Quantum Transport of Bosonic Cold Atoms in Double Well Optical Lattices

We numerically investigate, using the time evolving block decimation algorithm, the quantum transport of ultra-cold bosonic atoms in a double well optical lattice through slow and periodic modulation of the lattice parameters (intra- and inter-well tunneling, chemical potential, etc.). The transport of atoms does not depend on the rate of change of the parameters (as along as the change is slow) and can distribute atoms in optical lattices at the quantized level without involving external forces. The transport of atoms depends on the atom filling in each double well and the interaction between atoms. In the strongly interacting region, the bosonic atoms share the same transport properties as non-interacting fermions with quantized transport at the half filling and no atom transport at the integer filling. In the weakly interacting region, the number of the transported atoms is proportional to the atom filling. We show the signature of the quantum transport from the momentum distribution of atoms that can measured in the time of flight image. A semiclassical transport model is developed to explain the numerically observed transport of bosonic atoms in the non-interacting and strongly interacting limits. The scheme may serve as an quantized battery for atomtronics applications.Comment: 8 pages, 9 figures, accepted for publication in Phys. Rev.

Many-body Landau-Zener Transition in Cold Atom Double Well Optical Lattices

Ultra-cold atoms in optical lattices provide an ideal platform for exploring many-body physics of a large system arising from the coupling among a series of small identical systems whose few-body dynamics is exactly solvable. Using Landau-Zener (LZ) transition of bosonic atoms in double well optical lattices as an experimentally realizable model, we investigate such few to many body route by exploring the relation and difference between the small few-body (in one double well) and the large many-body (in double well lattice) non-equilibrium dynamics of cold atoms in optical lattices. We find the many-body coupling between double wells greatly enhances the LZ transition probability. The many-body dynamics in the double well lattice shares both similarity and difference from the few-body dynamics in one and two double wells. The sign of the on-site interaction plays a significant role on the many-body LZ transition. Various experimental signatures of the many-body LZ transition, including atom density, momentum distribution, and density-density correlation, are obtained.Comment: 7 pages, 6 figure

Straight Indium Antimonide Nanowires with Twinning Superlattices via a Solution Route

Indium antimonide (InSb) enables diverse applications in electronics and optoelectronics. However, to date, there has not been a report on the synthesis of InSb nanowires (NWs) via a solution-phase strategy. Here, we demonstrate for the first time the preparation of high-quality InSb NWs with twinning superlattices from a mild solution-phase synthetic environment from the reaction of commercial triphenylantimony with tris­(2,4-pentanedionato)-indium­(III). This reaction occurs at low temperatures from 165 to 195 °C (optimized at ∼180 °C), which is the lowest temperature reported for the growth of InSb NWs to date. Investigations reveal that the InSb NWs are grown via a solution–liquid–solid (SLS) mechanism due to the catalysis of the initially formed indium droplets in the mild solution-phase reaction system. The twinning superlattices in the InSb NWs are determined with a pseudoperiodic length of ∼42 monolayers, which result from an oscillating self-catalytic growth related to the periodical fluctuation between reduction rate of In and Sb sources in the route. The optical pump-terahertz probe spectroscopic measurement suggests that the InSb NWs have potential for applications in high-speed optoelectronic nanodevices

Rational Design of Goethite-Sulfide Nanowire Heterojunctions for High Current Density Water Splitting

The preparation of efficient and stable bifunctional electrocatalysts for electrochemical overall water splitting (OWS) to scale up commercial hydrogen production remains a great challenge. Here, we synthesized heterojunction structures consisting of Co9S8/Ni3S2 nanowire arrays and amorphous goethite (FeOOH, α-phase) particles as efficient OWS catalysts using an interface engineering strategy. The interfacial charge inhomogeneity caused by the heterojunction contact leads to the generation of a built-in electric field, which makes the electron-deficient FeOOH and electron-rich Co9S8/Ni3S2 favorable for hydrogen/oxygen evolution reaction, respectively, thus ensuring the excellent activity of FeOOH/Co9S8/Ni3S2 as a bifunctional catalyst. FeOOH/Co9S8/Ni3S2 exhibits impressive catalytic activity for the oxygen evolution reaction, achieving an ultralarge current density of 1000 mA cm–2 needed as low as 265 mV overpotential, and its stability was tested up to 1440 h. Furthermore, an excellent OWS output (1.55 V to generate 10 mA cm–2) is achieved by the bifunctional FeOOH/Co9S8/Ni3S2 catalysts

Rational Design of Goethite-Sulfide Nanowire Heterojunctions for High Current Density Water Splitting

The preparation of efficient and stable bifunctional electrocatalysts for electrochemical overall water splitting (OWS) to scale up commercial hydrogen production remains a great challenge. Here, we synthesized heterojunction structures consisting of Co9S8/Ni3S2 nanowire arrays and amorphous goethite (FeOOH, α-phase) particles as efficient OWS catalysts using an interface engineering strategy. The interfacial charge inhomogeneity caused by the heterojunction contact leads to the generation of a built-in electric field, which makes the electron-deficient FeOOH and electron-rich Co9S8/Ni3S2 favorable for hydrogen/oxygen evolution reaction, respectively, thus ensuring the excellent activity of FeOOH/Co9S8/Ni3S2 as a bifunctional catalyst. FeOOH/Co9S8/Ni3S2 exhibits impressive catalytic activity for the oxygen evolution reaction, achieving an ultralarge current density of 1000 mA cm–2 needed as low as 265 mV overpotential, and its stability was tested up to 1440 h. Furthermore, an excellent OWS output (1.55 V to generate 10 mA cm–2) is achieved by the bifunctional FeOOH/Co9S8/Ni3S2 catalysts

Causal Estimation of Position Bias in Recommender Systems Using Marketplace Instruments

Information retrieval systems, such as online marketplaces, news feeds, and search engines, are ubiquitous in today's digital society. They facilitate information discovery by ranking retrieved items on predicted relevance, i.e. likelihood of interaction (click, share) between users and items. Typically modeled using past interactions, such rankings have a major drawback: interaction depends on the attention items receive. A highly-relevant item placed outside a user's attention could receive little interaction. This discrepancy between observed interaction and true relevance is termed the position bias. Position bias degrades relevance estimation and when it compounds over time, it can silo users into false relevant items, causing marketplace inefficiencies. Position bias may be identified with randomized experiments, but such an approach can be prohibitive in cost and feasibility. Past research has also suggested propensity score methods, which do not adequately address unobserved confounding; and regression discontinuity designs, which have poor external validity. In this work, we address these concerns by leveraging the abundance of A/B tests in ranking evaluations as instrumental variables. Historical A/B tests allow us to access exogenous variation in rankings without manually introducing them, harming user experience and platform revenue. We demonstrate our methodology in two distinct applications at LinkedIn - feed ads and the People-You-May-Know (PYMK) recommender. The marketplaces comprise users and campaigns on the ads side, and invite senders and recipients on PYMK. By leveraging prior experimentation, we obtain quasi-experimental variation in item rankings that is orthogonal to user relevance. Our method provides robust position effect estimates that handle unobserved confounding well, greater generalizability, and easily extends to other information retrieval systems.Comment: 13 pages, 2 figure

Preparation of 1,8-dichloroanthraquinone/graphene oxide/poly (vinylidene fluoride) (1,8-AQ/GO/PVDF) mediator membrane and its application to catalyzing biodegradation of azo dyes

Anthraquinone is a redox mediator that can effectively catalyze the degradation of azo dyes by promoting the electron transfer. In this study, a mediator membrane with poly (vinylidene fluoride) (PVDF) as the membrane support and 1,8-dichloroanthraquinone (1,8-AQ) and graphene oxide (GO) as the additives was prepared and characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), mercury intrusion porosimetry (MIP), atomic force microscopy (AFM) and water contact angle. The introduction of GO increases the pure water flux of the membrane to 258.56±12.93 L/(m2·h). Its catalytic performances for the biodegradation of azo dyes were evaluated. Under the optimized conditions, the 1,8-AQ/GO/PVDF composite membrane is able to improve the dye degradation efficiency 2.2 times for reactive red X-3B and 1.1 times for acid red B, as compared with PVDF membrane. In addition, the mediator membrane maintains stable and high catalytic efficiency in the cyclic test and over 90 % dye degradation efficiency is still obtained after 5 cycles of decolorization. These results suggest the great application potentials of the 1,8-AQ/GO/PVDF membrane in the dye wastewater treatment

lncRNAs Are Involved in Sevoflurane Anesthesia-Related Brain Function Modulation through Affecting Mitochondrial Function and Aging Process

Long noncoding RNAs (lncRNAs) play important roles in brain function modulation and neurodegenerative diseases. However, whether lncRNA regulations are involved in the mechanisms of perioperative neurocognitive disorders, especially in anesthesia-related brain dysfunction, remain unknown. Therefore, we explored the expression and regulation pattern profiles of lncRNAs in the hippocampus of aged rats after sevoflurane anesthesia. Three lncRNAs and 772 protein-coding genes were identified by microarray analysis and evidenced by in vitro and in vivo experiments as differentially expressed. Functional annotation and differentially expressed- (DE-) lncRNA-mRNA coexpression networks reveal that DE-lncRNAs are associated with mitochondrial dysfunction and oxidative stress, aging-related metabolism alterations, DNA damage, and apoptosis, as well as neurodegenerative features during sevoflurane anesthesia. These results suggest that lncRNAs play roles in general anesthesia-related brain function modulation during the perioperative context and provide insights into the lncRNA-related modulation mechanisms and targets