Dual Channel H2O2 Photosynthesis in Pure Water over S-Scheme Heterojunction Cs3PMo12/CC Boosted by Proton and Electron Reservoirs.

Dual channel photo-driven H2O2 production in pure water on small-scale on-site setups is a promising strategy to provide low-concentrated H2O2 whenever needed. This process suffers, however, strongly from the fast recombination of photo-generated charge carriers and the sluggish oxidation process. Here, insoluble Keggin-type cesium phosphomolybdate Cs3PMo12O40 (abbreviated to Cs3PMo12) is introduced to carbonized cellulose (CC) to construct S-scheme heterojunction Cs3PMo12/CC. Dual channel H2O2 photosynthesis from both H2O oxidation and O2 reduction in pure water has been thus achieved with the production rate of 20.1 mmol L-1 gcat. -1 h-1, apparent quantum yield (AQY) of 2.1% and solar-to-chemical conversion (SCC) efficiency of 0.050%. H2O2 accumulative concentration reaches 4.9 mmol L-1. This high photocatalytic activity is guaranteed by unique features of Cs3PMo12/CC, namely, S-scheme heterojunction, electron reservoir, and proton reservoir. The former two enhance the separation of photo-generated charge carriers, while the latter speeds up the torpid oxidation process. In situ experiments reveal that H2O2 is formed via successive single-electron transfer in both channels. In real practice, exposing the reaction system under natural sunlight outdoors successfully results in 0.24 mmol L-1 H2O2. This work provides a key practical strategy for designing photocatalysts in modulating redox half-reactions in photosynthesis.

From NeRFLiX to NeRFLiX++: A General NeRF-Agnostic Restorer Paradigm.

Neural radiance fields (NeRF) have shown great success in novel view synthesis. However, recovering high-quality details from real-world scenes is still challenging for the existing NeRF-based approaches, due to the potential imperfect calibration information and scene representation inaccuracy. Even with high-quality training frames, the synthetic novel views produced by NeRF models still suffer from notable rendering artifacts, such as noise and blur. To address this, we propose NeRFLiX, a general NeRF-agnostic restorer paradigm that learns a degradation-driven inter-viewpoint mixer. Specially, we design a NeRF-style degradation modeling approach and construct large-scale training data, enabling the possibility of effectively removing NeRF-native rendering artifacts for deep neural networks. Moreover, beyond the degradation removal, we propose an inter-viewpoint aggregation framework that fuses highly related high-quality training images, pushing the performance of cutting-edge NeRF models to entirely new levels and producing highly photo-realistic synthetic views. Based on this paradigm, we further present NeRFLiX++ with a stronger two-stage NeRF degradation simulator and a faster inter-viewpoint mixer, achieving superior performance with significantly improved computational efficiency. Notably, NeRFLiX++ is capable of restoring photo-realistic ultra-high-resolution outputs from noisy low-resolution NeRF-rendered views. Extensive experiments demonstrate the excellent restoration ability of NeRFLiX++ on various novel view synthesis benchmarks.

Carbon Vacancy-Enhanced Activity of Fe-N-C Single Atom Catalysts toward Luminol Chemiluminescence in the Absence of H2O2.

The classic luminol-H2O2 chemiluminescence (CL) systems suffer from easy self-decomposition of H2O2 at room temperature, hindering the practical applications of the luminol-H2O2 CL system. In this work, unexpectedly, we found that the carbon vacancy-modified Fe-N-C single atom catalysts (VC-Fe-N-C SACs) can directly trigger a luminol solution to generate strong CL emission in the absence of H2O2. The Fe-based SACs were prepared through the conventional pyrolysis of zeolitic imidazolate frameworks. The massive carbon vacancies were readily introduced into Fe-N-C SACs through a tannic acid-etching process. Carbon vacancy significantly enhanced the catalytic activity of Fe-N-C SACs on the CL reaction of luminol-dissolved oxygen. The VC-Fe-N-C SACs performed a 13.4-fold CL enhancement compared with the classic luminol-Fe2+ system. It was found that the introduction of a carbon vacancy could efficiently promote dissolved oxygen to convert to reactive oxygen species. As a proof of concept, the developed CL system was applied to detect alkaline phosphatase with a linear range of 0.005-1 U/L as well as a detection limit of 0.003 U/L. This work demonstrated that VC-Fe-N-C SAC is a highly efficient CL catalyst that can promote the analytic application of the luminol CL system.

Synergy of multiple precipitate/matrix interface structures for a heat resistant high-strength Al alloy.

High strength aluminum alloys are widely used but their strength is reduced as nano-precipitates coarsen rapidly in medium and high temperatures, which greatly limits their application. Single solute segregation layers at precipitate/matrix interfaces are not satisfactory in stabilizing precipitates. Here we obtain multiple interface structures in an Al-Cu-Mg-Ag-Si-Sc alloy including Sc segregation layers, C and L phases as well as a newly discovered χ-AgMg phase, which partially cover the θ' precipitates. By atomic resolution characterizations and ab initio calculations, such interface structures have been confirmed to synergistically retard coarsening of precipitates. Therefore, the designed alloy shows the good combination of heat resistance and strength among all series of Al alloys, with 97% yield strength retained after thermal exposure, which is as high as 400 MPa. This concept of covering precipitates with multiple interface phases and segregation layers provides an effective strategy for designing other heat resistant materials.

Enhancing Energy Storage Performance in Lead-Free Bismuth Sodium Niobate-Based Tungsten Bronze Ceramics through Relaxor Tuning.

A series of tungsten bronze Sr2Na0.85Bi0.05Nb5-xTaxO15 (SBNN-xTa) ferroelectric ceramics were designed and synthesized by the traditional solid-phase reaction method. The B-site engineering strategy was utilized to induce structural distortion, order-disorder distribution, and polarization modulation to enhance relaxor behavior. Through investigating the impact of B-site Ta replacement on the structure, relaxor behavior, and energy storage performance, this study has shed light on the two main factors for relaxor nature: (1) with the increase of Ta substitution, the tungsten bronze crystal distortion and expansion induced the structural change from an orthorhombic Im2a phase to Bbm2 phase at room temperature; (2) the transition from ferroelectric to relaxor behavior could be attributed to the coordinate incommensurate local superstructural modulations and the generation of nanodomain structure regions. Moreover, we benefited from the effective decrease of ceramic grains and inhibition of abnormal growth. Finally, we obtained an effective energy storage density (Wrec) ∼ 1.6 J/cm3, an efficiency (η) ∼ 80%, a current density (CD) ∼ 1384.2 A/cm2, and a power density (PD) ∼ 138.4 MW/cm3.

Thickness-Independent Capacitive Performance of Holey Ti3 C2 Tx Film Prepared through a Mild Oxidation Strategy.

The Ti3 C2 Tx film with metallic conductivity and high pseudo-capacitance holds profound promise in flexible high-rate supercapacitors. However, the restacking of Ti3 C2 Tx sheets hinders ion access to thick film electrodes. Herein, a mild yet green route has been developed to partially oxidize Ti3 C2 Tx to TiO2 /Ti3 C2 Tx by introducing O2  molecules during refluxing the Ti3 C2 Tx suspension. The subsequent etching away of these TiO2  nanoparticles by HF leaves behind numerous in-plane nanopores on the Ti3 C2 Tx sheets. Electrochemical impedance spectroscopy shows that longer oxidation time of 40 min yields holey Ti3 C2 Tx (H-Ti3 C2 Tx ) with a much shorter relax time constant of 0.85 s at electrode thickness of 25 µm, which is 89 times smaller than that of the pristineTi3 C2 Tx film (75.58 s). Meanwhile, H-Ti3 C2 Tx film with 25 min oxidation exhibits less-dependent capacitive performance in film thickness range of 10-84 µm (1.63-6.41 mg cm-2 ) and maintains around 60% capacitance as the current density increases from 1 to 50 A g-1 . The findings clearly demonstrate that in-plane nanopores not only provide more electrochemically active sites, but also offer numerous pathways for rapid ion impregnation across the thick Ti3 C2 Tx film. The method reported herein would pave way for fabricating porous MXene materials toward high-rate flexible supercapacitor applications.

Utilizing Cell Culture Assisted Anodization to Fabricate Aluminium Oxide with a Gradient Microstep and Nanopore Structure.

Anodic aluminum oxide (AAO) with a gradient microstep and nanopore structure (GMNP) is fabricated by inversely using cell culture to control the reaction areas in the electrochemical anodization, which shows a larger porosity than that of typical planar AAO. The figure of the microstep is influenced by the cell dehydration temperature which controls the cell shrinkage degree. A GMNP AAO with a diameter of 2.5 cm is achieved. Polymer with a gradient microstep and nanonipple structure is fabricated using the GMNP AAO as the template, which denotes that GMNP AAO could become a broad platform for the structural preparation of various materials with advanced functions.

Group Sparsity Mixture Model and Its Application on Image Denoising.

Prior learning is a fundamental problem in the field of image processing. In this paper, we conduct a detailed study on (1) how to model and learn the prior of the image patch group, which consists of a group of non-local similar image patches, and (2) how to apply the learned prior to the whole image denoising task. To tackle the first problem, we propose a new prior model named Group Sparsity Mixture Model (GSMM). With the bilateral matrix multiplication, the GSMM can model both the local feature of a single patch and the relation among non-local similar patches, and thus it is very suitable for patch group based prior learning. This is supported by the parameter analysis which demonstrates that the learned GSMM successfully captures the inherent strong sparsity embodied in the image patch group. Besides, as a mixture model, GSMM can be used for patch group classification. This makes the image denoising method based on GSMM capable of processing patch groups flexibly. To tackle the second problem, we propose an efficient and effective patch group based image denoising framework, which is plug-and-play and compatible with any patch group prior model. Using this framework, we construct two versions of GSMM based image denoising methods, both of which outperform the competing methods based on other prior models, e.g., Field of Experts (FoE) and Gaussian Mixture Model (GMM). Also, the better version is competitive with the state-of-the-art model based method WNNM with about ×8 faster average running speed.

HEMlets PoSh: Learning Part-Centric Heatmap Triplets for 3D Human Pose and Shape Estimation.

Estimating 3D human pose from a single image is a challenging task. This work attempts to address the uncertainty of lifting the detected 2D joints to the 3D space by introducing an intermediate state - Part-Centric Heatmap Triplets (HEMlets), which shortens the gap between the 2D observation and the 3D interpretation. The HEMlets utilize three joint-heatmaps to represent the relative depth information of the end-joints for each skeletal body part. In our approach, a Convolutional Network (ConvNet) is first trained to predict HEMlets from the input image, followed by a volumetric joint-heatmap regression. We leverage on the integral operation to extract the joint locations from the volumetric heatmaps, guaranteeing end-to-end learning. Despite the simplicity of the network design, the quantitative comparisons show a significant performance improvement over the best-of-grade methods (e.g., 20 percent on Human3.6M). The proposed method naturally supports training with "in-the-wild" images, where only weakly-annotated relative depth information of skeletal joints is available. This further improves the generalization ability of our model, as validated by qualitative comparisons on outdoor images. Leveraging the strength of the HEMlets pose estimation, we further design and append a shallow yet effective network module to regress the SMPL parameters of the body pose and shape. We term the entire HEMlets-based human pose and shape recovery pipeline HEMlets PoSh. Extensive quantitative and qualitative experiments on the existing human body recovery benchmarks justify the state-of-the-art results obtained with our HEMlets PoSh approach.

Air-Stable 2D Cr5 Te8 Nanosheets with Thickness-Tunable Ferromagnetism.

2D magnetic materials have aroused widespread research interest owing to their promising application in spintronic devices. However, exploring new kinds of 2D magnetic materials with better stability and realizing their batch synthesis remain challenging. Herein, the synthesis of air-stable 2D Cr5 Te8 ultrathin crystals with tunable thickness via tube-in-tube chemical vapor deposition (CVD) growth technology is reported. The importance of tube-in-tube CVD growth, which can significantly suppress the equilibrium shift to the decomposition direction and facilitate that to the synthesis reaction direction, for the synthesis of high-quality Cr5 Te8 with accurate composition, is highlighted. By precisely adjusting the growth temperature, the thickness of Cr5 Te8 nanosheets is tuned from ≈1.2 nm to tens of nanometers, with the morphology changing from triangles to hexagons. Furthermore, magneto-optical Kerr effect measurements reveal that the Cr5 Te8 nanosheet is ferromagnetic with strong out-of-plane spin polarization. The Curie temperature exhibits a monotonic increase from 100 to 160 K as the Cr5 Te8 thickness increases from 10 to 30 nm and no apparent variation in surface roughness or magnetic properties after months of exposure to air. This study provides a robust method for the controllable synthesis of high-quality 2D ferromagnetic materials, which will facilitate research progress in spintronics.

Optical encoding of luminescent carbon nanodots in confined spaces.

Stable emissive carbon nanodots were generated in zeolite crystals using near infrared photon irradiation gradually converting the occluded organic template, originally used to synthesize the zeolite crystals, into discrete luminescent species consisting of nano-sized carbogenic fluorophores, as ascertained using Raman microscopy, and steady-state and time-resolved spectroscopic techniques. Photoactivation in a confocal laser fluorescence microscope allows 3D resolved writing of luminescent carbon nanodot patterns inside zeolites providing a cost-effective and non-toxic alternative to previously reported metal-based nanoclusters confined in zeolites, and opens up opportunities in bio-labelling and sensing applications.

Image Co-Skeletonization via Co-Segmentation.

Recent advances in the joint processing of a set of images have shown its advantages over individual processing. Unlike the existing works geared towards co-segmentation or co-localization, in this article, we explore a new joint processing topic: image co-skeletonization, which is defined as joint skeleton extraction of the foreground objects in an image collection. It is well known that object skeletonization in a single natural image is challenging, because there is hardly any prior knowledge available about the object present in the image. Therefore, we resort to the idea of image co-skeletonization, hoping that the commonness prior that exists across the semantically similar images can be leveraged to have such knowledge, similar to other joint processing problems such as co-segmentation. Moreover, earlier research has found that augmenting a skeletonization process with the object's shape information is highly beneficial in capturing the image context. Having made these two observations, we propose a coupled framework for co-skeletonization and co-segmentation tasks to facilitate shape information discovery for our co-skeletonization process through the co-segmentation process. While image co-skeletonization is our primary goal, the co-segmentation process might also benefit, in turn, from exploiting skeleton outputs of the co-skeletonization process as central object seeds through such a coupled framework. As a result, both can benefit from each other synergistically. For evaluating image co-skeletonization results, we also construct a novel benchmark dataset by annotating nearly 1.8 K images and dividing them into 38 semantic categories. Although the proposed idea is essentially a weakly supervised method, it can also be employed in supervised and unsupervised scenarios. Extensive experiments demonstrate that the proposed method achieves promising results in all three scenarios.

An enhanced plasmonic photothermal effect for crystal transformation by a heat-trapping structure.

Photothermal utilization is an important approach for sustaining global ecological balance. Due to the enhancement of light absorption through surface plasmon resonance, silver or gold nanostructures can be used as efficient photothermal heat sources in visible and near-infrared regions. Herein, a heat-trapping system of self-assembled gold nanoislands with a thin Al2O3 layer is designed to significantly enhance the photothermal effect, which can contribute to a fast crystal transformation. Compared with pure gold nanoislands, an approximately 10-fold enhancement of the photothermal conversion efficiency is observed by using the heat-trapping layer, which results from enhanced light absorption and efficient heat utilization. With the heat-trapping layer, a relatively high and stable photothermal conversion efficiency is realized even at low temperature, and the thermal stability of the plasmonic nanostructure is also observed to improve, especially for silver nanoislands used in air. These results provide a strong additional support for the further development of photothermal applications and offer an efficient pathway for the thermal manipulation of plasmons at the nanoscale.

Study of interfacial random strain fields in core-shell ZnO nanowires by scanning transmission electron microscopy.

Imaging strain fields at the nanoscale is crucial for understanding the physical properties as well as the performance of oxide heterostructures and electronic devices. Based on scanning transmission electron microscopy (STEM) techniques, we successfully imaged the random strain field at the interface of core-shell ZnO nanowires. Combining experimental observations and image simulations, we find that the strain contrast originates from dechanneling of electrons and increased diffuse scattering induced by static atomic displacements. For a thin sample with a random strain field, a positive strain contrast appears in the low-angle annular dark-field (LAADF) image and a negative contrast in the high-angle annular dark-field (HAADF) image, but for a thick sample (> 120 nm), the positive contrast always occurs in both the LAADF and HAADF images. Through the analysis of the relationship between strain contrast and various parameters, we also discuss the optimum experimental condition for imaging random strain fields.

Bismuthene Nanosheets for 1 µm Multipulse Generation.

Bismuthene, as a new two-dimensional material made up of diazo metal elements, has drawn massive attention for its unique electronic, mechanical, quantum, and nonlinear optical properties. In recent years, researchers have increasingly turned their attention to the ultrafast photonics fields based on bismuthene. However, the internal ultrashort pulse dynamics has seldom been explored yet. In this work, the nonlinear optical properties of bismuthene nanosheets have been studied and applied in a passively mode-locked fiber laser. The saturation intensity and modulation depth of a saturable absorber (SA) device are about 2.4 MW/cm2 and 1%, respectively. Thanks to the narrow band gap of bismuthene and tapered fiber structure, a special kind of noise-like multipulses has been obtained. The evolution of the pulsed laser is also studied. This proposed pulsed fiber laser based on a bismuthene SA device is well suitable for some applications such as material processing, optical logics, and so forth.

Plasmon-Driven Rapid In Situ Formation of Luminescence Single Crystal Nanoparticle.

Single crystal nanomaterials are very important for the fundamental investigation and application of luminescence. However, a very critical growth condition or high temperature treatment is always required for their preparation. Here, an easy and rapid in situ achievement of a single crystal luminescent material is realized by taking advantage of plasmon-induced thermal and catalysis effects. With the assistance of localized surface plasmon resonance of Au nanoparticles, polycrystalline NaYF4 transforms to single crystal Y2 O3 in tens of milliseconds, resulting in remarkable improvement of luminescence emission. It is important to point out that the single crystal transformation is also achieved even at a very low temperature, which is impossible with conventional approaches. Such a convenient and efficient plasmon assisted scheme provides a new technology for the rapid achievement of single crystal materials and extends the application of surface plasmon to a much broader field.

Strain-induced high-temperature perovskite ferromagnetic insulator.

Ferromagnetic insulators are required for many new magnetic devices, such as dissipationless quantum-spintronic devices, magnetic tunneling junctions, etc. Ferromagnetic insulators with a high Curie temperature and a high-symmetry structure are critical integration with common single-crystalline oxide films or substrates. So far, the commonly used ferromagnetic insulators mostly possess low-symmetry structures associated with a poor growth quality and widespread properties. The few known high-symmetry materials either have extremely low Curie temperatures (≤16 K), or require chemical doping of an otherwise antiferromagnetic matrix. Here we present compelling evidence that the LaCoO3 single-crystalline thin film under tensile strain is a rare undoped perovskite ferromagnetic insulator with a remarkably high TC of up to 90 K. Both experiments and first-principles calculations demonstrate tensile-strain-induced ferromagnetism which does not exist in bulk LaCoO3 The ferromagnetism is strongest within a nearly stoichiometric structure, disappearing when the Co2+ defect concentration reaches about 10%. Significant impact of the research includes demonstration of a strain-induced high-temperature ferromagnetic insulator, successful elevation of the transition over the liquid-nitrogen temperature, and high potential for integration into large-area device fabrication processes.

CODE: Coherence Based Decision Boundaries for Feature Correspondence.

A key challenge in feature correspondence is the difficulty in differentiating true and false matches at a local descriptor level. This forces adoption of strict similarity thresholds that discard many true matches. However, if analyzed at a global level, false matches are usually randomly scattered while true matches tend to be coherent (clustered around a few dominant motions), thus creating a coherence based separability constraint. This paper proposes a non-linear regression technique that can discover such a coherence based separability constraint from highly noisy matches and embed it into a correspondence likelihood model. Once computed, the model can filter the entire set of nearest neighbor matches (which typically contains over 90 percent false matches) for true matches. We integrate our technique into a full feature correspondence system which reliably generates large numbers of good quality correspondences over wide baselines where previous techniques provide few or no matches.

PatchMatch Filter: Edge-Aware Filtering Meets Randomized Search for Visual Correspondence.

Though many tasks in computer vision can be formulated elegantly as pixel-labeling problems, a typical challenge discouraging such a discrete formulation is often due to computational efficiency. Recent studies on fast cost volume filtering based on efficient edge-aware filters provide a fast alternative to solve discrete labeling problems, with the complexity independent of the support window size. However, these methods still have to step through the entire cost volume exhaustively, which makes the solution speed scale linearly with the label space size. When the label space is huge or even infinite, which is often the case for (subpixel-accurate) stereo and optical flow estimation, their computational complexity becomes quickly unacceptable. Developed to search approximate nearest neighbors rapidly, the PatchMatch method can significantly reduce the complexity dependency on the search space size. But, its pixel-wise randomized search and fragmented data access within the 3D cost volume seriously hinder the application of efficient cost slice filtering. This paper presents a generic and fast computational framework for general multi-labeling problems called PatchMatch Filter (PMF). We explore effective and efficient strategies to weave together these two fundamental techniques developed in isolation, i.e., PatchMatch-based randomized search and efficient edge-aware image filtering. By decompositing an image into compact superpixels, we also propose superpixel-based novel search strategies that generalize and improve the original PatchMatch method. Further motivated to improve the regularization strength, we propose a simple yet effective cross-scale consistency constraint, which handles labeling estimation for large low-textured regions more reliably than a single-scale PMF algorithm. Focusing on dense correspondence field estimation in this paper, we demonstrate PMF's applications in stereo and optical flow. Our PMF methods achieve top-tier correspondence accuracy but run much faster than other related competing methods, often giving over 10-100 times speedup.

Ultrahigh Energy Storage Performance of Lead-Free Oxide Multilayer Film Capacitors via Interface Engineering.

Ultrahigh energy storage density of 52.4 J cm-3 with optimistic efficiency of 72.3% is achieved by interface engineering of epitaxial lead-free oxide multilayers at room temperature. Moreover, the excellent thermal stability of the performances provides solid basis for widespread applications of the thin film systems in modern electronic and power modules in harsh working environments.