Nano Convergence最新文献

Metal-oxide thin-film semiconductors have been highlighted as next-generation space semiconductors owing to their excellent radiation hardness based on their dimensional advantages of very low thickness and insensitivity to crystal structure. However, thin-film transistors (TFTs) do not exhibit intrinsic radiation hardness owing to the chemical reactions at the interface exposed to ambient air. In this study, significantly enhanced radiation hardness of Al₂O₃-passivated ZnO TFTs against high-energy protons with energies of up to 100 MeV is obtained owing to the passivation layer blocking interactions with external reactants, thereby maintaining the chemical stability of the thin-film semiconductor. These results highlight the potential of passivated metal-oxide thin films for developing reliable radiation-hardened semiconductor devices that can be used in harsh space environments. In addition, the relationship between low-frequency noise and defects due to oxygen vacancies was revealed, which can be utilized to improve device reliability.

Electrochemical water splitting, which encompasses the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER), offers a promising route for sustainable hydrogen production. The development of efficient and cost-effective electrocatalysts is crucial for advancing this technology, especially given the reliance on expensive transition metals, such as Pt and Ir, in traditional catalysts. This review highlights recent advances in the design and optimization of electrocatalysts, focusing on density functional theory (DFT) as a key tool for understanding and improving catalytic performance in the HER and OER. We begin by exploring DFT-based approaches for evaluating catalytic activity under both acidic and alkaline conditions. The review then shifts to a material-oriented perspective, showcasing key catalyst materials and the theoretical strategies employed to enhance their performance. In addition, we discuss scaling relationships that exist between binding energies and electronic structures through the use of charge-density analysis and d-band theory. Advanced concepts, such as the effects of adsorbate coverage, solvation, and applied potential on catalytic behavior, are also discussed. We finally focus on integrating machine learning (ML) with DFT to enable high-throughput screening and accelerate the discovery of novel water-splitting catalysts. This comprehensive review underscores the pivotal role that DFT plays in advancing electrocatalyst design and highlights its potential for shaping the future of sustainable hydrogen production.

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Ferroelectric capacitive memories (FCMs) utilize ferroelectric polarization to modulate device capacitance for data storage, providing a new technological pathway to achieve two-terminal non-destructive-read ferroelectric memory. In contrast to the conventional resistive memories, the unique capacitive operation mechanism of FCMs transfers the memory reading and in-memory computing to charge domain, offering ultra-high energy efficiency, better compatibility to large-scale array, and negligible read disturbance. In recent years, extensive research has been conducted on FCMs. Various device designs were proposed and experimentally demonstrated with progressively enhanced performance, showing remarkable potential of the novel technology. This article summarizes several typical FCM devices by introducing their mechanisms, comparing their performance, and discussing their limitations. We further investigate the capacitive crossbar array operation and review the recent progress in the FCM integration and array-level demonstrations. In addition, we present the computing-in-memory applications of the FCMs to realize ultra-low-power machine learning acceleration for future computing systems.

The intriguing way the receptors in biological skin encode the tactile data has inspired the development of electronic skins (e-skin) with brain-inspired or neuromorphic computing. Starting with local (near sensor) data processing, there is an inherent mechanism in play that helps to scale down the data. This is particularly attractive when one considers the huge data produced by large number of sensors expected in a large area e-skin such as the whole-body skin of a robot. This underlines the need for biological skin like processing in the e-skin. Herein, we present multi-gate field-effect transistors (v-FET) having capacitively coupled floating gate (FG) to mimic some of the neural functions. The v-FETs are obtained by deterministic assembly of ZnO nanowires on a flexible substrate using contactless dielectrophoresis method, followed metallization using conventional microfabrication steps. The spatial summation of two presynaptic inputs (applied at multiple control gates) of the transistor confirm their neuron-like response. The temporal summation (such as paired-pulse facilitation) by presented v-FETs further confirm their neuron-like mimicking with one presynaptic input. The temporal and spatial summation functions, demonstrated by the v-FET presented here, could open interesting new avenues for development of neuromorphic electronic skin (v-skin) with possibility of biological-skin like distributed computing.

Two-dimensional halide perovskites are attracting attention due to their structural diversity, improved stability, and enhanced quantum efficiency compared to their three-dimensional counterparts. In particular, Dion-Jacobson (DJ) phase perovskites exhibit superior structural stability compared to Ruddlesden-Popper phase perovskites. The inherent quantum well structure of layered perovskites leads to highly anisotropic charge transport and optical properties. Therefore, controlling the preferred crystal orientation (parallel or perpendicular) is crucial for optimizing device performance. This work presents a rational strategy to control parallel and perpendicular crystal growth in C₆N₂H₁₆PbI₄ (4AMPPbI₄)-based DJ phase perovskite thin films. We demonstrate that crystal orientation depends on crystal growth rates, which can be controlled by varying the solvent composition, antisolvent, and annealing temperature. Direct and inverse photoelectron spectroscopy reveals that the electronic structure of 4AMPPbI₄, including its work function, ionization energy, and electron affinity, is orientation-dependent. Different orientations significantly affect carrier transport as confirmed by single-carrier devices. This study highlights the critical role of crystal orientation in DJ phase perovskites for designing high-performance optoelectronic devices.

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The advancement in high-performance computing technologies, including quantum and aerospace systems, necessitates components that operate efficiently at cryogenic temperatures. In this study, we demonstrate a hafnia-based ferroelectric tunnel junction (FTJ) that achieves a record-high tunneling electroresistance (TER) ratio of over 200,000 and decade-long retention characteristics. By introducing asymmetric oxygen vacancies through the strategic use of indium oxide (InO_x) layer, we enhance the TER ratio without increasing off-current, addressing the longstanding issue of low on-current in hafnia-based FTJs. Unlike prior approaches that led to leakage currents, our method optimizes tunneling behavior by leveraging the differential oxygen dissociation energy between InO_x and hafnium zirconium oxide (HZO). This results in asymmetric modulation of the tunnel barrier, enhancing electron tunneling in one polarization state while maintaining stability in the opposite state. Furthermore, we explore the intrinsic characteristics of the FTJ at cryogenic temperatures, where reduced thermal energy minimizes leakage currents and allows the maximization of device performance. These findings establish a new benchmark for TER in hafnia-based FTJs and provide valuable insights for the integration of these devices into advanced cryogenic memory systems.

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Perovskite solar cells (PSCs) have garnered significant attention for their high power conversion efficiency (PCE) and potential for cost-effective, large-scale manufacturing. This comprehensive review focuses on the role of buried interface engineering in enhancing the performance and stability of PSCs with both n-type electron transport layer/perovskite/p-type hole transport layer (n-i-p) and p-type hole transport layer/perovskite/n-type electron transport layer (p-i-n) structures. This study highlights key challenges associated with interface engineering, such as charge extraction, recombination loss, and energy level alignment. Various interface engineering techniques, such as surface passivation, self-assembled monolayers, and additive engineering, are explored in terms of their effectiveness in mitigating recombination loss and improving long-term device stability. This review also provides an in-depth analysis of material selection for the electron and hole transport layers, defect management techniques, and the influence of these on perovskite film quality and device stability. Advanced characterization methods for buried interfaces are discussed, providing insights into the structural, morphological, and electronic properties that govern device performance. Furthermore, we explore emerging approaches that target homogenous cation distribution and phase stability at buried interfaces, both of which are crucial for improving PCEs beyond current benchmarks. By synthesizing the latest research findings and identifying key challenges, this review aims to guide future directions in interface engineering for PSCs and ensure their successful use in next-generation sustainable energy technologies.

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Nanomaterials have emerged as transformative tools for detecting circulating tumor cells (CTCs) and circulating cancer stem cells (CCSCs), significantly enhancing cancer diagnostics and immunotherapy. Nanomaterials, including those composed of gold, magnetic materials, and silica, have enhanced the sensitivity, specificity, and efficiency of isolating these rare cells from blood. These developments are of paramount importance for the early detection of cancer and for providing real-time insights into metastasis and treatment resistance, which are essential for the development of personalized immunotherapies. The combination of nanomaterial-based platforms with phenotyping techniques, such as Raman spectroscopy and microfluidics, enables researchers to enhance immunotherapy protocols targeting specific CTC and CCSC markers. Nanomaterials also facilitate the targeted delivery of immunotherapeutic agents, including immune checkpoint inhibitors and therapeutic antibodies, directly to tumor cells. This synergistic approach has the potential to enhance therapeutic efficacy and mitigate the risk of metastasis and relapse. In conclusion, this review critically examines the use of nanomaterial-driven detection systems for detecting CTCs and CCSCs, their application in immunotherapy, and suggests future directions, highlighting their potential to transform the integration of diagnostics and treatment, thereby paving the way for more precise and personalized cancer therapies.

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