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Abstract Litterfall load is crucial in maintaining ecosystem health, controlling wildfires, and estimating carbon stock in arid regions. However, there is a lack of spatiotemporal analysis of litterfall in arid riparian forests. This study aims to estimate Litterfall load using a BP neural network based on vegetation indices from Landsat 5 and 8 satellite images, litterfall inventory data, slope, and distance to major river tributaries. It also aims to analyze the spatiotemporal distribution pattern of litter in the research area by estimating and analyzing the spatiotemporal pattern of litterfall along the desert riparian forests of the lower Qarqan and Tarim Rivers from 2001 to 2021. The results show that the initiation of the ecological water transfer project has facilitated the decomposition of litterfall, leading to an initial decline. Subsequently, the vegetation gradually recovered, leading to an increase in leaf litter input. Since 2001, litterfall initially decreased until reaching its lowest value of 4.39 × 109 kg in 2005, followed by a subsequent increase, reaching its highest value of 12.5 × 109 kg in 2021. The study concludes that ecological water conveyance promotes both the decomposition and increase of litterfall. Initially, it accelerates litterfall decomposition, while later stages foster an increase in Litterfall load. Meanwhile, due to the ecological water transfer project and the higher vegetation cover along the Tarim River compared to the Qarqan River, the Tarim River basin experiences higher average Litterfall load and variation.

The presence of ammonia in exhaled human breath serves as a crucial biomarker for renal diseases. This paper presents a highly sensitive ammonia sensor operable at room temperature, utilizing a Ti/Zr dual metal MOF as its core component, synthesized through a straightforward solvothermal reaction approach. The Ti/Zr-MOF demonstrates excellent responsiveness to ammonia gas, with a detection limit of remarkable sensitivity, reaching as low as 2 ppm. Notably, the sensor exhibits practical insensitivity to similar concentrations of other major interfering breath volatiles, including acetone, ethanol, and saturated moisture. Electron Paramagnetic Resonance (EPR) analysis confirms the presence of oxygen vacancies (Ov) in Ti/Zr-MOF materials, with Ti/Zr-MOF exhibiting stronger Ov signals and the potential for enhanced NH3 adsorption and capture. In-situ FTIR spectrum analysis reveals ammonia-induced -OH (H2O) moiety formation, indicating a reaction between adsorbed O2− species and ammonia, resulting in decreased electrical resistance of Ti/Zr-MOF.

Abstract Van der Waals (vdW) assembly of low-dimensional materials has proven the capability of creating structures with on-demand properties. It is predicted that the vdW encapsulation can induce a local high-pressure of a few GPa, which will strongly modify the structure and property of trapped materials. Here, we report on the structural collapse of carbon nanotubes (CNTs) induced by the vdW encapsulation. By simply covering CNTs with a hexagonal boron nitride flake, most of the CNTs (≈77%) convert from a tubular structure to a collapsed flat structure. Regardless of their original diameters, all the collapsed CNTs exhibit a uniform height of ≈0.7 nm, which is roughly the thickness of bilayer graphene. Such structural collapse is further confirmed by Raman spectroscopy, which shows a prominent broadening and blue shift in the Raman G-peak. The vdW encapsulation-induced collapse of CNTs is fully captured by molecular dynamics simulations of the local vdW pressure. Further near-field optical characterization reveals a metal-semiconductor transition in accompany with the CNT structural collapse. Our study provides not only a convenient approach to generate local high-pressure for fundamental research, but also a collapsed-CNT semiconductor for nanoelectronic applications.

Abstract Stacking order plays a crucial role in determining the crystal symmetry and has significant impacts on electronic, optical, magnetic, and topological properties. Electron-phonon coupling, which is central to a wide range of intriguing quantum phenomena, is expected to be intricately connected with stacking order. Understanding the stacking order-dependent electron-phonon coupling is essential for understanding peculiar physical phenomena associated with electron-phonon coupling, such as superconductivity and charge density waves. In this study, we investigate the effect of stacking order on electron-infrared phonon coupling in graphene trilayers. By using gate-tunable Raman spectroscopy and excitation frequency-dependent near-field infrared nanoscopy, we show that rhombohedral ABC-stacked trilayer graphene has a significant electron-infrared phonon coupling strength. Our findings provide novel insights into the superconductivity and other fundamental physical properties of rhombohedral ABC-stacked trilayer graphene, and can enable nondestructive and high-throughput imaging of trilayer graphene stacking order using Raman scattering.

Abstract Graphene nanoribbons (GNRs) are narrow strips of graphene with widths ranging from a few nanometers to a few tens of nanometers. GNRs possess most of the excellent properties of graphene, while also exhibiting unique physical characteristics not found in graphene, such as an adjustable band gap and spin-polarized edge states. These properties make GNRs an appealing candidate for carbon-based electronics. In this review, we begin by introducing the edge geometry and electronic bands of GNRs. We then discuss various methods for fabricating GNRs and analyze the characteristics of each method. Subsequently, the performance of GNR field-effect transistor devices obtained from a few representative GNR fabrication methods is discussed and compared. We also investigate the use of GNRs as quantum dots and spintronic devices. Finally, the challenges and opportunities of GNRs as a quantum material for next-generation electronics and spintronics are explored and proposed.

Ethylene glycol is odorless and harmful to humans. Each year, a large number of fatal cases are caused by ethylene glycol poisoning. Therefore, rapid identification of ethylene glycol is crucial. In this study, clay-like Ti3C2Tx MXene exhibits a larger interlayer spacing compared to accordion-like Ti3C2Tx MXene, which enhances the gas diffusion channels. Nitrogen doping can increase the active sites of clay-like Ti3C2Tx MXene. The introduction of nitrogen-doped carbon nanotubes into N-Ti3C2Tx was carried out to enhance selectivity towards ethylene glycol, leading to the formation of N-Ti3C2Tx MXene/N-CNTs. The N-Ti3C2Tx MXene/N-CNTs exhibits significant selectivity towards the ethylene glycol at room temperature. Meanwhile, the detection limit was 0.3484 ppm, with a shortened response/recovery time of 10.57/6.29 s. Meanwhile, the ethylene glycol sensor device has been prepared through custom-made circuit boards and sensing programs. Moreover, the adsorption and oxidation process of ethylene glycol on N-Ti3C2Tx MXene/N-CNTs was explored through in-situ infrared spectroscopy testing. This study revealed that the oxygen vacancies on the surface of N-Ti3C2Tx MXene/N-CNTs play a crucial role in the oxidative catalytic detection of ethylene glycol. The strategy of N-Ti3C2Tx MXene/N-CNTs provides a new avenue for the detection of ethylene glycol.

Abstract Homologous recombination deficiency (HRD) causes faulty double-strand break repair and is a prevalent cause of tumorigenesis. However, the incidence of HRD and its clinical significance in pan-cancer patients remain unknown. Using computational analysis of Single-nucleotide polymorphism array data from 10,619 cancer patients, we demonstrate that HRD frequently occurs across multiple cancer types. Analysis of the pan-cancer cohort revealed that HRD is not only a biomarker for ovarian cancer and triple-negative breast cancer, but also has clinical prognostic value in numerous cancer types, including adrenocortical cancer and thymoma. We discovered that homologous recombination–related genes have a high mutation or deletion frequency. Pathway analysis shows HRD is positively correlated with the DNA damage response and the immune-related signaling pathways. Single cell RNA sequencing of tumor-infiltrating lymphocytes reveals a significantly higher proportion of exhausted T cells in HRD patients, indicating pre-existing immunity. Finally, HRD could be utilized to predict pan-cancer patients’ responses to Programmed cell death protein 1 immunotherapy. In summary, our work establishes a comprehensive map of HRD in pan-cancer. The findings have significant implications for expanding the scope of Poly ADP-ribose polymerase inhibitor therapy and, possibly, immunotherapy.

Abstract Graphene nanoribbons (GNRs) and carbon nanotubes (CNTs), two representative one-dimensional (1D) graphitic materials, have attracted tremendous research interests due to their promising applications for future high-performance nanoelectronics. Although various methods have been developed for fabrication of GNRs or CNTs, a unified method allowing controllable synthesis of both of them, as well as their heterojunctions, which could largely benefit their nano-electronic applications, is still lacking. Here, we report on a generic growth of 1D carbon using nanoparticles catalyzed chemical vapor deposition (CVD) on atomically flat hexagonal boron nitride (h-BN) substrates. Relative ratio of the yielded GNRs and CNTs is able to be arbitrarily tuned by varying the growth temperature or feeding gas pressures. The tunability of the generic growth is quantitatively explained by a competing nucleation theory: nucleation into either GNRs or CNTs by the catalysts is determined by the free energy of their formation, which is controlled by the growth conditions. Under the guidance of the theory, we further realized growth of GNR/CNT intramolecular junctions through changing H2 partial pressure during a single growth process. Our study provides not only a universal and controllable method for growing 1D carbon nanostructures, but also a deep understanding of their growth mechanism, which would largely benefit future carbon-based electronics and optoelectronics.

Abstract The electrical and optical properties of twisted bilayer graphene (tBLG) depend sensitively on the twist angle. To study the angle dependent properties of the tBLG, currently it is required fabrication of a large number of samples with systematically varied twist angles. Here, we demonstrate the construction of in-situ twistable bilayer graphene, in which the twist angle of the two graphene monolayers can be in-situ tuned continuously in a large range with high precision. The controlled tuning of the twist angle is confirmed by a combination of real-space and spectroscopic characterizations, including atomic force microscopy (AFM) identification of crystal lattice orientation, scanning near-field optical microscopy (SNOM) imaging of superlattice domain walls, and resonant Raman spectroscopy of the largely enhanced G-mode. The developed in-situ twistable homostructure devices enable systematic investigation of the twist angle effects in a single device, thus could largely advance the research of twistronics.

The interplay between strong correlations and topology can lead to the emergence of intriguing quantum states of matter. One well-known example is the fractional quantum Hall effect, where exotic electron fluids with fractionally charged excitations form in partially filled Landau levels. The emergence of topological moiré flat bands provides exciting opportunities to realize the lattice analogs of both the integer and fractional quantum Hall effects without the need for an external magnetic field. These effects are known as the integer and fractional quantum anomalous Hall (IQAH and FQAH) effects. Here, we present direct transport evidence of the existence of both IQAH and FQAH effects in small-angle-twisted bilayer MoTe_{2}. At zero magnetic field, we observe well-quantized Hall resistance of h/e^{2} around moiré filling factor ν=−1 (corresponding to one hole per moiré unit cell), and nearly quantized Hall resistance of 3h/2e^{2} around ν=−2/3, respectively. Concomitantly, the longitudinal resistance exhibits distinct minima around ν=−1 and −2/3. The application of an electric field induces topological quantum phase transition from the IQAH state to a charge transfer insulator at ν=−1, and from the FQAH state to a topologically trivial correlated insulator, further transitioning to a metallic state at ν=−2/3. Our study paves the way for the investigation of fractionally charged excitations and anyonic statistics at zero magnetic field based on semiconductor moiré materials.

Abstract Introduction Cervical cancer has high mortality, high recurrence and poor prognosis. Although prognostic biomarkers such as clinicopathological features have been proposed, their accuracy and precision are far from satisfactory. Therefore, novel biomarkers are urgently needed for disease surveillance, prognosis prediction and treatment selection. Materials Differentially expressed genes (DEGs) between cervical cancer and normal tissues from three microarray datasets extracted from the Gene Expression Omnibus platform were identified and screened. Based on these DEGs, a six‐gene prognostic signature was constructed using cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas. Next, the molecular functions and related pathways of the six genes were investigated through gene set enrichment analysis and co‐expression analysis. Additionally, immunophenoscore analysis and the QuartataWeb Server were employed to explore the therapeutic value of the six‐gene signature. Results We discovered 178 overlapping DEGs in three microarray datasets and established a six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) prognostic signature with stable and excellent performance in predicting overall survival in different subgroups. Intriguingly, the six‐gene signature was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature might be used for predicting response to immune checkpoint inhibitors (ICIs) and the six genes may serve as new drug targets for cervical cancer. Conclusion Our study established a novel six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) signature that was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature was indicative of aggressive features of cervical cancer and therefore might serve as a promising biomarker for predicting not only overall survival but also ICI treatment effectiveness. Moreover, three genes (UPP1, ISG20 and GLTP) within the six‐gene signature have the potential to become novel drug targets.

Computer-aided drug design is an efficient method to analyze the development of disease-related drugs. However, developed as binding targets, medicines perform well in cell models and animal models but fail in human models. One main reason for this failure is that the human body has natural barriers, such as the blood-brain barrier, to block exogenous macromolecules. Thus, efficient and accurate predictions of drug molecules that can effectively pass the blood-brain barrier is necessary in developing drug treatments for brain tissue diseases. In this study, 7658 molecular structure features were extracted from 2354 drug molecule SMILE strings using computational methods. By integrating three feature selection algorithms of machine learning, 33 chemical structure features with significantly discriminant performance were screened out and used to construct multiple discriminant models. After a comprehensive comparison, the XGBoost model was selected as the final prediction model. After data preprocessing and parameter optimization, the model achieved 95% accuracy on the training set. To verify the model's stability, we introduced an external data set, which reached 96% accuracy of the model. This study applies new resampling methods and machine learning algorithms, and adjusts the application of resampling methods to obtain new chemical features to construct machine learning predictors. The features may contribute to the significant drug development that integrates biological analysis and machine learning algorithms.

The Glioma-associated oncogene (Gli) family members of zinc finger DNA-binding proteins are core effectors of Sonic hedgehog (SHH) signaling pathway. Studies in model organisms have identified that the Gli genes play critical roles during organ development, including the heart, brain, kidneys, etc. Deleterious mutations in GLI genes have previously been revealed in several human developmental disorders, but few in congenital heart disease (CHD). In this study, the mutations in GLI1-3 genes were captured by next generation sequencing in human cohorts composed of 412 individuals with CHD and 213 ethnically matched normal controls. A total of 20 patient-specific nonsynonymous rare mutations in coding regions of human GLI1-3 genes were identified. Functional analyses showed that GLI1 c.820G> T (p.G274C) is a gain-of-function mutation, while GLI1 c.878G>A (p.R293H) and c.1442T>A (p.L481X) are loss-of-function mutations. Our findings suggested that deleterious rare mutations in GLI1 gene broke the balance of the SHH signaling pathway regulation and may constitute a great contribution to human CHD, which shed new light on understanding genetic mechanism of embryo cardiogenesis regulated by SHH signaling.

Mixtures of nonfullerene acceptors (NFAs) are prepared to fine‐tune bulk heterojunction (BHJ) thin‐film morphologies. The acceptor phase resulting from these mixtures has unique physical properties with excellent optoelectronic processes that dictate the output of organic photovoltaic (OPV) devices. Remarkable short‐circuit current densities (JSC) and fill factors (FFs) are achieved due to the formation of better crystalline fibrils that suppress geminate recombination, leading to improved charge transport with enhanced crystallinity and aligned cascading energy levels confirm efficient exciton diffusion and dissociation, yielding more effective exciton recycling. The decreased Urbach energy and suppressed energetic disorder account for the improvement in the open‐circuit voltage (VOC). A maximum power conversion efficiency of 17.86% is obtained, underscoring the importance of using specific material interactions to produce a suitable morphology and manage energy loss, resulting in ideal organic solar cell (OSC) devices.

Abstract The donor/acceptor interaction in non‐fullerene organic photovoltaics leads to the mixing domain that dictates the morphology and electronic structure of the blended thin film. Initiative effort is paid to understand how these domain properties affect the device performances on high‐efficiency PM6:Y6 blends. Different fullerenes acceptors are used to manipulate the feature of mixing domain. It is seen that a tight packing in the mixing region is critical, which could effectively enhance the hole transfer and lead to the enlarged and narrow electron density of state (DOS). As a result, short‐circuit current (JSC) and fill factor (FF) are improved. The distribution of DOS and energy levels strongly influences open‐circuit voltage (VOC). The raised filling state of electron Fermi level is seen to be key in determining device VOC. Energy disorder is found to be a key factor to energy loss, which is highly correlated with the intermolecular distance in the mixing region. A 17.53% efficiency is obtained for optimized ternary devices, which is the highest value for similar systems. The current results indicate that a delicate optimization of the mixing domain property is an effective route to improve the VOC, JSC, and FF simultaneously, which provides new guidelines for morphology control toward high‐performance organic solar cells.

ABC-stacked trilayer graphene has exhibited a variety of correlated phenomena owing to its relatively flat bands and gate-tunable bandgap. However, convenient methods are still lacking for identifying ABC graphene with nanometer-scale resolution. Here we demonstrate that the scanning near-field optical microscope working in ambient conditions can provide quick recognition of ABC trilayer graphene with no ambiguity and excellent resolution (∼20 nm). The recognition is based on the difference in their near-field infrared (IR) responses between the ABA and ABC trilayers. We show that in most frequencies, the response of the ABC trilayer is weaker than the ABA trilayer. However, near the graphene phonon frequency (∼1585 cm ^−1 ), ABC’s response increases dramatically when gated and exhibits a narrow and sharp Fano-shape resonant line, whereas the ABA trilayer is largely featherless. Consequently, the IR contrast between ABC and ABA becomes reversed and can even be striking (ABC/ABA ∼ 3) near the graphene phonon frequency. The observed near-field IR features can serve as a golden rule to quickly distinguish ABA and ABC trilayers with no ambiguity, which could largely advance the exploration of correlation physics in ABC-stacked trilayer graphene.

Abstract Background Tight control of endosome trafficking is essential for the generation of a normally patterned embryo. Recent studies have found that VPS50 is a key ingredient in EARP which is required for recycling of internalized TfRs to the cell surface and dense-core vesicle maturation. However, the role of VPS50 in embryogenesis and human physiology are poorly understood. Results We identified a rare missense heterozygous VPS50 mutation (p. Gly169Val) in NTDs by high-throughput sequencing. In vitro functional analysis demonstrated that the p. Gly169Val was a loss-of-function mutation, delaying transferrin recycling and altering its interaction with VPS53. Using WISH during zebrafish embryogenesis, we demonstrated that vps50 gene was expressed throughout the early embryo, especially in the head. Abnormal body axis phenotypes were observed in those vps50 knock-down zebrafishes. Further rescue study in zebrafish suggested that the mutation displayed loss-of-function effects comparing with wild-type VPS50. Conclusions These findings thus demonstrated that the functional mutations in VPS50 might contribute to neurodevelopmental disorder and highlighted the critical importance of VPS50 function in cellular and organismal physiology.

Abstract Ovarian cancer patients with homologous recombination deficiency (HRD) tumors would benefit from PARP inhibitor (PARPi) therapy. However, patients with HRD tumors account for less than 50% of the whole cohort, so new biomarkers still need to be developed. Based on the data from the SNP array and somatic mutation profiles in the ovarian cancer genome, we found that high frequency of actionable mutations existed in patients with non‐HRD tumors. Through transcriptome analysis, we identified that a downstream target of the cGAS‐STING pathway, CXCL11, was upregulated in HRD tumors and could be used as a predictor of survival outcome. Further comprehensive analysis of the tumor immune microenvironment (TIME) revealed that CXCL11 expression signature was closely correlated with cytotoxic cells, neoantigen load and immune checkpoint blockade (ICB). Clinical trial data confirmed that the expression of CXCL11 could be used as a biomarker for anti‐PD‐1/PD‐L1 therapy. Finally, in vivo and in vitro experiments showed that cancer cells with PARPi treatment increased the expression of CXCL11. Collectively, our study not only provides biomarkers of ovarian cancer complementary to the HRD score but also introduces a potential new perspective for identifying prognostic biomarkers of immunotherapy.

Background: Machine learning (ML) has been gradually integrated into oncologic research but seldom applied to predict cervical cancer (CC), and no model has been reported to predict survival and site-specific recurrence simultaneously. Thus, we aimed to develop ML models to predict survival and site-specific recurrence in CC and to guide individual surveillance. Methods: We retrospectively collected data on CC patients from 2006 to 2017 in four hospitals. The survival or recurrence predictive value of the variables was analyzed using multivariate Cox, principal component, and K-means clustering analyses. The predictive performances of eight ML models were compared with logistic or Cox models. A novel web-based predictive calculator was developed based on the ML algorithms. Results: This study included 5112 women for analysis (268 deaths, 343 recurrences): (1) For site-specific recurrence, larger tumor size was associated with local recurrence, while positive lymph nodes were associated with distant recurrence. (2) The ML models exhibited better prognostic predictive performance than traditional models. (3) The ML models were superior to traditional models when multiple variables were used. (4) A novel predictive web-based calculator was developed and externally validated to predict survival and site-specific recurrence. Conclusion: ML models might be a better analytic approach in CC prognostic prediction than traditional models as they can predict survival and site-specific recurrence simultaneously, especially when using multiple variables. Moreover, our novel web-based calculator may provide clinicians with useful information and help them make individual postoperative follow-up plans and further treatment strategies.

Streaking of photoelectrons with optical lasers has been widely used for temporal characterization of attosecond extreme ultraviolet pulses. Recently, this technique has been adapted to characterize femtosecond x-ray pulses in free-electron lasers with the streaking imprinted by far-infrared and terahertz (THz) pulses. Here, we report successful implementation of THz streaking for time stamping of an ultrashort relativistic electron beam, whose energy is several orders of magnitude higher than photoelectrons. Such an ability is especially important for MeV ultrafast electron diffraction (UED) applications, where electron beams with a few femtosecond pulse width may be obtained with longitudinal compression, while the arrival time may fluctuate at a much larger timescale. Using this laser-driven THz streaking technique, the arrival time of an ultrashort electron beam with a 6-fs (rms) pulse width has been determined with 1.5-fs (rms) accuracy. Furthermore, we have proposed and demonstrated a noninvasive method for correction of the timing jitter with femtosecond accuracy through measurement of the compressed beam energy, which may allow one to advance UED towards a sub-10-fs frontier, far beyond the approximate 100-fs (rms) jitter.

Objective: To study the effects of transcutaneous electrical acupoint stimulation (TEAS) on length of stay (LOS) and hospitalization costs in postoperative inpatients. Methods: Two researchers collectively searched PubMed, Embase, Cochrane Library, China Network Knowledge Infrastructure, and Wanfang Database. The search time was set from the beginning to 25 April 2023, to identify randomized controlled trials articles that met the criteria. Statistical analyses were performed using the Stata software (version 16.0). The risk of bias was assessed using the Cochrane risk-of-bias tool, and publication bias was evaluated using a funnel plot and Egger's test. The quality of evidence was assessed according to the Grading of Recommendations Assessment, Development, and Evaluation approach. Results: Thirty-four randomized controlled trials were included. The main results showed that TEAS reduced hospitalization costs [standardized mean difference (SMD) = - 1.92; 95% CI: -3.40, -0.43), LOS (SMD= -1.00; 95% CI: - 1.30, - 0.70) and postoperative LOS (SMD= -0.70; 95% CI: - 0.91, - 0.49] in postoperative patients. Subgroup analyses further revealed that TEAS was effective in reducing both the overall and postoperative LOS in patients undergoing multiple surgical procedures. It is worth noting that the observed heterogeneity in the results may be attributed to variations in surgical procedures, stimulation frequencies, and stimulation points utilized in different trials. Conclusions: TEAS can help postoperative patients reduce their LOS and hospitalization cost. However, considering the bias identified and heterogeneity, the results of this review should be interpreted with caution. [ABSTRACT FROM AUTHOR]

High performance infrared light emitting diodes (LEDs) have drawn wide attention because of their significant applications in biomedicine, agriculture, aquaculture, night vision security systems and scientific researches. Due to the rapid development of infrared up-conversion devices, especially in the terahertz region, the studies on the GaAs-based infrared LEDs operating at low temperature (<20 K) are quite needed. In this paper, two representative GaAs-based LEDs (GaAs/AlGaAs double heterostructure LED (DH-LED) and GaAs (InGaAs)/AlGaAs quantum well infrared LED (QW-LED)) are fabricated and characterized with electroluminescence (EL) spectroscopy and electroluminescence efficiency (ELE) at different temperatures. The ELE of the QW-LED is about 70% higher at low temperatures (<150 K) but lower at high temperatures (>150 K) than that of the DH-LED. A developed rate equation method is used to analyze the ELE superiority of the QW-LED. Finally, the surface EL uniformity of the two LEDs is studied by using the charge coupled devices imaging. This study provides a guidance to choose and design LED structures for different operation temperatures. [ABSTRACT FROM AUTHOR]

Single-walled carbon nanotubes (SWCNTs), due to their outstanding electrical and optical properties, are expected to have extensive applications, such as in transparent conductive films and ultra-small field-effect transistors (FETs). However, those applications can only be best realized with pure metallic or pure semiconducting SWCNTs. Hence, identifying and separating metallic from semiconducting SWCNTs in as-grown samples are crucial. In addition, knowledge of the type of an SWCNT is also important for further exploring its new properties in fundamental science. Here we report employing scanning near-field optical microscopy (SNOM) as a direct and simple method to identify metallic and semiconducting SWCNTs on SiO2/Si substrates. Metallic and semiconducting SWCNTs show distinct near-field optical responses because the metallic tubes support plasmons whereas the semiconducting tubes do not. The reliability of this method is verified using FET testing and Rayleigh scattering spectroscopy. Our result demonstrates that the SNOM technique provides a reliable, simple, noninvasive and in situ method to distinguish between metallic and semiconducting SWCNTs. [ABSTRACT FROM AUTHOR]

Transferring high-quality exfoliated graphene flakes onto different substrates while keeping the graphene free of polymer residues is of great importance, but at the same time very challenging. Currently, the only feasible way is the so-called all-dry “pick-and-lift” method, in which a hexagonal boron nitride (hBN) flake is employed to serve as a stamp to pick up graphene from one substrate and to lift it down onto another substrate. The transferred graphene samples, however, are always covered or encapsulated by hBN flakes, which leads to difficulties in further characterizations. Here, we report an improved “pick-and-lift” method, which allows ultra-clean graphene flakes to be transferred onto a variety of substrates without hBN coverage. Basically, by exploiting the superlubricity at the graphene/hBN stack interface, we are able to remove the top-layer hBN stamp by applying a tangential force and expose the underneath graphene. [ABSTRACT FROM AUTHOR]