Metal-to-insulator transition (MIT) behaviors accompanied by a rapid reversible phase transition in vanadium dioxide (VO2) have gained substantial attention for investigations into various potential ...applications and obtaining good materials to study strongly correlated electronic behaviors in transition metal oxides (TMOs). Although its phase-transition mechanism is still controversial, during the past few decades, people have made great efforts in understanding the MIT mechanism, which could also benefit the investigation of MIT modulation. This review summarizes the recent progress in the phase-transition mechanism and modulation of VO2 materials. A representative understanding on the phase-transition mechanism, such as the lattice distortion and electron correlations, are discussed. Based on the research of the phase-transition mechanism, modulation methods, such as element doping, electric field (current and gating), and tensile/compression strain, as well as employing lasers, are summarized for comparison. Finally, discussions on future trends and perspectives are also provided. This review gives a comprehensive understanding of the mechanism of MIT behaviors and the phase-transition modulations.
In view of the various stability issues and high cost of enzymatic glucose biosensors, non-enzymatic biosensors have received great attention in recent research and development. Copper oxide (CuO) ...nanowires (NWs) were fabricated on Cu foil substrate using a simple thermal oxidation method. The phase and morphology of the CuO NWs could be controlled by synthesis temperature. Variation in oxidation states enables CuO NWs to form Cu (III) species, which is crucial in catalysing the eletro-oxidation of glucose. The Cu-based metal/oxide composite electrode works as a non-enzymatic biosensor that adapts to the fast, dynamic change in glucose concentration, with a low saturation concentration (~0.7 mM) and a lower detection limit of 0.1 mM, making CuO NWs an excellent sensor towards impaired fasting glucose. The simplicity, cost-effectiveness and non-toxicity features of this study might make a way for potentially scalable application in glucose biosensing.
To understand the formation process of ordered Au nano-ring arrays (NRA), a series of factors—including etchant gas and flow rate, chamber pressure and RF power—were systematically studied and a set ...of optimum parameters were deduced to fabricate this interesting structure. With plenty of active sites previously reported, a new role of ordered Au NRA is unlocked in this work. The ordered Au NRA could perform the electrochemical removal of rhodamine 6G (R-6G) at a high concentration in seawater within 12 min and complete discoloration within 9 min, which demonstrates ~7 times efficiency improvement from previous studies. The nanostructured surface also makes the ordered Au NRA a good substrate material in R-6G sensing using surface-enhanced Raman spectroscopy, which performs with better accuracy than the ultraviolet–visible light technique.
This article proposes an end-to-end learnt lossy image compression approach, which is built on top of the deep nerual network (DNN)-based variational auto-encoder (VAE) structure with Non-Local ...Attention optimization and Improved Context modeling (NLAIC). Our NLAIC 1) embeds non-local network operations as non-linear transforms in both main and hyper coders for deriving respective latent features and hyperpriors by exploiting both local and global correlations, 2) applies attention mechanism to generate implicit masks that are used to weigh the features for adaptive bit allocation, and 3) implements the improved conditional entropy modeling of latent features using joint 3D convolutional neural network (CNN)-based autoregressive contexts and hyperpriors. Towards the practical application, additional enhancements are also introduced to speed up the computational processing (e.g., parallel 3D CNN-based context prediction), decrease the memory consumption (e.g., sparse non-local processing) and reduce the implementation complexity (e.g., a unified model for variable rates without re-training). The proposed model outperforms existing learnt and conventional (e.g., BPG, JPEG2000, JPEG) image compression methods, on both Kodak and Tecnick datasets with the state-of-the-art compression efficiency, for both PSNR and MS-SSIM quality measurements. We have made all materials publicly accessible at https://njuvision.github.io/NIC for reproducible research.
Hyperspectral imaging has many applications from agriculture and astronomy to surveillance and mineralogy. However, it is often challenging to obtain high-resolution (HR) hyperspectral images using ...existing hyperspectral imaging techniques due to various hardware limitations. In this paper, we propose a new hyperspectral image super-resolution method from a low-resolution (LR) image and a HR reference image of the same scene. The estimation of the HR hyperspectral image is formulated as a joint estimation of the hyperspectral dictionary and the sparse codes based on the prior knowledge of the spatial-spectral sparsity of the hyperspectral image. The hyperspectral dictionary representing prototype reflectance spectra vectors of the scene is first learned from the input LR image. Specifically, an efficient non-negative dictionary learning algorithm using the block-coordinate descent optimization technique is proposed. Then, the sparse codes of the desired HR hyperspectral image with respect to learned hyperspectral basis are estimated from the pair of LR and HR reference images. To improve the accuracy of non-negative sparse coding, a clustering-based structured sparse coding method is proposed to exploit the spatial correlation among the learned sparse codes. The experimental results on both public datasets and real LR hypspectral images suggest that the proposed method substantially outperforms several existing HR hyperspectral image recovery techniques in the literature in terms of both objective quality metrics and computational efficiency.
The perovskite solar cell has emerged rapidly in the field of photovoltaics as it combines the merits of low cost, high efficiency, and excellent mechanical flexibility for versatile applications. ...However, there are significant concerns regarding its operational stability and mechanical robustness. Most of the previously reported approaches to address these concerns entail separate engineering of perovskite and charge-transporting layers. Herein we present a holistic design of perovskite and charge-transporting layers by synthesizing an interpenetrating perovskite/electron-transporting-layer interface. This interface is reaction-formed between a tin dioxide layer containing excess organic halide and a perovskite layer containing excess lead halide. Perovskite solar cells with such interfaces deliver efficiencies up to 22.2% and 20.1% for rigid and flexible versions, respectively. Long-term (1000 h) operational stability is demonstrated and the flexible devices show high endurance against mechanical-bending (2500 cycles) fatigue. Mechanistic insights into the relationship between the interpenetrating interface structure and performance enhancement are provided based on comprehensive, advanced, microscopic characterizations. This study highlights interface integrity as an important factor for designing efficient, operationally-stable, and mechanically-robust solar cells.
Ideal imaging, which is constantly pursued, requires the collection of all kinds of optical information of the objects in view, such as three-dimensional spatial information (3D) including the planar ...distribution and depth, and the colors, i.e., spectral information (1D). Although three-dimensional spatial imaging and spectral imaging have individually evolved rapidly, their straightforward combination is a cumbersome system, severely hindering the practical applications of four-dimensional (4D) imaging. Here, we demonstrate the ultra-compact spectral light-field imaging (SLIM) by using a transversely dispersive metalens array and a monochrome imaging sensor. With only one snapshot, the SLIM presents advanced imaging with a 4 nm spectral resolution and near-diffraction-limit spatial resolution. Consequently, visually indistinguishable objects and materials can be discriminated through SLIM, which promotes significant progress towards ideal plenoptic imaging.
Two-dimensional (2D) magnets with intrinsic ferromagnetic/antiferromagnetic (FM/AFM) ordering are highly desirable for future spintronic devices. However, the direct growth of their crystals is in ...its infancy. Here we report a chemical vapor deposition approach to controllably grow layered tetragonal and non-layered hexagonal FeTe nanoplates with their thicknesses down to 3.6 and 2.8 nm, respectively. Moreover, transport measurements reveal these obtained FeTe nanoflakes show a thickness-dependent magnetic transition. Antiferromagnetic tetragonal FeTe with the Néel temperature (T
) gradually decreases from 70 to 45 K as the thickness declines from 32 to 5 nm. And ferromagnetic hexagonal FeTe is accompanied by a drop of the Curie temperature (T
) from 220 K (30 nm) to 170 K (4 nm). Theoretical calculations indicate that the ferromagnetic order in hexagonal FeTe is originated from its concomitant lattice distortion and Stoner instability. This study highlights its potential applications in future spintronic devices.
Abstract
Thermoelectrics enable waste heat recovery, holding promises in relieving energy and environmental crisis. Lillianite materials have been long-term ignored due to low thermoelectric ...efficiency. Herein we report the discovery of superior thermoelectric performance in Pb
7
Bi
4
Se
13
based lillianites, with a peak figure of merit,
zT
of 1.35 at 800 K and a high average
zT
of 0.92 (450–800 K). A unique quality factor is established to predict and evaluate thermoelectric performances. It considers both band nonparabolicity and band gaps, commonly negligible in conventional quality factors. Such appealing performance is attributed to the convergence of effectively nested conduction bands, providing a high number of valley degeneracy, and a low thermal conductivity, stemming from large lattice anharmonicity, low-frequency localized Einstein modes and the coexistence of high-density moiré fringes and nanoscale defects. This work rekindles the vision that Pb
7
Bi
4
Se
13
based lillianites are promising candidates for highly efficient thermoelectric energy conversion.
The Boltzmann distribution of electrons sets a fundamental barrier to lowering energy consumption in metal-oxide-semiconductor field-effect transistors (MOSFETs). Negative capacitance FET (NC-FET), ...as an emerging FET architecture, is promising to overcome this thermionic limit and build ultra-low-power consuming electronics. Here, we demonstrate steep-slope NC-FETs based on two-dimensional molybdenum disulfide and CuInP
S
(CIPS) van der Waals (vdW) heterostructure. The vdW NC-FET provides an average subthreshold swing (SS) less than the Boltzmann's limit for over seven decades of drain current, with a minimum SS of 28 mV dec
. Negligible hysteresis is achieved in NC-FETs with the thickness of CIPS less than 20 nm. A voltage gain of 24 is measured for vdW NC-FET logic inverter. Flexible vdW NC-FET is further demonstrated with sub-60 mV dec
switching characteristics under the bending radius down to 3.8 mm. These results demonstrate the great potential of vdW NC-FET for ultra-low-power and flexible applications.
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