As the cornerstone for joint dimension reduction and feature extraction, extensive linear projection algorithms were proposed to fit various requirements. When being applied to image data, however, ...existing methods suffer from representation deficiency since the multi-way structure of the data is (partially) neglected. To solve this problem, we propose a novel Low-Rank Preserving t-Linear Projection (LRP-tP) model that preserves the intrinsic structure of the image data using t-product-based operations. The proposed model advances in four aspects: 1) LRP-tP learns the t-linear projection directly from the tensorial dataset so as to exploit the correlation among the multi-way data structure simultaneously; 2) to cope with the widely spread data errors, e.g., noise and corruptions, the robustness of LRP-tP is enhanced via self-representation learning; 3) LRP-tP is endowed with good discriminative ability by integrating the empirical classification error into the learning procedure; 4) an adaptive graph considering the similarity and locality of the data is jointly learned to precisely portray the data affinity. We devise an efficient algorithm to solve the proposed LRP-tP model using the alternating direction method of multipliers. Extensive experiments on image feature extraction have demonstrated the superiority of LRP-tP compared to the state-of-the-arts.
Plasmonic core–shell nanostructures have attracted considerable attention in the scientific community recently due to their highly tunable optical properties. Plasmon‐enhanced spectroscopies are one ...of the main applications of plasmonic nanomaterials. When excited by an incident laser of suitable wavelength, strong and highly localized electromagnetic (EM) fields are generated around plasmonic nanomaterials, which can significantly boost excitation and/or radiation processes that amplify Raman, fluorescence, or nonlinear signals and improve spectroscopic sensitivity. Herein, recent developments in plasmon‐enhanced spectroscopies utilizing core–shell nanostructures are reviewed, including shell‐isolated nanoparticle‐enhanced Raman spectroscopy (SHINERS), plasmon‐enhanced fluorescence spectroscopy, and plasmon‐enhanced nonlinear spectroscopy.
The highly localized and strong electromagnetic fields generated by plasmonic nanomaterials, when excited by incident lasers with suitable wavelengths, can greatly boost the excitation and/or radiation processes of various spectroscopies, including Raman, fluorescence, or nonlinear spectroscopies, giving enhanced signals and improved spectral sensitivity.
Precise control and accurate understanding of the ordering degree of bimetallic nanocatalysts (BNs) are challenging yet crucial to acquire advanced materials for the oxygen reduction reaction (ORR). ...AuCu BNs with various ordering degrees were synthesized to evaluate the influence of ordering degree on the ORR at a molecular level using in situ Raman spectroscopy. The activity of AuCu BNs was improved by over 2 times after a disorder‐to‐order transition, making the performance of highly ordered AuCu BNs exceed that of benchmark Pt/C. Direct Raman spectroscopic evidence of key intermediate (*OH) demonstrates that the active site is the combination site of Au and Cu. Moreover, two distinct *OH species are observed on the ordered and disordered structure, and the ordered site is more beneficial for ORR due to its lower affinity to *OH. This work deepens the understanding on the important role of ordering degree on BNs and enables the design of improved catalysts.
The critical role of the ordering degree of AuCu bimetallic catalysts was studied in situ by a shell‐isolated nanoparticle‐enhanced Raman spectroscopy satellite strategy and the molecular reaction mechanism is revealed.
The increasing popularity of battery-limited electric vehicles puts forward an important issue of how to charge the vehicles effectively. This problem, commonly referred to as Electric Vehicle ...Charging Scheduling (EVCS), has been proven to be NP-hard. Most of the existing works formulate the EVCS problem simply as a constrained shortest path finding problem and treat it by discrete optimization. However, other variables such as the charging amount of energy and the charging option at a station need to be considered in practical use. This paper hence formulates the EVCS problem as a hierarchical mixed-variable optimization problem, considering the dependency among the station selection, the charging option at each station and the charging amount settings. To adapt to the new problem model, we specifically design a Mixed-Variable Differentiate Evolution (MVDE) as the scheduling algorithm for our proposed EVCS system. The MVDE contains several specific operators, including a charging station route construction, a hierarchical mixed-variable mutation operator and a constraint-aware evaluation operator. Experimental results validate the effectiveness of our proposed MVDE-based system on both synthetic and real-world transportation networks.
Zinc–air batteries offer a possible solution for large‐scale energy storage due to their superhigh theoretical energy density, reliable safety, low cost, and long durability. However, their ...widespread application is hindered by low power density. Herein, a multiscale structural engineering of Ni‐doped CoO nanosheets (NSs) for zinc–air batteries with superior high power density/energy density and durability is reported for the first time. In micro‐ and nanoscale, robust 2D architecture together with numerous nanopores inside the nanosheets provides an advantageous micro/nanostructured surface for O2 diffusion and a high electrocatalytic active surface area. In atomic scale, Ni doping significantly enhances the intrinsic oxygen reduction reaction activity per active site. As a result of controlled multiscale structure, the primary zinc–air battery with engineered Ni‐doped CoO NSs electrode shows excellent performance with a record‐high discharge peak power density of 377 mW cm−2, and works stable for >400 h at 5 mA cm−2. Rechargeable zinc–air battery based on Ni‐doped CoO NSs affords an unprecedented small charge–discharge voltage of 0.63 V, outperforming state‐of‐the‐art Pt/C catalyst‐based device. Moreover, it is shown that Ni‐doped CoO NSs assembled into all‐solid‐state coin cells can power 17 light‐emitting diodes and charge an iPhone 7 mobile phone.
A multiscale structure engineering of Ni‐doped CoO nanosheets from micro‐ through nano‐ to atomic scale for high‐power‐density zinc–air batteries is demonstrated. The engineered zinc–air battery based on Ni‐doped CoO nanosheets realizes sufficient mass transport, abundant catalysts active sites, and excellent intrinsic activity simultaneously, affording a record‐high discharge peak power density of 377 mW cm−2.
Elucidating hydrogen oxidation reaction (HOR) mechanisms in alkaline conditions is vital for understanding and improving the efficiency of anion‐exchange‐membrane fuel cells. However, uncertainty ...remains around the alkaline HOR mechanism owing to a lack of direct in situ evidence of intermediates. In this study, in situ electrochemical surface‐enhanced Raman spectroscopy (SERS) and DFT were used to study HOR processes on PtNi alloy and Pt surfaces, respectively. Spectroscopic evidence indicates that adsorbed hydroxy species (OHad) were directly involved in HOR processes in alkaline conditions on the PtNi alloy surface. However, OHad species were not observed on the Pt surface during the HOR. We show that Ni doping promoted hydroxy adsorption on the platinum‐alloy catalytic surface, improving the HOR activity. DFT calculations also suggest that the free energy was decreased by hydroxy adsorption. Consequently, tuning OH adsorption by designing bifunctional catalysts is an efficient method for promoting HOR activity.
HOR on Au@PtNi surfaces in alkaline media has been investigated by in situ surface‐enhanced Raman spectroscopy (see picture). Direct spectroscopic evidence for OHad species was observed and further confirmed by deuterium isotopic experiments and DFT.
Core–shell nanoparticles are at the leading edge of the hot research topics and offer a wide range of applications in optics, biomedicine, environmental science, materials, catalysis, energy, and so ...forth, due to their excellent properties such as versatility, tunability, and stability. They have attracted enormous interest attributed to their dramatically tunable physicochemical features. Plasmonic core–shell nanomaterials are extensively used in surface-enhanced vibrational spectroscopies, in particular, surface-enhanced Raman spectroscopy (SERS), due to the unique localized surface plasmon resonance (LSPR) property. This review provides a comprehensive overview of core–shell nanoparticles in the context of fundamental and application aspects of SERS and discusses numerous classes of core–shell nanoparticles with their unique strategies and functions. Further, herein we also introduce the concept of shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) in detail because it overcomes the long-standing limitations of material and morphology generality encountered in traditional SERS. We then explain the SERS-enhancement mechanism with core–shell nanoparticles, as well as three generations of SERS hotspots for surface analysis of materials. To provide a clear view for readers, we summarize various approaches for the synthesis of core–shell nanoparticles and their applications in SERS, such as electrochemistry, bioanalysis, food safety, environmental safety, cultural heritage, materials, catalysis, and energy storage and conversion. Finally, we exemplify about the future developments in new core–shell nanomaterials with different functionalities for SERS and other surface-enhanced spectroscopies.
The Co‐based electrocatalyst is among the most promising candidates for electrochemical oxidation of 5‐hydroxymethylfurfural (HMF). However, the intrinsic active sites and detailed mechanism of this ...catalyst remains unclear. We combine experimental evidence and a theoretical study to show that electrogenerated Co3+ and Co4+ species act as chemical oxidants but with distinct roles in selective HMF oxidation. It is found that Co3+ is only capable of oxidizing formyl group to produce carboxylate while Co4+ is required for the initial oxidation of hydroxyl group with significantly faster kinetics. As a result, the product distribution shows explicit dependence on the Co oxidation states and selective production of 5‐hydroxymethyl‐2‐furancarboxylic acid (HMFCA) and 2,5‐furandicarboxylic acid (FDCA) are achieved by tuning the applied potential. This work offers essential mechanistic insight on Co‐catalyzed organic oxidation reactions and might guide the design of more efficient electrocatalysts.
A detailed mechanism for cobalt‐catalyzed electrochemical 5‐hydroxymethylfurfural (HMF) oxidation is revealed. A combined experimental and theoretical study shows that a Co3+ species is capable of oxidizing the formyl group to produce carboxylate but remains inert towards oxidation of the hydroxyl group. In contrast, a Co4+ species is required for the initial oxidation of the hydroxyl group in HMF.
Conductive and self-healing hydrogels are among the emerging materials that mimic the human skin and are important due to their probable prospects in soft robots and wearable electronics. However, ...the mechanical properties of the hydrogel matrix limit their applications. In this study, we developed a physicochemically dual cross-linked chemically modified-cellulose nanofibers-carbon nanotubes/polyacrylic acid (TOCNF-CNTs/PAA) hydrogel. The TOCNFs acted both as a nanofiller and dispersant to increase the mechanical strength of the PAA matrix and break the agglomerates of the CNTs. The final self-healing and conductive TOCNF-CNTs/PAA-0.7 (mass ratio of CNTs to AA) hydrogel with a uniform texture exhibited highly intrinsic stretchability (breaking elongation to ca. 850%), enhanced tensile properties (ca. 59 kPa), ideal conductivity (ca. 2.88 S m
− 1
) and pressure sensitivity. Besides, the composite hydrogels achieved up to approximately 98.36% and 99.99% self-healing efficiency for mechanical and electrical properties, respectively, without any external stimuli. Therefore, the as-designed multi-functional self-healing hydrogels, combined with stretching, sensitivity, and repeatability, possess the ability to monitor human activity and develop multifunctional, advanced, and commercial products such as wearable strain sensors, health monitors, and smart robots.
Graphic abstract
Cyclization of propargylamines with CO2 to obtain 2‐oxazolidone heterocyclic compounds is an essential reaction in industry but it is usually catalyzed by noble‐metal catalysts with organic bases as ...co‐catalysts under harsh conditions. We have synthesized a unique CuI/CuII mixed valence copper‐based framework {(CuI6I5)Cu3IIL6(DMA)3(NO3)⋅9DMA}n (1) with good solvent and thermal stability, as well as a high density of uncoordinated amino groups evenly distributed in the large nanoscopic channels. Catalytic experiments show that 1 can effectively catalyze the reaction of propargylamines with CO2, and the yield can reach 99 %. The turnover frequency (TOF) reaches a record value of 230 h−1, which is much higher than that of reported noble‐metal catalysts. Importantly, this is the first report of heterogeneously catalyzed green conversion of propargylamines with CO2 without solvents and co‐catalysts under low temperature and atmospheric pressure. A mechanistic study reveals that a triply synergistic catalytic effect between CuI/CuII and uncoordinated amino groups promotes highly efficient and green conversion of CO2. Furthermore, 1 directly catalyzes this reaction with high efficiency when using simulated flue gas as a CO2 source.
A mixed valence copper‐based cationic framework {(CuI6I5)Cu3IIL6(DMA)3(NO3)⋅9DMA}n was synthesized. The material realized the efficient and green conversion of propargylamine with CO2 in flue gas under solvent‐free and co‐catalyst free conditions.
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