We performed angle-resolved photoemission spectroscopy studies on the triple-layer Bi2Sr2Ca2Cu3O10+δ over a wide doping range. Although the doping level of the inner CuO2 plane is extremely low in underdoped samples, the d-wave SC gap is enhanced to the unprecedentedly large value of Δ0 ~ 80-100 meV at the antinode. This gap persists well above Tc without a Fermi arc, indicating a "nodal metal". We attribute the nodal metallic behavior to the unique local environment of the inner clean CuO2 plane, sandwiched by nearly optimally-doped two outer planes and hence subject to strong proximity effect from both sides. In the nodal metal, quasiparticle peaks show electron-hole symmetry, suggesting d-wave pairing fluctuations. Thus the proximity effect on the innermost CuO2 plane is the strongest in the triple-layer cuprates, which explains why the Tc reaches the maximum at the layer number of three in every multi-layer cuprate family.

Tantalum disulfide (1T-TaS2), being a Mott insulator with strong electron correlation, is highlighted for diverse collective quantum states in the 2D lattice, including charge density wave (CDW), spin liquid, and unconventional superconductivity. The Mott physics embedded in the 2D triangular CDW lattice has raised debates on stacking-dependent properties because interlayer interactions are sensitive to van der Waals (vdW) spacing. However, control of interlayer distance remains a challenge. Here, spiral lattices in the epitaxial TaS2 spirals are studied to probe collective properties with tunable interlayer interactions. A scalable synthesis of epitaxial TaS2 spirals is presented. A more than 50%-increased interlayer spacing enables prototype decoupled monolayers for enhanced electronic correlation exhibiting Mott physics at room-temperature and a simplified system to explore collective properties in vdW materials.

The observation of superconductivity in MnSe at 12 GPa motivated us to investigate whether superconductivity could be induced in MnSe at ambient conditions. A strain-induced structural change in the ultrathin film could be one route to the emergence of superconductivity. In this report, we present the physical property of MnSe ultrathin films, which become tetragonal (stretched ab-plane and shortened c-axis) on a (001) SrTiO3 (STO) substrate, prepared by the pulsed laser deposition (PLD) method. The physical properties of the tetragonal MnSe ultrathin films exhibit very different characteristics from those of the thick films and polycrystalline samples. The tetragonal MnSe films show substantial conductivity enhancement, which could be associated with the presence of superparamagnetism. The optical absorption data indicate that the electron transition through the indirect bandgap to the conduction band is significantly enhanced in tetragonal MnSe. Furthermore, the X-ray Mn L-edge absorption results also reveal an increase in unoccupied state valance bands. This theoretical study suggests that charge transfer from the substrate plays an important role in conductivity enhancement and the emergence of a ferromagnetic order that leads to superparamagnetism.

Biological signal encoding is shaped by the underlying neural circuitry. In Drosophila melanogaster , the mushroom body (MB) houses thousands of Kenyon cells (KCs) that process olfactory signals from hundreds of projection neurons (PNs). Previous studies debated the connectivity between PNs and KCs (random vs. structured). Our multiscale analysis of electron microscopic data revealed a hybrid network with diverse synaptic connection preferences and input divergence across different KC classes. Using MB connectome data, our simulation model, validated via functional imaging, accurately predicted distinct chemical sensitivities in the major KC classes. The model suggests that the hybrid network excels in detecting food odors while maintaining precise odor discrimination in different KC classes. These findings underscore the computational advantages of this hybrid network.

Since 2020, synchrotron radiation facilities in several Asia-Pacific countries have been collaborating in a major project called "SYNAPSE" (Synchrotrons for Neuroscience: an Asia-Pacific Scientific Enterprise). They use x-ray imaging to attack in a coordinated fashion one of the major issues in modern science: the structure of animal and human brains, including neurons and connections. The objective is to develop Google-like maps also including detailed structural and functional information for selected regions of interest. The sheer mass of data needed for the objective poses huge problems for the acquisition, processing, storage and use of images. In order to complete the task within a reasonable time, the key element of the SYNAPSE strategy is the parallel and coordinated work of several facilities on the same specimens. This article reviews different aspects of the enterprise, including the foundations of synchrotron radiation, coherence and of its role in advanced imaging, electron accelerators, x-ray optics and detectors. This will provide the foundation for an extensive presentation of the different components of SYNAPSE, with an overview of results already obtained within the consortium.

We present a comprehensive study of vortex structures in $d$-wave superconductors from large-scale renormalized mean-field theory of the square-lattice $t$-$t'$-$J$ model, which has been shown to provide a quantitative modeling for high-$T_c$ cuprate superconductors. With an efficient implementation of the kernel polynomial method for solving electronic structures, self-consistent calculations involving up to $10^5$ variational parameters are performed to investigate the vortex solutions on lattices of up to $10^4$ sites. By taking into account the strong correlation of the model, our calculations shed new lights on two puzzling results that have emerged from recent scanning tunneling microscopy (STM) experiments. The first concerns the issue of the zero-biased-conductance peak (ZBCP) at the vortex core for a uniform $d$-wave superconducting state. Despite its theoretical prediction, the ZBCP was not observed in most doping range of cuprates except in heavily over-doped samples at low magnetic field. The second issue is the nature of the checkerboard charge density waves (CDWs) with a period of about 8 unit cells in the vortex halo at optimal doping. Although it has been suggested that such bipartite structure arises from low-energy quasiparticle interference, another intriguing scenario posits that the checkerboard CDWs originate from an underlying bidirectional pair-density wave (PDW) ordering with the same period. We present a coherent interpretation of these experimental results based on systematic studies of the doping and magnetic field effects on vortex solutions with and without a checkerboard structure. The mechanism of the emergent intertwined orders within the vortex halo is also discussed.

We present a scalable machine learning (ML) model to predict local electronic properties such as on-site electron number and double occupation for disordered correlated electron systems. Our approach is based on the locality principle, or the nearsightedness nature, of many-electron systems, which means local electronic properties depend mainly on the immediate environment. A ML model is developed to encode this complex dependence of local quantities on the neighborhood. We demonstrate our approach using the square-lattice Anderson-Hubbard model, which is a paradigmatic system for studying the interplay between Mott transition and Anderson localization. We develop a lattice descriptor based on group-theoretical method to represent the on-site random potentials within a finite region. The resultant feature variables are used as input to a multi-layer fully connected neural network, which is trained from datasets of variational Monte Carlo (VMC) simulations on small systems. We show that the ML predictions agree reasonably well with the VMC data. Our work underscores the promising potential of ML methods for multi-scale modeling of correlated electron systems.

Using miniscope recordings of calcium fluorescence signals in the CA1 region of the hippocampus of mice, we monitor the neural activity of hippocampal regions while the animals are freely moving in an open chamber. Using a data-driven statistical modeling approach, the statistical properties of the recorded data are mapped to spin-glass models with pairwise interactions. Considering the parameter space of the model, the observed system is generally near a critical state between two distinct phases. The close proximity to the criticality is found to be robust against different ways of sampling and segmentation of the measured data. By independently altering the coupling distribution and the network structure of the statistical model, the network structures are found to be vital to maintain the proximity to the critical state. We further find the observed assignment of the coupling strengths makes the net coupling at each site more balanced with slight variation, which likely helps the maintenance of the critical state. Network analysis on the connectivity obtained by thresholding the coupling strengths find the connectivity of the networks to be well described by a random network model. These results are consistent across different experiments, sampling and segmentation choices in our analysis. A new result of our analysis is that the proximity to critical state and all the network properties are largely maintained even if random subsamples with a fraction of neurons are selected from the dataset as long as the number of neurons is more than 30 to 40. Thus the relevant degrees of freedom of CA1 region in the collective state we studied is not as large as one would expect.

It is important to study the properties of high quality single crystal in order to resolve the issue of an interesting material in which certain debatable fundamental properties exist. However, it is unfortunate that a sizable single crystal for experimental measurements is not always available. NbN is one of the examples; it has attracted scientific and engineering interest due to its diverse physical properties and a variety of structural phases. Until now superconductivity is only observed in cubic delta- and tetragonal gamma-NbN but not in hexagonal epsilon-NbN. Recently, Zou et al. reported the observation of superconductivity with T-c similar to 11.6 K in a hexagonal epsilon-NbN based on the measurement on a multiphase powder specimen. In order to resolve the issue, the work used the electron backscattering diffraction technique to characterize phases of micron-size NbN crystals from commercial powders and measure their transport properties. Our results unambiguously confirm that the hexagonal epsilon-NbN phase is not superconducting.

High-temperature superconductive (SC) cuprates exhibit not only a SC phase, but also competing orders, suppressing superconductivity. Charge order (CO) has been recognized as an important competing order, but its microscopic spatial interplay with SC phase as well as the interlayer coupling in CO and SC phases remain elusive, despite being essential for understanding the physical mechanisms of competing orders and hence superconductivity. Here we report the achievement of direct real-space imaging with atomic-scale resolution of cryogenically cleaved YBa 2 Cu 3 O 6.81 using cross-sectional scanning tunneling microscopy/spectroscopy. CO nanodomains are found embedded in the SC phase with a proximity-like boundary region characterized by mutual suppression of CO and superconductivity. Furthermore, SC coherence as well as CO occur on both CuO chain and plane layers, revealing carrier transport and density of states mixing between layers. The CO antiphase correlation along the c direction suggests a dominance of Coulomb repulsion over Josephson tunneling between adjacent layers.

Segmenting individual neurons from a large number of noisy raw images is the first step in building a comprehensive map of neuron-to-neuron connections for predicting information flow in the brain. Thousands of fluorescence-labeled brain neurons have been imaged. However, mapping a complete connectome remains challenging because imaged neurons are often entangled and manual segmentation of a large population of single neurons is laborious and prone to bias. In this study, we report an automatic algorithm, NeuroRetriever , for unbiased large-scale segmentation of confocal fluorescence images of single neurons in the adult Drosophila brain. NeuroRetriever uses a high-dynamic-range thresholding method to segment three-dimensional morphology of single neurons based on branch-specific structural features. Applying NeuroRetriever to automatically segment single neurons in 22,037 raw brain images, we successfully retrieved 28,125 individual neurons validated by human segmentation. Thus, automated NeuroRetriever will greatly accelerate 3D reconstruction of the single neurons for constructing the complete connectomes.

The rich phenomena in the FeSe and related compounds have attracted great interests as it provides fertile material to gain further insight into the mechanism of high temperature superconductivity. A natural follow-up work was to look into the possibility of superconductivity in MnSe. It was shown that MnP becomes superconducting with Tc ~ 1 K under pressure. We demonstrated in this work that high pressure can effectively suppress the complex magnetic characters of MnSe crystal when observed at ambient condition. MnSe under pressure is found to undergo several structural transformations: the cubic phase first partially transforms to the hexagonal phase at about 12 GPa, the crystal exhibits the coexistence of cubic, hexagonal and orthorhombic phases from 16 GPa to 30 GPa, and above 30 GPa the crystal shows a single orthorhombic phase. Superconductivity with Tc ~ 5 K was first observed at pressure ~12 GPa by magnetic measurements (~16 GPa by resistive measurements). The highest Tc is ~ 9 K (magnetic result) at ~35 GPa. Our observations suggest the observed superconductivity may closely relate to the pressure-induced structural change. However, the interface between the metallic and insulating boundaries may also play an important role to the pressure induced superconductivity in MnSe.

High-order topological charge is of intensive interest in the field of topological matters. In real materials, cubic Dirac point is rare and the chiral charge of one Weyl point (WP) has never be found to exceed |C| = 3 for spin- 1/2 electronic systems. In this work, we argue that a cubic Dirac point can result in one quadruple WP (|C| = 4 with double band degeneracy) when time-reversal symmetry is broken, provided that this cubic Dirac point is away from the high-symmetry points and involves coupling of eight bands, rather than four bands that were thought to be sufficient to describe a Dirac point. The eight-band manifold can be realized in materials with screw symmetry. Near the zone boundary along the screw axis, the folded bands are coupled to their parent bands, resulting in doubling dimension of the Hilbert space. Indeed, in $\epsilon$-TaN (space group 194 with screw symmetry) we find a quadruple WP when applying a Zeeman field along the screw axis. This quadruple WP away from high symmetry points is distinct from highly degenerate nodes at the high-symmetry points already reported. We further find that such a high chiral charge might be related to the parity mixing of bands with high degeneracy, which in turn alters the screw eigenvalues and the resulted chiral charge.

Recent Scanning Tunneling Spectra(STS) measurements on underdoped cuprates have found that the maximum superconducting transition temperature Tc increases when the size of charge transfer gap (CTG) is reduced. Applying pressure is another well-known method to increase the maximum Tc. However, these pressure experiments also found that Tc is enhanced in underdoped and optimally-doped samples but suppressed in overdoped ones. Here we present a possible mechanism based on the charge fluctuation to explain both these observed effects. Starting from the 3-band Hubbard model, we retrieve the charge fluctuation (CF) between the oxygen 2p6 band and copper 3d10 band, which is ignored in the t−J model. This model is investigated using the variational Monte Carlo method(VMC).

We investigate the correlated electrons in the magic-angle twisted bilayer graphene by using the slave-rotor mean-field theory. Owing to the extended figure of Wannier orbitals, we study the two-orbital cluster Hubbard model with spin-valley fourfold degeneracy, focusing around half-filling of valence bands below the neutrality point. The theory predicts multiple Mott insulator phases at fractional fillings not only for integer charges per moir\'e site, and it demonstrates that long-range electron hopping is highly suppressed because multiple-charge excitations are induced. Furthermore, the Kekule valence bond order is investigated and is found to extend the Mott insulator phases to occupy a finite doping region. Adjacent to Mott insulator phases, superconducting domes emerges by virtue of spin-valley fluctuations. This work has provided a primal understanding and interesting phenomena of the correlated system, and for its unique interaction the model might produce plenty of possibilities waiting to be explored.

High-order topological charge is of intensive interest in the field of topological matters. In real materials, cubic Dirac point is rare and the chiral charge of one Weyl point (WP) is generally limited to |C|<= 3 for spin-1/2 electronic systems. In this work, we argue that a cubic Dirac point can result in one quadruple WP (|C| = 4 with double band degeneracy) when time-reversal symmetry is broken, provided that this cubic Dirac point is away from the high-symmetry points and involves coupling of eight bands, rather than four bands that were thought to be sufficient to describe a Dirac point. The eight-band manifold can be realized in materials with screw symmetry. Near the zone boundary along the screw axis, the folded bands are coupled to their parent bands, resulting in doubling dimension of the Hilbert space. Indeed, in \epsilon-TaN (space group 194 with screw symmetry) we find a quadruple WP when applying a Zeeman field along the screw axis. This quadruple WP away from high symmetry points is distinct from highly degenerate nodes at the high-symmetry points already reported. We further find that such a high chiral charge might be related to the parity fixing of bands with high degeneracy, which in turn alters the screw eigenvalues and the resulted chiral charge.

The spatial resolution of x-ray free-electron laser (XFEL) coherent diffraction imaging is currently limited by the fluence of XFELs. Here, we clarify this issue by systematically studying the diffraction with a SPring-8 angstrom compact free electron laser XFEL on gold nanoparticles of size from 10 nm to 80 nm in water solution. The coherent x-ray diffraction patterns obtained from single XFEL pulses were quantitatively analyzed using a small-angle x-ray scattering scheme along with computer simulations. The results show that the detectability of Au nanoparticles can be described by a “master curve” as a function of total electron density, particle size, and x-ray fluence. The difficulty in detecting a small particle under the current XFEL fluence, however, could be largely eliminated by the image enhancement effect through interference from a strong scattering nanoparticle nearby. We investigate this image enhancement effect by quantitatively analyzing the two-particle scattering from Au nanoparticles, and further, applying it to detect a weak biological object of influenza virus with the aid of an Au nanoparticle.

Mapping the large neural networks of animal and human brains is a fundamental but so far elusive task, because of the massive amount of data and the consequent prohibitively long image taking and processing times. We developed an effective strategy called “AXON” (Accelerated X-ray Observation of Neurons) to solve this problem. AXON can achieve comprehensive whole-brain mapping within a reasonable time by combining fast image taking and processing, plus two other critical performances: three-dimensional (3D) imaging with high and isotropic spatial resolution, and multi-scale resolution. We successfully tested this strategy with coordinated experiments at four synchrotron facilities in Japan, Taiwan, Singapore and Korea on two animal models, Drosophila and mouse. Its performances notably allowed full 3D mapping of the Drosophila brain in a few days. With reasonable improvements, AXON can deliver full mapping of large animal and human brains on a realistic time scale of a few years.