Strong dopant dependence of electric transport in ion-gated MoS2

We report modifications of the temperature-dependent transport properties of $\mathrm{MoS_2}$ thin flakes via field-driven ion intercalation in an electric double layer transistor. We find that intercalation with $\mathrm{Li^+}$ ions induces the onset of an inhomogeneous superconducting state. Intercalation with $\mathrm{K^+}$ leads instead to a disorder-induced incipient metal-to-insulator transition. These findings suggest that similar ionic species can provide access to different electronic phases in the same material.Comment: 5 pages, 3 figure

Polarized resonant emission of monolayer WS2 coupled with plasmonic sawtooth nanoslit array

Transition metal dichalcogenide (TMDC) monolayers have enabled important applications in light emitting devices and integrated nanophotonics because of the direct bandgap, spin-valley locking and highly tunable excitonic properties. Nevertheless, the photoluminescence polarization is almost random at room temperature due to the valley decoherence. Here, we show the room temperature control of the polarization states of the excitonic emission by integrating WS2 monolayers with a delicately designed metasurface, i.e. a silver sawtooth nanoslit array. The random polarization is transformed to linear when WS2 excitons couple with the anisotropic resonant transmission modes that arise from the surface plasmon resonance in the metallic nanostructure. The coupling is found to enhance the valley coherence that contributes to ~30% of the total linear dichroism. Further modulating the transmission modes by optimizing metasurfaces, the total linear dichroism of the plasmon-exciton hybrid system can approach 80%, which prompts the development of photonic devices based on TMDCs

Fourier sum of squares certificates

The non-negativity of a function on a finite abelian group can be certified by its Fourier sum of squares (FSOS). In this paper, we propose a method of certifying the non-negativity of an integer-valued function by an FSOS certificate, which is defined to be an FSOS with a small error. We prove the existence of exponentially sparse polynomial and rational FSOS certificates and we provide two methods to validate them. As a consequence of the aforementioned existence theorems, we propose a semidefinite programming (SDP)-based algorithm to efficiently compute a sparse FSOS certificate. For applications, we consider certificate problems for maximum satisfiability (MAX-SAT) and maximum k-colorable subgraph (MkCS) and demonstrate our theoretical results and algorithm by numerical experiments

Strong anisotropic enhancement of photoluminescence in WS₂ integrated with plasmonic nanowire array

Layered transition metal dichalcogenides (TMDCs) have shown great potential for a wide range of applications in photonics and optoelectronics. Nevertheless, valley decoherence severely randomizes its polarization which is important to a light emitter. Plasmonic metasurface with a unique way to manipulate the light-matter interaction may provide an effective and practical solution. Here by integrating TMDCs with plasmonic nanowire arrays, we demonstrate strong anisotropic enhancement of the excitonic emission at different spectral positions. For the indirect bandgap transition in bilayer WS2, multifold enhancement can be achieved with the photoluminescence (PL) polarization either perpendicular or parallel to the long axis of nanowires, which arises from the coupling of WS2 with localized or guided plasmon modes, respectively. Moreover, PL of high linearity is obtained in the direct bandgap transition benefiting from, in addition to the plasmonic enhancement, the directional diffraction scattering of nanowire arrays. Our method with enhanced PL intensity contrasts to the conventional form-birefringence based on the aspect ratio of nanowire arrays where the intensity loss is remarkable. Our results provide a prototypical plasmon-exciton hybrid system for anisotropic enhancement of the PL at the nanoscale, enabling simultaneous control of the intensity, polarization and wavelength toward practical ultrathin photonic devices based on TMDCs

Metallic ground state in an ion-gated two-dimensional superconductor

Recently emerging two-dimensional (2D) superconductors in atomically thin layers and at heterogeneous interfaces are attracting growing interest in condensed matter physics. Here, we report that an ion-gated zirconium nitride chloride surface, exhibiting a dome-shaped phase diagram with a maximum critical temperature of 14.8 kelvin, behaves as a superconductor persisting to the 2D limit. The superconducting thickness estimated from the upper critical fields is congruent to 1.8 nanometers, which is thinner than one unit-cell. The majority of the vortex phase diagram down to 2 kelvin is occupied by a metallic state with a finite resistance, owing to the quantum creep of vortices caused by extremely weak pinning and disorder. Our findings highlight the potential of electric-field-induced superconductivity, establishing a new platform for accessing quantum phases in clean 2D superconductors.</p

Geostatistical and stochastic study of radionuclide transport in the unsaturated zone at Yucca Mountain

Motivation: Why Study of Unsaturated Zone? The unsaturated zone (UZ), where the proposed repository would be located, acts as a critical natural barrier by delaying the arrival of radionuclides at the saturated zone and by reducing radionuclide concentrations in groundwater through dispersion and dilution Quantitative prediction of radionuclide transport in the unsaturated zone becomes critical for performance assessment and design of the proposed repository of the Yucca Mountain Projec

Possible charge-density-wave signatures in the anomalous resistivity of Li-intercalated multilayer MoS2

We fabricate ion-gated field-effect transistors (iFET) on mechanically exfoliated multilayer MoS$_2$. We encapsulate the flake by Al$_2$O$_3$, leaving the device channel exposed at the edges only. A stable Li$^+$ intercalation in the MoS$_2$ lattice is induced by gating the samples with a Li-based polymeric electrolyte above $\sim$ 330 K and the doping state is fixed by quenching the device to $\sim$ 300 K. This intercalation process induces the emergence of anomalies in the temperature dependence of the sheet resistance and its first derivative, which are typically associated with structural/electronic/magnetic phase transitions. We suggest that these anomalies in the resistivity of MoS$_2$ can be naturally interpreted as the signature of a transition to a charge-density-wave phase induced by lithiation, in accordance with recent theoretical calculations.Comment: 8 pages, 4 figure

Geostatistical and stochastic study of flow and tracer transport in the unsaturated zone at Yucca Mountain

Yucca Mountain has been proposed by the U.S. Department of Energy as the nation’s long-term, permanent geologic repository for spent nuclear fuel or high-level radioactive waste. The potential repository would be located in Yucca Mountain’s unsaturated zone (UZ), which acts as a critical natural barrier delaying arrival of radionuclides to the water table. Since radionuclide transport in groundwater can pose serious threats to human health and the environment, it is important to understand how much and how fast water and radionuclides travel through the UZ to groundwater. The UZ system consists of multiple hydrogeologic units whose hydraulic and geochemical properties exhibit systematic and random spatial variation, or heterogeneity, at multiple scales. Predictions of radionuclide transport under such complicated conditions are uncertain, and the uncertainty complicates decision making and risk analysis. This project aims at using geostatistical and stochastic methods to assess uncertainty of unsaturated flow and radionuclide transport in the UZ at Yucca Mountain. Focus of this study is parameter uncertainty of hydraulic and transport properties of the UZ. The parametric uncertainty arises since limited parameter measurements are unable to deterministically describe spatial variability of the parameters. In this project, matrix porosity, permeability and sorption coefficient of the reactive tracer (neptunium) of the UZ are treated as random variables. Corresponding propagation of parametric uncertainty is quantitatively measured using mean, variance, 5th and 95th percentiles of simulated state variables (e.g., saturation, capillary pressure, percolation flux, and travel time). These statistics are evaluated using a Monte Carlo method, in which a three-dimensional flow and transport model implemented using the TOUGH2 code is executed with multiple parameter realizations of the random model parameters

Accessing the transport properties of graphene and its multi-layers at high carrier density

We present a comparative study of high carrier density transport in mono-, bi-, and trilayer graphene using electric-double-layer transistors to continuously tune the carrier density up to values exceeding 10^{14} cm^{-2}. Whereas in monolayer the conductivity saturates, in bi- and trilayer flling of the higher energy bands is observed to cause a non-monotonic behavior of the conductivity, and a large increase in the quantum capacitance. These systematic trends not only show how the intrinsic high-density transport properties of graphene can be accessed by field-effect, but also demonstrate the robustness of ion-gated graphene, which is crucial for possible future applications.Comment: 4 figures, 4 page

Regularized Artificial Neural Network Training for Biased Data of Soil Hydraulic Parameters

Abstract: Development and application of artificial neural network (ANN) pedotransfer functions for estimating soil hydraulic properties (SHP) have become popular in the last two decades. However, limited availability of SHP training data often constrains the full potential of improved SHP estimation with ANN in many practical situations. In many situations, SHP data are limited and could be biased by samples from a restricted portion of the data population. Artificial neural network pedotransfer functions developed under such situations are likely to yield biased estimates. We proposed a direct approach to minimize mean estimation errors (bias) in such situations and developed a regularized ANN algorithm. The new algorithm revised the ANN error function and its gradients with respect to neural network outputs. We applied the new algorithm to synthetically generated SHP data representing different data availability situations and found that the newly developed algorithms were effective in reducing bias. Training with both the new and conventional mean square error functions resulted in equally good results in test phases when ANN models were trained with randomly sampled unbiased data. However, when ANN was trained with and applied to SHP data with respectively different means (biased sample), the proposed regularized ANN was highly effective in minimizing the bias when compared with ANN with the conventional mean square error function