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The edges of 2D materials have emerged as promising electrochemical catalyst systems, yet their performance still lags behind that of noble metals. Here, we demonstrate the potential of oriented electric fields (OEFs) to enhance the electrochemical activity of 2D materials edges. By atomically engineering the edge of a fluorographene/graphene/MoS2 heterojunction nanoribbon, strong and localized OEFs were realized as confirmed by simulations and spatially resolved spectroscopy. The observed fringing OEF results in an enhancement of the heterogeneous charge transfer rate between the edge and the electrolyte by 2 orders of magnitude according to impedance spectroscopy. Ab initio calculations indicate a field-induced decrease in the reactant adsorption energy as the origin of this improvement. We apply the OEF-enhanced edge reactivity to hydrogen evolution reactions (HER) and observe a significantly enhanced electrochemical performance, as evidenced by a 30% decrease in Tafel slope and a 3-fold enhanced turnover frequency. Our findings demonstrate the potential of OEFs for tailoring the catalytic properties of 2D material edges toward future complex reactions.
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Two-dimensional (2D) materials promise advances in electronic devices beyond Moore's scaling law through extended functionality, such as non-monotonic dependence of device parameters on input parameters. However, the robustness and performance of effects like negative differential resistance (NDR) and anti-ambipolar behavior have been limited in scale and robustness by relying on atomic defects and complex heterojunctions. In this paper, we introduce a novel device concept that utilizes the quantum capacitance of junctions between 2D materials and molecular layers. We realized a variable capacitance 2D molecular junction (vc2Dmj) diode through the scalable integration of graphene and single layers of stearic acid. The vc2Dmj exhibits NDR with a substantial peak-to-valley ratio even at room temperature and an active negative resistance region. The origin of this unique behavior was identified through thermoelectric measurements and ab initio calculations to be a hybridization effect between graphene and the molecular layer. The enhancement of device parameters through morphology optimization highlights the potential of our approach toward new functionalities that advance the landscape of future electronics.
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Molybdenum disulfide (MoS2) has emerged as a promising material for catalysis and sustainable energy conversion. However, the inertness of its basal plane to electrochemical reactions poses challenges to the utilization of wafer-scale MoS2 in electrocatalysis. To overcome this limitation, we present a technique that enhances the catalytic activity of continuous MoS2 by preferentially activating its buried grain boundaries (GBs). Through mild UV irradiation, a significant enhancement in GB activity was observed that approaches the values for MoS2 edges, as confirmed by a site-selective photo-deposition technique and micro-electrochemical hydrogen evolution reaction (HER) measurements. Combined spectroscopic characterization and ab-initio simulation demonstrates substitutional oxygen functionalization at the grain boundaries to be the origin of this selective catalytic enhancement by an order of magnitude. Our approach not only improves the density of active sites in MoS2 catalytic processes but yields a new photocatalytic conversion process. By exploiting the difference in electronic structure between activated GBs and the basal plane, homo-compositional junctions were realized that improve the photocatalytic synthesis of hydrogen by 47% and achieve performances beyond the capabilities of other catalytic sites.
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Two-dimensional (2D) materials are promising successors for silicon transistor channels in ultimately scaled devices, necessitating significant research efforts to study their behavior at nanoscopic length scales. Unfortunately, current research has limited itself to direct patterning approaches, which limit the achievable resolution to the diffraction limit and introduce unwanted defects into the 2D material. The potential of multi-patterning to fabricate 2D materials features with unprecedented precision and low complexity at large scale is demonstrated here. By combining lithographic patterning of a mandrel and bottom-up self-expansion, this approach enables pattern resolution one order of magnitude below the lithographical resolution. In-depth characterization of the self-expansion double patterning (SEDP) process reveals the ability to manipulate the critical dimension with nanometer precision through a self-limiting and temperature-controlled oxidation process. These results indicate that the SEDP process can regain the quality and morphology of the 2D material, as shown by high-resolution microscopy and optical spectroscopy. This approach is shown to open up new avenues for research into high-performance, ultra-scaled 2D materials devices for future electronics.
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Two-dimensional transition metal nitrides offer intriguing possibilities for achieving novel electronic and mechanical functionality owing to their distinctive and tunable bonding characteristics compared to other 2D materials. We demonstrate here the enabling effects of strong bonding on the morphology and functionality of 2D tungsten nitrides. The employed bottom-up synthesis experienced a unique substrate stabilization effect beyond van-der-Waals epitaxy that favored W5N6 over lower metal nitrides. Comprehensive structural and electronic characterization reveals that monolayer W5N6 can be synthesized at large scale and shows semimetallic behavior with an intriguing indirect band structure. Moreover, the material exhibits exceptional resilience against mechanical damage and chemical reactions. Leveraging these electronic properties and robustness, we demonstrate the application of W5N6 as atomic-scale dry etch stops that allow the integration of high-performance 2D materials contacts. These findings highlight the potential of 2D transition metal nitrides for realizing advanced electronic devices and functional interfaces.
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Two-dimensional (2D) metal nitrides have garnered significant interest due to their potential applications in future electronics and quantum systems. However, the synthesis of such materials with sufficient uniformity and at relevant scales remains an unaddressed challenge. This study demonstrates the potential of confined growth to control and enhance the morphology of 2D metal nitrides. By restricting the reaction volume of vapor-liquid-solid reactions, an enhanced precursor concentration was achieved that reduces the nucleation density, resulting in larger grain sizes and suppression of multilayer growth. Detailed characterization reveals the importance of balancing the energetic and kinetic aspects of tungsten nitride formation toward this ability. The introduction of a promoter enabled the realization of large-scale, single-layer tungsten nitride with a uniform and high interfacial quality. Finally, our advance in morphology control was applied to the production of edge-enriched 2D tungsten nitrides with significantly enhanced hydrogen evolution ability, as indicated by an unprecedented Tafel slope of 55 mV/dec.
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Two-dimensional (2D) material-based nanoelectromechanical (NEM) resonators are expected to be enabling components in hybrid qubits that couple mechanical and electromagnetic degrees of freedom. However, challenges in their sensitivity and coherence time have to be overcome to realize such mechanohybrid quantum systems. We here demonstrate the potential of strain engineering to realize 2D material-based resonators with unprecedented performance. A liquid-based tension process was shown to enhance the resonance frequency and quality factor of graphene resonators six-fold. Spectroscopic and microscopic characterization reveals a surface-energy enhanced wall interaction as the origin of this effect. The response of our tensioned resonators is not limited by external loss factors and exhibits near-ideal internal losses, yielding superior resonance frequencies and quality factors to all previously reported 2D material devices. Our approach represents a powerful method of enhancing 2D NEM resonators for future quantum systems.
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Motor Imagery-based Brain Computer Interface (MI-BCI) is a typical active BCI with a main focus on motor intention identification. Hybrid motor imagery (MI) decoding methods that based on multi-modal fusion of Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), especially deep learning-based methods, become popular in recent MI-BCI studies. However, the fusion strategy and network design in deep learning-based methods are complex. To solve this problem, we proposed the multi-channel fusion method (MCF) to simplify current fusion methods, and we designed a multi-channel fusion hybrid network (MCFHNet) based on MCF. MCFHNet combines depthwise convolutional layers, channel attention mechanism, and Bidirectional Long Short Term Memory (Bi-LSTM) layers, which enables strong capability of feature extraction in spatial and temporal domain. The comparison between MCFHNet and representative deep learning-based methods was performed on an open EEG-fNIRS dataset. We found the proposed method can yield superior performance (mean accuracy of 99.641 % in 5-fold cross validation of an intra-subject experiment). This work provides a new option for multi-modal MI decoding, which can be applied in the rehabilitation field based on hybrid BCI systems.
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Interfaces Cérebro-Computador , Medicina , Eletroencefalografia , Imagens, Psicoterapia , Análise EspectralRESUMO
Clarifying the process of formation of diversity hotspots and the biogeographic connection between regions is critical in understanding the impact of environmental changes on organismal evolution. Polygonatum (Asparagaceae) is distributed across the Northern Hemisphere. It displays an uneven distribution, with more than 50% of its species occurring in the Himalaya-Hengduan Mountains (HHM). Here, we generated a time-calibrated phylogeny of Polygonatum, based on whole-plastome data, to reconstruct the genus' biogeographical history and morphological/chromosomal evolution. Our phylogenetic analyses strongly support the monophyly of Polygonatum and its division into three sections (i.e., Verticillata, Sibirica, and Polygonatum). Polygonatum originated from the HHM region during the early-Miocene (c. 20.10 Ma), and began to radiate since the mid-Miocene, driven by the uplift of the Qinghai-Tibet Plateau (QTP), increasingly colder/arid climates following the mid-Miocene Climatic Optimum (MMCO), and intensification of the East Asian winter monsoon. Dispersal from the HHM region to other regions was facilitated by the intensification of East Asian summer monsoon in response to global climatic warming during the MMCO. Decreasing dysploidy accompanied by karyotype change and polyploidization in Polygonatum appears to be associated with its diversification and colonization of new ecological niches. Our results highlight the importance of regional tectonic activities and past climatic changes from the Neogene onwards to the spatial-temporal diversification and distribution patterns of plant lineages with a wide distribution in the Northern Hemisphere. They also contribute to the knowledge of the uneven species richness between East Asia and other regions.
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Asparagaceae , Polygonatum , Ecossistema , Filogenia , Filogeografia , PlantasRESUMO
Background: Lung cancer is the leading cause of mortality in cancer patients. N7-methylguanosine (m7G) modification as a translational regulation pattern has been reported to participate in multiple types of cancer progression, but little is known in lung cancer. This study attempts to explore the role of m7G-related proteins in genetic and epigenetic variations in lung adenocarcinoma, and its relationship with clinical prognosis, immune infiltration, and immunotherapy. Methods: Sequencing data were obtained from the Genomic Data Commons (GDC) Data Portal and Gene Expression Omnibus (GEO) databases. Consensus clustering was utilized to distinguish m7G clusters, and responses to immunotherapy were also evaluated. Moreover, univariate and multivariate Cox and Least absolute shrinkage and selection operator LASSO Cox regression analyses were used to screen independent prognostic factors and generated risk scores for constructing a survival prediction model. Multiple cell types such as epithelial cells and immune cells were identified to verify the bulk RNA results. Short hairpin RNA (shRNA) Tet-on plasmids, Clustered Regularly Interspaced Short Palindromic Repeats CRISPR/Cas9 for knockout plasmids, and nucleoside diphosphate linked to moiety X-type motif 4 (NUDT4) overexpression plasmids were constructed to inhibit or promote tumor cell NUDT4 expression, then RT-qPCR, Cell Counting Kit-8 CCK8 proliferation assay, and Transwell assay were used to observe tumor cell biological functions. Results: Fifteen m7G-related genes were highly expressed in tumor samples, and 12 genes were associated with poor prognosis. m7G cluster-B had lower immune infiltration level, worse survival, and samples that predicted poor responses to immunotherapy. The multivariate Cox model showed that NUDT4 and WDR4 (WD repeat domain 4) were independent risk factors. Single-cell m7G gene set variation analysis (GSVA) scores also had a negative correlation tendency with immune infiltration level and T-cell Programmed Death-1 PD-1 expression, but the statistics were not significant. Knocking down and knocking out the NUDT4 expression significantly inhibited cell proliferation capability in A549 and H1299 cells. In contrast, overexpressing NUDT4 promoted tumor cell proliferation. However, there was no difference in migration capability in the knockdown, knockout, or overexpression groups. Conclusions: Our study revealed that m7G modification-related proteins are closely related to the tumor microenvironment, immune cell infiltration, responses to immunotherapy, and patients' prognosis in lung adenocarcinoma and could be useful biomarkers for the identification of patients who could benefit from immunotherapy. The m7G modification protein NUDT4 may be a novel biomarker in promoting the progression of lung cancer.
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We here report on the direct observation of ferroelectric properties of water ice in its 2D phase. Upon nanoelectromechanical confinement between two graphene layers, water forms a 2D ice phase at room temperature that exhibits a strong and permanent dipole which depends on the previously applied field, representing clear evidence for ferroelectric ordering. Characterization of this permanent polarization with respect to varying water partial pressure and temperature reveals the importance of forming a monolayer of 2D ice for ferroelectric ordering which agrees with ab-initio and molecular dynamics simulations conducted. The observed robust ferroelectric properties of 2D ice enable novel nanoelectromechanical devices that exhibit memristive properties. A unique bipolar mechanical switching behavior is observed where previous charging history controls the transition voltage between low-resistance and high-resistance state. This advance enables the realization of rugged, non-volatile, mechanical memory exhibiting switching ratios of 106, 4 bit storage capabilities and no degradation after 10,000 switching cycles.
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We here demonstrate the multifunctional properties of atomically thin heterojunctions that are enabled by their strong interfacial interactions and their application toward self-powered sensors with unprecedented performance. Bonding between tin diselenide and graphene produces thermoelectric and mechanoelectric properties beyond the ability of either component. A record-breaking ZT of 2.43 originated from the synergistic combination of graphene's high carrier conductivity and SnSe2-mediated thermal conductivity lowering. Moreover, spatially varying interaction at the SnSe2/graphene interface produces stress localization that results in a novel 2D-crack-assisted strain sensing mechanism whose sensitivity (GF = 450) is superior to all other 2D materials. Finally, a graphene-assisted growth process permits the formation of high-quality heterojunctions directly on polymeric substrates for flexible and transparent sensors that achieve self-powered strain sensing from a small temperature gradient. Our work enhances the fundamental understanding of multifunctionality at the atomic scale and provides a route toward structural health monitoring through ubiquitous and smart devices.
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Grafite , Dispositivos Eletrônicos Vestíveis , Condutividade Elétrica , Polímeros , TemperaturaRESUMO
Lateral heterojunctions in two-dimensional (2D) materials have demonstrated potential for high-performance sensors because of the unique electrostatic conditions at the interface. The increased complexity of producing such structures, however, has prevented their widespread use. We here demonstrate the simple and scalable fabrication of heterojunctions by a one-step synthesis process that yields photodetectors with superior device performance. Catalytic conversion of a solid precursor at optimized conditions was found to produce lateral nanostructured junctions between graphene domains and 3 nm thin amorphous carbon films. Carrier transport in these heterojunctions was found to proceed by minimizing the path through the amorphous carbon barriers, which results in a self-selective Schottky emission process with high uniformity and low emission barriers. We demonstrate the potential of thus produced heterojunctions by realizing a photodetector that combines an ultrahigh detectivity of 1013 Jones with microsecond response time, which represents the highest performance of 2D material heterojunction devices. These attractive features are retained even for millimeter-scale devices, and the demonstrated ability to produce transparent, patterned, and flexible sensors extends lateral heterojunction sensors toward wearable and large-scale electronics.
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Light-based information processing has the potential to increase speed, security, and scalability of electronic devices if issues in the device complexity could be resolved. We here demonstrate an integrated nanoelectronic device that can combine, store, and manipulate optical and electronic information. Employing a mechanically flexible and multilayered structure, a device is realized that shows memristive behavior. Illumination is shown to control the device operation in several unique ways. First, the device produces photocurrent that allows us to read out the device state in a self-powered manner. More importantly, a varying light intensity modulates the switching transition in a proportional manner that is akin to a neuron with variable plasticity and which can be taught and queried using either light or electrical inputs. This behavior enables a multilevel light-controlled logic and teaching schemes that can be applied to light-based communication devices and provides a route toward ubiquitous and low-cost sensors for future internet of things applications.
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Barrier-guided CVD growth could provide a new route to printed electronics by combining high quality 2D materials synthesis with scalable and cost-effective deposition methods. Unfortunately, we observe the limited stability of the barrier at growth conditions which results in its removal within minutes due to hydrogen etching. This work describes a route towards enhancing the stability of an ink-jet deposited barrier for high resolution patterning of high quality graphene. By modifying the etching kinetics under confinement, the barrier film could be stabilized and high resolution barriers could be retained even after 6 hours of graphene growth. Thus produced microscopic graphene devices exhibited an increase in conductivity by 6 orders of magnitude and a decrease in defectiveness by 48 times yielding performances that are superior to devices produced by traditional lithographical patterning which indicates the potential of our approach for future electronic applications.