Deep Self-Reconstruction Fusion Similarity Hashing for the Diagnosis of Alzheimer's Disease on Multi-Modal Data.

The pathogenesis of Alzheimer's disease (AD) is extremely intricate, which makes AD patients almost incurable. Recent studies have demonstrated that analyzing multi-modal data can offer a comprehensive perspective on the different stages of AD progression, which is beneficial for early diagnosis of AD. In this paper, we propose a deep self-reconstruction fusion similarity hashing (DS-FSH) method to effectively capture the AD-related biomarkers from the multi-modal data and leverage them to diagnose AD. Given that most existing methods ignore the topological structure of the data, a deep self-reconstruction model based on random walk graph regularization is designed to reconstruct the multi-modal data, thereby learning the nonlinear relationship between samples. Additionally, a fused similarity hash based on anchor graph is proposed to generate discriminative binary hash codes for multi-modal reconstructed data. This allows sample fused similarity to be effectively modeled by a fusion similarity matrix based on anchor graph while modal correlation can be approximated by Hamming distance. Especially, extracted features from the multi-modal data are classified using deep sparse autoencoders classifier. Finally, experiments conduct on the AD Neuroimaging Initiative database show that DS-FSH outperforms comparable methods of AD classification. To conclude, DS-FSH identifies multi-modal features closely associated with AD, which are expected to contribute significantly to understanding of the pathogenesis of AD.

Direct fabrication of high-quality vertical graphene nanowalls on arbitrary substrates without catalysts for tidal power generation.

The non-catalytic preparation of high-quality vertical graphene nanowalls (VGN) and graphene-based high output power hydrovoltaic effect power generation devices has always been difficult to achieve. In this work, we successfully prepared VGN with defect density, few layers and submicron domain size on a variety of substrates without catalysts through reasonable adjustment of growth conditions by the hot-wire chemical vapor deposition (HWCVD) method. The Raman test of the VGN prepared under optimal conditions showed that its ID/IG value was less than 1, and I2D/IG was more than 2.8. The deposition pressure was a key factor affecting the crystallization quality of the VGN. A suitable deposition pressure of 500 Pa could screen the active carbon clusters involved in the growth of nanowalls. The VGN prepared had excellent electrical properties and output of dropping-ion-droplet nano-power generation devices. Because of the larger crystal domain area and smaller contact angle of the VGN, the maximum output power exhibited at 100 Pa was 15.7 µW, which exceeded the value produced by other reported hydrovoltaic energy harvesting devices. All of them confirmed that VGN with improved quality had high application prospects in nano-energy devices.

Minimizing the Programming Power of Phase Change Memory by Using Graphene Nanoribbon Edge-Contact.

Nonvolatile phase-change random access memory (PCRAM) is regarded as one of the promising candidates for emerging mass storage in the era of Big Data. However, relatively high programming energy hurdles the further reduction of power consumption in PCRAM. Utilizing narrow edge-contact of graphene can effectively reduce the active volume of phase change material in each cell, and therefore realize low-power operation. Here, it demonstrates that the power consumption can be reduced to ≈53.7 fJ in a cell with ≈3 nm-wide graphene nanoribbon (GNR) as edge-contact, whose cross-sectional area is only ≈1 nm2 . It is found that the polarity of the bias pulse determines its cycle endurance in the asymmetric structure. If a positive bias is applied to the graphene electrode, the endurance can be extended at least one order longer than the case with a reversal of polarity. In addition, the introduction of the hexagonal boron nitride (h-BN) multilayer leads to a low resistance drift and a high programming speed in a memory cell. The work represents a great technological advance for the low-power PCRAM and can benefit in-memory computing in the future.

Oxidizing Hexagonal Boron Nitride into Fluorescent Structures by Photodissociated Directional Oxygen Radical.

Modifying the wide band gap semiconductor hexagonal boron nitride (hBN) can bring new chances in photonics. By virtue of the solvothermal/hydrothermal oxidation or functionalization, hBN can be converted into fluorescent nanodots. Until now, it has been a big challenge to drily oxidize hBN and turn it into bright fluorescent structures due to its superior chemical stability. Here, we report the oxidation of multilayer hBN into fluorescent structures by ultraviolet (UV, λ = 172 nm) photodissociated directional oxygen radical [O(3P)] in a gradient magnetic field. The paramagnetic O(3P), produced in a low-pressure O2 atmosphere, drifts toward hBN and then converts it into boron nitride oxide (BNO) micro/nanometer structures constituted by BO, BO2, and O-doped hBN. For a properly oxidized BNO substance, bright and photostable wide-band photoluminescence is realized with nanosecond-scaled lifetimes under the excitation of UV and visible lights.

Near Room-Temperature Synthesis of Vertical Graphene Nanowalls on Dielectrics.

Vertical graphene nanowalls (VGNs) with excellent heat-transfer properties are promising to be applied in the thermal management of electronic devices. However, high growth temperature makes VGNs unable to be directly prepared on semiconductors and polymers, which limits the practical application of VGNs. In this work, the near room-temperature growth of VGNs was realized by utilizing the hot filament chemical vapor deposition method. Catalytic tantalum (Ta) filaments promote the decomposition of acetylene at ∼1600 °C. Density functional theory calculations proved that C2H* was the main active carbon cluster during VGN growth. The restricted diffusion of C2H* clusters induced the vertical growth of graphene nanoflakes on various substrates below 150 °C. The direct growth of VGNs successfully realized the excellent interfacial contact, and the thermal contact resistance could reach 3.39 × 10-9 m2·K·W-1. The temperature of electronic chips had a 6.7 °C reduction by utilizing directly prepared VGNs instead of thermal conductive tape as thermal-interface materials, indicating the great potential of VGNs to be directly prepared on electronic devices for thermal management.

Advanced Data Encryption ​using 2D Materials.

Advanced data encryption requires the use of true random number generators (TRNGs) to produce unpredictable sequences of bits. TRNG circuits with high degree of randomness and low power consumption may be fabricated by using the random telegraph noise (RTN) current signals produced by polarized metal/insulator/metal (MIM) devices as entropy source. However, the RTN signals produced by MIM devices made of traditional insulators, i.e., transition metal oxides like HfO2 and Al2 O3 , are not stable enough due to the formation and lateral expansion of defect clusters, resulting in undesired current fluctuations and the disappearance of the RTN effect. Here, the fabrication of highly stable TRNG circuits with low power consumption, high degree of randomness (even for a long string of 224  - 1 bits), and high throughput of 1 Mbit s-1 by using MIM devices made of multilayer hexagonal boron nitride (h-BN) is shown. Their application is also demonstrated to produce one-time passwords, which is ideal for the internet-of-everything. The superior stability of the h-BN-based TRNG is related to the presence of few-atoms-wide defects embedded within the layered and crystalline structure of the h-BN stack, which produces a confinement effect that avoids their lateral expansion and results in stable operation.

Towards chirality control of graphene nanoribbons embedded in hexagonal boron nitride.

The integrated in-plane growth of graphene nanoribbons (GNRs) and hexagonal boron nitride (h-BN) could provide a promising route to achieve integrated circuitry of atomic thickness. However, fabrication of edge-specific GNRs in the lattice of h-BN still remains a significant challenge. Here we developed a two-step growth method and successfully achieved sub-5-nm-wide zigzag and armchair GNRs embedded in h-BN. Further transport measurements reveal that the sub-7-nm-wide zigzag GNRs exhibit openings of the bandgap inversely proportional to their width, while narrow armchair GNRs exhibit some fluctuation in the bandgap-width relationship. An obvious conductance peak is observed in the transfer curves of 8- to 10-nm-wide zigzag GNRs, while it is absent in most armchair GNRs. Zigzag GNRs exhibit a small magnetic conductance, while armchair GNRs have much higher magnetic conductance values. This integrated lateral growth of edge-specific GNRs in h-BN provides a promising route to achieve intricate nanoscale circuits.

MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations.

BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs with regulatory functions. Many studies have shown that miRNAs are closely associated with human diseases. Among the methods to explore the relationship between the miRNA and the disease, traditional methods are time-consuming and the accuracy needs to be improved. In view of the shortcoming of previous models, a method, collaborative matrix factorization based on matrix completion (MCCMF) is proposed to predict the unknown miRNA-disease associations. RESULTS: The complete matrix of the miRNA and the disease is obtained by matrix completion. Moreover, Gaussian Interaction Profile kernel is added to the miRNA functional similarity matrix and the disease semantic similarity matrix. Then the Weight K Nearest Known Neighbors method is used to pretreat the association matrix, so the model is close to the reality. Finally, collaborative matrix factorization method is applied to obtain the prediction results. Therefore, the MCCMF obtains a satisfactory result in the fivefold cross-validation, with an AUC of 0.9569 (0.0005). CONCLUSIONS: The AUC value of MCCMF is higher than other advanced methods in the fivefold cross validation experiment. In order to comprehensively evaluate the performance of MCCMF, accuracy, precision, recall and f-measure are also added. The final experimental results demonstrate that MCCMF outperforms other methods in predicting miRNA-disease associations. In the end, the effectiveness and practicability of MCCMF are further verified by researching three specific diseases.

Vacancy-Assisted Growth Mechanism of Multilayer Hexagonal Boron Nitride on a Fe2B Substrate.

The controllable synthesis of large-area and uniform hexagonal boron nitride (h-BN) films has been recently achieved on metal-boron alloy catalysts with the use of N2 feedstock, representing important progress in an economic and environmentally friendly process. However, the systematic investigation of the growth mechanism is still lacking, which impedes the further development of this method. In this work, on the basis of density functional theory (DFT) calculations and experiments, we reveal the vacancy-assisted growth mechanism of h-BN on Fe2B substrate. It is found that B vacancies created by the formation of BN dimers play important roles in the migration of B and N atoms near the catalyst surface. The diffusions of B and N atoms in the Fe2B substrate need to overcome energy barriers of only less than 1.5 eV, which enables abundant dissolution of N atoms near the catalytic surface. Moreover, we found the critical barrier for h-BN growth is in the nucleation stage, which is ∼2 eV. These advantages enable the synthesis of h-BN at a low temperature of 700 K in our experiments. This vacancy-assisted growth of h-BN films on Fe2B substrates is beneficial to the wafer-scale fabrication of multilayer materials, paving the way to potential applications in two-dimensional electronic and optoelectronic devices.

Vapor-liquid-solid growth of large-area multilayer hexagonal boron nitride on dielectric substrates.

Multilayer hexagonal boron nitride (h-BN) is highly desirable as a dielectric substrate for the fabrication of two-dimensional (2D) electronic and optoelectronic devices. However, the controllable synthesis of multilayer h-BN in large areas is still limited in terms of crystallinity, thickness and stacking order. Here, we report a vapor-liquid-solid growth (VLSG) method to achieve uniform multilayer h-BN by using a molten Fe82B18 alloy and N2 as reactants. Liquid Fe82B18 not only supplies boron but also continuously dissociates nitrogen atoms from the N2 vapor to support direct h-BN growth on a sapphire substrate; therefore, the VLSG method delivers high-quality h-BN multilayers with a controllable thickness. Further investigation of the phase evolution of the Fe-B-N system reveals that isothermal segregation dominates the growth of the h-BN. The approach herein demonstrates the feasibility for large-area fabrication of van der Waals 2D materials and heterostructures.

Epitaxial Growth of 6 in. Single-Crystalline Graphene on a Cu/Ni (111) Film at 750 °C via Chemical Vapor Deposition.

The future electronic application of graphene highly relies on the production of large-area high-quality single-crystal graphene. However, the growth of single-crystal graphene on different substrates via either single nucleation or seamless stitching is carried out at a temperature of 1000 °C or higher. The usage of this high temperature generates a variety of problems, including complexity of operation, higher contamination, metal evaporation, and wrinkles owing to the mismatch of thermal expansion coefficients between the substrate and graphene. Here, a new approach for the fabrication of ultraflat single-crystal graphene using Cu/Ni (111)/sapphire wafers at lower temperature is reported. It is found that the temperature of epitaxial growth of graphene using Cu/Ni (111) can be reduced to 750 °C, much lower than that of earlier reports on catalytic surfaces. Devices made of graphene grown at 750 °C have a carrier mobility up to ≈9700 cm2 V-1 s-1 at room temperature. This work shines light on a way toward a much lower temperature growth of high-quality graphene in single crystallinity, which could benefit future electronic applications.

Controlled synthesis of uniform multilayer hexagonal boron nitride films on Fe2B alloy.

Two-dimensional (2D) hexagonal boron nitride (h-BN) is highly appreciated for its excellent insulating performance and absence of dangling bonds, which could be employed to maintain the intrinsic properties of 2D materials. However, controllable synthesis of large scale multilayer h-BN is still very challenging. Here, we demonstrate chemical vapor deposition (CVD) growth of multilayer h-BN by using iron boride (Fe2B) alloy and nitrogen (N2) as precursors. Different from the self-limited growth mechanism of monolayer h-BN on catalytic metal surfaces, with sufficient B source in the bulk, Fe2B alloy promotes the controllable isothermal segregation of multilayer h-BN by reacting with active N atoms on the surface of the substrate. Microscopic and spectroscopic characterizations prove the high uniformity and crystalline quality of h-BN with a highly orientated layered lattice structure. The achievement of large scale multilayer h-BN in this work would facilitate its applications in 2D electronics and optoelectronics in the future.

How Low Nucleation Density of Graphene on CuNi Alloy is Achieved.

CuNi alloy foils are demonstrated to be one of the best substrates for synthesizing large area single-crystalline graphene because a very fast growth rate and low nucleation density can be simultaneously achieved. The fast growth rate is understood to be due the abundance of carbon precursor supply, as a result of the high catalytic activity of Ni atoms. However, a theoretical understanding of the low nucleation density remains controversial because it is known that a high carbon precursor concentration on the surface normally leads to a high nucleation density. Here, the graphene nucleation on the CuNi alloy surfaces is systematically explored and it is revealed that: i) carbon atom dissolution into the CuNi alloy passivates the alloy surface, thereby drastically increasing the graphene nucleation barrier; ii) carbon atom diffusion on the CuNi alloy surface is greatly suppressed by the inhomogeneous atomic structure of the surface; and iii) a prominent increase in the rate of carbon diffusion into the bulk occurs when the Ni composition is higher than the percolation threshold. This study reveals the key mechanism for graphene nucleation on CuNi alloy surfaces and provides a guideline for the catalyst design for the synthesis of graphene and other 2D materials.

Dielectric Breakdown in Chemical Vapor Deposited Hexagonal Boron Nitride.

Insulating films are essential in multiple electronic devices because they can provide essential functionalities, such as capacitance effects and electrical fields. Two-dimensional (2D) layered materials have superb electronic, physical, chemical, thermal, and optical properties, and they can be effectively used to provide additional performances, such as flexibility and transparency. 2D layered insulators are called to be essential in future electronic devices, but their reliability, degradation kinetics, and dielectric breakdown (BD) process are still not understood. In this work, the dielectric breakdown process of multilayer hexagonal boron nitride (h-BN) is analyzed on the nanoscale and on the device level, and the experimental results are studied via theoretical models. It is found that under electrical stress, local charge accumulation and charge trapping/detrapping are the onset mechanisms for dielectric BD formation. By means of conductive atomic force microscopy, the BD event was triggered at several locations on the surface of different dielectrics (SiO2, HfO2, Al2O3, multilayer h-BN, and monolayer h-BN); BD-induced hillocks rapidly appeared on the surface of all of them when the BD was reached, except in monolayer h-BN. The high thermal conductivity of h-BN combined with the one-atom-thick nature are genuine factors contributing to heat dissipation at the BD spot, which avoids self-accelerated and thermally driven catastrophic BD. These results point to monolayer h-BN as a sublime dielectric in terms of reliability, which may have important implications in future digital electronic devices.

Synthesis of High-Quality Graphene and Hexagonal Boron Nitride Monolayer In-Plane Heterostructure on Cu-Ni Alloy.

Graphene/hexagonal boron nitride (h-BN) monolayer in-plane heterostructure offers a novel material platform for both fundamental research and device applications. To obtain such a heterostructure in high quality via controllable synthetic approaches is still challenging. In this work, in-plane epitaxy of graphene/h-BN heterostructure is demonstrated on Cu-Ni substrates. The introduction of nickel to copper substrate not only enhances the capability of decomposing polyaminoborane residues but also promotes graphene growth via isothermal segregation. On the alloy surface partially covered by h-BN, graphene is found to nucleate at the corners of the as-formed h-BN grains, and the high growth rate for graphene minimizes the damage of graphene-growth process on h-BN lattice. As a result, high-quality graphene/h-BN in-plane heterostructure with epitaxial relationship can be formed, which is supported by extensive characterizations. Photodetector device applications are demonstrated based on the in-plane heterostructure. The success will have important impact on future research and applications based on this unique material platform.

Edge control of graphene domains grown on hexagonal boron nitride.

The edge structure of graphene has a significant influence on its electronic properties. However, control over the edge structure of graphene domains on insulating substrates is still challenging. Here we demonstrate edge control of graphene domains on hexagonal boron nitride (h-BN) by modifying the ratio of working-gases. Edge directions were determined with the help of both moiré patterns and atomic-resolution images obtained via atomic force microscopy measurements. It is believed that the variation of graphene edges is mainly attributed to different growth rates of armchair and zigzag edges. This work demonstrates a potential approach to fabricate smooth-edge graphene ribbons on h-BN.

Application of sodium-ion-based solid electrolyte in electrostatic tuning of carrier density in graphene.

Using a solid electrolyte to tune the carrier density in thin-film materials is an emerging technique that has potential applications in both basic and applied research. Until now, only materials containing small ions, such as protons and lithium ions, have been used to demonstrate the gating effect. Here, we report the study of a lab-synthesised sodium-ion-based solid electrolyte, which shows a much stronger capability to tune the carrier density in graphene than previously reported lithium-ion-based solid electrolyte. Our findings may stimulate the search for solid electrolytes better suited for gating applications, taking benefit of many existing materials developed for battery research.

Oriented graphene nanoribbons embedded in hexagonal boron nitride trenches.

Graphene nanoribbons (GNRs) are ultra-narrow strips of graphene that have the potential to be used in high-performance graphene-based semiconductor electronics. However, controlled growth of GNRs on dielectric substrates remains a challenge. Here, we report the successful growth of GNRs directly on hexagonal boron nitride substrates with smooth edges and controllable widths using chemical vapour deposition. The approach is based on a type of template growth that allows for the in-plane epitaxy of mono-layered GNRs in nano-trenches on hexagonal boron nitride with edges following a zigzag direction. The embedded GNR channels show excellent electronic properties, even at room temperature. Such in-plane hetero-integration of GNRs, which is compatible with integrated circuit processing, creates a gapped channel with a width of a few benzene rings, enabling the development of digital integrated circuitry based on GNRs.

Copper-Vapor-Assisted Rapid Synthesis of Large AB-Stacked Bilayer Graphene Domains on Cu-Ni Alloy.

The synergic effects of Cu85Ni15 and the copper vapor evaporated from copper foil enabled the fast growth of a ≈300 µm bilayer graphene in ≈10 minutes. The copper vapor reduces the growth rate of the first graphene layer while the carbon dissolved in the alloy boosts the growth of the subsequently developed second graphene layer with an AB-stacking order.

Fast growth of inch-sized single-crystalline graphene from a controlled single nucleus on Cu-Ni alloys.

Wafer-scale single-crystalline graphene monolayers are highly sought after as an ideal platform for electronic and other applications. At present, state-of-the-art growth methods based on chemical vapour deposition allow the synthesis of one-centimetre-sized single-crystalline graphene domains in ∼12 h, by suppressing nucleation events on the growth substrate. Here we demonstrate an efficient strategy for achieving large-area single-crystalline graphene by letting a single nucleus evolve into a monolayer at a fast rate. By locally feeding carbon precursors to a desired position of a substrate composed of an optimized Cu-Ni alloy, we synthesized an ∼1.5-inch-large graphene monolayer in 2.5 h. Localized feeding induces the formation of a single nucleus on the entire substrate, and the optimized alloy activates an isothermal segregation mechanism that greatly expedites the growth rate. This approach may also prove effective for the synthesis of wafer-scale single-crystalline monolayers of other two-dimensional materials.