Flexible but Refractory Single-Crystalline Hyperbolic Metamaterials

The fabrication of flexible single-crystalline plasmonic or photonic components in a scalable way is fundamentally important to flexible electronic and photonic devices with high speed, high energy efficiency, and high reliability. However, it remains to be a big challenge so far. Here, we have successfully synthesized flexible single-crystalline optical hyperbolic metamaterials by directly depositing refractory nitride superlattices on flexible fluoro phlogopite-mica substrates with magnetron sputtering. Interestingly, these flexible hyperbolic metamaterials show dual-band hyperbolic dispersion of dielectric constants with low dielectric losses and high figure-of-merit in the visible to near-infrared ranges. More importantly, the optical properties of these nitride-based flexible hyperbolic metamaterials show remarkable stability under either heating or bending. Therefore, the strategy developed in this work offers an easy and scalable route to fabricate flexible, high-performance, and refractory plasmonic or photonic components, which can significantly expand the applications of current electronic and photonic devices.Comment: 15 page

Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehension

The conversational machine reading comprehension (CMRC) task aims to answer questions in conversations, which has been a hot research topic in recent years because of its wide applications. However, existing CMRC benchmarks in which each conversation is assigned a static passage are inconsistent with real scenarios. Thus, model's comprehension ability towards real scenarios are hard to evaluate reasonably. To this end, we propose the first Chinese CMRC benchmark Orca and further provide zero-shot/few-shot settings to evaluate model's generalization ability towards diverse domains. We collect 831 hot-topic driven conversations with 4,742 turns in total. Each turn of a conversation is assigned with a response-related passage, aiming to evaluate model's comprehension ability more reasonably. The topics of conversations are collected from social media platform and cover 33 domains, trying to be consistent with real scenarios. Importantly, answers in Orca are all well-annotated natural responses rather than the specific spans or short phrase in previous datasets. Besides, we implement three strong baselines to tackle the challenge in Orca. The results indicate the great challenge of our CMRC benchmark. Our datatset and checkpoints are available at https://github.com/nuochenpku/Orca.Comment: 14 page

Parameter identification of PEMFC via feedforward neural network-pelican optimization algorithm

Parameter identification is a critical task in the research of proton exchange membrane fuel cells (PEMFC), which provides the basis for establishing an accurate and reliable PEMFC model. However, the nonlinear characteristics of PEMFC model as well as inevitable noise data and insufficient measurement data often overwhelm traditional optimization techniques. In particular, noise data and inadequate measurement data can introduce bias or lead to data loss. To address this problem, a novel hybrid optimization strategy is proposed. Firstly, a feedforward neural network (FNN) is employed to preprocess the measured data (i.e., reducing noise data and enriching measurement data). Furthermore, Gaussian noise and Rayleigh noise with three signal-to-noise ratio levels are introduced to simulate various disturbances of noise. Then, the pelican optimization algorithm (POA) is used to identify the parameters of PEMFC based on preprocessed data. Lastly, the effectiveness of the proposed strategy named FNN-POA is verified by comparing it with seven advanced competitive algorithms. Simulation results demonstrate that FNN-POA has higher robustness and optimization quality by comparing original data and preprocessed data. For instance, the root-mean-square error obtained by FNN-POA is reduced by 99.44% under medium temperature and medium pressure through noise reduction

Magnon-mediated interlayer coupling in an all-antiferromagnetic junction

The interlayer coupling mediated by fermions in ferromagnets brings about parallel and anti-parallel magnetization orientations of two magnetic layers, resulting in the giant magnetoresistance, which forms the foundation in spintronics and accelerates the development of information technology. However, the interlayer coupling mediated by another kind of quasi-particle, boson, is still lacking. Here we demonstrate such a static interlayer coupling at room temperature in an antiferromagnetic junction Fe2O3/Cr2O3/Fe2O3, where the two antiferromagnetic Fe2O3 layers are functional materials and the antiferromagnetic Cr2O3 layer serves as a spacer. The N\'eel vectors in the top and bottom Fe2O3 are strongly orthogonally coupled, which is bridged by a typical bosonic excitation (magnon) in the Cr2O3 spacer. Such an orthogonally coupling exceeds the category of traditional collinear interlayer coupling via fermions in ground state, reflecting the fluctuating nature of the magnons, as supported by our magnon quantum well model. Besides the fundamental significance on the quasi-particle-mediated interaction, the strong coupling in an antiferromagnetic magnon junction makes it a realistic candidate for practical antiferromagnetic spintronics and magnonics with ultrahigh-density integration.Comment: 19 pages, 4 figure

Volumetric chemical imaging in vivo by a remote-focusing stimulated Raman scattering microscope

Operable under ambient light and providing chemical selectivity, stimulated Raman scattering (SRS) microscopy opens a new window for imaging molecular events on a human subject, such as filtration of topical drugs through the skin. A typical approach for volumetric SRS imaging is through piezo scanning of an objective lens, which often disturbs the sample and offers a low axial scan rate. To address these challenges, we have developed a deformable mirror-based remote-focusing SRS microscope, which not only enables high-quality volumetric chemical imaging without mechanical scanning of the objective but also corrects the system aberrations simultaneously. Using the remote-focusing SRS microscope, we performed volumetric chemical imaging of living cells and captured in real time the dynamic diffusion of topical chemicals into human sweat pores.Published versio

Untargeted metabolomics of the cochleae from two laryngeally echolocating bats

High-frequency hearing is regarded as one of the most functionally important traits in laryngeally echolocating bats. Abundant candidate hearing-related genes have been identified to be the important genetic bases underlying high-frequency hearing for laryngeally echolocating bats, however, extensive metabolites presented in the cochleae have not been studied. In this study, we identified 4,717 annotated metabolites in the cochleae of two typical laryngeally echolocating bats using the liquid chromatography–mass spectroscopy technology, metabolites classified as amino acids, peptides, and fatty acid esters were identified as the most abundant in the cochleae of these two echolocating bat species, Rhinolophus sinicus and Vespertilio sinensis. Furthermore, 357 metabolites were identified as significant differentially accumulated (adjusted p-value <0.05) in the cochleae of these two bat species with distinct echolocating dominant frequencies. Downstream KEGG enrichment analyses indicated that multiple biological processes, including signaling pathways, nervous system, and metabolic process, were putatively different in the cochleae of R. sinicus and V. sinensis. For the first time, this study investigated the extensive metabolites and associated biological pathways in the cochleae of two laryngeal echolocating bats and expanded our knowledge of the metabolic molecular bases underlying high-frequency hearing in the cochleae of echolocating bats

Modulating solvated structure of Zn2+ and inducing surface crystallography by a simple organic molecule with abundant polar functional groups to synergistically stabilize zinc metal anodes for long-life aqueous zinc-ion batteries

Aqueous zinc-ion batteries (AZIBs) have attracted significant attention owing to their inherent security, low cost, abundant zinc (Zn) resources and high energy density. Nevertheless, the growth of zinc dendrites and side reactions on the surface of Zn anodes during repeatedly plating/stripping shorten the cycle life of AZIBs. Herein, a simple organic molecule with abundant polar functional groups, 2,2,2-trifluoroether formate (TF), has been proposed as a high-efficient additive in the ZnSO4 electrolyte to suppress the growth of Zn dendrites and side reaction during cycling. It is found that TF molecules can infiltrate the solvated sheath layer of the hydrated Zn2+ to reduce the number of highly chemically active H2O molecules owing to their strong binding energy with Zn2+. Simultaneously, TF molecules can preferentially adsorb onto the Zn surface, guiding the uniform deposition of Zn2+ along the crystalline surface of Zn(0 0 2). This dual action significantly inhibits the formation of Zn dendrites and side reactions, thus greatly extending the cycling life of the batteries. Accordingly, the Zn//Cu asymmetric cell with 2 % TF exhibits stable cycling for more than 3,800 cycles, achieving an excellent average Columbic efficiency (CE) of 99.81 % at 2 mA cm−2/1 mAh cm−2. Meanwhile, the Zn||Zn symmetric cell with 2 % TF demonstrates a superlong cycle life exceeding 3,800 h and 2,400 h at 2 mA cm−2/1 mAh cm−2 and 5 mA cm−2/2.5 mAh cm−2, respectively. Simultaneously, the Zn//VO2 full cell with 2 % TF possesses high initial capacity (276.8 mAh/g) and capacity retention (72.5 %) at 5 A/g after 500 cycles. This investigation provides new insights into stabilizing Zn metal anodes for AZIBs through the co-regulation of Zn2+ solvated structure and surface crystallography

Genomic Analyses Reveal Mutational Signatures and Frequently Altered Genes in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO