arXiv subjects

Ming Chen

Publications and source records attributed to Ming Chen.

At least 127 records · Page 7Linked to original sources

arXiv2020

Enforced freedom: electric-field-induced declustering of ionic-liquid ions in the double layer

Whereas the majority of ions in the bulk of a solvent-free ionic liquid is bound into clusters, this is expected to change in the electrical double layer (EDL), in which the resulting electric field 'prefers' to interact with electrical monopoles-free, unclustered ions. The competition between the propensity of ions to stay in a clustered state and the reduction of the energy of ions in electric field in the free state determines the resulting portion of free ions in the EDL. We present a study of this effect, based on the simplest possible mean-field theory. 'Cracking' of ion clusters into individual ions in electric field is accompanied by the change of the dielectric response of ionic liquid which is different in clustered and unclustered states. The predictions of the theory are verified and further explored by specially performed molecular dynamics simulations. A particular finding of the theory is that the differential capacitance vs potential curve displays a bell shape despite low concentration of free charge carriers, because the dielectric response of bound ions reduces the threshold concentration of the bell- to camel-shape transition. Whereas qualitatively these findings make perfect sense, in reality the exact numbers and criteria might be different as the presented simple theory does not take into account overscreening and oscillating charge and electrostatic potential distributions near the electrode. This is why testing the theory with computer simulations is essential, but the latter basically reproduce the qualitative conclusions of the theory.

physics.chem-ph↗

arXiv2020

Dopant levels in large nanocrystals using stochastic optimally tuned range-separated hybrid density functional theory

We apply a stochastic version of an optimally tuned range-separated hybrid functional to provide insight on the electronic properties of P- and B- doped Si nanocrystals of experimentally relevant sizes. We show that we can use the range-separation parameter for undoped systems to calculate accurate results for dopant activation energies. We apply this strategy for tuning functionals to study doped nanocrystals up to 2.5 nm in diameter at the hybrid functional level. In this confinement regime, the P- and B- dopants have large activation energies and have strongly localized states that lie deep within the energy gaps. Structural relaxation plays a greater role for B-substituted dopants and contributes to the increase in activation energy when the B dopant is near the nanocrystal surface.

cond-mat.mtrl-sci↗

arXiv2020

AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations

Deep learning based recommender systems (DLRSs) often have embedding layers, which are utilized to lessen the dimensionality of categorical variables (e.g. user/item identifiers) and meaningfully transform them in the low-dimensional space. The majority of existing DLRSs empirically pre-define a fixed and unified dimension for all user/item embeddings. It is evident from recent researches that different embedding sizes are highly desired for different users/items according to their popularity. However, manually selecting embedding sizes in recommender systems can be very challenging due to the large number of users/items and the dynamic nature of their popularity. Thus, in this paper, we propose an AutoML based end-to-end framework (AutoEmb), which can enable various embedding dimensions according to the popularity in an automated and dynamic manner. To be specific, we first enhance a typical DLRS to allow various embedding dimensions; then we propose an end-to-end differentiable framework that can automatically select different embedding dimensions according to user/item popularity; finally we propose an AutoML based optimization algorithm in a streaming recommendation setting. The experimental results based on widely used benchmark datasets demonstrate the effectiveness of the AutoEmb framework.

cs.IR↗

arXiv2020

Adding salt to expand voltage window of humid ionic liquids

Humid hydrophobic ionic liquids, widely used as electrolytes, have narrowed electrochemical windows, because their water, absorbed on the electrode surface, gets involved in electrolysis. In this work, we performed molecular dynamics simulations to explore effects of adding Li-salt in humid ionic liquids on the water adsorbed on the electrode surface. Results reveal that most of water molecules are pushed away from both cathode and anode, by adding salt. The water remained on the electrode is almost bound with Li+, which has significantly lowered activity. The Li+-bonding and re-arrangement of the surface-adsorbed water both facilitate the inhibition of water electrolysis, and thus prevent the reduction of electrochemical windows of humid hydrophobic ionic liquids. This finding is testified by cyclic voltammetry measurements where salt-in-humid ionic liquids exhibit enhanced electrochemical windows. Our work provides the underlying mechanism and a simple but practical approach for protection of humid ionic liquids from performance degradation.

physics.app-ph↗

arXiv2020

Nanoscale magnetic resonance imaging of proteins in a single cell

Magnetic resonance imaging (MRI) is a non-invasive and label-free technique widely used in medical diagnosis and life science research, and its success has benefited greatly from continuing efforts on enhancing contrast and resolution. Here we reported nanoscale MRI in a single cell using an atomic-size quantum sensor. With nitrogen-vacancy center in diamond, the intracellular protein ferritin has been imaged with a spatial resolution of ~ 10 nanometers, and ferritin-containing organelles were co-localized by correlative MRI and electron microscopy. Comparing to the current micrometer resolution in current state-of-art conventional MRI, our approach represents a 100-fold enhancement, and paves the way for MRI of intracellular proteins.

physics.bio-ph↗

arXiv2020

Single DNA Electron Spin Resonance Spectroscopy in Aqueous Solutions

Magnetic resonance spectroscopy of single biomolecules under near-physiological conditions may substantially advance understanding of biological function, yet remains very challenging. Here we use nitrogen-vacancy centers in diamonds to detect electron spin resonance spectra of individual, tethered DNA duplexes labeled with a nitroxide spin label in aqueous buffer solutions at ambient temperatures. This paves the way for magnetic resonance studies on single biomolecules and their inter-molecular interactions in a native-like environment.

physics.bio-ph↗

arXiv2020

Remarks on Replica Method and Sachdev-Ye-Kitaev Model

Through tracing back to EA/SK models, we disentangle the construction logic of SYK model. During the construction, we recall the technical essence of replica method. Then we point out the redundance of the flavor group and the slave indices as well as the color group via the generalization from 2-index SY model to its 4-index version and the simplification of the latter in terms of Majorana fermions. Spectacularly, such a simplification reserves the system's self-consistency condition. Getting rid of the redundance, the model itself and its effective action have the same $O(N_s)$ structural symmetry, while it realizes $AdS_2/CFT_1$ holography by the emergent conformal symmetry. We also clarify the model transmutation to matrix model and argue that the disorder-averaged SYK model naturally preserves a holographic nature. Based on the transmutation and the correspondence with vector model, SYK model is formally a hybrid of these two models. Its quantum and semiclassical properties are also discussed respectively.

hep-th↗

arXiv2019

Interdiffusion between gadolinia doped ceria and yttria stabilized zirconia in solid oxide fuel cells: experimental investigation and kinetic modeling

Interdiffusion between the yttria stabilized zirconia (YSZ) electrolyte and the gadolinia doped ceria (CGO) barrier layer is one of the major causes to the degradation of solid oxide fuel cells (SOFCs). We present in this work experimental investigations on CGO-YSZ bi-layer electrolyte sintered at 1250 C or 1315 C and element transport as a function of sintering temperature and dwelling time. In order to quantitatively simulate the experimental observations, the CALPHAD-type thermodynamic assessment of the CGO-YSZ system is performed by simplifying the system to a CeO2-ZrO2 quasi-binary system, and the kinetic descriptions (atomic mobilities) are constructed based on critical review of literature data. The CGO-YSZ interdiffusion is then modeled with the DICTRA software and the simulation results are compared with the experimental data under different sintering or long-term operating conditions. The corresponding ohmic resistance of the bi-layer electrolyte is predicted based on the simulated concentration profile. The results implies that the interdiffusion across the CGO-YSZ interface happens mainly during sintering at high temperature, while during long-term operation at relatively lower temperature the impact of interdiffusion on cell degradation is negligible.

cond-mat.mtrl-sci↗

arXiv2019

Six constructions of asymptotically optimal codebooks via the character sums

In this paper, using additive characters of finite field, we find a codebook which is equivalent to the measurement matrix in [20]. The advantage of our construction is that it can be generalized naturally to construct the other five classes of codebooks using additive and multiplicative characters of finite field. We determine the maximal cross-correlation amplitude of these codebooks by the properties of characters and character sums. We prove that all the codebooks we constructed are asymptotically optimal with respect to the Welch bound. The parameters of these codebooks are new.

cs.IT↗

arXiv2019

Photonic hook generated by twin-ellipse microcylinder

Recently, two special photonic jets, photonic hooks and twin photonic jets, have been proposed to deal with complex conditions in nanoscale manipulation. Photonic hooks are generated by a single light plane wave and an asymmetric microparticle, while the twin photonic jets are produced by two incident light beams. In this letter, we presented and demonstrate a method to combine photonic hooks and twin photonic jets. A single light plane wave and a symmetric microparticle, twin-ellipse microcylinder, are used in this research. The curvature degree, length and maximum E2 filed enhancement of twin photonic hooks are varied significantly, with the change of refractive indices and shape of twin-ellipse microcylinder. And a liquid-immersed core-shell is built to achieve a flexible tunability.

physics.optics↗

arXiv2019

Photonic hooks from Janus microcylinders

Recently, a type of curved light beams, photonic hooks (PHs), was theoretically predicted and experimentally observed. The production of photonic hook (PH) is due to the breaking of structural symmetry of a plane-wave illuminated microparticle. Herein, we presented and implemented a new approach, of utilizing the symmetry-broken of the microparticles in material composition, for the generation of PHs from Janus microcylinders. Finite element method based numerical simulation and energy flow diagram represented theoretical analysis were used to investigate the field distribution characteristics and formation mechanism of the PHs. The full width at half-maximum (FWHM) of the PH (~0.29$λ$) is smaller than the FWHM of the photonic nanojet (~0.35$λ$) formed from a circular microcylinder with the same geometric radius. By changing the refractive index contrasts between upper and lower half-cylinders, or rotating the Janus microcylinder relative to the central axis, the shape profiles of the PHs can be efficiently modulated. The tunability of the PHs through simple stretching or compression operations, for the Janus microcylinder constituted by one solid inorganic half-cylinder and the other flexible polymer half-cylinder, was studied and discussed as well.

physics.optics↗

arXiv2019

Stochastic Resolution of Identity for Real-Time Second-Order Green's Function: Ionization Potential and Quasi-particle Spectrum

We develop a stochastic resolution of identity approach to the real-time second-order Green's function (real-time sRI-GF2) theory, extending our recent work for imaginary-time Matsubara Green's function {\em J. Chem. Phys.} {\bf 151}, 044114 (2019)). The approach provides a framework to obtain the quasi-particle spectra across a wide range of frequencies as well as predict ionization potentials and electron affinities. To assess the accuracy of the real-time sRI-GF2, we study a series of molecules and compare our results to experiments and to a many-body perturbation approach based on the GW approximation, where we find that the real-time sRI-GF2 is as accurate as self-consistent GW. The stochastic formulation reduces the formal scaling to $O(N_e^3)$, where $N_e$ is the number of electrons. This is illustrated for a chain of hydrogen dimers, where we observe a slightly lower than cubic scaling for systems containing up to $N_e \approx 1000$.

physics.chem-ph↗

arXiv2019

A Caching Strategy Towards Maximal D2D Assisted Offloading Gain

Device-to-Device (D2D) communications incorporated with content caching have been regarded as a promising way to offload the cellular traffic data. In this paper, the caching strategy is investigated to maximize the D2D offloading gain with the comprehensive consideration of user collaborative characteristics as well as the physical transmission conditions. Specifically, for a given content, the number of interested users in different groups is different, and users always ask the most trustworthy user in proximity for D2D transmissions. An analytical expression of the D2D success probability is first derived, which represents the probability that the received signal to interference ratio is no less than a given threshold. As the formulated problem is non-convex, the optimal caching strategy for the special unbiased case is derived in a closed form, and a numerical searching algorithm is proposed to obtain the globally optimal solution for the general case. To reduce the computational complexity, an iterative algorithm based on the asymptotic approximation of the D2D success probability is proposed to obtain the solution that satisfies the Karush-Kuhn-Tucker conditions. The simulation results verify the effectiveness of the analytical results and show that the proposed algorithm outperforms the existing schemes in terms of offloading gain.

eess.SP↗

arXiv2019

Realization of Ohmic-contact and velocity saturation in organic field-effect transistors by crystallized monolayer

The contact resistance limits the down-scaling and operating range of OFETs. With the monolayer (1L) organic crystals and non-destructive metal/semiconductor interfaces, intrinsic mobility of 12.5 cm2V-1s-1 and Ohmic contact resistance of 40 ohm-cm were achieved. The on/off ratio maintained at 10^3 even at a small VDS of -0.1 mV. High current density of 4.2 uA/um was achieved with the 1L-crystal as the active layer. At such high current density, the velocity saturation and channel self-heating effects are observed in OFETs for the first time. In addition to the low contact resistance and high-resolution lithography, we suggest the thermal management of the high mobility OFETs will be the next major challenge to achieve high-speed densely integrated flexible electronics.

physics.app-ph↗

arXiv2019

FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images

In this paper, we propose an end-to-end deep neural network for solving the problem of imbalanced large and small organ segmentation in head and neck (HaN) CT images. To conduct radiotherapy planning for nasopharyngeal cancer, more than 10 organs-at-risk (normal organs) need to be precisely segmented in advance. However, the size ratio between large and small organs in the head could reach hundreds. Directly using such imbalanced organ annotations to train deep neural networks generally leads to inaccurate small-organ label maps. We propose a novel end-to-end deep neural network to solve this challenging problem by automatically locating, ROI-pooling, and segmenting small organs with specifically designed small-organ sub-networks while maintaining the accuracy of large organ segmentation. A strong main network with densely connected atrous spatial pyramid pooling and squeeze-and-excitation modules is used for segmenting large organs, where large organs' label maps are directly output. For small organs, their probabilistic locations instead of label maps are estimated by the main network. High-resolution and multi-scale feature volumes for each small organ are ROI-pooled according to their locations and are fed into small-organ networks for accurate segmenting small organs. Our proposed network is extensively tested on both collected real data and the \emph{MICCAI Head and Neck Auto Segmentation Challenge 2015} dataset, and shows superior performance compared with state-of-the-art segmentation methods.

eess.IV↗

arXiv2019

Cache Placement in Two-Tier HetNets with Limited Storage Capacity: Cache or Buffer?

In this paper, we aim to minimize the average file transmission delay via bandwidth allocation and cache placement in two-tier heterogeneous networks with limited storage capacity, which consists of cache capacity and buffer capacity. For average delay minimization problem with fixed bandwidth allocation, although this problem is nonconvex, the optimal solution is obtained in closed form by comparing all locally optimal solutions calculated from solving the Karush-Kuhn-Tucker conditions. To jointly optimize bandwidth allocation and cache placement, the optimal bandwidth allocation is first derived and then substituted into the original problem. The structure of the optimal caching strategy is presented, which shows that it is optimal to cache the files with high popularity instead of the files with big size. Based on this optimal structure, we propose an iterative algorithm with low complexity to obtain a suboptimal solution, where the closed-from expression is obtained in each step. Numerical results show the superiority of our solution compared to the conventional cache strategy without considering cache and buffer tradeoff in terms of delay.

cs.IT↗

arXiv2019

Voltage-controlled skyrmion-based artificial synapse in a synthetic antiferromagnet

Spintronics exhibits significant potential in neuromorphic computing system with high speed, high integration density, and low dissipation. In this letter, we propose an ultralow-dissipation spintronic memristor composed of a synthetic antiferromagnet (SAF) and a piezoelectric substrate. Skyrmions/skyrmion bubbles can be generated in the upper layer of SAF with weak anisotropy energy (Ea). With a weak electric field on the heterostructure, the interlayer antiferromagnetic coupling can be manipulated, giving rise to a continuous transition between a large skyrmion bubble and a small skyrmion. This thus induces the variation of the resistance of a magnetic tunneling junction. The synapse based on this principle may manipulate the weight in a wide range at a cost of a very low energy consumption of 0.3 fJ. These results pave a way to ultralow power neuromorphic computing applications.

physics.comp-ph↗

arXiv2019

Stochastic embedding DFT: theory and application to p-nitroaniline

Over this past decade, we combined the idea of stochastic resolution of identity with a variety of electronic structure methods. In our stochastic Kohn-Sham DFT method, the density is an average over multiple stochastic samples, with stochastic errors that decrease as the inverse square root of the number of sampling orbitals. Here we develop a stochastic embedding density functional theory method (se-DFT) that selectively reduces the stochastic error (specifically on the forces) for a selected sub-system(s). The motivation, similar to that of other quantum embedding methods, is that for many systems of practical interest the properties are often determined by only a small sub-system. In stochastic embedding DFT two sets of orbitals are used: a deterministic one associated with the embedded subspace, and the rest which is described by a stochastic set. The method is exact in the limit of large number of stochastic samples. We apply se-DFT to study a p-nitroaniline molecule in water, where the statistical errors in the forces on the system (the p-nitroaniline molecule) are reduced by an order of magnitude compared with non-embedding stochastic DFT.

physics.chem-ph↗