Abstract
Glucose electrolysis offers a prospect of value-added glucaric acid synthesis and energy-saving hydrogen production from the biomass-based platform molecules. Here we report that ...nanostructured NiFe oxide (NiFeO
x
) and nitride (NiFeN
x
) catalysts, synthesized from NiFe layered double hydroxide nanosheet arrays on three-dimensional Ni foams, demonstrate a high activity and selectivity towards anodic glucose oxidation. The electrolytic cell assembled with these two catalysts can deliver 100 mA cm
−2
at 1.39 V. A faradaic efficiency of 87% and glucaric acid yield of 83% are obtained from the glucose electrolysis, which takes place via a guluronic acid pathway evidenced by in-situ infrared spectroscopy. A rigorous process model combined with a techno-economic analysis shows that the electrochemical reduction of glucose produces glucaric acid at a 54% lower cost than the current chemical approach. This work suggests that glucose electrolysis is an energy-saving and cost-effective approach for H
2
production and biomass valorization.
Ferroelectricity usually fades away as materials are thinned down below a critical value. We reveal that the unique ionic-potential anharmonicity can induce spontaneous in-plane electrical ...polarization and ferroelectricity in monolayer group-IV monochalcogenides MX (M=Ge, Sn; X=S, Se). An effective Hamiltonian has been successfully extracted from the parametrized energy space, making it possible to study the ferroelectric phase transitions in a single-atom layer. The ferroelectricity in these materials is found to be robust and the corresponding Curie temperatures are higher than room temperature, making them promising for realizing ultrathin ferroelectric devices of broad interest. We further provide the phase diagram and predict other potentially two-dimensional ferroelectric materials.
We introduce a near-threshold parameterization that is more general than the effective-range expansion up to and including the effective range because it can also handle a near-threshold zero in the
...D
0
D
¯
∗
0
S
-wave. In terms of it we analyze the CDF data on inclusive
p
p
¯
scattering to
J
/
ψ
π
+
π
-
, and the Belle and BaBar data on
B
decays to
K
J
/
ψ
π
+
π
-
and
K
D
D
¯
∗
0
around the
D
0
D
¯
∗
0
threshold. It is shown that data can be reproduced with similar quality for
X
(3872) being a bound and/or a virtual state. We also find that
X
(3872) might be a higher-order virtual-state pole (double or triplet pole), in the limit in which the small
D
∗
0
width vanishes. Once the latter is restored the corrections to the pole position are non-analytic and much bigger than the
D
∗
0
width itself. The
X
(3872) compositeness coefficient in
D
0
D
¯
∗
0
ranges from nearly 0 up to 1 in the different scenarios.
Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and ...identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.
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•AI system that can diagnose COVID-19 pneumonia using CT scans•Prediction of progression to critical illness•Potential to improve performance of junior radiologists to the senior level•Can assist evaluation of drug treatment effects with CT quantification
Zhang et al. present an AI-based system, based on hundreds of thousands of human lung CT scan images, that can aid in distinguishing patients NCP versus other common pneumonia and can help to predict the prognosis of COVID-19 patients.
Pd-catalyzed cross-coupling reactions have become essential tools for the construction of carbon–carbon and carbon–heteroatom bonds. Over the last three decades, great efforts have been made with ...cross-coupling chemistry in the discovery, development, and commercialization of innovative new pharmaceuticals and agrochemicals (mainly herbicides, fungicides, and insecticides). In view of the growing interest in both modern crop protection and cross-coupling chemistry, this review gives a comprehensive overview of the successful applications of various Pd-catalyzed cross-coupling methodologies, which have been implemented as key steps in the synthesis of agrochemicals (on R&D and pilot-plant scales) such as the Heck, Suzuki, Sonogashira, Stille, and Negishi reactions, as well as decarboxylative, carbonylative, α-arylative, and carbon–nitrogen bond bond-forming cross-coupling reactions. Some perspectives and challenges for these catalytic coupling processes in the discovery of agrochemicals are briefly discussed in the final section. The examples chosen demonstrate that cross-coupling chemistry approaches open-up new, low-cost, and more efficient industrial routes to existing agrochemicals, and such methods also have the capability to lead the new generation of pesticides with novel modes of action for sustainable crop protection.
Under topological guidance, the self‐assembly process based on a tetratopic porphyrin synthon results in a hydrogen‐bonded organic framework (HOF) with the predicted square layers topology (sql) but ...unsatisfied stability. Strikingly, simply introducing a transition metal in the porphyrin center does not change the network topology but drastically causes noticeable change on noncovalent interaction, orbital overlap, and molecular geometry, therefore ultimately giving rise to a series of metalloporphyrinic HOFs with high surface area, and excellent stability (intact after being soaked in boiling water, concentrated HCl, and heated to 270 °C). On integrating both photosensitizers and catalytic sites into robust backbones, this series of HOFs can effectively catalyze the photoreduction of CO2 to CO, and their catalytic performances greatly depend on the chelated metal species in the porphyrin centers. This work enriches the library of stable functional HOFs and expands their applications in photocatalytic CO2 reduction.
Crystallographic and computational studies on a series of porphyrinic hydrogen‐bonded organic frameworks (HOFs) reveal that metallization of porphyrin centers greatly alters the orbital overlap of the adjacent porphyrin, the geometry of the molecule/layer, and the strength of noncovalent interactions. Therefore, metalloporphyrin HOFs exhibit much higher stability, surface area, and catalytic activity than metal‐free porphyrinic HOFs.
Co3O4 with a high theoretical capacitance has been widely recognized as a promising electrode material for supercapacitor, but its poor electrical conductivity and stability limit its practical ...applications. Here, we developed an effective synthetic route to synthesize one-dimensional (1D) porous ZnO/Co3O4 heterojunction composites. Benefiting from the heterostructure to promote the charge transfer and protect Co3O4 from corrosion and the 1D porous structure to improve ion diffusion and prevent structural collapse in charge and discharge process, the as-prepared ZnO/Co3O4 composites exhibited an excellent capacitive performance and good cycling stability. The specific capacitance of the ZnO/Co3O4-450 (1135 F g–1 at 1 A g–1) was 1.4 times higher than that of Co3O4 (814 F g–1), and the high-rate performance for ZnO/Co3O4-450 was 4.9 times better than that of Co3O4. Also, approximately 83% of its specific capacitance was retained after 5000 cycles at 10 A g–1. Most importantly, the as-fabricated asymmetric supercapacitor, with a ZnO/Co3O4-450 positive electrode and an activated carbon negative electrode, delivered a prominent energy density of 47.7 W h kg–1 and a high power density of 7500 W kg–1. Thus, the ZnO/Co3O4 composites could serve as a high-activity material for supercapacitor and the preparation method also offers an attractive strategy to enhance the capacitive performance of Co3O4.
Summary
Lycoris radiata is a main source of Amaryllidaceae alkaloids; however, the low content of these alkaloids in planta remains a limit to their pharmaceutical development and utilization. The ...accumulation of secondary metabolites can be enhanced in plants inoculated with fungal endophytes. In this study, we analysed the diversity of culturable fungal endophytes in different organs of L. radiata. Then, by analysing the correlation between the detectable rate of each fungal species and the content of each tested alkaloid, we proposed several fungal candidates implicated in the increase of alkaloid accumulation. This was verified by inoculating these candidates to L. radiata plants. Based on the results of two independent experiments conducted in May 2018 and October 2019, the individual inoculation of nine fungal endophytes significantly increased the total content of the tested alkaloids in the entire L. radiata plants. This is the first study in L. radiata to show that fungal endophytes are able to improve the accumulation of various alkaloids. Therefore, our results provide insights into a better understanding of interactions between plants and fungal endophytes and suggest an effective strategy for enhancing the alkaloid content in the cultivation of L. radiata.
Rain removal from a video is a challenging problem and has been recently investigated extensively. Nevertheless, the problem of rain removal from a single image was rarely studied in the literature, ...where no temporal information among successive images can be exploited, making the problem very challenging. In this paper, we propose a single-image-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis. Instead of directly applying a conventional image decomposition technique, the proposed method first decomposes an image into the low- and high-frequency (HF) parts using a bilateral filter. The HF part is then decomposed into a "rain component" and a "nonrain component" by performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Experimental results demonstrate the efficacy of the proposed algorithm.
Images/videos captured from outdoor visual devices are usually degraded by turbid media, such as haze, smoke, fog, rain, and snow. Haze is the most common one in outdoor scenes due to the atmosphere ...conditions. In this paper, a novel deep learning-based architecture (denoted by MSRL-DehazeNet) for single image haze removal relying on multi-scale residual learning (MSRL) and image decomposition is proposed. Instead of learning an end-to-end mapping between each pair of hazy image and its corresponding haze-free one adopted by most existing learning-based approaches, we reformulate the problem as restoration of the image base component. Based on the decomposition of a hazy image into the base and the detail components, haze removal (or dehazing) can be achieved by both of our multi-scale deep residual learning and our simplified U-Net learning only for mapping between hazy and haze-free base components, while the detail component is further enhanced via the other learned convolutional neural network (CNN). Moreover, benefited by the basic building block of our deep residual CNN architecture and our simplified U-Net structure, the feature maps (produced by extracting structural and statistical features), and each previous layer can be fully preserved and fed into the next layer. Therefore, possible color distortion in the recovered image would be avoided. As a result, the final haze-removed (or dehazed) image is obtained by integrating the haze-removed base and the enhanced detail image components. Experimental results have demonstrated good effectiveness of the proposed framework, compared with state-of-the-art approaches.
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