapacitors. This work developed a cost-effective method for massive production of three-dimensional (3D) porous graphene composite using melamine foam (MF) as a flexible scaffold. The MF was coated reduced graphene oxide (RGO) to form an interconnected conductive layer by dip-coating and vapor reduction, and loaded with polyaniline (PANI) by in-situ polymerization. The resulted PANI/RGO/MF, as self-supporting electrode, exhibits extraordinary mechanical flexibility and a high specific capacitance of 806.2 mF cm−2 at 0.5 mA cm−2. Furthermore, the assembled solid-state supercapacitor exhibits an outstanding capacity of 299.1 mF cm−2 at 0.5 mA cm−2, a high energy density of 26.6 μWh cm−2 at 200 μW cm−2, nearly 100 % capacitance retention at 0°–180°, and good cycling stability. This study provides a scalable strategy for fabricating graphene composite foam suitable for flexible energy storage application.

Laser-induced ultrasound in multiple thin layers-An analytical solution.

Laser-induced ultrasound is based on the thermo-elastic conversion of absorbed short light pulses to pressure pulses. In the work presented here, laser-induced ultrasound in a planar structure of interconnected layers with variations in optical, thermal, and mechanical properties is studied. Layered structures can be used for generating wideband ultrasonic pulses specific to a chosen application. An analytical time-domain solution is derived for the resulting pressure transmitted from the layered structure. The solution is derived for an arbitrary number of layers with an arbitrary optical absorption profile. Free space Green's functions with image sources are used to derive the solution. A solution employing the Beer-Lambert law is also proposed. The simplification with reflections only at the boundaries is in agreement with previous published results. The spectral properties of the generated pulse are derived, where the effects of optical absorption coefficients and layer thicknesses are shown. The analytical solution is compared to one-dimensional (1D) simulations and a three-dimensional (3D) simulation, realised as a two-dimensional (2D) axially symmetric case, using the matlab toolbox k-Wave. The 3D simulation on-axis pressure agrees well with the 1D analytical solution when the diameter of the laser beam is larger by approximately 1 order of magnitude than the thickness of the planar layered structure.

Vertically stacked skin-like active-matrix display with ultrahigh aperture ratio

Vertically stacked all-organic active-matrix organic light-emitting diodes are promising candidates for high-quality skin-like displays due to their high aperture ratio, extreme mechanical flexibility, and low-temperature processing ability. However, these displays suffer from process interferences when interconnecting functional layers made of all-organic materials. To overcome this challenge, we present an innovative integration strategy called “discrete preparation-multilayer lamination” based on microelectronic processes. In this strategy, each functional layer was prepared separately on different substrates to avoid chemical and physical damage caused by process interferences. A single interconnect layer was introduced between each vertically stacked functional layer to ensure mechanical compatibility and interconnection. Compared to the previously reported layer-by-layer preparation method, the proposed method eliminates the need for tedious protection via barrier and pixel-defining layer processing steps. Additionally, based on active-matrix display, this strategy allows multiple pixels to collectively display a pattern of “1” with an aperture ratio of 83%. Moreover, the average mobility of full-photolithographic organic thin-film transistors was 1.04 cm2 V−1 s−1, ensuring stable and uniform displays. This strategy forms the basis for the construction of vertically stacked active-matrix displays, which should facilitate the commercial development of skin-like displays in wearable electronics.

Hybrid interconnecting layers reduce current leakage losses in perovskite/silicon tandems with 81.8% fill factor

Hybrid interconnecting layers reduce current leakage losses in perovskite/silicon tandems with 81.8% fill factor