MoS2 Nanoribbon Transistors: Transition from Depletion-mode to Enhancement-mode by Channel Width Trimming

We study the channel width scaling of back-gated MoS2 metal-oxide-semiconductor field-effect transistors (MOSFETs) from 2 {\mu}m down to 60 nm. We reveal that the channel conductance scales linearly with channel width, indicating no evident edge damage for MoS2 nanoribbons with widths down to 60 nm as defined by plasma dry etching. However, these transistors show a strong positive threshold voltage (VT) shift with narrow channel widths of less than 200 nm. Our results also show that transistors with thinner channel thicknesses have larger VT shifts associated with width scaling. Devices fabricated on a 6 nm thick MoS2 crystal underwent the transition from depletion-mode to enhancement-mode.Comment: 3 pages, 3 figures, to appear in IEEE Electron Device Letter

First Experimental Demonstration of Gate-all-around III-V MOSFET by Top-down Approach

The first inversion-mode gate-all-around (GAA) III-V MOSFETs are experimentally demonstrated with a high mobility In0.53Ga0.47As channel and atomic-layer-deposited (ALD) Al2O3/WN gate stacks by a top-down approach. A well-controlled InGaAs nanowire release process and a novel ALD high-k/metal gate process has been developed to enable the fabrication of III-V GAA MOSFETs. Well-behaved on-state and off-state performance has been achieved with channel length (Lch) down to 50nm. A detailed scaling metrics study (S.S., DIBL, VT) with Lch of 50nm - 110nm and fin width (WFin) of 30nm - 50nm are carried out, showing the immunity to short channel effects with the advanced 3D structure. The GAA structure has provided a viable path towards ultimate scaling of III-V MOSFETs.Comment: IEEE IEDM 2011 pp. 769-772; Structures are valuable for low-dimensional physics stud

Magneto-Transport in MoS2: Phase Coherence, Spin Orbit Scattering and the Hall Factor

We have characterized phase coherence length, spin orbit scattering length, and the Hall factor in n-type MoS2 2D crystals via weak localization measurements and Hall-effect measurements. Weak localization measurements reveal a phase coherence length of ~50 nm at T = 400 mK for a few-layer MoS2 film, decreasing as T^-1/2 with increased temperatures. Weak localization measurements also allow us, for the first time without optical techniques, to estimate the spin orbit scattering length to be 430 nm, pointing to the potential of MoS2 for spintronics applications. Via Hall-effect measurements, we observe a low temperature Hall mobility of 311 cm2/Vs at T = 1 K which decreases as a power law with a characteristic exponent {\gamma}=1.5 from 10 K to 60 K. At room temperature, we observe Hall mobility of 24 cm2/Vs. By determining the Hall factor for MoS2 to be 1.35 at T = 1 K and 2.4 at room temperature, we observe drift mobility of 420 cm2/Vs and 56 cm2/Vs at T = 1 K and room temperature, respectively.Comment: ACS Nano nn402377

Variability Improvement by Interface Passivation and EOT Scaling of InGaAs Nanowire MOSFETs

High-performance InGaAs gate-all-around (GAA) nanowire MOSFETs with channel length ($L_{ch}$) down to 20 nm are fabricated by integrating a higher-k $LaAlO_3$-based gate-stack with an equivalent oxide thickness of 1.2nm. It is found that inserting an ultrathin (0.5 nm) $Al_2O_3$ interfacial layer between the higher k $LaAlO_3$ and InGaAs can significantly improve the interface quality and reduce device variation. As a result, a record low subthreshold swing of 63 mV/dec is demonstrated at sub-80-nm $L_{ch}$ for the first time, making InGaAs GAA nanowire devices a strong candidate for future low-power transistors.Chemistry and Chemical Biolog

Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls

Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies

Quantum-Hall plateau-plateau transition in top-gated epitaxial graphene grown on SiC (0001)

We investigate the low-temperature magneto-transport properties of monolayer epitaxial graphene films formed on the Si-face of semi-insulating 4H-SiC substrates by a high temperature sublimation process. A high-k top-gate on the epitaxial graphene is realized by inserting a fully oxidized nanometer thin aluminum film as a seeding layer, followed by an atomic layer deposition process. At low temperatures, the devices demonstrate a strong field effect by the top gate with an on/off ratio of ~7 and an electron mobility up to ~3250 cm^2/Vs. After the observation of the half-integer quantum Hall effect for monolayer epitaxial graphene films, detailed magneto-transport measurements have been carried out including varying densities, temperatures, magnetic fields and currents. We study the width of the distinguishable quantum-Hall plateau to plateau transition (Landau level index n=0 to n=1) as temperature (T) and current are varied. For both gate voltage and magnetic field sweeps and T>10 K the transition width goes as T^{-\kappa} with exponent \kappa ~0.42. This universal scaling exponent agrees well with those found in III-V heterojunctions with short range alloy disorders and in exfoliated graphene.Comment: accepted by Journal of Applied Physic

Altered metabolite levels and correlations in patients with colorectal cancer and polyps detected using seemingly unrelated regression analysis

Introduction: Metabolomics technologies enable the identification of putative biomarkers for numerous diseases; however, the influence of confounding factors on metabolite levels poses a major challenge in moving forward with such metabolites for pre-clinical or clinical applications. Objectives: To address this challenge, we analyzed metabolomics data from a colorectal cancer (CRC) study, and used seemingly unrelated regression (SUR) to account for the effects of confounding factors including gender, BMI, age, alcohol use, and smoking. Methods: A SUR model based on 113 serum metabolites quantified using targeted mass spectrometry, identified 20 metabolites that differentiated CRC patients (n = 36), patients with polyp (n = 39), and healthy subjects (n = 83). Models built using different groups of biologically related metabolites achieved improved differentiation and were significant for 26 out of 29 groups. Furthermore, the networks of correlated metabolites constructed for all groups of metabolites using the ParCorA algorithm, before or after application of the SUR model, showed significant alterations for CRC and polyp patients relative to healthy controls. Results: The results showed that demographic covariates, such as gender, BMI, BMI2, and smoking status, exhibit significant confounding effects on metabolite levels, which can be modeled effectively. Conclusion: These results not only provide new insights into addressing the major issue of confounding effects in metabolomics analysis, but also shed light on issues related to establishing reliable biomarkers and the biological connections between them in a complex disease

Targeted serum metabolite profiling and sequential metabolite ratio analysis for colorectal cancer progression monitoring

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide and a major cause of human morbidity and mortality. In addition to early detection, close monitoring of disease progression in CRC can be critical for patient prognosis and treatment decisions. Efforts have been made to develop new methods for improved early detection and patient monitoring; however, research focused on CRC surveillance for treatment response and disease recurrence using metabolomics has yet to be reported. In this proof of concept study, we applied a targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) metabolic profiling approach focused on sequential metabolite ratio analysis of serial serum samples to monitor disease progression from 20 CRC patients. The use of serial samples reduces patient to patient metabolic variability. A partial least squares-discriminant analysis (PLS-DA) model using a panel of five metabolites (succinate, N2, N2-dimethylguanosine, adenine, citraconic acid, and 1-methylguanosine) was established, and excellent model performance (sensitivity = 0.83, specificity = 0.94, area under the receiver operator characteristic curve (AUROC) = 0.91 was obtained, which is superior to the traditional CRC monitoring marker carcinoembryonic antigen (sensitivity = 0.75, specificity = 0.76, AUROC = 0.80). Monte Carlo cross validation was applied, and the robustness of our model was clearly observed by the separation of true classification models from the random permutation models. Our results suggest the potential utility of metabolic profiling for CRC disease monitoring

Polyethyleneimine-coated MXene quantum dots improve cotton tolerance to Verticillium dahliae by maintaining ROS homeostasis

Verticillium dahliae is a soil-borne hemibiotrophic fungal pathogen that threatens cotton production worldwide. In this study, we assemble the genomes of two V. dahliae isolates: the more virulence and defoliating isolate V991 and nondefoliating isolate 1cd3-2. Transcriptome and comparative genomics analyses show that genes associated with pathogen virulence are mostly induced at the late stage of infection (Stage II), accompanied by a burst of reactive oxygen species (ROS), with upregulation of more genes involved in defense response in cotton. We identify the V991-specific virulence gene SP3 that is highly expressed during the infection Stage II. V. dahliae SP3 knock-out strain shows attenuated virulence and triggers less ROS production in cotton plants. To control the disease, we employ polyethyleneimine-coated MXene quantum dots (PEI-MQDs) that possess the ability to remove ROS. Cotton seedlings treated with PEI-MQDs are capable of maintaining ROS homeostasis with enhanced peroxidase, catalase, and glutathione peroxidase activities and exhibit improved tolerance to V. dahliae. These results suggest that V. dahliae trigger ROS production to promote infection and scavenging ROS is an effective way to manage this disease. This study reveals a virulence mechanism of V. dahliae and provides a means for V. dahliae resistance that benefits cotton production