Enhanced electrocatalytic biomass oxidation at low voltage by Ni2+-O-Pd interfaces.

Challenges in direct catalytic oxidation of biomass-derived aldehyde and alcohol into acid with high activity and selectivity hinder the widespread biomass application. Herein, we demonstrate that a Pd/Ni(OH)2 catalyst with abundant Ni2+-O-Pd interfaces allows electrooxidation of 5-hydroxymethylfurfural to 2, 5-furandicarboxylic acid with a selectivity near 100 % and 2, 5-furandicarboxylic acid yield of 97.3% at 0.6 volts (versus a reversible hydrogen electrode) in 1 M KOH electrolyte under ambient conditions. The rate-determining step of the intermediate oxidation of 5-hydroxymethyl-2-furancarboxylic acid is promoted by the increased OH species and low C-H activation energy barrier at Ni2+-O-Pd interfaces. Further, the Ni2+-O-Pd interfaces prevent the agglomeration of Pd nanoparticles during the reaction, greatly improving the stability of the catalyst. In this work, Pd/Ni(OH)2 catalyst can achieve 100% 5-hydroxymethylfurfural conversion and >90% 2, 5-furandicarboxylic acid selectivity in a flow-cell and work stably over 200 h under a fixed cell voltage of 0.85 V.

PERF: Panoramic Neural Radiance Field from a Single Panorama.

Neural Radiance Field (NeRF) has achieved substantial progress in novel view synthesis given multi-view images. Recently, some works have attempted to train a NeRF from a single image with 3D priors. They mainly focus on a limited field of view with a few occlusions, which greatly limits their scalability to real-world 360-degree panoramic scenarios with large-size occlusions. In this paper, we present PERF, a 360-degree novel view synthesis framework that trains a panoramic neural radiance field from a single panorama. Notably, PERF allows 3D roaming in a complex scene without expensive and tedious image collection. To achieve this goal, we propose a novel collaborative RGBD inpainting method and a progressive inpainting-and-erasing method to lift up a 360-degree 2D scene to a 3D scene. Specifically, we first predict a panoramic depth map as initialization given a single panorama and reconstruct visible 3D regions with volume rendering. Then we introduce a collaborative RGBD inpainting approach into a NeRF for completing RGB images and depth maps from random views, which is derived from an RGB Stable Diffusion model and a monocular depth estimator. Finally, we introduce an inpainting-and-erasing strategy to avoid inconsistent geometry between a newly-sampled view and reference views. The two components are integrated into the learning of NeRFs in a unified optimization framework and achieve promising results. Extensive experiments on Replica and a new dataset PERF-in-the-wild demonstrate the superiority of our PERF over state-of-the-art methods. Our PERF can be widely used for real-world applications, such as panorama-to-3D, text-to-3D, and 3D scene stylization applications. Project page and code are available at https://github.com/perf-project/PeRF.

Integrated lithium niobate microwave photonic processing engine.

Integrated microwave photonics (MWP) is an intriguing technology for the generation, transmission and manipulation of microwave signals in chip-scale optical systems1,2. In particular, ultrafast processing of analogue signals in the optical domain with high fidelity and low latency could enable a variety of applications such as MWP filters3-5, microwave signal processing6-9 and image recognition10,11. An ideal integrated MWP processing platform should have both an efficient and high-speed electro-optic modulation block to faithfully perform microwave-optic conversion at low power and also a low-loss functional photonic network to implement various signal-processing tasks. Moreover, large-scale, low-cost manufacturability is required to monolithically integrate the two building blocks on the same chip. Here we demonstrate such an integrated MWP processing engine based on a 4 inch wafer-scale thin-film lithium niobate platform. It can perform multipurpose tasks with processing bandwidths of up to 67 GHz at complementary metal-oxide-semiconductor (CMOS)-compatible voltages. We achieve ultrafast analogue computation, namely temporal integration and differentiation, at sampling rates of up to 256 giga samples per second, and deploy these functions to showcase three proof-of-concept applications: solving ordinary differential equations, generating ultra-wideband signals and detecting edges in images. We further leverage the image edge detector to realize a photonic-assisted image segmentation model that can effectively outline the boundaries of melanoma lesion in medical diagnostic images. Our ultrafast lithium niobate MWP engine could provide compact, low-latency and cost-effective solutions for future wireless communications, high-resolution radar and photonic artificial intelligence.

Spectral Engineering of Optical Microresonators in Anisotropic Lithium Niobate Crystal.

On-chip optical microresonators are essential building blocks in integrated optics. The ability to arbitrarily engineer their resonant frequencies is crucial for exploring novel physics in synthetic frequency dimensions and practical applications like nonlinear optical parametric processes and dispersion-engineered frequency comb generation. Photonic crystal ring (PhCR) resonators are a versatile tool for such arbitrary frequency engineering, by controllably creating mode splitting at selected resonances. To date, these PhCRs have mostly been demonstrated in isotropic photonic materials, while such engineering can be significantly more complicated in anisotropic platforms that often offer more fruitful optical properties. Here, the spectral engineering of chip-scale optical microresonators is realized in the anisotropic lithium niobate (LN) crystal by a gradient design that precisely compensates for variations in both refractive index and perturbation strength. Controllable frequency splitting is experimentally demonstrated at single and multiple selected resonances in LN PhCR resonators with different sizes, while maintaining high quality-factors up to 1 × 106. Moreover, a sharp boundary is experimentally constructed in the synthetic frequency dimension based on an actively modulated x-cut LN gradient-PhCR, opening up new paths toward the arbitrary control of electro-optic comb spectral shapes and exploration of novel physics in the frequency degree of freedom.

Unraveling the Nanoscale Segregation Mechanism in N-Doped Niobium for Enhanced SRF Performance.

The nitrogen doping (N-doping) treatment for niobium superconducting radio-frequency (SRF) cavities is one of the key enabling technologies that support the development of more efficient future large accelerators. However, the N-doping results have diverged due to a complex chemical profile under the nitrogen-doped surface. Particularly, under industrial-scale production conditions, it is difficult to understand the underlying mechanism thus hindering performance improvement. Herein, a combination of spatially resolved and surface-sensitive approaches is employed to establish the detailed near-surface phase composition of thermally processed niobium. The results show that intermediate phase segregations, particularly the nanometric carbon-rich phase, can impede the nitridation process and limit the interactions between nitrogen and the niobium sub-surface. In comparison, the removal of the carbon-rich layer at the Nb surface leads to enhanced nitrogen binding at the Nb surface. Combining the RF test results, it is shown that the complex uniformity and grain boundary penetrations of impurity elements have a direct correlation with the mid-field quench behavior in the N-doped Nb cavities. Therefore, proper control of the nanometric intermediate phase formation in discrete thermal steps is critical in improving the ultimate performance and production yield of the Nb cavities.

SceneDreamer: Unbounded 3D Scene Generation From 2D Image Collections.

In this work, we present SceneDreamer, an unconditional generative model for unbounded 3D scenes, which synthesizes large-scale 3D landscapes from random noise. Our framework is learned from in-the-wild 2D image collections only, without any 3D annotations. At the core of SceneDreamer is a principled learning paradigm comprising: 1) an efficient yet expressive 3D scene representation, 2) a generative scene parameterization, and 3) an effective renderer that can leverage the knowledge from 2D images. Our approach begins with an efficient bird's-eye-view (BEV) representation generated from simplex noise, which includes a height field for surface elevation and a semantic field for detailed scene semantics. This BEV scene representation enables: 1) representing a 3D scene with quadratic complexity, 2) disentangled geometry and semantics, and 3) efficient training. Moreover, we propose a novel generative neural hash grid to parameterize the latent space based on 3D positions and scene semantics, aiming to encode generalizable features across various scenes. Lastly, a neural volumetric renderer, learned from 2D image collections through adversarial training, is employed to produce photorealistic images. Extensive experiments demonstrate the effectiveness of SceneDreamer and superiority over state-of-the-art methods in generating vivid yet diverse unbounded 3D worlds.

Efficient second- and higher-order harmonic generation from LiNbO3 metasurfaces.

Lithium niobate (LiNbO3) is a material that has drawn great interest in nonlinear optics because of its large nonlinear susceptibility and wide transparency window. However, for complex nonlinear processes such as high-harmonic generation (HHG), which involves frequency conversion over a wide frequency range, it can be extremely challenging for a bulk LiNbO3 crystal to fulfill the phase-matching conditions. LiNbO3 metasurfaces with resonantly enhanced nonlinear light-matter interaction at the nanoscale may circumvent such an issue. Here, we experimentally demonstrate efficient second-harmonic generation (SHG) and HHG from a LiNbO3 metasurface enhanced by guided-mode resonance. We observe a high normalized SHG efficiency of 5.1 × 10-5 cm2 GW-1. Moreover, with the alleviated above-gap absorption of the material, we demonstrate HHG up to the 7th order with the shortest generated wavelength of 226 nm. This work may provide a pathway towards compact coherent white-light sources with frequency spanning into the deep ultraviolet region for applications in spectroscopy and imaging.

Effects of degradation on the physicochemical and antioxidant properties of carboxymethyl pachymaran.

Poria cocos (Schw.) Wolf is a well-known edible and medicinal fungus. The polysaccharide in the sclerotium of P. cocos was extracted and prepared into carboxymethyl pachymaran (CMP). Three different degradation treatments including high temperature (HT), high pressure (HP) and gamma irradiation (GI) were used to process CMP. The changes in physicochemical properties and antioxidant activities of CMP were then comparatively investigated. We found that the molecular weights of HT-CMP, HP-CMP, and GI-CMP decreased from 787.9 kDa to 429.8, 569.5 and 6.0 kDa, respectively. Degradation treatments had no effect on the main chains of →3-ß-D-Glcp-(1 â†’ while changed the branched sugar residues. The polysaccharide chains of CMP were depolymerized after high pressure and gamma irradiation treatments. The three degradation methods improved the stability of CMP solution while decreased the thermal stability of CMP. In addition, we found that the GI-CMP with lowest molecular weight had the best antioxidant activity. Our results suggest that gamma irradiation treatment could degrade CMP as functional foods with strong antioxidant activity.

The Human Activity Radar Challenge: benchmarking based on the 'Radar signatures of human activities' dataset from Glasgow University.

Radar is an extremely valuable sensing technology for detecting moving targets and measuring their range, velocity, and angular positions. When people are monitored at home, radar is more likely to be accepted by end-users, as they already use WiFi, is perceived as privacy-preserving compared to cameras, and does not require user compliance as wearable sensors do. Furthermore, it is not affected by lighting condi-tions nor requires artificial lights that could cause discomfort in the home environment. So, radar-based human activities classification in the context of assisted living can empower an aging society to live at home independently longer. However, challenges remain as to the formulation of the most effective algorithms for radar-based human activities classification and their validation. To promote the exploration and cross-evaluation of different algorithms, our dataset released in 2019 was used to benchmark various classification approaches. The challenge was open from February 2020 to December 2020. A total of 23 organizations worldwide, forming 12 teams from academia and industry, participated in the inaugural Radar Challenge, and submitted 188 valid entries to the challenge. This paper presents an overview and evaluation of the approaches used for all primary contributions in this inaugural challenge. The proposed algorithms are summarized, and the main parameters affecting their performances are analyzed.

Atomic-level structural responsiveness to environmental conditions from 3D electron diffraction.

Electron microscopy has been widely used in the structural analysis of proteins, pharmaceutical products, and various functional materials in the past decades. However, one fact is often overlooked that the crystal structure might be sensitive to external environments and response manners, which will bring uncertainty to the structure determination and structure-property correlation. Here, we report the atomic-level ab initio structure determinations of microcrystals by combining 3D electron diffraction (3D ED) and environmental transmission electron microscope (TEM). Environmental conditions, including cryo, heating, gas and liquid, have been successfully achieved using in situ holders to reveal the simuli-responsive structures of crystals. Remarkable structural changes have been directly resolved by 3D ED in one flexible metal-organic framework, MIL-53, owing to the response of framework to pressures, temperatures, guest molecules, etc.

Efficient erbium-doped thin-film lithium niobate waveguide amplifiers.

Lithium niobate on insulator (LNOI) is an emerging photonic platform with great promise for use in future optical communications, nonlinear optics, and microwave photonics. An important integrated photonic building block, active waveguide amplifiers, however, are still missing in the LNOI platform. Here, we report an efficient and compact waveguide amplifier based on erbium-doped LNOI waveguides, achieved using a sequence of erbium-doped crystal growth, ion slicing, and lithography-based waveguide fabrication. Using a compact 5 mm long waveguide, we demonstrate an on-chip net gain of >5dB for 1530 nm signal light with a relatively low pump power of 21 mW at 980 nm. The efficient LNOI waveguide amplifiers could become an important fundamental element in future lithium niobate photonic integrated circuits.

Proof-of-principle demonstration of measurement-device-independent quantum key distribution based on intrinsically stable polarization-modulated units.

The experimental demonstration of measurement-device-independent quantum key distribution (MDI-QKD) has been widely demonstrated. Thus far, several experimental groups have implemented polarization encoding MDI-QKD but with manual polarization controllers, or polarization modulators that make circular polarization states unstable. Here, we apply an intrinsically stable polarization-modulated unit (PMU) to MDI-QKD so that Alice and Bob can modulate four BB84 polarization states, all of which can be kept stable from even the harsh environment. Moreover, our PMU can provide two operational polarization encoding modes suitable to different application scenarios. A proof-of-principle demonstration of MDI-QKD based on our PMU is implemented with an interference visibility of 46.6%, an average quantum bit error rate of 1.49% for the Z basis and the secure key rate of 4.25 × 10-6 bits per pulse. The proposed study is helpful for building polarization encoding MDI-QKD systems with better stability.

Magnetic Submicron Mullite Coatings with Oriented SiC Whiskers.

Addressing the challenge of making ceramic thin films with the in-plane-oriented nanorods, we propose to decorate the nanorods with magnetic nanoparticles and orient them using the external magnetic field. As an illustration, the mullite thin films with embedded and oriented SiC nanorods were synthesized. The SiC nanorods were decorated with the Fe3O4 nanoparticles. A two-step processing route was developed when the nanorods are first oriented in a sacrificial polymer layer. Then, the polymer film with the aligned nanorods was removed by heat-treatment. In the second step, a sol-gel/dip-coating method was applied to produce the mullite composite film. The main challenge was to guarantee that all of the nanorods that were initially randomly distributed in the polymer would have time to rotate toward the field direction before complete solidification of the sacrificial layer. Theoretical and experimental analyses of the orientational distribution of the nanorod axes were conducted to identify a relationship between the polymer viscosity and processing parameters of the system. In contrast to the ferromagnetic nanorods, the rate of rotation of paramagnetic nanorods and their time of alignment are more sensitive to the magnetic field. This methodology allows manufacturing of different ceramic films with aligned nanorods and making nonmagnetic ceramic coating magnetic.

Kinetics of evaporation and gel formation in thin films of ceramic precursors.

Precursors derived from the hydrolysis of organic or inorganic salts have been widely used to produce ceramic coatings for a broad variety of applications. When applying the liquid precursors to the substrates, it is extremely challenging to control the film uniformity and homogeneity. The rate of solvent evaporation at different locations is different, causing the viscosity variation and flows in the film. There is very limited knowledge about the viscosity change in evaporating ceramic precursors. Therefore, it is crucial to understand the effect of evaporation on viscosity variation in thin films and droplets. We use magnetic rotational spectroscopy to study the time dependence of viscosity in mullite precursors. A correlation between the viscosity change and evaporation kinetics is revealed. This correlation was used to relate the change of viscosity to the concentration of mullite. A master curve relating viscosity to the mullite concentration was constructed and used to propose a possible scenario of the viscosity increase during solvent evaporation.